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Land-use and climate change are major pressures on terrestrial biodiversity. Species' extinction risk and responses to human pressures relate to ecological traits and other characteristics in some clades. However, large-scale comparative assessments of the associations between traits and responses to multiple human pressures across multiple clades are needed. We investigated whether a set of ecological characteristics that are commonly measured across terrestrial vertebrates (ecological traits and geographic range area) are associated with species' responses to different land-use types and species' likely sensitivity to climate change. We aimed to test whether generalizable patterns in response to these pressures arise across both pressures and across vertebrate clades, which could inform assessments of the global signature of human pressures on vertebrate biodiversity and guide conservation efforts. At the species level, we investigated associations between land-use responses and ecological characteristics with a space-for-time substitution approach, making use of the PREDICTS database. We investigated associations between ecological characteristics and expected climate-change sensitivity, estimated from properties of species realized climatic niches. Among the characteristics we considered, 3 were consistently associated with strong land-use responses and high climate-change sensitivity across terrestrial vertebrate classes: narrow geographic range, narrow habitat breadth, and specialization on natural habitats (which described whether a species occurs in artificial habitats or not). The associations of other traits with species' land-use responses and climate-change sensitivity often depended on species' class and land-use type, highlighting an important degree of context dependency. In all classes, invertebrate eaters and fruit and nectar eaters tended to be negatively affected in disturbed land-use types, whereas invertebrate-eating and plant- and seed-eating birds were estimated to be more sensitive to climate change, raising concerns about the continuation of ecological processes sustained by these species under global changes. Our results highlight a consistently higher sensitivity of narrowly distributed species and habitat specialists to land-use and climate change, which provides support for capturing such characteristics in large-scale vulnerability assessments., (© 2023 Society for Conservation Biology.)

The continuous increase of urbanization and industrialization brought various climatic changes, leading to global warming. The unavailability of meteorological data makes remotely sensed data important for understanding climate change. Therefore, the land surface temperature (LST) is critical in understanding global climate changes and related hydrological processes. The main objective of this work is to explore the dominant drivers of land use and hydrologic indices for LST in drainage and non-drainage areas. Specifically, the relationship between LST changes, land use, and hydrologic indices in Northeast Qena, Egypt, was investigated. The Landsat 5 and 8 imagery, Geographic Information System (GIS), and R-package were applied to identify the change detection during 2000-2021. The normalized difference between vegetation index (NDVI), bare soil index (BSI), normalized difference built-up, built-up index (BUI), modified normalized difference water index (MNDWI), and soil-adjusted vegetation index (SAVI) were employed. The non-drainage or mountain areas were found to be more susceptible to high LST values. The comprehensive analysis and assessment of the spatiotemporal changes of LST indicated that land use and hydrologic indices were driving factors for LST changes. Considerably, LST retrieved from the Landsat imaginary showed significant variation between the maximum LST during 2000 (44.82°C) and 2021 (50.74°C). However, NDBI has got less spread during the past (2000) with 10-13%. A high negative correlation was observed between the LST and NDVI, while the SAVI and LST positively correlated. The results of this study provide relevant information for environmental planning to local management authorities., 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 Ltd. All rights reserved.)

Detecting biodiversity change and identifying its causes is challenging because biodiversity is multifaceted and temporal data often contain bias. Here, we model temporal change in species' abundance and biomass by using extensive data describing the population sizes and trends of native breeding birds in the United Kingdom (UK) and the European Union (EU). In addition, we explore how species' population trends vary with species' traits. We demonstrate significant change in the bird assemblages of the UK and EU, with substantial reductions in overall bird abundance and losses concentrated in a relatively small number of abundant and smaller sized species. By contrast, rarer and larger birds had generally fared better. Simultaneously, overall avian biomass had increased very slightly in the UK and was stable in the EU, indicating a change in community structure. Abundance trends across species were positively correlated with species' body mass and with trends in climate suitability, and varied with species' abundance, migration strategy and niche associations linked to diet. Our work highlights how changes in biodiversity cannot be captured easily by a single number; care is required when measuring and interpreting biodiversity change given that different metrics can provide very different insights. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Monitoring and assessing ecological quality (EQ) can help to understand the status and dynamics of the local ecosystem. Moreover, land use and climate change increase uncertainty in the ecosystem. The Luanhe River Basin (LHRB) is critical to the ecological security of the Beijing-Tianjin-Hebei region. To support ecosystem protection in the LHRB, we evaluated the EQ from 2001 to 2020 based on the Remote Sensing Ecological Index (RSEI) with the Google Earth Engine (GEE). Then, we introduced the coefficient of variation, Theil-Sen analysis, and Mann-Kendall test to quantify the variation and trend of the EQ. The results showed that the EQ in LHRB was relatively good, with 61.08% of the basin rated as 'good' or 'excellent'. The spatial distribution of EQ was low in the north and high in the middle, with strong improvement in the north and serious degradation in the south. The average EQ ranged from 0.58 to 0.64, showing a significant increasing trend. Furthermore, we found that the expansion of construction land has caused degradation of the EQ, whereas climate change likely improved the EQ in the upper and middle reaches of the LHRB. The results could help in understanding the state and trend of the eco-environment in the LHRB and support decision-making in land-use management and climate change.

Mounting evidence suggests that climate change, agricultural intensification and disease are impacting bumblebee health and contributing to species' declines. Identifying how these factors impact insect communities at large spatial and temporal scales is difficult, partly because species may respond in different ways. Further, the necessary data must span large spatial and temporal scales, which usually means they comprise aggregated, presence-only records collected using numerous methods (e.g. diversity surveys, educational collections, citizen-science projects, standardized ecological surveys). Here, we use occupancy models, which explicitly correct for biases in the species observation process, to quantify the effect of changes in temperature, precipitation and floral resources on bumblebee site occupancy over the past 12 decades in North America. We find no evidence of genus-wide declines in site occupancy, but do find that occupancy is strongly related to temperature, and is only weakly related to precipitation or floral resources. We also find that more species are likely to be climate change 'losers' than 'winners' and that this effect is primarily associated with changing temperature. Importantly, all trends were highly species-specific, highlighting that genus or community-wide measures may not reflect diverse species-specific patterns that are critical in guiding allocation of conservation resources.

The main objective of this work is the future prediction of the floods in India due to climate and land change. Human activity and related carbon emissions are the primary cause of land use and climate change, which has a substantial impact on extreme weather conditions, such as floods. This study presents high-resolution flood susceptibility maps of different future periods (up to 2100) using a combination of remote sensing data and GIS modelling. To quantify the future flood susceptibility various flood causative factors, Global circulation model (GCM) rainfall and land use and land cover (LULC) data are envisaged. The present flood susceptibility model has been evaluated through receiver operating characteristic (ROC) curve, where area under curve (AUC) value shows the 91.57% accuracy of this flood susceptibility model and it can be used for future flood susceptibility modelling. Based on the projected LULC, rainfall and flood susceptibility, the results of the study indicating maximum monthly rainfall will increase by approximately 40-50 mm in 2100, while the conversion of natural vegetation to agricultural and built-up land is about 0.071 million sq. km. and the severe flood event area will increase by up to 122% (0.15 million sq. km) from now on., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Wilderness areas are not immune to changes in land use, land cover, and/or climate. Future changes will intensify the balancing act of maintaining ecological conditions and untrammeled character within wilderness areas. We assessed the quantitative and spatial changes in land use, land cover, and climate predicted to occur in and around wilderness areas by (1) quantifying projected changes in land use and land cover around wilderness areas; (2) evaluating if public lands surrounding wilderness areas can buffer future land-use change; (3) quantifying future climate conditions in and around wilderness areas; and (4) identifying wilderness areas expected to experience the most change in land use, land cover, and climate. We used projections of land use (four variables), land cover (five variables), and climate (nine variables) to assess changes for 707 wilderness areas in the contiguous United States by mid-21st century under two scenarios (medium-low and high). We ranked all wilderness areas relative to each other by summing and ranking decile values for each land use, land cover, and climate variable and calculating a multivariate metric of future change. All wilderness areas were projected to experience some level of change by mid-century. The greatest land-use changes were associated with increases in agriculture, clear cutting, and developed land, while the greatest land cover changes were observed for grassland, forest, and shrubland. In 51.6% and 73.8% of wilderness areas, core area of natural vegetation surrounding wilderness was projected to decrease for the medium-low and high scenarios, respectfully. Presence of public land did not mitigate the influence of land-use change around wilderness areas. Geographically, projected changes occurred throughout the contiguous U.S., with areas in the northeast and upper Midwest projected to have the greatest land-use and climate change and the southwestern U.S. projected to undergo the greatest land cover and climate change. Our results provide insights into potential future threats to wilderness areas and the challenges associated with wilderness stewardship and climate adaptation. Despite the high degree of protection and remoteness of wilderness areas, effective management and preservation of these lands must consider future changes in land use, land cover, and climate., (© 2021 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

The interaction of land use/land cover (LULC) and climate change, to a large extent, involves anthropogenic activities. This study was carried out in the derived savannah of Nigeria, a delicate, transition ecological zone between the rainforest and savanna zones where the interaction of LULC and climate change could be well appreciated. Using the remote sensing and GIS, Land Change Modeler (LCM), and multivariate geostatistics tools, the study evaluated coupled interaction between LULC and climate change and assessed the changes in the land use/land cover patterns for the periods 1972, 1986, 2002, and 2019. It also evaluated the present (1941-2019) and future (2020-2050) variability in rainfall patterns and made an attempt to predict the interaction between LULC and climate change in future climate. The results suggest that the urban (built-up) area, waterbody, woodland, and farmland experienced a rapid increase of about 2,400%, 583%, 277%, and 32%, respectively, while the forest cover lost about 39% between 1972 and 2019. Furthermore, the study predicted 46% and 29% reduction in the forested area between 2002 and 2050 and 2019 and 2050, respectively. The study concludes that rainfall will be the major driver of LULC change within the study area under a future climate., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This paper assesses the long-term combined effects of land use (LU) and climate change on river hydrology and water scarcity of two rivers of the Western Ghats of India. The historical LU changes were studied for four decades (1988-2016) using the maximum likelihood algorithm and the long-term LU (2016-2075) was estimated using the Dyna-CLUE prediction model. Five General Circulation Models (GCMs) were utilized to assess the effects of climate change (CC) and the Soil and Water Assessment Tool (SWAT) model was used for hydrological modeling of the two river catchments. To characterize granular effects of LU and CC on regional hydrology, a scenario approach was adopted and three scenarios depicting near-future (2006-2040), mid-future (2041-2070), and far-future (2071-2100) based on climate were established. The present rate of LU change indicated a reduction in forest cover by 20% and an increase in urbanized areas by 9.5% between 1988 and 2016. It was estimated that forest cover in the catchments may be expected to halve compared to the present-day LU (55% in 2016 to 23% in 2075), along with large-scale conversion to agricultural lands (13.5% in 2016 to 49.5% in 2075). As a result of changes to LU and forecasted climate, it was found that rivers in the Western Ghats of India might face scarcity of fresh water in the next two decades until the year 2040. However, because of large-scale LU conversion toward the year 2050, streamflow in rivers might increase as high as 70.94% at certain times of the year. Although an increase in streamflow is perceived favorable, the streamflow changes during summer and winter may be expected to affect the cropping calendar and crop yield. The changes to streamflow were also linked to a 4.2% increase in ecologically sensitive wetlands of the Aghanashini river catchment., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Increased climate variability as a result of anthropogenic climate change can threaten the functioning of ecosystem services. However, diverse responses to climate change among species (response diversity) can provide ecosystems with resilience to this growing threat. Measuring and managing response diversity and resilience to global change are key ecological challenges. Here, we develop a novel index of climate resilience of ecosystem services, exemplified by the thermal resilience of predator communities providing biological pest control. Field assays revealed substantial differences in the temperature-dependent activity of predator species and indices of thermal resilience varied among predator communities occupying different fields. Predator assemblages with higher thermal resilience provided more stable pest control in microcosms where the temperature was experimentally varied, confirming that the index of thermal resilience developed here is linked to predator function. Importantly, complex landscapes containing a high number of non-crop habitat patches were more likely to contain predator communities with high thermal resilience. Thus, the conservation and restoration of non-crop habitats in agricultural landscapes-practices known to strengthen natural pest suppression under current conditions-will also confer resilience in ecosystem service provisioning to climate change.

The conceptualization of the Shared Socioeconomic Pathways (SSPs) framework represented a major leap in scenario development in the context of global environmental change and sustainability, providing significant advances from the previous scenario frameworks-especially the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios. It is highly likely that the SSP concept, along with its scenario narratives and their respective results, including land-use change projections, will play a substantial role in the forthcoming Sixth Assessment Report by the IPCC. Here, we offer some insights that could make the SSPs' projected future changes in global land use more comprehensive and also help improve the interpretability of such projections. For example, instead of focusing on the quantity of each land-use class at various time points which results only in a net change when change is detected between time points, we recommend that the projected gross gains and gross losses in each land-use class across all scenarios should also be considered. Overall, the insights presented could also help pave the way for stronger collaboration between the SSP-climate science community and the land system science community; such collaboration is much needed in addressing the challenges of global environmental change towards a climate-resilient sustainable development pathway.

The European Union's 2030 climate and energy policy and the 2030 Agenda for Sustainable Development underline the commitment to mitigate climate change and reduce its impacts by supporting sustainable use of resources. This commitment has become stricter in light of the ambitious climate neutrality target set by the European Green Deal for 2050. Water, Energy and Food are the key variables of the "Nexus Thinking" which face the sustainability challenge with a multi-sectoral approach. The aim of the paper is to show the methodological path toward the implementation of an integrated modeling platform based on the Nexus approach and consolidated energy system analysis methods to represent the agri-food system in a circular economy perspective (from the use of water, energy, biomass, and land to food production). The final aim is to support decision-making connected to climate change mitigation. The IEA-The Integrated MARKAL-EFOM System (TIMES) model generator was used to build up the Basilicata Water, Energy and Food model (TIMES-WEF model), which allows users a comprehensive evaluation of the impacts of climate change on the Basilicata agri-food system in terms of land use, yields and water availability and a critical comparison of these indicators in different scenarios. The paper focuses on the construction of the model's Reference Energy and Material System of the TIMES model, which integrates water and agricultural commodities into the energy framework, and on the results obtained through the calibration of the model β version to statistical data on agricultural activities.

The impacts of climate change on soil erosion are mainly caused by the changes in the amount and intensity of rainfall and rising temperature. The combination of rainfall and temperature change is likely to be accompanied by negative or positive variations in agricultural and forest management. Turkey contains vast fertile plains, high mountain chains and semi-arid lands, with a climate that ranges from marine to continental and therefore is susceptible to soil erosion under climate change, particularly on high gradients and in semi-arid areas. This study aims to model the soil erosion risk under climate change scenarios in Turkey using the Pan-European Soil Erosion Assessment (PESERA) model, predicting the likely effects of land use/cover and climate change on sediment transport and soil erosion in the country. For this purpose, PESERA was applied to estimate the monthly and annual soil loss for 12 land use/cover types in Turkey. The model inputs included 128 variables derived from soil, climate, land use/cover and topography data. The total soil loss from the land surface is speculated to be approximately 285.5 million tonnes per year. According to the IPCC 5th Assessment Report of four climate change scenarios, the total soil losses were predicted as 308.9, 323.5, 320.3 and 355.3 million tonnes for RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios respectively from 2060 to 2080. The predicted amounts of fertile soil loss from agricultural land in a year were predicted to be 55.5 million tonnes at present, and 62.7, 59.9, 61.7 and 58.1 under RCP2.6, RCP4.5, RCP6.0 and RCP8.5 respectively. This confirms that approximately 30% of the total erosion occurs over the agricultural lands. In this respect, degraded forests, scrub and arable lands were subjected to the highest erosion rate (68%) of the total, whereas, fruit trees and berry plantations reflected the lowest erosion rates. Low soil organic carbon, sparse vegetation cover and variable climatic conditions significantly enhanced the erosion of the cultivated lands by primarily removing the potential food for organisms. Finally, process-based models offer a valuable resource for decision-makers when improving environmental management schemes and also decrease uncertainty when considering risks.

Effective monitoring of the current status of species distributions and predicting future distributions are very important for conservation practices at the ecosystem and species levels. The human population, land use, and climate are important factors that influence the distributions of species. Even though future simulations have many uncertainties, such studies can provide a means of obtaining species distributions, range shifts, and food production and help mitigation and adaptation planning. Here, we simulate the population, land use/land cover and species distributions in the Eastern Ghats, India. A MaxEnt species distribution model was used to simulate the potential habitats of a group of endemic (28 species found in this region) and rare, endangered, and threatened (RET) (22 species found in this region) plant species on the basis of IPCC AR5 scenarios developed for 2050 and 2070. Simulations of populations in 2050 indicate that they will increase at a rate of 1.12% relative to the base year, 2011. These increases in population create a demand for more land for settlement and food productions. Land use land cover (LULC) simulations show an increase in built-up land from 3665.00 km 2 in 2015 to 3989.56 km 2 by 2050. There is a minor increase of 0.04% in the area under agriculture in 2050 compared with 2015. On the other hand, the habitat simulations show that the combined effects of climate and land use change have a greater influence on the decline of potential distributions of species. Climate change and the prevailing rate of LULC change will reduce the extents of the habitats of endemic and RET species (~ 60% and ~ 40%, respectively). The Eastern Ghats have become extensively fragmented due to human activities and have become a hotspot of endemic and RET species loss. Climate and LULC change will enhance the species loss and ecosystem services.

Identifying efficient adaptation measures in land and water use requires integrated approaches and a spatially and temporally explicit representation of water demand and supply. Stochastic climate information may further improve adaptation assessments to reduce the risk of misinterpretation of climate signals. We aim at developing an integrated modeling framework (IMF) that meets these requirements for assessing impacts of three stochastic climate scenarios (DRY, SIMILAR, WET), and regional irrigation water restrictions on land and water use. Furthermore, impacts on regional net benefits and the economic value of stochastic climate information (VOI) are assessed. The VOI is defined as the difference between regional net benefits with and without efficient adaptation of land and water use to a specific climate scenario. The IMF has been applied to the semi-arid Seewinkel region in Austria. Considering efficient adaptation, regional net benefits amount to 8 M€ and irrigation water use to 8.4 Mm³ in a DRY climate scenario. In a WET climate scenario and a scenario with SIMILAR conditions compared to the past, regional net benefits amount to 38 and 20 M€ and irrigation water use to 41 and 21 Mm³, respectively. High regional net benefits are obtained through an expansion of vineyards, irrigation, and fertilization. On average, the VOI is highest if land and water use is efficiently adapted to DRY but a WET scenario is realized (506 €/ha/a) and lowest with efficient adaptation to WET but the realization of a SIMILAR scenario (58 €/ha/a)., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Pervasive salinity in soil and water is affecting agricultural yield and the health of millions of delta dwellers in Asia. This is also being exacerbated by climate change through increases in sea level and tropical storm surges. One consequence of this has been a widespread introduction of salt water shrimp farming. Here, we show, using field data and modeling, how changes in climate and land use are likely to result in increased salinization of shallow groundwater in SE Asian mega-deltas. We also explore possible adaptation options. We find that possible future increase of episodic inundation events, combined with salt water shrimp farming, will cause rapid salinization of groundwater in the region making it less suitable for drinking water and irrigation. However, modified land use and water management practices can mitigate the impacts on groundwater, as well as the overlying soil, from future salinization. The study therefore provides guidance for adaptation planning to reduce future salinization in Asian deltas.

This study concerned the sediment issue of the Yellow River basin. The responses of hydrological and sedimental processes to future climate change in two upland watersheds with different dominant landscapes were estimated. Four Representative Concentration Pathway (RCP) scenarios with different radiative forcing levels were considered. The outputs of eleven Global Climate Models (GCMs) were used to represent the future climate status of the 2050s and 2070s, and an ensemble means was achieved to avoid uncertainty. The Long Ashton Research Station Weather Generator (LARS-WG) was employed to downscale the outputs of GCMs for future site-scale daily weather data estimations. The Generalized Watershed Loading Functions (GWLF) model was employed to model the streamflow and sediment yields under various scenarios and periods. The results showed that there would be generally hotter and wetter weather conditions in the future. Increased erosion and sediment yields could be found in the study area, with lesser increments in sediment in woodland than in cultivated field. The peak of sediment would appear in the 2050s, and integrated measures for sediment control should be implemented to reduce erosion and block delivery. The multi-model approach proposed in this study had reliable performance and could be applied in other similar areas with modest data conditions., Competing Interests: The authors declare no conflict of interest.

The impacts that climate change and land-use dynamics have on biodiversity are already visible in the distribution and behaviour of a large number of species. By using a Bayesian framework, including land-use, meteorological, topography and other variables as explanatory variables, such as distance to roads and urban centres, we modeled a number of species within each cell of a regular lattice for Catalonia, Spain, in the period of 2004 to 2010. We estimated a slight increase in daily maximum temperature and a more significant increase in minimum temperature (a 5-year increase of 0.159 °C in maximum temperature, and an increase of 0.332 °C in minimum temperature). The estimation shows that the total number of species was greater than expected in the cells where land use was not urban-38.4%, in forests and 55.2% in mixed forests. Finally, we observed that most invasive species are found in areas where the minimum temperature is expected to increase. Our study can help with making important recommendations as to where, when and how future threats could affect specie distribution and the kind of planning processes needed for when protected natural areas will be unable to continue to support all the species they were designed to protect.

Agricultural, industrial and urban development have all contributed to increased salinity in streams and rivers, but the likely effects of future development and climate change are unknown. I developed two empirical models to estimate how these combined effects might affect salinity by the end of this century (measured as electrical conductivity, EC). The first model predicts natural background from static (e.g. geology and soils) and dynamic (i.e. climate and vegetation) environmental factors and explained 78% of the variation in EC. I then compared the estimated background EC with current measurements at 2001 sites chosen probabilistically from all conterminous USA streams. EC was more than 50% greater at 34% of these sites. The second model predicts deviation of EC from background as a function of human land use and environmental factors and explained 60% of the variation in alteration from background. I then predicted the effects of climate and land use change on EC at the end of the century by replacing dynamic variables with published projections of future conditions based on the A2 emissions scenario. By the end of the century, the median EC is predicted to increase from 0.319 mS cm -1 to 0.524 mS cm -1 with over 50% of streams having greater than 50% increases in EC and 35% more than doubling their EC. Most of the change is related to increases in human land use, with climate change accounting for only 12% of the increase. In extreme cases, increased salinity may make water unsuitable for human use, but widespread moderate increases are likely a greater threat to stream ecosystems owing to the elimination of low EC habitats.This article is part of the theme issue 'Salt in freshwaters: causes, ecological consequences and future prospects'., (© 2018 The Author(s).)

The objective of the study was to detect and identify land cover changes in Laikipia County of Kenya that have occurred during the last three decades. The land use types of study area are six, of which three are the main and the other three are the minor. The main three, forest, shrub or bush land and grassland, changed during the period, of which grasslands reduced by 5864 ha (40%), forest by 3071 ha (24%) and shrub and bush land increased by 8912 ha (43%). The other three minor land use types were bare land which had reduced by 238 ha (45%), river bed vegetation increased by 209 ha (72%) and agriculture increased by 52 ha (600%) over the period decades. Differences in spatiotemporal variations of vegetation could be largely attributed to the effects of climate factors, anthropogenic activities and their interactions. Precipitation and temperature have been demonstrated to be the key climate factors for plant growth and vegetation development where rainfall decreased by 200 mm and temperatures increased by 1.5 °C over the period. Also, the opinion of the community on the change of land use and management was attributed to climate change and also adaptation strategies applied by the community over time. For example unlike the common understanding that forest resources utilisation increases with increasing human population, Mukogodo dry forested ecosystem case is different in that the majority of the respondents (78.9%) reported that the forest resource use was more in that period than now and also a similar majority (74.2%) had the same opinion that forest resource utilisation was low compared to last 30 years. In Yaaku community, change impacts were evidenced and thus mitigation measures suggested to address the impacts which included the following: controlled bush management and indigenous grass reseeding programme were advocated to restore original grasslands, and agricultural (crop farming) activities are carried out in designated areas outside the forest conservation areas (ecosystem zoning) all in consultation with government (political class), community and other stakeholders. Groups are organised (environmental management committee) to address conservation, political and vulnerability issues in the pastoral dry forested ecosystem which will sustain pastoralism in the ecosystem.

Growing human and ecological costs due to increasing wildfire are an urgent concern in policy and management, particularly given projections of worsening fire conditions under climate change. Thus, understanding the relationship between climatic variation and fire activity is a critically important scientific question. Different factors limit fire behavior in different places and times, but most fire-climate analyses are conducted across broad spatial extents that mask geographical variation. This could result in overly broad or inappropriate management and policy decisions that neglect to account for regionally specific or other important factors driving fire activity. We developed statistical models relating seasonal temperature and precipitation variables to historical annual fire activity for 37 different regions across the continental United States and asked whether and how fire-climate relationships vary geographically, and why climate is more important in some regions than in others. Climatic variation played a significant role in explaining annual fire activity in some regions, but the relative importance of seasonal temperature or precipitation, in addition to the overall importance of climate, varied substantially depending on geographical context. Human presence was the primary reason that climate explained less fire activity in some regions than in others. That is, where human presence was more prominent, climate was less important. This means that humans may not only influence fire regimes but their presence can actually override, or swamp out, the effect of climate. Thus, geographical context as well as human influence should be considered alongside climate in national wildfire policy and management., Competing Interests: The authors declare no conflict of interest.

Increasing global CO2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO2 world. Crop model inter-comparison studies have identified large uncertainties and biases associated with climate change. The need to quantify uncertainty has drawn the fields of plant molecular physiology, crop breeding and biology, and climate change modeling closer together. Comparing data from different models that have been used to assess the potential climate change impacts on soybean and maize production, future yield losses have been predicted for both major crops. When CO2 fertilization effects are taken into account significant yield gains are predicted for soybean, together with a shift in global production from the Southern to the Northern hemisphere. Maize production is also forecast to shift northwards. However, unless plant breeders are able to produce new hybrids with improved traits, the forecasted yield losses for maize will only be mitigated by agro-management adaptations. In addition, the increasing demands of a growing world population will require larger areas of marginal land to be used for maize and soybean production. We summarize the outputs of crop models, together with mitigation options for decreasing the negative impacts of climate on the global maize and soybean production, providing an overview of projected land-use change as a major determining factor for future global crop production., (© The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.)

We study changes in crop cover under future climate and socio-economic projections. This study is not only organised around the global and regional adaptation or vulnerability to climate change but also includes the influence of projected changes in socio-economic, technological and biophysical drivers, especially regional gross domestic product. The climatic data are obtained from simulations of RCP4.5 and 8.5 by four global circulation models/earth system models from 2000 to 2100. We use Random Forest, an empirical statistical model, to project the future crop cover. Our results show that, at the global scale, increases and decreases in crop cover cancel each other out. Crop cover in the Northern Hemisphere is projected to be impacted more by future climate than the in Southern Hemisphere because of the disparity in the warming rate and precipitation patterns between the two Hemispheres. We found that crop cover in temperate regions is projected to decrease more than in tropical regions. We identified regions of concern and opportunities for climate change adaptation and investment.

We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact of changes in such pollution on riverine ecosystems showing that these will be spatially heterogeneous. Moreover, we consider further knock-on effects upon the recreational benefits derived from water environments, which we assess using revealed preference methods. This analysis permits a multi-layered examination of the economic consequences of climate change, assessing the sequence of impacts from climate change through farm gross margins, land use, water quality and recreation, both at the individual and catchment scale., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Woody encroachment in 'open' biomes like grasslands and savannahs is occurring globally. Both local and global drivers, including elevated CO2, have been implicated in these increases. The relative importance of different processes is unresolved as there are few multi-site, multi-land-use evaluations of woody plant encroachment. We measured 70 years of woody cover changes over a 1020 km(2) area covering four land uses (commercial ranching, conservation with elephants, conservation without elephants and communal rangelands) across a rainfall gradient in South African savannahs. Different directions of woody cover change would be expected for each different land use, unless a global factor is causing the increases. Woody cover change was measured between 1940 and 2010 using the aerial photo record. Detection of woody cover from each aerial photograph was automated using eCognitions' Object-based image analysis (OBIA). Woody cover doubled in all land uses across the rainfall gradient, except in conservation areas with elephants in low-rainfall savannahs. Woody cover in 2010 in low-rainfall savannahs frequently exceeded the maximum woody cover threshold predicted for African savannahs. The results indicate that a global factor, of which elevated CO2 is the likely candidate, may be driving encroachment. Elephants in low-rainfall savannahs prevent encroachment and localized megafaunal extinction is a probable additional cause of encroachment.This article is part of the themed issue 'Tropical grassy biomes: linking ecology, human use and conservation'., (© 2016 The Author(s).)

Butterfly populations are naturally patchy and undergo extinctions and recolonizations. Analyses based on more than 2 decades of data on California's Central Valley butterfly fauna show a net loss in species richness through time. We analyzed 22 years of phenological and faunistic data for butterflies to investigate patterns of species richness over time. We then used 18-22 years of data on changes in regional land use and 37 years of seasonal climate data to develop an explanatory model. The model related the effects of changes in land-use patterns, from working landscapes (farm and ranchland) to urban and suburban landscapes, and of a changing climate on butterfly species richness. Additionally, we investigated local trends in land use and climate. A decline in the area of farmland and ranchland, an increase in minimum temperatures during the summer and maximum temperatures in the fall negatively affected net species richness, whereas increased minimum temperatures in the spring and greater precipitation in the previous summer positively affected species richness. According to the model, there was a threshold between 30% and 40% working-landscape area below which further loss of working-landscape area had a proportionally greater effect on butterfly richness. Some of the isolated effects of a warming climate acted in opposition to affect butterfly richness. Three of the 4 climate variables that most affected richness showed systematic trends (spring and summer mean minimum and fall mean maximum temperatures). Higher spring minimum temperatures were associated with greater species richness, whereas higher summer temperatures in the previous year and lower rainfall were linked to lower richness. Patterns of land use contributed to declines in species richness (although the pattern was not linear), but the net effect of a changing climate on butterfly richness was more difficult to discern., (© 2014 Society for Conservation Biology.)

Globally, annual emissions from managed organic soils accounts for up to 5% of all anthropogenic greenhouse gas (GHG) emissions. Climate-wise management and restoration of degraded organic soils could reduce GHG emissions quickly and at relatively low costs. The European Union (EU) Member States that have large areas of organic soils with high GHG emissions are Sweden, Finland, Germany, Ireland, Poland, Netherlands, and the Baltic countries. To meet the climate targets and objectives of the Paris Agreement the land-use sector is indispensable and mitigation policies targeting organic soils will be needed. The international regulatory framework is broad and quite unspecific. In contrast, the European Union has initiated binding regulation for the land-use sector through the EU Climate Law, the EU LULUCF regulation, and the proposed EU Nature Restoration Law. However, even this regulatory approach is not on track to deliver on its binding ambitions, indicating the need for more effective implementation measures also on organic soils in the EU and its member states. Furthermore, we argue that appropriate policy selection should consider current knowledge regarding the climate impacts of management options of organic soils. Lastly, we need more studies on GHG emissions, and standardized methods for GHG inventories, to resolve uncertainties surrounding the impacts of management to GHG emissions. Successful policy implementation requires more efforts but also improved scientific justification through continuous consideration of climate policy integrity and strengthening of the reliability of GHG inventories. [ABSTRACT FROM AUTHOR]

This study used Theil–Sen median trend analysis and Mann–Kendall test, which are more suitable for long-term series research, to analyze high-precision NPP data and investigate the spatiotemporal characteristics of NPP (net primary productivity) in northwest Liaoning from 2001 to 2021. We further analyzed the impact of the natural environment and land use types on NPP in the region using correlation and a one-way linear regression analysis. The results show that (1) the interannual NPP values exhibited a generally increasing yet fluctuating trend, with the gradient of NPP decrease moving from northwest to southeast. (2) NPP in northwest Liaoning was predominantly influenced by climatic variations, with significant impacts from the combined precipitation–temperature effects seen in 74% of the region, 65% influenced by precipitation alone, and 26% by non-climatic factors. (3) The interaction of soil and vegetation also impacted NPP, which displayed variable rising trends across different soil types in northwest Liaoning. (4) Alterations in land use led to a hierarchical arrangement of the multi-year average NPP values, listed from highest to lowest as forest land, grassland, cultivated land, built-up areas, unused land, and watersheds. [ABSTRACT FROM AUTHOR]

As a fundamental element of global carbon storage, the storage carbon in terrestrial ecosystem is significant for climate change mitigation. Land use/cover change (LUCC) is a main impact element of ecosystems' carbon storage. Evaluating the relation between land use change and carbon storage is vital for lowering global carbon emissions. Taking Hainan Island as an example, this paper employs the InVEST as well as the CA-Markov models to assess and predict how different land use affects carbon storage in various situations from 2000 to 2020 and from 2030 to 2050 on Hainan Island. The influence factors, together with driving mechanisms of carbon storage spatial distribution are quantitatively analyzed as well in this paper. The results demonstrate that, from 2000 to 2020, Hainan Island's net increase in built land was 605.49 km2, representing a growth rate of 77.05%. Over the last 20 years, Hainan Island's carbon storage and density have decreased by 5.90 Tg and 1.75 Mg/hm2, respectively. The sharp rise in built land mainly makes the carbon storage decline. From 2030 to 2050, land use changes on Hainan Island are expected to result in differing degrees of carbon storage loss in various scenarios. In 2050, Hainan Island's carbon storage will decline by 17.36 Tg in the Natural Development Scenario (NDS), 13.61 Tg in the Farmland Protection Scenario (FPS), and 8.06 Tg in the Ecological Protection Scenario (EPS) compared to 2020. The EPS can efficiently maintain carbon sequestration capability, but it cannot effectively prevent cropland area loss. Regarding the carbon storage's spatial distribution, Hainan Island generally exhibits a pattern of high carbon storages in the low and middle carbon storages in the surrounding areas. Areas with high value are primarily located in Hainan Island's central and southern mountainous areas, whereas areas with low value are primarily located in surrounding areas with lower elevations, primarily encompassing built land and cropland. Geographic detection presented the spatial differentiation of carbon storage in Hainan Island is mainly influenced by factors like slope, land use intensity, and DEM, as well as its interaction with other factors is significantly strengthened (p < 0.05). Under the strategic framework of the "carbon peaking and carbon neutrality" goal and the national ecological civilization pilot zone, it is imperative to carefully consider scenarios for ecological protection and farmland protection, adopt ecological regulation models with spatial differentiation, and implement land use policies to improve ecosystem stability, which will contribute to carbon storage loss reduction and ensure food and ecological security. [ABSTRACT FROM AUTHOR]

Young shoots of Aralia elata and young leaves of Eleutherococcus senticosus are two major non-timber forest products in northeastern China. However, human activities and climate change have resulted in serious threats to the habitats of two trees, which greatly limits resource conservation and exploitation of economic forest trees. We used the MaxEnt model to predict the suitable habitats of the two economic trees and analyzed the dominant factors affecting their distribution. The results showed that the suitable habitat areas of A. elata and E. senticosus in the current period were 159950 km2 and 123449 km2, respectively, and the suitable habitats of both economic forest trees were located in the eastern part of the northeast region. Climate factors (Annual precipitation, Precipitation Seasonality) and land use factors are important variables influencing changes in suitable habitat for both trees. With the change of climate and land use in the future, the overall trend of suitable habitat for both economic forest trees shows a northward and then a southward migration. These results may provide assistance in developing strategies for resource conservation and sustainable use of A. elata and E. senticosus, and we suggest that stable and suitable habitats should be selected as areas for in situ conservation and breeding of the two economic forest trees. [ABSTRACT FROM AUTHOR]

Climate change causes a global rise in mean air temperature and an increased frequency of temperature extremes. Recent studies link sharp temperature changes between consecutive days to increased mortality, reduced economic growth, and negative effects on ecosystems. This study assesses the variability of the daily maximum air temperature between two consecutive days (i.e., temperature volatility) across Germany from 1990 to 2022. Using observation-based raster data of maximum daily temperature at 0.1° × 0.1° spatial resolution, we assess temperature volatility regarding: (1) magnitude, (2) seasonality, (3) directionality (day-to-day warming vs. cooling), and (4) trends. Further, we analyse land cover changes during the period and examine their correlation to extreme temperature volatility (Tve). The results show that Tve mostly occurred during spring and summer. The magnitude of Tve increased with distance to the coast north-west to south during all seasons and was highest during spring and summer (>10 °C). Overall, Tve was particularly associated with day-to-day cooling (in spring, summer, autumn), while in winter, >60% of days were associated with warming in north and central Germany. Less than 12% of Germany showed significant trends in median Tve associated with warming over the period. Significant trends included increases (>0.26 °C/year) and decreases (−0.09 °C/year) in extreme day-to-day warming during autumn and winter in northeastern Germany. In spring, the majority (>60%) of southern areas showed significant positive trends (up to 0.16 °C/year) in Tve associated with day-to-day cooling. During winter, summer, and autumn, trends in extreme day-to-day cooling were insignificant in over 80% of Germany. Within all land cover types, Tve predominantly varied between 6 °C and 9 °C. Changes in land cover, especially transforming coniferous forests for agricultural purposes, were accompanied by increasing Tve up to 0.49 °C. Understanding rapid temperature changes is crucial for climate change mitigation strategies and limiting the impacts on human health and on the environment. [ABSTRACT FROM AUTHOR]

Deploying onshore wind energy as a cornerstone of future global energy systems challenges societies and decision-makers worldwide. Expanding wind energy should contribute to a more sustainable electricity generation without harnessing humans and their environment. Opponents often highlight the negative environmental impacts of wind energy to impede its expansion. This study reviews 152 studies to synthesize, summarize, and discuss critically the current knowledge, research gaps, and mitigation strategies on the environmental impacts of onshore wind energy. The investigated effects comprise impacts on the abiotic and biotic environment, with birds and bats in particular, noise and visual impacts. Effects are discussed in the context of social acceptance, other energy technologies, and wind energy expansion in forests. This review illustrates that many effects are highly case-specific and must be more generalizable. Studies are biased regarding the research focus and areas, needing more standardized research methods and long-term measurements. Most studies focus on the direct mortality of birds and bats at wind farms and are concentrated in Europe and North America. Knowledge gaps persist for many impact categories, and the efficacy of mitigation strategies has yet to be proven. More targeted, unbiased research is required that allows for an objective evaluation of the environmental impacts of wind energy and strategies to mitigate them. Impacts, such as those on biodiversity, need to be addressed in the context of other anthropogenic influences and the benefits of wind energy. This forms the basis for a socially acceptable, efficient, and sustainable expansion of wind energy. [ABSTRACT FROM AUTHOR]

This study assessed the impacts of the land use/cover (LULC) and climate changes on the runoff and sediment flows in the Megech watershed. The Geospatial Water Erosion Prediction Project (GeoWEPP) was used to assess LULC and climate changes' impact on runoff, soil loss, and sediment yield. The QGIS 2.16.3 plugin module for land use change evaluation (MOLUSCE) tool with the cellular automata artificial neural network (CA-ANN) was used for LULC prediction based on historical data and exploratory maps. Two commonly used representative concentration pathways (RCPs)—4.5 and 8.5—were used for climate projection in the 2030s, 2050s, and 2070s. The LULC prediction analysis showed an expansion of cropland and settlement areas, with the reduction in the forest and rangelands. The climate projections indicated an increase in maximum temperatures and altered precipitation patterns, particularly with increased wet months and reduced dry periods. The average annual soil loss and sediment yield rates were estimated to increase under both the RCP4.5 and RCP8.5 climate scenarios, with a more noticeable increase under RCP8.5. By integrating DEM, soil, land use, and climate data, we evaluated runoff, soil loss, and sediment yield changes on only land use/cover, only climate, and the combined impacts in the watershed. The results revealed that, under all combined scenarios, the sediment yield in the Megech Reservoir was projected to substantially increase by 23.28–41.01%, showing a potential loss of reservoir capacity. This study recommends strong climate adaptation and mitigation measures to alleviate the impact on land and water resources. It is possible to lessen the combined impacts of climate and LULC change through implementing best-management practices and adaptation strategies for the identified scenarios. [ABSTRACT FROM AUTHOR]

The first Earth Day on April 22, 1970, celebrated the grassroots environmental movement that began in the '60s and early '70s and ushered in the creation of a new legal framework for controlling pollution and addressing environmental concerns in the United States. However, more than fifty years later, some experts fear that the environmental progress achieved during the '70s and '80s has begun to stall as the United States and other nations experience broad economic hardship and must shift their focus to more immediate concerns. Therefore, even as the damaging effects of climate change threaten communities across the globe, the next major environmental movement is unlikely to happen at the federal or global level. Instead, state and local citizens and governments must address the increasing impacts of climate change by exploring short- and long-term approaches to land use planning and environmental regulation to prepare communities to be resilient to coming changes. This Article attempts to consolidate the various land use tools, such as planning, zoning, sustainable and green development, eminent domain, inverse condemnation, nuisance law, renewable energy incentives, and smart cities, which can help communities and individuals deal with past, current, and future impacts from climate change. These more localized tools present greater opportunities to prepare for climate change and continuing disasters, address systemic inequalities and disruptive histories, and build or rebuild resilient communities through mitigation and adaptation. This Article suggests that the principle of social ecological resilience is an effective concept to deal with climate change when our ecosystems are prone to disruption, promoting a land use system that manages risk through mitigation and adaptation. By incorporating principles of social-ecological resilience, sustainability, and adaptation into the circle of disaster risk management and other regulatory responses, communities can better prepare for the future while also establishing equitable laws and policies. The Article continues by assessing local land use concepts that are available to mitigate and adapt to climate change at the community level. While local governments have a vital role in establishing mitigation and adaptation strategies through a variety of land use regulations and policymaking, the participation of all citizens who live and work in the community----particularly the vulnerable ones----is also essential for creating planning and governance strategies that further a community's resilience goals. This inclusive, community-wide approach provides a framework for assessing emergency response strategies at the local level, analyzing various compensation models to spread risks following a disaster, and facilitating cohesive and effective rebuilding efforts. Bearing all these tools in mind, this Article concludes that adaptive governance informed by resilience thinking at the local level will help build (and rebuild) communities capable of withstanding whatever the future holds. [ABSTRACT FROM AUTHOR]

Amidst the challenges posed by global climate change and accelerated urbanization, the structure and distribution of land use are shifting dramatically, exacerbating ecological and land-use conflicts, particularly in China. Effective land resource management requires accurate forecasts of land use and cover change (LUCC). However, the future trajectory of LUCC, influenced by climate change and urbanization, remains uncertain. This study developed an integrated multi-scenario framework by combining system dynamics and patch-generating land use simulation models to predict future LUCC in high-density urban regions under various Shared Socioeconomic Pathway (SSP)–Representative Concentration Pathway (RCP) scenarios. The results showed the following: (1) From 2020 to 2050, cultivated land, unused land, and water are projected to decrease, while construction land is expected to increase. (2) Future land use patterns exhibit significant spatial heterogeneity across three scenarios. Construction land will expand in all districts of Hangzhou, particularly in the main urban areas. Under the SSP585 scenario, the expansion of construction land is most significant, while it is the least under the SSP126 scenario. (3) Distinct factors drive the expansion of different land use types. The digital elevation model is the predominant factor for the expansion of forest and grassland, contributing 19.25% and 30.76%, respectively. Night light contributes the most to cultivated land and construction land, at 13.94% and 20.35%, respectively. (4) The average land use intensity (LUI) in central urban districts markedly surpasses that in the surrounding suburban areas, with Xiacheng having the highest LUI and Chun'an the lowest. Under the SSP126 scenario, the area with increased LUI is significantly smaller than under the SSP245 and SSP585 scenarios. These findings offer valuable guidance for sustainable planning and built environment management in Hangzhou and similarly situated urban centers worldwide. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is one of the most important variables in the physical processes of surface energy and water balance. The temporal behavior of LST was analyzed between the latitudes 32°00′ S and 34°24′ S (Valparaíso and Metropolitana regions of Chile) for three summer months (December, January, and February) in the 2000–2017 period, using the Terra MODIS image information and applying the Mann–Kendall test. The results show an increase in LST in the study area, particularly in the Andes mountain range in January (5240 km2), which mainly comprises areas devoid of vegetation and eternal snow and glaciers, and are zones that act as water reserves for the capital city of Santiago. Similarly, vegetated areas such as forests, grasslands, and shrublands also show increasing trends in LST but over smaller surfaces. Because this study is regional, it is recommended to improve the spatial and temporal resolutions of the images to obtain conclusions on more local scales. [ABSTRACT FROM AUTHOR]

Climate change has become a global issue and is predicted to impact less-developed regions, such as sub-Saharan Africa, severely. Innovative, sustainable renewable energy systems are essential to mitigate climate change's effects and unlock the region's potential, especially with the increasing energy demands and population growth. The region relies heavily on fossil fuels, which calls for urgent action towards energy security and expansion. Hybrid floating solar photovoltaic-hydropower (FPV-HEP) technology has emerged as a cost-effective and transformative solution to accelerate the low-carbon energy transition in sub-Saharan Africa. The technology combines solar panels with existing hydropower infrastructure, ensuring energy security while reducing carbon emissions. This technology offers several benefits over conventional ground-mounted solar systems, including efficient land utilization, energy generation, and water conservation. However, its adoption remains challenging due to technical complexities and evolving regulatory frameworks. Despite these challenges, Nigerian energy professionals have preferred renewable alternatives, mainly distributed solar PV and FPV-HEP plants. This collective embrace of FPV and renewables reflects a growing understanding of their critical role in mitigating climate change through sustainable energy practices. This research aims to contribute to the existing body of knowledge and assist policymakers in making informed decisions on adopting this technology. It also stimulates further research on this topic, offering a new potential solution to the ever-increasing demand for green energy in the region to meet their sustainable development needs. [ABSTRACT FROM AUTHOR]

Since 1990, global forest area has been reducing; tropical forests have suffered from different anthropogenic and natural factors that account for forest loss. Tropical deforestation is the second driver of anthropogenic emissions; increasing demand and investments in tropical forests drive these emissions. These forests attract significant foreign direct investments, but the effects of these investments on carbon emissions from land use, land-use change, and forestry are not well enshrined in the literature for the countries under study. This paper seeks to analyse the impact of foreign direct investments on carbon emissions from land use, land-use change, and forestry amongst 30 tropical forest countries from 1996 to 2019. The sampled countries were disaggregated by tropical blocs: Amazon, Congo basin, Australasia, and Southeast Asia, and by income levels; low-income, lower-middle, upper-middle, and high-income. The findings reveal a U-shape structure of the impact of FDI on carbon emissions from LULUCF within Congo basin and Amazon countries; at higher levels of FDI, emissions from LULUCF will increase while Australasia and Southeast Asian countries show an inverted U-shape impact, thus at higher levels of FDI, there will be a negative and significant impact on carbon emissions from LULUCF. The income levels reveal an inverted U-shape for low-income and high-income countries and a U-shape for upper-middle-income countries; the impact for lower-middle-income countries is not significant. Overall, for the whole sample, the impact depicts a U-shape. This paper proposes high-level development of environmental conditions for FDI for different sectors that align with country and regional green growth plans. Enhancing national and regional governance systems to enforce decisions and fight corruption effectively can significantly promote green FDI for green growth. [ABSTRACT FROM AUTHOR]

Desertification is a specific land-degrading process, reducing soil productivity and potentially threatening global food security. Therefore, spatially and temporally identifying and mapping desertification-sensitive areas is essential for better management. The current study aimed to (1) assess spatial areas sensitive to desertification and (2) examine the changing tendency of the desertification-sensitive areas over the past 25 years in the provincial Ninh Thuan. The desertification sensitivity index (DSI) was computed based on the Medalus model using 10 quantitative parameters, grouped into the soil, climate, and vegetation quality indexes, computed for the years 1996, 2005, 2010, and 2016. GIS was used to map desertification-sensitive areas associated with five DSI classes. Results showed that classes II and III had the highest area percentage, followed by classes IV and V, and class I. The classes most sensitive to desertification (classes IV and V) covered around 13 to 17%, and classes II and III were 25 to 32% of the total study area, respectively. The coastal areas located in the southeastern parts were more sensitive to desertification than the other parts. Over the four examined periods, the areas of classes IV and V increased while those of classes II and I decreased. These indicated that the study province tended to increase in its desertification sensitivity with a severe increase in the coastal areas over the past 25 years. The key factors involved in these changes could be related the human activities and climate variation, which could be more serious in southeastern areas than in the other areas. [ABSTRACT FROM AUTHOR]

In the global carbon cycle, atmospheric carbon emissions, both 'natural' and anthropogenic, are balanced by carbon uptake (i.e., sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago, the ratio between emitted and sequestered carbon has varied considerably, with atmospheric CO2 levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil, and gas. Relatively low atmospheric CO2 levels were the norm for the past 10 million years, and during the past million years, they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO2 levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with the domestication of crops and livestock, leading to urbanisation and the development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO2 emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance, it is important to understand the roles of potential biological carbon sequestration systems and to devise strategies to facilitate net CO2 uptake; for example, via changes in the patterns of land use, such as afforestation, preventing deforestation, and facilitating agriculture–agroforestry transitions. [ABSTRACT FROM AUTHOR]

Investigating the influence of human activities and climate change on streamflow and sediment load is of great significance for understanding the hydrological cycle, addressing climate change, and ensuring sustainable water resource management. Based on observed data of precipitation, streamflow, and sediment load from 1990 to 2021 in the Xiliugou Basin, trend and abrupt change analyses of streamflow and sediment load were conducted using the coefficient of variation and Bayesian change point detection method. The effects of climate change and human activities on streamflow and sediment load were further examined through the double mass curve method, with a focus on the impact of land use changes on streamflow and sediment load dynamics. The results indicated that: (1) During the study period, there was a consistent decreasing trend in streamflow, sediment load, and precipitation, with respective rates of −77.76 × 104 m3/year, −55.97 × 104 Mt/year, and −0.84 mm/year. The distribution of annual streamflow and sediment load in the basin was uneven, with 61.05% of precipitation occurring during the wet season and the peak sediment discharge month being July, accounting for 58.90% of the total annual sediment load. (2) The variations in streamflow and sediment load in the Xiliugou Basin exhibited distinct stage characteristics, with abrupt changes occurring around 1997. Both streamflow and sediment load showed significant fluctuations from the reference period to the changing period, decreasing by 45.54% and 82.85%, respectively. (3) A positive correlation between precipitation and streamflow was observed in the Xiliugou Basin, with correlation coefficients (R) of 0.62 and 0.49, indicating a stimulating effect of precipitation on streamflow and sediment load. Human activities significantly reduced sediment load in the Xiliugou Basin from 1998 to 2021, contributing to a reduction of 115.08%. (4) An increase in cropland, water, and barren areas would lead to higher streamflow and sediment load, while an increase in grassland, forest, and impervious areas would decrease both streamflow and sediment load. [ABSTRACT FROM AUTHOR]

The robust carbon storage (CS) capacity of terrestrial ecosystems is crucial in mitigating climate change and holds indispensable significance for global sustainable development. The diverse topography of Central Asia (CA), comprising oases, grasslands, forests, deserts, and glaciers, has fostered industries like animal husbandry, irrigation agriculture, and mining. However, the fragile arid ecosystems of CA render it highly sensitive to climate change and human activities, with their impact on the sustainable development of multifunctional landscapes in this region remaining ambiguous in the future. This study linked land use changes with multiple socio-economic and ecological indicators to predict the dynamics of land use and changes in CS in CA. The findings reveal a significant spatial heterogeneity in CS, with considerable variations among five countries driven by differences in landscape composition. Kyrgyzstan and Kazakhstan, characterized by grasslands, demonstrate higher CS per unit area, whereas Turkmenistan, dominated by barren land, exhibits the lowest CS per unit area. Strategies involving innovative development and improved biodiversity conservation have proven effective in augmenting CS. Meanwhile, high economic and population growth stimulates the expansion of cropland and urban land, reducing the CS capacity of ecosystems. This study contributes to a more precise assessment of CS dynamics in CA. Furthermore, by elucidating the interrelationships between future socio-economic development and environmental conservation in CA, it offers solutions for enhancing the conservation of multifunctional landscapes in CA. [ABSTRACT FROM AUTHOR]

During the Holocene, the upper and middle reaches of the Yellow River valley in China were pivotal areas for agricultural development. Quantitatively reconstructing the spatiotemporal changes in prehistoric human land use is essential for understanding, from a long-term perspective, the interactions among evolutions of climate, agriculture, and human activities. Based on 327 archaeological sites and the PLUM (prehistoric land use model), we quantitatively reconstructed human land use changes from 6 to 3 ka BP (thousands of years before the present) in the Tao River valley, the second-largest tributary in the upper reach of the Yellow River valley. The results indicated that regional land use areas increased from 571 km2 to 1468 km2, with spatial expansion from the lower reach to the upper–middle reach of the Tao River valley. A comparison of the five areas distributed across the upper and middle reaches of the Yellow River valley revealed two different trends of increasing land use from 8 to 3 ka BP within these areas. The first group (the Wei River and Yiluo River valleys) exhibited rapid and substantial growth before 5 ka BP, while the second group (the Huangshui River and Tao River valleys, and the Yunlin district) showed a much slower and less significant increase before 5 ka BP, but a more obvious increase thereafter. The asynchronous increases in these areas indicate an expansion of land use from the southeastern part of the upper and middle reaches of the Yellow River Valley to across the entire region between 8 and 3 ka BP, which was primarily driven by agricultural development and cultural communication. [ABSTRACT FROM AUTHOR]

Land-use change may significantly influence streamflow. The semi-empirical model PhosFate was used to analyze the impact of land use and climate change on streamflow by choosing the Guishui watershed as a pilot site and then expanding, applying it to all of North China. The Guishui watershed (North Beijing, China) has experienced a dramatic decline in its streamflow in recent decades. Parallel to this, significant land-use change has happened in this area; afforestation programs have increased forest cover from 41% (1980) to 59% (2013) and a similar increase in forest cover can also be observed in North China. Managing flow decline requires separating climatic and direct human-influenced effects. The results showed the following: (1) Afforestation is a major factor that decreased total flow in the Guishui watershed from 1996 to 2014; total flow increased by around 24% more than the actual dataset in the constant scenario (no afforestation) and decreased by 5% more than the actual dataset in the forest scenario (all agriculture land use transferred to forests). (2) When forest coverage increases, the Qinghai–Tibet Plateau and the Loess Plateau are the most sensitive areas regarding total flow in North China; the total flow change rate increased by up to 25% in these two areas when land use shifted from sparse vegetation to mixed forests. After analyzing the contributions of these two factors, we formulated recommendations on future afforestation practices for North China. In the central–north and northwest districts, the annual precipitation is under 520 mm and 790 mm, respectively, and the practice of afforestation should be more carefully planned to prevent severe damage to streams. This research also proved that the PhosFate model can be used in North China, which would be a practical tool for watershed management. [ABSTRACT FROM AUTHOR]

The agro-pastoral transitional zone in northern China is an important agricultural and pastoral production base. This study focuses on the eastern section of the agro-pastoral transitional zone in northern China. Combined with spatio-temporal analysis, stepwise regression, and gray relation analysis, we analyzed the average annual growth rate, spatio-temporal changes, and influencing factors of agricultural and pastoral production in the study area during 2000–2020. The results show that, in the past 20 years, the agricultural and pastoral production of the 50 municipal districts and counties has significantly changed, among which the agricultural production of 38 municipal districts and counties has shown an extremely significant increase. Generally, the growth rate of agricultural production is higher than that of pastoral production. Agricultural and pastoral production in the study area is influenced by socio-economic and land use/cover factors, with an average correlation degree of 0.79 and 0.88, respectively. Climate change affects agricultural production in agricultural counties, with a correlation degree of 0.85. The results of this research provide valuable insights into understanding the long-term temporal and spatial changes in agricultural and pastoral production and help to develop sound agriculture and pastoral management practices in the eastern section of the agro-pastoral transitional zone in Northern China. [ABSTRACT FROM AUTHOR]

Several factors, including natural and human-induced, can affect river discharge. This study aims to examine the influence of land use changes and climate change on the monthly average streamflow time series in the Talar River basin, in northern Iran. To investigate the impact of human factors, namely land use change and point source operations, on monthly average streamflow, the DBEST method was used to detect any breakpoint in the streamflow time series caused by gradual changes in land use and climate. The SWAT model was used to simulate the basin at Kiakola and Shirghah stations, between 2001 and 2020. The land use maps were created for the years 2001 and 2019. Calibration and validation at the Kiakola station showed that the Nash-Sutcliffe model (NSE) had an efficiency of 0.8 and 0.76, respectively, while at the Shirghah station, the same values were 0.84 and 0.75. Findings revealed that human activities, specifically the combined impact of land use change and point source operations, had a 60% influence on the monthly average streamflow of the Talar River. They further showed that the combination of land use and harvesting played the most significant role in the basin's outflow on a monthly scale. HIGHLIGHTS DBEST was the application executed in the R environment using the 'DBEST' package.; The SWAT model with SUFI-2 calibration method was used to simulate the streamflow.; Findings revealed that human activities, specifically the combined impact of land use change and point source operations, had a 60% influence on the monthly average streamflow.; The findings of this research can provide support for water resource management decisions in Talar river basin.;

The prevalence of flooding in Nigeria in the past few years (with its devastating consequences) has become a source ofconcern for policymakers and researchers alike. Scholars have attributed the high frequency of flooding, particularly in thesouthern region of Nigeria, to several factors; climatic variation and land use/land cover changes are themes that fall underthe domain of natural and anthropogenic causes of flooding, respectively. This study examined climatic variations andchanging land use/land cover in southern Nigeria with the view of determining their synergistic effects on flooding. Weadopted a mixed approach for data collection with the use of Geographic Information System (GIS), retrieval of primary datafrom meteorological stations in the region, and field surveys. Findings show a significant decrease in rural land uses likearable lands, wetlands, and undisturbed forests; while there was a corresponding increase in urban/peri-urban land uses likesettlements and tree-crop plantations over the period from 1999 to 2019. The land use/land cover changes have manifestedin the destabilization of the microclimate, distortion of the carbon circle, loss of biodiversity, reduction of ecosystem servicesof the natural areas, and flooding. The decadal rainfall trends over the past three decades show consistent extremities withmean rainfall duration decreasing while the mean intensity increases; aggravating soil erosion, urban runoff challenges, andflooding. Climatic variations (mainly extreme rainfall patterns) synergize with inefficient land use management to exacerbateflooding in southern Nigeria. While policymakers in this region may not have the standalone capacity to significantly controlclimate change and the consequential variations in the local microclimate, they can re-engineer land use policies to eliminateor substantially degrade anthropogenic factors that exacerbate flooding.

Land use/cover change has an important impact on global climate change and carbon cycle, and it has become another major source of carbon emission after energy consumption. Therefore, this study focuses on the main line of "land use carbon emissions-spatial and temporal patterns-influencing factors," and selects 13 cities in Jiangsu Province as the research object. Based on the data of land use and energy consumption, combined with the method of land use carbon emissions and ArcGIS technology, this study conducted a quantitative analysis of the spatio-temporal distribution of carbon emissions in Jiangsu Province. The factors affecting the spatial distribution of carbon emissions from land use in Jiangsu Province were discussed by using Geographic detector. The results show that: 1) Carbon emissions in Jiangsu Province showed an overall growth trend, from 16215.44 × 104tC in 2010-23597.68 × 104tC in 2020, with an average annual growth rate of 4.55%, of which the construction land and watersheds had a greater impact on carbon sources and sinks, respectively. 2) During the period, there were significant differences in carbon emission levels among different cities in Jiangsu Province, and the land use carbon emission in Jiangsu Province showed a stable spatial pattern of "northwest--southeast." The southern part of Jiangsu is always the hot area of carbon emission, while the cold spot area is mainly distributed in the northern and central parts of Jiangsu. 3) The interaction of factors such as economic development, industrial structure, energy intensity, land use and human activities is an important reason for the spatio-temporal differences of land use carbon emissions in Jiangsu Province. Among them, the level of urbanization, population size and economic aggregate have significant effects on carbon emissions. [ABSTRACT FROM AUTHOR]

Remote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (Tair), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, this study analyzes time-series data from Landsat and MODIS satellites, alongside Tair climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in Tair and LST during the summer months from 1984 to 2023, with a notable positive correlation between Tair and LST across both datasets. MODIS data exhibit a stronger correlation (R2 = 0.879) compared to Landsat (R2 = 0.663). The application of a supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations: a 70.3% increase in urban land and a decrement in vegetative cover comprising a 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09 °C and 2.16 °C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30 °C and 2.24 °C, with the bare land class showing the highest fluctuation 2.46 °C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p > 0.05 for both monthly and annual datasets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as the warmest classes at 39.51 °C and 38.20 °C, respectively, and classifies water at 35.96 °C, dense vegetation at 35.52 °C, and sparse vegetation 37.71 °C as the coldest, which is a trend that is consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects. [ABSTRACT FROM AUTHOR]