Cropland Expansion Research Articles

Adoption of improved crop varieties limited biodiversity losses, terrestrial carbon emissions, and cropland expansion in the tropics.

Research investments in crop improvements, including by national and international agricultural research centers, have made significant contributions to raising yields of staple food crops in developing countries. Although mostly intended to improve food security and rural incomes, innovations in crop production also have major implications for the environment. Building on the latest productivity estimates from historical crop improvements in developing countries and using a gridded (0.25 degrees) equilibrium model of global agriculture, we assess the impacts of improved crop varieties on cropland use, threatened biodiversity, and terrestrial carbon stocks over 1961-2015. We replicate a historical baseline and produce a counterfactual scenario which shows the impact of omitting productivity improvements from these technologies. The results show that higher crop productivity generally lowered commodity prices, which reduced incentives to expand cropland except in those areas where productivity gains outweighed price declines. The net global effect of technology adoption was to limit conversion of natural habitat to agricultural use, although it did cause cropland to expand in some areas. We estimate that adoption of improved crop varieties in developing countries saved on net 16.03 [95% CI, 12.33 to 20.89] million hectares worldwide. With more natural habitat preserved, around 1,043 [95% CI, 616 to 1,503] threatened animal and plant species extinctions were avoided over this period. In addition, net land use savings from the improved crop varieties resulted in avoided terrestrial greenhouse gas (GHG) emissions of around 5.35 [95% CI, 3.75 to 7.22] billion metric tons CO2 equivalent retained in terrestrial carbon stocks.

Opinion: Understanding the impacts of agriculture and food systems on atmospheric chemistry is instrumental to achieving multiple Sustainable Development Goals

Abstract. Agriculture and food systems play important roles in shaping atmospheric chemistry and air quality, most dominantly via the release of reactive nitrogen (Nr) compounds but also via agricultural burning, energy use, and cropland and pastureland expansion. In this opinion article, we first succinctly review our current understanding of agricultural and food-system emissions of Nr and other atmospherically relevant compounds; their fates and impacts on air quality, human health, and terrestrial ecosystems; and how such emissions can be potentially mitigated through better cropland management, livestock management, and whole-food-system transformation. In doing so, we highlight important knowledge gaps that warrant more extensive research and argue that we scientists need to provide a more detailed, process-based understanding of the impacts of agriculture and food systems on atmospheric chemistry, including both chemical composition and processes, especially as the importance of emissions from other fossil-fuel-intensive sectors is fading in the face of regulatory measures worldwide. Such knowledge is necessary to guide food-system transformation in technologically feasible, economically viable, socially inclusive, and environmentally responsible ways and is essential to help society achieve multiple Sustainable Development Goals (SDGs), especially to ensure food security for people, protect human and ecosystem health, improve farmers' livelihoods, and ultimately help communities achieve socioeconomic and environmental sustainability.

Cropland expansion links climate extremes and diets in Nigeria.

Climate change threatens smallholder agriculture and food security in the Global South. While cropland expansion is often used to counter adverse climate effects despite ecological trade-offs, the benefits for diets and nutrition remain unclear. This study quantitatively examines relationships between climate anomalies, forest loss from cropland expansion, and dietary outcomes in Nigeria, Africa's most populous country. Combining high-resolution data on forest cover and climate variables within random forest and panel regression models, we find that 25 to 31% of annual forest loss is linked to climate variability. Using georeferenced household survey data, we then find that changes in forest cover have a significant positive association with changes in child diet diversity-a key proxy of nutritional adequacy-while cropland expansion does not, suggesting that such forest conversions may be an ineffective climate adaptation strategy for improving nutrition. Our findings highlight the potential of nutrition-sensitive climate adaptation to enhance yields, promote nutritious cropping choices, and protect remaining forests.

US Corn Belt enhances regional precipitation recycling

Precipitation recycling, where evapotranspiration (ET) from the land surface contributes to precipitation within the same region, is a critical component of the water cycle. This process is especially important for the US Corn Belt, where extensive cropland expansions and irrigation activities have significantly transformed the landscape and affected the regional climate. Previous studies investigating precipitation recycling typically relied on analytical models with simplifying assumptions, overlooking the complex interactions between groundwater hydrology and agricultural management. In this study, we use high-resolution climate models coupled with an explicit water vapor tracer algorithm to quantify the impacts of shallow groundwater, dynamic crop growth, and irrigation on regional precipitation recycling in the US Corn Belt. We find that these coupled groundwater-crop-irrigation processes reduce surface temperatures and increase the growing season precipitation. The increase in precipitation is attributed to a significant enhancement of the precipitation recycling ratio from 14 to 18%. This enhanced precipitation recycling is stronger in a dry year than normal and wet years, depending on both large-scale moisture transport and local ET. Our study underscores the critical role of groundwater hydrology and agricultural management in altering the regional water cycle, with important implications for regional climate predictions and food and water security.

Large-scale Commercial Agricultural Investment: Implications for Land Use/Land Cover Dynamics in Guba District, Northwest Ethiopia

Large-Scale Commercial Agricultural Investment (LSCAI) is expected to improve the living conditions of host communities while ensuring the productive use of natural resources. However, its impact on the local environment and land use/land cover (LULC) dynamics was not well investigated in Guba District, northwest Ethiopia. This study aimed to examine the implications of LSCAI projects on LULC change dynamics. To achieve this, the study employed a concurrent triangulation design, combining of qualitative and quantitative data. Data for the study were collected from primary and secondary sources, including satellite images with ground verification. The LULC map was prepared and image classification conducted by employing Arc GIS10.5 and ERDAS 2014. Structured interviews were conducted with 351 households, and unstructured in-depth interviews were conducted with key informants. The study revealed a significant increase in LULC over time. Dense forest cover decreased by 0.61% and open woodlands decreased by 1.25% per year. In contrast, cropland expanded by 1.79% per year between 1990 and 2019. Particularly, between 2010 and 2019, the rate of cropland expansion reached 3.25% per year due to the influx of LSCAI projects. This indicates that the expansion of LSCAI projects has nearly doubled the rate of LULC change in the study area. During the key informant interviews, it was confirmed that the period from 2010 to 2019 witnessed substantial expansion of LSCAI projects in the study area. Local communities also expressed concerns about the potential threats posed by LSCAI, including deforestation, land dispossession, malpractices, violent conflicts, and increased charcoal production. The main drivers of severe LULC are anthropogenic factors that promote the expansion of LSCAI. It is recommended that in the process of LSCAI, land identification and transfer to developers should be done in consultation with local communities, and the policy direction on natural resource utilization should be revisited to ensure the most sustainable use of land resources.

Spatial-Temporal Evolution and Cooling Effect of Irrigated Cropland in Inner Mongolia Region

Monitoring the dynamic distribution of irrigated cropland and assessing its cooling effects are essential for advancing sustainable agriculture amid climate change. This study presents an integrated framework for irrigated cropland monitoring and cooling effect assessment. Leveraging dense time series vegetation indices with Google Earth Engine (GEE), we evaluated multiple machine learning algorithms within to identify the most robust approach (random forest algorithm) for mapping irrigated cropland in Inner Mongolia from 2010 to 2020. Furthermore, we developed an effective method to quantify the diurnal, seasonal, and interannual cooling effects of irrigation. Our generated irrigated cropland maps demonstrate high accuracy, with overall accuracy ranging from 0.85 to 0.89. This framework effectively captures regional cropland expansion patterns, revealing a substantial increase in irrigated cropland across Inner Mongolia by 27,466.09 km2 (about +64%) between 2010 and 2020, with particularly pronounced growth occurring after 2014. Analysis reveals that irrigated cropland lowered average daily land surface temperature (LST) by 0.25 °C compared to rain-fed cropland, with the strongest cooling effect observed between July and August by approximately 0.64 °C, closely associated with increased evapotranspiration. Our work highlights the potential of satellite-based irrigation monitoring and climate impact analysis, offering a valuable tool for supporting climate-resilient agriculture practices.

Agricultural Intensification and Cropland Expansion in the Semi-Arid Foothills of Kirthar Range: Implications for Water Management and Food Security

Agricultural Intensification and Cropland Expansion in the Semi-Arid Foothills of Kirthar Range: Implications for Water Management and Food Security

Analysing the Spatial and Temporal Characteristics of Ecological Land Encroachment by Cropland Expansion and Its Drivers in Cambodia

The rapid expansion of cropland in Cambodia, the world’s seventh-largest rice exporter, has created an imbalance in land use structure. However, there is a lack of quantitative investigation of the loss of ecological land as a result of the expansion of cropland and its drivers. In this research, spatial autocorrelation, landscape pattern index and transfer matrix methods were used based on land use data from 2000 to 2023. Then, the eXtreme Gradient Boosting-SHapley Additive exPlanations (XGBoost-SHAP) and Geographic Detector were used to explore the drivers of cropland expansion. The findings indicate that the expanse of agricultural land in Cambodia has significantly increased by 13.47%. The proportion of cropland to the land area (37.87%) is close to that of forest (40.19%). Cultivated land is dominated by rice fields, supplemented by drylands. Spatial clustering is obvious in both drylands and rice fields. Drylands are mainly concentrated in the eastern and western mountainous areas and the northern border, while rice fields are concentrated in the central plains. Cultivated land encroached on a total of 30,579.27km2 of ecological land, of which 62.88% was dry land and 37.12% was rice fields. Forests and shrubs are the main source of expansion of cropland. In addition, soil type (0.18), elevation (0.17) and GDP (0.17), population (0.52) and their interactions strongly drove the expansion of dryland and rice fields. Cambodia should conduct scientific research to assess the demand for cropland by population growth and economic progress. It should realize the orderly growth of cultivated land, reduce the damage to ecological land, and promote the coordinated development of society, environment and economy.

Synergistic Matching and Influencing Factors of Grain Production and Cropland Net Primary Productivity in the Black Soil Region of Northeast China

Exploring the spatiotemporal dynamics, spatial mismatch, and complex influencing mechanism of grain production and cropland productivity in the black soil region of northeast China (BSRNC) is essential for the synergistic protection and utilization of black soil cropland and sustainable grain production. The BSRNC has realized cropland expansion and grain production increases in the past decades. This implied a substantial investment has been made in the region’s agriculture. However, at present, knowledge on the spatial mismatch and influencing factors of grain production and cropland productivity is still unclear. This study analyzed the spatial–temporal mismatch characteristics of grain production and cropland net primary productivity (CNPP) using the gravity center model, spatial autocorrelation analysis, and spatial mismatch index (SMI), and identified the spatial heterogeneity and prediction–response relationships of influencing factors based on a geographically and temporally weighted regression (GTWR) model and boosted regression tree (BRT) machine learning algorithm. The findings indicated that grain production and CNPP have been increasing, but the overall spatial pattern of cold hotspots has not changed obviously in the BSRNC from 2000 to 2020. The SMI has shown a decreasing trend, indicating that the synergistic development of grain production and CNPP has been obvious, which plays an important role in sustainable food supply capacity. Agricultural production and the natural environment have always been critical factors influencing the spatial mismatch. Specifically, the marginal impact of fertilizer application has undergone a shift. This study may provide new clues for the formulation of regional strategies for sustainable food supply and black soil cropland system protection.

Land cover change and its driving factors in Siberia from 1992 to 2020.

Siberia occupies vast areas underlain by permafrost, and understanding its land cover changes is important for ecological environmental protection in a warming climate. Based on the land cover and climate datasets, we analyzed the land cover changes and their drivers in Siberia from 1992 to 2020. The results show that ① From 1992 to 2020, the areas of evergreen needleleaf trees and deciduous needleleaf trees in Siberia decreased by 9% and 2.5%, and the areas of grassland, shrub, cropland, and construction land increased by 1.5%, 14.2%, 2.8%, and 39.2%, respectively. Cropland expansion had the fastest rate of 1.85% in the continuous permafrost zone, and construction land expansion had the fastest rate of 3.07% in the non-permafrost zone. ② The center of gravity of agricultural land continues to migrate to the northeast, and the center of gravity of construction land continues to migrate to the southwest. ③ The primary drivers for the land cover changes were temperature and precipitation, and active layer thickness also affected grassland, cropland, and deciduous needleleaf trees. The correlation coefficient between active layer thickness and cropland area is 0.74 in the continuous permafrost zone. The interaction between factors is mostly manifested as a two-factor enhancement, with the highest q-value of the interaction of temperature and precipitation for explanatory power. Our results suggest that climate change and permafrost degradation significantly changed land cover in Siberia. This finding deepens our understanding of the mechanisms of land cover change under the influence of permafrost degradation and provides a new perspective on the land cover changes in permafrost regions.

Socioeconomic analysis of deforestation and economically sustainable farming systems to foster forest landscape restoration in central Togo

Cropland expansion, driven by increasing population pressure and economic demands, is a major contributor to accelerating deforestation. While most studies have focused on the spatial and temporal analysis of landscape changes using Geographic Information Systems (GIS) and remote sensing, there has been less emphasis on the socioeconomic analysis of these changes. Understanding the socioeconomic dynamics of affected areas is essential for implementing practical corrective actions. We apply linear programming and welfare maximization theory to examine how population growth impacts competition between agriculture and forest land use, per capita cash income, and subsistence consumption from privately owned farms. Focusing on the Tchamba district in Togo, we aim to determine the sustainability of farming systems to better inform the ongoing Forest Landscape Restoration (FLR) program. The findings show that the current agricultural systems can support the population growth rate (2.68% per year in the Tchamba district) and per capita income until at least 2063. However, the current agricultural systems cannot support one human generation, which is estimated to be 65 years. These results underscore the need to enhance farming technologies, boost land productivity, diversify income sources to meet the rising food demand and curb forest clearing for farmland expansion. By integrating these insights into the FLR program, this research highlights the importance of a comprehensive policy framework that supports sustainable agricultural practices, community engagement, enforcement of regulations, and economic diversification. This approach will guide restoration efforts and strengthen the resilience and productivity of agricultural systems under population and income pressures.

Gazing at long-term linkages between agricultural land use and population growth in India: an inverted “U-shape” relationship

Abstract This study investigates the linkages between changes in agricultural land use and population growth in India. We have employed long-term time series and a panel dataset of 1869 samples (267 districts × 7 time points from 1961 to 2021) to determine this. We theorize that there is an inverted “U-shape” relationship between changes in population growth and agricultural land. Our findings suggest a positive impact of population growth on the change in cultivated land. However, this relationship was not static during 1961–2021. We found a two-stage split relationship with a breakpoint in 1981. Prior to the 1980s, there was a 12% expansion in cultivated land in response to a unit increase in population growth. During the post-1980s, with a unit decline in population growth, there was a 5% reduction in cultivated land. The findings were reaffirmed through several robustness checks: analyses using alternative outcome variables, alternative break points in a segmented regression model, and spatial modeling. From a policy perspective, this study advances the need for the reduction of population growth rate in high-fertility states and the adoption of superior and green technology for agricultural intensification and diversification to stop cropland expansion at the cost of environmental sustainability.

Assessing the Consistency of Five Remote Sensing-Based Land Cover Products for Monitoring Cropland Changes in China

The accuracy assessment of cropland products is a critical prerequisite for agricultural planning and food security evaluations. Current accuracy assessments of remote sensing-based cropland products focused on the consistency of spatial patterns for specific years, yet the reliability of these cropland products in time-series analysis remains unclear. Using cropland area data from the second and third national land surveys of China (referred to as NLSCD) as a benchmark, we evaluate the area-based and spatial-based consistency of cropland changes in five 30 m time-series land cover products covering 2010 and 2020, including the annual cropland dataset of China (CACD), the annual China Land Cover Dataset (CLCD), China’s Land-use/cover dataset (CLUD), the Global Land-Cover product with Fine Classification System (GLC_FCS30), and GlobeLand30. We also employed the GeoDetector model to explore the relationships between the consistency in cropland change and the environmental factors (e.g., cropland fragmentation, topographic features, frequency of cloud cover, and management practices). The area-based consistency analysis showed that all five cropland products indicate a declining trend in cropland areas in China over the past decade, while the amount of cropland loss ranges from 5.59% to 57.85% of that reported by the NLSCD. At the prefecture-level city scale, the correlation coefficients between the cropland area changes detected by five cropland products and the NLSCD are low, with GlobeLand30 having the highest coefficient at 0.67. The proportion of prefecture-level cities where the change direction of cropland area in each cropland product is inconsistent with the NLSCD ranges from 13.27% to 39.23%, with CLCD showing the highest proportion and CLUD the lowest. At the pixel scale, the spatial-based consistency analysis reveals that 79.51% of cropland expansion pixels and 77.79% of cropland loss pixels are completely inconsistent across five cropland products, with the southern part of China exhibiting greater inconsistency compared to Northwest China. Besides, the frequency of cloud cover and management practices (e.g., irrigation) are the primary environmental factors influencing consistency in cropland expansion and loss, respectively. These results suggest low consistency in cropland change across five cropland products, emphasizing the need to address these inconsistencies when generating time-series cropland datasets via remote sensing.

Analyzing and Predicting LUCC and Carbon Storage Changes in Xinjiang’s Arid Ecosystems Under the Carbon Neutrality Goal

Land use/cover change (LUCC) significantly alters the carbon storage capacity of ecosystems with a profound impact on global climate change. The influence of land use changes on carbon storage capacity and the projection of future carbon stock changes under different scenarios are essential for achieving carbon peak and neutrality goals. This study applied the PLUS-InVEST model to predict the land use pattern in China’s arid Xinjiang Region in 2020–2050. The model assessed the carbon stock under four scenarios. Analysis of the historical LUCC data showed that the carbon storage in Xinjiang in 2000–2020 in five-year intervals was 85.69 × 108, 85.79 × 108, 85.87 × 108, 86.01 × 108, and 86.71 × 108 t. The rise in carbon sequestration capacity in the study area, attributable to the expansion of cropland, water, and unused land areas, brought a concomitant increment in the regional carbon storage by 1.03 × 108 t. However, prediction results for 2030–2050 showed that carbon storage capacity under the four scenarios would decrease by 0.11 × 108 and increase by 1.2 × 108, 0.98 × 108 t, and 1.28 × 108 t, respectively. The findings indicate that different land transfer modes will significantly affect Xinjiang’s carbon storage quantity, distribution, and trend. This research informs the past, present, and future of carbon storage in arid ecosystems of Xinjiang. It offers a reference for Xinjiang’s development planning and informs the efforts to achieve the carbon peak and neutrality goals.

Assessing the impact of strictly protecting 30%–50% of global land on carbon dynamics in natural and agricultural ecosystems

Societal Impact StatementStrictly protected areas for nature conservation are a key policy to benefit biodiversity and climate change mitigation since reduced deforestation and ecosystem restoration enhance carbon stocks. However, there is controversy regarding their potential societal impacts, such as competition for land and food security. Here, we investigate the implications of protecting 30% and 50% of the global ice‐free land surface on the spatiotemporal dynamics of ecosystem carbon uptake and losses, agricultural land use and synergies with food production. The study provides insights into the role of protected areas on the global terrestrial carbon store, contributing to climate change mitigation and biodiversity conservation efforts.Summary Agriculture and forestry use around half of the global ice‐free land and are major drivers of biodiversity loss. For this reason, the post‐2020 Global Biodiversity Framework of the Convention on Biological Diversity (CBD) targets at least 30% of protected global land by 2030. This study evaluates the impacts of different land‐use change scenarios on the storage of carbon in terrestrial ecosystems and trade‐offs and synergies in the global food production system by comparing a reference scenario with no additional protected area expansion targets and two scenarios with strict area‐based protection targets of 30% and 50% of the ice‐free land surface. A net global gain in carbon storage up to 110 PgC was projected for 2056–2060 in the protection scenarios compared to the reference scenario (equivalent to around 10 years of current global anthropogenic C emissions). However, regional disparities in carbon storage are large and include carbon losses in areas identified as having—at least on a decadal perspective—‘irrecoverable’ carbon. In the protection scenarios, cropland expansion in some regions is accompanied by intensification of production with an increase of up to 8% in the use of N fertiliser, which may lead to pollution and additional greenhouse gas emissions.

Spatiotemporal variation in grain production performance and efficiency of the cultivated landscapes in Upper Blue Nile Basin of Ethiopia: the impact of residual moisture-based farming on water and food security

Analysis of grain production performance can provide reference information to explore multiple cropping options and further improve the resource use efficiency of farming methods. This study investigated the spatiotemporal dynamics of grain production performance and efficiency of major crop production systems (CPS) in the Ethiopia’s Blue Nile Basin. The results show that only 39% of the basin is currently cultivated, although a significant cropland expansion (10%) was recorded between 1985 and 2020. The study identified 11 major CPS, mostly practiced in the basin. Of these, single cropping based on the main rainy season (Meher-Only) covers the largest area (26%), followed by Meher-Residual-Intermittent (12%) and Meher-Belg-Dependable (11%). Extended-Meher, Meher-Residual-Dependable, Meher-Residual-Intermittent, and Meher-Belg-Dependable are the four more powerful CPS with higher efficiency. Comparatively, CPS practiced in Wet-Woyna-Dega and Wet-Dega have better overall performance. Findings confirm that agricultural space management (land) and green-water (rainfall) utilization are the most influential factors, followed by land use planning and land use systems (CPS) invention. As landscape suitability for grain production governs future performance, in the low elevation and flood plains parts of the basin, the possibility of creating additional space into the food system is very high. In mountainous and high-altitude regions, the efficiency of grain production will decrease because incorporating additional arable land into the food system is trivial. In the last three decades, in BNB, only 10% of arable land (equivalent to 30 million quintals of food) has been added to the good system, which can support approximately 6 million people. Compared to the population growth of the basin (12 million 1985–2020), its contribution to the food system was less than 50%. This confirms that multiple cropping systems, such as Residual moisture-based CPS, have played a significant role in boosting the food system in the basin. Therefore, improving grain production performance/efficiency requires targeted investments, including the invention of more adaptable crop varieties, efficient cropping practices, and the introduction of advanced agricultural space and water management technologies. The results of the study will help identify important policy gaps and suggest possible options to enhance residual farming and other multiple cropping systems.

Assessing land use change from food croplands to rubber in Ghana's Ellembelle district: Implications for food self-sufficiency

There is evidence that cocoa and cashew farmers are targeting croplands for expansion, reducing cropland areas with negative implications for food self-sufficiency in Ghana. However, research on the dynamics of rubber expansion and its possible impact on food self-sufficiency is limited. This study analysed the intensity of land use transition from food crops to rubber and its implications for food self-sufficiency among rubber-growing households in the Ellembelle District. Land use maps were used to analyse the intensity of transition associated with rubber and food crops from 1991 to 2022. Additionally, questionnaires were used to gather information on rubber expansion, cropland loss, and food self-sufficiency from 160 rubber farmers. A Chi-square test was used to determine the relationship between households that converted croplands to rubber and food self-sufficiency. The study showed that rubber had expanded by 9647.5 ha, mainly targeting food croplands. Majority (75.3 %) of farmers reported a decline in food availability, 68.5 % reported reduced access to food, and 49.3 % indicated a decline in dietary diversity, indicating a general decrease in food self-sufficiency. However, there was no statistically significant relation between farmers who converted cropland to rubber and food self-sufficiency. This suggests that the decline in food self-sufficiency is not a result of rubber expansion but of the disproportional cropland expansion to population growth and known challenges to crop production. To achieve food self-sufficiency, there is a need to increase food crop farming among rubber-growing farmers. This can be achieved by allowing rubber farmers to spare lands solely for food crop farming, providing subsidised agricultural inputs, and enhanced extension support. Also, creating a reliable market for staple food crops such as cassava and addressing supply chain obstacles like poor road networks are essential for making food crop farming competitive.

Global change drives potential niche contraction and range shift of globally threatened African vulture

Human-induced global change poses an increasingly severe threat to biodiversity, with species having limited population sizes being particularly vulnerable. Mapping and modeling the distribution ranges of such species, along with detecting potential range shifts and contractions at both local and regional scales, are essential for developing effective conservation plans. Ruppell's vulture Gyps rueppelli, an ecologically important bird species native to Africa, is experiencing a rapid decline in its range. The purpose of this study is to map and model potential regional spatio-temporal distribution of Ruppell's vulture in Africa, alongside detecting the possibility of the species' range shifts and contractions. A total of 804 rarefied localities were identified where the Ruppell's vulture was the dominant bird species. This study employed the Maximum Entropy (MaxEnt) algorithm to perform species distribution modeling for the Ruppell's vulture. The modeling considered current climate conditions (1970s-2000s) as a baseline, along with two future climate change scenarios (Shared Socioeconomic Pathways: SSPs 245 and 585) for two future time periods (2050s and 2070s). The model's performance was evaluated by optimizing settings and examining the Area under the Receiver Operating Characteristic Curve (AUC-ROC). Among the 13 bioclimatic and anthropogenic variables included in the model, four (isothermality, cropland expansion, anthropogenic biomes, and urban expansion (in order of importance)) emerged as the most influential drivers of Ruppell's vulture regional distribution. All considered Species distribution models (SDMs) achieved high predictive performance, with AUC-ROC values exceeding 0.9.The model predicted a total of approximately 19,453 ha of suitable habitat for Ruppell's vultures in Africa, with East Africa identified as the most prominent region under the current climate scenario. Isothermality (38.8%) was the primary factor influencing Ruppell's vulture distribution, followed by agricultural expansion (29.9%) and anthropogenic biomes (7.2%) in the face of global change. The results reveal considerable future habitat loss (up to 61%) for Ruppell's vultures in the study area, alongside an eastward range shift (longitudinal axis) by the 2050s under projected climate change scenarios. These imply that Ruppell's vultures face imminent population decline and range shift due to significant habitat loss and climate change. Hence, prioritizing the development and implementation of a coordinated conservation program that incorporates captive breeding and assisted migration is critical to save this vulture species in its native African range.

Crops Feed Rain to Drylands in Northwest China

AbstractAs a key region supplementing China's limited croplands, Northwest China has undergone rapid cropland expansion over the past decades to satisfy rising food demand from population growth and socio‐economic development. Although cropland expansion may overconsume local water resources in general, in Northwest China, increased precipitation and enhanced glacier melt have increased the water available for croplands. Counterintuitively, the enhanced evapotranspiration (ET) resulting from this cropland expansion could benefit remote ecologically vulnerable natural vegetation through atmospheric moisture recycling. In this study, we used a moisture tracking model to quantify contributions of croplands and cropland expansion to local precipitation and the consequent precipitation supply to natural vegetation in Northwest China. We found that the croplands contributed 27.69 billion m3/year (2.13%) of regional total precipitation and supplied 17.30 billion m3/year (2.39%) of precipitation over natural vegetation, and the cropland expansion resulted in a net increase of 80.25 million m3/year (1.07% of the total increase) in regional precipitation and 36.23 million m3/year (4.56% of the total increase) in precipitation supply for natural vegetation. Among different types of natural vegetation, grasslands received the most precipitation supply due to its vast area, followed by forests and shrublands. The more arid regions experienced not only faster rates of cropland expansion but also obtained a greater increase in regional precipitation and precipitation supply to natural vegetation. Our study quantifies the ecological impacts of cropland expansion through moisture recycling in Northwest China. This shows the complexities of water competition between agricultural development and ecological conservation in drylands and elsewhere.

Increase in per capita cropland imbalance across countries from 1985 to 2022: A threat to achieving Sustainable Development Goals

Sustainable Development Goal 2 (SDG 2, zero hunger) highlights that global hunger and food insecurity have worsened since 2015, driven in part by growing imbalance. Addressing the challenge of achieving SDG 2 in the face of rapid global population growth requires sustained attention to global and national cropland changes. Accurately quantifying the correlation between population and cropland area (i.e., SDG 2.4.1 per capita cropland) and analyzing the trends of global cropland imbalance are essential for a comprehensive understanding of SDG 2. In this study, we utilized a new global 30 m land-cover dynamic dataset (GLC_FCS30D) to analyze cropland dynamics, quantify per capita cropland and its changes across various countries and levels of development. Our results indicate that the global cropland area expanded by 0.944 million km2 from 1985 to 2022, with an average expansion rate of 2.42 × 104 km2/yr. However, the global per capita cropland area decreased from 0.347 ha in 1985 to 0.217 ha in 2022, mainly due to a higher population increase of nearly 65% in the same period. In the context of globalization, cropland expansion and per capita cropland exhibited spatial imbalances globally, particularly in developing countries. Developing countries saw an increase in total cropland area by 7.09% but a significant decrease in per capita cropland area by 37.38%. From a temporal perspective, the global imbalance has been steadily increasing with the Gini index rising from 0.895 in 1985 to 0.909 in 2022. Consequently, this study reveals an increasing imbalance across various countries, which threatens the attainment of the targets of SDG 2.