Restored vegetation is more resistant to extreme drought events than natural vegetation in Southwest China

Nonlinear influences of climatic, vegetative, geographic and soil factors on soil water use efficiency of global karst landscapes: Insights from explainable machine learning

Soil Water Use Efficiency (SWUE) represents a vital metric for assessing the relationship between carbon acquisition and soil moisture (SM) depletion in terrestrial ecosystems. However, the elucidation of time-lagged and cumulative effects, nonlinear influences, and indirect contributions of explanatory variables, including climate and vegetation characteristics, on SWUE in global karst landscapes remains limited. In this study, we analyzed the time-lagged and cumulative effects of climatic and biological factors on SWUE in global karst landscapes using the Autoregressive Distributed Lag Model. By comparing nine machine learning models, we further revealed the nonlinear effects, as well as the direct and indirect contributions of climatic, geographic, soil, and biological explanatory variables on SWUE across varying aridity, using the Random Forest Model, SHapley Additive exPlanations, Generalized Additive Model, and Partial Least Squares-Structural Equation Modeling (PLS-SEM). The findings suggested that precipitation and wind speed exert the most substantial time-lagged and cumulative impacts on SWUE in global karst landscapes, respectively. The Random Forest model outperforms eight other machine learning models, including CatBoost, LightGBM, and XGBoost, in accurately simulating SWUE. In global karst landscapes, SWUE was significantly affected by the positive contributions of evapotranspiration, leaf area index, and temperature, as well as the negative impacts of latitude and longitude. These influences exhibited varying degrees of nonlinearity across the aridity gradient. Using PLS-SEM based on the 'geo-climatic-soil-biological' cascade effect, it was found that gross primary production directly and significantly influences karst SWUE under both drought-prone and water-abundant conditions, significantly exceeding the impact of SM. Geographic, climatic, and biological factors indirectly influenced karst SWUE by affecting gross primary production. The impact of soil type, soil carbon and nitrogen content, and rootable depth on SWUE was minimal. This study enhances our understanding of carbon sinks and the water‑carbon cycle, providing valuable insights into resource use efficiency within karst environments.

Relationships among vegetation restoration, drought and hydropower generation in the karst and non-karst regions of Southwest China over the past two decades

To curb the intensification of desertification, China has implemented a series of measures to control rocky desertification. However, the interaction between vegetation restoration and the frequent occurrence of extreme weather events has complicated the drought situation in Southwest China. Therefore, in this study, the vegetation health index (VHI) was used to analyze the spatiotemporal variations in drought. Additionally, the fractional vegetation cover (FVC), VHI, vegetation condition index (VCI), and temperature condition index (TCI) were compared between karst and non-karst regions. Additionally, the driving factors of drought and the response of hydropower generation (HG) to drought conditions were explored. The results revealed that (1) after the implementation of measures to combat desertification, the FVC and VHI increased annually by 0.37 % and 0.801, respectively, from 2002 to 2022. In Southwest China, the increase rates of the VCI and TCI were 1.993 and 0.349 yr-1, respectively, with VCI increase as a key factor in enhancing the VHI. (2) VHI improvement in karst regions was significantly greater than that in non-karst areas, indicating effective rocky desertification control efforts. (3) The geodetector analysis results indicated that the topography is the primary factor influencing the spatial distribution of drought in Southwest China, followed by climatic factors. (4) During drought occurrence, the gap between HG and the total electricity consumption in Southwest China increased, leading to increases in fossil fuel-based power generation and pollutant emissions.

A greater negative impact of future climate change on vegetation in Central Asia: Evidence from trajectory/pattern analysis

In the context of global warming, vegetation changes exhibit various patterns, yet previous studies have focused primarily on monotonic changes, often overlooking the complexity and diversity of multiple change processes. Therefore, it is crucial to further explore vegetation dynamics and diverse change trajectories in this region under future climate scenarios to obtain a more comprehensive understanding of local ecosystem evolution. In this study, we established an integrated machine learning prediction framework and a vegetation change trajectory recognition framework to predict the dynamics of vegetation in Central Asia under future climate change scenarios and identify its change trajectories, thus revealing the potential impacts of future climate change on vegetation in the region. The findings suggest that various future climate scenarios will negatively affect most vegetation in Central Asia, with vegetation change intensity increasing with increasing emission trajectories. Analyses of different time scales and trend variations consistently revealed more pronounced downward trends. Vegetation change trajectory analysis revealed that most vegetation has undergone nonlinear and dramatic changes, with negative changes outnumbering positive changes and curve changes outnumbering abrupt changes. Under the highest emission scenario (SSP5-8.5), the abrupt vegetation changes and curve changes are 1.7 times and 1.3 times greater, respectively, than those under the SSP1-2.6 scenario. When transitioning from lower emission pathways (SSP1-2.6, SSP2-4.5) to higher emission pathways (SSP3-7.0, SSP5-8.5), the vegetation change trajectories shift from neutral and negative curve changes to abrupt negative changes. Across climate scenarios, the key climate factors influencing vegetation changes are mostly evapotranspiration and soil moisture, with temperature and relative humidity exerting relatively minor effects. Our study reveals the negative response of vegetation in Central Asia to climate change from the perspective of vegetation dynamics and change trajectories, providing a scientific basis for the development of effective ecological protection and climate adaptation strategies.

Disentangling the impact of climate change, human activities, vegetation dynamics and atmospheric CO2 concentration on soil water use efficiency in global karst landscapes

Soil Water Use Efficiency (SWUE), which quantifies the carbon gain against each unit of soil moisture depletion, represents an essential ecological parameter that delineates the carbon-water coupling within terrestrial ecosystems. However, the spatiotemporal dynamics of SWUE, its sensitivity to environmental variables, and the underlying driving mechanisms across various temporal scales in the global karst region are largely uncharted. This study utilized the sensitivity algorithm of partial least squares regression, partial differential equations, and elasticity coefficients to investigate the characteristics of SWUE variations across different climatic zones in the global karst region and their responsiveness to environmental variables. Moreover, the study quantified the individual contributions of climate variability, atmospheric carbon dioxide concentration, human activities, and vegetation changes to SWUE variations. The results indicated that SWUE across different climatic zones in the global karst region demonstrated an increasing trend from 2000 to 2018, with the most notable improvement observed in the humid zone. SWUE presented regular distribution and variation characteristics across different latitudinal zones at a monthly scale. The sensitivity of SWUE to precipitation was significantly higher compared to its responsiveness to other environmental factors. Additionally, the trend in SWUE's sensitivity to precipitation demonstrated the most significant change. The sensitivity of SWUE to various environmental factors and the trend of this sensitivity in the arid zone revealed significant variation compared to other climatic zones. Gross primary productivity and soil moisture were identified as the intrinsic factors influencing SWUE changes, contributing 16 % and - 84 %, respectively. Climate variability and human activities were identified as the primary exogenous factors contributing to the increase in SWUE, accounting for 76 % and 16 %, respectively. This study advances the understanding of carbon-water coupling in karst regions, providing significant insights into the ecological management of global karst environments amidst climate variations.

Understanding drought propagation through coupling spatiotemporal features using vine copulas: A compound drought perspective

Accurately evaluating drought impact on agriculture poses a challenge to regional food security, particularly in compound drought (i.e., meteorological and agricultural drought co-occurring) scenarios. This study presents a novel approach utilizing Vine copula for coupling spatiotemporal features to evaluate drought propagation. Three-dimensional clustering method was employed to identify meteorological and agricultural drought events, which excelled in capturing dynamic evolution characteristics (duration, area, severity, etc.) as well as integrating them into comprehensive meteorological drought intensity (IMD) and agricultural drought intensity (IAD). Through spatiotemporal matching, compound drought events were extracted from the meteorological-agricultural drought event pairs. From compound drought perspective, compound duration (CD) and compound area (CA) were devised to characterize drought propagation potential across time and space. Finally, the Vine copula method was employed to model the interdependence between four key coupling features, namely IMD, IAD, CD, and CA, and evaluate the probability of triggering agricultural drought with different intensity levels. Results showed that CD and CA can respectively characterize the temporal and spatial accumulation scale of drought propagation. At a certain IMD level, CD significantly influences the propagation probability (i.e., "stratification" phenomenon), while CA increases the probability proportionally. Probability evaluation lacking spatiotemporal information may underestimate the likelihood of drought propagation characterized by "low-IMD" but "long-CD" or "large-CA". The four-dimensional Vine copula structure can effectively couple dependence relationships of compound drought characteristics, and exhibits reliable robustness. This research provides stakeholders accurate probabilistic evaluation under compound drought scenarios, offering new insight into drought propagation.

Assessment of the restoration potential for ecological sustainability in the Xijiang River basin, Southwest China: A comparative analysis of karst and non-karst areas

Vegetation restoration is an eco-friendly strategy for countering land degradation and biodiversity loss. Since 2000-2001, large-scale restoration projects have been performed in Southwest China, with the net primary productivity (NPP) increasing over the past two decades. However, negative ecohydrological impacts, including streamflow decline and soil moisture deficit, have been reported following afforestation. Current understanding of the permissible NPP capacity (NPPcap) and NPP potential (NPPpot) under karst and non-karst areas or planted and natural vegetations constrained by environmental factors remains unclear. Here multiple environmental drivers characterizing the heterogeneous landscape in the Xijiang River Basin (Southwest China) were employed to predict the NPPcap using a random forest model. Results showed that 85% of the area exhibited an increasing trend in NPPcap during 2001-2018. Overall, 3.50% of the area has exceeded the NPPcap, implying an excessive plantation and potential water deficit in these areas. Excluding agriculture activities, urban areas, and water bodies, we found there is room for an average extra 22.85% of NPP enhancement. The NPPpot was spatially imbalanced, with high NPPpot located in the northeast, indicating these areas as a target area for future vegetation restoration. Moreover, the NPPpot reduction in karst areas (1.12 g C m-2 a-1) was more pronounced than in non-karst areas (0.26 g C m-2 a-1), highlighting a stronger negative impact on NPPpot in karst areas. Furthermore, significant NPPpot differences were found between planted vegetation and natural vegetation for both karst and non-karst areas. According to the findings, we identified four separate restoration sub-zones and proposed tailored strategies to guide the implementation of future restoration efforts. Our study highlights restoration potential and where land is available for reforestation but also the urgent need for future restoration activities towards ecosystem sustainability.

Drought thresholds that impact vegetation reveal the divergent responses of vegetation growth to drought across China

Identifying droughts and accurately evaluating drought impacts on vegetation growth are crucial to understanding the terrestrial carbon balance across China. However, few studies have identified the critical drought thresholds that impact China's vegetation growth, leading to large uncertainty in assessing the ecological consequences of droughts. In this study, we utilize gridded surface soil moisture data and satellite-observed normalized difference vegetation index (NDVI) to assess vegetation response to droughts in China during 2001-2018. Based on the nonlinear relationship between changing drought stress and the coincident anomalies of NDVI during the growing season, we derive the spatial patterns of satellite-based drought thresholds (T SM ) that impact vegetation growth in China via a framework for detecting drought thresholds combining the methods of feature extraction, coincidence analysis, and piecewise linear regression. The T SM values represent percentile-based drought threshold levels, with smaller T SM values corresponding to more negative anomalies of soil moisture. On average, T SM is at the 8.7th percentile and detectable in 64.4% of China's vegetated lands, with lower values in North China and Jianghan Plain and higher values in the Inner Mongolia Plateau. Furthermore, T SM for forests is commonly lower than that for grasslands. We also find that agricultural irrigation modifies the drought thresholds for croplands in the Sichuan Basin. For future projections, Earth System Models predict that more regions in China will face an increasing risk for ecological drought, and the Hexi Corridor-Hetao Plain and Shandong Peninsula will become hotspots of ecological drought. This study has important implications for accurately evaluating the impacts of drought on vegetation growth in China and provides a scientific reference for the effective ecomanagement of China's terrestrial ecosystems.

Effects of extreme drought events on vegetation activity from the perspectives of meteorological and soil droughts in southwestern China

Under climate warming, extreme drought events (EDEs) in southwestern China have become more frequent and severe and have had significant impacts on vegetation growth. Clarifying the influence of soil and meteorological droughts on the vegetation photosynthetic rate (PHR) and respiration rate (RER) can help policymakers to anticipate the impacts of drought on vegetation and take measures to reduce losses. In this study, the frequency and features of EDEs from 1990 to 2021 were analyzed using the standardized precipitation evapotranspiration index, and the longest-lasting and most severe EDE was chosen to assess the effects of drought on vegetation activity. Then, a land surface model was used to simulate the vegetation PHR and RER. Finally, the effects of the EDE on the vegetation PHR and RER were analyzed from the perspectives of soil and meteorological droughts. The results revealed that from 1990 to 2021, a total of 11 EDEs were observed in southwestern China, and the longest-lasting and most severe EDE occurred in 2009-2010 (EDE2009/2010). EDE2009/2010 significantly reduced the monthly mean PHR and RER by 9.82 g C m-2 month-1 and 0.80 g C m-2 month-1, respectively, causing a cumulative reduction of approximately 5.61 × 1013 g C. Soil and meteorological droughts had a driving force of 39 % on the PHR changes and an explanatory force of 42 % on the RER reduction. In particular, the soil drought had an average explanatory force of 25 % on the PHR and made a contribution of 24 % to the RER. The drought affected different types of vegetation differently, and crops were more susceptible than grassland and forests on the monthly time scale. The vegetation exhibited resilience to drought, returning to normal PHR and RER levels 2 months after the end of EDE2009/2010. This research contributes to understanding and predicting the impact of EDEs on vegetation growth in southwestern China.

Compensatory response of ecosystem carbon-water cycling following severe drought in Southwestern China

Climate change has increased the frequency and length of droughts, but many uncertainties remain regarding the impacts of this aridification on terrestrial ecosystem function. Vegetation water use efficiency and carbon sequestration capacity are crucial determinants that both respond to and mediate the effects of drought. However, it is important to note that the consequences of drought on these processes can persist for years. A deeper exploration of these "drought legacy effects" will help improve our understanding of how climate change alter ecosystem carbon-water cycling. Here, we investigate the spatial patterns of drought legacy effects on remotely-sensed vegetation greenness (NDVI), net primary productivity (NPP) and water use efficiency (WUE) in southwestern China, a biodiversity hotspot that was impacted by an extreme drought in 2009-2010, with a particular focus on the tradeoff between WUE and NPP. Despite widespread negative drought legacy effects in NDVI (impacting 61.26 % of the study region), there was a general increase in NPP (58.68 %) and a decrease in WUE (67.53 %) in the year following drought (2011). This drought legacy effect was most evident in forests, while drought legacies in grasslands were less common. Drought legacies were also most apparent in relatively warm and humid areas. During the study period (2002 to 2018), we found that drought impacts on WUE also lagged behind changes in NPP by 1-2 years in forests, which highlights how drought legacies may manifest differently across ecosystem processes. Our study demonstrated that severe drought conditions may significantly affect the carbon sequestration capacity and water use efficiency of vegetation in southwestern China, and that forests may compensate for the detrimental effects of water stress by increasing water use and biomass growth after drought episodes.