This article investigates the influence of climatic and geographical characteristics in south-western region of Bangladesh on the temporal dynamics of post-cyclone impacts, with a critical focus on biophysical contexts. By quantitatively assessing the environmental consequences of cyclones Amphan (2020), Yaas (2021), Mocha (2023) and Remal (2024), the study offers a nuanced understanding of flood damage extent and vegetation health, measured through advanced remote sensing and geospatial techniques. Using Sentinel-1 (GRD) and Sentinel-2 (MSI) satellite imageries from 2020 to 2024, the study has examined post-cyclone changes of vegetation health and flood damage extent using available indices such as Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI). The results exhibit substantial spatial disparities occurred due to the cyclone events, with NDVI variations ranging from - 0.124 to 0.546 (Amphan), - 0.033 to 0.498 (Mocha), - 0.086 to 0.458 (Yaas), and - 0.061 to 0.362 (Remal), indicating significant ecological stress. Corresponding SAVI changes ranged from - 0.001 to 0.396 (Amphan), - 0.029 to 0.338 (Mocha), - 0.002 to 0.345 (Yaas), and - 0.0524 to 0.269 (Remal). Negative indices underscore potential vegetation degradation, while positive values indicate resilience or post-cyclone recovery. Furthermore, flood damage analysis indicates to a more severe and unevenly distributed impact than previously recognized, particularly in areas with pre-existing vulnerabilities with the damage extent variations between - 35.918 to - 2.0093 (Amphan), - 35.334 to - 4.4059 (Mocha), - 34.806 to - 0.94921 (Yaas), and - 48.469 to 0.00255 (Remal). The Geographically Weighted Regression (GWR), model demonstrates a robust relationship, with r2 values of 0.894, 0.889, 0.899, and 0.95, indicating that approximately 85% of the ecological changes are driven by fluctuations of vegetation due to flood. The insight from this research provides a foundation of flood damage assessment technique occurred by cyclones in a short span of time to aid immediate policy recommendations to enhance resilience in remote areas of the coastal regions of Bangladesh.

Ongoing and widespread permafrost degradation potentially affects terrestrial ecosystems, whereas the changes in its effects on vegetation under climate change remain unclear. Here, we estimated the relative contribution of progressive active layer thickness (ALT) increases to vegetation gross primary productivity (GPP) in the northern permafrost region during the 21st century. Our results revealed that ALT changes accounted for 40% of the GPP increase in the permafrost region during 2000-2021, with amplified effects observed in late growing season (September-October) (43.2%-45.4%) and was especially notable in tundra ecosystems (51%-52.6%). However, projections indicated that this contribution could decrease considerably in the coming decades. Model simulations suggest that once ALT increments (relative to the 2001-2021 baseline) reach approximately 90 cm between 2035 and 2045, the promoting effect of ALT increase on vegetation growth may disappear. These findings provide crucial insights for accurately modelling and predicting ecosystem carbon dynamics in northern high latitudinal regions.

Florida's unique climatic and geographical features have profoundly influenced its hurricane history. This study quantitatively examines the effects of Hurricane Ian on urban vegetation in Fort Myers, Florida, using remote sensing data. We analyzed pre- and post-hurricane vegetation indices, including NDVI (Normalized Difference Vegetation Index), ARVI (Atmospherically Resistant Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index). Our findings reveal varied spatial impacts, with NDVI changes ranging from -0.03 to 0.333, ARVI changes from -0.016 to 0.25, and SAVI changes from -0.04 to 0.5. Negative values indicate vegetation damage, while positive values suggest resilience or recovery. The study area experienced a 63.75% reduction in vegetation cover, from 67.10 km(2) before Hurricane Ian to 24.325 km(2) after. Pre-hurricane NDVI ranged from -0.2298 to 0.5663, while post-hurricane values ranged from -0.189 to 0.521, indicating overall vegetation stress. ARVI maxima decreased from 0.379 to 0.352, and SAVI maxima from 0.849 to 0.782, further confirming vegetation damage. Support Vector Machine classification achieved 89% accuracy (Kappa = 0.85) for prehurricane and 87% (Kappa = 0.83) for post-hurricane vegetation mapping. These findings enhance our understanding of hurricane impacts on urban green infrastructure, with significant implications for urban planning and disaster preparedness in coastal cities prone to extreme weather events. The outcomes enhance damage assessment methodologies and provide valuable insights into the ecological consequences of hurricanes on urban ecosystems.

Since 2012, the Mountain Excavation and City Construction (MECC) project has been implemented extensively on the Loess Plateau of China, transforming gullies into flat land for urban sprawl by leveling loess hilltops to fill in valleys. However, this unprecedented human activity has caused widespread controversy over its unknown potential ecological impacts. Quantitative assessment of the impacts of the MECC project on the vegetation is key to ecological management and restoration. Taking the largest MECC project area on the Loess Plateau, Yan'an New District (YND), as the study area, this study investigated the spatiotemporal pattern of vegetation dynamics before and after the implementation of the MECC project using a multitemporal normalized difference vegetation index (NDVI) time series from 2009 to 2023 and explored the response of vegetation dynamics to the large-scale MECC project. The results showed that the vegetation dynamics in the YND exhibited significant spatial and temporal heterogeneity due to the MECC project, with the vegetation in the project-affected areas showing rapid damage followed by slow recovery. Vegetation damage occurred only in the project-affected area, and 84 % of these areas began recovery within 10 years, indicating the limited impact of the large-scale MECC project on the regional vegetation. The strong correlation between vegetation dynamics and the MECC project suggested that the destruction and recovery of vegetation in the project -affected areas was mainly under anthropogenic control, which highlights the importance of targeted ecological policies. Specifically, the MECC project induced local anthropogenic damage to the plant population structure during the land creation period, but regeneration and rational allocation of the vegetation were achieved through urbanization, gradually forming a new balanced ecological environment. These findings will contribute to a full understanding of the response of vegetation to such large-scale engineering activities and help local governments adopt projects or policies that facilitate vegetation recovery.

Fire in the Northern Alps is comparatively rare. Yet, previous human-ignited fire events in subalpine forests up to the treeline have triggered severe fire damage to vegetation and soil. Here, we investigate post-fire vegetation dynamics in the Northern Limestone Alps about 80 years after disturbance. We observed higher species richness in burned compared to unburned vegetation and clearly distinct floristic communities emerging after fire-driven forest removal, with several alpine specialist species uniquely found in the burned subalpine sites. The functional composition of vegetation was also distinct, with higher relative forb cover in burned plots. This difference was likely driven by disturbance-related environmental changes, such as increased light availability, offering safe sites for subalpine and alpine species. Due to a general lack of tree encroachment, we consider this a case of arrested succession after fire. We conclude that the recovery of fire-affected subalpine forests is modulated by complex interactions of climatic and biotic filters producing extreme site conditions, controlling the recolonization of the disturbed areas by forest species while providing safe sites for the establishment of a rich subalpine and alpine low-statured flora. The coupling of disturbance and abiotic filters makes high-elevation treeline ecotones very vulnerable to climate change.

To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together with CHIRPS rainfall and MODIS LST at annual, seasonal and monthly scales for the period spanning 2000 to 2022. Additionally, MODIS Potential Evapotranspiration (PET), Ground Water Storage (GWS), Soil Moisture (SM) and nighttime light datasets were compiled to explore their spatial relationships with vegetation and other selected environmental parameters. Non-parametric statistics were applied to estimate the magnitude of trends, along with correlation and residual trend analysis to quantify the relative influence of Climate Change (CC) and Human Activities (HA) on vegetation dynamics using Google Earth Engine algorithms. The study reveals regional contrasts in trends that are evidently related to elevation. An annual increasing trend in rainfall (21.3 mm/decade, p < 0.05), together with augmented vegetation cover and slightly cooler (-0.07 degrees C/decade) LST is revealed in the high-elevation areas. Meanwhile, LST in the plain regions exhibit a warming trend (0.02 degrees C/decade) and decreased in vegetation and rainfall, accompanied by substantial reductions in GWS and SM related to increased PET. Linear regression demonstrates a strongly significant relationship between rainfall and EVI (R-2 = 0.92), although a negative relationship is apparent between LST and vegetation (R-2 = -0.83). Additionally, increased LST in the lowelevation parts of the study area impacted PET (R-2 = 0.87), which triggered EVI loss (R2 = 0.93). Moreover, increased HA resulted in losses of 25.5 mm GSW and 1.5 mm SM annually. The relative contributions of CC and HA are shown to vary with elevation. At higher elevations, CC and HA contribute respectively 85% and 15% to the increase in EVI. However, at lower elevations, reduced EVI is largely (79%) due to human activities. This needs to be considered in managing the future of vulnerable socio-ecological systems in the state of Haryana.

Climate warming in northern high latitudes has progressed twice as fast as the global average, leading to prominent but puzzling changes in vegetation structure and functioning of tundra and boreal ecosystems. While some regions are becoming greener, others have lost or shifted vegetation condition as indicated by a browning signal. The mechanisms underlying this 'greening or browning enigma' remain poorly understood. Here we use multi-sourced time-series of satellite-derived vegetation indices to reveal that spectral greening is associated with reductions in surface water cover (i.e. fraction of surface water bodies), whereas spectral browning is linked to increases in surface water cover. These patterns are consistently observed from both 30 m resolution Landsat data and 250 m resolution MODIS data on the basis of grid cells sized of 1, 2 and 4 km. Our study provides, to our knowledge, the first biome-scale demonstration that interactions between vegetation condition and water cover change can explain the contrasting trajectories of ecosystem dynamics across the northern high latitudes in response to climate warming. These divergent trajectories we identified have major implications for ecosystem functioning, carbon sequestration and feedbacks to the climate system. Further unraveling the interaction between vegetation and surface water will be essential if we are to understand the fate of tundra and boreal biomes in a warming climate.

Thermokarst depressions are widespread phenomena due to permafrost degradation in the Arctic, whereas only few are known from mountain permafrost of the mid-latitudes. In the Italian Central Alps, close to the Stelvio Pass (2,763 m above sea level), a ski run was built in 1987. Since 1981, statistically significant air warming has been recorded, especially during summer (+0.65 degrees C per decade). Permafrost temperature recorded at the nearby Share Stelvio Borehole between 1990 and 2011 exhibited a rapid increase (> 0.8 degrees C per decade) and an active-layer thickening (7 cm/year). Between the years 1999 and 2003, some thermokarst depressions started to develop, initially in the lower part of the ski run and then extending to higher elevations. The depressions increased in number, size, and depth with time. Since ski-run construction, the area remained free of vegetation until early 2000, when vegetation colonization started, showing a coupling with the onset of thermokarst development and summer warming. Vegetation changes accelerated with the ingress of pioneer and early-successional as well as of late-successional species. Moreover, the ingress of shrub species (Salix spp.) typical of lower elevation belts (subalpine and even montane) was dated to 2004. All the observed features show a rapid and coupled response of the abiotic and biotic components of this ecosystem to climate warming. Our data also confirm the similarity of the observed responses and dynamics of the alpine tundra with the Arctic tundra with regard to both permafrost and vegetation.

Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 degrees C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R-2 = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70-85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state.

Frozen ground degradation under a warming climate profoundly influences the growth of alpine vegetation in the source region of the Qinghai-Tibet Plateau. This study investigated spatiotemporal variations in the frozen ground distribution, the active layer thickness (ALT) of permafrost (PF) soil and the soil freeze depth (SFD) in seasonally frozen soil from 1980 to 2018 using the temperature at the top of permafrost (TTOP) model and Stefan equation. We compared the effects of these variations on vegetation growth among different frozen ground types and vegetation types in the source region of the Yellow River (SRYR). The results showed that approximately half of the PF area (20.37% of the SRYR) was projected to degrade into seasonally frozen ground (SFG) during the past four decades; furthermore, the areal average ALT increased by 3.47 cm/yr, and the areal average SFD decreased by 0.93 cm/yr from 1980 to 2018. Accordingly, the growing season Normalized Difference Vegetation Index (NDVI) presented an increasing trend of 0.002/10yr, and the increase rate and proportion of areas with NDVI increase were largest in the transition zone where PF degraded to SFG (the PF to SFG zone). A correlation analysis indicated that variations in ALT and SFD in the SRYR were significantly correlated with increases of NDVI in the growing season. However, a rapid decrease in SFD (< -1.4 cm/10yr) could have reduced the soil moisture and, thus, decreased the NDVI. The NDVI for most vegetation types exhibited a significant positive correlation with ALT and a negative correlation with SFD. However, the steppe NDVI exhibited a significant negative correlation with the SFD in the PF to SFG zone but a positive correlation in the SFG zone, which was mainly limited by water condition because of different change rates of the SFD.