Arachis pintoi cover cropping increases drought survival of Citrus latifolia in an intercrop with Coffea arabica

Arachis pintoi cover cropping increases drought survival of Citrus latifolia in an intercrop with Coffea arabica | 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 Arachis pintoi cover cropping increases drought survival of Citrus latifolia in an intercrop with Coffea arabica Samuel Coulbourn Flores, Dora Trejo Aguilar, Jacob Bañuelos This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8431754/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 Aims: Once rare, extended droughts are becoming more frequent in parts of the wet tropics, impacting rain-fed production of major commodities including citrus and coffee. We hypothesized that the dense, deep-rooted, perennial cover crop Arachis pintoi would keep soil cool and moist during drought, protecting young Citrus latifolia trees. Methods: We measured moisture (NDMI) and vegetation (gNDVI) index using Sentinel2 multispectral imaging. We also made ground measurements of leaf stomatal conductance, soil temperature, and soil aggregation. Results: A. pintoi cover cropped plots had significantly higher NDMI and gNDVI, lower soil temperature, and larger soil aggregate cross-sectional area, in particular when compared to bare soil. After a rain and in full sun, C. latifolia transpiration spiked in bare soil but not in A. pintoi cover cropped plots. Zero C. latifolia trees died from drought in full-sun, cover-cropped plots. Similarly, zero died in shaded, bare-soil plots. In contrast, 6 (of 27) trees in full-sun, bare-soil conditions died. Conclusions: A. pintoi appears to maintain soil conditions that are conducive to C. latifolia survival during the dry season. The effect appears to be mostly due to shading, as cover cropping becomes dispensable under partial tree shade. Remote sensing detected treatment effects despite small experimental plot sizes. The higher post-rain leaf transpiration suggests C. latifolia may contribute to soil drying in bare soil. Higher vegetation index and soil aggregation suggest cover cropping may provide additional long term benefits in soil carbon sequestration. Agroforestry remote sensing cover crop mycorrhizal inoculant drought survival. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction The Cumulative Water Deficit is deteriorating throughout tropical rainforests on all three continents where it was observed in 26 years of historical C-band radar (which penetrates clouds but only partially penetrates canopies) images from multiple satellite sources (Tao et al., 2022 ). This makes drought a serious threat to agriculture in the wet tropics;(Merga and Beksisa, 2023 ) it reduces Persian lime ( C. latifolia ) weight (Rivera-Hernández et al., 2022 ) and directly contributes to increasing coffee ( C. arabica ) prices (Massrie, 2025 ). Intense solar radiation and lack of canopy cover can result in large fluctuations in soil temperature. (Jarrah et al. 2022 ) Soil temperature fluctuations critically influence root growth. High soil temperature depletes soil nitrogen (by mineralization) and carbon (by increasing microbial respiration and reducing microbial biomass) (Tian et al. 2023 ). Understanding how to modulate soil thermal environments has become essential for designing resilient production systems under accelerating climate variability. Cover crops modify the the soil–atmosphere interface through shading, increased albedo, reduced wind speed, and greater incorporation of organic residues, thereby reducing daily maximum temperatures, mitigating evaporative losses, improving soil porosity and water infiltration (Akchaya et al. 2025 ), and stabilizing soil moisture (Al-Shammary et al. 2025 ). C. latifolia can be intercropped with C. arabica due to compatible interrow distances; this combination has not been earlier reported. Shade trees increase drought survival of C. arabica (Massrie, 2025 ) while also increasing biodiversity and yielding a second crop. The three-species C. latifolia - C. arabica - A. pintoi system has reasons to provide improved drought and economic resilience as well as ecosystem services (Merga and Beksisa, 2023 ; Tao et al., 2022 ). Environmental benefit of Coffea arabica C. arabica performs many services to the ecosystem and to its intercrops. At higher planting densities (similar to those of this work), C. arabica can increase storage of carbon and nutrients. Soil carbon sequestration has been found to be negative at low tree densities (under 700 trees/ha) (Noponen et al., 2013 ). However if litter and above-ground carbon is considered, coffee can store around 40 t C/ha, per measurements in Ethiopian agroforestry systems (Niguse et al., 2022 ). Globally over 10 Mha are under coffee cultivation, arguing for a significant carbon storage potential. Intercropping with C. arabica increases fruit productivity of Macadamia integrifolia , as well as growth of mahogany and rubber trees. This effect has been attributed to the favorable microclimate under the C. arabica , including increased nutrients and soil shading, (Perdoná and Soratto, 2015 ) presumably better conserving moisture. C. arabica can also decrease acidity and erosion in soil (Pavan et al., 1999 ). C. arabica intercropped with one additional species has more beneficial effects on soil carbon, microbial biomass and activity, and soil compaction, compared to a monoculture (de Carvalho et al., 2024 ; Pavan et al., 1999 ). In that work, a three-species intercrop (such as that performed here) was suggested for future study. The contribution of A. pintoi to soil moisture management, climate buffering, and soil physical resilience has not been fully elucidated in the context of tropical perennial agriculture. Benefits of Arachis pintoi Arachis pintoi is a perennial peanut variety widely used as an agricultural cover crop. It can lower soil temperature (Blanco-Canqui and Ruis, 2020 ) while increasing soil moisture, carbon, nitrogen, potassium, calcium, magnesium, sodium, electrical conductivity, and pH. It tolerates drought of about 13 weeks (by some measures). A. pintoi had a positive effect on the stem diameters of fruit trees intercropped with it, arguably more than could be obtained with chemical fertilizer (Dornelles et al., 2016 ). It conserved soil moisture better than four other cover crops, purportedly because as a perennial it maintains leaves across the seasons, and as its higher C/N ratio makes for slower degradation. It tolerates partial shade, and is thus suited to coffee plantations. A. pintoi has several useful qualities: 1. It is low growing (usually under 30cm) which means it never grows high enough to shade young trees. This also means mowing gives it an advantage over taller weeds. 2. It closes to form dense foliage, reducing soil evaporation by reducing solar radiation (Unger and Vigil, 1998 ) and wind velocity at the soil surface. 3. It has a tap root that can exceed 1m and so can access water in deep soil layers 4. It can endure many weeks of drought without loss of foliage. For all its advantages, there are many conditions for which A. pintoi is inappropriate. It may compete with some crops for water, dry soils due to transpiration, (Unger and Vigil, 1998 ) and so may be more suited for humid rather than semi-arid regions. The buried peanuts may attract rodents (Johns, 1994 ). It has slow growth, does not compete well with fast-growing grasses, and can be difficult to establish (Vidhya et al., 2024 ). It also had negative effects on banana fruit size (Johns, 1994 ). For maize it has been shown to reduce erosion and increase N, P, and organic C, but decrease corn yield (Sumiahadi et al., 10 2018). The prior literature makes no mention of the use of A. pintoi with C. latifolia or C. arabica . Sustainability of Persian lime production Hectares under Persian lime production in Veracruz have increased in recent years, driven by a high price in the US market. However the increase is not considered sustainable, due to increasingly variable temperature and precipitation. Increases in temperature and changes in precipitation have been particularly harmful to citrus (Valdés-Rodríguez et al., 2023 ) and are likely to continue intensifying in Veracruz, (Castillo-Martínez et al., 2022 ) as in other citrus growing regions. Another sustainability issue arises from the consumption of fertilizer, water, land, and labor (Castillo-Martínez et al., 2022 ). Thus it is urgent to make Persian lime production drought resistant and control its environmental impact. Intercropping often results in increased water use efficiency. Much of this is due to shading. Water redistribution has been observed, suggesting that shallow rooted trees like C. latifolia may benefit from intercropping with relatively deep rooted species such as C. arabica and A. Pintoi (Liu et al., 2025 ). Root systems of C. arabica, A. pintoi , and C. latifolia The roots of plants respond postembryonically to resources, soil hydrology and chemistry, plant spacing, pruning, etc. making it impossible to make strict statements. However root characteristics are clearly relevant to the success of an intercropping system. Here we summarize expert opinion on root depths of these three species and speculate as to how they may interact. C. arabica has roots up to 3m deep according to (Ferreira et al., 01 2019). Other authors report root depths of 80cm (Partelli et al., 2020 ). A. pintoi roots can grow to 1.2 m deep (Partelli et al., 2020 ; Tropical Grasslands, 1995 ). C. latifolia is widely considered to have shallow roots. In an irrigated orchard in Brazil, at least half of water extraction was found at soil depth between 0 and 375mm, and none below 875mm. At most 7% of root length was found at depths 875-1125mm (de la Mora, 2007 ). A separate Brazilian study found that (within rows of lime) by far most root area was in the top 250mm of soil, with no more than 10% of root area at depths of 750-1000mm (Neves et al., 2004 ). A well-developed root system may be important to the ecological benefits of C. arabica and/or A. pintoi . Glasshouse experiments have shown that Cajanus cajan (but not Sesbania sesban ) redistribute deuterated water to adjacent Zea mays plants through hydraulic lifting. It was further found that shading the Cajanus cajan increased the water redistribution (Sekiya and Yano, 2004 ). If this mechanism exists in the C. latifolia - C. arabica - A. pintoi system it is possible that as the C. latifolia grows and creates shade, the A. pintoi will provide it with more water which it and the C. arabica can access from deeper soil layers. Much apparently depends on the root associations that form between the three species. Soil aggregate sizes Arbuscular mycorrhizae, such as that which colonize C. latifolia, C. arabica, and A. pintoi , produce glomalin-related soil proteins that stabilize carbon, moisture, and soil aggregates (clods) (Rillig 2004 ). Soil aggregate sizes are an indicator of soil properties and health, and can change with land use. They are also related to soil type and content of fine roots and other remnants, and other soil microbial components. Cover crops can increase the proportion of larger-size aggregates, related to increased SOC.(Dai et al., 2024 ) Hypotheses We proposed that: H1 Plots cover-cropped with A. pintoi will have lower temperature and higher humidity. H2 The A. pintoi plots should have a higher rate of C. latifolia survival compared to bare soil. Method & Results We planted C. latifolia (with sour orange rootstock)(Franco Valderrama et al., 2021 ) at 4m between trees and 5m between rows, starting 1/2024 (dates follow (DD/)MM/YYYY), resulting in a density of 500 trees/ha. Between rows of C. latifolia , we planted double-rows of C. arabica , Marsellesa variety, at 1.5m x 1.5m, starting in 7/2024. The overall density of coffee was 2667 trees/ha. Starting in 7/2024, the we planted A. pintoi in a 0.3x0.3m grid. The A. pintoi fully closed by 5/2025. During this period the plots were rainfed. We divided the farm into experimental plots to test elements of the system, shown in Fig. 1 and Fig. 2 . The reference system was implemented in plot 1A. Plot 6 was the last to be planted, and this was done near the start of winter when germination becomes difficult; as a result this plot has a mix of A. pintoi and weeds. Most plots were too small to monitor by remote sensing, so we created groupings in Table 1 . Table 1 Treatment groups for remote sensing. Plots other than 7,8 were too small to be analyzed separately. Heterogeneity refers to minor differences within the treatment group, see text. There is a large boulder in plots 1C,1D which may influence remote sensing results, so we excluded those plots from ARA. Remote sensing measurements were relative to MAIZE in order to compensate differences in scene brightness. Acronym Plots Main treatment. (Remote sensing area, m 2 ) Heterogeneity ARA 1A,1B, 2,3 A. pintoi cover cropped. (1190 m 2 ) Plot 3 has C. latifolia but no C.arabica. Plots 2,3 have no mycorrhizal inoculant. Plot 1B was amended with anthill soil when planting C. arabica . BSU 4,5 Bare soil, unshaded (400 m 2 ) Plot 4 has C. arabica planted with no mycorrhizal inoculant. BSSh 1 Bare soil, partial tree shade None MIX 6 A. pintoi and native weeds None WEEDS 7 Native weed cover (8100 m 2 ) None MAIZE 8 Maize (7100 m 2 ) None C. latifolia leaf transpiration We used an SC-1 leaf porometer (Meter Group, Munich, Germany) to measure C. latifolia stomatal conductance. The goal was to compare the treatments, so for strongest signal we chose one dark, healthy leaf, growing as close to the ground as possible, from each tree. Dessicator beads were changed after every 10 measurements. Soil aggregate size measurement Soil samples were taken along the sample line, bagged, and marked with the collection location. The samples were then spread out and allowed to dry on white office paper. They were then photographed along with a ruler. We measured the size of the aggregates using ImageJ software, and recorded along with the sample’s site of collection and treatment. The ImageJ processing was similar to that of (J. Kumara, 2012 ). We used the ruler in the image to set the scale. We converted the images to binary, and finally computed the area of each aggregate. Transient effect of A. pintoi and mycorrhizal inoculant on C. arabica in autumn after planting In the autumn after planting, the C. arabica under + COVER/+INOC treatment had good (dark, green) leaf color and its typical shiny cuticle. -COVER/+INOC showed leaf yellowing, suggesting that A. pintoi provided nitrogen as desired. C. arabica under + COVER/-INOC had dull leaf cuticle (Fig. 3 , 16/10/2024 panel). The effect disappeared over the winter (Fig. 3 , 14/01/2025 panel), to the point that the staff evaluated the -COVER condition as better for plant health. The conditions shown in the 16/10/2024 panel did not return in 10/2025. C. arabica infection and change in A. pintoi management Two problems arose during A. pintoi establishment, we here present their corrective action. First, the trees appeared to be growing faster and have better leaf color in the WEEDS plot, compared to ARA, which we ascribed to competition between C. arabica and A. pintoi , rather than the desired fixation of soil nitrogen by the latter. Second, we observed a (possibly fungal) discolored growth on the stalks and leaves of the coffee trees. We attributed this to excess moisture due to shading by the A. pintoi. To address both, we: 1. mowed the A. pintoi . 2. edged around the trees (Figure G). After these two interventions the discoloration on stalks and leaves disappeared (Fig. 4 .B,C). We ascribed this to a reduction in moisture. We also noted an improvement in C. arabica leaf color. The A. pintoi was in flower at the time, so the mowing should have interrupted the fruiting process. The mowing litter was left in place to provide fertilizer – popularly called “chop-and-drop.” A. pintoi looks brown after mowing, but regrows within 2 weeks. Cover cropping and soil temperature In unshaded conditions, ARA soil is 4.5°C cooler than BSU, with high statistical significance. BSSh was shaded by trees, and had a similar temperature to ARA (Fig. 5 ). Thus A. pintoi reduces soil temperature, and the effect is due to shading. When we took soil samples from BSU, moisture from the soil condensed on the inner wall of the 50mL falcon tubes, suggesting high soil evaporation. This higher temperature was palpable to us while taking measurements. C. latifolia leaf transpiration On 03/05/2025, one day after a rain broke otherwise dry conditions [Figure 6 ], we took leaf porometer measurements on C. latifolia trees along the blue line in Fig. 1 . We detected a greater leaf transpiration in the BSU compared to the plots [Figure 7 ]. C. latifolia drought survival BSU was planted with 27 C. latifolia trees of which 6 died (Fig. 1 ). Plots 2 and 3 were planted with 30 and 1A,B with 75 trees; of these 105 trees (comprising ARA), 1 died (row 3 tree 1, felled by wind). If we apply the cumulative hypergeometric distribution, with a population of 105 including 7 successes, sample of 28, and 6 successes in the sample, we obtain a significance of p = .001. C. arabica tree deaths were not counted, but we noted that those in BSU had high drought-related mortality as well. Some C. arabica seedlings also died in ARA, apparently from competition with A. pintoi. , albeit at lower rates. Soil moisture and vegetation index by remote sensing Soil moisture was measured by NDMI (Normalized Difference Moisture Index). NDMI is computed from Sentinel2 multispectral images, namely the NIR (Near Infrared, at 10m resolution) and SWIR (Short Wave Infrared, 20m resolution) bands. It is correlated with surface moisture content. GNDVI (Green Normalized Difference Vegetation Index) is computed from the NIR and green (visual, 10m resolution) bands. GNDVI is correlated with chlorophyll content. The effect of the cover crop on NDMI and GNDVI was most significant in the DS (dry season). During this period we noticed a drying out of the soil which soon led to a die-off of several lime (Fig. 1 ) and coffee trees in BSU. The DS traditionally runs March-June (de la Mora, 2007 ). For our remote sensing measurements, we considered the DS to run 1 March to 30 June. In 2025 the DS arguably ended by 15 June [Figure 6 ], however changing the end of the DS did not change the conclusions. BSU had no A. pintoi , and conscientious mowing had made the weeds too weak to survive the conditions as the 2025 DS started, so these dried out leaving bare soil. During the 2025 DS, NDMI was lower in BSU than in ARA. In the 2024 DS (before the A. pintoi was established) there was no significant difference in NDMI between these two areas. An overhead view of BSU, ARA, MAIZE, and WEEDS is shown in Fig. 8 . A) Red trace: temperature, 10-day rolling average. Thin blue bars: precipitation. Both from visualcrossing.com. Grey boxes: cloudy days (no GNDVI or NDMI measurement), detected by average RGB intensity > 1650. The DS is indicated with horizontal black bars. B) GNDVI for ARA (A. pintoi), BSU (bare soil), and WEEDS, relative to the MAIZE plot. Vertical error bars reflect ± 1 standard deviation. Quantities are averaged over the DS, indicated with pink vertical bars. In 2025, ARA has higher GNDVI than BSU (p = .009, by z-test), or MAIZE (p = .0009). For the difference between ARA and WEEDS, p = 0.07. ARA GNDVI is higher in 2025 (when the plot had established A. pintoi ) than 2024 (when it was bare soil, p = 0.02) and in 2023 (when it had maize, p = 0.03). C) ARA has higher NDMI than BSU (p = .03). Effect of A. pintoi on soil aggregate size The photos of soil samples were separated into four groups, +/-COVER and +/-INOC. INOC did not appear to have an effect on the aggregate area distribution, but as the mycorrhiza was only applied to the C. arabica roots , we further subdivided the + COVER/+INOC based on where the sample was taken (under a C. latifolia vs under a C. arabica tree), however this was not discernibly different from the overall + COVER/+INOC (data not shown). The A. pintoi cover crop, however, did have a significant effect on the aggregate size distribution (Fig. 10 ). Discussion The goal of this work was to evaluate the drought protective effect of A. pintoi on C. latifolia . There were zero C. latifolia tree deaths due to drought in the A. pintoi cover cropped plots, whereas the bare-soil plots had a significant fraction of trees die. The full-sun, A. pintoi plots (ARA) had soil temperature 4.5°C cooler than the ASU. There was also significantly higher NDMI, a remote measurement of moisture, in ARA than in BSU in 2025 (Fig. 9 ). This appears to be primarily due to soil shading by the dense A. pintoi canopy, as the tree-shaded, bare-soil (BSSh) plots had temperature indistinguishable from that of ARA. However we do not rule out hydraulic lifting as a contributing factor.(Sekiya and Yano, 2004 ) GNDVI, a measure of chlorophyll, was higher for ARA than BSU in 2025 (Fig. 9 ). The GNDVI was also higher for ARA in 2025 (when the A. pintoi had closed) than for ARA in 2024 (when there was no A. pintoi ) or 2023 (when there was maize). Thus A. pintoi cover cropping leads to more photosynthesis per ha. Photosynthesis leads to production of plant biomass, and also produces carbohydrates that can be traded with mycorrhiza for nutrients, leading to increased soil microbial biomass. All of this may ultimately increase soil carbon. Indeed the A. pintoi is affecting soil properties, namely the distribution of soil aggregate sizes is wider (more aggregates in the > 100mm 2 size range, Fig. 10 ). Cover crop roots and organic matter can affect the distribution of size of soil pores (Al-Shammary et al. 2025 ). Mycorrhizae such those associated with A. pintoi increase aggregate stability (Rillig 2004 ). On the other hand INOC, the mycorrhizal inoculant treatment, had no clear effect on soil aggregate size distribution. Since the +/-INOC samples were taken from different locations, these had the effect of validating our conclusions regarding the soil aggregate size distribution in relation to A. pintoi . INOC did appear to give the C. arabica its expected waxy sheen in the autumn after planting, without it the leaves took on a matte finish. The difference in finish disappeared soon after (Fig. 3 ). As mentioned, INOC had no clear effect on soil aggregate sizes a year after planting. This could be related to the experimental fields’ history, as a once-mature C. arabica plantation, with soil still in good condition. The mycorrhizal inoculant similarly has its origin in mature C. arabica plantations. It could be that in good C. arabica plantation soils, the inoculant has only a short-term effect, after which the existing soil microbiome outcompetes the inoculant. C. latifolia in BSU had higher post-rain leaf transpiration than that in ARA. The soil was still wet but the canopy and air were dry. The BSU trees were already suffering from earlier water stress, and the warmer (compared to ARA) soil may have led the trees to use transpiration to cool their leaves. Faster soil drying is a clear risk of this strategy. Although this work is about drought survival, the test system and method have consequences well beyond that. This is the first report of a C. latifolia / C. arabica intercropping system. It is also the first report of A. pintoi as a cover crop with either of these trees. This remote sensing results show that for sufficiently strong signals and appropriate references (here all measurements were relative to MAIZE) and time-averaging (over the entire DS), moisture and vegetation can be measured for small plots previously considered too small for Sentinel2 (Novák and Křížová, 2020 ). In conclusion, the A. pintoi cover crop had a strong effect on soil moisture (by remote sensing), temperature (measured on-site), and structure, compared to bare soil in full sun. As a result, 100% of C. latifolia survived the DS in the former. Bare soil in shade had similarly good results in soil temperature and tree condition, indicating that shading provides a similar protective effect. We conclude that A. pintoi does indeed provide drought protection for young trees, and the effect is likely due mainly to soil shading. Differences in vegetation index and soil structure suggest future benefits in soil carbon sequestration. Abbreviations NDMI Normalized Difference Moisture Index NDVI Normalized Difference Vegetation Index SOC Soil Organic Carbon A. pintoi Arachis pintoi C. latifolia Citrus latifolia C. arabica Coffea arabica Declarations Funding and other support We gratefully acknowledge advice and a gift of 4000 C. arabica seedlings from Henrik Öhman, Exportadora de Cafe California, and the Starbucks 100 million trees initiative. Flores is supported by the Swedish University of Agricultural Sciences and the Swedish Research Council grant VR-M 2016-06301, The National Graduate School in Medical Bioinformatics (MedBioInfo). Availability Code is available at github.com/samuelflores/earth-observation . Competing interests S. Flores intends to sell coffee and lime grown on the experimental plots. D. Trejo sells mycorrhizal inoculant through Universidad Veracruzana. Author contributions D. Trejo suggested the use of A. pintoi and her mycorrhizal inoculant. J. 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Proc Natl Acad Sci U S A 119:e2116626119 Tropical, Grasslands (1995) Unger PW, Vigil MF (1998) Cover crop effects on soil water relationships. J Soil Water Conserv 53:200–207 Valdés-Rodríguez OA, Salas-Martínez F, Palacios-Wassenaar OM (2023) Hydrometeorological hazards on crop production in the State of Veracruz, Mexico. Atmos (Basel) 14:287 Vidhya V, Jyothibabu R, Alok KT, Rashid CP, Arunpandi N, Devi CRA, Gupta GVM, Thirumurugan R (2024) Ecophysiological status of copepods in the oxygen minimum zone of Eastern Arabian Sea. Mar Pollut Bull 211:117370 Akchaya K, Parasuraman P, Pandian K et al (2025) Boosting resource use efficiency, soil fertility, food security, ecosystem services, and climate resilience with legume intercropping: a review. Front Sustain Food Syst 9. https://doi.org/10.3389/fsufs.2025.1527256 Al-Shammary AAG, Al-Shihmani LSS, Fernández-Gálvez J, Caballero-Calvo A (2025) A comprehensive review of impacts of soil management practices and climate adaptation strategies on soil thermal conductivity in agricultural soils. Rev Environ Sci Biotechnol 24:513–543 Jarrah M, Mayel S, Franko U, Kuka K (2022) Effects of agricultural management practices on the temporal variability of soil temperature under different crop rotations in Bad Lauchstaedt-Germany. Agron (Basel) 12:1199 Rillig MC (2004) Arbuscular mycorrhizae, glomalin, and soil aggregation. Can J Soil Sci 84:355–363 Tian Y, Schindlbacher A, Malo CU et al (2023) Long-term warming of a forest soil reduces microbial biomass and its carbon and nitrogen use efficiencies. Soil Biol Biochem 184:109109 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8431754","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580990655,"identity":"a06a39b5-cd6f-41af-8eab-e3db73a9b1ef","order_by":0,"name":"Samuel Coulbourn Flores","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYNCCAgZ+PjCjgkGGSC0GDJJtYMYZBh4StTC2EaFFvv10msQHAwYJNvbehw9/zqvjMTjA/vABXvPP5G6TnAHSwnPc2Jh322GgFh5jA/xOyt0mzWPAUMcmkcYmzbjtAEgLmwReh/W/3Sb9B2SLRBr7z59zwA57/gOvZ24AbWGAaGFj4G1gBmphMMOrw+DG282WPQYSQL8cY5bmOXaYR/IwjzEBh+VuvPGjwkaCn72N8eOPmjo5vuPtDz/gtQYCkI1lJkL9KBgFo2AUjAL8AADjTDzxWLWp3AAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-3869-8147","institution":"Swedish University of Agricultural Science Faculty of Veterinary Medicine and Animal Science: Sveriges Lantbruksuniversitet Veterinarmedicin och husdjursvetenskap","correspondingAuthor":true,"prefix":"","firstName":"Samuel","middleName":"Coulbourn","lastName":"Flores","suffix":""},{"id":580990656,"identity":"08ff16f6-2c12-4fce-9bed-86ac1a47dde3","order_by":1,"name":"Dora Trejo Aguilar","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Dora","middleName":"Trejo","lastName":"Aguilar","suffix":""},{"id":580990657,"identity":"41937333-fa68-45aa-8cc2-3946afff5b2e","order_by":2,"name":"Jacob Bañuelos","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jacob","middleName":"","lastName":"Bañuelos","suffix":""}],"badges":[],"createdAt":"2025-12-23 08:18:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8431754/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8431754/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101459745,"identity":"6f0ea089-1e7c-4eb8-a729-20139e05f87f","added_by":"auto","created_at":"2026-01-30 01:31:37","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":71869,"visible":true,"origin":"","legend":"\u003cp\u003ePlanting map of plots 1-6. Boundaries shown by red dashed lines. CAF = coffee trees planted in alleys between rows of lime (as opposed to empty alleys). INOC = mycorrhizal and bacterial inoculant added to coffee seedlings prior to planting. COV = \u003cem\u003eA. pintoi\u003c/em\u003e planted as a cover crop. Green ovals: \u003cem\u003eC. latifolia\u003c/em\u003e trees. Red X: dead lime trees. Pink circles: \u003cem\u003eC. arabica\u003c/em\u003e trees. Horizontal numbers: \u003cem\u003eC. latifolia\u003c/em\u003e row numbers. Vertical green numbers: \u003cem\u003eC. latifolia\u003c/em\u003e tree numbers. “Water” indicates location of spring-fed water tank. Measurements were made of leaves and soil along the blue dashed line. Blue line condition is sunny except for plot 1.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/caa4469cff422ac8e364fc18.jpeg"},{"id":101459748,"identity":"77c1a94e-0aa2-48bb-abc3-960e0f8a3e3f","added_by":"auto","created_at":"2026-01-30 01:31:37","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1928790,"visible":true,"origin":"","legend":"\u003cp\u003ePanorama view looking south. Plot numbers in red. Note bare soil in plots 1, 4, 5.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/2a2764cb58e22314ce7fde19.jpeg"},{"id":101459746,"identity":"f7bc132f-f169-46f0-81f2-151f3a99e1fd","added_by":"auto","created_at":"2026-01-30 01:31:37","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":499976,"visible":true,"origin":"","legend":"\u003cp\u003eTransient effect of A. pintoi and mycorrhizal inoculant on C. arabica. Upper panels: Note leaf yellowing in -COVER/+INOC, and dull\u003cem\u003e \u003c/em\u003eleaf cuticle in +COVER/-INOC. Lower panels: -COVER/+INOC color and +COVER/-INOC cuticle luster improved greatly over winter.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/03a5fa8e6a1c54d6f0a514bf.jpeg"},{"id":101459750,"identity":"fc236807-6820-4a55-9a09-8c7a6595c93d","added_by":"auto","created_at":"2026-01-30 01:31:37","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":503244,"visible":true,"origin":"","legend":"\u003cp\u003eArachis pintoi management. A: \u003cem\u003eC. arabica\u003c/em\u003eseedling showing unidentified infection growing on stem, as well as poor leaf coloration, 3-7-2025. \u003cem\u003eA. pintoi \u003c/em\u003eis shown surrounding the \u003cem\u003eC. arabica. \u003c/em\u003eB: Edging around \u003cem\u003eC. arabica\u003c/em\u003e, 06/08/2025 . Note fully closed \u003cem\u003eA. pintoi\u003c/em\u003emat, and improved leaf color on \u003cem\u003eC. arabica\u003c/em\u003e. C: After mowing, 01/10/2025. Mown litter is left on ground, and \u003cem\u003eA. pintoi\u003c/em\u003e later regrows.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/be47cf35a742ece39074d9dc.jpeg"},{"id":101752091,"identity":"b8d86150-03d7-4a98-b02c-6fe311d2df44","added_by":"auto","created_at":"2026-02-03 10:25:17","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":123901,"visible":true,"origin":"","legend":"\u003cp\u003eSoil surface temperature. The difference between ARA and BSU soil temperature is significant (p=0.0009, by two-sample unpaired Student’s t with unequal variances, t = -8.5). Ambient temperature (2-5-2025) was minimum 17.2, average 21.5, and maximum 26.4°C.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/662f2f1a09aba56fb0861bcb.jpeg"},{"id":101459743,"identity":"a4e9f699-dd4e-4784-8222-f9115f366013","added_by":"auto","created_at":"2026-01-30 01:31:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":277695,"visible":true,"origin":"","legend":"\u003cp\u003eRainfall and temperature at experiment site, including leaf porometer measurement date and end of DS. Red trace indicates mean, shaded red area indicates day’s minimum to maximum temperature range. Data from visualcrossing.com. 35mm rain fell on 03/05/2025, one day before our leaf porometer measurements of 04/05/2025. This was preceded by 10 days of little rain. DS appears to end by 15/07/2025.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/9a051310c180904b388a2d35.png"},{"id":101752370,"identity":"26f6054c-c389-4f8a-8b32-4636782dc146","added_by":"auto","created_at":"2026-02-03 10:27:05","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":131154,"visible":true,"origin":"","legend":"\u003cp\u003eFoliar transpiration on \u003cem\u003eC. latifolia\u003c/em\u003e, 1 day post-rain. Measured on 04/05/2025 . Red dots: individual measurements. BSU and ARA have significantly different mean transpiration (Two-sample unpaired Student’s t with unequal variances, t = -4.3, p=0.003). The BSSh tree is row 1 tree 0, transpiration reading 80.8 mmol/m/m/s.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/bde1bcf0f7d4fdbefb17d3b1.jpeg"},{"id":101459752,"identity":"c9ebad85-429c-4cb2-a5ad-85ec8a748739","added_by":"auto","created_at":"2026-01-30 01:31:37","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":197217,"visible":true,"origin":"","legend":"\u003cp\u003eTreatment groups for remote sensing. Image from ESRI, plots marked using GeoDataFrames (GDFs) and LeafMap. WEEDS plot marked onsite using a GPS cellphone. ARA and BSU mapped using a combination of GPS and the planting map of Figure 1. MAIZE GDF placed using ESRI image only.\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/bd76b1f3a190146987ce03a9.jpeg"},{"id":101459751,"identity":"fbf8cdbf-caa7-4305-b9c5-a0edc6571794","added_by":"auto","created_at":"2026-01-30 01:31:37","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":766406,"visible":true,"origin":"","legend":"\u003cp\u003eWeather, GNDVI, and NDMI over three treatments, against MAIZE as a reference.\u003c/p\u003e\n\u003cp\u003eA) Red trace: temperature, 10-day rolling average. Thin blue bars: precipitation. Both from visualcrossing.com. Grey boxes: cloudy days (no GNDVI or NDMI measurement), detected by average RGB intensity \u0026gt; 1650. The DS is indicated with horizontal black bars.\u003c/p\u003e\n\u003cp\u003eB) GNDVI for ARA (A. pintoi), BSU (bare soil), and WEEDS, relative to the MAIZE plot. Vertical error bars reflect ±1 standard deviation. \u0026nbsp;Quantities are averaged over the DS, indicated with pink vertical bars. In 2025, ARA has higher GNDVI than BSU (p=.009, by z-test), or MAIZE (p=.0009). For the difference between ARA and WEEDS, p=0.07. ARA GNDVI is higher in 2025 (when the plot had established \u003cem\u003eA. pintoi\u003c/em\u003e) than 2024 (when it was bare soil, p=0.02) and in 2023 (when it had maize, p=0.03).\u003c/p\u003e\n\u003cp\u003eC) ARA has higher NDMI than BSU (p=.03).\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/0cb24dc6f8cd81c3769a482c.jpeg"},{"id":101751759,"identity":"cf1b6b74-8186-4675-83f4-e24180ba0ad8","added_by":"auto","created_at":"2026-02-03 10:23:13","extension":"jpeg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":113007,"visible":true,"origin":"","legend":"\u003cp\u003eHistogram of soil aggregate area (measured from photographs of soil samples) under four treatments. Bin size is 10 mm\u003csup\u003e2\u003c/sup\u003e. Sample size n refers to the number of aggregates detected in the photographs.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/f574cd42327a05fa01952adb.jpeg"},{"id":109324977,"identity":"a00498d4-7997-4c89-887a-bc561e992a8e","added_by":"auto","created_at":"2026-05-15 14:33:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4882514,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8431754/v1/feea7ebe-d0b6-4e95-a50e-d00ccd09541f.pdf"}],"financialInterests":"","formattedTitle":"Arachis pintoi cover cropping increases drought survival of Citrus latifolia in an intercrop with Coffea arabica","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Cumulative Water Deficit is deteriorating throughout tropical rainforests on all three continents where it was observed in 26 years of historical C-band radar (which penetrates clouds but only partially penetrates canopies) images from multiple satellite sources (Tao et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This makes drought a serious threat to agriculture in the wet tropics;(Merga and Beksisa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) it reduces Persian lime (\u003cem\u003eC. latifolia\u003c/em\u003e) weight (Rivera-Hern\u0026aacute;ndez et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and directly contributes to increasing coffee (\u003cem\u003eC. arabica\u003c/em\u003e) prices (Massrie, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIntense solar radiation and lack of canopy cover can result in large fluctuations in soil temperature. (Jarrah et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) Soil temperature fluctuations critically influence root growth. High soil temperature depletes soil nitrogen (by mineralization) and carbon (by increasing microbial respiration and reducing microbial biomass) (Tian et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Understanding how to modulate soil thermal environments has become essential for designing resilient production systems under accelerating climate variability. Cover crops modify the the soil\u0026ndash;atmosphere interface through shading, increased albedo, reduced wind speed, and greater incorporation of organic residues, thereby reducing daily maximum temperatures, mitigating evaporative losses, improving soil porosity and water infiltration (Akchaya et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and stabilizing soil moisture (Al-Shammary et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. latifolia\u003c/em\u003e can be intercropped with \u003cem\u003eC. arabica\u003c/em\u003e due to compatible interrow distances; this combination has not been earlier reported. Shade trees increase drought survival of \u003cem\u003eC. arabica\u003c/em\u003e (Massrie, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) while also increasing biodiversity and yielding a second crop. The three-species \u003cem\u003eC. latifolia - C. arabica - A. pintoi\u003c/em\u003e system has reasons to provide improved drought and economic resilience as well as ecosystem services (Merga and Beksisa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tao et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEnvironmental benefit of \u003cem\u003eCoffea arabica\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. arabica\u003c/em\u003e performs many services to the ecosystem and to its intercrops. At higher planting densities (similar to those of this work), \u003cem\u003eC. arabica\u003c/em\u003e can increase storage of carbon and nutrients. Soil carbon sequestration has been found to be negative at low tree densities (under 700 trees/ha) (Noponen et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However if litter and above-ground carbon is considered, coffee can store around 40 t C/ha, per measurements in Ethiopian agroforestry systems (Niguse et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Globally over 10 Mha are under coffee cultivation, arguing for a significant carbon storage potential.\u003c/p\u003e \u003cp\u003eIntercropping with \u003cem\u003eC. arabica\u003c/em\u003e increases fruit productivity of \u003cem\u003eMacadamia integrifolia\u003c/em\u003e, as well as growth of mahogany and rubber trees. This effect has been attributed to the favorable microclimate under the \u003cem\u003eC. arabica\u003c/em\u003e, including increased nutrients and soil shading, (Perdon\u0026aacute; and Soratto, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) presumably better conserving moisture. \u003cem\u003eC. arabica\u003c/em\u003e can also decrease acidity and erosion in soil (Pavan et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. arabica\u003c/em\u003e intercropped with one additional species has more beneficial effects on soil carbon, microbial biomass and activity, and soil compaction, compared to a monoculture (de Carvalho et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pavan et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). In that work, a three-species intercrop (such as that performed here) was suggested for future study. The contribution of \u003cem\u003eA. pintoi\u003c/em\u003e to soil moisture management, climate buffering, and soil physical resilience has not been fully elucidated in the context of tropical perennial agriculture.\u003c/p\u003e \u003cp\u003eBenefits of \u003cem\u003eArachis pintoi\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eArachis pintoi\u003c/em\u003e is a perennial peanut variety widely used as an agricultural cover crop. It can lower soil temperature (Blanco-Canqui and Ruis, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) while increasing soil moisture, carbon, nitrogen, potassium, calcium, magnesium, sodium, electrical conductivity, and pH. It tolerates drought of about 13 weeks (by some measures). \u003cem\u003eA. pintoi\u003c/em\u003e had a positive effect on the stem diameters of fruit trees intercropped with it, arguably more than could be obtained with chemical fertilizer (Dornelles et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). It conserved soil moisture better than four other cover crops, purportedly because as a perennial it maintains leaves across the seasons, and as its higher C/N ratio makes for slower degradation. It tolerates partial shade, and is thus suited to coffee plantations. \u003cem\u003eA. pintoi\u003c/em\u003e has several useful qualities:\u003c/p\u003e \u003cp\u003e1. It is low growing (usually under 30cm) which means it never grows high enough to shade young trees. This also means mowing gives it an advantage over taller weeds.\u003c/p\u003e \u003cp\u003e2. It closes to form dense foliage, reducing soil evaporation by reducing solar radiation (Unger and Vigil, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) and wind velocity at the soil surface.\u003c/p\u003e \u003cp\u003e3. It has a tap root that can exceed 1m and so can access water in deep soil layers\u003c/p\u003e \u003cp\u003e4. It can endure many weeks of drought without loss of foliage.\u003c/p\u003e \u003cp\u003eFor all its advantages, there are many conditions for which \u003cem\u003eA. pintoi\u003c/em\u003e is inappropriate. It may compete with some crops for water, dry soils due to transpiration, (Unger and Vigil, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) and so may be more suited for humid rather than semi-arid regions. The buried peanuts may attract rodents (Johns, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). It has slow growth, does not compete well with fast-growing grasses, and can be difficult to establish (Vidhya et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It also had negative effects on banana fruit size (Johns, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). For maize it has been shown to reduce erosion and increase N, P, and organic C, but decrease corn yield (Sumiahadi et al., 10 2018). The prior literature makes no mention of the use of \u003cem\u003eA. pintoi\u003c/em\u003e with \u003cem\u003eC. latifolia\u003c/em\u003e or \u003cem\u003eC. arabica\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eSustainability of Persian lime production\u003c/p\u003e \u003cp\u003eHectares under Persian lime production in Veracruz have increased in recent years, driven by a high price in the US market. However the increase is not considered sustainable, due to increasingly variable temperature and precipitation. Increases in temperature and changes in precipitation have been particularly harmful to citrus (Vald\u0026eacute;s-Rodr\u0026iacute;guez et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and are likely to continue intensifying in Veracruz, (Castillo-Mart\u0026iacute;nez et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) as in other citrus growing regions. Another sustainability issue arises from the consumption of fertilizer, water, land, and labor (Castillo-Mart\u0026iacute;nez et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus it is urgent to make Persian lime production drought resistant and control its environmental impact.\u003c/p\u003e \u003cp\u003eIntercropping often results in increased water use efficiency. Much of this is due to shading. Water redistribution has been observed, suggesting that shallow rooted trees like \u003cem\u003eC. latifolia\u003c/em\u003e may benefit from intercropping with relatively deep rooted species such as \u003cem\u003eC. arabica\u003c/em\u003e and \u003cem\u003eA. Pintoi\u003c/em\u003e (Liu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRoot systems of \u003cem\u003eC. arabica, A. pintoi\u003c/em\u003e, and \u003cem\u003eC. latifolia\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe roots of plants respond postembryonically to resources, soil hydrology and chemistry, plant spacing, pruning, etc. making it impossible to make strict statements. However root characteristics are clearly relevant to the success of an intercropping system. Here we summarize expert opinion on root depths of these three species and speculate as to how they may interact.\u003c/p\u003e \u003cp\u003e\u003cem\u003eC. arabica\u003c/em\u003e has roots up to 3m deep according to (Ferreira et al., 01 2019). Other authors report root depths of 80cm (Partelli et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). \u003cem\u003eA. pintoi\u003c/em\u003e roots can grow to 1.2 m deep (Partelli et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tropical Grasslands, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). \u003cem\u003eC. latifolia\u003c/em\u003e is widely considered to have shallow roots. In an irrigated orchard in Brazil, at least half of water extraction was found at soil depth between 0 and 375mm, and none below 875mm. At most 7% of root length was found at depths 875-1125mm (de la Mora, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). A separate Brazilian study found that (within rows of lime) by far most root area was in the top 250mm of soil, with no more than 10% of root area at depths of 750-1000mm (Neves et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA well-developed root system may be important to the ecological benefits of \u003cem\u003eC. arabica\u003c/em\u003e and/or \u003cem\u003eA. pintoi\u003c/em\u003e. Glasshouse experiments have shown that \u003cem\u003eCajanus cajan\u003c/em\u003e (but not \u003cem\u003eSesbania sesban\u003c/em\u003e) redistribute deuterated water to adjacent \u003cem\u003eZea mays\u003c/em\u003e plants through hydraulic lifting. It was further found that shading the \u003cem\u003eCajanus cajan\u003c/em\u003e increased the water redistribution (Sekiya and Yano, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). If this mechanism exists in the \u003cem\u003eC. latifolia - C. arabica - A. pintoi\u003c/em\u003e system it is possible that as the \u003cem\u003eC. latifolia\u003c/em\u003e grows and creates shade, the \u003cem\u003eA. pintoi\u003c/em\u003e will provide it with more water which it and the \u003cem\u003eC. arabica\u003c/em\u003e can access from deeper soil layers. Much apparently depends on the root associations that form between the three species.\u003c/p\u003e \u003cp\u003eSoil aggregate sizes\u003c/p\u003e \u003cp\u003eArbuscular mycorrhizae, such as that which colonize \u003cem\u003eC. latifolia, C. arabica, and A. pintoi\u003c/em\u003e, produce glomalin-related soil proteins that stabilize carbon, moisture, and soil aggregates (clods) (Rillig \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Soil aggregate sizes are an indicator of soil properties and health, and can change with land use. They are also related to soil type and content of fine roots and other remnants, and other soil microbial components. Cover crops can increase the proportion of larger-size aggregates, related to increased SOC.(Dai et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eHypotheses\u003c/p\u003e \u003cp\u003eWe proposed that:\u003c/p\u003e \u003cp\u003eH1 Plots cover-cropped with \u003cem\u003eA. pintoi\u003c/em\u003e will have lower temperature and higher humidity.\u003c/p\u003e \u003cp\u003eH2 The \u003cem\u003eA. pintoi\u003c/em\u003e plots should have a higher rate of \u003cem\u003eC. latifolia\u003c/em\u003e survival compared to bare soil.\u003c/p\u003e "},{"header":"Method \u0026 Results","content":"\u003cp\u003eWe planted \u003cem\u003eC. latifolia\u003c/em\u003e (with sour orange rootstock)(Franco Valderrama et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) at 4m between trees and 5m between rows, starting 1/2024 (dates follow (DD/)MM/YYYY), resulting in a density of 500 trees/ha. Between rows of \u003cem\u003eC. latifolia\u003c/em\u003e, we planted double-rows of \u003cem\u003eC. arabica\u003c/em\u003e, Marsellesa variety, at 1.5m x 1.5m, starting in 7/2024. The overall density of coffee was 2667 trees/ha. Starting in 7/2024, the we planted \u003cem\u003eA. pintoi\u003c/em\u003e in a 0.3x0.3m grid. The \u003cem\u003eA. pintoi\u003c/em\u003e fully closed by 5/2025. During this period the plots were rainfed.\u003c/p\u003e \u003cp\u003eWe divided the farm into experimental plots to test elements of the system, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The reference system was implemented in plot 1A. Plot 6 was the last to be planted, and this was done near the start of winter when germination becomes difficult; as a result this plot has a mix of \u003cem\u003eA. pintoi\u003c/em\u003e and weeds. Most plots were too small to monitor by remote sensing, so we created groupings in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \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\u003eTreatment groups for remote sensing. Plots other than 7,8 were too small to be analyzed separately. Heterogeneity refers to minor differences within the treatment group, see text. There is a large boulder in plots 1C,1D which may influence remote sensing results, so we excluded those plots from ARA. Remote sensing measurements were relative to MAIZE in order to compensate differences in scene brightness.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcronym\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlots\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMain treatment. (Remote sensing area, m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeterogeneity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1A,1B, 2,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eA. pintoi\u003c/em\u003e cover cropped. (1190 m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePlot 3 has \u003cem\u003eC. latifolia\u003c/em\u003e but no \u003cem\u003eC.arabica.\u003c/em\u003e Plots 2,3 have no mycorrhizal inoculant.\u003c/p\u003e \u003cp\u003ePlot 1B was amended with anthill soil when planting \u003cem\u003eC. arabica\u003c/em\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBare soil, unshaded (400 m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePlot 4 has \u003cem\u003eC. arabica\u003c/em\u003e planted with no mycorrhizal inoculant.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSSh\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\u003eBare soil, partial tree shade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMIX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eA. pintoi\u003c/em\u003e and native weeds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWEEDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNative weed cover (8100 m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMAIZE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaize (7100 m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eC. latifolia\u003c/em\u003e leaf transpiration\u003c/p\u003e \u003cp\u003eWe used an SC-1 leaf porometer (Meter Group, Munich, Germany) to measure \u003cem\u003eC. latifolia\u003c/em\u003e stomatal conductance. The goal was to compare the treatments, so for strongest signal we chose one dark, healthy leaf, growing as close to the ground as possible, from each tree. Dessicator beads were changed after every 10 measurements.\u003c/p\u003e \u003cp\u003eSoil aggregate size measurement\u003c/p\u003e \u003cp\u003eSoil samples were taken along the sample line, bagged, and marked with the collection location. The samples were then spread out and allowed to dry on white office paper. They were then photographed along with a ruler. We measured the size of the aggregates using ImageJ software, and recorded along with the sample\u0026rsquo;s site of collection and treatment. The ImageJ processing was similar to that of (J. Kumara, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). We used the ruler in the image to set the scale. We converted the images to binary, and finally computed the area of each aggregate.\u003c/p\u003e \u003cp\u003eTransient effect of \u003cem\u003eA. pintoi\u003c/em\u003e and mycorrhizal inoculant on \u003cem\u003eC. arabica\u003c/em\u003e in autumn after planting\u003c/p\u003e \u003cp\u003eIn the autumn after planting, the \u003cem\u003eC. arabica\u003c/em\u003e under +\u0026thinsp;COVER/+INOC treatment had good (dark, green) leaf color and its typical shiny cuticle. -COVER/+INOC showed leaf yellowing, suggesting that \u003cem\u003eA. pintoi\u003c/em\u003e provided nitrogen as desired. \u003cem\u003eC. arabica\u003c/em\u003e under +\u0026thinsp;COVER/-INOC had dull leaf cuticle (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, 16/10/2024 panel). The effect disappeared over the winter (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, 14/01/2025 panel), to the point that the staff evaluated the -COVER condition as better for plant health. The conditions shown in the 16/10/2024 panel did not return in 10/2025.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eC. arabica\u003c/em\u003e infection and change in \u003cem\u003eA. pintoi\u003c/em\u003e management\u003c/p\u003e \u003cp\u003eTwo problems arose during \u003cem\u003eA. pintoi\u003c/em\u003e establishment, we here present their corrective action. First, the trees appeared to be growing faster and have better leaf color in the WEEDS plot, compared to ARA, which we ascribed to competition between \u003cem\u003eC. arabica\u003c/em\u003e and \u003cem\u003eA. pintoi\u003c/em\u003e, rather than the desired fixation of soil nitrogen by the latter. Second, we observed a (possibly fungal) discolored growth on the stalks and leaves of the coffee trees. We attributed this to excess moisture due to shading by the \u003cem\u003eA. pintoi.\u003c/em\u003e To address both, we: 1. mowed the \u003cem\u003eA. pintoi\u003c/em\u003e. 2. edged around the trees (Figure G).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter these two interventions the discoloration on stalks and leaves disappeared (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.B,C). We ascribed this to a reduction in moisture. We also noted an improvement in \u003cem\u003eC. arabica\u003c/em\u003e leaf color. The \u003cem\u003eA. pintoi\u003c/em\u003e was in flower at the time, so the mowing should have interrupted the fruiting process. The mowing litter was left in place to provide fertilizer \u0026ndash; popularly called \u0026ldquo;chop-and-drop.\u0026rdquo; \u003cem\u003eA. pintoi\u003c/em\u003e looks brown after mowing, but regrows within 2 weeks.\u003c/p\u003e \u003cp\u003eCover cropping and soil temperature\u003c/p\u003e \u003cp\u003eIn unshaded conditions, ARA soil is 4.5\u0026deg;C cooler than BSU, with high statistical significance. BSSh was shaded by trees, and had a similar temperature to ARA (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Thus \u003cem\u003eA. pintoi\u003c/em\u003e reduces soil temperature, and the effect is due to shading. When we took soil samples from BSU, moisture from the soil condensed on the inner wall of the 50mL falcon tubes, suggesting high soil evaporation. This higher temperature was palpable to us while taking measurements.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eC. latifolia\u003c/em\u003e leaf transpiration\u003c/p\u003e \u003cp\u003eOn 03/05/2025, one day after a rain broke otherwise dry conditions [Figure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e], we took leaf porometer measurements on \u003cem\u003eC. latifolia\u003c/em\u003e trees along the blue line in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. We detected a greater leaf transpiration in the BSU compared to the plots [Figure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eC. latifolia\u003c/em\u003e drought survival\u003c/p\u003e \u003cp\u003eBSU was planted with 27 \u003cem\u003eC. latifolia\u003c/em\u003e trees of which 6 died (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Plots 2 and 3 were planted with 30 and 1A,B with 75 trees; of these 105 trees (comprising ARA), 1 died (row 3 tree 1, felled by wind). If we apply the cumulative hypergeometric distribution, with a population of 105 including 7 successes, sample of 28, and 6 successes in the sample, we obtain a significance of p\u0026thinsp;=\u0026thinsp;.001.\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. arabica\u003c/em\u003e tree deaths were not counted, but we noted that those in BSU had high drought-related mortality as well. Some \u003cem\u003eC. arabica\u003c/em\u003e seedlings also died in ARA, apparently from competition with \u003cem\u003eA. pintoi.\u003c/em\u003e, albeit at lower rates.\u003c/p\u003e \u003cp\u003eSoil moisture and vegetation index by remote sensing\u003c/p\u003e \u003cp\u003eSoil moisture was measured by NDMI (Normalized Difference Moisture Index). NDMI is computed from Sentinel2 multispectral images, namely the NIR (Near Infrared, at 10m resolution) and SWIR (Short Wave Infrared, 20m resolution) bands. It is correlated with surface moisture content. GNDVI (Green Normalized Difference Vegetation Index) is computed from the NIR and green (visual, 10m resolution) bands. GNDVI is correlated with chlorophyll content.\u003c/p\u003e \u003cp\u003eThe effect of the cover crop on NDMI and GNDVI was most significant in the DS (dry season). During this period we noticed a drying out of the soil which soon led to a die-off of several lime (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and coffee trees in BSU. The DS traditionally runs March-June (de la Mora, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). For our remote sensing measurements, we considered the DS to run 1 March to 30 June. In 2025 the DS arguably ended by 15 June [Figure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e], however changing the end of the DS did not change the conclusions.\u003c/p\u003e \u003cp\u003eBSU had no \u003cem\u003eA. pintoi\u003c/em\u003e, and conscientious mowing had made the weeds too weak to survive the conditions as the 2025 DS started, so these dried out leaving bare soil. During the 2025 DS, NDMI was lower in BSU than in ARA. In the 2024 DS (before the A. pintoi was established) there was no significant difference in NDMI between these two areas. An overhead view of BSU, ARA, MAIZE, and WEEDS is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA) Red trace: temperature, 10-day rolling average. Thin blue bars: precipitation. Both from visualcrossing.com. Grey boxes: cloudy days (no GNDVI or NDMI measurement), detected by average RGB intensity\u0026thinsp;\u0026gt;\u0026thinsp;1650. The DS is indicated with horizontal black bars.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eB) GNDVI for ARA (A. pintoi), BSU (bare soil), and WEEDS, relative to the MAIZE plot. Vertical error bars reflect\u0026thinsp;\u0026plusmn;\u0026thinsp;1 standard deviation. Quantities are averaged over the DS, indicated with pink vertical bars. In 2025, ARA has higher GNDVI than BSU (p\u0026thinsp;=\u0026thinsp;.009, by z-test), or MAIZE (p\u0026thinsp;=\u0026thinsp;.0009). For the difference between ARA and WEEDS, p\u0026thinsp;=\u0026thinsp;0.07. ARA GNDVI is higher in 2025 (when the plot had established \u003cem\u003eA. pintoi\u003c/em\u003e) than 2024 (when it was bare soil, p\u0026thinsp;=\u0026thinsp;0.02) and in 2023 (when it had maize, p\u0026thinsp;=\u0026thinsp;0.03).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eC) ARA has higher NDMI than BSU (p\u0026thinsp;=\u0026thinsp;.03).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eEffect of \u003cem\u003eA. pintoi\u003c/em\u003e on soil aggregate size\u003c/p\u003e \u003cp\u003eThe photos of soil samples were separated into four groups, +/-COVER and +/-INOC. INOC did not appear to have an effect on the aggregate area distribution, but as the mycorrhiza was only applied to the \u003cem\u003eC. arabica roots\u003c/em\u003e, we further subdivided the +\u0026thinsp;COVER/+INOC based on where the sample was taken (under a \u003cem\u003eC. latifolia\u003c/em\u003e vs under a \u003cem\u003eC. arabica\u003c/em\u003e tree), however this was not discernibly different from the overall\u0026thinsp;+\u0026thinsp;COVER/+INOC (data not shown). The \u003cem\u003eA. pintoi\u003c/em\u003e cover crop, however, did have a significant effect on the aggregate size distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe goal of this work was to evaluate the drought protective effect of \u003cem\u003eA. pintoi\u003c/em\u003e on \u003cem\u003eC. latifolia\u003c/em\u003e. There were zero \u003cem\u003eC. latifolia\u003c/em\u003e tree deaths due to drought in the \u003cem\u003eA. pintoi\u003c/em\u003e cover cropped plots, whereas the bare-soil plots had a significant fraction of trees die.\u003c/p\u003e \u003cp\u003eThe full-sun, \u003cem\u003eA. pintoi\u003c/em\u003e plots (ARA) had soil temperature 4.5\u0026deg;C cooler than the ASU. There was also significantly higher NDMI, a remote measurement of moisture, in ARA than in BSU in 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). This appears to be primarily due to soil shading by the dense \u003cem\u003eA. pintoi\u003c/em\u003e canopy, as the tree-shaded, bare-soil (BSSh) plots had temperature indistinguishable from that of ARA. However we do not rule out hydraulic lifting as a contributing factor.(Sekiya and Yano, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eGNDVI, a measure of chlorophyll, was higher for ARA than BSU in 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The GNDVI was also higher for ARA in 2025 (when the \u003cem\u003eA. pintoi\u003c/em\u003e had closed) than for ARA in 2024 (when there was no \u003cem\u003eA. pintoi\u003c/em\u003e) or 2023 (when there was maize). Thus \u003cem\u003eA. pintoi\u003c/em\u003e cover cropping leads to more photosynthesis per ha. Photosynthesis leads to production of plant biomass, and also produces carbohydrates that can be traded with mycorrhiza for nutrients, leading to increased soil microbial biomass. All of this may ultimately increase soil carbon.\u003c/p\u003e \u003cp\u003eIndeed the \u003cem\u003eA. pintoi\u003c/em\u003e is affecting soil properties, namely the distribution of soil aggregate sizes is wider (more aggregates in the \u0026gt;\u0026thinsp;100mm\u003csup\u003e2\u003c/sup\u003e size range, Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Cover crop roots and organic matter can affect the distribution of size of soil pores (Al-Shammary et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Mycorrhizae such those associated with \u003cem\u003eA. pintoi\u003c/em\u003e increase aggregate stability (Rillig \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). On the other hand INOC, the mycorrhizal inoculant treatment, had no clear effect on soil aggregate size distribution. Since the +/-INOC samples were taken from different locations, these had the effect of validating our conclusions regarding the soil aggregate size distribution in relation to \u003cem\u003eA. pintoi\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eINOC did appear to give the \u003cem\u003eC. arabica\u003c/em\u003e its expected waxy sheen in the autumn after planting, without it the leaves took on a matte finish. The difference in finish disappeared soon after (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). As mentioned, INOC had no clear effect on soil aggregate sizes a year after planting. This could be related to the experimental fields\u0026rsquo; history, as a once-mature \u003cem\u003eC. arabica\u003c/em\u003e plantation, with soil still in good condition. The mycorrhizal inoculant similarly has its origin in mature \u003cem\u003eC. arabica\u003c/em\u003e plantations. It could be that in good \u003cem\u003eC. arabica\u003c/em\u003e plantation soils, the inoculant has only a short-term effect, after which the existing soil microbiome outcompetes the inoculant.\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. latifolia\u003c/em\u003e in BSU had higher post-rain leaf transpiration than that in ARA. The soil was still wet but the canopy and air were dry. The BSU trees were already suffering from earlier water stress, and the warmer (compared to ARA) soil may have led the trees to use transpiration to cool their leaves. Faster soil drying is a clear risk of this strategy.\u003c/p\u003e \u003cp\u003eAlthough this work is about drought survival, the test system and method have consequences well beyond that. This is the first report of a \u003cem\u003eC. latifolia / C. arabica\u003c/em\u003e intercropping system. It is also the first report of \u003cem\u003eA. pintoi\u003c/em\u003e as a cover crop with either of these trees. This remote sensing results show that for sufficiently strong signals and appropriate references (here all measurements were relative to MAIZE) and time-averaging (over the entire DS), moisture and vegetation can be measured for small plots previously considered too small for Sentinel2 (Nov\u0026aacute;k and Kř\u0026iacute;žov\u0026aacute;, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, the \u003cem\u003eA. pintoi\u003c/em\u003e cover crop had a strong effect on soil moisture (by remote sensing), temperature (measured on-site), and structure, compared to bare soil in full sun. As a result, 100% of \u003cem\u003eC. latifolia\u003c/em\u003e survived the DS in the former. Bare soil in shade had similarly good results in soil temperature and tree condition, indicating that shading provides a similar protective effect. We conclude that \u003cem\u003eA. pintoi\u003c/em\u003e does indeed provide drought protection for young trees, and the effect is likely due mainly to soil shading. Differences in vegetation index and soil structure suggest future benefits in soil carbon sequestration.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNDMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNormalized Difference Moisture Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNDVI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNormalized Difference Vegetation Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSoil Organic Carbon\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eA. pintoi\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eArachis pintoi\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eC. latifolia\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eCitrus latifolia\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eC. arabica\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eCoffea arabica\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding and other support\u003c/h2\u003e\n\u003cp\u003eWe gratefully acknowledge advice and a gift of 4000 \u003cem\u003eC. arabica\u0026nbsp;\u003c/em\u003eseedlings from Henrik \u0026Ouml;hman, Exportadora de Cafe California, and the Starbucks 100 million trees initiative. Flores is supported by the Swedish University of Agricultural Sciences and the Swedish Research Council grant VR-M 2016-06301, The National Graduate School in Medical Bioinformatics (MedBioInfo).\u003c/p\u003e\n\u003ch2\u003eAvailability\u003c/h2\u003e\n\u003cp\u003eCode is available at github.com/samuelflores/earth-observation .\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eS. Flores intends to sell coffee and lime grown on the experimental plots. D. Trejo sells mycorrhizal inoculant through Universidad Veracruzana.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eD. Trejo suggested the use of \u003cem\u003eA. pintoi\u0026nbsp;\u003c/em\u003eand her mycorrhizal inoculant. J. Ba\u0026ntilde;uelos measured soil temperatures and aggregate sizes. Both consulted throughout the project. S. Flores conceived and implemented the agroforestry system, supervised agricultural staff, wrote the code, processed the data, and wrote the paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlele JO, Ding Q, Sayed HAA (2023) A combined ridging and cover crop tillage system for sustainable coffee plantation in Kenya. Agron (Basel) 13:655\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlanco-Canqui H, Ruis SJ (2020) Cover crop impacts on soil physical properties: A review. 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Soil Biol Biochem 184:109109\u003c/span\u003e\u003c/li\u003e\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":"Agroforestry, remote sensing, cover crop, mycorrhizal inoculant, drought survival.","lastPublishedDoi":"10.21203/rs.3.rs-8431754/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8431754/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims:\u003c/h2\u003e \u003cp\u003eOnce rare, extended droughts are becoming more frequent in parts of the wet tropics, impacting rain-fed production of major commodities including citrus and coffee. We hypothesized that the dense, deep-rooted, perennial cover crop \u003cem\u003eArachis pintoi\u003c/em\u003e would keep soil cool and moist during drought, protecting young \u003cem\u003eCitrus latifolia\u003c/em\u003e trees.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eWe measured moisture (NDMI) and vegetation (gNDVI) index using Sentinel2 multispectral imaging. We also made ground measurements of leaf stomatal conductance, soil temperature, and soil aggregation.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003e \u003cem\u003eA. pintoi\u003c/em\u003e cover cropped plots had significantly higher NDMI and gNDVI, lower soil temperature, and larger soil aggregate cross-sectional area, in particular when compared to bare soil. After a rain and in full sun, \u003cem\u003eC. latifolia\u003c/em\u003e transpiration spiked in bare soil but not in \u003cem\u003eA. pintoi\u003c/em\u003e cover cropped plots. Zero \u003cem\u003eC. latifolia\u003c/em\u003e trees died from drought in full-sun, cover-cropped plots. Similarly, zero died in shaded, bare-soil plots. In contrast, 6 (of 27) trees in full-sun, bare-soil conditions died.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003e \u003cem\u003eA. pintoi\u003c/em\u003e appears to maintain soil conditions that are conducive to \u003cem\u003eC. latifolia\u003c/em\u003e survival during the dry season. The effect appears to be mostly due to shading, as cover cropping becomes dispensable under partial tree shade. Remote sensing detected treatment effects despite small experimental plot sizes. The higher post-rain leaf transpiration suggests \u003cem\u003eC. latifolia\u003c/em\u003e may contribute to soil drying in bare soil. Higher vegetation index and soil aggregation suggest cover cropping may provide additional long term benefits in soil carbon sequestration.\u003c/p\u003e","manuscriptTitle":"Arachis pintoi cover cropping increases drought survival of Citrus latifolia in an intercrop with Coffea arabica","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-30 01:31:32","doi":"10.21203/rs.3.rs-8431754/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":"4dbff6b6-63d6-4824-b7c0-d894c89bcacd","owner":[],"postedDate":"January 30th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Reject after review","date":"2026-05-15T10:32:45+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T14:33:06+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-30 01:31:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8431754","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8431754","identity":"rs-8431754","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}