Drylands contribute disproportionately to observed global productivity increases

Driving mechanism of natural vegetation response to climate change in China from 2001 to 2022

Understanding driving mechanism of natural vegetation response to climate change is crucial for maintaining vegetation stability. In this study, driving mechanism of natural vegetation sensitivity to precipitation (SVP) and temperature (SVT) changes in China were analyzed based on Normalized Difference Vegetation Index (NDVI), Solar-induced Chlorophyll Fluorescence (SIF), Dead Fuel Index (DFI), and climate, hydrological, and CO2 data. Results showed that NDVI and SIF significantly increased but DFI significantly decreased from 2001 to 2022, with proportion of over 67 % of natural vegetation area. The SVP of NDVI (SVPN) and DFI (SVPD) of natural vegetation decreased while SVP of SIF (SVPS) increased during 2001-2022, with average of -6.8 × 10-5/mm, -9.9 × 10-3/mm, and 2.3 × 10-5/mm, respectively. The SVPN and SVPD decreased from arid to humid regions, SVPS was high in semi-arid and semi-humid regions. The SVP was correlated with precipitation, runoff, CO2 and surface soil moisture (SSM), and their correlation was higher in drier regions. The SVT of NDVI (SVTN) of natural vegetation increased while SVT of SIF (SVTS) and DFI (SVTD) decreased during 2001-2022, with average of 13.3 × 10-3/°C, 7 × 10-3/°C, and -1.2/°C, respectively. And there was no significant spatial variation of SVT in different climate regions. The SVT was correlated with aridity index (AI), potential evapotranspiration (PET), temperature and SSM. The explanation of climate, hydrological, and CO2 for SVP and SVT was over 64 %, especially for SVTD at 76.2 %. The influencing factors had great explanations for alpine vegetation, desert, needle-leaf forest, and shrubland, and small explanations for broadleaf forest, mixed forest, and wetland. Overall, natural vegetation of China greened and its dependence on climate change decreased, SVP and SVT were driven by hydrology and heat, respectively. These findings will provide scientific basis for vegetation to cope with future extreme events and maintain vegetation stability.

The relationship between ecosystem functions and air pollutants based on spatial distribution patterns of forest and grassland: A case study of the Mongolian Plateau

Revealing how spatial distribution patterns of forest and grassland affect ecosystem functions (EF) and hence control air pollutant (AP) concentrations is a key precondition for the development of ecological spatial layouts. However, there are not enough large-scale studies analyzing this interaction. Firstly, this study is based on the topological properties of forest and grass spatial distribution patterns to establish the relationship between EF and AP. The EAsim (Vegetation patterns-Ecosystem function - Air pollutant Simulation) model was then constructed to simulate the effects of changes in spatial distribution patterns of forest and grass on EF and AP concentration. The results showed that the spatial distribution of the forest and grassland on the Mongolian Plateau (MP) exhibited four basic patterns. Among them, the Core-Linked Ring pattern (CLR) accounted for the highest proportion of 40.74% and showed the highest stability. When all the spatial distribution patterns of forest and grass in the region are in CLR pattern, the water use efficiency of vegetation in the region will be increased by 39.60%, the wind and sand control function will be enhanced by 7.74%, while the concentration of AP will be reduced by 22.21%. The study confirms that by adjusting the distribution pattern of forest and grassland sources, the EF can be effectively enhanced and the concentration of AP can be reduced. This finding may provide a strategy for the enhancement of EF and management of AP in arid and semi-arid regions.

Climate change enhances greening while human activities accelerate degradation in northern China's grasslands

Northern China's grasslands play a pivotal role in livestock production, energy utilization, and ecosystem balance, both domestically and globally. However, they exhibit pronounced temporal variability and marked spatial heterogeneity. Since most existing studies rely on single vegetation indices and regional-scale analyses, they may introduce biases in interpreting grassland dynamics and their underlying drivers. To address this gap, we integrated both functional and structural indices - Gross Primary Productivity (GPP), solar-Induced chlorophyll fluorescence (SIF), Normalized Difference Vegetation Index (NDVI), and Leaf Area Index (LAI) - to systematically investigate spatiotemporal trends across various grassland types in northern China. Using partial derivative analysis, we quantified the relative contributions of climate change and human activities to these observed vegetation trends. Results indicated that over 70 % of grassland areas, especially temperate grasslands, showed an overall increase in vegetation indices, while a decline was observed in the southwestern alpine grasslands. Climate change was the primary driver of grassland greening (56.55 %-63.83 %), primarily through increased precipitation in temperate grasslands and rising temperatures in alpine grasslands. Human activities contributed substantially to greening (36.17 %-43.45 %), especially in desertified temperate grasslands (e.g., Mu Us Sandy Land, Gansu, Ningxia, Xinjiang) and Qinghai alpine meadows, mainly through farmland restoration and desertification control. Conversely, human activities also served as the primary driver of grassland degradation (51.70 %-69.64 %) in certain alpine regions, where overgrazing and population growth - compounded by rising temperatures and declining soil moisture - led to significant vegetation losses. Moreover, 72.66 % of temperate grasslands demonstrated strong coupling between vegetation structure and function, whereas 57.59 % of alpine grasslands exhibited increasing GPP alongside declines in both LAI and SIF. Overall, these findings underscore the spatial heterogeneity of grassland responses to climatic and anthropogenic drivers, highlighting the necessity of employing multiple vegetation indices to guide targeted and effective grassland management strategies.

Greening but enhanced vegetation water stress in the Yellow River Basin: A holistic perspective

The Yellow River Basin (YRB) has emerged as a focal point of global vegetation greening due to climate change and human activities. Given its ecological vulnerability and intense human activities, environmental sustainability has become an urgent concern for scholars. Current research on the hydrological effects of vegetation greening, from a reductionist perspective, still struggle to answer the crucial question that whether vegetation water stress is increasing or decreasing. Towards that, we adopt a holistic perspective to explore the relationships between monthly vegetation dynamics and multiple water stress indicators in the YRB from 1982 to 2018. Using statistical methods and the random forest model, we revealed that both gross primary productivity and water use efficiency showed an increasing trend, with rates of 5.83 g Cm-2 and 0.01 g Cmm-1m-2 per year, respectively. We identified that with increasing climatic aridity, the water stress factors for vegetation transition from monthly scale water conditions (vapor pressure deficit, VPD) to 1-2 months scale (soil water content, SWC) and seasonal scale (standardized precipitation evapotranspiration index-3, SPEI-3) water balance status. And with an aridity index of 0.35 as the threshold, the response of vegetation to water stress factors exhibits marked spatial differentiation. Furthermore, since 2000, despite a persistent greening trend in the YRB, there has been a noticeable expansion in the spatial range of intermediate and long-term water stress factors (SWC, SPEI-3), indicating an enhancing vegetation water stress. This suggests that a serious attention should be paid to the future ecological security of the YRB under the intensified climate change.

Advanced precipitation peak offsets middle growing-season drought in impacting grassland C sink

Redistribution of precipitation across seasons is a widespread phenomenon affecting dryland ecosystems globally. However, the impacts of shifting seasonal precipitation patterns on carbon (C) cycling and sequestration in dryland ecosystems remain poorly understood. In this study, we conducted a 10-yr (2013-2022) field manipulative experiment that altered the timing of growing-season precipitation peaks in a semi-arid grassland. We found that the delayed precipitation peak suppressed plant growth and thus reduced gross ecosystem productivity, ecosystem respiration, and net ecosystem productivity due to middle growing-season water stress. Surprisingly, shifting more precipitation to the early growing season can advance plant development, increase the dominance of drought-tolerant forbs, and thus compensate for the negative impacts of middle growing-season water stress on ecosystem C cycling, leading to a neutral change in grassland C sink. Our findings indicate that greater precipitation and plant development in spring could act as a crucial mechanism, maintaining plant growth and stabilizing ecosystem C sink. This underscores the urgent need to incorporate precipitation seasonality into Earth system models, which is crucial for improving projections of terrestrial C cycling and sequestration under future climate change scenarios.

Ecological restoration enhances dryland carbon stock by reducing surface soil carbon loss due to wind erosion

Enhancing terrestrial carbon (C) stock through ecological restoration, one of the prominent approaches for natural climate solutions, is conventionally considered to be achieved through an ecological pathway, i.e., increased plant C uptake. By conducting a comprehensive regional survey of 4279 1 × 1 m2 plots at 517 sites across China's drylands and a 13-y manipulative experiment in a semiarid grassland within the same region, we show that greater soil and ecosystem C stocks in restored than degraded lands result predominantly from decreased surface soil C loss via suppressed wind erosion. This biophysical pathway is always overlooked in model evaluation of land-based C mitigation strategies. Surprisingly, stimulated plant growth plays a minor role in regulating C stocks under ecological restoration. In addition, the overall enhancement of C stocks in the restored lands increases with both initial degradation intensity and restoration duration. At the national scale, the rate of soil C accumulation (7.87 Tg C y-1) due to reduced wind erosion and surface soil C loss under dryland restoration is equal to 38.8% of afforestation and 56.2% of forest protection in China. Incorporating this unique but largely missed biophysical C-conserving mechanism into land surface models will greatly improve global assessments of the potential of land restoration for mitigating climate change.

Unraveling the complex interconnections between food-energy-water nexus sustainability and the supply-demand of related ecosystem services

Matching the supply and demand of related ecosystem services can be an effective way to realize long-term sustainable management of the food-energy-water nexus (FEW Nexus) in drylands. However, few studies have focused on the matching of supply and demand for ecosystem services associated with advancing the sustainability of FEW-Nexus, there is limited research in this domain, which lacks systematic and quantitative analysis of the relationship between them and FEW Nexus sustainability. Here, this research takes the West Liaohe River Basin in the arid region of China as a case study. Based on a localized FEW Nexus sustainability evaluation index system, the FEW Nexus sustainability and the supply-demand matching characteristics of the corresponding ecosystem services in the West Liaohe River Basin from 2005 to 2015 were assessed. The relationship between them was analyzed quantitatively through the methods of coupling coordination degree and geographical detector. The results showed a synergistic improvement in both FEW Nexus sustainability and the supply-demand situation of combined ecosystem services. The supply of food production and water yield were able to meet their demands adequately from 2005 to 2015, with a strengthening surplus, leading to an overall surplus and gradual improvement in the integrated ecosystem services. This surplus synergistically promoted the process of FEW Nexus sustainability. The results of the geographical detector indicate that the supply-demand ratio of carbon sequestration was the main factor influencing FEW Nexus sustainability. Areas with higher FEW Nexus sustainability tended to have larger deficits in carbon sequestration, which was more evident in areas with high levels of urbanization. Therefore, the key to enhancing FEW Nexus sustainability in the basin is to balance the supply of and demand for carbon sequestration services. Overall, the present study not only provides a basis for strengthening the management of the supply-demand of ecosystem services associated with FEW to achieve regional sustainable development, but also offers insights into how the growing demand for the FEW Nexus is exerting pressure on the balance between supply and demand of related ecosystem services.

Impact of Natural and Human Factors on Dryland Vegetation in Eurasia from 2003 to 2022

Eurasian dryland ecosystems consist mainly of cropland and grassland, and their changes are driven by both natural factors and human activities. This study utilized the normalized difference vegetation index (NDVI), gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) to analyze the changing characteristics of vegetation activity in Eurasia over the past two decades. Additionally, we integrated the mean annual temperature (MAT), the mean annual precipitation (MAP), the soil moisture (SM), the vapor pressure deficit (VPD) and the terrestrial water storage (TWS) to analyze natural factors' influence on the vegetation activity from 2003 to 2022. Through partial correlation and residual analysis, we quantitatively described the contributions of both natural and human factors to changes in vegetation activity. The results indicated an overall increasing trend in vegetation activity in Eurasia; the growth rates of vegetation greenness, productivity and photosynthetic capacity were 1.00 × 10-3 yr-1 (p < 0.01), 1.30 g C m-2 yr-2 (p < 0.01) and 1.00 × 10-3 Wm-2μm-1sr-1yr-1 (p < 0.01), respectively. Furthermore, we found that soil moisture was the most important natural factor influencing vegetation activity. Human activities were identified as the main driving factors of vegetation activity in the Eurasian drylands. The relative contributions of human-induced changes to NDVI, GPP and SIF were 52.45%, 55.81% and 74.18%, respectively. These findings can deepen our understanding of the impacts of current natural change and intensified human activities on dryland vegetation coverage change in Eurasia.

The relationship between structure and ecosystem services of forest and grassland based on pattern analysis method: A case study of the Mongolian Plateau

Global warming has led to severe land desertification on the Mongolian plateau. It puts great environmental pressure on vegetation communities. This pressure leads to fragmentation of land use and landscape patterns, thus triggering changes in the spatial distribution patterns of vegetation. The spatial distribution pattern of vegetation is crucial for the performance of its ecosystem services. However, there is not enough research on the relationship between large-scale spatial distribution patterns of vegetation and ecosystem services. Therefore, this study is to construct an ecological spatial network on the Mongolian Plateau based on landscape ecology and complex network theory. Combining pattern analysis methods to analyze the network, we obtained the spatial and temporal trends of forest and grass spatial distribution patterns from 2000 to 2100, and explored the relationship between the topological properties of source patches and ecosystem services in different patterns. It was found that there are four basic patterns of spatial distribution of forest and grass in the Mongolian Plateau. The Core-Linked Ring pattern accounts for 40.74 % and exhibits the highest stability. Under the SSP5-RCP8.5 scenario, source patches are reduced by 22.76 % in 2100. Topological indicators of source patches showed significant correlations with ecosystem services. For example, the CUE of grassland patches in the Centralized Star pattern was positively correlated with betweeness centrality. The most significant improvement in WUE after optimization is 19.90 % compared to pre-optimization. The conclusion of the study shows that the spatial distribution pattern of vegetation can be used to enhance the stability of ecological spatial network and improve ecosystem services at a larger scale. It can provide a certain reference for the study of spatial patterns of vegetation distribution in arid and semi-arid areas.

Grassland productivity in arid Central Asia depends on the greening rate rather than the growing season length

Climate change has induced substantial impact on the gross primary productivity (GPP) of terrestrial ecosystems by affecting vegetation phenology. Nevertheless, it remains unclear which among the mean rates of grass greening (RG), yellowing (RY), and the length of growing season (LOS) exhibit stronger explanatory power for GPP variations, and how RG and RY affect GPP variations under warming scenarios. Here, we explored the relationship between RG, RY, LOS, and GPP in arid Central Asia (ACA) from 1982 to 2019, elucidating the response mechanisms of RG, RY, and GPP to the mean temperature (TMP), vapor pressure deficit (VPD), precipitation (PRE), and soil moisture (SM). The results showed that the multi-year average length of greening (LG) in ACA was 22.7 days shorter than that of yellowing (LY) and the multi-year average GPP during LG (GPPlg) was 38.28 g C m-2 d -1 more than that of during LY (GPPly). RG and RY were positively correlated with GPPlg and GPPly, although the degree of correlation between RG and GPPlg was higher than that between RY and GPPly. Increases in RG and RY contributed to an increase in GPPlg (55.44 % of annual GPP) and GPPly (35.44 % of annual GPP). The correlation between RG and GPPlg was the strongest (0.49), followed by RY and GPPly (0.33), and LOS and GPP was the weakest (0.21). TMP, VPD, PRE, and SM primarily affected GPP by influencing RG and RY, rather than direct effects. The positive effects of TMP during LG (TMPlg), PRE during LG (PRElg), and SM during LG (SMlg) facilitated increases in RG and GPPlg, and higher VPD during LY (VPDly) and lower PRE during LY (PREly) accelerated increases in RY. Our study elucidated the impact of vegetation growth rate on GPP, thus providing an alternate method of quantifying the relationship between vegetation phenology and GPP.

Research needs on the biodiversity-ecosystem functioning relationship in drylands

Research carried out in drylands over the last decade has provided major insights on the biodiversity-ecosystem functioning relationship (BEFr) and about how biodiversity interacts with other important factors, such as climate and soil properties, to determine ecosystem functioning and services. Despite this, there are important gaps in our understanding of the BEFr in drylands that should be addressed by future research. In this perspective we highlight some of these gaps, which include: 1) the need to study the BEFr in bare soils devoid of perennial vascular vegetation and biocrusts, a major feature of dryland ecosystems, 2) evaluating how intra-specific trait variability, a key but understudied facet of functional diversity, modulate the BEFr, 3) addressing the influence of biotic interactions on the BEFr, including plant-animal interactions and those between microorganisms associated to biocrusts, 4) studying how differences in species-area relationships and beta diversity are associated with ecosystem functioning, and 5) considering the role of temporal variability and human activities, both present and past, particularly those linked to land use (e.g., grazing) and urbanization. Tackling these gaps will not only advance our comprehension of the BEFr but will also bolster the effectiveness of management and ecological restoration strategies, crucial for safeguarding dryland ecosystems and the livelihoods of their inhabitants.

CMIP6 ESMs overestimate greening and the photosynthesis trends in Dryland East Asia

The Dryland East Asia (DEA) is one of the largest inland arid regions, and vegetation is very sensitive to climate change. The complex environment in DEA with defects of modeling construction make it difficult to simulate and predict changes in vegetation structure and productivity. Here, we use the emergent constraint (EC) method to constrain the future interannual leaf area index (LAI) and gross primary productivity (GPP) trends in DEA, under four scenarios of the latest Sixth Coupled Model Intercomparison Project (CMIP6) model ensemble. LAI and GPP increase in all scenarios in the near term (2015-2050), with continued growth in SSP370 and SSP585 and stasis in SSP126 and SSP245 in the far term (2051-2100). However, after building effective EC relationships, the constrained increasing trends of LAI (GPP) are reduced by 43.5 %-53.9 % (30.5 %-50.0 %) compared with the uncertainties of the original ensemble, which are reduced by 10.0 %-45.7 % (4.6 %-34.3 %). We also extend the EC in moving windows and grid cells, further strengthening the robustness of the constraints, especially by illustrating spatial sources of these emergent relationships. Overestimations of LAI and GPP trends suggest that current CMIP6 models may be insufficient to capture the complex relationships between climate change and vegetation dynamics in DEA; however, these models can be adjusted based on established emergent relationships.

Combating land degradation through human efforts: Ongoing challenges for sustainable development of global drylands

Drylands, as highly vulnerable ecosystems, support environmental functions and human well-being. Nevertheless, widespread land degradation and desertification present significant global and regional environmental challenges, with limited consensus on their area and degree. This study used time-series vegetation productivity and meteorological data from 2000 to 2020 to quantify global land degradation trends and driving factors in drylands. The results show a notable restoration of land degradation in drylands worldwide, with the area of improved land exceeding the degraded area by 1.4 times, although the threat of degradation persists. India and China emerge as pioneers in effective land improvement strategies, offering valuable experiences for other regions. Combined effects, as quantitatively distinguished by our established model, dominate the degradation and improvement processes. Notably, human activities play a decisive role in influencing land degradation trends, with the potential for either exacerbation or reversal. This study provides new perspectives on environmental health and human activities from global and regional observations. Finally, our research provides scientific support for desertification control and contributes to the overall advancement of the SDGs globally.

Recent impacts of water management on dryland's salinization and degradation neutralization

Reducing soil salinization of croplands with optimized irrigation and water management is essential to achieve land degradation neutralization (LDN). The effectiveness and sustainability of various irrigation and water management measures to reduce basin-scale salinization remain uncertain. Here we used remote sensing to estimate the soil salinity of arid croplands from 1984 to 2021. We then use Bayesian network analysis to compare the spatial-temporal response of salinity to water management, including various irrigation and drainage methods, in ten large arid river basins: Nile, Tigris-Euphrates, Indus, Tarim, Amu, Ili, Syr, Junggar, Colorado, and San Joaquin. In basins at more advanced phases of development, managers implemented drip and groundwater irrigation and thus effectively controlled salinity by lowering groundwater levels. For the remaining basins using conventional flood irrigation, economic development and policies are crucial for establishing a virtuous circle of "improving irrigation systems, reducing salinity, and increasing agricultural incomes" which is necessary to achieve LDN.

Vegetation structural shift tells environmental changes on the Tibetan Plateau over 40 years

Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes. However, such information at the regional scale is still lacking due to methodological limitations. Beyond remote sensing indicators only recognizing vegetation productivity, we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes. Over the past 40 years, we revealed that (1) the proportion of alpine meadows in alpine grasslands increased from 50% to 69%, well-reflecting the warming and wetting trend; (2) dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76% and 92%, respectively; (3) the climate factor mainly drove the distribution of Stipa purpurea formation, but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities. Therefore, the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent. Overall, the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau, but also innovates large-scale vegetation study paradigm.