Drought of early time in growing season decreases community aboveground biomass, but increases belowground biomass in a desert steppe

Drought of early time in growing season decreases community aboveground biomass, but increases belowground biomass in a desert steppe | 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 Drought of early time in growing season decreases community aboveground biomass, but increases belowground biomass in a desert steppe Xiangyun Li, Xiaoan Zuo, Ping Yue, Xueyong Zhao, Ya Hu, Xinxin Guo, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-284808/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: Increasing drought induced by global climate changes is altering the structure and function of grassland ecosystems. However, there is a lack of understanding of how drought affects the allocation and trade-off of above- and belowground biomass in desert steppe. We conducted a four-year (2015-2018) drought experiment to examine the responses of community above-and belowground biomass (AGB and BGB) to manipulated drought and natural drought in the early period of growing season (from March to June) in a desert steppe. We compared the associations of drought with species diversity (species richness and density), community-weighted means (CWM) of five traits, and soil factors (soil Water, soil carbon content, and soil nitrogen content) for grass communities. Meanwhile, we used the structural equation modeling (SEM) to elucidate whether drought affects AGB and BGB by altering species diversity, functional traits and soil factors. Results: We found that drought reduced the species richness, and species modified the CWM of traits to cope with drought. Manipulated drought had the effect on soil water content, but not on soil carbon and nitrogen content. We also found that the experimental and natural drought decreased AGB, while natural drought increased BGB. AGB was correlated with species richness, density, plant height and soil water, while BGB was correlated with CWM of plant height, CWM of specific leaf area, CWM of leaf dry matter content, CWM of leaf nitrogen content, soil water, soil carbon and nitrogen content. The SEM results indicated that the experimental and natural drought indirectly decreased AGB by reducing species richness and plant height, while natural drought and soil nitrogen content directly affected BGB. Conclusions: These results suggest that species richness and functional traits can modulate the effects of drought on AGB, however natural drought and soil nitrogen determine BGB. Our findings demonstrate that the long-term observation and experiment are necessary to understand the underlying mechanism of the allocation and trade-off of community above-and belowground biomass. Ecological Modeling Terrestrial Ecology Precipitation changes Biodiversity Plant traits Allocation of biomass Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Global climatic changes are expected to increase the risk of extreme drought events during the growing season [1, 2]. Drought has pervasive impacts on ecosystem structure and function, especially in water-limited grasslands [3, 4]. Therefore, changes in rainfall may affect the allocation and trade-off of plant biomass by altering community compositions and structure [3, 4]. Several studies have reported the responses of vegetation to climatic change [5, 6]. However, the effect of drought on both aboveground and belowground biomass remain unclear. Moreover, the timing of drought occurrence would play an equally or more important role with the severity of drought itself [7]. Thus, this manipulated drought experiment of 4 years can help us to identify influences of extreme drought on the arid ecosystems, and this is feasible for adaptive management of the region. The impact of climate change on biodiversity is greater than any other factor [8]. The control of species diversity including species richness and abundance is received the most focus [8, 9]. The relationship between ecosystem productivity and species diversity has been debated for decades [10]. Generally speaking, higher species diversity supports higher plant productivity but remains variation in other geographic regions [8, 11]. Globally, regions with climate are either cold or arid support few species than regions where the climates are both warm and wet [12]. Most species diversity-biomass relationship studies have focused on aboveground biomass instead of underground biomass [13]. In a few studies on the relationship between belowground biomass and species diversity, it was found that there was a positive or uncorrelated relationship between them, due to the selection of diversity indexes and the research sites [14]. Plant biomass is important for ecosystem functions and services [15]. Therefore, examining the relationship between biodiversity and biomass can provide support for further understanding of ecosystem management. Functional traits are measurable characteristics of plants after long-term response and adaptation to the external environment [16, 17]. According to the dominance/mass ratio hypothesis, the functional trait of dominant species can directly affect ecosystem functions [18, 19]. Some traits at a community-level are the predictors of plant community responses to precipitation changes [20, 21]. Shifts in precipitation patterns can lead to changes in traits and species abundance, thereby shaping plant distributions or compositions [22]. The key plant traits, such as plant height, specific leaf area (SLA), leaf dry matter content (LDMC), leaf carbon content (LCC) and leaf nitrogen content (LNC), reflect plant strategies for coping with changing climate conditions [23]. For example, drought or drought in the growing season causes a decrease in plant height and an increase in SLA and LDMC [24]. The plant functional traits as potential covariates may lead to the allocation of biomass under drought according to the optimal partitioning theory [25, 26]. However, the link between the allocation of biomass and plant functional traits remains poorly known [26]. Therefore, understanding the relationship is important to understand the consequences of a precipitation pattern change in arid and semi-arid areas. Precipitation manipulation experiment is a direct way to study shifts in community compositions and ecosystem functions following short-term precipitation change [27, 28]. Over the two decades, the studies on experimentally reducing precipitation have greatly increased to investigate how increased aridity might influence the ecosystems [29, 30]. However, community responses to extreme drought vary geographically [31, 32]. The semiarid grassland region of northern China is desirable for investigating the effects of extreme drought on structure and function of grassland ecosystems, and the predicted effects can guide semiarid grassland to cope with future climate change. Here, we conducted a four-year experiment that imposed extreme growing season drought, including two types: (1) a 66% reduction of rainfall from May to August (-66%) and (2) a 100% reduction of rainfall from June to July (-60 Days). This allowed us to examine the changes in the desert steppe under manipulative drought experiment. We asked the following questions: (1) How species diversity, community-level trait and soil property respond to the experimental drought in desert steppe? (2) How does the above- and belowground biomass allocation change in the four consecutive years of drought treatments? (3) Which indexes of vegetation and soil property mediate the allocation of biomass response to drought in desert steppe. Results The species richness and AGB were significantly affected by drought, year and their interaction ( p < 0.05, Additional file 1 Table S4, Fig. 1a and 1c). Specifically, drought treatment significantly reduced AGB and species richness excluded species richness in 2015(Fig. 1a and 1c). The density was positively corrected with drought and year, and the BGB was significantly affected by year and the interaction of drought and year ( p < 0.05, Additional file 1 Table S4, Fig. 1b and 1d). Surprisedly, BGB was increased with years, regardless of drought treatment ( p < 0.05, Fig. 1d). The CWM of height in desert steppe was significantly affected by drought, year and their interaction (Additional file 1 Table S4, Fig. 2a). The CWM of height in 2018 was significantly lower than that in 2015-2016 under extreme drought (-66% and -60 Days) (p < 0.05; Fig. 2a). However, CWM of SLA, LDMC and LNC were only affected by years (Additional file 1 Table S4, Fig. 2b-c and 2e). CWM of SLA and LNC increased following the time and reached their maximum in 2018 (Fig. 2b and 2e). In contrast, CWM of LDMC were decreased following the time and reached their minimum in 2018 (Fig. 2c). CWM of LCC had significant differences only under the drought treatment of 60 days in 2015-2016 (Fig. 2d). Drought, year and their interaction had a significant influence on soil water content (p < 0.05, Additional file 1 Table S4, Fig. 3c). There were significant differences in soil water content between 2015-2016 and 2018 under different drought treatments (p < 0.05; Fig. 3c). The soil water content in 2015 and 2017 was significantly lower than that in 2016 and 2018 under CONT, while significantly higher in 2018 than that in 2015 under -66% and -60 Days drought treatment (p < 0.05; Fig. 3c). The soil carbon content and soil nitrogen content are only affected by years (p < 0.01, Additional file 1 Table S4, Fig. 3a-b). Under -66% treatment, the soil carbon content in 2017 was significantly higher than that in 2015-2016 and 2018, and soil nitrogen content in 2015 was significantly higher than that in 2016-2018 (p < 0.05; Fig. 3a-b). Across the four years, AGB was positive correlated with species diversity (species richness and density) (p < 0.001; Fig. 4 a-b), CWM of plant height (p < 0.001; Fig. 4c) and soil water (p < 0.01; Fig. 5a). BGB was positive correlated with CWM of SLA (p < 0.001; Fig. 4d), LNC (p < 0.001; Fig. 4f), soil water (p < 0.01; Fig. 5b) and soil carbon (p < 0.01; Fig. 5c). However, we found significant negative relationships between BGB and CWM of LDMC (p < 0.001; Fig. 4e), plant height (p < 0.05; Fig. 4g) and soil nitrogen (p < 0.05; Fig. 5d). On the one hand, there were no differences in above- and belowground biomass, species density, CWM of traits and soil factors between -66% and -60 Days; on the other hand, only the precipitation in the early growing season (March to June) was correlated with the above- and belowground biomass (Additional file 1 Table S2), so we combined the two treatments as a variable to represent drought and selected the precipitation in the early growing season (March to June) in structural equation model (SEM). The SEM was performed to quantify the direct vs indirect effects of how drought, precipitation in the early growing season (March to June), soil factors and CWM of plant traits on AGB or BGB. The model including the drought, precipitation, species richness, plant height and soil N was the best fit (χ2= 16.936, P = 0.110; RMSEA = 0.087; GFI = 0.911) to explain 60% variance of AGB and 56% variance of BGB (Fig. 6). The SEM models showed that increasing precipitation in the early growing season directly increased AGB and indirectly increased AGB through its positive impact on plant height (Table 1). The increasing plant height directly increased AGB and BGB (Table 1). The drought had a negative direct impact on AGB, also, the indirect impact of drought on AGB was through its negative impact on species richness and plant height (Table 1). The increasing species richness directly increased AGB (Table 1). Increasing soil N content and precipitation in the early growing season directly decreased BGB (Table 1). Discussion The response of ecosystems to changing precipitation is driven in part by species diversity and plant community functional traits. Thus, elucidating the variation of species diversity and CWM of traits under drought of an early time in the growing season is critically important for improving predictions of ecosystem responses to changing precipitation. In semiarid grasslands of northern China, water is the limiting constraint to ecosystem development [33]. Here, we conducted an extreme drought experiment of four years to determine how desert steppe ecosystem modify plant community in response to the drought. Our findings demonstrated that the species diversity was sensitive to extreme drought. We found that extreme drought, compared with the control, significantly reduced species richness in 2016-2018 (Fig. 1). Experimental drought changed biodiversity that can be explained by species turnover/re-ordering caused by the cumulative effect of extreme drought (Additional file 1 Table S1). Experimental drought can modify species either through shifts in genotypic abundance and phenotypic plasticity by acting as an environment filter [34, 35]. On a temporal scale, there was no significant difference in species richness under extreme drought, which is contrary to other findings that suggested that plant species richness is more sensitive to drought in the arid ecosystem [34, 36]. One possible explanation for this difference could be the low soil moisture caused by extreme drought reduced the number of reproductive buds in more species [37, 38]. The relationship between functional traits of plants reflects the adaptation strategies of plants to the environment [34]. Plants usually adopt combinations of functional traits to adapt to changing environments [39]. In this study, we found that CWM of traits experimental drought had no response to experimental drought but had a significant response to natural drought (Fig. 1), which might be attributed to changes in species composition (Additional file 1 Table S1). We observed CWM of SLA and LNC increased, while CWM of plant height and LDMC decreased year by year. Previous studies respectively showed that plant height was significantly positively correlated with LDMC [39, 40], SLA was significantly negatively correlated with LDMC [41, 42], and SLA was significantly positively correlated with LNC [43, 44]. Our results are consistent with previous studies that showed that plants adapted to drought by changing leaf morphology and nutrient distribution. Plant nutrient contents usually reflect soil nutrient availability [45], however, we do not observe a match between plant nutrient concentrations and soil nutrient supply which also have been reported by other findings [46, 47]. This mismatch may be due to the lower soil moisture content, which results in limited nutrient flow and nutrient uptake by plants [48, 49]. Our results indicated that the aboveground biomass was significantly reduced by drought treatment every year，which has been shown in several studies [50, 51]. However, the significant increase in underground biomass due to drought treatment occurred only in 2017. This difference from the optimal distribution theory may be due to the extreme drought alters in root distribution rather than the total amount of root biomass [52, 53]. Meanwhile, our findings demonstrated that AGB tended to decrease year by year and belowground biomass to increase, which in agreement with previous findings that have shown consecutive precipitation treatments can cause cumulative influence on ecosystem productivity [53, 54]. The SEM results showed that CWM of plant height controlled by drought treatments and precipitation in the early growing season (March to June) exerted a direct effect on AGB. This is consistent with that CWM of traits determine the ecosystem function, which supports the mass ratio hypothesis [55, 56]. And it also proves that plant height is an important and comprehensive trait to reflect the ability of plants to adapt to changes in the environment [57]. Not surprisingly, drought and rainfall in March-June had direct impacts on AGB, confirming that in the previous findings [58, 59]. Our findings were consistent with others that precipitation and soil N had direct effects on belowground biomass [60]. These results suggest that precipitation in the early growing season has an important effect on biomass allocation. In our study, species richness was affected by drought treatment and has a positive correlation, which is consistent with the findings that the positive linear relationship is one of the common forms of the species richness–biomass relationship patterns [61, 62]. Conclusion This study showed that natural drought of early time in growing season can reduce the aboveground biomass and increased the belowground biomass, suggesting that the rainfall of early time in growing season plays an important role in maintaining ecosystem structure and function in desert steppe. Community-level plant height is an important predictor for AGB in desert steppe. Plant investment in root system is a strategy for plants to adapt to soil nutrient reduction and drought of the early time in growing season, which provides deep insight into the mechanism of the above- and belowground biomass allocation of plants. Methods Experimental site This study was conducted in the Urat Desert‐grassland Ecosystem Research Station (106°58′E, 41°25′N, 1,650 m above sea level) located in western Inner Mongolia, China. The region has a temperate continental monsoon climate, and the mean annual precipitation is 139.5 mm, about 70% occurring during the growing season [63]. Main soil type in the study area is brown calcium, and the dominant species in the desert steppe are Stipa glareosa , Peganum harmala and Allium polyrhizum (Additional file 1 Table S1). Experimental treatments The extreme drought experiment was established in 2014 and was conducted from 2015 to 2018. This experiment involved three treatments: (1) a control (ambient precipitation, without shelters), (2) a -66% drought treatment (66% reduction from May 1 to August 31, with shelters), (3) and a -60 Days drought treatment (100% reduction from June 1 to July 31, with shelters). There are eighteen 6 × 6 m plots in total, which are randomly distributed in location and organized into six blocks. Each plot was located at least 2 m from the nearest neighboring plot and established a 1-m external buffer to minimize the edge effects. To prevent hydrological exchange with the surrounding soil, a 1 m deep sheet of plastic flashing was established in each plot. The roofs consisted of strips of clear polycarbonate plastic was situated 2 m above the ground at the highest point, which allowed for the circulation of air and avoided microclimatic changes. Polycarbonate plastic has been confirmed to have minimal influence on photosynthetically active radiation [64]. Sampling and analysis During the peak of each growing season from 2015-2018, a quadrat (1 × 1 m) was set up in each experimental plot for vegetation investigation and sampling. Quadrat was marked to prevent subsequent resampling in the next year. We measured the number and the maximum height of each species within quadrat. Besides, we harvested all aboveground biomass (AGB) by species in each quadrat. Finally, we estimated belowground biomass (BGB) using a root auger (8 cm diameter) to measure root mass at a depth of 0-20 cm. The roots samples were taken back to the laboratory and then were washed free of soil over a mesh sieve (mesh size of 0.25 mm). All above- and belowground biomasses were dried at 65 °C in an oven for 48 h and weighed in the lab. We determined five key functional traits to reflect the plant morphology and growth investment [65, 66]: plant height, specific leaf area (SLA), leaf dry matter content (LDMC), leaf carbon content (LCC) and leaf nitrogen content (LNC). These traits were measured for the dominant species making up 90% of the total plant cover in each plot. The five traits on 10 individuals per species in each plot were obtained by using the standard methodologies [67]. We calculated community-weighted means (CWM) of single-trait by multiplying the trait value of each species by its relative biomass in the community [68]. CWM can reflect the characteristics of community functional traits [69]. In each plot, three soil samples (0–10 cm depth) were collected to determine soil water, and one mixed soil sample from three random replicates was collected to measure soil organic carbon and total nitrogen content. Leaf carbon and nitrogen content (%), as well as soil organic carbon and total nitrogen content (g Kg -1 ), were measured by using an Elemental Analyzer [24] (Costech ECS 4010, Italy) with a reduction temperature of 650°C and a combustion temperature of 980°C. Data analysis The annual precipitation gradually decreased from 2015 to 2017, and increased in 2018 due to increased precipitation in July and August (Additional file 1 Figure S1). The precipitation in the early time of 2015-2018 growing season (March to June) was 56.2mm, 77.9mm, 28.8mm and 21.4 mm, respectively (Additional file 1 Figure S1), which decreased in an inter-annual timescale. Thus, we assess how experimental drought and natural drought in the early period of growing season affected structure and function of grassland ecosystems. We analyzed the response of each variable to extreme drought using separate repeated measures mixed model ANOVAs with year, treatment, and their interaction as fixed factor and block as a random factor (Additional file 1 Table S4). One-way ANOVA was conducted to assess the significant differences of species richness, Density, AGB, BGB, CWM of Height, CWM of SLA, CWM of LDMC, CWM of LCC, CWM of LNC, Soil Carbon, Soil Nitrogen, and Soil Water over to extreme drought among years. A level of P < 0.05 was considered significant. Data are presented as mean ± standard error throughout. Then, the simple regression models with a standard 95% confidence range were used to assess whether CWM of traits and soil factors could explain AGB and BGB. Based on the simple regression and the Correlation coefficients of each variable (Additional file 1 Table S3), a structural equation modeling (SEM) was performed, in which drought treatment and the precipitation in the early time were treated as exogenous variables; species diversity, CWM of trait, and soil factors were considered as endogenous variables; AGB and BGB were regarded as the response variable. We assessed the best fitting model using a Chi-square test, root mean square error of approximation and goodness-of-fit index [19], which was performed by AMOS 20.0 (Amos Development, Spring House, PA, USA). Data analysis and plotting were run with the SPSS16.0 and SigmaPlot12.0 for Windows statistics program, respectively. The simple regression models were performed using the trendline function in the basic Trendline package of R software (v4.0.0, R Core Team, 2020). List of Abbreviations AGB: aboveground biomass BGB: belowground biomass CWM: community-weighted means SLA: specific leaf area LDMC: leaf dry matter content LCC: leaf carbon content LNC: leaf nitrogen content Soil N: soil nitrogen content Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests Funding This study was supported by the Second Tibetan Plateau Scientific Expedition and Research program (2019QZKK0305), National Natural Science Foundation of China (42071140 and 41622103) and Youth Innovation Promotion Association CAS (1100000036). Authors' contributions Xiaoan Zuo and Qiang Yu designed this experiment; Ping Yue, Ya Hu, Xinxin Guo, Aixia Guo, and Chong Xu contributed significantly to analysis and manuscript preparation; Xiangyun Li performed the data analyses and wrote the manuscript; Xiaoan Zuo, Ping Yue, and Xueyong Zhao helped perform the analysis with constructive discussions. Acknowledgements We are very grateful to Dr. Julio Di Rienzo for the support of FDiversity software. References Easterling DR, Meehl GA, Parmesan C, Changnon SA, Karl TR, Mearns LO: Climate extremes: Observations, modeling, and impacts. Science 2000, 289(5487):2068-2074. Smith MD: An ecological perspective on extreme climatic events: a synthetic definition and framework to guide future research. J Ecol 2011, 99(3):656-663. 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Denton EM, Dietrich JD, Smith MD, Knapp AK: Drought timing differentially affects above- and belowground productivity in a mesic grassland. Plant Ecol 2017, 218(3):317-328. Zheng SX, Ren HY, Lan ZC, Li WH, Wang KB, Bai YF: Effects of grazing on leaf traits and ecosystem functioning in Inner Mongolia grasslands: scaling from species to community. Biogeosciences 2010, 7(3):1117-1132. Bai Y, Wu J, Pan Q, Huang J, Wang Q, Li F, Buyantuyev A, Han X: Positive linear relationship between productivity and diversity: evidence from the Eurasian Steppe. J Appl Ecol 2007, 44(5):1023-1034. Bhandari J, Zhang Y: Effect of altitude and soil properties on biomass and plant richness in the grasslands of Tibet, China, and Manang District, Nepal. Ecosphere 2019, 10. Liu LX, Zhao XY, Chang XL, Lian J: Impact of Precipitation Fluctuation on Desert-Grassland ANPP. Sustainability-Basel 2016, 8(12). Yahdjian L, Sala OE: A rainout shelter design for intercepting different amounts of rainfall. Oecologia 2002, 133(2):95-101. Valencia E, Maestre FT, Le Bagousse-Pinguet Y, Quero JL, Tamme R, Borger L, Garcia-Gomez M, Gross N: Functional diversity enhances the resistance of ecosystem multifunctionality to aridity in Mediterranean drylands. New Phytol 2015, 206(2):660-671. Guittar J, Goldberg D, Klanderud K, Telford RJ, Vandvik V: Can trait patterns along gradients predict plant community responses to climate change? Ecology 2016, 97(10):2791-2801. Cornelissen JHC, Lavorel S, Garnier E, Diaz S, Buchmann N, Gurvich DE, Reich PB, ter Steege H, Morgan HD, van der Heijden MGA et al: A handbook of protocols for standardised and easy measurement of plant functional traits worldwide. Aust J Bot 2003, 51(4):335-380. Kichenin E, Wardle DA, Peltzer DA, Morse CW, Freschet GT: Contrasting effects of plant inter- and intraspecific variation on community-level trait measures along an environmental gradient. Funct Ecol 2013, 27(5):1254-1261. Debouk H, de Bello F, Sebastia MT: Functional Trait Changes, Productivity Shifts and Vegetation Stability in Mountain Grasslands during a Short-Term Warming. Plos One 2015, 10(10). Table Table 1 The total, direct and indirect standardized effects on above- and belowground biomass from the structural equation model. Predictor Pathways Effect Aboveground biomass Drought Direct -0.40 Indirect -0.24 Total -0.64 Precipitation Direct 0.25 Indirect 0.08 Total 0.33 Height Direct 0.20 Indirect NS Total 0.20 Species richness Direct 0.28 Indirect NS Total 0.28 Belowground biomass Soil nitrogen content Direct -0.32 Indirect NS Total -0.32 Precipitation Direct -0.71 Indirect 0.03 Total -0.67 Height Direct 0.09 Indirect NS Total 0.09 NS, non-signi fi cant relationships. Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 14 Apr, 2021 Reviews received at journal 12 Apr, 2021 Reviews received at journal 06 Apr, 2021 Reviewers agreed at journal 01 Apr, 2021 Reviewers agreed at journal 29 Mar, 2021 Reviewers invited by journal 18 Mar, 2021 Editor assigned by journal 18 Mar, 2021 Editor invited by journal 14 Mar, 2021 Submission checks completed at journal 28 Feb, 2021 First submitted to journal 27 Feb, 2021 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. 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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-284808","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":14169992,"identity":"daa40799-0508-4dea-a938-18ce5cddf059","order_by":0,"name":"Xiangyun Li","email":"","orcid":"","institution":"Urat Desert-grassland Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science","correspondingAuthor":false,"prefix":"","firstName":"Xiangyun","middleName":"","lastName":"Li","suffix":""},{"id":14169993,"identity":"3e669689-f127-4fbe-8889-263f44a13ec0","order_by":1,"name":"Xiaoan Zuo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYNCCCgsGAxK1nJEgVQtjGyla5GckH5P4OU/C3pyB+eEHhpo7RFgwIy3ZsHebBLNlA5uxBMOxZ4S1MEvkGD7g3SbBZnCAwYyBseEwYS1sEjkGB//OkeAxOMD+jTgtPEBbHvM2SEgYHOAh0hYJnmfJxjLHJAwsm3mKJRKOEaFFvj35mOSbGht7c/b2jR8+1BChBQGYgTiBFA2jYBSMglEwCnADAMHpLqAzUGhvAAAAAElFTkSuQmCC","orcid":"","institution":"Urat Desert-grassland Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science","correspondingAuthor":true,"prefix":"","firstName":"Xiaoan","middleName":"","lastName":"Zuo","suffix":""},{"id":14169994,"identity":"b79057bc-8b39-4a62-9b81-73397b176081","order_by":2,"name":"Ping Yue","email":"","orcid":"","institution":"Urat Desert-grassland Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Yue","suffix":""},{"id":14169995,"identity":"ca5de1ad-fc92-46b9-b692-d1178f32ec79","order_by":3,"name":"Xueyong Zhao","email":"","orcid":"","institution":"Naiman Desertification Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science","correspondingAuthor":false,"prefix":"","firstName":"Xueyong","middleName":"","lastName":"Zhao","suffix":""},{"id":14169996,"identity":"02e23940-125d-4d81-a78e-6f5efbd955e6","order_by":4,"name":"Ya Hu","email":"","orcid":"","institution":"Urat Desert-grassland Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science","correspondingAuthor":false,"prefix":"","firstName":"Ya","middleName":"","lastName":"Hu","suffix":""},{"id":14169997,"identity":"3fcb8fe4-16f5-4b93-9bee-e46ca18568a4","order_by":5,"name":"Xinxin Guo","email":"","orcid":"","institution":"Urat Desert-grassland Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science","correspondingAuthor":false,"prefix":"","firstName":"Xinxin","middleName":"","lastName":"Guo","suffix":""},{"id":14169998,"identity":"be24cdb3-5c68-4ba8-b8dc-cbc6a85faf92","order_by":6,"name":"Aixia Guo","email":"","orcid":"","institution":"Urat Desert-grassland Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science","correspondingAuthor":false,"prefix":"","firstName":"Aixia","middleName":"","lastName":"Guo","suffix":""},{"id":14169999,"identity":"11ef0fdb-5957-4ac3-b658-fddf2baeb69e","order_by":7,"name":"Chong Xu","email":"","orcid":"","institution":"National Hulunber Grassland Ecosystem Observation and Research Station, Chinese Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Chong","middleName":"","lastName":"Xu","suffix":""},{"id":14170000,"identity":"2bae0ca1-597c-4965-80dc-1963c8231c6c","order_by":8,"name":"Qiang Yu","email":"","orcid":"","institution":"National Hulunber Grassland Ecosystem Observation and Research Station, Chinese Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2021-02-28 04:44:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-284808/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-284808/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":6910050,"identity":"d4115526-8c5b-4472-a417-ccd3b5971d18","added_by":"auto","created_at":"2021-03-13 00:13:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":71328,"visible":true,"origin":"","legend":"Effects of extreme drought (CONT, control; -66%, reduce 66% in rainfall from May to August; -60 Days, reduce 100% in rainfall from June to July) on plant community characteristics of desert steppe during the treatment years (2015–2018). AGB, aboveground plant biomass; BGB, belowground root biomass. Variables are shown as mean ± SE (n = 6). Different lowercase letters indicate significant differences between years for the same treatments in p\u003c 0.05. Statistical significance of drought effect in each year is depicted as ** p\u003c0.0 1 and * p\u003c0.05.","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-284808/v1/084af7fc492a4dbbadc3cc9c.png"},{"id":6910194,"identity":"c1aa13e5-6c00-4050-aca6-d627e0f7c7ed","added_by":"auto","created_at":"2021-03-13 00:16:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":72503,"visible":true,"origin":"","legend":"Effects of extreme drought (CONT, control; -66%, reduce 66% in rainfall from May to August; -60 Days, reduce 100% in rainfall from June to July) on plant community trait during the treatment years (2015–2018). SLA, specific leaf area; LDMC, leaf dry matter content; LCC, leaf carbon content LNC, leaf nitrogen content. Variables are shown as mean ± SE (n = 6). Different lowercase letters indicate significant differences between years for the same treatments in p\u003c 0.05. Statistical significance of drought effect in each year is depicted as ** p\u003c0.0 1 and * p\u003c0.05.","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-284808/v1/2a3700485bb4f56bcae86760.png"},{"id":6910190,"identity":"683f6901-3fb9-4cda-ab09-a7932cfb3bf2","added_by":"auto","created_at":"2021-03-13 00:16:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89706,"visible":true,"origin":"","legend":"Effects of extreme drought (CONT, control; -66%, reduce 66% in rainfall from May to August; -60 Days, reduce 100% in rainfall from June to July) on soil characteristics during the treatment years (2015–2018). Soil Carbon, 0-20cm soil carbon content; Soil Nitrogen, 0-20cm soil nitrogen content; Soil Water, 0-20cm soil water content. Variables are shown as mean ± SE (n = 6). Different lowercase letters indicate significant differences between years for the same treatments in p\u003c 0.05. Statistical significance of drought effect in each year is depicted as ** p\u003c0.0 1 and * p\u003c0.05. ","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-284808/v1/dbeb6b84a26c946835f2a016.jpg"},{"id":6910192,"identity":"97b6201e-ff81-4a27-8b38-704722af2f94","added_by":"auto","created_at":"2021-03-13 00:16:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":193358,"visible":true,"origin":"","legend":"Relationships of community above-and belowground biomass with species diversity and community-weighted functional traits across four years in the desert steppe. Only significant (p≤ 0.05) relationships were shown. Notes: SLA, specific leaf area; LDMC, leaf dry matter content; LNC, leaf nitrogen content. ","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-284808/v1/4c871a838342f7fe68a0048b.png"},{"id":6910193,"identity":"daed6f1f-5adb-422b-8268-7a80151d0392","added_by":"auto","created_at":"2021-03-13 00:16:42","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":87584,"visible":true,"origin":"","legend":"Relationships of community above-and belowground biomass with soil factors across four years in the desert steppe. Only significant (p≤ 0.05) relationships were shown.","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-284808/v1/56702ee481b6e2246bf9d286.png"},{"id":6910053,"identity":"b9d4fcd4-f6c3-43a0-8a96-241e69c8dbbb","added_by":"auto","created_at":"2021-03-13 00:13:42","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":47321,"visible":true,"origin":"","legend":"Structural equation modeling (SEM) depicting the effect paths of extreme drought treatments, precipitation in the early growing season (March to June), functional trait and soil properties on above- and belowground biomass. Square boxes indicate variables included in the model. Single headed arrows indicate paths. Numbers on path is the standardized regression weights. Total explained variance (R2) of biomass is on the right corner of boxes. Using the *, ** and*** to show the significance along the paths at the level of P \u003c 0.05, P \u003c 0.01and P \u003c 0.001. Results of model fitting: χ^2=16.936，P=0.110，RMSEA=0.087，GFI=0.911","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-284808/v1/ecf63b59271c53890ef301e5.png"},{"id":13679767,"identity":"1564a34b-ebea-471f-bf0d-ec7b76780e60","added_by":"auto","created_at":"2021-09-17 11:45:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":778486,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-284808/v1/5b12b4cc-caa4-4084-8ee7-3a7ebfbf1b5f.pdf"},{"id":6910211,"identity":"5d8b6b0a-15b0-47e1-bdcc-b358dcceceed","added_by":"auto","created_at":"2021-03-13 00:19:42","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":122433,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-284808/v1/3fb3da75f8afe9ab75f91634.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Drought of early time in growing season decreases community aboveground biomass, but increases belowground biomass in a desert steppe","fulltext":[{"header":"Background","content":"\u003cp\u003eGlobal climatic changes are expected to increase the risk of extreme drought events during the growing season [1, 2]. Drought has pervasive impacts on ecosystem structure and function, especially in water-limited grasslands [3, 4].\u0026nbsp;Therefore, changes in rainfall may affect the allocation and trade-off of plant biomass by altering community compositions and structure [3, 4]. Several studies have reported the responses of vegetation to climatic change [5, 6]. However, the effect of drought on both aboveground and belowground biomass remain unclear. Moreover, the timing of drought occurrence would play an equally or more important role with the severity of drought itself [7]. Thus, this manipulated drought experiment of 4 years can help us to identify influences of extreme drought on the arid ecosystems, and this is feasible for adaptive management of the region.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe impact of climate change on biodiversity is greater than any other factor\u0026nbsp;[8]. The control of species diversity including species richness and abundance is received the most focus [8, 9]. The relationship between ecosystem productivity and species diversity has been debated for decades [10]. Generally speaking, higher species diversity supports higher plant productivity but remains variation in other geographic regions [8, 11]. Globally, regions with climate are either cold or arid support few species than regions where the climates are both warm and wet [12].\u0026nbsp;Most species diversity-biomass relationship studies have focused on aboveground biomass instead of underground biomass [13]. In a few studies on the relationship between belowground biomass and species diversity, it was found that there was a positive or uncorrelated relationship between them, due to the selection of diversity indexes and the research sites [14]. Plant biomass is important for ecosystem functions and services [15]. Therefore, examining the relationship between biodiversity and biomass can provide support for further understanding of ecosystem management.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunctional traits are measurable characteristics of plants after long-term response and adaptation to the external environment [16, 17]. According to the dominance/mass ratio hypothesis, the functional trait of dominant species can directly affect ecosystem functions [18, 19].\u0026nbsp;Some traits at a community-level are the predictors of plant community responses to precipitation changes [20, 21]. Shifts in precipitation patterns can lead to changes in traits and species abundance, thereby shaping plant distributions or compositions [22].\u0026nbsp;The key plant traits, such as plant height, specific leaf area (SLA), leaf dry matter content (LDMC), leaf carbon content (LCC) and leaf nitrogen content (LNC), reflect plant strategies for coping with changing climate conditions [23]. For example, drought or drought in the growing season causes a decrease in plant height and an increase in SLA and LDMC [24]. The plant functional traits as potential covariates may lead to the allocation of biomass under drought according to the optimal partitioning theory [25, 26]. However, the link between the allocation of biomass and plant functional traits remains poorly known [26]. Therefore, understanding the relationship is important to understand the consequences of a precipitation pattern change in arid and semi-arid areas.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrecipitation manipulation experiment is a direct way to study shifts in community compositions and ecosystem functions following short-term precipitation change [27, 28]. Over the two decades, the studies on experimentally reducing precipitation have greatly increased to investigate how increased aridity might influence the ecosystems [29, 30]. However, community responses to extreme drought vary geographically [31, 32]. The semiarid grassland region of northern China is desirable for investigating the effects of extreme drought on structure and function of grassland ecosystems, and the predicted effects can guide semiarid grassland to cope with future climate change. Here, we conducted a four-year experiment that imposed extreme growing season drought, including two types: (1) a 66% reduction of rainfall from May to August (-66%) and (2) a 100% reduction of rainfall from June to July (-60 Days). This allowed us to examine the changes in the desert steppe under manipulative drought experiment. We asked the following questions: (1) How species diversity, community-level trait and soil property respond to the experimental drought in desert steppe? (2) How does the above- and belowground biomass allocation change in the four consecutive years of drought treatments? (3) Which indexes of vegetation and soil property mediate the allocation of biomass response to drought in desert steppe.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe species richness and AGB were significantly affected by drought, year and their interaction (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05, Additional file 1 Table S4, Fig. 1a and 1c). Specifically, drought treatment significantly reduced AGB and species richness excluded species richness in 2015(Fig. 1a and 1c). The density was positively corrected with drought and year, and the BGB was significantly affected by year and the interaction of drought and year (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05, Additional file 1 Table S4, Fig. 1b and 1d). Surprisedly, BGB was increased with years,\u0026nbsp;regardless of drought treatment (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05, Fig. 1d).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe CWM of height in desert steppe was significantly affected by drought, year and their interaction (Additional file 1 Table S4, Fig. 2a). The CWM of height in 2018 was significantly lower than that in 2015-2016 under extreme drought (-66% and -60 Days) (p \u0026lt; 0.05; Fig. 2a). However, CWM of SLA, LDMC and LNC were only affected by years (Additional file 1 Table S4, Fig. 2b-c and 2e). CWM of SLA and LNC increased following the time and reached their maximum in 2018 (Fig. 2b and 2e). In contrast, CWM of LDMC were decreased following the time and reached their minimum in 2018 (Fig. 2c). CWM of LCC had significant differences only under the drought treatment of 60 days in 2015-2016 (Fig. 2d).\u003c/p\u003e\n\u003cp\u003eDrought, year and their interaction had a significant influence on soil water content (p \u0026lt; 0.05, Additional file 1 Table S4, Fig. 3c). There were significant differences in soil water content between 2015-2016 and 2018 under different drought treatments (p \u0026lt; 0.05; Fig. 3c). The soil water content in 2015 and 2017 was significantly lower than that in 2016 and 2018 under CONT, while significantly higher in 2018 than that in 2015 under -66% and -60 Days drought treatment (p \u0026lt; 0.05; Fig. 3c). The soil carbon content and soil nitrogen content are only affected by years (p \u0026lt; 0.01, Additional file 1 Table S4, Fig. 3a-b). Under -66% treatment, the soil carbon content in 2017 was significantly higher than that in 2015-2016 and 2018, and soil nitrogen content in 2015 was significantly higher than that in 2016-2018 (p \u0026lt; 0.05; Fig. 3a-b).\u003c/p\u003e\n\u003cp\u003eAcross the four years, AGB was positive correlated with species diversity (species richness and density) (p \u0026lt; 0.001; Fig. 4 a-b), CWM of plant height (p \u0026lt; 0.001; Fig. 4c) and soil water (p \u0026lt; 0.01; Fig. 5a). BGB was positive correlated with CWM of SLA (p \u0026lt; 0.001; Fig. 4d), LNC (p \u0026lt; 0.001; Fig. 4f), soil water (p \u0026lt; 0.01; Fig. 5b) and soil carbon (p \u0026lt; 0.01; Fig. 5c). However, we found significant negative relationships between BGB and CWM of LDMC (p \u0026lt; 0.001; Fig. 4e), plant height (p \u0026lt; 0.05; Fig. 4g) and soil nitrogen (p \u0026lt; 0.05; Fig. 5d).\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn the one hand, there were no differences in above- and belowground biomass, species density, CWM of traits and soil factors between -66% and -60 Days; on the other hand, only the precipitation in the early growing season (March to June) was correlated with the above- and belowground biomass (Additional file 1 Table S2), so we combined the two treatments as a variable to represent drought and selected the precipitation in the early growing season (March to June) in structural equation model (SEM). The SEM was performed to quantify the direct vs indirect effects of how drought, precipitation in the early growing season (March to June), soil factors and CWM of plant traits on AGB or BGB. The model including the drought, precipitation, species richness, plant height and soil N was the best fit (\u0026chi;2= 16.936, P = 0.110; RMSEA = 0.087; GFI = 0.911) to explain 60% variance of AGB and 56% variance of BGB (Fig. 6).\u003c/p\u003e\n\u003cp\u003eThe SEM models showed that increasing precipitation in the early growing season directly increased AGB and indirectly increased AGB through its positive impact on plant height (Table 1). The increasing plant height directly increased AGB and BGB (Table 1). The drought had a negative direct impact on AGB, also, the indirect impact of drought on AGB was through its negative impact on species richness and plant height (Table 1). The increasing species richness directly increased AGB (Table 1). Increasing soil N content and precipitation in the early growing season directly decreased BGB (Table 1).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe response of ecosystems to changing precipitation is driven in part by species diversity and plant community functional traits. Thus, elucidating the variation of species diversity and CWM of traits under drought of an early time in the growing season is critically important for improving predictions of ecosystem responses to changing precipitation. In semiarid grasslands of northern China, water is the limiting constraint to ecosystem development [33]. Here, we conducted an extreme drought experiment of four years to determine how desert steppe ecosystem modify plant community in response to the drought.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings demonstrated that the species diversity was sensitive to\u0026nbsp;extreme drought. We found that extreme drought,\u0026nbsp;compared with the control, significantly reduced species richness in 2016-2018 (Fig. 1). Experimental drought changed biodiversity that can be explained by species turnover/re-ordering caused by the cumulative effect of extreme drought (Additional file 1 Table S1). Experimental drought can modify species either through shifts in genotypic abundance and phenotypic plasticity by acting as an environment filter [34, 35].\u0026nbsp;On a temporal scale, there was no significant difference in species richness under extreme drought, which is contrary to other findings that suggested that plant species richness is more sensitive to drought in the arid ecosystem [34, 36]. One possible explanation for this difference could be the low soil moisture caused by extreme drought reduced the number of reproductive buds in more species [37, 38].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe relationship between functional traits of plants reflects the adaptation strategies of plants to the environment [34]. Plants usually adopt combinations of functional traits to adapt to changing environments [39].\u0026nbsp;In this study, we found that CWM of traits experimental drought had no response to experimental drought but had a significant response to natural drought (Fig. 1),\u0026nbsp;which might be attributed to changes in species composition (Additional file 1 Table S1).\u0026nbsp;We observed CWM of SLA and LNC increased, while CWM of plant height and LDMC decreased year by year. Previous studies respectively showed that plant height was significantly positively correlated with LDMC [39, 40], SLA was significantly negatively correlated with LDMC [41, 42], and SLA was significantly positively correlated with LNC [43, 44]. Our results are consistent with previous studies that showed that plants adapted to drought by changing leaf morphology and nutrient distribution. Plant nutrient contents usually reflect soil nutrient availability [45], however, we do not observe a match between plant nutrient concentrations and soil nutrient supply which also have been reported by other findings [46, 47]. This mismatch may be due to the lower soil moisture content, which results in limited nutrient flow and nutrient uptake by plants [48, 49].\u003c/p\u003e\n\u003cp\u003eOur results indicated that the aboveground biomass was significantly reduced by drought treatment every year，which has been shown in several studies [50, 51]. However, the significant increase in underground biomass due to drought treatment occurred only in 2017. This difference from the optimal distribution theory may be due to the extreme drought alters in root distribution rather than the total amount of root biomass [52, 53]. Meanwhile, our findings demonstrated that AGB tended to decrease year by year and belowground biomass to increase, which in agreement with previous findings that have shown consecutive precipitation treatments can cause cumulative influence on ecosystem productivity [53, 54]. The SEM results showed that CWM of plant height controlled by drought treatments and precipitation in the early growing season (March to June) exerted a direct effect on AGB. This is consistent with that CWM of traits determine the ecosystem function, which supports the mass ratio hypothesis [55, 56]. And it also proves that plant height is an important and comprehensive trait to reflect the ability of plants to adapt to changes in the environment [57]. Not surprisingly, drought and rainfall in March-June had direct impacts on AGB, confirming that in the previous findings [58, 59]. Our findings were consistent with others that precipitation and soil N had direct effects on belowground biomass [60]. These results suggest that precipitation in the early growing season has an important effect on biomass allocation. In our study, species richness was affected by drought treatment and has a positive correlation, which is consistent with the findings that the positive linear relationship is one of the common forms of the species richness\u0026ndash;biomass relationship patterns [61, 62].\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study showed that natural drought of early time in growing season can reduce the aboveground biomass and increased the belowground biomass, suggesting that the rainfall of early time in growing season plays an important role in maintaining ecosystem structure and function in desert steppe. Community-level plant height is an important predictor for AGB in desert steppe. Plant investment in root system is a strategy for plants to adapt to soil nutrient reduction and drought of the early time in growing season, which provides deep insight into the mechanism of the above- and belowground biomass allocation of plants.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eExperimental site\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted\u0026nbsp;in\u0026nbsp;the Urat Desert‐grassland Ecosystem Research Station (106\u0026deg;58\u0026prime;E, 41\u0026deg;25\u0026prime;N, 1,650 m above sea level) located in western\u0026nbsp;Inner Mongolia, China.\u0026nbsp;The region has a temperate continental monsoon climate, and the mean annual precipitation is 139.5 mm, about 70% occurring during the growing season [63]. Main soil type in the study area is brown calcium, and the dominant species in the desert steppe are \u003cem\u003eStipa glareosa\u003c/em\u003e, \u003cem\u003ePeganum harmala\u003c/em\u003e and\u003cem\u003e\u0026nbsp;Allium polyrhizum\u003c/em\u003e (Additional file 1 Table S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental treatments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe extreme drought experiment was established in 2014 and was conducted from 2015 to 2018.\u0026nbsp;This experiment involved three treatments: (1) a control (ambient precipitation, without shelters), (2) a -66% drought treatment (66% reduction from May 1 to August 31, with shelters), (3) and a -60 Days drought treatment (100% reduction from June 1 to July 31, with shelters). There are eighteen 6 \u0026times; 6 m plots in total, which are randomly distributed in location and organized into six blocks. Each plot was located at least 2 m from the nearest neighboring plot and established a 1-m external buffer to minimize the edge effects. To prevent hydrological exchange with the surrounding soil, a 1 m deep sheet of plastic flashing was established in each plot. The roofs consisted of strips of clear polycarbonate plastic was situated 2 m above the ground at the highest point, which allowed for the circulation of air and avoided microclimatic changes. Polycarbonate plastic has been confirmed to have minimal influence on photosynthetically active radiation [64].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the peak of each growing season from 2015-2018, a quadrat (1 \u0026times; 1 m) was set up in each experimental plot for vegetation investigation and sampling. Quadrat was marked to prevent subsequent resampling in the next year. We measured the number and the maximum height of each species\u0026nbsp;within quadrat. Besides, we harvested\u0026nbsp;all aboveground biomass (AGB)\u0026nbsp;by species\u0026nbsp;in each quadrat. Finally,\u0026nbsp;we estimated belowground biomass (BGB) using a root auger (8 cm diameter) to measure root mass at a depth of 0-20 cm.\u0026nbsp;The roots samples were taken back to the laboratory and then were washed free of soil over a mesh sieve (mesh size of 0.25 mm). All above- and belowground biomasses were dried at 65 \u0026deg;C in an oven for 48 h and weighed in the lab.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe determined five key functional traits to reflect the plant morphology and growth investment [65, 66]: plant height, specific leaf area (SLA), leaf dry matter content (LDMC), leaf carbon content (LCC) and leaf nitrogen content (LNC). These traits were measured for the dominant species making up 90% of the total plant cover in each plot. The five traits on 10 individuals per species in each plot were obtained by using the standard methodologies [67]. We calculated\u0026nbsp;community-weighted means (CWM) of single-trait\u0026nbsp;by multiplying the trait value of each species by its relative biomass in the community\u0026nbsp;[68]. CWM can reflect the characteristics of community functional traits [69].\u0026nbsp;In each plot, three soil samples (0\u0026ndash;10 cm depth) were collected to determine soil water, and one mixed soil sample from three random replicates was collected to measure soil organic carbon and total nitrogen content. Leaf carbon and nitrogen content (%), as well as soil organic carbon and total nitrogen content (g Kg\u003csup\u003e-1\u003c/sup\u003e), were measured by using an Elemental Analyzer [24] (Costech ECS 4010, Italy) with a reduction temperature of 650\u0026deg;C and a combustion temperature of 980\u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe annual precipitation gradually decreased from 2015 to 2017, and increased in 2018 due to increased precipitation in July and August (Additional file 1 Figure S1). The precipitation in the early time of 2015-2018 growing season (March to June) was 56.2mm, 77.9mm, 28.8mm and 21.4 mm, respectively (Additional file 1 Figure S1), which decreased in an inter-annual timescale. Thus, we assess how experimental\u0026nbsp;drought and natural drought\u0026nbsp;in the early period of growing season\u0026nbsp;affected\u0026nbsp;structure and function of grassland ecosystems.\u003c/p\u003e\n\u003cp\u003eWe analyzed the response of each variable to extreme drought using separate repeated measures mixed model ANOVAs with year, treatment, and their interaction as fixed factor and block as a random factor (Additional file 1 Table S4). One-way ANOVA was conducted to assess the significant differences of species richness, Density, AGB, BGB, CWM of Height, CWM of SLA, CWM of LDMC, CWM of LCC, CWM of LNC, Soil Carbon, Soil Nitrogen, and Soil Water over to extreme drought among years. A level of P \u0026lt; 0.05 was considered significant. Data are presented as mean \u0026plusmn; standard error throughout.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThen, the simple regression models with a standard 95% confidence range were used to assess whether CWM of traits and soil factors could explain AGB and BGB. Based on the simple regression and the Correlation coefficients of each variable (Additional file 1 Table S3),\u0026nbsp;a structural equation modeling (SEM) was performed, in which drought treatment and\u0026nbsp;the precipitation in the early time were treated as exogenous variables; species diversity, CWM of\u0026nbsp;trait, and soil factors were considered as endogenous variables; AGB and BGB were regarded as the response variable. We assessed the best fitting model using a Chi-square test, root mean square error of approximation and goodness-of-fit index [19], which was performed by AMOS 20.0 (Amos Development, Spring House, PA, USA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData analysis and plotting were run with the SPSS16.0 and SigmaPlot12.0 for Windows statistics program, respectively. The simple regression models were performed using the\u003cem\u003e\u0026nbsp;trendline\u0026nbsp;\u003c/em\u003efunction in the \u003cem\u003ebasic Trendline\u0026nbsp;\u003c/em\u003epackage of R software (v4.0.0, R Core Team, 2020).\u003c/p\u003e"},{"header":"List of Abbreviations","content":"\u003cp\u003eAGB: aboveground biomass\u003c/p\u003e\n\u003cp\u003eBGB: belowground biomass\u003c/p\u003e\n\u003cp\u003eCWM: community-weighted means\u003c/p\u003e\n\u003cp\u003eSLA: specific leaf area\u003c/p\u003e\n\u003cp\u003eLDMC: leaf dry matter content\u003c/p\u003e\n\u003cp\u003eLCC: leaf carbon content\u003c/p\u003e\n\u003cp\u003eLNC: leaf nitrogen content\u003c/p\u003e\n\u003cp\u003eSoil N: soil nitrogen content\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis\u0026nbsp;study\u0026nbsp;was\u0026nbsp;supported\u0026nbsp;by\u0026nbsp;the\u0026nbsp;Second\u0026nbsp;Tibetan\u0026nbsp;Plateau\u0026nbsp;Scientific\u0026nbsp;Expedition and Research program (2019QZKK0305), National Natural Science Foundation of China (42071140 and 41622103) and Youth Innovation Promotion Association CAS (1100000036).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXiaoan Zuo and Qiang Yu designed this experiment;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;Ping Yue, Ya Hu, Xinxin Guo, Aixia Guo, and Chong Xu contributed significantly to analysis and manuscript preparation;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;Xiangyun Li performed the data analyses and wrote the manuscript;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;Xiaoan Zuo, Ping Yue, and Xueyong Zhao helped perform the analysis with constructive discussions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are very grateful to Dr. Julio Di Rienzo for the support of FDiversity software.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEasterling DR, Meehl GA, Parmesan C, Changnon SA, Karl TR, Mearns LO: Climate extremes: Observations, modeling, and impacts. \u003cem\u003eScience \u003c/em\u003e2000, 289(5487):2068-2074.\u003c/li\u003e\n\u003cli\u003eSmith MD: An ecological perspective on extreme climatic events: a synthetic definition and framework to guide future research. \u003cem\u003eJ Ecol \u003c/em\u003e2011, 99(3):656-663.\u003c/li\u003e\n\u003cli\u003eKnapp AK, Hoover DL, Wilcox KR, Avolio ML, Koerner SE, La Pierre KJ, Loik ME, Luo YQ, Sala OE, Smith MD: Characterizing differences in precipitation regimes of extreme wet and dry years: implications for climate change experiments. \u003cem\u003eGlobal Change Biol \u003c/em\u003e2015, 21(7):2624-2633.\u003c/li\u003e\n\u003cli\u003eCopeland SM, On SPH, Latimer AM, Damschen EI, Eskelinen AM, Fernandez-Going B, Spasojevic MJ, Anacker BL, Thorne JH: Ecological effects of extreme drought on Californian herbaceous plant communities. \u003cem\u003eEcol Monogr \u003c/em\u003e2016, 86(3):295-311.\u003c/li\u003e\n\u003cli\u003eFranklin J, Serra-Diaz JM, Syphard AD, Regan HM: Global change and terrestrial plant community dynamics. \u003cem\u003eP Natl Acad Sci USA \u003c/em\u003e2016, 113(14):3725-3734.\u003c/li\u003e\n\u003cli\u003eMa MJ, Collins SL, Du GZ: Direct and indirect effects of temperature and precipitation on alpine seed banks in the Tibetan Plateau. \u003cem\u003eEcol Appl \u003c/em\u003e2020, 30(5).\u003c/li\u003e\n\u003cli\u003eZhang H, Yu H, Zhou CT, Zhao HT, Qian XQ: Aboveground net primary productivity not CO2 exchange remain stable under three timing of extreme drought in a semi-arid steppe. \u003cem\u003ePlos One \u003c/em\u003e2019, 14(3).\u003c/li\u003e\n\u003cli\u003eHarrison S, Spasojevic MJ, Li DJ: Climate and plant community diversity in space and time. \u003cem\u003eP Natl Acad Sci USA \u003c/em\u003e2020, 117(9):4464-4470.\u003c/li\u003e\n\u003cli\u003eChen YX, Huang YY, Niklaus PA, Castro-Izaguirre N, Clark AT, Bruelheide H, Ma KP, Schmid B: Directed species loss reduces community productivity in a subtropical forest biodiversity experiment (Mar, 10.1038/s41559-020-1127-4, 2020). \u003cem\u003eNat Ecol Evol \u003c/em\u003e2020, 4(4):660-660.\u003c/li\u003e\n\u003cli\u003eGrace JB, Anderson TM, Seabloom EW, Borer ET, Adler PB, Harpole WS, Hautier Y, Hillebrand H, Lind EM, Partel M\u003cem\u003e et al\u003c/em\u003e: Integrative modelling reveals mechanisms linking productivity and plant species richness. \u003cem\u003eNature \u003c/em\u003e2016, 529(7586):390-+.\u003c/li\u003e\n\u003cli\u003eRabosky DL, Hurlbert AH: Species Richness at Continental Scales Is Dominated by Ecological Limits. \u003cem\u003eAm Nat \u003c/em\u003e2015, 185(5):572-583.\u003c/li\u003e\n\u003cli\u003eHarrison S, Spasojevic MJ, Li D: Climate and plant community diversity in space and time. \u003cem\u003eProc Natl Acad Sci U S A \u003c/em\u003e2020, 117(9):4464-4470.\u003c/li\u003e\n\u003cli\u003eWu GL, Zhang ZN, Wang D, Shi ZH, Zhu YJ: Interactions of soil water content heterogeneity and species diversity patterns in semi-arid steppes on the Loess Plateau of China. \u003cem\u003eJ Hydrol \u003c/em\u003e2014, 519:1362-1367.\u003c/li\u003e\n\u003cli\u003eLi Y, Dong S, Liu S, Su X, Wang X, Zhang Y, Zhao Z, Gao X, Li S, Tang L: Relationships between plant diversity and biomass production of alpine grasslands are dependent on the spatial scale and the dimension of biodiversity. \u003cem\u003eEcol Eng \u003c/em\u003e2019, 127:375-382.\u003c/li\u003e\n\u003cli\u003eWu GL, Liu Y, Tian FP, Shi ZH: Legumes Functional Group Promotes Soil Organic Carbon and Nitrogen Storage by Increasing Plant Diversity. \u003cem\u003eLand Degrad Dev \u003c/em\u003e2017, 28(4):1336-1344.\u003c/li\u003e\n\u003cli\u003eKimball S, Funk JL, Spasojevic MJ, Suding KN, Parker S, Goulden ML: Can functional traits predict plant community response to global change? 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New Phytol 2015, 206(2):660-671.\u003c/li\u003e\n\u003cli\u003eGuittar J, Goldberg D, Klanderud K, Telford RJ, Vandvik V: Can trait patterns along gradients predict plant community responses to climate change? Ecology 2016, 97(10):2791-2801.\u003c/li\u003e\n\u003cli\u003eCornelissen JHC, Lavorel S, Garnier E, Diaz S, Buchmann N, Gurvich DE, Reich PB, ter Steege H, Morgan HD, van der Heijden MGA et al: A handbook of protocols for standardised and easy measurement of plant functional traits worldwide. Aust J Bot 2003, 51(4):335-380.\u003c/li\u003e\n\u003cli\u003eKichenin E, Wardle DA, Peltzer DA, Morse CW, Freschet GT: Contrasting effects of plant inter- and intraspecific variation on community-level trait measures along an environmental gradient. Funct Ecol 2013, 27(5):1254-1261.\u003c/li\u003e\n\u003cli\u003eDebouk H, de Bello F, Sebastia MT: Functional Trait Changes, Productivity Shifts and Vegetation Stability in Mountain Grasslands during a Short-Term Warming. Plos One 2015, 10(10).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp style=\"margin:0in;text-align:justify;font-size:14px;font-family:DengXian;line-height:200%;\"\u003e\u003cstrong\u003e\u003cspan style='font-size:13px;line-height:200%;font-family:\"Times New Roman\",serif;'\u003eTable 1\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003cspan style='font-size:13px;line-height:200%;font-family:\"Times New Roman\",serif;'\u003eThe total, direct and indirect standardized effects on above- and belowground biomass from the structural equation model.\u003c/span\u003e\u003c/p\u003e\n\u003ctable style=\"border: none;width:210.2pt;border-collapse:collapse;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-color: black white;border-style: solid;border-width: 1pt;padding: 0.05in 0.1in;height: 18.15pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePredictor\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: 1pt solid black;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 18.15pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePathways\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: 1pt solid black;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 18.15pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cstrong\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;Effect\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 210.2pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eAboveground biomass\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eDrought\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eDirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-0.40\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eIndirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-0.24\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eTotal\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-0.64\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePrecipitation\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eDirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.25\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eIndirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.08\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eTotal\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.33\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eHeight\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eDirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.20\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eIndirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNS\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eTotal\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.20\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eSpecies richness\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eDirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.28\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eIndirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNS\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eTotal\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.28\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 210.2pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eBelowground biomass\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eSoil nitrogen content\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eDirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-0.32\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eIndirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eNS\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eTotal\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-0.32\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003ePrecipitation\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eDirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-0.71\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eIndirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.03\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eTotal\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e-0.67\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eHeight\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eDirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49.8pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e0.09\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94.05pt;border-right: 1pt solid white;border-bottom: 1pt solid white;border-left: 1pt solid white;border-image: initial;border-top: none;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.3pt;border-top: none;border-left: none;border-bottom: 1pt solid white;border-right: 1pt solid white;padding: 0.05in 0.1in;height: 17pt;vertical-align: top;\"\u003e\n \u003cp style=\"margin:0in;text-align:left;font-size:14px;font-family:DengXian;\"\u003e\u003cspan style='font-size:11px;font-family:\"Times New Roman\",serif;'\u003eIndirect\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n 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Evolution](http://bmcevolbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/evob/default.aspx","title":"BMC Ecology and Evolution","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Precipitation changes, Biodiversity, Plant traits, Allocation of biomass","lastPublishedDoi":"10.21203/rs.3.rs-284808/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-284808/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eIncreasing drought induced by global climate changes is altering the structure and function of grassland ecosystems. However, there is a lack of understanding of how drought affects the allocation and trade-off of above- and belowground biomass in desert steppe. We conducted a four-year (2015-2018) drought experiment to examine the responses of community above-and belowground biomass (AGB and BGB) to manipulated drought and natural drought in the early period of growing season (from March to June) in a desert steppe. We compared the associations of drought with species diversity (species richness and density), community-weighted means (CWM) of five traits, and soil factors (soil Water, soil carbon content, and soil nitrogen content) for grass communities. Meanwhile, we used the structural equation modeling (SEM) to elucidate whether drought affects AGB and BGB by altering species diversity, functional traits and soil factors.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e We found that drought reduced the species richness, and species modified the CWM of traits to cope with drought. Manipulated drought had the effect on soil water content, but not on soil carbon and nitrogen content. We also found that the experimental and natural drought decreased AGB, while natural drought increased BGB. AGB was correlated with species richness, density, plant height and soil water, while BGB was correlated with CWM of plant height, CWM of specific leaf area, CWM of leaf dry matter content, CWM of leaf nitrogen content, soil water, soil carbon and nitrogen content. The SEM results indicated that the experimental and natural drought indirectly decreased AGB by reducing species richness and plant height, while natural drought and soil nitrogen content directly affected BGB. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThese results suggest that species richness and functional traits can modulate the effects of drought on AGB, however natural drought and soil nitrogen determine BGB. Our findings demonstrate that the long-term observation and experiment are necessary to understand the underlying\u0026nbsp;mechanism of the allocation and trade-off of community above-and belowground biomass.\u003c/p\u003e","manuscriptTitle":"Drought of early time in growing season decreases community aboveground biomass, but increases belowground biomass in a desert steppe","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-03-13 00:13:40","doi":"10.21203/rs.3.rs-284808/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-04-15T00:26:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-04-12T07:04:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-04-06T05:30:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"348b3577-f3e6-48ad-a72d-c063e0872b2a","date":"2021-04-01T05:34:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"ef40016e-fd35-427d-a33c-c122525fbe84","date":"2021-03-30T02:32:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-03-18T15:57:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-03-18T10:33:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-03-15T01:27:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-03-01T02:16:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Ecology and Evolution","date":"2021-02-28T04:35:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-ecology-and-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"evob","sideBox":"Learn more about [BMC Ecology and Evolution](http://bmcevolbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/evob/default.aspx","title":"BMC Ecology and Evolution","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7ebea89f-1dc3-4de6-9cb2-c413d34e3f17","owner":[],"postedDate":"March 13th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":2936783,"name":"Ecological Modeling"},{"id":2936784,"name":"Terrestrial Ecology"}],"tags":[],"updatedAt":"2021-05-25T07:44:11+00:00","versionOfRecord":[],"versionCreatedAt":"2021-03-13 00:13:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-284808","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-284808","identity":"rs-284808","version":["v1"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}