The effects of trees on soil properties and carbon storage in spatially distributed agroforestry systems in northwestern India

The effects of trees on soil properties and carbon storage in spatially distributed agroforestry systems in northwestern India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The effects of trees on soil properties and carbon storage in spatially distributed agroforestry systems in northwestern India Bilas Singh, Genda Singh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6841363/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The impact of trees on soils is diverse, varying based on tree species and environmental conditions. To better understand the functionality and services of agroforestry systems, we assessed the impact of trees on soil properties and carbon storage in 14 traditional agroforestry systems in Rajasthan, India. Trees were counted for species and density, and were measured for height, diameter at breast height (dbh), and canopy diameter in 0.5 ha plots on 84 farmlands. Soil pH, electrical conductivity (EC), organic carbon (SOC), total nitrogen (TN), available phosphorus, and exchangeable potassium were assessed for samples collected at 1 m from the tree, the canopy edge, and 5 m away from the canopy edge as a control. Soil variables differed significantly between systems and distances from the trees. SOC, TN, phosphorus, potassium, and C-stock showed + 2.3–25.0% increase, whereas pH/EC decreased beneath the tree canopy compared to the control. P. cineraria , P. juliflora , and A. indica exhibited high SOC, TN, phosphorus, and potassium, respectively. Soil pH and EC were low under A. excelsa . Most soil variables increased with an increase in tree size. Rainfall negatively impacted soil pH, EC, and potassium. Climate significantly influenced the distribution of agroforestry systems, and the growth and dynamics of the dominant trees within these systems were key drivers for improving soil nutrients, properties, and carbon storage. These findings suggest that integrating trees into farming systems through planting can improve soil fertility, enhance carbon storage, and help restore degraded farmlands, contributing to both sustainable agricultural production and climate change mitigation. Dry region trees on farmlands relative tree effects soil characteristics tree growth Figures Figure 1 Figure 2 Figure 3 Introduction The productivity of dryland agroecosystems is restrained by poor soil conditions, water scarcity, and high temperatures (Du et al., 2022 ). Land degradation accelerated by severe soil erosion and low soil fertility affects land productivity (Lalitha and Kumar, 2015 ). Soil organic carbon (SOC) and nutrients promote land productivity, impacting food security and environmental health (Das et al., 2022 ; Rathore et al., 2022 ). However, SOC and nutrients are considerably below their natural potential in dry areas, where they are mainly related to low vegetation cover (Jones et al., 2013 ) and poor management practices (Prasad et al., 2023 ). However, soil texture also plays a role in storing soil carbon (Singh et al., 2007 ; Blume et al., 2016 ). The intensification of conventional agriculture using high-yielding cultivars, chemical fertilizers, pesticides, and the expansion of irrigation also depletes soil organic carbon (Priya and Pani, 2017 ) and affects soil fertility and sustainable food production (Adekiya et al., 2023 ). Trees integrated into agricultural systems, known as agroforestry, offer significant benefits for soil health, food security, and ecosystem services (Baker et al., 2025 ; Smith et al., 2020 ; Zomer et al., 2016 ). They enhance SOC by depositing leaf litter and root exudates, influencing several bio-physical and bio-chemical processes and regulating the health of the soil substrate (Sharma et al., 2024 ). The organic C from leaf litter and fine roots of different tree species is chemically more diverse because different tree species exhibit different functional traits (Dori et al., 2022 ). The quality and location of litter in soil significantly impact its decomposition and the subsequent enrichment of litter-derived carbon in soil microbial biomass and soil carbon pools (Hu et al., 2016 ; Tripathi et al., 2013 ). This process ultimately enhances soil fertility and nutrient cycling. Roots of trees stabilise soil structure, prevent erosion, improve water infiltration (Dollinger and Jose, 2018 ), and reduce losses of organic materials and nutrients (Fahad et al., 2022 ). Thus, trees directly contribute to soil carbon, the first limiting factor in dry areas for crop growth and production (Mesfin and Haileselassie, 2022 ). Trees and shrubs on agricultural lands have an overall positive but variable effect on soil carbon (Felix et al., 2018 ; Singh et al., 2014 ). Increased tree density and biological diversity also result in higher soil carbon (Saha et al., 2009 ). Relatively high soil nitrogen, organic carbon, and potassium under a tree canopy than cropland is a result of high organic matter inputs from litter and fine roots (Schroth et al., 2003 ; Gindaba et al., 2005 ; Bayala et al., 2018 ; Prasad et al., 2019 ). Such changes are controlled by cropping systems, tree species, soil cultivation methods, soil properties, stand age, site management, topography, and climatic conditions (Deng et al., 2016 ; Negasha et al., 2022 ). Microbial activities, rainfall, temperature, soil pH, and soil types also influence soil fertility in an agroforestry system (Manjur et al., 2014 ; Cao et al., 2016 ). This shows tree inclusion improves soil fertility and may sustain food output by conserving biodiversity and enhancing organic matter, microbiological activity, and nutrient cycling (Pinho et al., 2012 ; Octavia et al., 2023 ). However, the effects of tree species on soil properties are species-specific and vary with climatic conditions (Gota et al., 2024 ; Ngaba et al., 2024 ). In dry areas, many tree species are maintained on farmlands for improved land productivity and to get various economic, social, and environmental benefits (Eddy and Yang, 2022 ; Ngaba et al., 2024 ; Singh et al., 2017 ). However, due to their availability in different climatic conditions, tree species differ in growth and characteristics in improving soil and sequestering carbon (Dori et al., 2022 ). The extent to which soil properties and SOC/carbon stock change across tree species and climatic conditions needs assessment and evaluation for the system suitability and climate mitigation (Rolo et al., 2023 ). Because of the above facts, the objectives of this study were (i) to explore distribution and growth characteristics of trees species in agroforestry systems of different climatic zone of Rajasthan; and (ii) to assess soil properties and identify potential tree species for the highest levels of soil improvement and carbon storage in the region. We hypothesised that (1) different species vary in altering soil properties and carbon storage, and (2) the extent of improvement increases with an increase in tree size (age). Materials and methods Study area and climate This study focuses on traditional agroforestry systems within ten agroclimatic zones (ACZs) in western arid and southeastern semi-arid regions of Rajasthan (Table S1 ). Rajasthan lies between 23° 30' and 30° 11' N latitudes and 69° 29' and 78° 17' E longitudes covering 3, 42,239 km 2 area, i.e. 10.4% of Indian territory (Fig. 1 ). Annual rainfall ranges between 150 mm in Jaisalmer to 1100 mm in Jhalawar district with > 60% coefficient of variation in arid and < 30% in the wetter parts of the state. The area receives about 86% of the annual rainfall during the monsoon months of June to September. The state experiences high daily temperature fluctuations. The average maximum temperature ranges from 33 to 3°C, and the minimum ranges from 18 to 20°C. The soils of Rajasthan have been classified into 15 great groups, nine suborders and five orders according to the international system of soil classification (Soil Survey Staff, 1998 ). Torripsamments of Entisols, and Haplocambids, Haplocalcids and Petrocalcids of Aridisols dominate in arid regions. Haplustepts of Inceptisols, Haplusterts of Vertisols and Haplustalfs of Alfisols dominate in the semi-arid region. Torripsamments, Haplocambids and Haplustepts together accounted for nearly 80% of the Rajasthan areas. However, most soils are low in nitrogen, phosphorus, and soil organic carbon (Joshi, 1984 ; Kumar et al., 2021 ). Study design and soil sampling Data were collected during 2016-17 and 2017-18, covering both ‘Kharif’ (June to October) and ‘Rabi’ (November to March) seasons. Fourteen tree species were recorded on the farmlands and were considered as the tree-based agroforestry systems (Supplementary Table A1). Twenty-one crops were growing in association with the above tree species during the ‘Kharif’ and ‘Rabi’ seasons. Prominent crop species were Pearlmillet ( Pennisetum typhoides ), Guar ( Cyamopsis tetragonoloba ), Moong bean ( Vigna radiata ) during ‘Kharif’ season, and Wheat ( Triticum aestivum ), Mustard ( Brassica nigra ), etc. in ‘Rabi’ seasons (Supplementary Table A1). Three replicate plots of 0.5 ha area were laid out in different tree-crop combinations on 84 farmlands in 15 districts covering 10 ACZs of the province. All tree species in the plots were enumerated for their population and measured for height, diameter at breast height (dbh), and canopy diameter (two sides perpendicular to each other). For soil characteristics, soil samples were collected in 0–30 cm soil layer. To monitor spatial variations, soil sampling was done at 1 m distance from the tree trunk, the canopy edge, and 5 m away from the canopy edge of the tree (ST) as a control from sampling sites (Fig. 1 ). The soil samples collected were brought to the laboratory, air-dried, sieved through a 2-mm mesh, and subjected to various physicochemical analyses. Soil physicochemical analysis Soil pH and electrical conductivity (EC) were determined in a 1:2 soil: water suspension ratio using pH/EC meters Model Elico LI-120 (Jackson, 1973 ). Soil organic carbon (SOC) was determined by the partial oxidation method of Walkley and Black ( 1934 ). Total nitrogen (N) was determined using a CNS Analyser, Elementar Model Vario EL Cube, Hanau, Germany, using Sulphanilamide as the standard. Available phosphorus (PO 4 -P) was determined by Olson’s extraction method (Jackson, 1973 ) using a UV-visible spectrophotometer, Model Shimadzu-1650 PC. Exchangeable Potassium (K) was extracted from air-dried soil samples by shaking with 0.5M Ammonium acetate/acetic acid buffer solution for 30 minutes, and the filtered extract was then determined using the Flame Photometer, Model 1385. Soil bulk density (BD) was estimated by collecting soil samples in 0–30 cm soil layer using an iron core cutter of fixed volume. Core samples were weighed and dried in an oven to constant weight at 110°C in a hot air oven for 72 hrs (McIntyre and Loveday, 1974 ). BD was calculated in g cm − ³ by dividing the volume of the core cutter by the dry weight of the soil. Carbon stock (Mg ha − 1 ) was calculated using SOC (g 100 g − 1 ), BD (g cm − 3 ) and soil depth (30 cm) data in the following equation: $$\:\text{S}\text{o}\text{i}\text{l}\:\text{C}\:\text{s}\text{t}\text{o}\text{c}\text{k}\:\left(\text{M}\text{g}\:{\text{h}\text{a}}^{-1}\right)=\text{D}\text{e}\text{p}\text{t}\text{h}\text{*}\text{B}\text{D}\text{*}\text{S}\text{O}\text{C}$$ 1 …………………. Data calculation and statistical analysis Relative Tree Effects (RTE) were calculated to observe the effects of dominant tree species on different soil parameters (Markham and Chanway, 1996 ). Negative values of RTE indicate beneficial (facilitation), and positive values show competition. $$\:\text{R}\text{T}\text{E}=\frac{(X\text{c}\:-X\text{c}\text{z})}{x\:}$$ 2 ………………………………………………….. where X was the performance variable of the target soil parameter in the control (c) and canopy zone (cz) of the tree, and x was the higher value of X c or X cz . All data collected were subjected to analysis of variance using the SPSS statistical package. Data on soil pH, EC, SOC, total N, PO 4 -P, and K were analysed using two-way ANOVA considering tree species and distance from the tree trunks as the main factors. Tree population density and growth parameters were tested using one-way ANOVA. Duncan Multiple Range Tests (DMRT) were applied to group tree systems and distance from the tree for homogeneous subsets at a p < 0.05 level. The Pearson’s correlation coefficient was also calculated. Regression analysis was also conducted to determine the relationships of rainfall and soil SOC with soil variables. Results Agroforestry systems Fourteen tree species-based systems were identified on the farmlands in different agroclimatic zones of Rajasthan (Table 1 ). The most frequently observed agroforestry system was Vachellia nilotica (L.) P.J.H. Hurter & Mabb. based. It was followed by Prosopis cineraria (L.) Druce. based. Both Ailanthus excelsa Roxb. and Azadirachta indica A. Juss. based systems showed a 9.1% frequency of occurrence. The number of tree species (richness) varied from 1.5 species in Salvadora oleoides -based system to 5.6 species in Vachellia leucophloea -based system. Table 1 Different agroforestry systems and their frequency of occurrence in Rajasthan SNo. Species botanical name Family Local name Frequency (%) Richness (nos)* Tree species 1 Ailanthus excelsa Roxb. Simaroubaceae Ardu 9.1 3.8 ± 0.5 2 Azadirachta indica A. Juss. Meliaceae Neem 9.1 1.9 ± 0.4 3 Dalbergia sissoo Roxb. Ex DC. Fabaceae Shisham 6.4 2.0 ± 0.6 4 Prosopis cineraria (L.) Druce. Fabaceae Khezri 10.9 2.8 ± 1.0 5 Prosopis juliflora (Sw.) DC. Fabaceae Vilayati Babool 1.8 3.4 ± 1.0 6 Salvadora oleoides Decne. Salvadoraceae Meetha Jaal 4.5 1.5 ± 0.6 7 Senegalia senegal (L.) Britton. Fabaceae Kumath 4.5 2.4 ± 1.1 8 Tecomella undulata (Sm.) Seem. Bignoniaceae Rohida 7.3 2.9 ± 1.6 9 Tectona grandis L f. Lamiaceae Teak/Sagaun 1.8 2.5 ± 0.6 10 Vachellia leucophloea (Roxb,) Willd. Fabaceae Raunj 5.5 5.6 ± 1.3 11 Vachellia nilotica (L.) P.J.H. Hurter & Mabb. Fabaceae Deshi Babool 23.6 4.3 ± 2.6 12 Vaqchellia tortilis (Forssk.) Galasso & Banfi. Fabaceae Israeli Babool 6.4 4.0 ± 0.5 13 V. nilotica var. cupressiformis (J.L. Stewart) Ali. Fabaceae Ramkanti 3.6 3.2 ± 1.8 14 Zizyphus mauritiana Lamk. Rhamnaceae Ber 5.5 4.4 ± 2.1 *Tree species richness values are mean ± standard deviation of multiple replications. Densities and growth of trees in agroforestry The average density of total trees was 12.8 trees ha − 1 across the agroforestry systems. It varied significantly from 3.7 tree ha − 1 in D. sissoo/V. tortilis to 30.0 tree ha − 1 in the T. grandis- based system (Table 2 ). The density of tree species in agroforestry systems varies, with T. grandis and S. senegal systems showing higher densities compared to others. Except for T. grandis , S. senegal , and V. nilotica , the density of other tree species was below the average (i.e., 7.0 tree ha − 1 ). The average contribution of the other tree species to the total population was 45.3%. The average height, dbh, and canopy diameter of selected trees varied significantly between agroforestry systems (Table 2 ). The mean tree height was 8.46 m across the species. D. sissoo, T. grandis , and A. indica trees exhibited greater height than other species. Heights of T. undulata, V. nilotica var. cupressiformis , S. oleoides , V. leucophloea , and Z. mauritiana trees were below average. S. oleoides exhibited the greatest dbh, whereas the dbh of Z. mauritiana was less than that of other species. Average dbh and canopy diameter across the species were 33.67 cm and 6.94 m, respectively. The canopy diameter was highest in V. tortilis and lowest in T. grandis . P. cineraria , T. undulata , P. juliflora , A. excelsa , and A. indica had medium canopy diameters. Table 2 Population density and growth parameters of tree species in different agroforestry systems in Rajasthan. Values are mean ± 1SD of multiple replications Tree-based system (selected tree system) Population density (nos. ha − 1 ) Growth variable of selected trees Selected species Others species Total Height (m) DBH (cm) Canopy dia. (m) Ailanthus excelsa 4.8 ± 2.65 a 7.4 ± 8.09 a 12.1 ± 10.33 ab 9.1 ± 2.76 c 36.85 ± 16.91 cd 7.7 ± 1.01 cde Azadirachta indica 2.5 ± 1.83 a 13.4 ± 9.18 a 15.8 ± 11.83 bc 9.5 ± 2.70 cd 36.54 ± 13.76 cd 7.5 ± 2.09 cde Dalbergia sissoo 2.9 ± 1.56 a 0.8 ± 0.07 a 3.7 ± 1.62 a 11.8 ± 4.22 e 35.91 ± 14.39 bcd 8.8 ± 2.40 e Prosopis cineraria 6.3 ± 3.24 b 6.9 ± 5.62 a 13.6 ± 7.64 ab 8.2 ± 2.02 bc 35.67 ± 10.95 bcd 7.0 ± 1.58 cde P. juliflora 0.8 ± 0.02 a 6.8 ± 1.00 a 7.6 ± 1.20 a 8.7 ± 1.61 bc 32.22 ± 7.46 bcd 7.5 ± 1.93 cde Salvadora oleoides 5.0 ± 4.31 a 4.3 ± 0.35 a 9.2 ± 3.96 a 7.5 ± 2.65 bc 89.81 ± 34.26 e 7.8 ± 2.69 cde Senegalia senegal 23.7 ± 7.10 d 3.9 ± 0.40 a 27.4 ± 7.20 bc 6.7 ± 2.26 ab 18.30 ± 8.99 a 5.8 ± 2.10 bc Tecomella undulata 4.5 ± 2.26 a 7.8 ± 3.72 a 12.3 ± 3.99 ab 8.2 ± 2.58 bc 34.19 ± 9.26 bcd 6.6 ± 1.84 bcd Tectona grandis 25.0 ± 0.0 d 5.0 ± 0.00 a 30.0 ± 0.00 c 11.3 ± 0.36 de 19.09 ± 4.29 a 3.2 ± 0.10 a Vachellia leucophloea 3.1 ± 1.49 a 7.4 ± 3.75 a 8.4 ± 0.57 a 6.8 ± 0.93 ab 26.14 ± 6.13 abc 6.6 ± 1.22 bcd Vachellia nilotica 3.4 ± 1.90 a 3.9 ± 4.04 a 7.3 ± 4.46 a 8.7 ± 2.11 bc 33.18 ± 9.99 cd 8.7 ± 3.06 de V. nilotica var. cupressiformis 11.6 ± 9.75 c 5.0 ± 7.07 a 16.6 ± 3.68 bc 7.6 ± 1.17 bc 24.23 ± 5.1 ab 3.9 ± 0.46 a V. tortilis 0.9 ± 0.57 a 4.9 ± 4.95 a 5.8 ± 5.52 a 9.3 ± 2.40 c 32.56 ± 11.24 bcd 11.1 ± 4.30 f Zizyphus mauritiana 3.4 ± 1.97 a 5.1 ± 2.87 a 8.5 ± 0.92 a 5.0 ± 0.88 a 16.73 ± 6.75 a 5.0 ± 1.90 ab Mean 7.0 5.8 12.8 8.46 33.67 6.94 One-way ANOVA F value 16.72** 1.51 2.2.78* 17.12** 49.93** 18.71** P value < 0.01 ns < 0.05 < 0.01 < 0.01 < 0.01 ns - not-significant at p < 0.05, *-significant at p < 0.05, ** - significant at p < 0.01. Values with different alphabets as superscripts in a column indicate significant (p < 0.05) differences. Changes in soil properties Soil pH, electrical conductivity (EC), soil organic carbon (SOC), total nitrogen (TN), available phosphorus (PO 4 -P), and exchangeable potassium (K) varied significantly between agroforestry systems. However, it was significant only for TN and K for distances from the tree (Supplementary Table A2). When the agroforestry system was considered, the soil pH and EC were significantly lower in the T. grandis- based system. Soil pH was highest in Z. mauritiana and S. senegal- based systems, whereas EC was the highest in D. sissoo- based systems (Table 3 ). Most systems did not differ in soil pH and EC (Duncan Multiple Range tests, DMRT), though variations between the highest and lowest values of these parameters were > 1.0 unit. The highest SOC and TN were in the soils of T. grandis , and the lowest were beneath P. juliflora- based systems, with 5.1-fold and 5.8-fold variation, respectively. However, SOC did not differ between the soils of S. oleoides , S. senegal , T. undulata , V. nilotica var. cupressiformis , and Z. mauritiana -based systems. Likewise, TN did not differ between the soils of A. excelsa , S. oleoides , S. senegal , V. tortilis , and Z. mauritiana -based systems. Soil available PO 4 -P was 2.98 mg kg − 1 in D. sissoo and increased to the highest (7.09 mg kg − 1 soil) in the T. grandis -based system. The availability of K was highest in P. juliflora and lowest in V. nilotica var. cupressiformis- based system, showing 3.0-fold variation. Table 3 Effects of tree species on soil physicochemical properties in different agroforestry systems in Rajasthan. Values are mean ± 1SD of multiple replications. Tree system Soil parameters pH EC (dS m − 1 ) SOC (%) Total N (%) PO 4 -P (mg kg − 1 ) K (mg kg − 1 ) A. excelsa 8.09 ± 0.38 cdef 1.13 ± 0.29 def 0.18 ± 0.04 b 0.07 ± 0.03 bcd 5.09 ± 3.37 d 96 ± 0.73 a A. indica 7.94 ± 0.53 cd 1.06 ± 0.57 de 0.20 ± 0.16 bc 0.10 ± 0.05 def 5.21 ± 2.84 d 126 ± 102 ab D. sissoo 8.15 ± 0.21 ef 1.79 ± 0.71 g 0.25 ± 0.09 de 0.10 ± 0.03 def 2.98 ± 1.04 a 190 ± 66 cd P. cineraria 8.11 ± 0.27 def 0.97 ± 0.67 cde 0.15 ± 0.05 abc 0.06 ± 0.03 abc 4.21 ± 1.74 bcd 146 ± 59 b P. juliflora 7.93 ± 0.06 cd 0.24 ± 0.02 a 0.10 ± 0.02 a 0.04 ± 0.02 a 3.23 ± 0.12 ab 209 ± 36 d S. oleoides 8.05 ± 0.46 cde 1.19 ± 0.77 def 0.14 ± 0.05 abc 0.07 ± 0.02 bcd 3.93 ± 0.51 abc 135 ± 41 ab S. senegal 8.44 ± 0.23 g 1.14 ± 0.40 def 0.14 ± 0.03 abc 0.07 ± 0.08 bcd 3.40 ± 1.27 ab 132 ± 73 ab T. grandis 7.19 ± 0.36 a 0.15 ± 0.04 a 0.51 ± 0.01 g 0.23 ± 0.04 g 7.09 ± 2.46 e 100 ± 14 a T. undulata 8.23 ± 0.40 f 0.86 ± 0.55 cd 0.13 ± 0.03 ab 0.05 ± 0.02 ab 3.91 ± 1.19 abc 134 ± 51 ab V. nilotica 7.96 ± 0.31 cd 1.08 ± 0.82 def 0.32 ± 0.21 f 0.12 ± 0.08 f 6.26 ± 2.99 e 154 ± 112 bc V. nilotica var. cupressiformis 8.04 ± 0.09 cde 1.04 ± 0.11 de 0.12 ± 0.01 ab 0.08 ± 0.01 cde 3.57 ± 0.25 ab 69 ± 3.00 a V. leucophloea 7.54 ± 0.3 b 0.70 ± 0.45 bc 0.30 ± 0.22 ef 0.10 ± 0.03 ef 5.00 ± 1.08 cd 108 ± 49 ab V. tortilis 7.92 ± 0.22 c 0.39 ± 0.36 ab 0.11 ± 0.03 a 0.07 ± 0.03 bcd 3.28 ± 0.60 ab 197 ± 61 d Z. mauritiana 8.41 ± 0.16 g 1.32 ± 0.86 ef 0.13 ± 0.04 ab 0.07 ± 0.02 bcd 3.81 ± 0.74 ab 129 ± 56 ab Mean 8.09 1.05 0.20 0.09 4.69 140 F value for two-way ANOVA System 51.31** 26.28** 46.96** 36.73** 30.66** 12.58** Values with different alphabets as superscripts in a column indicate significant differences at p < 0.05. The ns, * and ** are not-significant at p < 0.05, significant at p < 0.05, and significant at p < 0.01, respectively. Soil organic carbon, TN, PO 4 -P, and K were significantly higher in the canopy zone than outside the canopy zone soils (control). Soil pH was significantly lower near the tree trunk and increased to the highest in the control through the canopy edge soil (Table 4 ). In contrast, soil EC and K were highest near tree trunks and decreased to the lowest in the soils of the control plots. SOC, TN, and available PO 4 -P were greater at the canopy edge and lowest in the control plots. SOC was 15.8% and 10.5% higher near the tree and at the canopy edge than in the control plot, whereas TN was 12.5% higher near the tree and at the canopy edge, respectively. Availability of PO 4 -P was higher by 8.2% near the tree and by 8.4% at the canopy edge. The system × distance interaction was not significant for all soil parameters, indicating their independent behaviour for the soil variables. Table 4 Effects of distance from trees on soil properties in different agroforestry systems in Rajasthan. Values are mean ± 1SD of multiple replications. Canopy zone Soil parameters pH EC (dSm − 1 ) SOC (%) Total N (%) PO 4 -P (mg kg − 1 ) K (mg kg − 1 ) Near tree 8.04 ± 0.39 a 1.11 ± 0.80 b 0.21 ± 0.15 b 0.09 ± 0.06 b 4.65 ± 2.46 b 154 ± 88 b Canopy edge 8.10 ± 0.38 b 1.04 ± 0.66 ab 0.22 ± 0.16 c 0.09 ± 0.06 b 4.66 ± 2.28 b 140 ± 83 ab Control 8.10 ± 0.37 b 1.00 ± 0.59 a 0.19 ± 0.14 a 0.08 ± 0.05 a 4.30 ± 2.36 a 134 ± 75 a Mean 8.08 1.05 0.203 0.09 4.54 143 F-value of Two-way ANOVA Distance (D) 2.21ns 0.45ns 2.39ns 4.68** 2.01ns 3.09* System × D 0.81ns 0.66ns 0.14ns 0.32ns 0.10ns 0.81ns Values with different alphabets as superscripts in a column indicate significant differences at p < 0.05. The ns, * and ** are not-significant at p < 0.05, significant at p < 0.05, and significant at p < 0.01, respectively. Soil carbon storage The average soil C stock in the 0–30 cm soil layer of different agroforestry systems is shown in Fig. 2 . This varied ( p < 0.05) due to both agroforestry systems and distances from the trees. The soil C stock varied by 5-fold between the agroforestry systems across distances. It was highest beneath T. grandis (22.85 Mg ha − 1 ), followed by V. leucophloea and V. nilotica . Soil C stock did not differ between the soils of P. juliflora, T. undulata, V. nilotica var. cupressiformis , V. tortilis, Z. mauritiana, S. oleoides , S. senegal , and P. cineraria (Fig. 2 a). A. indica, D. sissoo , and V. nilotica- based systems showed higher than the average soil C stock. While considering distances from the tree trunk across systems, soil C stock was lowest in the control. The difference in C-stock between soils near the tree and the tree canopy edge was insignificant (Fig. 2 b). Average soil C stock was 10.11% higher near trees and 15.55% higher at the canopy edge compared with the control plots. The increase in C stock in the canopy zone soils of different trees compared to the control ranged from 4.0% in T. grandis to 28.3% in P. cineraria -based system (Fig. 2 c). System × distance interaction was not significant, showing independent behaviour of these factors. Relative tree effects (RTE) The relative tree effects (RTE) values of most soil variables (except EC and PO 4 -P) varied significantly between tree-based systems (Table 5 ). RTE for soil pH (RTE pH ) was lowest (-0.018) in A. excelsa and highest (+ 0.019) in the V. nilotica var. cupressiformis- based system. Other systems did not differ in RTE pH (DMRT). RTE EC was lowest (-0.179) in P. juliflora / P. cineraria and highest (-0.022) in the T. grandis- based system. RTE SOC, and RTE PO4−P values were negative and ranged from − 0.214 for D. sissoo to -0.047 for T. grandis , and from − 0.149 for A. indica to -0.018 for D. sissoo , respectively. Effects of most of the tree species (except A. excelsa ) on TN were positive, with RTE TN values of -0.279 for P. juliflora to + 0.015 for A. excelsa -based systems. For soil K, most tree-based systems showed positive effects (except A. excelsa and D. sissoo ) with RTE K values ranging from − 0.203 for V. tortilis to + 0.049 for A. excelsa . Table 5 The relative tree effect on changes in soil properties in different agroforestry systems in Rajasthan. Values are mean ± 1SD (in the second row) of multiple replications. Tree-based system Soil parameters pH EC SOC N PO 4 -P K Ailanthus excelsa -0.018 a -0.115 ab -0.123 bcde + 0.015 c -0.067 a + 0.045 c ± 0.040 ± 0.100 ± 0.086 ± 0.071 ± 0.327 ± 0.323 Azadirachta indica -0.002 ab -0.095 ab -0.104 bcde -0.168 abc -0.149 a -0.160 a ± 0.031 ± 0.056 ± 0.045 ± 0.150 ± 0.244 ± 0.329 Dalbergia sissoo -0.005 ab -0.130 ab -0.214 a -0.108 abc -0.018 a + 0.034 bc ± 0.019 ± 0.255 ± 0.140 ± 0.151 ± 0.189 ± 0.119 Prosopis cineraria + 0.004 bc -0.178 a -0.186 ab -0.063 abc -0.037 a -0.110 abc ± 0.016 ± 0.127 ± 0.115 ± 0.443 ± 0.310 ± 0.182 Prosopis juliflora + 0.001 abc -0.179 a -0.133 abcde -0.279 a -0.048 a -0.023 abc ± 0.009 ± 0.036 ± 0.074 ± 0.103 ± 0.019 ± 0.235 Salavadora oleoides + 0.005 bc -0.114 ab -0.121 bcde -0.186 abc -0.092 a -0.083 abc ± 0.036 ± 0.109 ± 0.097 ± 0.062 ± 0.106 ± 0.243 Senegalia senegal + 0.015 bc -0.110 ab -0.149 bcde -0.129 ab -0.082 a -0.030 abc ± 0.018 ± 0.083 ± 0.073 ± 0.349 ± 0.121 ± 0.161 Tecomella undulata + 0.007 bc -0.082 ab -0.147 abcd -0.124 abc -0.052 a -0.055 abc ± 0.025 ± 0.148 ± 0.100 ± 0.241 ± 0.142 ± 0.163 Tectona grandis -0.003 ab -0.022 b -0.047e -0.069 abc -0.077 a -0.020 abc ± 0.028 ± 0.021 ± 0.047 ± 0.171 ± 0.087 ± 0.187 Vachellia luecophloea + 0.007 bc -0.077 ab -0.077 de -0.038 bc -0.099 a -0.170 a ± 0.011 ± 0.034 ± 0.034 ± 0.164 ± 0.118 ± 0.113 V. nilotica var. cupressiformis -0.003 bc -0.092 ab -0.047 cde -0.069 abc -0.077 a -0.082 abc ± 0.028 ± 0.021 ± 0.047 ± 0.171 ± 0.087 ± 0.187 Vachellia nilotica + 0.010 bc -0.134 ab -0.170 abc -0.106 abc -0.078 a -0.149 ab ± 0.026 ± 0.185 ± 0.164 ± 0.276 ± 0.217 ± 0.204 Vachellia tortilis + 0.015 bc -0.133 ab -0.149 abcd -0.129 abc -0.082 a -0.203 a ± 0.018 ± 0.083 ± 0.073 ± 0.349 ± 0.121 ± 0.161 Zizyphus mauritiana -0.005 ab -0.125 ab -0.163 abcd -0.139 abc -0.109 a -0.087 abc ± 0.010 ± 0.141 ± 0.100 ± 0.087 ± 0.091 ± 0.172 Mean + 0.003 -0.122 -0.148 -0.120 -0.074 -0.090 One-way ANOVA F value 3.442** 1.526ns 3.534** 2.052* 0.711ns 3.432** Values with different alphabets as superscripts in a column indicate significant differences at p < 0.05. The ns, * and ** are not-significant at p < 0.05, significant at p < 0.05, and significant at p < 0.01, respectively. ‘-’ indicates a positive effect, whereas ‘+’ indicates competitive effects. Correlation and regression Annual rainfall exhibited positive correlations with tree density, SOC, TN, PO 4 -P, and SOC-stock, and negative correlations with soil K, pH, and EC (Table 6 ). Tree species richness was positively correlated to DBH, canopy diameter, and soil K, whereas it showed negative correlations with SOC and other soil variables. Per cent SOC was correlated positively to tree height and soil nutrients, and negatively to pH and EC. Tree canopy diameter was positively correlated with SOC and nutrients. Selected tree density (STD) was correlated positively to soil PO 4 -P and negatively to K, DBH, and canopy diameter. Soil C-stock was correlated positively to tree height, canopy diameter, SOC, and nutrients, and negatively to soil pH and EC. We observed a significant linear relationship between rainfall and SOC (Y = 0.128 + 0.0004X, R 2 = 0.038, F = 50.26, p < 0.01). Relationships of rainfall and SOC with other soil variables were similar, except for soil K, which increased with a decrease in rainfall and an increase in SOC. Soil TN and PO 4 -P increased, and K, pH, and EC decreased with increases in rainfall (Fig. 3 a-e). Likewise, soil pH and EC decreased, whereas TN, PO 4 -P, and K increased with an increase in SOC (Fig. 3 f-j). Table 6 Correlation matrix of different soil variables in agroforestry systems in Rajasthan, India Variable Variable Rainfall Height DBH CDia TD STD OTD pH EC SOC Total N PO 4 -P K C-stock Rainfall 1 -0.30** -0.13** -0.27** 0.53** 0.63** ns -0.24** -0.29** 0.20** 0.27** 0.29** -0.40** 0.24** Height -0.30** 1 0.51** 0.67** ns 0.03 ns -0.08* 0.13** 0.14** 0.06* 0.06* 0.15** 0.10** DBH -0.13** 0.51** 1 0.38** ns -0.45** 0.32** -0.11** 0.09** ns ns 0.06* 0.07* ns CDia 0-.27** 0.67** 0.38** 1 ns -0.47** 0.13** -0.06* 0.09** 0.15** ns 0.16** 0.16** 0.11** TD 0.53** ns ns -0.46** 1 0.74** 0.59** -0.06* -0.10* ns 0.13** 0.12** -0.30** ns STD 0.63** ns -0.45** -0.47** 0.74** 1 -0.11* -0.07* -0.15** 0.15** 0.18** 0.30** -0.38** 0.14** OTD ns ns 0.32 0.13 0.59** -0.11* 1 ns ns -0.17** ns -0.22** ns -0.17** Richness ns 0.06* 0.15** 0.16** -0.06* -0.30** - -0.06* -0.22** -0.27** -0.21** ns 0.06* -0.23** BD 0.11* -0.27** ns -0.31** 0.33** 0.23** - 0.16** -0.26** -0.33** -0.21** -0.43** ns -0.20** pH -0.24** -0.08* -0.11** -0.06* ns ns ns 1 0.31** -0.37** -0.31** -0.19** -0.10** -0.38** EC -0.29** 0.13** -0.09 0.09* ns -0.15** ns 0.31** 1 -0.18** -0.17** -0.10** ns -0.21** SOC 0.20** 0.14** ns 0.15** ns 0.15** ns -0.37** -0.18** 1 0.76** 0.26** 0.31**. 0.99** Total N 0.27** ns ns 0.11** 0.13** 0.18** ns -0.31** -0.17** 0.76** 1 0.17** 0.28** 0.75** PO 4 -P 0.29** ns ns 0.16** 0.12** 0.30** ns -0.19** -0.10** 0.26** 0.17** 1 -0.16** 0.20** K -0.40** 0.15** 0.07* 0.16** -0.30* -0.38** ns -0.10** ns 0.31** 0.28** -0.16** 1 0.29** C-stock 0.24** 0.10** 0.05 0.11** ns 0.14** ns -0.38** -0.21** 0.99** 0.75** 0.20** 0.29** 1 The ns, * and ** are not-significant at p < 0.05, significant at p < 0.05, and significant at p < 0.01, respectively (n = 1275). TD, tree density; STD, selected tree density; OTD, other tree density; Cdia, canopy diameter; BD, bulk density. Discussion Composition and growth of trees The diverse distribution of 14 different agroforestry systems, each with variations in tree density, growth patterns, and species richness, can be attributed to a combination of climatic conditions, edaphic conditions, and socioeconomic factors (Saxena, 1994 ; Singh et al., 2024 ). These factors influence where specific agroforestry systems thrive and the types of trees and crops that are most suitable. Tree density of 7.0-12.1 trees ha − 1 for A. excelsa , S. senegal , and V. leucophloea -based systems was very similar to the observation of Tewari et al. ( 2014 ) for P. cineraria (8.2–14.2 trees ha − 1 ). The higher frequency of Prosopis cineraria in arid western Rajasthan and Vachellia nilotica in areas with higher rainfall and deeper/medium soils indicates their respective adaptive strategies (Hussain, 2015 ). The social acceptance of trees resulted in increased species richness on the farmlands. However, reduced tree density (r = 0.63, p < 0.01) with a decrease in annual rainfall indicates a negative impact of poor soil status and low soil water on tree density. The use of tractors and intensive cultivation has also supported the uprooting and destruction of woody vegetation, affecting the density of S. oleoides and P. cineraria and the least preferred species like V. tortilis and P. juliflora (0.7–1.2 tree ha − 1 ) on farmlands (Bhati et al., 2017 ). Species characteristics and climate-influenced growth in tree species resulted in significant differences in height, dbh, and canopy diameter among agroforestry systems. Although temperature and annual rainfall are the dominant drivers favouring diameter growth (Żywiec et al., 2017 ; Gauli et al., 2022 ), the increased tree growth, particularly of D. sissoo in Sriganganagar and Hanumangarh with low precipitation, was due to canal water irrigation. The highest dbh for S. oleoides and the smaller size of Z. mauritiana and S. senegal trees were attributed to edaphic and climatic conditions and species-specific growth (Mensah et al., 2023 ). Negative correlations between tree growth and soil pH also supported this inference. Soil physicochemical changes in agroforestry systems Soil pH and EC impacted plant growth by influencing salt concentrations, nutrient release by weathering, the solubility of released materials, and the amount of nutrients stored in the soil (Neina, 2019 ). Soils were slightly alkaline in reaction and normal in salinity. However, a wide variation in soil pH and EC between different agroforestry systems was associated with climatic conditions, mineral weathering, and salt accumulation through surface runoff (Naorem et al., 2023 ). However, below-average soil pH in most agroforestry systems was due to high SOC and leaching of major base cations in low-texture soils (Meena and Mathur, 2017 ). High EC in the soils associated with D. sissoo grown in irrigated areas was due to overirrigation, a rise in groundwater table and increased level of salinisation (Kumar et al., 2017 ; Rani et al., 2023 ). Relatively greater EC under Z. mauritiana and S. oleoides trees were due to low rainfall (aridity index of 0.03–0.20) and adaptation in these species to occupy soils with high salt concentration (Verma et al., 2018 ; Dagar et al., 2023 ). Significantly lower RTE EC for P. juliflora and P. cineraria compared to T. grandis showed the tolerance of the former species to moderately saline soils. This inference was also supported by a negative correlation between rainfall and soil pH (r = -0.24, p < 0.01) and EC (r = -0.29, p < 0.001). However, variations in SOC (5.1-fold) and C-stock (5.0-fold) between P. juliflora and T. grandis were certainly due to variability in rainfall and soil conditions. Singh et al. ( 2007 ) also observed greater SOC in Alfisols, Vertisols and Inceptisols than Aridisols, and this was associated with higher rainfall, clay content and greater vegetative input. Positive correlations of rainfall with SOC (r = 0.194, p < 0.001), total N (r = 0.269, p < 0.001), and PO 4 -P (r = 0.291, p < 0.001) highlight the importance of rainfall and corresponding soil water availability on soil nutrient availability. The increase in tree size (height, dbh, and canopy diameter) improved soil properties by influencing litter input and nutrient cycling (Murovhi et al., 2012 ; Gupta et al., 2017 ). Significantly high SOC in T. grandis, V. nilotica , and V. luecophloea systems was due to their availability in relatively high rainfall zones with sandy loam to black soil. Likewise, low SOC in P. cineraria, S. senegal , S. oleoides, T. undulata, Z. mauritiana , V. tortilis, P. juliflora -based systems was associated with the sandy soils. This showed the importance of tree species and soil texture influencing the spatial pattern of SOC (Pinho et al., 2012 ; Shi et al., 2012 ). The importance of soil texture on SOC retention was also shown by 25.0% and 2.4% increases in SOC beneath P. cineraria (growing in sandy soil area) and T. grandis (clay soil area), respectively, compared to the control. RTE SOC value of -0.047 for T. grandis and − 0.186 for P. cineraria also supports the inference (Table 4 ). Earlier studies also suggest negative correlations of SOC with sand, mean high temperature and pH of the soil, and positive correlations with mean annual rainfall, silt, and clay content of different tree stands (Burke et al., 1989 ; Devi, 2021 ). A wide variation in total N (0.04% in P. juliflora to 0.23% in T. grandis ), available PO 4 -P (2.98 mg kg − 1 in D. sissoo to 7.09 mg kg − 1 in T. grandis ), and K (69 mg kg − 1 in V. nilotica var. cupressiformis to 209 mg kg − 1 in P. juliflora based system) indicate the impact of soil water through rainfall and tree attributes contributing to litter addition and fine roots turnover (Patel et al., 2018 ; Sayno et al., 2023). This inference was also supported by relationships of rainfall and SOC with other soil variables, i.e. enhanced total N and PO 4 -P (Fig. 3 ). However, the nutrient cycle process is also controlled by several factors like tree species, soil properties (clay content, pH), stand age, management practices, topography, and climatic conditions (Jandal et al., 2007 ; Negasha et al., 2022 ). Magersa and Worku ( 2018 ) also recorded higher SOM and total N in the soils associated with Acacia species than P. juliflora . Thus, tree-specific variations in soil characteristics highlight the potential of different tree species in building SOC and available N, P, and K, depending on their use in phytobiomass production and subsequent returns in the form of litter (Aggarwal et al., 1993 ; Yadav et al., 2011 ). Greater availability of PO 4 -P under T. grandis and V. nilotica was related to loam to clay loam soils (Takner et al., 2009 ). In contrast, low (p > 0.05, DMRT) availability of PO 4 -P in A. indica , V. luecophloea , A. excelsa , P. cineraria , and S. oleoides- based systems was due to sandy loam soil and their use in the growth of trees and the companion crops. Binkley et al. ( 1992 ) observed that N-fixing tree species increase N and P cycling by producing more litter and favouring greater release of soil nutrients than non-N-fixing tree species. However, the non-significant difference in soil PO 4 -P between N 2 -fixing and non-N 2 -fixing species in the study was due to a wide range of climatic and edaphic conditions. The low PO 4 -P availability in the soils of D. sissoo and P. juliflora- based systems was because of the fast growth rate and greater use of soil nutrients compared to other species (Deng et al., 2016 ). The findings of Agarwal et al. (1976) also suggested an increase in soil fertility status in P. cineraria and T. undulata particularly SOC, total N, and available PO 4 -P compared to the soils under P. juliflora- based system Another possibility of increased soil nutrients under tree canopy was the dropping and excreta of birds and cattle taking shelter to these tree species, particularly in dry areas, contributing enormously towards making the agroforestry system more fertile (Bhati et al., 2017 ; Bremer et al., 2022 ). Spatial variations in soil properties Significantly higher values of soil EC, SOC, TN, PO 4 -P, and K under the canopy zone soil than in the control were due to added litter and its decomposition (Tadesse et al., 2016 ; Mesfin and Haileselassie, 2022 ; Syano et al., 2023 ). This was also supported by negative values of RTE of these soil variables in most agroforestry systems. Greater soil pH near the tree trunk under V. leucophloea , and at the canopy edge under A. excelsa , S. oleoides , P. juliflora , V. leucophloea , Z. mauritiana , D. sissoo and S. senegal might be due to cations (i.e., Ca, Mg, K, and Na) rich litter production. Other studies have also reported an increase in soil pH, K, and PO 4 -P under tree canopy than in the open field (Gindaba et al., 2005 ; Diallo et al., 2019 ). A general order of different sites like control < near tree < canopy edge for SOC, total N and PO 4 -P, and control < canopy edge < near tree for EC and K was attributed to the effect of a balance between uptake by trees/ crops and their release through added litter, fine root turn over and tree characteristics (Isaac and Borden, 2019 ; Steinfeld et al., 2023 ). However, the lowest EC near the tree of T. grandis, S. oleoides , A. excelsa , P. juliflora , and V. tortilis was due to increased uptake of salts by these species as observed in another study (Singh et al., 2022 ), where indigenous S. oleoides, T. undulata , P. cineraria , and S. persica showed a greater potential for salts and nutrients absorption from the wastewater contaminated soils. Soil available PO 4 -P was also affected by different tree species (Batterman et al., 2018 ), as it was greater near trees in V. luecophloea, Z. mauritiana , V. tortilis , and A. indica and at the canopy edge in A. indica, S. oleoides , D. sissoo , and Z. mauritiana based systems than the other sites. This indicates that phosphorus availability also depends on soil organic matter and soil texture (Louche et al., 2010 ). A significantly high concentration of exchangeable K near trees (12.82%) was due to its addition by tree litter, particularly P. juliflora , D. sissoo, V. tortilis, V. nilotica , and P. cineraria (Kumar et al., 2017 ). Potential trees in improving soil properties and C-sequestration Significant increase in SOC under the canopies of P. cineraria, P. juliflora , D. sissoo , and V. tortilis than beneath T. grandis, A. indica , and V. leucophloea trees highlights the importance of legume trees in soil amelioration (Gei and Powers, 2013 ). Patel et al. ( 2018 ) found an increase in SOC under canopy trees in the order: A. indica < P. juliflora < P. cineraria < V. tortilis . Increases in SOC and C-stock were associated with a decrease in soil pH and EC, and an increase in soil nutrients (Fig. 3 f-j), highlighting the positive role of SOC on soil nutrients (Dori et al., 2022 ; Prasad et al., 2023 ). However, the highest concentration of soil N beneath P. juliflora and V. tortilis than under P. cineraria and A. indica was attributed to lopping of the latter two species for fodder, which affected the amount of litter added to the soil (Patel et al., 2018 ). The relatively high RTE TN in P. cineraria (-0.063) than P. juliflora (-0.279) also shows the impact of species on soil nutrient variations (Bhati et al., 2017 ; Jouybari et al., 2022 ). Observed greater soil K under A. indica, V. tortilis, V. leucophloea, V. nilotica , and P. cineraria than beneath A. excelsa, D. sissoo , S. senegal , and P. juliflora was because of litter quality and K concentration in the litter. Tanga et al. ( 2014 ) recorded soil K levels greater in V. tortilis than in Balanites aegyptiaca and V. seyal -based systems. The magnitude of reduction in soil pH, EC and an increase in SOC, total N, PO 4 -P, and K beneath the tree canopy compared with those outside the canopy zone highlights the impact of tree species on improvement in soil fertility and carbon sequestration in agroforestry systems (Singh, 2009 ; Ashaye, 2017). However, positive correlations of soil C-stock with tree height and canopy diameter highlight the impact of tree size in enhancing soil carbon sequestration. Conclusion and recommendations Climatic factors, particularly rainfall, are the most influential drivers governing the distribution of agroforestry systems and the population and growth of trees within the systems. However, the increase in SOC, total N, available PO 4 -P, K, and C stock, and decrease in soil pH and EC showed a positive impact of trees on soil properties. The dominance of the tree species of the tree-based system appeared to be more influential in improving soil characteristics. The positive influence of trees increased with an increase in growth size (height, DBH, and canopy diameter). The effects were significantly high for P. cineraria and V. tortilis in arid regions, and V. nilotica , A. indica , and V. leucophloea -based systems in the semiarid areas. Significant decrease in soil pH and EC beneath A. excelsa and V. tortilis , increase in SOC under P. cineraria , total N under P. juliflora , and available PO 4 -P and exchangeable K beneath A. indica are the effects of tree species. Although exotics like P. juliflora and V. tortilis also exhibited wide adaptability and soil improvement characteristics, indigenous tree species appeared better than exotics and can be given preference. This study highlights species-specific services of the agroforestry systems in terms of improved soil properties and enhanced soil carbon storage. These findings emphasise the potential of tree-based systems in agriculture to boost land productivity and create new income streams through carbon sequestration. Farmers can use this information to select suitable tree-based systems, enhancing both their livelihoods and environmental sustainability. Declarations Data Availability All data generated or analysed during this study are included in this article. Acknowledgments The authors are grateful to the Director, ICFRE-AFRI, Jodhpur, for providing the required amenities and inspiration to complete this research work. Thanks are also due to the farmers for their consent and help during field data recording on their farmlands. We also acknowledge the financial assistance from the Forest Department, the Government of Rajasthan, and the help of forest staff of different divisions during the study period. Funding This work was supported by the State Forest Department, Government of Rajasthan, India. Author and information Bilas Singh: Extension Division, Arid Forest Research Institute, Jodhpur, India G. Singh: Forest Ecology and Climate Change Division, Arid Forest Research Institute, Jodhpur, India. Present address: 1/279, Viraj Khand, Gomti Nagar, Lucknow-226010 (UP), India Contributions B. Singh & G. Singh. Both authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by BS. The first draft of the manuscript was prepared by BS, and edited and revised by GS. Both authors read and approved the final manuscript. Corresponding author Correspondence to [email protected] Ethics declarations Competing interests The authors declare no competing interests. Supplementary information Supplementary data References Adekiya, A. O., Alori, E. T., Ogunbode, T. O., Sangoyomi, T., & Oriade, O. A. (2023). Enhancing organic carbon content in tropical soils: strategies for sustainable agriculture and climate change mitigation. 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(2014). Livelihood improvements and climate change adaptations through agroforestry in hot arid environments. In J.C. Dagar et al. (Eds.), Agroforestry systems in India: Livelihood Security and Ecosystem Services. Advances in Agroforestry , 10. https://doi: 10.1007/978-81-322-1662-9_6 Tripathi, G., Deora, R., & Singh, G. (2013). The influence of litter quality and micro-habitat on litter decomposition and soil properties in a silvopasture system. Acta Oecologica , 50 , 40-50. Verma, S. S., Verma, R. P., Verma, S. K., Yadav, A. L., & Verma, A. K. (2018). Responses of Ber ( Ziziphus mauritiana Lamk.) varieties to different level of salinity. Int. J. Current Microbiol. App. Sci. , 7 , 580–591. Walkley, A., & Black, I. A. (1934). An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Science, 37 , 29-38. Yadav, R. S., Yadav, B. L., Chhipa, B. R., Dhayani, S. K., & Ram, M. (2011). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6841363","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":474316409,"identity":"87136ad8-b173-4ffb-b8a4-2c7b11b1cb69","order_by":0,"name":"Bilas Singh","email":"","orcid":"","institution":"Arid Forest Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Bilas","middleName":"","lastName":"Singh","suffix":""},{"id":474316411,"identity":"03755a2c-89c3-439c-ab0a-fcd72350c11a","order_by":1,"name":"Genda Singh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYJACCQhibHzwocIGyGdsPECkFuZmwxln0kBaGojRAiLZ26R52w6D2Xi1yLv3Hrzx449Fnnx0I0jLebu17YeBttTYROPSYnjmXLJlb5tEseGdg82Wc87dTt52JhGo5VhabgMuLTNyzCR4GyQSN85IbLzxpux2stkBoBbGhsO4tcx/Yyb55w9YS4MED9u5ZLPzD/FrkZfgMZPmYZNInC+R2CTJ03bAzuwGAVsMeHKMrWXbJBI3SCSCAjk5wewG0JYEPH6Rbz9jePPNn7rE+TPSHwKj0s7e7DyIUWOD25YDaIxEsMoEHMrBtjSgMezxKB4Fo2AUjIIRCgCGQWr7axZUWwAAAABJRU5ErkJggg==","orcid":"","institution":"Arid Forest Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Genda","middleName":"","lastName":"Singh","suffix":""}],"badges":[],"createdAt":"2025-06-07 07:53:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6841363/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6841363/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86026710,"identity":"707f3b00-7a3e-4592-9c99-0404fbf2362e","added_by":"auto","created_at":"2025-07-04 13:20:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":484634,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical distribution of soil sampling points in traditional agroforestry systems in Rajasthan.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6841363/v1/300f54a82556ea6214f61f13.png"},{"id":86027374,"identity":"39beb2b5-f572-4f97-80d1-fc724c758d05","added_by":"auto","created_at":"2025-07-04 13:28:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60345,"visible":true,"origin":"","legend":"\u003cp\u003eAverage soil C stock (0-30 cm) across agroforestry systems (a) and distance from tree trunk (b) in Rajasthan. Per cent increase in C stock under the canopy zone over control (c)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6841363/v1/47a4455ab9230d0fdd6dbd32.png"},{"id":86026711,"identity":"86ebebae-6035-4bb4-a6d9-7b00b45f9110","added_by":"auto","created_at":"2025-07-04 13:20:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":147620,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships annual rainfall (a-e) and SOC (f-j) with other soil variables in agroforestry systems in Rajasthan. Variables on the X-axis of the left and right panels are the same as in the bottom panels.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6841363/v1/8ec14ecfb0f83cc15717ed36.png"},{"id":91102135,"identity":"e2fb6236-406d-471e-94cd-bb51b8ec258f","added_by":"auto","created_at":"2025-09-11 14:54:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2177145,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6841363/v1/c771c7c8-9ecf-4c0b-b897-68068509a02c.pdf"},{"id":86026708,"identity":"1b16a111-b71b-4244-80c0-c9bb3c4f8dff","added_by":"auto","created_at":"2025-07-04 13:20:20","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":32034,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-6841363/v1/4b510ac3ca2e7e053155b8bc.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The effects of trees on soil properties and carbon storage in spatially distributed agroforestry systems in northwestern India","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe productivity of dryland agroecosystems is restrained by poor soil conditions, water scarcity, and high temperatures (Du et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Land degradation accelerated by severe soil erosion and low soil fertility affects land productivity (Lalitha and Kumar, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Soil organic carbon (SOC) and nutrients promote land productivity, impacting food security and environmental health (Das et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rathore et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, SOC and nutrients are considerably below their natural potential in dry areas, where they are mainly related to low vegetation cover (Jones et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and poor management practices (Prasad et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, soil texture also plays a role in storing soil carbon (Singh et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Blume et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The intensification of conventional agriculture using high-yielding cultivars, chemical fertilizers, pesticides, and the expansion of irrigation also depletes soil organic carbon (Priya and Pani, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and affects soil fertility and sustainable food production (Adekiya et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTrees integrated into agricultural systems, known as agroforestry, offer significant benefits for soil health, food security, and ecosystem services (Baker et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Smith et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zomer et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). They enhance SOC by depositing leaf litter and root exudates, influencing several bio-physical and bio-chemical processes and regulating the health of the soil substrate (Sharma et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The organic C from leaf litter and fine roots of different tree species is chemically more diverse because different tree species exhibit different functional traits (Dori et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The quality and location of litter in soil significantly impact its decomposition and the subsequent enrichment of litter-derived carbon in soil microbial biomass and soil carbon pools (Hu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Tripathi et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This process ultimately enhances soil fertility and nutrient cycling. Roots of trees stabilise soil structure, prevent erosion, improve water infiltration (Dollinger and Jose, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and reduce losses of organic materials and nutrients (Fahad et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, trees directly contribute to soil carbon, the first limiting factor in dry areas for crop growth and production (Mesfin and Haileselassie, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTrees and shrubs on agricultural lands have an overall positive but variable effect on soil carbon (Felix et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Singh et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Increased tree density and biological diversity also result in higher soil carbon (Saha et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Relatively high soil nitrogen, organic carbon, and potassium under a tree canopy than cropland is a result of high organic matter inputs from litter and fine roots (Schroth et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Gindaba et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Bayala et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Prasad et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Such changes are controlled by cropping systems, tree species, soil cultivation methods, soil properties, stand age, site management, topography, and climatic conditions (Deng et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Negasha et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Microbial activities, rainfall, temperature, soil pH, and soil types also influence soil fertility in an agroforestry system (Manjur et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Cao et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This shows tree inclusion improves soil fertility and may sustain food output by conserving biodiversity and enhancing organic matter, microbiological activity, and nutrient cycling (Pinho et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Octavia et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the effects of tree species on soil properties are species-specific and vary with climatic conditions (Gota et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ngaba et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In dry areas, many tree species are maintained on farmlands for improved land productivity and to get various economic, social, and environmental benefits (Eddy and Yang, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ngaba et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Singh et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, due to their availability in different climatic conditions, tree species differ in growth and characteristics in improving soil and sequestering carbon (Dori et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The extent to which soil properties and SOC/carbon stock change across tree species and climatic conditions needs assessment and evaluation for the system suitability and climate mitigation (Rolo et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBecause of the above facts, the objectives of this study were (i) to explore distribution and growth characteristics of trees species in agroforestry systems of different climatic zone of Rajasthan; and (ii) to assess soil properties and identify potential tree species for the highest levels of soil improvement and carbon storage in the region. We hypothesised that (1) different species vary in altering soil properties and carbon storage, and (2) the extent of improvement increases with an increase in tree size (age).\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eStudy area and climate\u003c/p\u003e \u003cp\u003eThis study focuses on traditional agroforestry systems within ten agroclimatic zones (ACZs) in western arid and southeastern semi-arid regions of Rajasthan (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Rajasthan lies between 23\u0026deg; 30' and 30\u0026deg; 11' N latitudes and 69\u0026deg; 29' and 78\u0026deg; 17' E longitudes covering 3, 42,239 km\u003csup\u003e2\u003c/sup\u003e area, i.e. 10.4% of Indian territory (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Annual rainfall ranges between 150 mm in Jaisalmer to 1100 mm in Jhalawar district with \u0026gt;\u0026thinsp;60% coefficient of variation in arid and \u0026lt;\u0026thinsp;30% in the wetter parts of the state. The area receives about 86% of the annual rainfall during the monsoon months of June to September. The state experiences high daily temperature fluctuations. The average maximum temperature ranges from 33 to 3\u0026deg;C, and the minimum ranges from 18 to 20\u0026deg;C. The soils of Rajasthan have been classified into 15 great groups, nine suborders and five orders according to the international system of soil classification (Soil Survey Staff, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Torripsamments of Entisols, and Haplocambids, Haplocalcids and Petrocalcids of Aridisols dominate in arid regions. Haplustepts of Inceptisols, Haplusterts of Vertisols and Haplustalfs of Alfisols dominate in the semi-arid region. Torripsamments, Haplocambids and Haplustepts together accounted for nearly 80% of the Rajasthan areas. However, most soils are low in nitrogen, phosphorus, and soil organic carbon (Joshi, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Kumar et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStudy design and soil sampling\u003c/p\u003e \u003cp\u003eData were collected during 2016-17 and 2017-18, covering both \u0026lsquo;Kharif\u0026rsquo; (June to October) and \u0026lsquo;Rabi\u0026rsquo; (November to March) seasons. Fourteen tree species were recorded on the farmlands and were considered as the tree-based agroforestry systems (Supplementary Table A1). Twenty-one crops were growing in association with the above tree species during the \u0026lsquo;Kharif\u0026rsquo; and \u0026lsquo;Rabi\u0026rsquo; seasons. Prominent crop species were Pearlmillet (\u003cem\u003ePennisetum typhoides\u003c/em\u003e), Guar (\u003cem\u003eCyamopsis tetragonoloba\u003c/em\u003e), Moong bean (\u003cem\u003eVigna radiata\u003c/em\u003e) during \u0026lsquo;Kharif\u0026rsquo; season, and Wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e), Mustard (\u003cem\u003eBrassica nigra\u003c/em\u003e), etc. in \u0026lsquo;Rabi\u0026rsquo; seasons (Supplementary Table A1). Three replicate plots of 0.5 ha area were laid out in different tree-crop combinations on 84 farmlands in 15 districts covering 10 ACZs of the province. All tree species in the plots were enumerated for their population and measured for height, diameter at breast height (dbh), and canopy diameter (two sides perpendicular to each other). For soil characteristics, soil samples were collected in 0\u0026ndash;30 cm soil layer. To monitor spatial variations, soil sampling was done at 1 m distance from the tree trunk, the canopy edge, and 5 m away from the canopy edge of the tree (ST) as a control from sampling sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The soil samples collected were brought to the laboratory, air-dried, sieved through a 2-mm mesh, and subjected to various physicochemical analyses.\u003c/p\u003e \u003cp\u003eSoil physicochemical analysis\u003c/p\u003e \u003cp\u003eSoil pH and electrical conductivity (EC) were determined in a 1:2 soil: water suspension ratio using pH/EC meters Model Elico LI-120 (Jackson, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1973\u003c/span\u003e). Soil organic carbon (SOC) was determined by the partial oxidation method of Walkley and Black (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1934\u003c/span\u003e). Total nitrogen (N) was determined using a CNS Analyser, Elementar Model Vario EL Cube, Hanau, Germany, using Sulphanilamide as the standard. Available phosphorus (PO\u003csub\u003e4\u003c/sub\u003e-P) was determined by Olson\u0026rsquo;s extraction method (Jackson, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1973\u003c/span\u003e) using a UV-visible spectrophotometer, Model Shimadzu-1650 PC. Exchangeable Potassium (K) was extracted from air-dried soil samples by shaking with 0.5M Ammonium acetate/acetic acid buffer solution for 30 minutes, and the filtered extract was then determined using the Flame Photometer, Model 1385. Soil bulk density (BD) was estimated by collecting soil samples in 0\u0026ndash;30 cm soil layer using an iron core cutter of fixed volume. Core samples were weighed and dried in an oven to constant weight at 110\u0026deg;C in a hot air oven for 72 hrs (McIntyre and Loveday, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). BD was calculated in g cm\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup3; by dividing the volume of the core cutter by the dry weight of the soil. Carbon stock (Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was calculated using SOC (g 100 g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), BD (g cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e) and soil depth (30 cm) data in the following equation:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\text{S}\\text{o}\\text{i}\\text{l}\\:\\text{C}\\:\\text{s}\\text{t}\\text{o}\\text{c}\\text{k}\\:\\left(\\text{M}\\text{g}\\:{\\text{h}\\text{a}}^{-1}\\right)=\\text{D}\\text{e}\\text{p}\\text{t}\\text{h}\\text{*}\\text{B}\\text{D}\\text{*}\\text{S}\\text{O}\\text{C}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u003c/p\u003e \u003cp\u003eData calculation and statistical analysis\u003c/p\u003e \u003cp\u003eRelative Tree Effects (RTE) were calculated to observe the effects of dominant tree species on different soil parameters (Markham and Chanway, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Negative values of RTE indicate beneficial (facilitation), and positive values show competition.\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\text{R}\\text{T}\\text{E}=\\frac{(X\\text{c}\\:-X\\text{c}\\text{z})}{x\\:}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eX\u003c/em\u003e was the performance variable of the target soil parameter in the control (c) and canopy zone (cz) of the tree, and x was the higher value of \u003cem\u003eX\u003c/em\u003e\u003csub\u003ec\u003c/sub\u003e or \u003cem\u003eX\u003c/em\u003e\u003csub\u003ecz\u003c/sub\u003e. All data collected were subjected to analysis of variance using the SPSS statistical package. Data on soil pH, EC, SOC, total N, PO\u003csub\u003e4\u003c/sub\u003e-P, and K were analysed using two-way ANOVA considering tree species and distance from the tree trunks as the main factors. Tree population density and growth parameters were tested using one-way ANOVA. Duncan Multiple Range Tests (DMRT) were applied to group tree systems and distance from the tree for homogeneous subsets at a \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level. The Pearson\u0026rsquo;s correlation coefficient was also calculated. Regression analysis was also conducted to determine the relationships of rainfall and soil SOC with soil variables.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAgroforestry systems\u003c/p\u003e \u003cp\u003eFourteen tree species-based systems were identified on the farmlands in different agroclimatic zones of Rajasthan (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The most frequently observed agroforestry system was \u003cem\u003eVachellia nilotica\u003c/em\u003e (L.) P.J.H. Hurter \u0026amp; Mabb. based. It was followed by \u003cem\u003eProsopis cineraria\u003c/em\u003e (L.) Druce. based. Both \u003cem\u003eAilanthus excelsa\u003c/em\u003e Roxb. and \u003cem\u003eAzadirachta indica\u003c/em\u003e A. Juss. based systems showed a 9.1% frequency of occurrence. The number of tree species (richness) varied from 1.5 species in \u003cem\u003eSalvadora oleoides\u003c/em\u003e-based system to 5.6 species in \u003cem\u003eVachellia leucophloea\u003c/em\u003e-based system.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferent agroforestry systems and their frequency of occurrence in Rajasthan\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecies botanical name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFamily\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLocal name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRichness (nos)*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTree species\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAilanthus excelsa\u003c/em\u003e Roxb.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimaroubaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArdu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAzadirachta indica\u003c/em\u003e A. Juss.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeliaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNeem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eDalbergia sissoo\u003c/em\u003e Roxb. Ex DC.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFabaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShisham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eProsopis cineraria\u003c/em\u003e (L.) Druce.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFabaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKhezri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eProsopis juliflora\u003c/em\u003e (Sw.) DC.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFabaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVilayati Babool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSalvadora oleoides\u003c/em\u003e Decne.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSalvadoraceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeetha Jaal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSenegalia senegal\u003c/em\u003e (L.) Britton.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFabaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKumath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTecomella undulata\u003c/em\u003e (Sm.) Seem.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBignoniaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRohida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTectona grandis\u003c/em\u003e L f.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLamiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTeak/Sagaun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eVachellia leucophloea\u003c/em\u003e (Roxb,) Willd.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFabaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaunj\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eVachellia nilotica\u003c/em\u003e (L.) P.J.H. Hurter \u0026amp; Mabb.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFabaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDeshi Babool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eVaqchellia tortilis\u003c/em\u003e (Forssk.) Galasso \u0026amp; Banfi.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFabaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIsraeli Babool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eV. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis\u003c/em\u003e (J.L. Stewart) Ali.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFabaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRamkanti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eZizyphus mauritiana\u003c/em\u003e Lamk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRhamnaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Tree species richness values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation of multiple replications.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDensities and growth of trees in agroforestry\u003c/p\u003e \u003cp\u003eThe average density of total trees was 12.8 trees ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e across the agroforestry systems. It varied significantly from 3.7 tree ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eD. sissoo/V. tortilis\u003c/em\u003e to 30.0 tree ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in the \u003cem\u003eT. grandis-\u003c/em\u003ebased system (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The density of tree species in agroforestry systems varies, with \u003cem\u003eT. grandis\u003c/em\u003e and \u003cem\u003eS. senegal\u003c/em\u003e systems showing higher densities compared to others. Except for \u003cem\u003eT. grandis\u003c/em\u003e, \u003cem\u003eS. senegal\u003c/em\u003e, and \u003cem\u003eV. nilotica\u003c/em\u003e, the density of other tree species was below the average (i.e., 7.0 tree ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). The average contribution of the other tree species to the total population was 45.3%. The average height, dbh, and canopy diameter of selected trees varied significantly between agroforestry systems (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The mean tree height was 8.46 m across the species. \u003cem\u003eD. sissoo, T. grandis\u003c/em\u003e, and \u003cem\u003eA. indica\u003c/em\u003e trees exhibited greater height than other species. Heights of \u003cem\u003eT. undulata, V. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis\u003c/em\u003e, \u003cem\u003eS. oleoides\u003c/em\u003e, \u003cem\u003eV. leucophloea\u003c/em\u003e, and \u003cem\u003eZ. mauritiana\u003c/em\u003e trees were below average. \u003cem\u003eS. oleoides\u003c/em\u003e exhibited the greatest dbh, whereas the dbh of \u003cem\u003eZ. mauritiana\u003c/em\u003e was less than that of other species. Average dbh and canopy diameter across the species were 33.67 cm and 6.94 m, respectively. The canopy diameter was highest in \u003cem\u003eV. tortilis\u003c/em\u003e and lowest in \u003cem\u003eT. grandis\u003c/em\u003e. \u003cem\u003eP. cineraria\u003c/em\u003e, \u003cem\u003eT. undulata\u003c/em\u003e, \u003cem\u003eP. juliflora\u003c/em\u003e, \u003cem\u003eA. excelsa\u003c/em\u003e, and \u003cem\u003eA. indica\u003c/em\u003e had medium canopy diameters.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePopulation density and growth parameters of tree species in different agroforestry systems in Rajasthan. Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;1SD of multiple replications\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTree-based system (selected tree system)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePopulation density (nos. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eGrowth variable of selected trees\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelected species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOthers species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHeight (m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDBH (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCanopy dia. (m)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAilanthus excelsa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.09\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.85\u0026thinsp;\u0026plusmn;\u0026thinsp;16.91\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAzadirachta indica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.18\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.83\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.70\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.54\u0026thinsp;\u0026plusmn;\u0026thinsp;13.76\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDalbergia sissoo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.22\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.91\u0026thinsp;\u0026plusmn;\u0026thinsp;14.39\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProsopis cineraria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.62\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.64\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.67\u0026thinsp;\u0026plusmn;\u0026thinsp;10.95\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP. juliflora\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.22\u0026thinsp;\u0026plusmn;\u0026thinsp;7.46\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSalvadora oleoides\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.96\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.81\u0026thinsp;\u0026plusmn;\u0026thinsp;34.26\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.69\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSenegalia senegal\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.10\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.20\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.30\u0026thinsp;\u0026plusmn;\u0026thinsp;8.99\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.10\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTecomella undulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.19\u0026thinsp;\u0026plusmn;\u0026thinsp;9.26\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTectona grandis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.09\u0026thinsp;\u0026plusmn;\u0026thinsp;4.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVachellia leucophloea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.49\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.14\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVachellia nilotica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.18\u0026thinsp;\u0026plusmn;\u0026thinsp;9.99\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eV. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.75\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.68\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.23\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eV. tortilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.95\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.52\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.56\u0026thinsp;\u0026plusmn;\u0026thinsp;11.24\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.30\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZizyphus mauritiana\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.73\u0026thinsp;\u0026plusmn;\u0026thinsp;6.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eOne-way ANOVA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.72**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2.78*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.12**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.93**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.71**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ens - not-significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *-significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** - significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eValues with different alphabets as superscripts in a column indicate significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) differences.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eChanges in soil properties\u003c/p\u003e \u003cp\u003eSoil pH, electrical conductivity (EC), soil organic carbon (SOC), total nitrogen (TN), available phosphorus (PO\u003csub\u003e4\u003c/sub\u003e-P), and exchangeable potassium (K) varied significantly between agroforestry systems. However, it was significant only for TN and K for distances from the tree (Supplementary Table A2). When the agroforestry system was considered, the soil pH and EC were significantly lower in the \u003cem\u003eT. grandis-\u003c/em\u003ebased system. Soil pH was highest in \u003cem\u003eZ. mauritiana\u003c/em\u003e and \u003cem\u003eS. senegal-\u003c/em\u003ebased systems, whereas EC was the highest in \u003cem\u003eD. sissoo-\u003c/em\u003ebased systems (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Most systems did not differ in soil pH and EC (Duncan Multiple Range tests, DMRT), though variations between the highest and lowest values of these parameters were \u0026gt;\u0026thinsp;1.0 unit. The highest SOC and TN were in the soils of \u003cem\u003eT. grandis\u003c/em\u003e, and the lowest were beneath \u003cem\u003eP. juliflora-\u003c/em\u003ebased systems, with 5.1-fold and 5.8-fold variation, respectively. However, SOC did not differ between the soils of \u003cem\u003eS. oleoides\u003c/em\u003e, \u003cem\u003eS. senegal\u003c/em\u003e, \u003cem\u003eT. undulata\u003c/em\u003e, \u003cem\u003eV. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis\u003c/em\u003e, and \u003cem\u003eZ. mauritiana\u003c/em\u003e-based systems. Likewise, TN did not differ between the soils of \u003cem\u003eA. excelsa\u003c/em\u003e, \u003cem\u003eS. oleoides\u003c/em\u003e, \u003cem\u003eS. senegal\u003c/em\u003e, \u003cem\u003eV. tortilis\u003c/em\u003e, and \u003cem\u003eZ. mauritiana\u003c/em\u003e-based systems. Soil available PO\u003csub\u003e4\u003c/sub\u003e-P was 2.98 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eD. sissoo\u003c/em\u003e and increased to the highest (7.09 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil) in the \u003cem\u003eT. grandis\u003c/em\u003e-based system. The availability of K was highest in \u003cem\u003eP. juliflora\u003c/em\u003e and lowest in \u003cem\u003eV. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis-\u003c/em\u003ebased system, showing 3.0-fold variation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of tree species on soil physicochemical properties in different agroforestry systems in Rajasthan. Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;1SD of multiple replications.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTree system\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eSoil parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEC (dS m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSOC (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePO\u003csub\u003e4\u003c/sub\u003e-P (mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eK (mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. excelsa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003ecdef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003edef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.37\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. indica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003edef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.21\u0026thinsp;\u0026plusmn;\u0026thinsp;2.84\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e126\u0026thinsp;\u0026plusmn;\u0026thinsp;102\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eD. sissoo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003csup\u003eef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003edef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.98\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e190\u0026thinsp;\u0026plusmn;\u0026thinsp;66\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP. cineraria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003csup\u003edef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e146\u0026thinsp;\u0026plusmn;\u0026thinsp;59\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP. juliflora\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e209\u0026thinsp;\u0026plusmn;\u0026thinsp;36\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. oleoides\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003csup\u003edef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e135\u0026thinsp;\u0026plusmn;\u0026thinsp;41\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. senegal\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003csup\u003edef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e132\u0026thinsp;\u0026plusmn;\u0026thinsp;73\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eT. grandis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.09\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eT. undulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e134\u0026thinsp;\u0026plusmn;\u0026thinsp;51\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eV. nilotica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003csup\u003edef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e154\u0026thinsp;\u0026plusmn;\u0026thinsp;112\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eV. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e69\u0026thinsp;\u0026plusmn;\u0026thinsp;3.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eV. leucophloea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003eef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e108\u0026thinsp;\u0026plusmn;\u0026thinsp;49\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eV. tortilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e197\u0026thinsp;\u0026plusmn;\u0026thinsp;61\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZ. mauritiana\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003csup\u003eef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e129\u0026thinsp;\u0026plusmn;\u0026thinsp;56\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eF value for two-way ANOVA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.31**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.28**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.96**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.73**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.66**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.58**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eValues with different alphabets as superscripts in a column indicate significant differences at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eThe ns, * and ** are not-significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, respectively.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSoil organic carbon, TN, PO\u003csub\u003e4\u003c/sub\u003e-P, and K were significantly higher in the canopy zone than outside the canopy zone soils (control). Soil pH was significantly lower near the tree trunk and increased to the highest in the control through the canopy edge soil (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In contrast, soil EC and K were highest near tree trunks and decreased to the lowest in the soils of the control plots. SOC, TN, and available PO\u003csub\u003e4\u003c/sub\u003e-P were greater at the canopy edge and lowest in the control plots. SOC was 15.8% and 10.5% higher near the tree and at the canopy edge than in the control plot, whereas TN was 12.5% higher near the tree and at the canopy edge, respectively. Availability of PO\u003csub\u003e4\u003c/sub\u003e-P was higher by 8.2% near the tree and by 8.4% at the canopy edge. The system \u0026times; distance interaction was not significant for all soil parameters, indicating their independent behaviour for the soil variables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of distance from trees on soil properties in different agroforestry systems in Rajasthan. Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;1SD of multiple replications.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCanopy zone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eSoil parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEC (dSm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSOC (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePO\u003csub\u003e4\u003c/sub\u003e-P (mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eK (mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNear tree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e154\u0026thinsp;\u0026plusmn;\u0026thinsp;88\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanopy edge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e140\u0026thinsp;\u0026plusmn;\u0026thinsp;83\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e134\u0026thinsp;\u0026plusmn;\u0026thinsp;75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eF-value of Two-way ANOVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistance (D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.21ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.39ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.68**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.01ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.09*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem \u0026times; D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.81ns\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eValues with different alphabets as superscripts in a column indicate significant differences at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eThe ns, * and ** are not-significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, respectively.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSoil carbon storage\u003c/p\u003e \u003cp\u003eThe average soil C stock in the 0\u0026ndash;30 cm soil layer of different agroforestry systems is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. This varied (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) due to both agroforestry systems and distances from the trees. The soil C stock varied by 5-fold between the agroforestry systems across distances. It was highest beneath \u003cem\u003eT. grandis\u003c/em\u003e (22.85 Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), followed by \u003cem\u003eV. leucophloea\u003c/em\u003e and \u003cem\u003eV. nilotica\u003c/em\u003e. Soil C stock did not differ between the soils of \u003cem\u003eP. juliflora, T. undulata, V. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis\u003c/em\u003e, \u003cem\u003eV. tortilis, Z. mauritiana, S. oleoides\u003c/em\u003e, \u003cem\u003eS. senegal\u003c/em\u003e, and \u003cem\u003eP. cineraria\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). \u003cem\u003eA. indica, D. sissoo\u003c/em\u003e, and \u003cem\u003eV. nilotica-\u003c/em\u003ebased systems showed higher than the average soil C stock. While considering distances from the tree trunk across systems, soil C stock was lowest in the control. The difference in C-stock between soils near the tree and the tree canopy edge was insignificant (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Average soil C stock was 10.11% higher near trees and 15.55% higher at the canopy edge compared with the control plots. The increase in C stock in the canopy zone soils of different trees compared to the control ranged from 4.0% in \u003cem\u003eT. grandis\u003c/em\u003e to 28.3% in \u003cem\u003eP. cineraria\u003c/em\u003e-based system (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). System \u0026times; distance interaction was not significant, showing independent behaviour of these factors.\u003c/p\u003e \u003cp\u003eRelative tree effects (RTE)\u003c/p\u003e \u003cp\u003eThe relative tree effects (RTE) values of most soil variables (except EC and PO\u003csub\u003e4\u003c/sub\u003e-P) varied significantly between tree-based systems (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). RTE for soil pH (RTE\u003csub\u003epH\u003c/sub\u003e) was lowest (-0.018) in \u003cem\u003eA. excelsa\u003c/em\u003e and highest (+\u0026thinsp;0.019) in the \u003cem\u003eV. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis-\u003c/em\u003ebased system. Other systems did not differ in RTE\u003csub\u003epH\u003c/sub\u003e (DMRT). RTE\u003csub\u003eEC\u003c/sub\u003e was lowest (-0.179) in \u003cem\u003eP. juliflora\u003c/em\u003e/\u003cem\u003eP. cineraria\u003c/em\u003e and highest (-0.022) in the \u003cem\u003eT. grandis-\u003c/em\u003ebased system. RTE\u003csub\u003eSOC,\u003c/sub\u003e and RTE\u003csub\u003ePO4\u0026minus;P\u003c/sub\u003e values were negative and ranged from \u0026minus;\u0026thinsp;0.214 for \u003cem\u003eD. sissoo\u003c/em\u003e to -0.047 for \u003cem\u003eT. grandis\u003c/em\u003e, and from \u0026minus;\u0026thinsp;0.149 for \u003cem\u003eA. indica\u003c/em\u003e to -0.018 for \u003cem\u003eD. sissoo\u003c/em\u003e, respectively. Effects of most of the tree species (except \u003cem\u003eA. excelsa\u003c/em\u003e) on TN were positive, with RTE\u003csub\u003eTN\u003c/sub\u003e values of -0.279 for \u003cem\u003eP. juliflora\u003c/em\u003e to +\u0026thinsp;0.015 for \u003cem\u003eA. excelsa\u003c/em\u003e-based systems. For soil K, most tree-based systems showed positive effects (except \u003cem\u003eA. excelsa\u003c/em\u003e and \u003cem\u003eD. sissoo\u003c/em\u003e) with RTE\u003csub\u003eK\u003c/sub\u003e values ranging from \u0026minus;\u0026thinsp;0.203 for \u003cem\u003eV. tortilis\u003c/em\u003e to +\u0026thinsp;0.049 for \u003cem\u003eA. excelsa\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe relative tree effect on changes in soil properties in different agroforestry systems in Rajasthan. Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;1SD (in the second row) of multiple replications.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTree-based system\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eSoil parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSOC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePO\u003csub\u003e4\u003c/sub\u003e-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAilanthus excelsa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.018\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.115\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.123\u003csup\u003ebcde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u0026thinsp;0.015\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.067\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u0026thinsp;0.045\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.323\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAzadirachta indica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.002\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.095\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.104\u003csup\u003ebcde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.168\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.149\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.160\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDalbergia sissoo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.005\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.130\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.214\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.108\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.018\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u0026thinsp;0.034\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProsopis cineraria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.004\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.178\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.186\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.063\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.037\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.110\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProsopis juliflora\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.001\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.179\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.133\u003csup\u003eabcde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.279\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.048\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.023\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSalavadora oleoides\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.005\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.114\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.121\u003csup\u003ebcde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.186\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.092\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.083\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSenegalia senegal\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.015\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.110\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.149\u003csup\u003ebcde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.129\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.082\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.030\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTecomella undulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.007\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.082\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.147\u003csup\u003eabcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.124\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.052\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.055\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTectona grandis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.003\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.022\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.047e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.069\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.077\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.020\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.187\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVachellia luecophloea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.007\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.077\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.077\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.038\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.099\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.170\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eV. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.003\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.092\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.047\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.069\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.077\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.082\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.187\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVachellia nilotica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.010\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.134\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.170\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.106\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.078\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.149\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVachellia tortilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.015\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.133\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.149\u003csup\u003eabcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.129\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.082\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.203\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZizyphus mauritiana\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.005\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.125\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.163\u003csup\u003eabcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.139\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.109\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.087\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.172\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eOne-way ANOVA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.442**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.526ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.534**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.052*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.711ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.432**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eValues with different alphabets as superscripts in a column indicate significant differences at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eThe ns, * and ** are not-significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, respectively. \u0026lsquo;-\u0026rsquo; indicates a positive effect, whereas \u0026lsquo;+\u0026rsquo; indicates competitive effects.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCorrelation and regression\u003c/p\u003e \u003cp\u003eAnnual rainfall exhibited positive correlations with tree density, SOC, TN, PO\u003csub\u003e4\u003c/sub\u003e-P, and SOC-stock, and negative correlations with soil K, pH, and EC (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Tree species richness was positively correlated to DBH, canopy diameter, and soil K, whereas it showed negative correlations with SOC and other soil variables. Per cent SOC was correlated positively to tree height and soil nutrients, and negatively to pH and EC. Tree canopy diameter was positively correlated with SOC and nutrients. Selected tree density (STD) was correlated positively to soil PO\u003csub\u003e4\u003c/sub\u003e-P and negatively to K, DBH, and canopy diameter. Soil C-stock was correlated positively to tree height, canopy diameter, SOC, and nutrients, and negatively to soil pH and EC. We observed a significant linear relationship between rainfall and SOC (Y\u0026thinsp;=\u0026thinsp;0.128\u0026thinsp;+\u0026thinsp;0.0004X, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.038, \u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;50.26, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Relationships of rainfall and SOC with other soil variables were similar, except for soil K, which increased with a decrease in rainfall and an increase in SOC. Soil TN and PO\u003csub\u003e4\u003c/sub\u003e-P increased, and K, pH, and EC decreased with increases in rainfall (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-e). Likewise, soil pH and EC decreased, whereas TN, PO\u003csub\u003e4\u003c/sub\u003e-P, and K increased with an increase in SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef-j).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation matrix of different soil variables in agroforestry systems in Rajasthan, India\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"14\" nameend=\"c15\" namest=\"c2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRainfall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDBH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCDia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSTD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOTD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSOC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eTotal N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003ePO\u003csub\u003e4\u003c/sub\u003e-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eC-stock\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRainfall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.30**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.13**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.27**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.53**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.63**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.24**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.29**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.20**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.27**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.29**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.40**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.24**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.30**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.08*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.13**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.14**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.06*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.06*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.15**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.10**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.13**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.45**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.32**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.11**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.09**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.06*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.07*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-.27**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.47**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003cp\u003e0.20**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.37**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.18**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.76**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.26**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.31**.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.99**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.27**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.31**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.76**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.28**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.75**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePO\u003csub\u003e4\u003c/sub\u003e-P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.30**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.19**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.10**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.26**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.16**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.20**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.40**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.30*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.38**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.10**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.31**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.28**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.16**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.29**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-stock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.38**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.21**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.99**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.75**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.20**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.29**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"15\"\u003eThe ns, * and ** are not-significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, respectively (n\u0026thinsp;=\u0026thinsp;1275).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"15\"\u003eTD, tree density; STD, selected tree density; OTD, other tree density; Cdia, canopy diameter; BD, bulk density.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eComposition and growth of trees\u003c/p\u003e \u003cp\u003eThe diverse distribution of 14 different agroforestry systems, each with variations in tree density, growth patterns, and species richness, can be attributed to a combination of climatic conditions, edaphic conditions, and socioeconomic factors (Saxena, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Singh et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These factors influence where specific agroforestry systems thrive and the types of trees and crops that are most suitable. Tree density of 7.0-12.1 trees ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for \u003cem\u003eA. excelsa\u003c/em\u003e, \u003cem\u003eS. senegal\u003c/em\u003e, and \u003cem\u003eV. leucophloea\u003c/em\u003e-based systems was very similar to the observation of Tewari et al. (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) for \u003cem\u003eP. cineraria\u003c/em\u003e (8.2\u0026ndash;14.2 trees ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). The higher frequency of \u003cem\u003eProsopis cineraria\u003c/em\u003e in arid western Rajasthan and \u003cem\u003eVachellia nilotica\u003c/em\u003e in areas with higher rainfall and deeper/medium soils indicates their respective adaptive strategies (Hussain, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The social acceptance of trees resulted in increased species richness on the farmlands. However, reduced tree density (r\u0026thinsp;=\u0026thinsp;0.63, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) with a decrease in annual rainfall indicates a negative impact of poor soil status and low soil water on tree density. The use of tractors and intensive cultivation has also supported the uprooting and destruction of woody vegetation, affecting the density of \u003cem\u003eS. oleoides\u003c/em\u003e and \u003cem\u003eP. cineraria\u003c/em\u003e and the least preferred species like \u003cem\u003eV. tortilis\u003c/em\u003e and \u003cem\u003eP. juliflora\u003c/em\u003e (0.7\u0026ndash;1.2 tree ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) on farmlands (Bhati et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Species characteristics and climate-influenced growth in tree species resulted in significant differences in height, dbh, and canopy diameter among agroforestry systems. Although temperature and annual rainfall are the dominant drivers favouring diameter growth (Żywiec et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Gauli et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the increased tree growth, particularly of \u003cem\u003eD. sissoo\u003c/em\u003e in Sriganganagar and Hanumangarh with low precipitation, was due to canal water irrigation. The highest dbh for \u003cem\u003eS. oleoides\u003c/em\u003e and the smaller size of \u003cem\u003eZ. mauritiana\u003c/em\u003e and \u003cem\u003eS. senegal\u003c/em\u003e trees were attributed to edaphic and climatic conditions and species-specific growth (Mensah et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Negative correlations between tree growth and soil pH also supported this inference.\u003c/p\u003e \u003cp\u003eSoil physicochemical changes in agroforestry systems\u003c/p\u003e \u003cp\u003eSoil pH and EC impacted plant growth by influencing salt concentrations, nutrient release by weathering, the solubility of released materials, and the amount of nutrients stored in the soil (Neina, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Soils were slightly alkaline in reaction and normal in salinity. However, a wide variation in soil pH and EC between different agroforestry systems was associated with climatic conditions, mineral weathering, and salt accumulation through surface runoff (Naorem et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, below-average soil pH in most agroforestry systems was due to high SOC and leaching of major base cations in low-texture soils (Meena and Mathur, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). High EC in the soils associated with \u003cem\u003eD. sissoo\u003c/em\u003e grown in irrigated areas was due to overirrigation, a rise in groundwater table and increased level of salinisation (Kumar et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rani et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Relatively greater EC under \u003cem\u003eZ. mauritiana\u003c/em\u003e and \u003cem\u003eS. oleoides\u003c/em\u003e trees were due to low rainfall (aridity index of 0.03\u0026ndash;0.20) and adaptation in these species to occupy soils with high salt concentration (Verma et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Dagar et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Significantly lower RTE\u003csub\u003eEC\u003c/sub\u003e for \u003cem\u003eP. juliflora\u003c/em\u003e and \u003cem\u003eP. cineraria\u003c/em\u003e compared to \u003cem\u003eT. grandis\u003c/em\u003e showed the tolerance of the former species to moderately saline soils. This inference was also supported by a negative correlation between rainfall and soil pH (r = -0.24, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and EC (r = -0.29, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, variations in SOC (5.1-fold) and C-stock (5.0-fold) between \u003cem\u003eP. juliflora\u003c/em\u003e and \u003cem\u003eT. grandis\u003c/em\u003e were certainly due to variability in rainfall and soil conditions. Singh et al. (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) also observed greater SOC in Alfisols, Vertisols and Inceptisols than Aridisols, and this was associated with higher rainfall, clay content and greater vegetative input. Positive correlations of rainfall with SOC (r\u0026thinsp;=\u0026thinsp;0.194, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), total N (r\u0026thinsp;=\u0026thinsp;0.269, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and PO\u003csub\u003e4\u003c/sub\u003e-P (r\u0026thinsp;=\u0026thinsp;0.291, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) highlight the importance of rainfall and corresponding soil water availability on soil nutrient availability. The increase in tree size (height, dbh, and canopy diameter) improved soil properties by influencing litter input and nutrient cycling (Murovhi et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Gupta et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Significantly high SOC in \u003cem\u003eT. grandis, V. nilotica\u003c/em\u003e, and \u003cem\u003eV. luecophloea\u003c/em\u003e systems was due to their availability in relatively high rainfall zones with sandy loam to black soil. Likewise, low SOC in \u003cem\u003eP. cineraria, S. senegal\u003c/em\u003e, \u003cem\u003eS. oleoides, T. undulata, Z. mauritiana\u003c/em\u003e, \u003cem\u003eV. tortilis, P. juliflora\u003c/em\u003e-based systems was associated with the sandy soils. This showed the importance of tree species and soil texture influencing the spatial pattern of SOC (Pinho et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Shi et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The importance of soil texture on SOC retention was also shown by 25.0% and 2.4% increases in SOC beneath \u003cem\u003eP. cineraria\u003c/em\u003e (growing in sandy soil area) and \u003cem\u003eT. grandis\u003c/em\u003e (clay soil area), respectively, compared to the control. RTE\u003csub\u003eSOC\u003c/sub\u003e value of -0.047 for \u003cem\u003eT. grandis\u003c/em\u003e and \u0026minus;\u0026thinsp;0.186 for \u003cem\u003eP. cineraria\u003c/em\u003e also supports the inference (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Earlier studies also suggest negative correlations of SOC with sand, mean high temperature and pH of the soil, and positive correlations with mean annual rainfall, silt, and clay content of different tree stands (Burke et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Devi, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA wide variation in total N (0.04% in \u003cem\u003eP. juliflora\u003c/em\u003e to 0.23% in \u003cem\u003eT. grandis\u003c/em\u003e), available PO\u003csub\u003e4\u003c/sub\u003e-P (2.98 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eD. sissoo\u003c/em\u003e to 7.09 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eT. grandis\u003c/em\u003e), and K (69 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eV. nilotica\u003c/em\u003e var. \u003cem\u003ecupressiformis\u003c/em\u003e to 209 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eP. juliflora\u003c/em\u003e based system) indicate the impact of soil water through rainfall and tree attributes contributing to litter addition and fine roots turnover (Patel et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sayno et al., 2023). This inference was also supported by relationships of rainfall and SOC with other soil variables, i.e. enhanced total N and PO\u003csub\u003e4\u003c/sub\u003e-P (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, the nutrient cycle process is also controlled by several factors like tree species, soil properties (clay content, pH), stand age, management practices, topography, and climatic conditions (Jandal et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Negasha et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Magersa and Worku (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) also recorded higher SOM and total N in the soils associated with Acacia species than \u003cem\u003eP. juliflora\u003c/em\u003e. Thus, tree-specific variations in soil characteristics highlight the potential of different tree species in building SOC and available N, P, and K, depending on their use in phytobiomass production and subsequent returns in the form of litter (Aggarwal et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Yadav et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Greater availability of PO\u003csub\u003e4\u003c/sub\u003e-P under \u003cem\u003eT. grandis\u003c/em\u003e and \u003cem\u003eV. nilotica\u003c/em\u003e was related to loam to clay loam soils (Takner et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In contrast, low (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, DMRT) availability of PO\u003csub\u003e4\u003c/sub\u003e-P in \u003cem\u003eA. indica\u003c/em\u003e, \u003cem\u003eV. luecophloea\u003c/em\u003e, \u003cem\u003eA. excelsa\u003c/em\u003e, \u003cem\u003eP. cineraria\u003c/em\u003e, and \u003cem\u003eS. oleoides-\u003c/em\u003ebased systems was due to sandy loam soil and their use in the growth of trees and the companion crops. Binkley et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1992\u003c/span\u003e) observed that N-fixing tree species increase N and P cycling by producing more litter and favouring greater release of soil nutrients than non-N-fixing tree species. However, the non-significant difference in soil PO\u003csub\u003e4\u003c/sub\u003e-P between N\u003csub\u003e2\u003c/sub\u003e-fixing and non-N\u003csub\u003e2\u003c/sub\u003e-fixing species in the study was due to a wide range of climatic and edaphic conditions. The low PO\u003csub\u003e4\u003c/sub\u003e-P availability in the soils of \u003cem\u003eD. sissoo\u003c/em\u003e and \u003cem\u003eP. juliflora-\u003c/em\u003ebased systems was because of the fast growth rate and greater use of soil nutrients compared to other species (Deng et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The findings of Agarwal et al. (1976) also suggested an increase in soil fertility status in \u003cem\u003eP. cineraria\u003c/em\u003e and \u003cem\u003eT. undulata\u003c/em\u003e particularly SOC, total N, and available PO\u003csub\u003e4\u003c/sub\u003e-P compared to the soils under \u003cem\u003eP. juliflora-\u003c/em\u003ebased system Another possibility of increased soil nutrients under tree canopy was the dropping and excreta of birds and cattle taking shelter to these tree species, particularly in dry areas, contributing enormously towards making the agroforestry system more fertile (Bhati et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Bremer et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSpatial variations in soil properties\u003c/p\u003e \u003cp\u003eSignificantly higher values of soil EC, SOC, TN, PO\u003csub\u003e4\u003c/sub\u003e-P, and K under the canopy zone soil than in the control were due to added litter and its decomposition (Tadesse et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mesfin and Haileselassie, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Syano et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This was also supported by negative values of RTE of these soil variables in most agroforestry systems. Greater soil pH near the tree trunk under \u003cem\u003eV. leucophloea\u003c/em\u003e, and at the canopy edge under \u003cem\u003eA. excelsa\u003c/em\u003e, \u003cem\u003eS. oleoides\u003c/em\u003e, \u003cem\u003eP. juliflora\u003c/em\u003e, \u003cem\u003eV. leucophloea\u003c/em\u003e, \u003cem\u003eZ. mauritiana\u003c/em\u003e, \u003cem\u003eD. sissoo\u003c/em\u003e and \u003cem\u003eS. senegal\u003c/em\u003e might be due to cations (i.e., Ca, Mg, K, and Na) rich litter production. Other studies have also reported an increase in soil pH, K, and PO\u003csub\u003e4\u003c/sub\u003e-P under tree canopy than in the open field (Gindaba et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Diallo et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A general order of different sites like control\u0026thinsp;\u0026lt;\u0026thinsp;near tree\u0026thinsp;\u0026lt;\u0026thinsp;canopy edge for SOC, total N and PO\u003csub\u003e4\u003c/sub\u003e-P, and control\u0026thinsp;\u0026lt;\u0026thinsp;canopy edge\u0026thinsp;\u0026lt;\u0026thinsp;near tree for EC and K was attributed to the effect of a balance between uptake by trees/ crops and their release through added litter, fine root turn over and tree characteristics (Isaac and Borden, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Steinfeld et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the lowest EC near the tree of \u003cem\u003eT. grandis, S. oleoides\u003c/em\u003e, \u003cem\u003eA. excelsa\u003c/em\u003e, \u003cem\u003eP. juliflora\u003c/em\u003e, and \u003cem\u003eV. tortilis\u003c/em\u003e was due to increased uptake of salts by these species as observed in another study (Singh et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), where indigenous \u003cem\u003eS. oleoides, T. undulata\u003c/em\u003e, \u003cem\u003eP. cineraria\u003c/em\u003e, and \u003cem\u003eS. persica\u003c/em\u003e showed a greater potential for salts and nutrients absorption from the wastewater contaminated soils. Soil available PO\u003csub\u003e4\u003c/sub\u003e-P was also affected by different tree species (Batterman et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), as it was greater near trees in \u003cem\u003eV. luecophloea, Z. mauritiana\u003c/em\u003e, \u003cem\u003eV. tortilis\u003c/em\u003e, and \u003cem\u003eA. indica\u003c/em\u003e and at the canopy edge in \u003cem\u003eA. indica, S. oleoides\u003c/em\u003e, \u003cem\u003eD. sissoo\u003c/em\u003e, and \u003cem\u003eZ. mauritiana\u003c/em\u003e based systems than the other sites. This indicates that phosphorus availability also depends on soil organic matter and soil texture (Louche et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). A significantly high concentration of exchangeable K near trees (12.82%) was due to its addition by tree litter, particularly \u003cem\u003eP. juliflora\u003c/em\u003e, \u003cem\u003eD. sissoo, V. tortilis, V. nilotica\u003c/em\u003e, and \u003cem\u003eP. cineraria\u003c/em\u003e (Kumar et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePotential trees in improving soil properties and C-sequestration\u003c/p\u003e \u003cp\u003eSignificant increase in SOC under the canopies of \u003cem\u003eP. cineraria, P. juliflora\u003c/em\u003e, \u003cem\u003eD. sissoo\u003c/em\u003e, and \u003cem\u003eV. tortilis\u003c/em\u003e than beneath \u003cem\u003eT. grandis, A. indica\u003c/em\u003e, and \u003cem\u003eV. leucophloea\u003c/em\u003e trees highlights the importance of legume trees in soil amelioration (Gei and Powers, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Patel et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found an increase in SOC under canopy trees in the order: \u003cem\u003eA. indica\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eP. juliflora\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eP. cineraria\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eV. tortilis\u003c/em\u003e. Increases in SOC and C-stock were associated with a decrease in soil pH and EC, and an increase in soil nutrients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef-j), highlighting the positive role of SOC on soil nutrients (Dori et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Prasad et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the highest concentration of soil N beneath \u003cem\u003eP. juliflora\u003c/em\u003e and \u003cem\u003eV. tortilis\u003c/em\u003e than under \u003cem\u003eP. cineraria\u003c/em\u003e and \u003cem\u003eA. indica\u003c/em\u003e was attributed to lopping of the latter two species for fodder, which affected the amount of litter added to the soil (Patel et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The relatively high RTE\u003csub\u003eTN\u003c/sub\u003e in \u003cem\u003eP. cineraria\u003c/em\u003e (-0.063) than \u003cem\u003eP. juliflora\u003c/em\u003e (-0.279) also shows the impact of species on soil nutrient variations (Bhati et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jouybari et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Observed greater soil K under \u003cem\u003eA. indica, V. tortilis, V. leucophloea, V. nilotica\u003c/em\u003e, and \u003cem\u003eP. cineraria\u003c/em\u003e than beneath \u003cem\u003eA. excelsa, D. sissoo\u003c/em\u003e, \u003cem\u003eS. senegal\u003c/em\u003e, and \u003cem\u003eP. juliflora\u003c/em\u003e was because of litter quality and K concentration in the litter. Tanga et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) recorded soil K levels greater in \u003cem\u003eV. tortilis\u003c/em\u003e than in \u003cem\u003eBalanites aegyptiaca\u003c/em\u003e and \u003cem\u003eV. seyal\u003c/em\u003e-based systems. The magnitude of reduction in soil pH, EC and an increase in SOC, total N, PO\u003csub\u003e4\u003c/sub\u003e-P, and K beneath the tree canopy compared with those outside the canopy zone highlights the impact of tree species on improvement in soil fertility and carbon sequestration in agroforestry systems (Singh, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Ashaye, 2017). However, positive correlations of soil C-stock with tree height and canopy diameter highlight the impact of tree size in enhancing soil carbon sequestration.\u003c/p\u003e"},{"header":"Conclusion and recommendations","content":"\u003cp\u003eClimatic factors, particularly rainfall, are the most influential drivers governing the distribution of agroforestry systems and the population and growth of trees within the systems. However, the increase in SOC, total N, available PO\u003csub\u003e4\u003c/sub\u003e-P, K, and C stock, and decrease in soil pH and EC showed a positive impact of trees on soil properties. The dominance of the tree species of the tree-based system appeared to be more influential in improving soil characteristics. The positive influence of trees increased with an increase in growth size (height, DBH, and canopy diameter). The effects were significantly high for \u003cem\u003eP. cineraria\u003c/em\u003e and \u003cem\u003eV. tortilis\u003c/em\u003e in arid regions, and \u003cem\u003eV. nilotica\u003c/em\u003e, \u003cem\u003eA. indica\u003c/em\u003e, and \u003cem\u003eV. leucophloea\u003c/em\u003e-based systems in the semiarid areas. Significant decrease in soil pH and EC beneath \u003cem\u003eA. excelsa\u003c/em\u003e and \u003cem\u003eV. tortilis\u003c/em\u003e, increase in SOC under \u003cem\u003eP. cineraria\u003c/em\u003e, total N under \u003cem\u003eP. juliflora\u003c/em\u003e, and available PO\u003csub\u003e4\u003c/sub\u003e-P and exchangeable K beneath \u003cem\u003eA. indica\u003c/em\u003e are the effects of tree species. Although exotics like \u003cem\u003eP. juliflora\u003c/em\u003e and \u003cem\u003eV. tortilis\u003c/em\u003e also exhibited wide adaptability and soil improvement characteristics, indigenous tree species appeared better than exotics and can be given preference. This study highlights species-specific services of the agroforestry systems in terms of improved soil properties and enhanced soil carbon storage. These findings emphasise the potential of tree-based systems in agriculture to boost land productivity and create new income streams through carbon sequestration. Farmers can use this information to select suitable tree-based systems, enhancing both their livelihoods and environmental sustainability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the Director, ICFRE-AFRI, Jodhpur, for providing the required amenities and inspiration to complete this research work. Thanks are also due to the farmers for their consent and help during field data recording on their farmlands. We also acknowledge the financial assistance from the Forest Department, the Government of Rajasthan, and the help of forest staff of different divisions during the study period. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the State Forest Department, Government of Rajasthan, India.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor and information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBilas Singh: Extension Division, Arid Forest Research Institute, Jodhpur, India\u003c/p\u003e\n\u003cp\u003eG. Singh: Forest Ecology and Climate Change Division, Arid Forest Research Institute, Jodhpur, India. Present address: 1/279, Viraj Khand, Gomti Nagar, Lucknow-226010 (UP), India\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eB. Singh \u0026amp; G. Singh. Both authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by BS. The first draft of the manuscript was prepared by BS, and edited and revised by GS. Both authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to\u0026nbsp;[email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary data\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdekiya, A. O., Alori, E. T., Ogunbode, T. O., Sangoyomi, T., \u0026amp; Oriade, O. A. (2023). 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Long-term effect of temperature and precipitation on radial growth in a threatened thermo-Mediterranean tree population. \u003cem\u003eTrees, 31\u003c/em\u003e, 491-501. https://doi.org/10.1007/s00468-016-1472-8.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dry region, trees on farmlands, relative tree effects, soil characteristics, tree growth","lastPublishedDoi":"10.21203/rs.3.rs-6841363/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6841363/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe impact of trees on soils is diverse, varying based on tree species and environmental conditions. To better understand the functionality and services of agroforestry systems, we assessed the impact of trees on soil properties and carbon storage in 14 traditional agroforestry systems in Rajasthan, India. Trees were counted for species and density, and were measured for height, diameter at breast height (dbh), and canopy diameter in 0.5 ha plots on 84 farmlands. Soil pH, electrical conductivity (EC), organic carbon (SOC), total nitrogen (TN), available phosphorus, and exchangeable potassium were assessed for samples collected at 1 m from the tree, the canopy edge, and 5 m away from the canopy edge as a control. Soil variables differed significantly between systems and distances from the trees. SOC, TN, phosphorus, potassium, and C-stock showed\u0026thinsp;+\u0026thinsp;2.3\u0026ndash;25.0% increase, whereas pH/EC decreased beneath the tree canopy compared to the control. \u003cem\u003eP. cineraria\u003c/em\u003e, \u003cem\u003eP. juliflora\u003c/em\u003e, and \u003cem\u003eA. indica\u003c/em\u003e exhibited high SOC, TN, phosphorus, and potassium, respectively. Soil pH and EC were low under \u003cem\u003eA. excelsa\u003c/em\u003e. Most soil variables increased with an increase in tree size. Rainfall negatively impacted soil pH, EC, and potassium. Climate significantly influenced the distribution of agroforestry systems, and the growth and dynamics of the dominant trees within these systems were key drivers for improving soil nutrients, properties, and carbon storage. These findings suggest that integrating trees into farming systems through planting can improve soil fertility, enhance carbon storage, and help restore degraded farmlands, contributing to both sustainable agricultural production and climate change mitigation.\u003c/p\u003e","manuscriptTitle":"The effects of trees on soil properties and carbon storage in spatially distributed agroforestry systems in northwestern India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-04 13:20:16","doi":"10.21203/rs.3.rs-6841363/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"261f3140-cf07-48ca-bea5-9cf680a2df07","owner":[],"postedDate":"July 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-01T01:23:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-04 13:20:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6841363","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6841363","identity":"rs-6841363","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}