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There is 78 % permafrost and seasonal frozen soil in the Yangtze River’s Source Region (SRYR), which is situated in the middle of the Qinghai-Xizang Plateau. Three distinct scenarios were developed in the Soil and Water Assessment Tool (SWAT) to model the effects of land cover change (LCC) on various water balance components. Discharge and percolation of groundwater have decreased by mid-December. This demonstrates the seasonal contributions of subsurface water, which diminish when soil freezes. During winter, when surface water inputs are low, groundwater storage becomes even more critical to ensure water supply due to this periodic trend. An impermeable layer underneath the active layer thickness decreases GWQ and PERC in LCC + permafrost scenario. The water transport and storage phase reached a critical point in August when precipitation, permafrost thawing, and snowmelt caused LATQ to surge. To prevent waterlogging and save water for dry periods, it is necessary to control this peak flow phase. Hydrological processes, permafrost dynamics, and land cover changes in the SRYR are difficult, according to the data. These interactions enhance water circulation throughout the year, recharge of groundwater supplies, surface runoff, and lateral flow. For the region’s water resource management to be effective in sustaining ecohydrology, ensuring appropriate water storage, and alleviating freshwater scarcity, these dynamics must be considered.

This study observes and records land cover changes in Al-Baha to track urban growth. The study develops a schematic vision of urban mass's current and future shape and distribution and its growth to achieve sustainable urban development, reduce service and social differences between city areas, and integrate urban and rural areas. The study uses inductive methods to monitor urban developments, population growth, and land use through Al-Baha's structural schemes by extracting digital data from satellite imagery to survey historical land cover changes. The mapping software ArcGIS v10.8 processed these digital data and the final map compositions. Through this urban mass study, the research predicted city growth and development. Capabilities and functions must shape urban and rural-urban communities. The development must also consider the National Urban Development Strategy, the relative importance of rural-urban communities, and their expected functional role in influencing the development of small rural communities adjacent to them to reduce migration from rural areas near the city. The study highlighted changes in city land coverage. Al-Baha expanded from 1982 to 1995. Al-Baha's transformation from village to city accelerated, increasing its area from 31 km2 to 44 km2. Many villages beyond 40 were included in the decisions. From 2006–2021, the city's area grew 221%. It increased from 60 km2 to 133 km2 in an urban area, indicating false urban growth. The study stressed the importance of geographic information systems (GIS) and remote sensing (RS). The study recommends urban development in suitable areas because agricultural development is not feasible, especially in the northeast. Land use changes should be prevented by planning regulations because these agricultural areas are essential. Helping urban development move away from agricultural areas, especially on the eastern axis, is crucial. Create new urban centers along Al-Baha's western cliff to attract residents and relieve pressure. Limited linear expansion, especially in the northeast, and more expansive urbanization are also significant. Maps should also show when the Al-Baha region's expansionary scope changed and the urban boundaries that had to be reached by a specific time while development plans were efficiently monitored.

Deforestation in the form of forest land use change (FLUC) increases the emission of greenhouse gases, disrupts the water cycle, dries the soil, and reduces the growth of plant products. This has a direct effect on the well-being of local communities whose livelihoods depend on the forest and threatens biodiversity. The systematic review aimed to analyze the studies conducted on the effects of FLUC on biodiversity ecosystem services (BECS) and human well-being (HWB) of local communities. The study utilized a qualitative content analysis (QCA) based on a deductive approach, which reviewed 114 scientific documents, particularly research articles, selected by searching keywords through a purposeful sampling method. The FLUC indicators in the two groups of dominant morphology (intensity, scale, pattern, and usage) and recessive morphology (function, property rights, and management mode) had 172 repetitions in the articles. Moreover, the BECS criteria (regulating, provisioning, supportive, and cultural services) and HWB (items related to Maslow's hierarchy of needs, subjective well-being, objective well-being, and preferences) had 125 and 148 repetitions, respectively. Results confirm the relationship and effects of FLUC on BECS and HWB, which emphasizes the mutual role of these variables in social, economic, and environmental studies in future research programs. An increase in FLUC can decline the performance and structure of BECS and have a negative impact on the HWB of those communities who depend on forest. Findings are presented in the form of a model that provides a comprehensive understanding of the relationships between FLUC, BECS, and HWB for relevant decision makers.

Vegetation greening not only offers climate benefits but also enhances residents' well-being in urban areas. China and India lead the world in terms of global greening. However, systematic studies summarizing the green development levels of both countries are still lacking. Here, we explore the regional significant greening levels and spatial distribution characteristics of China and India across multiple spatial scales using the significant greening level as an indicator. Additionally, we analyze the diverse relationships between significant greening in China and India and factors such as land use, economy, and population. The results indicate that areas with significant greening in China are primarily located in some mountainous regions in the central and eastern parts, while in India, areas with significant greening are mainly distributed in plain and plateau regions. Within significantly greening areas, 55.57% in China are forests, and 95.67% in India are croplands. The greening level in built-up areas in China is mostly positively correlated with economic factors, but in economically disadvantaged areas, the greening level is not necessarily the lowest. In Indian built-up areas, the greening level is negatively correlated with the economy. Regarding the relationship with urbanization, the greening level in the surrounding areas of built-up areas in both China and India generally decreases with the increasing degree of urbanization's influence, but the damage caused by urban development to the greening level in India is much higher than in China. 83% of cities in China have medium-range per capita greening levels, while 60% of cities in India have per capita greening levels in the lower range. A systematic analysis and summary of China and India's greening development can provide strategic references for other developing countries to enhance greening initiatives and improve their level of sustainable development.

This research investigates the impact of sea level rise (SLR) on the Indus Delta, a vital ecosystem increasingly vulnerable to climate change repercussions. The objective of this study is to comprehensively assess the flooded areas under various shared socioeconomic pathway (SSP) scenarios based on the Intergovernmental Panel on Climate Change's (IPCC) 6th Assessment Report. The study employs a GIS-based bathtub model, utilizing historical (1995–2014) and IPCC-projected (2020–2150) tide gauge data from Karachi, Kandla, and Okha stations to identify potential inundated areas threatened by coastal flooding. Additionally, it analyzes LANDSAT-derived multispectral images to identify coastal erosion hotspots and changes in the landscape. A supervised random forest classifier is used to classify major landforms and understand alterations in land cover. Furthermore, neural network-based cellular automata simulations are applied to predict future land cover for 2050, 2100, and 2150 at risk of inundation. The results indicate that under different SSP scenarios, the estimated inundated land area varies from 307.36 km2 (5 % confidence on SSP1-1.9) to 7150.8 km2 (95 % confidence on SSP5-8.5). By 2150, the region will lose over 550 km2 of agricultural land and 535 km2 of mangroves (mean SLR projection). This work emphasizes identifying sensitive land cover for SLR-induced coastal flooding. It might fuel future policy and modeling endeavors to reduce SLR uncertainty and build effective coastal inundation mitigation methods.

Study region: The Fenhe River Basin, China Study focus: The hydrological parameters remained constant in a changing environment may no longer be applicable. The split-sample calibration method based on sliding window division (SWD-SSC) was proposed as a time-varying method, which confronts a challenge in the past due to the small number of samples and discontinuity. The annual LULC input and 11-year-block sliding scheme in distributed SWAT model were used to calibrate parameters. Sensitive parameters related to runoff, vegetation canopy and soil moisture demonstrated how characteristics change over time. Non-linear relationships for parameter variations were constructed by multiple algorithms combined with vegetation indexes, land use, human activity such as social economy factors. New hydrological insights for the region: SWD-SSC method performed well during the whole periods. When the same parameters sets were applied to all periods, the accuracy will be inferior to SWD-SSC with a decrease by 12–200% in NSE. Random Forests and Back-Propagation neural network show best performance in describing the relationship between hydrological parameters and environmental factors. The impact of climate change and human activities on runoff account for 33.2% and 66.8%. The impact of land use changes on runoff are 10.9% (-2.53 mm) and 8.7% (-1.35 mm) by time-varying parameters fixed parameters, respectively. These findings aid in the comprehension of hydrological processes and enhance simulation accuracy under changing environment, ensuring future regional water safety.

The unsustainable expansion of cities is generating urban heat islands (UHIs) by exchanging (trading) vegetation cover (green) for built impervious surfaces which is associated with heat-related health risks, globally. This phenomenon is exacerbated by climate change and anthropogenic activities like urban population growth, particularly in African cities. This study explores the spatio-temporal trends of land surface temperature (LST), land use land cover (LULC) and their economic and health risks in the Greater Accra Metropolitan Area (GAMA) of Ghana, from 1991 to 2021. We extracted LST/LULC information from Landsat datasets to perform change analysis, alongside an online survey across 56 communities on how LST relates to economic and human health risks perceptions of residents. The results show urbanization of GAMA is trading greens for heated surfaces, impacting communities’ health risks. While the built environment grew (8.6%), the vegetation cover declined (2.5%) and the mean LST rose (0.8⁰C) in 25 years. A 30⁰C LST corresponds to the point of inflexion of exchanging green vegetative cover for heated built surfaces. The forest community of Kisseman, the populous community of Dansoman and the harbour city of Tema corresponded to the first, fourth and fifth LST quintiles, changing at −0.05⁰C, 0.06⁰C and 0.164⁰C per year. The common health risks include discomfort from heavy sweating, headaches, dehydration, thirst and skin rashes. These results call for climate action and green spatial planning through urban forestry and environmentalism in GAMA. For urban resilience and sustainable cities, we advocate green-cooling multi-purpose housing, roads, and industrial infrastructure.

Vegetation is crucial in enhancing the urban environment and benefiting human settlements. Consequently, monitoring and attributing vegetation dynamics in urban agglomerations are paramount. Nevertheless, quantitatively assessing the driving mechanisms of urban vegetation proves challenging due to its direct regulation by human land use activities and its susceptibility to influences from urban environmental changes intertwined with global environmental shifts. A critical obstacle arises from the scarcity of reliable long-term observation data, further amplifying the difficulty of such research. Using a newly developed technique that effectively resolves cross-sensor bias and low revisiting frequency issues, we generated Landsat-based long-term vegetation indices data (NDVI, EVI, and NIRv) during 1986–2020. Our study quantified spatiotemporal vegetation changes and examined the contributions of various drivers, including atmospheric CO2 concentration, climate variations, and land cover changes over the past four decades in two representative urban agglomerations in China: the Wuhan Metropolitan Area (WMA) and the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). We found notable and prevalent rising trends of vegetation growth in WMA and GBA during 1986–2020, with considerable spatial and time-period variability. Greening was continuously observed in WMA with a significant increasing trend (0.0019 yr−1, p

Land conservation has been recognized as a multifunctional adaptive strategy to tackle climate change as it includes the ability to mitigate risk and enhance biodiversity. However, limited empirical studies focus on the climatic adaptive functions of land conservation. Employing various geospatial and statistical techniques, including remote sensing, logistic regression, and landscape metrics, we investigate the effects of land conservation’s spatial characteristics. These characteristics affect the functional efficacy of climate adaptation in urban coastal regions, influencing regional economic vitality in the United States and China. Empirical results indicate that regional economic vitality is positively affected by parks and grassland, patch growth patterns, higher urban density, and closer proximities to coastlines and major roads. In contrast, the core growth form of land conservation has a negative economic effect. Among the estimated variables, we find that the patch growth form of land conservation and closer proximity to higher urban density have the largest positive effects on economic vitality across the study sites. Our findings contribute to both land conservation policy and the climate change literature by uncovering the spatially explicit effects of land conservation related to climate change adaptation.

Are all humans morally responsible and deserving of blame for land cover change? Land cover change research has yet to provide an answer to this moral question. The purpose of this study was to answer the moral question of land cover change by conducting a land cover change analysis in six sampled metropolitan/municipal/districts [MMDAs] in Ghana, identify the agents of land cover change, and cluster the agents based on their moral responsibility and culpability. Supervised classification of Landsat images from 1987 to 2022 for the six MMDAs indicated that farmlands increased the most in area size although one-third of the respondents (agents) were into farming and agro-processing occupation. Based on respondants actions, knowledge and norms they were clustered into seven groups (“responsible and culpable”-25.1 %, “responsible due to culpable ignorance”-17.7 %, “responsible although lack knowledge”-14.1 %, “responsible due to weak norms”-9.1 %, “not responsible”-11 % and “not responsible due to culpable ignorance”-9.3 %) using Mason moral responsibility and culpability decision tree. The large number of respondants found to be responsible and culpable was because they had less knowledge about the consequences of land cover change, which limited their participation in environmental protection initiatives. The findings give sufficient evidence to promote educational programs for responsible land cover conservation and alternative livelihoods programs in Ghana.

Topographical maps from the nineteenth century hold significant historical and environmental value, providing insights into landscape changes over the past two centuries. These maps feature distinct symbols representing various land cover types, such as forests and wetlands, offering a unique historical perspective on land-use changes. For example, there has been a significant reduction in wetlands because of agricultural expansion and intensification which lead to biodiversity loss and increased greenhouse gas emissions globally. Our study uses U-net CNN to automatically segment wetland symbols from nineteenth century maps from hundreds of map sheets for an area of interest a large river catchment in Ireland. Extracted wetland extents were intersected with digital land cover datasets to estimate current land cover on former wetland (on both organic and mineral soils). Utilizing U-Net, we successfully automated the segmentation of wetland symbols from hundreds of nineteenth-century map sheets, focusing on a large river catchment area in Ireland. Our analysis achieved a very high F1 score of 98.2% and a Kappa of 89%. While it is challenging to verify the veracity of historical map content, the largely untapped information contained within these maps are important for understanding landscape change over time, and especially before the era of Earth observation & remote sensing. The data extracted from these sources can inform modern environmental management strategies, for example, in targeted rewetting of peatlands, or in habitat restoration.

Accurate information on the spatiotemporal distribution of urban renewal (UR) is important for sustainable urban development. Due to its complexity, existing studies could not completely describe the land cover types after demolition, and lacked the effective conversion rules to monitor the whole process of UR demolition and reconstruction which made it impossible to obtain high-precision UR extent, demolition time, and reconstruction time. This study proposed an UR monitoring framework by combining Point of Interest, nighttime light RS data, time-series RS data from Google Earth high-resolution and Landsat imageries. The urban vacant land was introduced to supplement the land cover classification system for UR monitoring and extracted by DeepLabv3 semantic segmentation model. The new conversion rules were then generated to track the historical changes in urban land types, and the multi-temporal classification model was applied to extract spatial and temporal characteristics of UR process. Results showed a total of 3,525.55 hm2 UR region were identified in Shenzhen during 2012–2020, and the largest demolition and reconstruction areas were both observed in 2019. The F1 and F2 scores of extracted UR extent, UR demolition time, and UR reconstruction time were larger than 0.72, 0.63 and 0.66, respectively, indicating high overall accuracies. Our proposed framework is important for the UR dynamic monitoring and can provide scientific basis for future urban construction.

In order to protect natural ecosystems, areas that can provide higher ecosystem services are usually designated as ecological priority protection areas. However, some areas with good natural and socio-cultural conditions (called ecological improvement zones in this study, EIZs) that do not provide the highest ecosystem services are often ignored. Therefore, this study attempts to use ecological functional zones as the research unit. And delineating the EIZs by combining multiple critical impact thresholds of ecosystem health (EH) change. Northwestern Hubei Province (NWHB), an important ecological function area in China, was selected as the study area. The results show that (1) the landscape of cultivated land tends to be fragmented, due to being occupied by a large amount of rural–urban land; (2) from 2000 to 2020, the EH in NWHB gradually improved; (3) spatially, the western region of NWHB is dominated by multiple ESs synergetic zone, while the eastern region is a food provision zone; and (4) except for GDP and population density, which are monotonically negatively correlated with EH, all other natural and anthropogenic factors have critical impact thresholds. The critical impact thresholds vary significantly among different ecological functional zones in different periods (e.g., In biodiversity - carbon storage synergetic zone, the threshold of DEM of around less than 1150 m in 2000 decreased to 480 m in 2005 with a clear trend of EH improvement). Meanwhile, from 2000 to 2020, EIZs are mainly distributed in key synergistic bundles in different periods. This study aims to provide services for the planning and management of ecological functional zones.

Forests are vital in combating climate change by storing and sequestrating CO2 from the atmosphere. Measuring the influence of land use/land cover (LULC) changes on the capacity of carbon storage (CS) within forest ecosystems presents a significant challenge. This study employs remote sensing techniques to examine the changes in spatiotemporal patterns of CS in the Chittagong Hill Tracts (CHT), resulting from LULC alterations between 1996 and 2021. LULC change patterns were identified for six different years utilizing the Google Earth Engine (GEE). The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was combined with GEE to evaluate the changing patterns of CS. The study discovered that the CHT region experienced a loss of 21.65 × 106 Mg of CS, owing to a 21% reduction in vegetation cover (2862.85 km^2) during the study period. The central city area (Chittagong) accounted for the most significant loss of CS (7.99 × 106 Mg), while the suburban areas of Khagrachari (0.92 × 106 Mg) and Rangamati (3.53 × 106 Mg) contributed the least. The multiple regression model revealed that elevation and vegetation characteristics significantly influenced CS. The findings underscore the importance of developing policies and strategies that mitigate the adverse effects of land cover change on CS, and advocate for sustainable forest management practices that strike a balance between ecological, social, and economic concerns.

Grasslands have been subject to contraction and fragmentation processes worldwide, mainly due to their transformation into commercial tree plantations and agricultural lands. Identifying the remaining grasslands areas and the drivers of its fragmentation constitute an important step towards their appreciation, conservation and sustainability monitoring. The Eastern Plains of Uruguay constitute a region of recognized national and international conservation importance, but rice cultivation has spread extensively over the last 60 years, resulting in a strong transformation of its natural biomes. Our objectives were to map natural grasslands remnants in this complex landscape characterized by a high presence of different post-agricultural stages of vegetation; to quantify grassland fragmentation and its spatial variability in the landscape; and to identify the main drivers of the fragmentation process. We intersected a current supervised classification of the Eastern Plains of Uruguay (743,600 ha) with a mask of croplands from the previous ten years to discriminate grasslands remnants. We quantified the landscape fragmentation and described the relative contribution of different biophysical and anthropogenic factors in grasslands spatial configuration. Our results showed that natural grassland currently occupies only 21% of the Eastern Plains surface and it is in an advanced stage of fragmentation, comparable to that of the most historically transformed regions of the Rio de la Plata Grasslands. A few variables that determine the expansion of agriculture (large cadastral parcels size, high road network density and low topographical variation) drive the fragmentation process, relegating grassland to places with unfavorable characteristics for the development of rice cultivation.

Land cover mapping is fundamental for national and international agencies to monitor forest resources. However, monitoring forest disturbances by direct comparison of these maps poses several difficulties and challenges. As a result, different methodologies have been explored to detect forest disturbances. However, most of them cannot be fully integrated with land cover map production since they require additional input data, while others are not suitable for monitoring small land parcels. This study presents a methodology that fulfils the need to integrate land cover mapping with land cover change detection. Specifically, this methodology was designed to complement the Sentinel-2-based land cover mapping used in Galicia, northwest Spain, a region characterized by small land parceling. First, two previously obtained land cover maps from 2019 and 2020 were compared to identify all the pixels with potential land cover changes using QGIS. The behavior of spectral indexes in a time series were then analyzed to identify which of the previously identified pixels correspond to forest disturbances. This step was implemented in the software R. Using the Normalized Difference Vegetation Index (NDVI) to detect different land cover changes it was obtained an overall accuracy of 82%, considering the existence of varying phenologies, diverse topographic conditions, and areas with a high level of stand fragmentation. This study could help agencies that have already developed their own land cover maps to easily advance the integration of their maps with land cover change detection, since this technique can be applied with any land cover mapping methodology based on multitemporal analysis of satellite images, without the need for additional input data.

Soil erosion is a vector of disturbances to agricultural productivity and economic development in the western highlands of Ethiopia. Yet, tough vegetation cover loss swapped to other land uses could have amplified the soil loss rate at which land cover change preceded, but little is known about their effects on soil loss in the Limu-Seqa watershed. This study was designed to evaluate the historical trends of the effects of land use-land cover change on soil erosion dynamics as a threshold for potential monitoring of soil loss. Satellite image data of 1987, 2002, 2021, and DEM-20 m resolution were used. The RUSLE model was applied with primary parameters to generate soil loss. Findings show that average annual soil loss increased from 4.5 in 1987 to 13.5 t ha−1 yr−1 in 2002 and surpassed to 45.35 t ha−1 yr−1 in 2021 as a result of LULC changes, particularly the transition of forest and overgrazed land to cropland (43.83%) and dense-forest to poor-open-up forest (6.92%) between 1987 and 2021. Soil loss during the recent study period was substantially affected by a substantial LULC change, from forest to cropland. The severe and very severe erosion risk categories jointly cover more than half of the entire catchment, which contributes to two-thirds of the total mean annual soil loss in the watershed, which is found to be over and above soil loss tolerance (SLT) in Ethiopia and tropical regions. Therefore, given the robust economic and political status of priority conservation measures, red hues areas are significant.

Droughts that are hotter, more frequent, and last longer; pest outbreaks that are more extensive and more common; and fires that are more frequent, more extensive, and perhaps more severe have raised concern that forests in the western United States may not return once disturbed by one or more of these agents. Numerous field-based studies have been undertaken to better understand forest response to these changing disturbance regimes. Meta-analyses of these studies provide broad guidelines on the biotic and abiotic factors that hinder forest recovery, but study-to-study differences in methods and objectives do not support estimation of the total extent of potentially impaired forest succession. In this research, we provide an estimate of the area of potentially impaired forest succession. The estimate was derived from modeling of an 18-year land cover and Normalized Difference Vegetation Index (NDVI) time series supported by an extensive ancillary dataset. We estimate an upper bound of approximately 3470 km2 of disturbed forest that may not return or reattain prior composition and structure. Based on the data used, fire appears to be the main disturbance agent of impaired forest succession, although climatic factors cannot be discounted. The numerous field studies routinely cite distal seed sources as a factor that hinders forest recovery, and we estimate that 20 % of the upper bound estimate has no forest cover within a 4.4-ha neighborhood. Our upper bound estimate is about 0.5 % of the 2001 mapped extent of western United States forests. The estimate is cognizant of measurement and modeling uncertainties (i.e., upper bound) and uncertainties related to successional rates and trajectories (i.e., potential).

The success of Chilean salmon farming’s early cultivation stages is largely facilitated by access to high-quality water, which is provisioned by watersheds dominated by native forests and defined by high precipitation levels. In recent decades, human activities have increasingly affected both attributes. This study analyzed the risk of climate change in 123 watersheds that supply water to land-based salmon farms in south-central Chile (36.5−43°S). The risk was calculated based on exposure (fingerling and smolt production), sensitivity (land cover maps for three time periods), and hazard indicators (four climate change indicators). The results show a disturbing reality: under a high emissions scenario (RCP 8.5), more than 50% of the current fingerling and smolts production would be located in high or very high-risk areas. These projections are the result of both a drier and warmer climate as well as the continued processes of deforestation and fragmentation of native forests, a spatio-temporal combination which could limit the availability and quality of the water needed for optimal aquaculture production. The risk analysis suggests that landscape configuration may be a potential alternative to mitigate the consequences of climate change on Chilean salmon farming. This is particularly important in areas such as south-central Chile, where the current watershed management and/or conservation strategies do not ensure landscapes resilient to projected hydroclimatic changes.

Research findings concerning the main processes influencing water resources differ substantially, and so the topic remains controversial. Recent studies indicate that the changes in water yield, expressed through the n-parameter of Budyko framework, are associated with vegetation coverage changes. Here, we use runoff measurements and outputs from 13 dynamic global vegetation models, to investigate the underlying drivers of the n-parameter changes. Unlike previous studies, we instead find that climate change is the primary driver of adjustments on water resources. Changing climatic characteristics, particularly the intensity and seasonality of rainfall, modulates the runoff generation process. Indirect effects of climate change occur through altering vegetation properties, which in turn also impact river flow. We also find that in the arid and sparse vegetation regions, water yield is more sensitive to changes in n-parameter. Thus, the Budyko framework provides a reliable parameter-sparse representation of runoff changes, and reveals that terrestrial water cycle is changing substantially under climate change. This climate forcing requires on-going investigation to generate more refined and reliable projections of future water availability.

The Tibetan Plateau (TP) is an important ecological security shelter in China, yet the environment here remains fragile and is difficult to restore. This ecosystem is likely to face additional threats in the future as it will be influenced by human activities and climate change. Although a number of investigations regarding land cover changes on the TP as well as resultant influences on ecosystem services have been performed over recent decades, reliable evaluation of future land cover change scenarios and their potential ecological impacts remain absent. Thus, to remedy this, we developed a method that can spatially and explicitly evaluate TP ecosystem services responses to future land cover changes. Simulation results for TP land cover changes between 2010 and 2030 reveal that under a business-as-usual scenario, grassland area will increase by 1.04%, wetland area will increase by 6.01%, and forested area will increase by 0.07%. In contrast, under an ecological protection scenario, forested and wetland areas will increase by 1.06% and 28.87% respectively, while grassland area will increase by 7.09%. We then calculated the responses of ecosystem services over the period same period; results show that under a business-as-usual scenario, land cover changes on the TP would lead to a net primary productively (NPP) increase of 0.004%, a 0.011% decrease in soil conservation services, and a 0.023% decrease in water yield. In contrast, under an ecological protection scenario, land cover changes on the TP would lead to a NPP increase of 0.006%, a 0.007% decrease in soil conservation services, and a 0.007% decrease in water yield. Ecosystem service values given an ecological protection scenario will be slightly higher than those given a business-as-usual scenario.

Study region: Cathedral Peak Research Catchments, uKhahlamba Drakensberg mountain range, South Africa. Study focus: The focus was to determine the seasonal pattern of evapotranspiration (ET) over a bracken canopy, which is a product of degradation within the montane grasslands of the uKhahlamba Drakensberg mountains. Surface renewal (SR) was investigated as a viable alternative to eddy covariance for long-term estimation of ET within a remote high rainfall montane landscape. The SR dissipation method was used to observe ET over the bracken canopy for 23 months, across two consecutive years with variable seasonal rainfall timing and amounts. Besides ET, rainfall and energy flux components were observed. New hydrological insights for the region: The SR dissipation method was shown to be adequate for the long-term estimation of evapotranspiration over a bracken canopy within a remote high summer rainfall montane landscape. The bracken canopy was found to have a distinct seasonal cycle. Autumn was most sensitive to rainfall amount and timing, as late annual rainfall during autumn decreases bracken ET compared to higher summer rainfall followed by a lower autumn rainfall. Comparing the evapotranspiration of bracken from this study to the evapotranspiration of natural grassland in previous studies, the largest difference in evapotranspiration between the canopies occurs in winter.

This paper adds to the landscape ecological integrity (LEI) literature by emphasising the need to move beyond the assumption of a linear relationship between fragmentation metrics and ecological integrity. This study argues that such a relationship is weak or even non-existent when not associated with specific species or ecological process. Thus, using the Greater Accra Region of Ghana as a case, this study assessed the quality and spatio-temporal distribution of terrestrial small mammal habitats, as influenced by changing land cover, highlighting the implications for LEI. First, the study used fragmentation statistics to model changing land cover from 1986 to 2020. This was followed by the use of the Leo Breiman's random forest algorithm to predict small mammal distribution in the same period. The results showed that normalized difference vegetation index (NDVI) has a high predictive importance on small mammal distribution. Decreasing the vegetated areas does not necessarily lead to a decrease in species habitats. However, the decreasing forest areas and shrub-lands leads to a statistically significant increase in small mammal population in built-up areas while their population reduced within farmlands. The paper concludes that an increase in small mammal habitats in built-up areas does mean improved landscape ecological health, considering that these built-up areas are not natural abodes.

China has implemented a series of large-scale afforestation projects to improve its ecological environment in recent decades. Meanwhile, the climate conditions in China have changed substantially. However, whether afforestation or climate change dominates vegetation gross primary production (GPP) in different stages of such afforestation projects is not clear. Here, taking the region of the Shelterbelt Program for Pearl River (SPPR) as the study area, we conducted six scenario simulations using the two-leaf light use efficiency (TL-LUE) model to decouple the effects of land cover change (LCC) and climate factors, i.e., solar radiation (Rad), vapor pressure deficit (VPD), and air temperature (Ta), on forest GPP, and disentangled the impact of various factors on forest GPP in Phase II (2001–2010) and Phase III (2011–2018). We found that industrialization and urbanization slightly changed the total forest area, partly offsetting the ecological benefits of the afforestation project in Phase II, and forest GPP increased slowly. As a result, Rad became the dominant factor of forest GPP increase (the cumulative contribution of 25.68 TgC in 10 years, accounting for 33.51%). In contrast, in Phase III, due to the further expansion of the afforestation area and the natural growth of earlier planted forests, the forest GPP increased rapidly, as did the contribution of LCC. Finally, LCC replaced Rad to become the primary contributor (the cumulative contribution of 114.42 TgC in 8 years, accounting for 60.51%) to the forest GPP increase. During the whole study period, Ta contributed insignificantly to the variation in forest GPP, while to some extent VPD decreased the forest GPP (−12.90% and −4.11% of the contributions in the two phases, respectively). The results suggest that the emergence of ecological benefits of afforestation projects requires a certain time length and forestation scale. Our study provides a basis for formulating effective land use policies.

Impervious surface expansion (ISE) refers to the phenomenon that natural surfaces are covered by artificial materials, such as cement, asphalt, bricks, etc., usually due to human activities. Over recent decades, the rapid growth of the global population, economic development, and continuous urbanization have contributed to extensive ISE, which caused significant losses in terrestrial ecosystem carbon pools. A global assessment effort is lacking because of limited comprehensive data on carbon pools and uncertainties surrounding the extent of ISE. In this study, we aimed to quantify the carbon emissions resulting from global ISE between 1985 and 2020, following the method provided by the Intergovernmental Panel on Climate Change (IPCC) Guidelines. We first divided global land into 87 fine geographical zones by overlaying continental boundary information with an ecological zone map. Then, multiple time-series impervious surface data products, land cover dynamic monitoring product, global biomass data, and topsoil organic carbon (TSOC) information were integrated to build a lookup table (LUT) of biomass and TSOC density for these fine geographical zones. Last, we employed the IPCC method to estimate carbon emissions from ISE between 1985 and 2020. Our findings indicated a global ISE encompassing a total area of 58.12 Mha, with cropland encroachment accounting for 67.30 %. Over the past 35 years, cumulative committed carbon emissions from global ISE reached 1.14 ± 0.38 PgC, with TSOC representing 54.55 % and biomass carbon contributing 45.45 %., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Hydrological change is a conspicuous signal of land use intensification in human-dominated landscapes. We hypothesized that land conversion and land use change increase the availability of lentic habitats and associated biodiversity in Southern Amazonian landscapes through at least four drivers. River damming promotes the formation of reservoirs, which are novel permanent lentic water bodies. A rise in the water table driven by local deforestation promotes the expansion of shallow riparian floodplains. Soil compaction and the deliberate construction of cattle and drainage ponds promote the increase in temporary water bodies in interfluves. We tested these hypotheses using data on habitat characterization and biological surveys of amphibians and fish in forests, pastures and soybean fields in the headwaters of the Xingu River in Mato Grosso, Brazil. Lentic habitat availability sharply increased in deforested land, with consequences to freshwater biodiversity. Reservoir formation influenced both fish and amphibian assemblage structure. Fish species ranged from strongly favored to strongly disfavored by reservoir conditions. Amphibian richness and abundance increased in pasture and soybean streams relative to forests in proportion to the density of reservoirs in the landscape. Expansion of stream floodplains increased the abundance of Melanorivulus megaroni, a fish species indicator of shallow lentic habitats. Rainwater accumulation in temporary ponds and puddles, absent from well-drained forested interfluves, allowed the invasion of converted interfluves by twelve species of open-area amphibians. A literature review indicates that these four drivers of hydrological change are geographically widespread suggesting that we may be witnessing a major yet previously unaccounted form of habitat change in deforested Amazonia, affecting both biodiversity and human health.

Extensive urbanization in coastal southern California has reduced natural habitat in this biodiversity hotspot. To better conserve ecological communities, state and federal agencies, along with local jurisdictions and private stakeholders, developed regional conservation plans for southern California. Although many protected areas exist within this region, the patchwork nature of these protected areas might not provide good coverage for species that require multiple habitat components, such as amphibians with complex life histories. Because of declines in the past century, the status of the western spadefoot (Spea hammondii) in southern California is of concern to state and federal wildlife agencies. Species distribution models (SDMs) can aid in determining the conservation status of imperiled species by projecting where suitable habitat remains and how much is protected from further development. We built SDMs that integrated site-occupancy data from systematic pitfall trapping surveys and presence-only data from biodiversity databases and citizen science platforms to project the current distribution of western spadefoots in southern California. Western spadefoot occurrence was positively related to the cover of grassland or shrub/scrub and the % sand in the soil within a 1000 m buffer, and was negatively related to slope, elevation, and distance to ephemeral streams or vernal pools. Most of the remaining unprotected habitat for western spadefoots is in the southern half of its historical range in western San Diego and Riverside counties. A few large tracts of spadefoot habitat exist on U.S. Department of Defense lands and smaller tracts remain on ecological reserves owned by state and local government agencies. Only small patches of habitat remain in the northern half of this clade’s historical range in Ventura, Orange, Los Angeles, and San Bernardino counties. Existing regional conservation plans provide ostensible spatial coverage of the majority of extant habitat for western spadefoots in southern California, but most of the habitat within the jurisdiction of these plans lacks formal protection, exposing this species to further declines as urbanization continues in the 21st century.

As forest is under increasing pressure, the rapid conversion or degradation of forest has attracted strong concern. Obtaining quantitative information of forest change based on satellite imagery becomes necessary and urgent, especially the detailed “from-to” information. In this study, a semi-automatic method called direction-dominated change vector analysis (DCVA) was proposed to detect “from-to” information of forest change. DCVA is composed of three steps: (1) determining candidate changed pixels, (2) determining direction ranges for different forest change types, and (3) determining final changed pixels for each forest change type. Like the classic change vector analysis (CVA), the magnitude and direction of change vector (CV) are used to detect the changed areas and types in DCVA, respectively. However, CVA is “magnitude-dominated” by setting only one magnitude threshold for different change types, while DCVA is “direction-dominated” by determining change types according to change direction at first, followed by setting different magnitude threshold for each change type. In this case, DCVA holds the advantage of accurately detecting changed areas for different change types by considering the specific characteristics of each change type. Experiments are performed with Sentinel-2A satellite images to demonstrate the advantages of DCVA for forest change detection. The changed areas with four types of forest change were successfully extracted by DCVA. The comparison of both geometric and thematic accuracies between DCVA and CVA further indicates the effectiveness of the proposed method for forest change detection.

Land use and land cover change (LULCC) is a general term for the human modification of Earth's terrestrial surface. These modifications come by direct and indirect activities of human actions when securing essential resources. Therefore, it is necessary to analyze these land changes for the best management of natural resources and to ensure better livelihood of the inhabitants.The influx of population from the Kumasi metropolis and peripheral areas coupled with urbanization is causing rapid changes to LULC in the Atwima Nwabiagya District. This has put pressure on the land cover especially in the forest cover areas and has affected the socioeconomic activities in the district. In view of this problem, this research sought to map and analyze the spatio-temporal LULCC patterns using multi-temporal satellite images from 1986-2019 and to identify the socioeconomic factors and their impact of LULC on the study area. Seven LULC classes were identified including; bare land, closed forest, cropland, open forest, savannah, settlement, and water. The results showed that during the period under review (1986-2019) there have been losses of 4178.5 hectares (7%) in closed and open forest and bare land whilst crop land and settlement have seen an increase of 21685.3 hectares (37%). In all, settlement establishment as a result of population increase, commercial activities, and porous land tenure system was identified as the main factors for LULCC in the Atwima Nwabiagya District.

The effects of riparian restoration and soil and water conservation practices on catchment hydrology are still unclear. Here, we assess whether a positive change in soil and water conservation practices and riparian reforestation will affect the water availability and boost resilience in a Brazilian Cerrado basin under climate change scenarios. This study was developed in the Três Marias basin (50.600 km²) located in southeastern Brazil. First, we calibrated (1992–2005) and evaluated (2006–2012) the Soil and Water Assessment Tool (SWAT) model. Then, we created a land cover and land use change (LCLUC) scenario that considers improving soil and water conservation practices and the reforestation of riparian zones, following the recommendations of the Brazilian Payment for Ecosystem Services (PES). We also used the trend SSP2-4.5 and the fossil-based economy SSP5-8.5 (Shared Socioeconomic Pathways) climate scenarios data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) project for the period of 2015–2100. Along with a decrease of 5 %–15 % in precipitation in the projected period, an increase of 7 %–15 % in forest areas due to the LCLUC scenarios generated an increase in evapotranspiration values up to 38 %, resulting in a decrease of surface runoff and baseflow. Riparian reforestation and soil and water conservation practices did not necessarily enhance water availability on the simulations performed, as expected by many PES.

Land Cover (LC) is going through a dramatic change due to rapid urbanization, especially in urban areas. The impervious land covers (built-up areas) are replacing the natural land covers (vegetation and waterbody) rapidly, which significantly contributes to the increase of Land Surface Temperature (LST). Increased LST deteriorates the meteorological condition in urban areas and causes Surface Urban Heat Island (SUHI) effect. The vulnerability of the SUHI effect can be described quantitatively and qualitatively by Urban Thermal Field Variance Index (UTFVI) phenomenon. The study investigates the changing pattern of the SUHI and its magnitude with Landsat TM/OLI time-series satellite imageries from 1988 to 2018 and establishes the relationship between LC change and LST variations in Chattogram city. The relationships are defined by correlation analysis, cross-section profiles, and Simple Linear Regression Models (SLRM). The results suggest that vegetation cover, water body, and bare-soil have decreased by 2%, 7%, and 10%, respectively, where the built-up area has increased by 19% in the study area during the study period. The average LST of the study area has increased by approximately 10 °C in the last 30 years. Weightage of the SUHI affected area has also increased over time due to its direct linkage with LST. No area was affected by the SUHI phenomenon in 1988, which was found more than 35% in 2018. Only 1.69% area was found under the strongest UTFVI phenomenon in 1988, which increased significantly by 27.53% in 2018. In statistical analysis, regression models are used to define LC and LST relationship for every LC type. The LC and LST relationship analyses demonstrate a significant positive correlation with the built-up area while it is negative with vegetation, waterbody, and bare soil. The findings of this study will help city officials and policymakers to prepare a sustainable urban land development plan to minimize the negative consequences of unplanned urbanization and heat stress-related issues.

Quantifying the impacts of vegetation restoration (VR) on energy exchange is essential for exploring climate-vegetation interactions. Due to the complexity of land–atmosphere energy exchange and limited observation networks, the influence of VR on the energy balance remains unclear. To improve the understanding of the energy budget change associated with VR in the Loess Plateau (LP), we performed a series of sensitivity simulation experiments using the Community Land Model within the Community Earth System Model, and the spatiotemporal responses of energy exchange to VR and the roles of VR in the variations in energy budget under climate change were investigated. The results showed that the land cover changes from 2000 to 2015 exerted a positive effect on net radiation (NR) and sensible heat (SH), and evident increases in annual mean NR and SH were found in the southeastern LP where larger-scale cropland was converted to grassland or forestland, with increasing magnitudes exceeding 2 W/m2. Latent heat (LH) increased only during May–July, particularly on the southern edge of LP. The increasing magnitudes of NR and LH under Representative Concentration Pathway (RCP)8.5 were larger than those under RCP4.5, with the greatest differences being approximately 4 W/m2 and 5 W/m2 during 2081–2100 for NR and LH, respectively. SH remained nearly stable under RCP4.5 and showed a weak decrease under RCP8.5. Under the same RCP, only slight differences in the energy budget components were detected between the land cover condition in 2015 and 2000, with the largest difference of 0.8 W/m2 in SH during 2021–2040. These results suggested that although both VR and climate warming exerted positive effects on NR, the impact of climate change was larger than that of VR in the LP, and a shift in the local surface energy budget toward LH would occur with climate warming.

Understanding where ecosystem services (ES) are and quantifying their supply using stakeholderś information is key for effective sustainable management. This paper describes a participatory methodology for extracting stakeholders’ ES perception for continental Portugal based on land cover using analytical hierarchy process (AHP), matrix-based approach with data visualization techniques, and scenario analysis. Results show that drought regulation was the most valued ES by stakeholders and recreation was considered the least important. Results also show that the “Agricultural areas and “Forests and semi-natural areas” land cover classes provide about two-thirds of the total ES for the country. An “Economic development” scenario will yield negative values for all ES except recreation and food supply, whereas an “Environmental development” scenario will increase all ES, except food supply. Finally, a “Sustainable development” scenario, presents values between the previous two scenarios and is the best for food supply. This operational methodology for extracting information from stakeholders and to report information on the mapping and assessment of ES can be helpful for sustainable planning in Portugal and elsewhere.

Sundarban mangrove is the largest continuous mangrove forest in the world and is the habitat of an incredible amount of biodiversity. Biodiversity loss and degradation of this highly ecologically productive mangrove forest due to climate change will have a tremendous impact on the livelihood of the people living in the deltaic region. The present study was aimed to find out the dynamics of change in different land cover for the greater Sundarban region. The multi-temporal Landsat images were used to understand the dynamics in three decades from 1998 to 2018. The analysis revealed that Sundarban mangrove forest changed very insignificantly. The change between 1998 and 2008 was approximately 1.2%, i.e. around 26.2 km2, and the change between the year 2008 and 2018 was approximately 1.27%, which consists of 28 km2. However, the dynamics of open mangrove forest and dense mangrove forest were found very high. The human habitat and aquaculture were found as the most rapidly expanding land-use type in this landscape. Area under human habitat has increased approximately 80%, i.e. nearly 654 km2 between 1998 and 2018; area under aquaculture has increased approximately 116% (i.e. around 231 km2) between 1998 and 2008. The MLP-Markov Chain based modelling of land-use has shown an overwhelming increase in human habitat in near future. However, being situated in the close vicinity of dense human population of the city Kolkata, the mangrove habitat remained intact, which is largely due to great amount of conservation efforts that have been exercised by the Govt. and the local forest department. The landscape statistical analysis for understanding the ecological dynamics of every land cover types showed that in 2018, the human habitat became second dominant category in this study area. The aquaculture practice for high economic value has pushed down the native agricultural practice in the region.

Natural and anthropogenic forces on Earth create changes in biophysical characteristics of landscapes in the forms of modifications or transformations. Since landscapes are composed of spatially configured patches of different land cover types, changes in the pattern composition and configuration may be used as indicators for identifying environmental trends and their underlying causes. To this end, pattern indices hold a strong potential to conceptualize landscape structure in many different ways. This study aims to analyse landscape changes in an urbanized coastal landscape in the eastern Mediterranean region of Turkey using pattern indices as development indicators. For this purpose, the spatial distribution of built-up areas was extracted for the years 1989, 1995, 2001, 2007 and 2019 using geo-referenced SPOT and Sentinel images. Eight landscape structure indices were calculated to demonstrate spatial and temporal diversity of area/edge, shape and aggregation characteristics of built-up patches. These indices are (1) class area (CA), (2) percentage of landscape (PL), (3) largest patch index (LPI), (4) edge density, (5) perimeter-area ratio (PARA), (6) fractal dimension (FRAC), (7) related circumscribing circle (RCC) and (8) percentage of like-adjacencies (PLADJ). The study area was divided into 215 grid-units to represent spatial diversity of development. The aforementioned indices were calculated separately for each of the units. The spatial distribution of built-up areas was also associated with land capability to assess land degradation trends. Results showed that much of the development occurred on Class I and II lands that are in fact prime agricultural areas. Results also suggest that the structure of building patches and the way that it changes vary between the coast and inland.

The Greater Accra region is the most urbanized region in Ghana. Over the last decade, the region has undergone rapid population shift and urban sprawl. This has modified the natural environment of the area and led to the formation and warming of Urban Heat Island (UHI). Previous studies have not established enough evidence on the existence of UHI phenomenon in the region. For this reason, this study examined the existence, magnitude, and spatial extent of UHI warming as well as its effect on temperature extremes in the region. The study used Landsat satellite imagery captured in 1991, 2002 and 2017, and in-situ daily minimum and maximum temperature data spanning the period 1980 to 2017. The satellite images were processed and analyzed using an integrated Geographic Information System (GIS) and remote sensing technique while extreme temperature indices were assessed with the ClimPACT2 software. The study found that UHI existed in the region with an increasing spatial coverage and a magnitude of about 4.07 ∘C, 5.79 ∘C, and 4.86 ∘C in 1991, 2002, and 2017 respectively. The built-up and bare land areas experienced the strongest effect of UHI warming. In addition, enhanced UHI warming effect caused an increase in the frequency and intensity of warm temperature extremes in the region. A faster increase in night time temperatures than day time resulted in a decrease in diurnal temperature range of the region. Considering the high rate of warming amidst rapid urban expansion, more warming is expected in the region. This is expected to exacerbate climate extreme events and weather-related health issues. It is also expected to increase energy consumption, air pollution and human discomfort.

Tanguar Haor is one of the two listed Ramsar Site of this country which contains a rich amount of biodiversity as well as a highly productive ecosystem. But the valuable landscape undergoes a radical change in its form over the decades. This study uses past and recent satellite data to evaluate the typical landscape change over the decades. Both pre-classification and post classification change detection approach was used to assess the change result from 1980 to 2010. In pre-classification approach CVA, NDVI and NDWI analysis were implemented to assess the change scenario. Maximum likelihood supervised classification technique was performed to create the signature class of significant land cover category (deep water, shallow water, vegetation, and settlement). After ensuring satisfactory accuracy value for each classified image a detail post classification change detection analysis was executed. Image differencing, statistical change detection techniques (transition probability matrix), change dynamics analysis was also operated to evaluate the statistics of past change relative to present. This study illustrated that, about 40% land cover of the total study area has been converted over 30 years period. Forested and high land vegetation’s are disappearing rapidly, deep water bodies consist of large lakes are becoming the rare feature of the study area. Widespread development of settlement and dominant shallow water feature are converting the natural wetland a permanent low lying agricultural land.

The Three Gorges Project, the largest hydroelectric project in the world, has attracted widespread attention regarding its impact on regional climate. However, existing studies on the climate effects of the Three Gorges Project construction are not sufficient due to limited data accumulation. In this study, we analyzed the annual and seasonal trend changes in temperature, precipitation, and humidity over the Three Gorges Reservoir Area (TGRA) based on long-term meteorological stations data, remote sensing data, and reanalysis products. Observation minus reanalysis method (OMR) was used to reveal possible impacts of land cover changes on climate changes. Major results indicated that the TGRA experienced an overall warming trend for both annual and seasonal variations, with greater rising trends in the upstream. Except for autumn, the relative humidity of most regions mainly showed significant downward trends, indicating an overall drying trend in the TGRA. There was insignificant change in total precipitation and precipitable water vapor, with the largest variation observed during the summer. Although there were small differences among these datasets, their results of climate changes showed good consistency overall. In addition, the results of OMR indicated that land cover changes mainly had a warming and drying effect on the middle and upper reaches, and a cooling and moistening effect on the lower reaches of the TGRA. This may be due to the impact of land cover changes on the surface energy balance, thus affected temperature and humidity. The study has important reference value for understanding the climate changes in the TGRA and the climate effects brought about by large-scale engineering construction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Climate change and human activity have resulted in increasing change of vegetation growth globally. Numerous studies have been conducted on extreme climate events and analyses of ecological environment evolution. However, such studies have placed little emphasis on vegetation change and spatial variation in this type of ecotone. Accordingly, this study analyzed the changes in vegetation type and growth using the 16-d composite MOD13A1 product with 1-km resolution and MOD12Q1 product with 1-km resolution. We used the mean, maximum, standard deviation normalized-difference vegetation index (NDVI) values, and the rate of change (ROC) of NDVI value to explain vegetation changes within the studied ecotone. Our results showed that significant vegetation type and growth changes have occurred in the study area. From 2001 to 2013, for example, with the exception of 2001, 2004 and 2009, a certain extent of grassland area was converted to cropland. Drought severity index (DSI) results indicate that there exists drought in 2001, 2004 and 2009. Such temporal changes in cropland and grassland area confirmed the ecological vulnerability of the ecotone. At the same time, vegetation varied spatially from west to east and from south to north. The mean, maximum and standard deviation NDVI values were all sorted in descending order based on differences in latitude and longitude, as follows: NDVI2013>NDVI2009>NDVI2004>NDVI2001

Study region: The Thames catchment in southern England, UK. Study focus: Modelling with 124 years of rainfall, potential evaporation (PE), temperature and naturalised flow data. Daily rainfall-runoff flow simulation using current and three historic land cover scenarios to determine the stationarity of catchment response examined through three time-frames of analysis – annual, seasonal and flow extremes. The criterion of response stationarity is often assumed in climate change impact studies. New hydrological insights: The generally close correspondence between observed and simulated flows using the same model parameter values for the whole period is indicative of the temporal stability of hydrological processes and catchment response, and the quality of the hydrometric data. Changes that have occurred are a decrease in flood peak response times, typically two to three days pre and post the early 1940s, from change in agricultural practices and channel conveyance, and an increase of about 15% in summer flow from increase in urban land cover between the first decade of the 20th and 21st centuries. The water balance was found to be sensitive to the PE data used, with care needed to avoid discontinuity between two parts of the data record using different methods for calculation. Long-term mean annual rainfall shows little change but contrasting patterns of variation in seasonal rainfall demonstrate a variable climate for which simulated flow is similar to observed flow.

The biodiversity of the Andean Chocó in western Ecuador and Colombia is threatened by anthropogenic changes in land cover. The main goal of this study was to contribute to conservation of 12 threatened species of amphibians at a cloud forest site in northwestern Ecuador, by identifying and proposing protection of critical areas. We used Geographic Information Systems (GIS) and remote sensing techniques to quantify land cover changes over 35 years and outline important areas for amphibian conservation. We performed a supervised classification of an IKONOS satellite image from 2011 and two aerial photographs from 1977 and 2000. The 2011 IKONOS satellite image classification was used to delineate areas important for conservation of threatened amphibians within a 200 m buffer around rivers and streams. The overall classification accuracy of the three images was ≥80%. Forest cover was reduced by 17% during the last 34 years. However, only 50% of the study area retained the initial (1977) forest cover, as land was cleared for farming and eventually reforested. Finally, using the 2011 IKONOS satellite image, we delineated areas of potential conservation interest that would benefit the long term survival of threatened amphibian species at the Ecuadorian cloud forest site studied.

Conversion of natural land cover can degrade water quality in water supply watersheds and increase treatment costs for Public Water Systems (PWSs), but there are few studies that have fully evaluated land cover and water quality relationships in mixed use watersheds across broad hydroclimatic settings. We related upstream land cover (forest, other natural land covers, development, and agriculture) to observed and modeled water quality across the southeastern US and specifically at 1746 PWS drinking water intake facilities. While there was considerable complexity and variability in the relationship between land cover and water quality, results suggest that Total Nitrogen (TN), Total Phosphorus (TP) and Suspended Sediment (SS) concentrations decrease significantly with increasing forest cover, and increase with increasing developed or agricultural cover. Catchments with dominant (>90 %) agricultural land cover had the greatest export rates for TN, TP, and SS based on SPARROW model estimates, followed by developed-dominant, then forest- and other-natural-dominant catchments. Variability in modeled TN, TP, and SS export rates by land cover type was driven by variability in natural background sources and catchment characteristics that affected water quality even in forest-dominated catchments. Both intake setting (i.e., run-of-river or reservoir) and upstream land cover were important determinants of water quality at PWS intakes. Of all PWS intakes, 15 % had high raw water quality, and 85 % of those were on reservoirs. Of the run-of-river intakes with high raw water quality, 75 % had at least 50 % forest land cover upstream. In addition, PWS intakes obtaining surface water supply from smaller upstream catchments may experience the largest losses of natural land cover based on projections of land cover in 2070. These results illustrate the complexity and variability in the relationship between land cover and water quality at broad scales, but also suggest that forest conservation can enhance the resilience of drinking water supplies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier B.V.)

Agriculture is one the main drivers of bird decline in both Europe and North America. While it is clear that agricultural practices and changes in the rural landscape directly and indirectly affect bird communities, we still do not know the extent to which these impacts might change across broad spatial and temporal scales. To address this question, we combined information on agricultural activities with occurrence and abundance of 358 bird species across five time periods spanning 20 years in Canada. As a proxy for agricultural impact, we used a combined index that included different agricultural metrics, such as cropland and tillage area and area treated with pesticides. We found that agriculture impact was negatively associated with bird diversity and evenness across all 20 years studied, but these associations seemed to vary by region. We found good support for an overall negative association between agriculture impact and bird diversity and evenness in the Eastern and Atlantic regions but weaker associations in the Prairies and Pacific. These findings suggest that agricultural activities result in bird communities that are less diverse and disproportionately benefit certain species. The spatial variation in the impact of agriculture on bird diversity and evenness we observed is likely a result of regional differences in the native vegetation, the type of crops and commodities produced, the historical context of agriculture, as well as the native bird community and the extent of their association with open habitat. Thus, our work provides support for the idea that the on-going agricultural impact on bird communities, while largely negative, is not uniform, and can vary across broad geographic regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Impacts of land cover conversion have been studied well from the top-of-canopy level using satellite observations. Yet, the warming or cooling impacts of land cover and management change (LCMC) from below-canopy level remain less explored. Here, we studied the below-canopy temperature change from field to landscape level across multiple LCMC in southeastern Kenya. To study this, in situ microclimate sensors, satellite observations, and high-resolution below-canopy temperature modelling approaches were used. Our results show that from field to landscape scale, forest to cropland conversion, followed by thicket to cropland change, generate higher surface temperature warming than other conversion types. At field scale, tree loss increases the mean soil temperature (measured at 6 cm below ground) more than the mean below-canopy surface temperature but its impact on the diurnal temperature range was higher on surface temperature than soil temperature in both forest to cropland and thicket to cropland/grassland conversions. At landscape scale, compared with top-of-canopy land surface temperature warming, which was estimated at Landsat overpass time (∼10:30 a.m.), forest to cropland conversion generates ∼3 °C higher below-canopy surface temperature warming. Land management change, through fencing of wildlife conservation areas and limiting mobility of mega browsers, can have an impact on woody cover and induce more below-canopy surface temperature warming than top-of-canopy in comparison with non-conservancy areas. These results indicate that human induced land changes can generate more below-canopy warming than inferred from top-of-canopy satellite observations. Together, the results highlight the importance of considering the climatic impacts of LCMC from both top-of-canopy and below-canopy level for effective mitigation of anthropogenic warming from land surface changes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Drought-land cover change (D-LCC) is considered to be an important stress factor that affects vegetation greenness and productivity (VG&P) in global terrestrial ecosystems. Understanding the effects of D-LCC on VG&P benefits the development of terrestrial ecosystem models and the prediction of ecosystem evolution. However, till today, the mechanism remains underexploited. In this study, based on the Theil-Sen median estimator and Mann-Kendall test, Hurst exponent evaluation and rescaled range analysis (R/S), Pearson and Partial correlation coefficient analyses, we explore the spatiotemporal distribution characteristics and future trends of Leaf area index (LAI), Net primary productivity (NPP), Solar-induced chlorophyll fluorescence (SIF), Standardized precipitation evapotranspiration index (SPEI), Soil moisture (SM), Land cover type (LC), and the impact mechanism of D-LCC on global VG&P. Our results provide four major insights. First, three independent satellite observations consistently indicate that the world is experiencing an increasing trend of VG&P: LAI (17.69 %), NPP (20.32 %) and SIF (16.46 %). Nonetheless, productivity-reducing trends are unfolding in some tropical regions, notably the Amazon rainforest and the Congo basin. Second, from 2001 to 2020, the frequency, severity, duration, and scope of global droughts have been increasing. Third, the impact of land cover change on global VG&P is region-dependent. Finally, our results indicate that the continuous growth of VG&P in the global vegetation area is likely to become more difficult to maintain., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)