Multifaceted responses of vegetation to average and extreme climate change over global drylands

Exploring the multifaceted reason for deficits in soil water within different soil layers in China's drylands

Soil water regulates the hydrological cycle and provides the water required for vegetation growth in drylands. However, existing studies have rarely investigated the reason for changes in soil water within different layers and compared differences in the contribution of driving factors from spatial and inter-annual perspectives. This study analyzed the dynamics of soil water content (SWC) at shallow (0-28 cm), intermediate (28-100 cm), and deep (100-289 cm) layers. The individual and interactive effects of different environmental factors on the spatial heterogeneity of SWC were investigated using the geographical detector. By selecting evapotranspiration (ET), precipitation, air temperature, land surface temperature (LST), and the Normalized Difference Vegetation Index (NDVI), we determined the influences of these factors on SWC dynamics for each layer as well as their contributions using ridge regression. Meanwhile, we also analyzed the influence of extreme events and lag effects of climatic factors on SWC. The results showed that SWC in each layer primarily exhibited a downward trend. In different layers, all interactive factors (two factors) had stronger effects on the spatial heterogeneity of SWC compared to any individual factor. Precipitation was the largest contributor (25.03 ± 20.66%) to SWC dynamics in shallow layer but its contribution decreased with increasing soil depth. NDVI mainly controlled the SWC in intermediate and deep layers with the largest contribution and exerted a dual effect on SWC. The contributions of air temperature and LST were the smallest. The lagged months of precipitation and air temperature on SWC increased with soil depth. Precipitation extremes with long duration and warm temperature extremes had large contributions and exceeded that of the average climate changes. These findings can provide a deeper insight into soil water dynamics and their environmental factors and scientific guidance for maintaining the hydrological cycle and sustainable development of vegetation in drylands.

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.

Spatiotemporal variation and GeoDetector analysis of NDVI at the northern foothills of the Yinshan Mountains in Inner Mongolia over the past 40 years

The study of spatiotemporal variation and driving forces of the normalized difference vegetation index (NDVI) is conducive to regional ecosystem protection and natural resource management. Based on the 1982-2022 GIMMS NDVI data and 26 influencing variables, by using the Theil-Sen median slope analysis, Mann-Kendall (M - K) test method and GeoDetector model, we analyzed the spatial and temporal characteristics of vegetation cover and the driving factors of its spatial differentiation in the northern foothills of the Yinshan Mountains in Inner Mongolia. The NDVI showed a significantly increasing trend during 1982-2022, with a growth rate of 0.0091 per decade. It is further predicted that future change in NDVI will continue the 1982-2022 trend, and sustainable improvement will dominate in the future; however, 17.69 % of vegetation will degrade, that is, NDVI will degrade instead of improvement. The spatial distribution of the NDVI in the northern foothills of the study area was generally characterized by high in the east and low in the west. Annual precipitation (Pre), evapotranspiration (Evp), relative humidity (Rhu) and sunshine hours (Ssd) had >70 % explanatory power (73.5, 79.9, 79.0, and 74.9 %, respectively). The explanatory power of edaphic factors was >30 %, whereas anthropogenic and topographic factors had little influence on the spatial variation of NDVI, with an explanatory power of <30 %. Thus, climatic factors were the dominant factors influencing the spatial variability of NDVI in the study area. The results of the interaction detector analysis showed nonlinear strengthening for any two factors, and the interaction between Rhu and barometric pressure had the highest explanatory power. There were optimal ranges or characteristics of each factor that promoted vegetation growth. This study investigated the differences in the explanatory power of different factors on the NDVI and the optimal range of individual factors to promote vegetation growth, which can provide a basis for the development of vegetation resource management programs.

Time-lag and accumulation responses of vegetation growth to average and extreme precipitation and temperature events in China between 2001 and 2020

Climate change is often closely related to vegetation dynamics; time lag (Tlag) and accumulative effects (Tacc) are non-negligible phenomena when studying the interaction between climate and vegetation. But, amidst the escalating frequency of extreme climatic events, the quantification of temporal effects (Teffects) of such extremes on vegetation remains scarce. This research quantifies the Tlag and Tacc responses of China's vegetation to episodes of extreme temperature and precipitation since the early 2000s, utilizing daily meteorological data series. Overall, the precipitation in China has become wetter, and nighttime temperatures have risen significantly. The proportion of areas with Teffects ranged from 1.15 % to 15.95 %, and the correlation coefficient between the climate indices and the Normalized Difference Vegetation Index (NDVI) increased by 0.05 to 0.38 when considering the Teffects, compared to not considering it. The Tacc of vegetation had the strongest response (70.74-88.01 %) to extreme events among all the tested climate indices. Moreover, the Tacc of consecutive climate events had a greater impact on vegetation growth than individual climate event. The average Tacc for extreme temperature and extreme precipitation was 1.7-3.09 months and 2.17-3.25 months, respectively. Events like the over 95 % (R95p) and 99 % (R99p) percentile heavy precipitation and the maximum precipitation amount in one day (Rx1day) caused significant Teffects on NDVI. In addition, 90 % of grasslands exhibit Tacc, mainly contributed by the extreme precipitation indices (55.7 %), while the Teffects of forests were stronger than those of extreme temperature. Furthermore, NDVI was more affected by annual precipitation than by extreme precipitation, but the opposite was true for temperature. The results of this study highlight the importance of considering the Tlag and Tacc when predicting the effects of climate change on vegetation dynamics.

Global responses of wetland methane emissions to extreme temperature and precipitation

As global warming continues, events of extreme heat or heavy precipitation will become more frequent, while events of extreme cold will become less so. How wetlands around the globe will react to these extreme events is unclear yet critical, because they are among the greatest natural sources of methane(CH4). Here we use seven indices of extreme climate and the rate of methane emission from global wetlands(WME) during 2000-2019 simulated by 12 published models as input data. Our analyses suggest that extreme cold (particularly extreme low temperatures) inhibits WME, whereas extreme heat (particularly extreme high temperatures) accelerates WME. Our results also suggest that daily precipitation >10 mm accelerates WME, while much higher daily precipitation levels can slow WME. The correlation of extreme high temperature and precipitation with rate of WME became stronger during the study period, while the correlation between extreme low temperature and WME rate became weaker.

Dual effects on vegetation from urban expansion in the drylands of northern China: A multiscale investigation using the vegetation disturbance index

Drylands contribute roughly 40 % of the global net primary productivity and are essential for achieving sustainable development. Investigating the effects on vegetation from urban expansion in drylands within the context of rapid urbanization could help enhance the sustainability of dryland cities. With the use of the drylands of northern China (DNC) as an example, we applied the vegetation disturbance index to investigate the negative and positive effects on vegetation from urban expansion in drylands. The results revealed that the DNC experienced massive and rapid urban expansion from 2000 to 2020. Urban land in the entire DNC increased by 19,646 km2 from 8141 to 27,787 km2, with an annual growth rate of 6.3 %. Urban expansion in the DNC imposed both negative and positive effects on regional vegetation. The area with negative effects reached 7736 km2 and was mainly concentrated in the dry subhumid zones. The area with positive effects amounted to 5011 km2 and was comparable among the dry subhumid, semiarid, and arid zones. Land use/cover change induced by population growth significantly contributed to these negative effects, while the positive effects were largely caused by economic growth. Therefore, it is recommended to strike a balance between urban growth and vegetation conservation to mitigate the adverse effects on vegetation from urban expansion in drylands. Simultaneously, it is imperative to expand urban green spaces and build sustainable and livable ecological cities to facilitate sustainable urban development.

In-situ supplementary irrigation device for afforestation under extreme high temperature: An exploration in North China

Afforestation plays a crucial role in environmental management for many countries. Yet, frequently extreme high temperature (EHT) events in arid and semi-arid regions easily cause the death of artificially planted saplings. To address this, we present a new in-situ supplementary irrigation device (SID) consisting of a rainwater catching board, a storage tank, and ceramic emitters. A continuous EHT experiment combined with the HYDRUS-2D model in North China is further conducted to investigate the soil water-heat properties of the in-situ SID and the growth performance of the planted saplings (Platycladus orientalis) under EHT. The results show that in-situ SID keeps a stable and suitable soil water-heat status in the root layer of the planted saplings under EHT. Especially, the in-situ SID with one ceramic emitter maintains the soil water moisture in a narrow and suitable range from 0.149 cm3 cm-3 to 0.153 cm3 cm-3, and reduces the maximum soil temperature by 2.7 °C compared to the traditional irrigation method. Furthermore, the in-situ SID with one ceramic emitter presents the highest average leaf water content (66.9%), new shoot (35.0 mm), and tree height (62.0 mm). The economic benefit analysis finds that the in-situ SID provides a shorter time to recover high funds and saves a large amount of irrigation water resources. Overall, this study provides an effective irrigation device for forest managers to improve the ecological service effectiveness of afforestation in areas with frequent EHT events and scarce water resources.

Disentangling influences of driving forces on intra-annual variability in sediment discharge in karst watersheds

The intra-annual variability in sediment discharge was considerably influenced by the climate variability and vegetation dynamics. Because of the coupled or relationships between climatic and vegetation variables, it is still challenging to decouple the direct and indirect effects of climate variability and vegetation dynamics on hydrological and sediment transport processes. The purpose of this study is to decouple influences of individual driving force on intra-annual distribution of sediment discharge during 2003-2017 using the partial least squares structural equation model (PLS-SEM) method in four typical karst watersheds of Southwest China. The coefficient of variation (Cv), Completely regulation coefficient (Cr), Lorenz asymmetry coefficient and Gini coefficient were used to represent the intra-annual sediment discharge variability. Results showed that the monthly sediment discharge (190 % < Cv < 353 %) exhibited greater variability than its potential affecting factors (18 % < Cv < 101 %). From the PLS-SEM analysis, the water discharge, climate, and vegetation together explain 57 %-75 %, 64 %-79 %, and 53 %-80 % of the total variance in Cv, Cr, and Gini coefficient, respectively. Specifically, water discharge exerts the largest influence on sediment discharge variability (0.65 ≤ direct effect ≤0.97, P < 0.05), while vegetation dynamic mainly indirectly affects sediment discharge variability (-0.88 ≤ indirect effect ≤ -0.01) through influencing water discharge. The climate factors also principally indirectly affect the sediment discharge variability (-0.47 ≤ indirect effect ≤0.19) by affecting water discharge and vegetation. The PLS-SEM can effectively reveal the driving force and influencing mechanism of intra-annual sediment discharge changes, and provide an important reference for regional soil and water resources management in karst watersheds. Future studies can decouple the influences of the extreme climate, unique lithology, discontinuous soil, heterogeneous landscape, and special geomorphology on spatial variability in sediment discharge across different karst watersheds.

Alpine grassland greening on the Northern Tibetan Plateau driven by climate change and human activities considering extreme temperature and soil moisture

Alpine grassland is among the world's most vulnerable ecosystems, characterized by a high sensitivity to climate change (CC) and human activities (HA). Quantifying the relative contributions of CC and HA to grassland change plays a crucial role in safeguarding grassland ecological security and devising sustainable grassland management strategies. Although there were adequate studies focusing on the separate impacts of CC and HA on alpine ecosystem, insufficient attention has been given to investigating the effects of extreme temperatures and soil moisture. In this study, the spatiotemporal variations of alpine grassland were analyzed based on MODIS NDVI during the growing season from 2000 to 2020 in Naqu, using partial least squares regression and residual analysis methods to analyze the importance of climate factors and the impacts of CC and HA on grassland change. The results show that the NDVI during the growing season in Naqu exhibited an increasing trend of 0.0046/10a. At the biome scale, the most significant and rapid increase was observed in alpine desert and alpine desert grassland. Extreme temperature and soil moisture (SM) exerted a more significant importance on alpine grassland at whole scale. SM always showed a significant importance at biome and grid scale. The contributions of CC and HA to the change during the growing season were calculated as 0.0032/10a and 0.0015/10a, respectively, accounting for 68.05 % and 31.05 %. CC dominated the increase in NDVI during the growing season; HA contributed positively to NDVI in most areas of Naqu. The results are expected to enhance our understanding of grassland variations under CC and HA and provide a scientific basis for future ecological conservation in alpine regions.

Response of grassland growing season length to extreme climatic events on the Qinghai-Tibetan Plateau

Extreme Climatic Events (ECEs) are increasing in intensity, frequency, and duration as the earth warms, which greatly affects the vegetation phenology. However, the response of vegetation phenology to different types of ECEs (e.g., extreme hot, extreme cold, extreme drought, and extreme wet) has not been extensively studied. To fill this knowledge gap, we investigated the relationship between the length of growing season (LOS) of grassland and ECEs on the Qinghai-Tibetan Plateau (QTP). First, we analyzed the spatial distribution and interannual trends of phenology based on the MODIS Normalized Difference Vegetation Index (NDVI). Second, we used Coincidence Rate (CR) analysis to quantify the relationship between LOS anomalies and ECEs. Finally, we analyzed the sensitivity of LOS to the intensity of ECEs. The results indicated that the spatial distribution of LOS was closely related to local hydrothermal conditions, with longer LOS in places with more precipitation or higher temperatures during the growing season, and LOS extended by 0.28 days/year from 2000 to 2022. Moreover, we found that the CR of negative LOS anomalies to ECEs notably exhibited variations along climatic gradients, with higher CR to extreme hot generally occurring in warmer areas. Meanwhile, the CR of extreme wet increased while the CR of extreme drought decreased with increasing precipitation. We also found that the sensitivity of LOS to ECEs changed more markedly, along the climatic gradients, in alpine ecoregions compared to temperate ecoregions. Overall, the sensitivities of LOS ranked in descending order of absolute sensitivity to extreme drought, extreme wet, extreme hot, and extreme cold. This study furthers our understanding of the grassland response to ECEs under different hydrothermal conditions, which can provide valuable reference for the management and conservation of grassland ecosystems in QTP under future climate change scenarios.

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.