Revealing spatiotemporal dynamics and driving mechanisms of ecological vulnerability under climate and human pressures using multi-source remote sensing in the dryland of China

Understanding the impact of anthropogenic climate variability on the surface inundation dynamics in the wetlands of drylands:  A case study of Ile-Balkhash Delta, Kazakhstan.Kanchan Mishra1*, Philip Weber1, Kathryn E. Fitzsimmons21Department of Geosciences, University of Tübingen, Schnarrenbergstrasse 94-96, 72076 Tübingen, Germany.2School of Earth Atmosphere and Environment, Monash University, Clayton VIC, Australia(*Email: kanchan.mishra@uni-tuebingen.de)The Ile-Balkhash Delta, a Ramsar wetland of international importance in southeastern Kazakhstan, is one of the largest deltas in arid Central Asia (ACA). Like other waterbodies in dryland regions, the Ile-Balkhash delta faces degradation and desertification driven by anthropogenic climate change and human-induced alterations. These changes disrupt the structure, function, and distribution of wetlands, resulting in ecological and socio-economic impacts, including habitat loss, declining water quality and quantity, and reduced carbon sequestration. Despite their sensitivity to environmental changes, the surface water dynamics of these wetlands remain poorly understood in arid settings.This study aims to assess the seasonal surface inundation patterns (SIP) and their spatio-temporal dynamics in the Ile-Balkhash Delta from 1992 to 2024 using remote sensing, GIS, and logistic regression analysis. Climatic and anthropogenic drivers of wetland dynamics are identified, while a new classification algorithm quantifies degradation patterns and transitions under the current regulated hydrological regime, offering insights into physical processes and conservation strategies.The study reveals a strong seasonal variability, with persistent water coverage peaking in spring (15.4%) and declining in summer (10.4%), reflecting substantial reductions during drier months. Interannual variability shows peaks in wetland areas during years such as 2000, 2004, 2010, 2016, and 2018, likely linked to upstream discharge and snowmelt. However, a marked decline in coverage post-2018 suggests potential shifts in the hydrological conditions of the wetlands. The analysis further highlights that upstream inflows and hydrological connectivity exert a stronger influence on wetland dynamics than localized rainfall and temperature, which primarily regulate evaporation rates. Across the entire delta (27,791 km²), total lost (231.95 km²) and gained (246.04 km²) areas are nearly balanced. However, persistent water remains limited (617.28 km², 10.6%), while seasonal and temporary water has expanded, emphasizing the dominance of temporary water areas. Regionally, the coastal region (SR-1, 2,750 km²) shows a net increase in inundation, with gains (117.84 km²) far exceeding losses (7.99 km²), resulting in dynamic seasonal water coverage. In contrast, the main Central Ile River Delta (SR-2, 5,357 km²) shows a net areal decline, with losses (127.35 km²) surpassing gains (40.70 km²), despite heightened seasonal fluctuations. Similarly, the southern arid inland regions (SR-3, 1,039 km²) exhibit modest gains (11.64 km²) dominated by larger losses (37.46 km²), indicating a shift toward ephemeral water occurrences. The findings highlight the complex and dynamic nature of water variability in the Ile-Balkhash Delta, emphasizing the need for integrated water management strategies to address ongoing hydrological changes and support wetland conservation under evolving climate and human pressures. 

Southwest China, with typical karst, is one of the 36 biodiversity hotspots in the world, facing extreme ecological fragility due to thin soils, limited water retention, and high bedrock exposure. This fragility intensifies under climate change and human pressures, threatening regional sustainable development. Ecological strategic areas (ESAs) are critical safeguards for ecosystem resilience, yet their spatiotemporal dynamics and driving mechanisms remain poorly quantified. To address this gap, this study constructed a multidimensional ecological health assessment framework (pattern integrity–process efficiency–function diversity). By integrating Sen’s slope, a correlated Mann–Kendall (CMK) test, the Hurst index, and fuzzy C-means clustering, we systematically evaluated ecological health trends and identified ESA differentiation patterns for 2000–2024. Orthogonal partial least squares structural equation modeling (OPLS-SEM) quantified driving factor intensities and pathways. The results revealed that ecological health improved overall but exhibited significant spatial disparity: persistently high in southern Guangdong and most of Yunnan, and persistently low in the Sichuan Basin and eastern Hubei, with 41.47% of counties showing declining/slightly declining trends. ESAs were concentrated in the southwest/southeast, whereas high-EHI ESAs increased while low-EHI ESAs declined. Additionally, the natural environmental and human interference impacts decreased, while unique geographic factors (notably the rock exposure rate, with persistently significant negative effects) increased. This long-term, multidimensional assessment provides a scientific foundation for targeted conservation and sustainable development strategies in fragile karst ecosystems.

Mapping ecological vulnerability to fire for effective conservation management of natural protected areas

It is crucial to decouple and coordinate human consumption and its environmental pressure for achieving sustainable development. As an important aspect of United Nations Sustainable Development Goal (SDG12), sustainability on material consuming is still in its early stages of research. To address the research gap in sustainable consumption of vegetation net primary productivity (NPP), this study analyzed the spatio-temporal dynamics of human consumption and environmental pressure in the Yangtze River Economic Zone (YREZ) using consumption-based HANPP (cHANPP) and Human Appropriation of Net Primary Production (HANPP) as indicators. Later, we measured their decoupling relationship using Tapio decoupling approach. We found that distribution of HANPP and cHANPP were regionally separated, with the former mainly concentrated in the middle and upper reaches provinces, while the latter concentrated in the lower reach provinces. From 2004 to 2019, the relationship between HANPP and cHANPP changed from strong negative decoupling to weak decoupling in the YREZ. Furthermore, the relationship was differed among different regions. As a whole, developing regions showed a weak decoupling state, experiencing an increase in environmental pressure (i.e., HANPP) alongside increased human consumption (i.e., cHANPP). In contrast, developed regions showed a strong decoupling state, experiencing a decrease in environmental pressure (i.e., HANPP) alongside increased human consumption (i.e., cHANPP). Our study highlights that different countermeasures should be formulated by regions according to their own situation to realize sustainable regional development.

This study aims to assess the spatio-temporal dynamics of vegetation in the Zouagha Forest, located in northeastern Algeria, over the period 2000-2020, taking into account the degradation induced by the complex interactions between biotic, abiotic, and anthropogenic factors. The analysis of vegetation indices, notably the NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index), for the years 2000, 2010, and 2020 reveals divergent trends. The NDVI shows a slight increase, rising from 0.20 in 2000 to 0.33 in 2020, suggesting a moderate regeneration of the vegetation cover. In contrast, the EVI records a notable decline, dropping from 0.38 in 2000 to 0.30 in 2020, indicating a continuous degradation in vegetation quality. Additionally, the SAVI shifts from −0.10 to 0.07, reflecting a modest improvement, yet the vegetation remains weak in terms of density and quality. This divergence between the indices suggests a spatial variation in vegetation conditions, indicating a growing heterogeneity in vegetation distribution across the forest. This phenomenon is exacerbated by unfavorable climatic conditions, such as reduced rainfall and rising temperatures. These changes, combined with anthropogenic pressures such as deforestation, greatly limit the forest’s natural regeneration capacity. Moreover, pest attacks, particularly by ( Lymantria dispar ) and ( Tortrix viridana ), contribute to uneven degradation of the forest ecosystem. These findings highlight the urgency of developing sustainable management strategies, incorporating soil restoration and water resource management, to strengthen the ecological resilience of the Zouagha Forest in the face of growing challenges posed by climate change and human pressures.

Road mediated spatio-temporal tree decline in traditional agroforests in an African biosphere reserve

This study investigates the responses of endemic macroinvertebrate species in the Martil River Basin (Morocco) to physic o chemical (T, pH, Cond and DO), land use, biotic indices (IBMWP, IHF and QBR), and hydro-morphological factors. Sampling was conducted over four seasons (2017) at 19 stations, revealing 1,768 individuals belonging to 32 endemic species. Hydro p syche iberomaroccana was the most abundant species, while Choroterpes volubilis was the most widespread. Biogeographical analysis highlighted a high proportion of Ibero-Maghrebian endemics. Multivariate analyses revealed significant biotypological differences among stream types, with sensitive endemic species predominantly found in highland / midland permanent stations, positively correlated with dissolved oxygen, altitude, and biotic indices. In contrast, lentic, thermophilic, and eurytopic species were more common in downstream areas, exposed to agricultural, industrial, and urban activities, and associated with higher temperatures and pollution levels. Seasonal and spatial variability in taxonomic composition was strongly influenced by hydr o logical intermittency and human pressures, with endemic species diversity and abundance peaking in spring. Despite their ec o logical importance, with the exception of Odonata, none of the species from other orders are currently listed on the IUCN Red List or in Annex IV of Moroccan Law 29-05 concerning the protection of wild flora and fauna species and the control of their trade. The findings underscore the urgent need for targeted conservation strategies to address threats from climate change, habitat degradation, and anthropogenic activities.

Complex Adaptive Systems, soil degradation and land sensitivity to desertification: A multivariate assessment of Italian agro-forest landscape

Aboveground biomass (AGB) is a key indicator of forest structure and carbon sequestration, yet its dynamics under concurrent anthropogenic disturbances remain poorly understood. This study investigates the spatiotemporal dynamics and driving mechanisms of AGB in the Jianfengling tropical lowland rainforest (JFLTLR) within Hainan Tropical Rainforest National Park (NRHTR) from 2015 to 2023. Six machine learning models—Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Decision Tree (DT), and Random Forest (RF)—were evaluated, with RF achieving the highest accuracy (R2 = 0.83). Therefore, RF was employed to generate high-resolution annual AGB maps based on Sentinel-1/2 data fusion, field surveys, socio-economic indicators, and topographic variables. Human pressure was quantified using the Human Influence Index (HII). Threshold analysis revealed a critical breakpoint at ΔHII ≈ 0.1712: below this level, AGB remained relatively stable, whereas beyond it, biomass declined sharply (≈−2.65 mg·ha−1 per 0.01 ΔHII). Partial least squares structural equation modeling (PLS-SEM) identified plantation forests as the dominant negative driver, while GDP (−0.91) and road (−1.04) exerted strong indirect effects through HII, peaking in 2019 before weakening under ecological restoration policies. Spatially, biomass remained resilient within central core zones but declined in peripheral regions associated with road expansion. Temporally, AGB exhibited a trajectory of decline, partial recovery, and renewed loss, resulting in a net reduction of ≈ 0.0393 × 106 mg. These findings underscore the urgent need for a “core stabilization–peripheral containment” strategy integrating disturbance early-warning systems, transportation planning that minimizes impacts on high-AGB corridors, and the strengthening of ecological corridors to maintain carbon-sink capacity and guide differentiated rainforest conservation.

Habitat ecological integrity and environmental impact assessment of anthropic activities: A GIS-based fuzzy logic model for sites of high biodiversity conservation interest

For Shenyang, the central city of Northeast China, its municipal-level Territorial Spatial Planning is of great significance to the whole of Northeast China. Territorial Spatial Planning is an essential carrier of China’s ecological civilization construction. The demarcation of “three districts and three lines” defines the scope of ecological protection areas, which is of guiding significance to the future development of ecological civilization construction. The regional ecological vulnerability assessment can provide reference for ecological pattern planning and the demarcation of ecological red lines in “three districts and three lines”. In order to explore the spatial distribution pattern of ecological vulnerability in Shenyang, predict the development trend of ecological vulnerability in the future and guide the construction of ecological civilization in Shenyang and provide certain basis for Shenyang’s Territorial Spatial Planning and the delineation of “three districts and three lines”. This paper based on the “sensitivity-resilience-pressure” model selected 13 indexes, to evaluate the ecological vulnerability of Shenyang from 2010 to 2020. Furthermore, the spatial distribution characteristics and influencing factors of ecological vulnerability in Shenyang are summarized using spatial autocorrelation analysis and geographic detector model, and the future development trend of ecological vulnerability in Shenyang in 2025 is predicted by using CA-Markov model. The results show that: (1) In 2010, 2015 and 2020, the total area of slightly vulnerable areas in Shenyang was large, and the ecological vulnerability showed a gradually vulnerable spatial change trend from south to north and from west to east. (2) The results of geographical detectors show that normalized difference vegetation index, economic density and nighttime light intensity are the main driving factors of ecological vulnerability in Shenyang. (3) The forecast result of CA-Markov model is reliable. In 2025, the ecological vulnerability of Shenyang will be mainly light and extreme vulnerability areas, and the areas of light and extreme vulnerability areas will increase in 2025. The research results can provide some reference for the delineation of “three districts and three lines” and ecological protection in Shenyang’s Territorial Spatial Planning, and have certain significance for promoting regional sustainable development and balancing ecological protection and economic development.

Rapid urbanization and climate change are exacerbating ecological vulnerability in dryland urban agglomerations, threatening ecosystem stability and sustainability. However, persistent technological gaps in large-scale, fine-grained and long-term monitoring hinder a comprehensive understanding of vulnerability patterns in these fragile regions. To address this, a novel Dryland Ecological Vulnerability Index (DEVI) is proposed by integrating six key indicators and combining remote sensing and machine learning to simplify the complex vulnerability scoping diagram (VSD). The Hohhot-Baotou-Ordos-Yulin urban agglomeration, a typical fragile region in China’s drylands, was selected as a case study to examine the spatiotemporal dynamics of ecological vulnerability from 1986 to 2024. SHapley Additive exPlanations (SHAP) coupled with XGBoost revealed the impact mechanisms and nonlinear interactions of natural and anthropogenic drivers. Results showed that DEVI effectively captured the surface ecological features, such as mobile sand, with high correlations (>0.79) to indicators. Over nearly 40 years, DEVI initially increased, then decreased, indicating ecological conditions first deteriorated and then improved, with an overall improvement of 14%. Vulnerability notably reduced in the Loess Hills but remained high in the Ordos Plateau and northern Inner Mongolia, with degradation areas still exceeding improvements by 4.5%, reflecting an imbalance in current ecological governance. Fortunately, improved areas have been increasing, with spatial sustainability reaching 82.8%, largely driven by land cover restoration (46.6%) and socioeconomic factors (27.0%). The study also identified the thresholds and interaction effects of key drivers, delineated new ecological management zones, and proposed targeted improvement suggestions. This study provides a novel index for ecological vulnerability monitoring and further offers practical guidance for sustainable development in dryland urban agglomerations.

This study uses remote sensing and GIS techniques to examine the intensity and dynamics of land use/cover change and environmental indices across a four-decade period in the Chingola district of Zambia, from 1972 to 2020 using five classification stages (1972, 1992, 2001, 2013, and 2020). A total of 10 key climate change detection monitoring indices were generated using RClimDex to examine the implications of land degradation on the bioclimatic factors from 1983 to 2020. The findings revealed a significant expansion in Built-ups (7.3%/year), farmlands (3.18%/year), and mining areas (0.82%/year) at the expense of natural resources. The highest human pressure was exerted on Savannah woodlands (−0.78), through agriculture (0.76) and infrastructure development (0.44) between 1992 and 2001.The analysis of the bioclimatic indices revealed a significant decline in rainfall quantity and intensity, and a rising in temperature (warmer days and nights). The Annual rainfall has decreased by −3.25%, while the potential evapotranspiration has increased by 0.04% from 1983 to 2020, resulting in an Aridity Index of 0.60 and a moisture deficit index of −0.42. To offset agriculture’s propensity to spatially expand and further encroach into savannah woodlands and forests, urban containment policies and programs that stimulate agricultural intensification are needed to reduce urban sprawl and protect the city’s remaining forestlands.

Climate change intensifies ecosystem vulnerability in mountainous regions, particularly in Northwestern Sichuan's Terrestrial Ecosystems (TENS), where complex terrain amplifies impacts on biodiversity and carbon dynamics. This study assesses spatiotemporal ecological vulnerability using the IPCC exposure-sensitivity-resilience framework. We applied autoregressive modeling and a 5-year moving window to monthly NDVI, temperature, and precipitation data from 1983 to 2022. Results show vulnerability index (VI) increases latitudinally from south to north, driven by inverse temperature correlations. Longitudinally, VI forms a V-shaped pattern due to topographic and monsoon influences. Wetlands are most vulnerable (VI ≈ 0.48) from precipitation sensitivity, while forests show lowest vulnerability (VI ≈ 0.43) due to high resilience. Temporally, VI fluctuates nonlinearly with decline (1985-1994) under cool-humid conditions, increase (1994-2008) amid warmer-drier El Niño effects, and sharp decline (2008-2011) from La Niña and sand control initiatives. Spatially, 34.6% of areas exhibit decline-increase-decline-increase trends. Centroids of decreasing VI shift southwest-to-north, indicating recovery diffusion. Increasing VI centroids move northwest-central-north. These findings underscore ecosystem-specific adaptive management and conservation policies, especially in northern TENS, to mitigate accelerating climate pressures.

The Kubuqi Desert represents a key ecologically fragile region in northern China, primarily functioning as a windbreak and sand-fixation barrier while also contributing to regional ecological balance. However, the area’s ecological vulnerability is pronounced, and investigating the spatiotemporal dynamics of vegetation carbon storage and associated driving mechanisms is essential for the scientific formulation of ecological restoration strategies. This research incorporates multi-source remote-sensing datasets (including Landsat 8 OLI/TIRS Level 2, Sentinel-1 Synthetic Aperture Radar (SAR), ERA5 daily meteorological data, GEDI Level 4B, SRTM GL1 v003, and ESA WorldCover v100) based on the Google Earth Engine (GEE) platform, and employs multiple machine-learning algorithms (validation metrics of the machine learning model: R2 = 0.917, RMSE = 0.251) to develop a dynamic monitoring model of vegetation carbon storage in the Kubuqi Desert during the period 2019–2023. The analysis systematically evaluates the influence of climatic variables and anthropogenic activities on the spatiotemporal differentiation of carbon storage. The results indicate a slight upward trend in overall carbon storage across the study area (average annual increase of 0.4%), with high values predominantly concentrated in vegetated regions (up to 5.22 Mg/Ha) and low values distributed in bare lands and desert zones (0.5–0.7 Mg/Ha). Altitude, temperature, and slope serve as the primary driving factors governing carbon-storage variability. The findings suggest that scientifically guided vegetation restoration and optimized water-resource management can enhance the carbon-sink capacity of the Kubuqi Desert, offering a robust scientific basis for ecological governance and carbon budget assessment in arid and semi-arid desert ecosystems.