Drylands Of China Research Articles

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China

The drylands of China cover approximately 6.6×106 km2 and are home to approximately 5.8×108 people, providing important ecosystem services for human survival and development. However, dryland ecosystems are extremely fragile and sensitive to external environmental changes. Land use and land cover (LULC) changes significantly impact soil structure and function, thus affecting the soil multifunctionality (SMF). However, the effect of LULC changes on the SMF in the drylands of China has rarely been reported. In this study, we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center. We explored the drivers of the SMF changes under different LULC types (including forest, grassland, shrubland, and desert) and used structural equation modeling to explore the main driver of the SMF changes. The results showed that the SMF under the four LULC types decreased in the following descending order: forest, grassland, shrubland, and desert. The main driver of the SMF changes under different LULC types was mean annual temperature (MAT). In addition to MAT, pH in forest, soil moisture (SM) and soil biodiversity index in grassland, SM in shrubland, and aridity index in desert are crucial factors for the SMF changes. Therefore, the SMF in the drylands of China is regulated mainly by MAT and pH, and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes. The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

A New Merged Product Reveals Precipitation Features over Drylands in China

Due to the considerable uncertainties inherent in the datasets describing the spatiotemporal distributions of precipitation in the drylands of China, this study presents a new merged monthly precipitation product with a spatial resolution of approximately 0.2° × 0.2° during 1980–2019. The newly developed precipitation product was validated at different temporal scales (e.g., monthly, seasonally, and annually). The results show that the new product consistently aligns with the spatiotemporal distributions reported by the Chinese Meteorological Administration Land Data Assimilation System (CLDAS) product and Multi-Source Weighted Ensemble Precipitation (MSWEP). The merged product exhibits exceptional quality in describing the drylands of China, with a bias of −2.19 mm month−1 relative to MSWEP. In addition, the annual trend of the merged product (0.09 mm month−1 yr−1) also closely aligns with that of the MSWEP (0.11 mm month−1 yr−1) during 1980–2019. The increasing trend indicates that the water cycle and wetting process intensified in the drylands of China during this period. In particular, there was an increase in wetting during the period from 2001–2019. Generally, the merged product exhibits potential value for improving our understanding of the climate and water cycle in the drylands of China.

Capturing woody aboveground biomass historical change and potential under climate change using Landsat time-series for afforestation in dryland of China

Capturing long-term dynamics and the potential under climate change of woody aboveground biomass (AGB) is imperative for calculating and raising carbon sequestration of afforestation in dryland. It is always been a great challenge to accurately capture AGB dynamics of sparse woody vegetation mixed with grassland using only Landsat time-series, resulting in changing trajectory of woody AGB estimates cannot accurately reflect woody vegetation growth regularity in dryland. In this study, surface reflectance (SR) sensitive to woody AGB was firstly selected and interannual time-series of composited SR was smoothed using S-G filter for each pixel, and then optimal machine learning algorithm was selected to estimate woody AGB time-series. Pixels that have reached AGB potential were detected based on the AGB changing trajectory, and the potential was spatial-temporal extended using random forest model combining environmental variables under current climate condition and CMIP6 climate models. Results show that: 1) minimum value composite based on NIRv during Jul.-Sep. is more capable of explaining woody AGB variation in dryland (R = 0.87, p < 0.01), and Random Forest (RF) model has the best performance in estimating woody AGB (R2 = 0.75, RMSE = 4.74 t·ha−1) among sis commonly used machine learning models. 2) Annual woody AGB estimates can be perfectly fitted with a logistic growth curve (R2 = 0.97, p < 0.001) indicating explicit growth regularity of woody vegetation, which provides physiological foundation for determining woody AGB potential. 3) Woody AGB potential can be accurately simulated by RF combining environmental variables (R2 = 0.95, RMSE = 2.89 t·ha−1), and current woody AGB still has a potential of small increase, whereas the overall losses of woody AGB potential were observed in 2030, 2040 and 2050 under CMIP6 SSP-RCP scenarios.

Responses of Soil C, N, P and Enzyme Activities to Biological Soil Crusts in China: A Meta-Analysis.

Biological soil crusts (BSCs) are often referred to as the "living skin" of arid regions worldwide. Yet, the combined impact of BSCs on soil carbon (C), nitrogen (N), phosphorus (P), and enzyme activities remains not fully understood. This study identified, screened and reviewed 71 out of 2856 literature sources to assess the responses of soil C, N, P and enzyme activity to BSCs through a meta-analysis. The results indicated that BSC presence significantly increased soil C, N, P and soil enzyme activity, and this increasing effect was significantly influenced by the types of BSCs. Results from the overall effect showed that soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), total phosphorus (TP), and available phosphorus (AP) increased by 107.88%, 84.52%, 45.43%, 27.46%, and 54.71%, respectively, and four soil enzyme activities (Alkaline Phosphatase, Cellulase, Sucrase, and Urease) increased by 93.65-229.27%. The highest increases in SOC, TN and AN content occurred in the soil covered with lichen crusts and moss crusts, and significant increases in Alkaline Phosphatase and Cellulase were observed in the soil covered with moss crusts and mixed crusts, suggesting that moss crusts can synergistically enhance soil C and N pool and enzyme activity. Additionally, variations in soil C, N, P content, and enzyme activity were observed under different environmental settings, with more pronounced improvements seen in coarse and medium-textured soils compared to fine-textured soils, particularly at a depth of 5 cm from the soil surface. BSCs in desert ecosystems showed more significant increases in SOC, TN, AN, and Alkaline Phosphatase compared to forest and grassland ecosystems. Specifically, BSCs at low altitude (≤500 m) with an annual average rainfall of 0-400 mm and an annual average temperature ≤ 10 °C were the most conducive to improving soil C, N, and P levels. Our results highlight the role of BSCs and their type in increasing soil C, N, P and enzyme activities, with these effects significantly impacted by soil texture, ecosystem type, and climatic conditions. The implications of these findings are crucial for soil enhancement, ecosystem revitalization, windbreak, and sand stabilization efforts in the drylands of China.

C:N:P stoichiometric characteristics and drivers of surface soil in the drylands of China

C:N:P stoichiometric characteristics and drivers of surface soil in the drylands of China

Evaluating soil acidification risk and its effects on biodiversity–ecosystem multifunctionality relationships in the drylands of China

BackgroundSoil acidification caused by anthropogenic activities may affect soil biochemical cycling, biodiversity, productivity, and multiple ecosystem-related functions in drylands. However, to date, such information is lacking to support this hypothesis. MethodsBased on a transect survey of 78 naturally assembled shrub communities, we calculated acid deposition flux in Northwest China and evaluated its likely ecological effects by testing three alternative hypotheses, namely: niche complementarity, mass ratio, and vegetation quantity hypotheses. Rao's quadratic entropy and community-weighted mean traits were employed to represent the complementary aspect of niche complementarity and mass ratio effects, respectively. ResultsWe observed that in the past four decades, the concentrations of exchangeable base cations in soil in Northwest China have decreased significantly to the extent of having faced the risk of depletion, whereas changes in the calcium carbonate content and pH of soil were not significant. Acid deposition primarily increased the aboveground biomass and shrub density in shrublands but had no significant effect on shrub richness and ecosystem multifunctionality (EMF), indicating that acid deposition had positive but weak ecological effects on dryland ecosystems. Community weighted mean of functional traits (representing the mass ratio hypothesis) correlated negatively with EMF, whereas both Rao's quadratic entropy (representing the niche complementarity hypothesis) and aboveground biomass (representing the vegetation quantity hypothesis) correlated positively but insignificantly with EMF. These biodiversity–EMF relationships highlight the fragility and instability of drylands relative to forest ecosystems. ConclusionsThe findings from this study serve as important reference points to understand the risk of soil acidification in arid regions and its impacts on biodiversity–EMF relationships.

Optimized NPK fertilizer recommendations based on topsoil available nutrient criteria for wheat in drylands of China

The optimized management of crop fertilization is very important for improving crop yield and reducing the consumption of chemical fertilizers. Critical nutrient values can be used for evaluating the nutritional status of a crop, and they reflect the nutrient concentrations above which the plant is sufficiently supplied for achieving the maximum potential yield. Based on on-farm surveys of 504 farmers and 60 field experimental sites in the drylands of China, we proposed a recommended fertilization method to determine nitrogen (N), phosphorus (P), and potassium (K) fertilizer input rates for wheat production, and then validated the method by a field experiment at 66 different sites in northern China. The results showed that wheat grain yield varied from 1.1 to 9.2 t ha−1, averaging 4.6 t ha−1, and it had a quadratic relationship with the topsoil (0−20 cm) nitrate N and soil available P contents at harvest. However, yield was not correlated with the inputs of N, P, and K fertilizers. Based on the relationship (exponential decay model) between 95–105% of the relative yield and topsoil nitrate N, available P, and available K contents at wheat harvest from 60 field experiments, the topsoil critical nutrient values were determined as 34.6, 15.6, and 150 mg kg−1 for soil nitrate N, available P, and available K, respectively. Then, based on five groups of relative yield (>125%, 115–125%, 105–115%, 95–105%, and <95%) and the model, the five groups of topsoil critical nutrient levels and fertilization coefficients (Fc) were determined. Finally, we proposed a new method for calculating the recommended fertilizer input rate as: Fr=Gy×Nr×Fc, where Fr is the recommended fertilizer (N/P/K) input rate; Gy is the potential grain yield; Nr is the N(NrN), P(NrP), and K(NrK) nutrient requirements for wheat to produce 1,000 kg of grain; and Fc is a coefficient for N(Nc)/P(Pc)/K(Kc) fertilizer. A 2-year validated experiment confirmed that the new method reduced N fertilizer input by 17.5% (38.5 kg N ha−1) and P fertilizer input by 43.5% (57.5 kg P2O5 ha−1) in northern China and did not reduce the wheat yield. This outcome can significantly increase the farmers’ benefits (by 7.58%, or 139 US$ ha−1). Therefore, this new recommended fertilization method can be used as a tool to guide N, P, and K fertilizer application rates for dryland wheat production.

Impacts of re-vegetation on soil water dynamics in a semiarid region of Northwest China

Understanding how vegetation (shrub) cover in drylands affects local-to-regional soil water dynamics and associated water balances is of immense importance because of the abundance of afforestation projects worldwide. Vegetation's role in the control of soil water presents a particular challenge to soil water storage (SWS) management in the drylands of China. To address this knowledge gap, we conducted a two-year study in the Mu Us Desert of northwest China. The study involved the acquisition of in-situ soil water measurements within the first 180 cm of soil at three sand dune sites characterized by their differences in % shrub cover. The sand dunes varied from a vegetation-free, bare-ground sand dune site (BF) and two partly vegetated sites, one with medium-level (40 %) and another with high shrub cover (80 %; MF and HF, respectively). Results revealed that the site with the high shrub cover (HF) suffered a net reduction in soil water content (SWC) by up to 32.7 and 39.8 % in the shallow and deep subsoil (0–100 and 100–180 cm), respectively, when compared to corresponding changes at the BF site. Soil water content was shown to be largely influenced by site properties, namely shrub biomass and litter density (p < 0.05). Due to aboveground vegetation and rainfall interception by the litter, 32.2 mm of effective rainfall was reduced to the soil for every 10 %-increase in shrub cover. Bands of soil water depletion during the dry year did not fully recover during the following wet year, resulting in the development of a dried soil layer with an average SWC of 4.6–7.8 %. Increased evapotranspiration (ETtotal) led to a decrease in SWS and relative extractable soil water (REW), which caused ETtotal at HF to be lower than the rate observed at MF. These findings highlight the need for improvements in current restoration strategies, meant at striking a balance between vegetation restoration and SWC by developing optimal plant-community cover and mosaicked vegetation systems.

Distinguishing natural and anthropogenic contributions to biological soil crust distribution in China's drylands

Desertification caused by natural factors and human activities seriously threatens dryland biological communities. However, the impact of these factors on non-vascular plants in drylands has not been fully documented. This study proposed a framework to distinguish the natural and anthropogenic contributions to the distribution of the biological soil crust (BSC) coverage. The 20 model-simulated environmental datasets, including climate, soil characteristics and terrain, were selected to explore the internal relationship between these environmental drivers and BSC coverage. Random forest classification and regression models were developed to calculate the BSC coverage in the drylands of China under natural conditions. By subtracting the predicted natural BSC coverage from the observed BSC coverage, the spatial distribution of changes in BSC coverage attributed to human activities was mapped. The results showed that in the limited vegetation areas of China's drylands, human activities had a positive impact on BSC coverage in only 11.3 % of the regions while having a negative effect on 25.4 % of the regions. Moreover, human activities led to a 33 % reduction in BSC coverage in these regions. The positive impacts of large-scale ecological restoration projects on BSC coverage in the drylands of China were limited due to land use changes caused by human economic activities. This framework provides support for assessing regional variations in anthropogenic impacts on dryland BSC communities and contributes to the development of appropriate dryland management policies.

Climate and human impact together drive changes in ecosystem multifunctionality in the drylands of China

China's drylands encompass an area of approximately 6.60 × 106 km2 and are home to around 580 million people, providing crucial ecosystem services. The escalating impacts of global climate change are expected to exacerbate aridity, thereby adversely affecting ecosystem services and human well–being. Hence, there is a crucial need to prioritize the study of ecosystem multifunctionality (EMF) in drylands and investigate the underlying factors driving EMF changes. We collected field sampling and indoor analysis data, as well as raster level sampling data to obtain indices related to soil nutrients, vegetation, human footprint index (HFI), soil biodiversity index (SBI), and climate (mean annual temperature [MAT], mean annual precipitation [MAP], potential evapotranspiration [PET]), and soil characteristics (soil sand content [Sand], soil moisture [SM], soil pH). EMF was calculated using the averaging approach, and the cluster–multi–threshold approach. We employed the mantel test, mixed–effects model, random forest algorithm, piecewise structural equation model, and variation partition analysis to explore the significance of factors on EMF changes. The findings revealed significant correlations between EMF and all factors except pH and Sand. All factors collectively accounted for 52.7 %–57.4 % of the variation in mono– (the effect on each of the carbon, nitrogen and phosphorus functions separately) and multifunctionality. The combined effects of all factors had the greatest contribution (8.1 %–16.3 %) variation in EMF. HFI consistently emerged as the most important factor in controlling EMF variation and proved to be the most significant predictor of EMF changes. All factors examined were significant predictors of EMF change. Our study demonstrated that HFI played the most direct influence on EMF changes, surpassing the impact of any single variable. However, the overall contribution of climate (integrating MAP, MAT, and PET) to EMF change was also extremely important. Therefore, future assessments and predictions of ecological functions in drylands should consider not only the direct effects of climate change but also the integrated analysis of human impact.

Aridification alters the diversity of airborne bacteria in drylands of China

Dryland ecosystems, which vary sensitively to drought owing to climate change and human activities, frequently cause large-scale aeolian dispersal of terrestrial-mineral and biological particles. To date, very few studies have focused on the atmosphere-land exchange of bacteria in drylands. To understand the bacterial transport from the terrestrial environment to the atmosphere over drylands, soil and aerosol samples were collected at 19 sites in arid and semi-arid regions across drylands of China in the summer of 2017. The 16S rRNA gene sequencing revealed that the bacterial diversity in the atmosphere was significantly lower than that in terrestrial ecosystems for all the collected samples. Moreover, bacterial diversity in the atmosphere increases in arid regions compared to semi-arid regions, while those of the terrestrial environment were maintained regardless of the region. Additionally, the terrestrial bacterial sources contributed to the airborne bacteria more significantly in arid regions than those in semi-arid regions (accounting for 10.0 ± 1.1% and 3.5 ± 1.1%, respectively). The arid conditions tended to enhance the atmospheric emissions of Chloroflexi, while the members of Bacteroidetes were dominant in both the atmospheres of the semi-arid and arid regions. The differences in bacterial community structures between the terrestrial and atmospheric ecosystems are thought to depend on the ground surface characteristics such as vegetation and terrestrial substrates. Meteorological drought may alter terrestrial characteristics, which regulate airborne bacterial dispersal from dryland to its downwind regions, suggesting that more attention should be paid to the bacterial roles in the biology-health-climate process in the future.

Quantifying the policy-driven large scale vegetation restoration effects on evapotranspiration over drylands in China

Evapotranspiration (ET) is a key variable in the water cycle and reflects the ecosystem's feedback into the climate system. However, quantitative studies on the response of ET to large-scale vegetation restoration projects and climate change are still lacking, especially in drylands. To address this deficiency, this research examined the variation in ET since the implementation of restoration projects in the drylands of China in 2000–2018, and utilized quantitative analysis methods to investigate the effects of six environmental factors, including temperature (TEM), precipitation (PRE), solar radiation (RAD), vapour pressure deficit (VPD), soil moisture (SM), and leaf area index (LAI) on ET. Furthermore, a new method was proposed to detect the ET change caused by land use and land cover change (LUCC). The results indicated that ET showed a significant increasing trend (3.54 mm yr−1) during 2000–2018, and PRE was identified as a main influential factor with an ET contribution rate of more than 50%, especially in areas with insignificant vegetation greening. Additionally, the LAI had a major positive impact on ET in the areas of significant vegetation greening, and the contribution rate was nearly 40%. Furthermore, large-scale vegetation restoration expanded the area of high-transpiration vegetation types, and the ΔET (net variable quantity of ET caused by LUCC) increased obviously especially for the changes from cropland and grassland to forest, and barren land to grassland. These findings provide a new perspective for future assessments and further decision making regarding vegetation restoration projects in drylands.

Variations and driving factors of leaf functional traits in the dominant desert plant species along an environmental gradient in the drylands of China

Leaf functional traits (LFTs) of desert plants are responsive, adaptable and highly plastic to their environment. However, the macroscale variation in LFTs and driving factors underlying this variation remain unclear, especially for desert plants. Here, we measured eight LFTs, including leaf carbon concentration (LCC), leaf nitrogen concentration (LNC), leaf phosphorus concentration (LPC), specific leaf area (SLA), leaf dry matter content (LDMC), leaf mass per area (LMA), leaf thickness (LTH) and leaf tissue density (LTD) across 114 sites along environmental gradient in the drylands of China and in Guazhou Common Garden and evaluated the effect of environment and phylogeny on the LFTs. We noted that for all species, the mean values of LCC, LNC, LPC, SLA, LDMC, LMA, LTH and LTD were 384.62 mg g−1, 19.91 mg g−1, 1.12 mg g−1, 79.62 cm2 g−1, 0.74 g g−1, 237.39 g m−2, 0.38 mm and 0.91 g cm−3, respectively. LFTs exhibited significant geographical variations and the LNC, LMA and LTH in the plants of Guazhou Common Garden were significantly higher than the field sites in the drylands of China. LDMC and LTD of plants in Guazhou Common Garden were, however, considerably lower than those in the drylands of China. LCC, LPC, LTH and LTD differed significantly among different plant lifeforms, while LNC, SLA, LDMC and LMA didn't show significant variations. We found that the environmental variables explained higher spatial variations (3.6–66.3 %) in LFTs than the phylogeny (1.8–54.2 %). The LCC significantly increased, while LDMC and LTD decreased with increased temperature and reduced precipitation. LPC, LDMC, LMA, and LTD significantly increased, while SLA and LTH decreased with increased aridity. However, leaf elements were not significantly correlated with soil nutrients. The mean annual precipitation was a key factor controlling variations in LFTs at the macroscale in the drylands of China. These findings will provide new insights to better understand the response of LFTs and plants adaptation along environmental gradient in drylands, and will serve as a reference for studying biogeographic patterns of leaf traits.

Dryland agricultural expansion leads to lower content and higher variability of soil inorganic carbon in topsoil

Soil inorganic carbon (SIC) is of key importance to the global carbon cycle and mitigating climate change. However, decades of agricultural expansion in the drylands have resulted in vast and fragmented agricultural landscapes and have potentially affected SIC. Previous studies investigating the impact of agricultural expansion on SIC have primarily focused on cultivation impacts, while ignoring edge effects from agricultural land boundaries. Here, we combined cultivation impacts with edge effects and fully evaluated the impacts of agricultural expansion on SIC. We conducted spatial statistical and buffer analyses using a SIC distribution map, which was developed using 388 sample points in 0 – 20 cm topsoil over the Sangong River watershed in drylands of China. We found that decades-long agricultural expansion resulted in lower content and higher variability of SIC in topsoil. Specifically, cultivation decreased SIC content by 28.57% (1.64 g kg−1) and increased SIC variability by 95.71% (0.67 g kg−1) in agricultural lands. Edge effects altered SIC content by − 1.95–11.51% (−0.11 to 0.54 g kg−1) and increased SIC variability by 39.14% (0.34 g kg−1) at edges. In addition, we found that fewer sampling points in areas with high SIC variability (e.g., agricultural lands and edges) decreased the estimation accuracy. Our study highlights the need for SIC conservation during dryland agricultural expansion. Also, it suggests that as many sampling points as possible should be set in high variability areas, which is especially useful for accurately estimating SIC distribution in drylands.

Plant trait networks reveal adaptation strategies in the drylands of China

BackgroundPlants accomplish multiple functions by the interrelationships between functional traits. Clarifying the complex relationships between plant traits would enable us to better understand how plants employ different strategies to adapt to the environment. Although increasing attention is being paid to plant traits, few studies focused on the adaptation to aridity through the relationship among multiple traits. We established plant trait networks (PTNs) to explore the interdependence of sixteen plant traits across drylands.ResultsOur results revealed significant differences in PTNs among different plant life-forms and different levels of aridity. Trait relationships for woody plants were weaker, but were more modularized than for herbs. Woody plants were more connected in economic traits, whereas herbs were more connected in structural traits to reduce damage caused by drought. Furthermore, the correlations between traits were tighter with higher edge density in semi-arid than in arid regions, suggesting that resource sharing and trait coordination are more advantageous under low drought conditions. Importantly, our results demonstrated that stem phosphorus concentration (SPC) was a hub trait correlated with other traits across drylands.ConclusionsThe results demonstrate that plants exhibited adaptations to the arid environment by adjusting trait modules through alternative strategies. PTNs provide a new insight into understanding the adaptation strategies of plants to drought stress based on the interdependence among plant functional traits.

Dynamic Assessment and Sustainability Strategies of Ecological Security in the Irtysh River Basin of Xinjiang, China.

The drylands of China are extensive, and they are home to more than one-third of the country's population. However, the watershed territories of the drylands, where the majority of human activities are concentrated have long experienced strained human-land relationships, culminating in ecological security concerns. Correspondingly, it is essential to carry out a comprehensive assessment of the ecological security of dryland watersheds and to identify the key factors influencing ecological security in order to formulate strategies that ensure the sustainability of drylands. Premised on the Driving-Pressure-State-Impact-Response (DPSIR) model, this study developed an ecological security index and applied it to the Irtysh River Basin of Xinjiang, China, from 2000 to 2020. The obstacle degree model was applied to reveal the obstacles in two dimensions: criterion level and indicator level. The findings suggested that the ecological security comprehensive index in the Irtysh River Basin has increased significantly from 2000 to 2020, irrespective of the fact that it decreased during the study period and then increased. The ecological security level changed from 'critically safe' in 2000 to 'general safety' in 2020, with the state subsystem and pressure subsystem becoming ecological security weaknesses. The primary factors influencing the ecological security of the study area were water consumption, the area of high-efficiency water-saving irrigation, the proportion of wetland area, vegetation coverage, and livestock population. The ecological security of different counties in the basin varies greatly, whereas the factors that influence ecological security showed both similarities and differences among the counties. In light of on the findings, we proposed that future strategies for ecological security enhancement should concentrate on enacting the policy of localizing spatial differentiation, optimizing industrial structure, strengthening scientific and technological support in the field of water conservation, bolstering the treatment capacity of environmental facilities, and implementing the Mountains-Rivers-Forests-Farmlands-Lakes-Grasslands System to support the sustainable development of dryland watersheds.

Concentrations and bioconcentration factors of leaf microelements in response to environmental gradients in drylands of China.

Determining response patterns of plant leaf elements to environmental variables would be beneficial in understanding plant adaptive strategies and in predicting ecosystem biogeochemistry processes. Despite the vital role of microelements in life chemistry and ecosystem functioning, little is known about how plant microelement concentrations, especially their bioconcentration factors (BCFs, the ratio of plant to soil concentration of elements), respond to large-scale environmental gradients, such as aridity, soil properties and anthropogenic activities, in drylands. The aim of the present study was to fill this important gap. We determined leaf microelement BCFs by measuring the concentrations of Mn, Fe, Ni, Cu and Zn in soils from 33 sites and leaves of 111 plants from 67 species across the drylands of China. Leaf microelement concentrations were maintained within normal ranges to satisfy the basic requirements of plants, even in nutrient-poor soil. Aridity, soil organic carbon (SOC) and electrical conductivity (EC) had positive effects, while soil pH had a negative effect on leaf microelement concentrations. Except for Fe, aridity affected leaf microelement BCFs negatively and indirectly by increasing soil pH and SOC. Anthropogenic activities and soil clay contents had relatively weak impacts on both leaf microelement concentrations and BCFs. Moreover, leaf microelement concentrations and BCFs shifted with thresholds at 0.89 for aridity and 7.9 and 8.9 for soil pH. Woody plants were positive indicator species and herbaceous plants were mainly negative indicator species of leaf microelement concentrations and BCFs for aridity and soil pH. Our results suggest that increased aridity limits the absorption of microelements by plant leaves and enhances leaf microelement concentrations. The identification of indicator species for the response of plant microelements to aridity and key soil characteristics revealed that woody species in drylands were more tolerant to environmental changes than herbaceous species.

Precipitation preferences alter the relative importance of herbaceous plant diversity for multifunctionality in the drylands of China

BackgroundMultiple components of biodiversity are excellent predictors of precipitation-induced changes in ecosystem function. However, the importance of differing scales (alpha versus beta) is usually overlooked in biodiversity–ecosystem multifunctionality studies. Consequently, little is known about how precipitation regulates the relationship between multifunctionality and multiple components of alpha and beta diversity.AimsWe investigated geographic patterns of herbaceous plant diversity and ecosystem multifunctionality along a precipitation gradient spanning more than 2010 km in Northwest China.MethodsWe assessed the effects of herbaceous species, phylogenetic, and functional components at different scales on multifunctionality in drylands.ResultsThe alpha diversity of species and functional beta diversity were key components explaining the variation in multifunctionality. As the main environmental factor, MAP (mean annual precipitation) affected multifunctionality by changing the mediating variables (i.e., species alpha and functional beta diversity). More importantly, a certain precipitation threshold was detected for the relationship of multifunctionality to species alpha and functional beta diversity. MAPs of approximately 158 mm and 140 mm modulated this relationship (shifting it from uncorrelated to significantly correlated).ConclusionsOur findings provide insights into previously neglected mechanisms by which diversity in herbaceous layers at different scales affects ecosystem multifunctionality. It is highlighted that MAP regulates the relationship between diversity and multifunctionality in dryland ecosystems at different scales. Further, diversity may have substantial consequences for multifunctionality where MAP is higher. These empirical results provide a comprehensive understanding of the biodiversity–multifunctionality relationship in the context of precipitation, ultimately contributing to conservation and restoration programs for multifunctionality in drylands.

Vegetation restoration dominates increase in water use efficiency in drylands of China

Dryland ecosystems are crucial components within the Earth and atmospheric systems, and a number of projects have been implemented to restore vegetation in drylands in the recent years. However, these regions are experiencing extreme climatic changes, and the impact of these projects are unclear. To gain a better understanding of the effectiveness of these projects, we employed water use efficiency (WUE), the ratio of gross primary production (GPP) to terrestrial evapotranspiration (ET), to predict future dryland ecosystem dynamics, and detected the underlying causes of WUE changes. We analysed the WUE trends and the decomposed components of WUE, namely the GPP to plant transportation ratio (GPP/T) and the plant transportation to terrestrial evapotranspiration (T/ET) ratio, between 2003 and 2018 in China’s drylands. The results indicated that 70.3 % of the study area had an upward WUE trend, and T/ET was the dominant factor of the WUE trend in 74.9 % of the areas investigated. Furthermore, the increase in T/ET was associated with growth in leaf area index (LAI). The rising WUE rate in the vegetation restoration project areas was significantly higher than that in other areas along with the drought gradient (P < 0.05), which indicated WUE increasing was strongly influenced by the increase in LAI resulting from vegetation restoration. Thus, our research affirms that vegetation restoration greatly influences WUE increase. However, over time, WUE in these restored drylands is likely to decrease due to increased VPD and plantation saturation, so future strategies for vegetation restoration in drylands are therefore required.

Spatial variability and driving factors of soil multifunctionality in drylands of China

Drylands are highly vulnerable to climate change and human activities. The drylands of China account for approximately 10.8% of global drylands, and China is the country most severely affected by aridity in Asia. Therefore, studying the spatial variation characteristics in soil multifunctionality (SMF) and investigating the driving factors are critical for elucidating and managing the functions of dryland ecosystems in China. Based on the environmental factors (mean annual precipitation (MAP), mean annual temperature (MAT), solar radiation (Srad), soil acidity (pH), enhanced vegetation index (EVI), and cation exchange capacity (CEC)) and aridity from the Dataset of soil properties for land surface modeling over China, we used non-linear regression, ordinary least square (OLS) regression, structural equation model (SEM), and other analytical methods to investigate the relationships of SMF with environmental factors across different aridity levels in China. SMF in different dryland regions varied significantly and showed a patchy distribution, with SMF index values ranging from −1.21 to 2.42. Regions with SMF index values from −0.20 to 0.51 accounting for 63.0% of dryland area in China. OLS regression results revealed that environmental factors like MAP, MAT, Srad, pH, EVI, and CEC were significantly related to SMF (P ​< ​0.05). MAP and MAT were correlated to SMF at the whole aridity level (P ​< ​0.05). SEM results showed that the driving factors of SMF differed depending on the aridity level. Soil pH was the strongest driving factor of SMF when the aridity was less than 0.80 (P ​< ​0.001). Both soil CEC and EVI had a positive effect on SMF when aridity was greater than 0.80 (P ​< ​0.01), with soil CEC being the strongest driving factor. The importance ranking revealed that the relative importance contribution of soil pH to SMF was greatest when aridity was less than 0.80 (66.9%). When aridity was set to greater than 0.80, the relative importance contributions of CEC and EVI to SMF increased (45.1% and 31.9%, respectively). Our findings indicated that SMF had high spatial heterogeneity in drylands of China. The aridity threshold controlled the impact of environmental factors on SMF.