A global record of annual terrestrial Human Footprint dataset from 2000 to 2018

Spatio-temporal prediction of groundwater vulnerability based on CNN-LSTM model with self-attention mechanism: A case study in Hetao Plain, northern China

Located in northern China, the Hetao Plain is an important agro-economic zone and population centre. The deterioration of local groundwater quality has had a serious impact on human health and economic development. Nowadays, the groundwater vulnerability assessment (GVA) has become an essential task to identify the current status and development trend of groundwater quality. In this study, the Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models are integrated to realize the spatio-temporal prediction of regional groundwater vulnerability by introducing the Self-attention mechanism. The study firstly builds the CNN-LSTM model with self-attention (SA) mechanism and evaluates the prediction accuracy of the model for groundwater vulnerability compared to other common machine learning models such as Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The results indicate that the CNN-LSTM model outperforms these models, demonstrating its significance in groundwater vulnerability assessment. It can be posited that the predictions indicate an increased risk of groundwater vulnerability in the study area over the coming years. This increase can be attributed to the synergistic impact of global climate anomalies and intensified local human activities. Moreover, the overall groundwater vulnerability risk in the entire region has increased, evident from both the notably high value and standard deviation. This suggests that the spatial variability of groundwater vulnerability in the area is expected to expand in the future due to the sustained progression of climate change and human activities. The model can be optimized for diverse applications across regional environmental assessment, pollution prediction, and risk statistics. This study holds particular significance for ecological protection and groundwater resource management.

Occurrence, ecology and health risk assessment of organophosphate triesters and diesters in surface and ground water from southwest of China

The occurrence of organophosphate triesters (OPEs) and organophosphate diesters (m-OPEs) in ground water is still unclear. To fill the blank, ground water samples in dry and wet seasons, surface river water and paired sediment samples were collected in Sichuan province and analyzed for 14 kinds of OPEs and 7 m-OPEs. Except Trimethyl phosphate was scarcely detected, the other OPEs were extensively found in aquatic environment. The concentrations of Ʃ14OPEs and Ʃ7m-OPEs ranged from 45.0 to 231 ng/L and from 1.25 to 62.3 ng/L in ground water and ranged from 2.20 to 1709 and from 0.08 to 35.5 ng/L in surface water, respectively. Compared to other reports, the pollution in Minjiang and Tuojiang river was at medium level. The concentration ratios and correlation analysis between OPEs and m-OPEs indicated that OPEs in ground water had three main sources, and m-OPEs mainly came from direct usage. Low ecological risk was found for surface water. The carcinogenic and non-carcinogenic risks of OPEs in surface and ground water via ingestion and dermal contact in moderate and high exposure scenarios were assessed, and results suggested the risks to human which mainly caused by Tri(2-chloroisopropyl) phosphate could be negligible.

Research on the Economic Loss Model of Invasive Alien Species Based on Multidimensional Data Spatialization-A Case Study of Economic Losses Caused by Hyphantria cunea in Jiangsu Province

IAS imposes significant impacts on native ecosystems and economies. Current assessment methods for economic losses predominantly rely on habitat suitability estimation and database extrapolation, often lacking integration of causal inference and dynamic spatial drivers. H. cunea, a pervasive invasive pest in Jiangsu Province, China, exemplifies this challenge through its rapid spread and multi-sector economic impacts. To address these limitations, we innovatively integrated three models: (1) Difference-in-Differences (DID) quantified causal economic impacts through spatiotemporal comparison of infested/non-infested areas; (2) GeoDetector identified key spatial drivers via stratified heterogeneity analysis; (3) MaxEnt projected ecological suitability under climate scenarios. The synergy enabled dynamic loss attribution: GeoDetector optimized DID's variable selection, while MaxEnt constrained loss extrapolation to ecologically plausible zones, achieving multi-scale causal-spatial-climate integration absent in conventional approaches. In Jiangsu Province, H. cunea caused CNY 89.2 million in primary sector losses in 2022, with forestry disproportionately impacted, accounting for 58.3% of the total losses. The DID model revealed nonlinear temporal impacts indicating a loss of 0.163 forestry per 30 m2 grid, while MaxEnt projected 22% habitat contraction under the SSP5-8.5 scenario by 2060, which corresponds to climate-adjusted losses of CNY 147 million. Spatial prioritization identified northern Jiangsu (e.g., Xuzhou, Lianyungang) as high-risk zones requiring immediate intervention. The framework enables spatially explicit prioritization of containment efforts-grids identified as high-risk necessitate a tripling of funding in comparison to low-risk areas. And SSP-specific loss projections support dynamic budget planning under climate uncertainty. By integrating causal attribution, ecological realism, and climate resilience, this model transforms IAS management from reactive firefighting to proactive, data-driven governance. It provides a replicable toolkit for balancing ecological preservation and economic stability in the Anthropocene.

Nonlinear dynamics of ecosystem productivity and its driving mechanisms in arid regions: A case study of Ebinur Lake Basin

Arid zone ecosystems exhibit significant sensitivity to climate change and human activities, often demonstrating pronounced nonlinear characteristics in their response processes. This study focuses on the typical inland basin of the Ebinur Lake Basin in the arid region of northwest China. Utilizing long-term remote sensing and meteorological data from 1982 to 2018, combined with an improved BFAST algorithm, the XGBoost-SHAP analytical framework, and Partial Least Squares Structural Equation Modeling (PLS-SEM), we systematically investigated the nonlinear variation characteristics of Gross Primary Productivity (GPP) and its underlying driving mechanisms. The results reveal that tipping points in GPP changes were detected in 99.78 % of the Ebinur Lake Basin, with the "Negative Reversal" type (initially increasing and then decreasing) being the most prevalent, accounting for 35.91 % of the cases. The majority of GPP tipping points occurred between 1998 and 2002, with the highest frequency observed in 1998 (10.54 %). Vapor pressure deficit (VPD) was identified as the primary factor controlling GPP changes in the Ebinur Lake Basin. However, in areas where the ecosystem exhibited a recovery trend, temperature surpassed VPD as the dominant driving factor, indicating that improved temperature conditions are critical for productivity restoration. These findings enhance our understanding of the nonlinear characteristics and underlying mechanisms of arid zone ecosystems, providing a scientific basis for adaptive ecosystem management in the region.

First rangewide density estimate of the endemic and isolated Luangwa giraffe in Zambia

The Luangwa giraffe (Giraffa tippelskirchi thornicrofti), a subspecies of the Masai giraffe endemic to the Luangwa Valley of northeastern Zambia, inhabits an increasingly human-modified landscape. Accurate and current population estimates are critical to evaluating their status and identifying effective conservation strategies. However, sparse monitoring since the early 1900s has limited inferences about population size, structure, and range. To address this, we conducted the most spatially extensive and systematic survey to date of Luangwa giraffe across its distribution, extending survey effort 120 km south of their officially recognized extent. Using spatial capture recapture modeling, we estimated 651-890 giraffe and an overall density of 0.04-0.05 giraffe/km2. Density decreased to nought beyond 7.5 km from permanent rivers, consistent with preferred forage concentrated in riparian areas. Increasing giraffe density estimates up to a threshold of the Human Footprint Index suggested that limited human presence may have negligible consequences on movement and resource selection. This was likely due to suitable habitat and minimal conflict despite human presence. However, without mitigating land-use planning, rapid land conversion threatens human-giraffe coexistence. An even sex ratio and small proportion of subadults implied a stable population, but sex-biased and temporal dynamics in space use, impacts of predation, and stochastic risks necessitate continued monitoring. This study highlights the value of systematic large-scale monitoring and opportunities for data integration across long-term monitoring programs to evaluate factors driving Luangwa giraffe dynamics and to inform science-based conservation of this unique and isolated population.

The SESAME Human-Earth Atlas

Human activities such as food production, mining, transportation, and construction have extensively modified Earth's land and marine environments, causing biodiversity loss, water pollution, soil erosion, and climate change. However, studying spatial aspects of the relationships that link the global human system with non-human parts of the Earth-system is hampered by data fragmentation. Here we present the Surface Earth System Analysis and Modeling Environment (SESAME) Human-Earth Atlas, which includes hundreds of variables capturing both human and non-human aspects of the Earth system on two common spatial grids of 1- and 0.25-degree resolution. The Atlas is structured by common spheres, and many variables resolve changes over time. Machine learning is used selectively to interpolate data in undersampled regions. Many of the national-level tabular human system variables are downscaled to spatial grids using dasymetric mapping, accounting for country boundary changes over time. Raster, point, line, polygon, and tabular jurisdictional (i.e., country) data were mapped onto a standardized spatial grid at the desired resolution. The Atlas facilitates data discovery and modeling of human-Earth system dynamics.

Conservation effectiveness of terrestrial mammals and its relationship with representativeness of protected areas in China

Mammal suitable habitats are increasingly threatened by human disturbance, yet quantifying the performance of protected areas (PAs) in conserving these habitats remains challenging. Additionally, research on the relationship between the representativeness of PAs and their effectiveness in conserving mammal suitable habitats remains limited. To address this gap, we predicted the potential suitable habitats (PSHs) of terrestrial mammals across China using species distribution models. We then developed a rapid assessment method to evaluate the effectiveness of PAs in mitigating human footprints (HFP) within the mammal PSHs. Locally Weighted Scatterplot Smoothing (Lowess) was applied to identify the optimal proportion of mammal PSHs represented by PAs that maximizes conservation effectiveness. Our analysis revealed that 99.6 % of mammal PSHs experienced a significant increase in HFP from 2011 to 2020, with narrow-range species showing the most rapid growth. Despite these pressures, PAs effectively mitigated HFP within the PSHs of 92 % of species. For mammal species with varying PSH sizes, the highest effectiveness in PA representativeness was observed at 29 % for species with PSH < 100,000 km2, 19 % for species with 100,000 km2 ≤ PSH ≤ 250,000 km2, and 17 % for species with PSH > 250,000 km2. Our findings emphasize the need to enhance the representativeness of PAs for mammal suitable habitats, particularly for narrow-range species. This study will provide scientific guidance for the conservation of suitable habitats for terrestrial mammals in China and globally, as well as for the strategic planning of PAs.

The Involvement of Human Factors Brings New Findings for Predicting Global Suitability Habitat for Hyphantria cunea (Lepidoptera: Arctiidae)

Invasive pests have spread globally at an unprecedented scale, severely threatening biodiversity and resulting in significant economic losses, emerging as a global problem. This study utilizes the Maxent model, incorporating human and natural factors to predict the current and future potential global distribution of Hyphantria cunea, for comparison with climate change. Results indicate that under the influence of climate change, human factors have significantly altered the potential global distribution of H. cunea. In contrast to the potential distribution driven by climate change, this paper suggests that the suitable habitat area for H. cunea in Oceania, Southern Hemisphere, is expected to increase. Over the long term, under the SSP126 and 585 scenarios, there is a forecasted reduction of 25.2% and 33.2% in the suitable living area for H. cunea, whereas the SSP245 and 370 scenarios anticipate increases of 13.9% and 5.7%, respectively. Moreover, this research identifies areas of high suitability across continents and forecasts changes in the distribution patterns of H. cunea in the future. It offers crucial insights for developing more effective global quarantine strategies and pest management policies.

Potential construction area identification of the transboundary national park bridging ecology, society and economics: A case study of Mount Everest region

In biodiverse border regions, establishing transboundary national parks is essential for conserving ecological integrity, promoting sustainable development, and enhancing cross-border cooperation. This study aims to develop an integrated hierarchical identification model that bridges ecology, society, and economics to support effective site selection. We introduce a novel model that comprehensively evaluates potential construction areas based on three criteria-irreplaceability, connectivity, and cost-effectiveness. The model categorizes the landscape into three priority zones: core ecological areas, connective ecological areas, and peripheral radiation areas. Key indicators such as ecosystem service value, landscape ecological risk, and human activity intensity are employed to assess these zones. Application of the model to the Mount Everest region identified a total potential area of 63,824 km2 for the transboundary national park. Within this area, core ecological areas account for 22.54 %, connective ecological areas for 21.35 %, and peripheral radiation areas for 56.12 %. Significantly, disparities in ecosystem service value, ecological risk, and human activity intensity exist across the China-Nepal border, with indicator variations closely aligned with the corresponding priority zones. The findings underscore the need for China and Nepal to consider regional and national differences when planning future park construction. Tailored zonal management and a dynamic cooperative mechanism are key to sustainable and effective transboundary park development.

Mammals on the Margins: Identifying the Drivers and Limitations of Range Expansion

Accurately estimating species distributions is critical for tracking how biodiversity is shaped by global change. While some species are expanding their ranges, the importance of factors like climate change, habitat change, and human avoidance for explaining this expansion is not well understood. Here, we used observations of 94 North American mammals on iNaturalist to (1) identify errors of omission in the existing range maps; (2) differentiate between extra-range populations that are likely products of natural expansions vs. introductions; and (3) test hypotheses about where natural range expansions occur. We found a substantial percentage of observations were outside both IUCN (16%) and Area of Habitat (36%) maps, suggesting that integrating contemporary citizen science data would improve existing range maps. We estimated that most observations outside IUCN ranges were natural expansions and 95% of species had at least one naturally expanding population. We also identified introductions for 36% of species, which were particularly extensive for several species. We show that natural range expansions are generally associated with a lighter human footprint and less habitat change and are not associated with warming temperatures. This suggests that habitat modifications by humans constrain the ability of species to expand their range to track a changing climate. We also found substantial variation in the directionality of effects from all factors across species, meaning that our species-specific findings will be useful for conservation planning. Our study demonstrates that citizen science data can be useful for conservation by tracking how organisms are responding, or failing to respond, to global change.

Impacts of dams and reservoirs on riparian vegetation in China under climate change

China has built over 100,000 dams by 2020, with the total capacity of reservoirs reaching 989 billion cubic meters. The effects of reservoirs on the ecological environment of riparian zones need thorough study, yet current research covers only a small portion of China's completed dams. This study uses fixed effects vector decomposition and structural equation modeling to quantify the response of riparian vegetation to reservoirs near 921 completed dams in China, within a range of 1-10 km. The results reveal spatial variations in the response of vegetation to dam construction. Within a 1 km of the reservoir, riparian vegetation is negatively affected by habitat fragmentation and altered hydrological conditions (Coeff -0.14, P < 0.05). However, with increasing distance from the reservoirs, the effects diminish (P > 0.05, 2-5 km) or even become positive (Coeff > 0, P < 0.05, 5-10 km). Within the 1-10 km buffers, the negative effects of dams and reservoirs on riparian vegetation through climate and soil also show a distance decay (P < 0.05). This study provides new evidence of the long-term effects of hydraulic engineering development on riparian vegetation and explores the pathways and spatial scope of these impacts, which has important implications for hydropower planning and river ecosystem management.

Protected areas mitigate the reduction in habitat suitability for swans under climate change: A case study in the Yellow River Basin

Changes in migratory birds' habitats are important indicators of the health of global ecosystems. However, the habitat dynamics of the flagship swan species in China's major river basins and the adaptive strategies these species employ to respond to climate change have remained unclear. Using citizen science data, survey data, and species distribution models, we explored how three future climate scenarios for 2040-2060 affect habitat suitability for migratory swans in the Yellow River Basin. We also evaluated the role of protected areas (PAs) in mitigating the negative impacts of climate change. We found that (1) under current climate conditions, the Mute Swan (Cygnus olor), the Bewick's Swan (Cygnus columbianus bewickii), and the Whooper Swan (Cygnus cygnus) occupy substantial suitable habitats, with the Whooper Swan having the most extensive range. (2) the Mute Swan and the Bewick's Swan were predicted to experience the largest habitat loss under the high-emission scenario, while the Whooper Swan would benefit from climate change by gaining suitable habitat, especially under the medium-emission scenario. (3) PAs were most effective in mitigating the adverse effects of climate change on habitat suitability for the Mute Swan, followed by the Whooper Swan, with limited mitigating effect for the Bewick's Swan. These findings highlight the need for species-specific conservation strategies and the critical role of PAs in preserving habitat suitability under climate change.

Mitigation of human activity impacts on habitat quality in the Chengdu-Chongqing urban agglomeration

Habitat is one of the important contents in regional ecological security research. However, whether the impact of human activities on habitat quality has been effectively controlled remains to be further explored. Using urban-rural gradients, spatial autocorrelation analysis, and the MGWR model, we assessed how human activities have affected habitat quality in the Chengdu-Chongqing urban agglomeration. Our results show that habitat quality has consistently declined over the past two decades, exhibiting a "low in the middle, high around the edges" spatial distribution pattern. Over 60% of the area is at medium or lower habitat quality levels. Simultaneously, the human activity intensity has clearly increased, affecting approximately 114,354.68 km2 of area. Although habitat quality is slowly declining and the negative effects of human activities are being gradually controlled, the areas with both low human activity and low habitat quality have grown by 42.83%, suggesting that the management of human activities is expected to face increasing challenges in the future.

Global extent and change in human modification of terrestrial ecosystems from 1990 to 2022

Habitat loss and degradation associated with industrial development is the primary threat and dominant driver of biodiversity loss globally. Spatially-explicit datasets that estimate human pressures are essential to understand the extent and rate of anthropogenic impacts on ecosystems and are critical to inform conservation commitments and efforts under the Global Biodiversity Framework. We leveraged the human modification framework to generate comprehensive, consistent, detailed, robust, temporal, and contemporary datasets to map cumulative and individual threats associated with industrial human activities to terrestrial biodiversity and ecosystems from 1990 to 2022. In ~2022, 43% of terrestrial lands had very low levels of modification, while 27%, 20%, and 10% had low, moderate, and high modification, respectively. Nearly 2/3 of biomes and 1/2 of ecoregions currently are moderately-modified, and 24% of terrestrial ecosystems (31 M km2) experienced increased modification from 1990 to 2020. About 29% of countries and 31% of ecoregions might also be particularly vulnerable to biodiversity loss given their above-average increased modification and less than 30% protection.

Response of Montane Fish Biodiversity to Landscape and Anthropogenic Activity Under Potential Water Quality Pathways

Mountain river ecosystems, globally recognized biodiversity hotspots shaped by pronounced landscape heterogeneity, are facing intensifying anthropogenic pressures. However, interactions between landscape and anthropogenic activity on montane fish biodiversity remain poorly quantified. Taking the Yuan River (Yunnan, China) as a model system, environmental DNA (eDNA) and partial least squares structural equation modeling (PLS-SEM) were coupled to disentangle responses of fish biodiversity facets (taxonomic, functional and genetic diversity) to elevation and human footprint gradients. First, eDNA-derived taxonomic composition (R = 0.97 against catch data) demonstrated Cypriniformes and Perciformes dominance. Second, downstream areas exhibited enhanced taxonomic (R = 0.32) and functional diversity (R = 0.49), contrasting with upstream genetic diversity maxima (R = -0.47). Third, elevation gradients and human footprint exerted stronger direct effects on taxonomic diversity than on functional or genetic metrics, independent of spatial autocorrelation. Crucially, PLS-SEM identified water quality (i.e., total phosphorus (TP), total nitrogen (TN), biochemical oxygen demand (BOD5), and total organic carbon (TOC)) as a pivotal mediator linking elevation and human footprint to biodiversity outcomes. Overall, the present study establishes a mechanistic framework for disentangling landscape and anthropogenic drivers of biodiversity change, offering a scalable reference for conservation prioritization in montane freshwater ecosystems.

Urbanization Pressures on Climate Adaptation Capacity of Forest Habitats

Urbanization extensively shapes the wildland-urban interfaces (WUIs). However, the effects of urbanization on forest habitats in WUIs as thermal refuges for biodiversity remain elusive. Here, we show that urbanization-induced increases in human footprints cause canopy degradation of forest habitats in WUIs, including declines in forest coverage (-12.61% ± 0.05%), leaf area index (-0.45 ± 0.01 m2 m-2), and canopy height (-3.74 ± 0.02 m). Canopy degradation weakens forest-based climate change adaptation, inferred by reduced forest habitat connectivity (-9.45% ± 0.08%) and elevated daily mean surface temperature (0.41°C ± 0.01°C) in WUIs, leading to a rise in frequency (0.22 ± 0.01 days) and intensity (1.05°C ± 0.02°C) of annual mean thermal extremes compared to that in nearby wildlands. A 10.01% ± 0.07% lower mean species richness in WUIs than nearby wildlands demonstrates local biodiversity loss in WUIs driven by intense human footprints, declined habitat connectivity, and increased thermal stress. We highlight the need for urban planning to fully integrate solutions for climate adaptation and biodiversity conservation.

Genetic diversity and population structure of Oncomelania hupensis in Sichuan Province, China: implications for schistosomiasis control

Schistosomiasis, caused by the infection with Schistosoma japonicum, remains a significant public health concern in China. As the sole intermediate host of S. japonicum, the breeding and spread of Oncomelania hupensis contribute significantly to the potential risk of disease occurrence and transmission. Exploring the population genetics of the snail vector is conducive to better understanding its distribution and dispersal patterns, and provides more data for future snail surveillance and control from a molecular perspective. The genetic diversity and population structure of O. hupensis in Sichuan Province were evaluated based on sequencing of mitochondrial cytochrome c oxidase subunit 1. A total of 215 snail isolates were collected from 30 counties, identifying 80 haplotypes with high nucleotide diversity (0.05871 ± 0.00160) and haplotype diversity (0.979 ± 0.003). Phylogenetic analysis and haplotype network construction identified five distinct clades. Notably, clade 1 was confined within the Panxi region, while clade 5 exhibited a widespread distribution across the studied areas, distinct from the other four clades, but showing a close genetic relationship to individuals from Yunnan. Spatial differentiation was revealed by significant pairwise genetic distance values detected in 313 out of 435 population pairs, ranging from 0.07632 to 1.00000. Analysis of molecular variance (AMOVA) showed that the majority of variance occurred among populations, but significant differences were also observed among landscape groups. AMOVA also provided support for clade separation by exhibiting significant genetic differences among the clades, which explained 78.23% of the overall variation. Geographical distance and precipitation were found to display a significant correlation with the genetic differentiation pattern of O. hupensis in both Mantel and partial Mantel tests. Temporal stability was observed over sampling intervals of 7 years, particularly among snail populations inhabiting the Panxi area, despite prolonged molluscicide treatment. This study provides updated insights into the genetic diversity and population structure of O. hupensis in Sichuan Province, which contribute to a better understanding of the challenges faced in snail control. In light of the findings, the integration of molecular insights into snail monitoring and control, and the reinforcement of collaborative efforts in neighboring regions, in addition to long-distance monitoring, are suggested.

Host life stage susceptibility to the chytrid fungus in a Neotropical torrent frog

Pathogen-host systems become complex when they involve life histories with multiple stages. Understanding these complexities is particularly important for investigating the infection dynamics of the amphibian pathogen Batrachochytrium dendrobatidis (Bd). Here, we investigate whether Bd infection susceptibility differs between host life stages and determine the influence of environmental factors on Bd infection rates across remnant populations of a Neotropical torrent frog. We found that Bd infection probability varies between tadpoles and adults in Hylodes phyllodes, with tadpoles exhibiting a higher likelihood of infection. Tadpoles are tolerant to Bd, acting as zoospore reservoirs, potentially aiding in the pathogen's persistence in the environment and infecting other susceptible hosts. Topographic complexity, species richness, the human footprint, precipitation seasonality and diurnal temperature variations influenced Bd infection rates. Conservation strategies should encompass both host life stages, monitoring from larvae to adults, while also evaluating threats synergistically, such as the human footprint, to effectively predict and mitigate the impact of Bd on susceptible populations.

A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production

Land use is intimately linked to key components of the Earth system, including the climate system, biodiversity and biogeochemical cycles. Advanced understanding of patterns and dynamics of land use is vital for assessing impacts on these system components and for developing strategies to ensure sustainability. However, thematically detailed data that enable the analyses of spatiotemporal dynamics of land use, including land-use intensity, are currently lacking. This study presents a comprehensive land-use data cube (LUIcube) that traces global land-use area and intensity developments between 1992 and 2020 annually at 30 arcsecond spatial resolution. It discerns 32 land-use classes that can be aggregated to cropland, grazing land, forestry, built-up land and wilderness. Land-use intensity is represented through the framework of Human Appropriation of Net Primary Production, which allows to quantify changes in NPP, respectively biomass flows, induced by land conversion and land-management. The LUIcube provides the necessary database for analyzing the role of natural and socioeconomic drivers of land-use change and its ecological impacts to inform strategies for sustainable land management.

Methane emissions from thermokarst lakes must emphasize the ice-melting impact on the Tibetan Plateau

Thermokarst lakes, serving as significant sources of methane (CH4), play a crucial role in affecting the feedback of permafrost carbon cycle to global warming. However, accurately assessing CH4 emissions from these lakes remains challenging due to limited observations during lake ice melting periods. In this study, by integrating field surveys with machine learning modeling, we offer a comprehensive assessment of present and future CH4 emissions from thermokarst lakes on the Tibetan Plateau. Our results reveal that the previously underestimated CH4 release from lake ice bubble and water storage during ice melting periods is 11.2 ± 1.6 Gg C of CH4, accounting for 17 ± 4% of the annual total release from lakes. Despite thermokarst lakes cover only 0.2% of the permafrost area, they annually emit 65.5 ± 10.0 Gg C of CH4, which offsets 6.4% of the net carbon sink in alpine grasslands on the plateau. Considering the loss of lake ice, the expansion of thermokarst lakes is projected to lead to 1.1-1.2 folds increase in CH4 emissions by 2100. Our study allows foreseeing future CH4 emissions from the rapid expanding thermokarst lakes and sheds new lights on processes controlling the carbon-climate feedback in alpine permafrost ecosystems.

Temporal and Spatial Dynamics of Rodent Species Habitats in the Ordos Desert Steppe, China

Climate change is driving the restructuring of global biological communities. As a species sensitive to climate change, studying the response of small rodents to climate change is helpful to indirectly understand the changes in ecology and biodiversity in a certain region. Here, we use the MaxEnt (maximum entropy) model to predict the distribution patterns, main influencing factors, and range changes of various small rodents in the Ordos desert steppe in China under different climate change scenarios in the future (2050s: average for 2041-2060). The results show that when the parameters are FC = LQHPT, and RM = 4, the MaxEnt model is optimal and AUC = 0.833. We found that NDVI (normalized difference vegetation index), Bio 12 (annual precipitation), and TOC (total organic carbon) are important driving factors affecting the suitability of the small rodent habitat distribution in the region. At the same time, the main influencing factors were also different for different rodent species. We selected 4 dominant species for analysis and found that, under the situation of future climate warming, the high-suitability habitat area of Allactaga sibirica and Phodopus roborovskii will decrease, while that of Meriones meridianus and Meriones unguiculatus will increase. Our research results suggest that local governments should take early preventive measures, strengthen species protection, and respond to ecological challenges brought about by climate change promptly.

Multiscale exploration of spatiotemporal dynamics in China's largest urban agglomeration: An interactive coupling perspective on human activity intensity and ecosystem health

Human economic construction increasingly impacts highly sensitive ecological zones, weakening ecosystem health in cross-regional urban agglomerations. Exploring the spatiotemporal dynamics of urban agglomerations from the interactive coupling perspective between human activity intensity (HAI) and ecosystem health index (EHI) is crucial for resolving human-land conflicts. This study developed a human-land coupling assessment framework integrating human footprint and ecosystem Maintain-Bearing-Service-Resilience models. Across multiple scales, from urban agglomerations and cities to grid cells, we initially employed exploratory spatiotemporal data analysis techniques to reveal HAI and EHI evolution patterns. Subsequently, we used the four-quadrant model, coupling coordination degree (CCD), and relative development model to explore their spatiotemporal interactions. Applied to China's largest urban agglomeration, the middle reaches of the Yangtze River urban agglomerations (MRYRUA), results revealed a significant spatiotemporal mismatch pattern between HAI and EHI. High HAI and low EHI areas were widely distributed in highly urbanized waterfront plains. At the urban agglomeration scale, HAI and EHI exhibited spatiotemporal differentiation patterns extending toward polarization along the Yangtze River Economic Belt, while their correlation intensity among cities indicated conflicting development patterns. At the grid scale, the spatiotemporal clustering pattern highlighted waterfront built-up areas as HAI hotspots and peripheral forest zones as EHI hotspots. The interactive relationship between HAI and EHI shifted increasingly towards Quadrant IV as HAI rose. The coupling levels between HAI and EHI will tend toward misalignment as urbanization advances, although current CCD shows positive trends. This study offers scientific guidance for achieving sustainable development in urban agglomerations across multiple scales.

Land use types, basin characteristics and water quality together shape riverine phytoplankton community composition and diversity

Exploring the combined effects of basin characteristics, land use types, and human activities on phytoplankton biomass, community composition and diversity is important for developing effective river protection strategies. In the present study, 182 phytoplankton samples were collected in the Hanjian and Danjiang River basins and the explanation rate of the above factors was analyzed. Water quality was the primary factor affecting riverine phytoplankton biomass, with an explanation rate to Chl a reaching 59.8%. Water quality was also the primary factor affecting phytoplankton diversity but the contribution of land use types and basin characteristics was also high. In addition to affecting phytoplankton communities and diversity by affecting water quality, diverse land use can increase the taxa of algae discharged through soil erosion processes. Elevation and slope were the main basin characteristics regulating phytoplankton community and diversity because they can determine the retention time of phytoplankton in rivers. The results also showed that land use types were the primary factor affecting the critical relative abundance of extinction (a), competition coefficient (k), environmental taxa capacity (N), but water quality was the primary factor affecting Shannon index, Simpson index, and Pielou index. This difference indicated that index a, k, and N could reflect specific characteristics of phytoplankton diversity that were not reflected by the latter indices. Our results implied that land use types and basin characteristics affected the discharge of exotic algal taxa, retention time, and other factors, thereby influencing the composition and diversity of riverine phytoplankton communities.

Climate change enhances greening while human activities accelerate degradation in northern China's grasslands

Northern China's grasslands play a pivotal role in livestock production, energy utilization, and ecosystem balance, both domestically and globally. However, they exhibit pronounced temporal variability and marked spatial heterogeneity. Since most existing studies rely on single vegetation indices and regional-scale analyses, they may introduce biases in interpreting grassland dynamics and their underlying drivers. To address this gap, we integrated both functional and structural indices - Gross Primary Productivity (GPP), solar-Induced chlorophyll fluorescence (SIF), Normalized Difference Vegetation Index (NDVI), and Leaf Area Index (LAI) - to systematically investigate spatiotemporal trends across various grassland types in northern China. Using partial derivative analysis, we quantified the relative contributions of climate change and human activities to these observed vegetation trends. Results indicated that over 70 % of grassland areas, especially temperate grasslands, showed an overall increase in vegetation indices, while a decline was observed in the southwestern alpine grasslands. Climate change was the primary driver of grassland greening (56.55 %-63.83 %), primarily through increased precipitation in temperate grasslands and rising temperatures in alpine grasslands. Human activities contributed substantially to greening (36.17 %-43.45 %), especially in desertified temperate grasslands (e.g., Mu Us Sandy Land, Gansu, Ningxia, Xinjiang) and Qinghai alpine meadows, mainly through farmland restoration and desertification control. Conversely, human activities also served as the primary driver of grassland degradation (51.70 %-69.64 %) in certain alpine regions, where overgrazing and population growth - compounded by rising temperatures and declining soil moisture - led to significant vegetation losses. Moreover, 72.66 % of temperate grasslands demonstrated strong coupling between vegetation structure and function, whereas 57.59 % of alpine grasslands exhibited increasing GPP alongside declines in both LAI and SIF. Overall, these findings underscore the spatial heterogeneity of grassland responses to climatic and anthropogenic drivers, highlighting the necessity of employing multiple vegetation indices to guide targeted and effective grassland management strategies.

Impacts of road development in sub-Saharan Africa: A call for holistic perspectives in research and policy

This perspective explores the multifaceted development challenges related to road network expansion in sub-Saharan Africa, where recent infrastructure investments reflect transformative ambitions but also imply socio-ecological tradeoffs. Roads can boost economic growth by facilitating trade, tourism, and access to essential services, yet they simultaneously contribute to ecosystem fragmentation, biodiversity loss, and human-wildlife conflicts. Looking at the history of Africa's road development, we find that mega-projects-often funded by international donors-reshape political and economic landscapes while altering rural livelihoods and ecosystems. We synthesize literature and case studies to reveal critical trends and propose solutions, urging for a shift toward sustainable, evidence-based infrastructure strategies that balance development with environmental stewardship. We further advocate for transdisciplinary approaches and community engagement to align road expansion with long-term stakeholder needs so as to minimize adverse impacts on Africa's socio-ecological systems.

Assessment of environmental and socioeconomic drivers of urban stormwater microplastics using machine learning

Microplastics (MPs) are ubiquitous environmental contaminants with urban landscapes as major source areas of MPs and stormwater runoff as an important transport pathway to receiving aquatic environments. To better delineate the drivers of urban stormwater MP loads, we created a global dataset of stormwater MP concentrations extracted from 107 stormwater catchments (SWCs). Using this dataset, we trained and tested three optimized gradient boosting Machine Learning (ML) models. Twenty hydrometeorological and socioeconomic variables, as well as the MP size definitions considered in the individual SWCs, were included as potential predictors of the observed MP concentrations. CatBoost emerged as the best-performing ML model. Shapley additive explanations revealed that features related to hydrometeorological conditions, watershed characteristics and human activity, and plastic waste management practices contributed 34, 25, and 4.8%, respectively, to the model's predictive performance. The MP size definition, that is, the lower size limit and the width of the size range, accounted for the remaining 36% variability in the predicted MP concentrations. The lack of a consistent definition of the MP size range among studies therefore represents a major source of uncertainty in the comparative analysis of urban stormwater MP concentrations. The proposed ML modeling approach can generate first estimates of MP concentrations in urban stormwater when data are sparse and serve as a quantitative tool for benchmarking the added value of including further data layers and applying uniform definitions of size classes of environmental MPs.

Nonlinear influences of climatic, vegetative, geographic and soil factors on soil water use efficiency of global karst landscapes: Insights from explainable machine learning

Soil Water Use Efficiency (SWUE) represents a vital metric for assessing the relationship between carbon acquisition and soil moisture (SM) depletion in terrestrial ecosystems. However, the elucidation of time-lagged and cumulative effects, nonlinear influences, and indirect contributions of explanatory variables, including climate and vegetation characteristics, on SWUE in global karst landscapes remains limited. In this study, we analyzed the time-lagged and cumulative effects of climatic and biological factors on SWUE in global karst landscapes using the Autoregressive Distributed Lag Model. By comparing nine machine learning models, we further revealed the nonlinear effects, as well as the direct and indirect contributions of climatic, geographic, soil, and biological explanatory variables on SWUE across varying aridity, using the Random Forest Model, SHapley Additive exPlanations, Generalized Additive Model, and Partial Least Squares-Structural Equation Modeling (PLS-SEM). The findings suggested that precipitation and wind speed exert the most substantial time-lagged and cumulative impacts on SWUE in global karst landscapes, respectively. The Random Forest model outperforms eight other machine learning models, including CatBoost, LightGBM, and XGBoost, in accurately simulating SWUE. In global karst landscapes, SWUE was significantly affected by the positive contributions of evapotranspiration, leaf area index, and temperature, as well as the negative impacts of latitude and longitude. These influences exhibited varying degrees of nonlinearity across the aridity gradient. Using PLS-SEM based on the 'geo-climatic-soil-biological' cascade effect, it was found that gross primary production directly and significantly influences karst SWUE under both drought-prone and water-abundant conditions, significantly exceeding the impact of SM. Geographic, climatic, and biological factors indirectly influenced karst SWUE by affecting gross primary production. The impact of soil type, soil carbon and nitrogen content, and rootable depth on SWUE was minimal. This study enhances our understanding of carbon sinks and the water‑carbon cycle, providing valuable insights into resource use efficiency within karst environments.

A compendium of 8,176 bat RNA viral metagenomes reveals ecological drivers and circulation dynamics

Bats are natural hosts for many emerging viruses for which spillover to humans is a major risk, but the diversity and ecology of bat viruses is poorly understood. Here we generated 8,176 RNA viral metagenomes by metatranscriptomic sequencing of organ and swab samples from 4,143 bats representing 40 species across 52 locations in China. The resulting database, the BtCN-Virome, expands bat RNA virus diversity by over 3.4-fold. Some viruses in the BtCN-Virome are traced to mammals, birds, arthropods, mollusks and plants. Diet, infection dynamics and environmental parameters such as humidity and forest coverage shape virus distribution. Compared with those in the wild, bats dwelling in human settlements harboured more diverse viruses that also circulated in humans and domestic animals, including Nipah and Lloviu viruses not previously reported in China. The BtCN-Virome provides important insights into the genetic diversity, ecological drivers and circulation dynamics of bat viruses, highlighting the need for surveillance of bats near human settlements.

Assessing tick attachments to humans with citizen science data: spatio-temporal mapping in Switzerland from 2015 to 2021 using spatialMaxent

BACKGROUND

Ticks are the primary vectors of numerous zoonotic pathogens, transmitting more pathogens than any other blood-feeding arthropod. In the northern hemisphere, tick-borne disease cases in humans, such as Lyme borreliosis and tick-borne encephalitis, have risen in recent years, and are a significant burden on public healthcare systems. The spread of these diseases is further reinforced by climate change, which leads to expanding tick habitats. Switzerland is among the countries in which tick-borne diseases are a major public health concern, with increasing incidence rates reported in recent years.

METHODS

In response to these challenges, the "Tick Prevention" app was developed by the Zurich University of Applied Sciences and operated by A&K Strategy Ltd. in Switzerland. The app allows for the collection of large amounts of data on tick attachment to humans through a citizen science approach. In this study, citizen science data were utilized to map tick attachment to humans in Switzerland at a 100 m spatial resolution, on a monthly basis, for the years 2015 to 2021. The maps were created using a state-of-the-art modeling approach with the software extension spatialMaxent, which accounts for spatial autocorrelation when creating Maxent models.

RESULTS

Our results consist of 84 maps displaying the risk of tick attachments to humans in Switzerland, with the model showing good overall performance, with median AUC ROC values ranging from 0.82 in 2018 to 0.92 in 2017 and 2021 and convincing spatial distribution, verified by tick experts for Switzerland. Our study reveals that tick attachment to humans is particularly high at the edges of settlement areas, especially in sparsely built-up suburban regions with green spaces, while it is lower in densely urbanized areas. Additionally, forested areas near cities also show increased risk levels.

CONCLUSIONS

This mapping aims to guide public health interventions to reduce human exposure to ticks and to inform the resource planning of healthcare facilities. Our findings suggest that citizen science data can be valuable for modeling and mapping tick attachment risk, indicating the potential of citizen science data for use in epidemiological surveillance and public healthcare planning.

Response of carbon storage to land use change and multi-scenario predictions in Zunyi, China

Evaluating and predicting how carbon storage (CS) is impacted by land use change can enable optimizing of future spatial layouts and coordinate land use and ecosystem services. This paper explores the changes in and driving factors of Zunyi CS from 2000 to 2020, predicts the changes in CS under different development scenarios, and determines the optimal development scenario. Woodland and farmland are the main land use types in Zunyi. Land use change was reflected mainly in the mutual conversion among woodland, farmland, and grassland and by their conversion to construction land and water. In 2000, 2010, and 2020, the CS in Zunyi was 658.77 × 10^6 t, 661.44 × 10^6 t, and 658.35 × 10^6 t, respectively. Woodland, farmland and grassland conversions to construction land and water were primarily responsible for CS loss. The normalized difference vegetation index (NDVI) is the main factor influencing the pattern of CS (q > 10%). Furthermore, the impacts of the human footprint index and population density are increasing. In 2030, the CS of Zunyi is trending downward. Under the ecological-farmland conservation scenario (ECS), the CS is estimated to be 656.67 × 10^6 t, with the smallest decrease (- 0.26%) among timepoints. The effective control of woodland and farmland weakens the trend of CS reduction.

Promoting Balanced Ecological-economic Development in Ecologically Vulnerable Regions: Spatio-temporal Variation and Driving Factors

Formulating a consistent standard for ecosystem service value (ESV) estimation and incorporating it into government decision-making is an important way to achieve balanced ecological-economic development. Taking the ecologically vulnerable areas in Northwest China as an example, this paper uses the value transfer method to estimate the ESV of cropland, forest, grassland, waters, and unused land; analyzes the spatio-temporal characteristics of the increment of ESV (△ESV) and ecological-economic harmony (EEH) index in each city; as well as identifies their key influential factors. The results suggest that value transfer is a feasible approach to developing a consistent standard for ESV estimation. The ecological-economic system is limited by the natural environment, economic growth, local government, population, and the development of agriculture and livestock. The main factors that affect unit ESV, total ESV, and EEH are connected but vary across space. The findings can provide a reference for estimating ESV across regions, formulating policies for land management and ecological protection, and promoting sustainable development.

Changing patterns of global nitrogen deposition driven by socio-economic development

Advances in manufacturing and trade have reshaped global nitrogen deposition patterns, yet their dynamics and drivers remain unclear. Here, we compile a comprehensive global nitrogen deposition database spanning 1977-2021, aggregating 52,671 site-years of data from observation networks and published articles. This database show that global nitrogen deposition to land is 92.7 Tg N in 2020. Total nitrogen deposition increases initially, stabilizing after peaking in 2015. Developing countries at low and middle latitudes emerge as new hotspots. The gross domestic product per capita is found to be highly and non-linearly correlated with global nitrogen deposition dynamic evolution, and reduced nitrogen deposition peaks higher and earlier than oxidized nitrogen deposition. Our findings underscore the need for policies that align agricultural and industrial progress to facilitate the peak shift or reduction of nitrogen deposition in developing countries and to strengthen measures to address NH3 emission hotspots in developed countries.

Global patterns of lake microplastic pollution: Insights from regional human development levels

Microplastics have emerged as a pervasive pollutant across various environmental media. Nevertheless, our understanding of their occurrence, sources, and drivers in global lakes still needs to be completed due to limited data. This study compiled data from 117 studies (2016-May 2024) on microplastic contamination in lake surface water and sediment, encompassing surface water samples in 351 lakes and lake sediment samples in 200 lakes across 43 countries. Using meta-analysis and statistical methods, the study reveals significant regional variability in microplastic pollution, with concentrations ranging from 0.09 to 130,000 items/m3 in surface water and from 5.41 to 18,100 items/kg in sediment. Most microplastics were under 1 mm in particle size, accounting for approximately 79 % of lake surface water and 76 % of sediment. Transparent and blue microplastics were the most common, constituting 34 % and 21 % of lake surface water and 28 % and 18 % of sediment, respectively. Fibers were the dominant shape, representing 47 % of lake surface water and 48 % of sediment. The primary identified polymer types were polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET). Countries like India, Pakistan, and China had higher contamination levels. Positive correlations were found between microplastic abundance in surface water and factors like human footprint index (r = 0.29, p < 0.01), precipitation (r = 0.21, p < 0.05), and net surface solar radiation (r = 0.43, p < 0.001). In contrast, negative correlations were observed with the human development index (r = -0.61, p < 0.01) and wind speed (r = -0.42, p < 0.001). In sediment, microplastics abundance correlated positively with the human footprint index (r = 0.45, p < 0.001). This study underscores the variability in microplastic pollution in global lakes and the role of human activities and environmental factors, offering a valuable reference for future research.

Widespread homogenization in vegetation activities along the elevational gradients across the Himalaya over the past 40 years

Mountainous regions are vital biodiversity hotspots with high heterogeneity, providing essential refugia for vegetation. However, climate change threatens this diversity with the potential homogenization of the distinct environmental conditions at different elevations. Here, we used a time-series (1985-2023) of Normalized Difference Vegetation Index (NDVI) from Landsat archives (30 m) to quantify vegetation changes across an elevation gradient on Himalaya Mountain. Our analysis revealed that over the past 40 years, the Himalayas have experienced widespread greening, accompanied by homogenization of vegetation across elevations. This homogenization, characterized by a reduction in the differences between high and low elevations, can be attributed to two main factors: (1) increased warming and a higher snowmelt rate at high elevations, facilitating rapid changes in high-elevation vegetation activities; and (2) higher anthropogenic disturbance at low and mid elevations, thus inhibiting low-elevation vegetation. These factors have resulted in a reduction of habitat differentiation along the mountain slopes, homogenizing vegetation and potentially threatening the unique biodiversity adapted to specific elevational zones. Our findings emphasize the urgent need for conservation strategies that prioritize the protection of heterogeneous mountain habitats to preserve their rich biodiversity in the face of climate change.

The impact of anthropogenic pressures on microbial diversity and river multifunctionality relationships on a global scale

Conserving biodiversity is crucial for maintaining essential ecosystem functions, as indicated by the positive relationships between biodiversity and ecosystem functioning. However, the impacts of declining biodiversity on ecosystem functions in response to mounting human pressures remain uncertain. This uncertainty arises from the complexity of trade-offs among human activities, climate change, river properties, and biodiversity, which have not been comprehensively addressed collectively. Here, we provide evidence that river biodiversity was significantly and positively associated with multifunctionality and contributed to key ecosystem functions such as microbially driven water purification, leaf litter decomposition and pathogen control. However, human pressure led to abrupt changes in microbial diversity and river multifunctionality relationships at a human pressure value of 0.5. In approximately 30 % (N = 58) of countries globally, the ratio of area above this threshold exceeded the global average (∼11 %), especially in Europe. Results show that human pressure affected ecosystem functions through direct effects and interactive effects. We provide more direct evidence that the nonadditive effects triggered by prevailing human pressure impact the multifunctionality of rivers globally. Under high levels of human stress, the beneficial effects of biodiversity on nutrient cycling, carbon storage, gross primary productivity, leaf litter decomposition, and pathogen control tend to diminish. Our findings highlight that considering interactions between human pressure and local abiotic and biotic factors is key for understanding the fate of river ecosystems under climate change and increasing human pressure.

Feedbacks between phytoplankton and global changes in a riverine source-mainstem-estuary continuum

Global changes have led to alterations in phytoplankton community structure and dynamics in aquatic environments. However, limited information is available on the comprehensive impacts of global changes on phytoplankton communities along river systems affected by anthropogenic activities. This study explores how anthropogenic pressures and climate change affect phytoplankton community transitions and induce harmful algal blooms by employing field surveys and a 40-year historical data analysis along China's Yangtze River source-mainstem-estuary continuum. Results revealed significantly higher phytoplankton density and biodiversity in the mainstem compared to the source and estuary zones. From the river's source to its mainstem and estuary, the dominant phytoplankton community formed a transition pattern (diatoms - chlorophytes - cyanobacteria - diatoms). Similarly, phytoplankton functional groups transitioned from mixed to eutrophic groups, signaling a shift in water quality towards moderate eutrophication, although it has not yet threatened the survival of diverse phytoplankton species. Moreover, compared to climate change, anthropogenic activities have more significantly intensified the urban heat island effect and nutrient inputs, thereby promoting phytoplankton cell density and biodiversity, particularly in the case of eutrophic functional groups. However, since 2003, governmental regulations have slowed the increase in nitrogen and phosphorus transport flux from the source to the estuary, contributing to the stabilization of harmful algal blooms at low levels in the estuary and adjacent waters. Strict control of nitrogen-to-phosphorus ratios is essential for preserving biodiversity, mitigating eutrophication, and preventing harmful algal blooms, thereby ensuring ecological balance and protecting water environments along the Yangtze River.

A Retrospective Report on the Infestation and Distribution of Chiggers on an Endemic Rodent Species (Apodemus latronum) in Southwest China

Chiggers are the exclusive vector of Orientia tsutsugamushi, which is the causative agent of scrub typhus. Based on the field surveys in southwest China between 2001 and 2022, this paper retrospectively reported the chigger infestation and distribution on the large-eared field mouse (Apodemus latronum), an endemic rodent species in the region, for the first time. A total of 933 chiggers were collected from 501 mice, and these chiggers were identified as 2 families, 8 genera, and 61 species. The overall infestation prevalence (PM) and mean abundance (MA) of A. latronum with chiggers reached 19.76% and 1.86 mites/per mouse, respectively. The chigger infestation indices on adult A. latronum (PM = 38.28%, MA = 5.11) were higher than those on juvenile mice (PM = 12.63%, MA = 0.97) with p < 0.01, showing an age bias of infestation. The relative fatness (K) was used to reflect the nutrition status of the mouse host. The mouse hosts with good nutrition (K = 3.4 ± 0.89 g/cm3) harbored fewer chiggers than the hosts with poor nutrition (K = 2.2 ± 0.90 g/cm3) (p < 0.01). The infestation indices of chiggers on A. latronum obviously fluctuated along different altitude gradients (p < 0.01). With the increase in altitudes, the β diversity of the chigger community showed a gradually increasing tendency. The spillover chord diagram, which was based on indices of PAC (potential for apparent competition), revealed high spillover potentials of dominant chigger species dispersing from high altitude gradients to the lowest one. The chigger abundance was positively correlated with the mean monthly temperature (tmp), mean monthly humidity (hum), the mean monthly precipitation (pre), and the human footprint (hfp), and it was negatively correlated with the altitude (ele) (p < 0.05). The temperature and humidity are the most important factors which influence the chigger infestation.

A two-dimensional four-quadrant assessment method to explore the spatiotemporal coupling and coordination relationship of human activities and ecological environment

Human activities that involve diverse behaviors and feature a variety of participations and collaborations usually lead to varying and dynamic impacts on the ecological environment. Quantitative analysis of the dynamic changes and complex relationships between human activities and the ecological environment (eco-environment) can provide crucial insights for ecological protecting and balance maintaining. We proposed a two-dimensional four-quadrant assessment method based on the dynamic changes in Human Activity Index (HAI) - Environmental Ecological Condition Index (EECI) to analyze the dynamic trends and coupling coordination degree (CCD) between HAI and EECI. This approach was applied in an empirical study of Hainan Province. A comprehensive HAI at a resolution of 1 km × 1 km is established to measure human activities, while an EECI is developed to evaluate ecological environment quality. The eco-environment showed continuous improvement, with the HAI initially rising and then declining. Analysis of coupling coordination revealed a ratio of 6:1 between coordinated development regions and conflict regions, indicating a gradual improvement in overall coupling coordination. The interaction between the HAI and EECI is strengthening, though variations exist across different locations. Using the geodetector method, we identified Net Primary Productivity (NPP), Land use and land cover (LULC), and Particulate Matter (PM) as the primary factors influencing changes in coupling coordination between HAI and EECI. These factors indirectly affect the stability and carrying capacity of the ecological environment. This method facilitates a quantitative examination of the dynamic relationship between HAI and EECI in different regions, offering insights into ecosystem functionality, biodiversity maintenance, and the effect of HAI on the region.

Changes of ecological vulnerability in areas with different urban expansion patterns- A case study in the Yanhe river basin, China

Urban expansion has the potentiality to disrupt ecosystems and form highly fragile urban landscapes. However, studies investigating the impact of different urban expansion patterns on the ecological environments are relatively limited. Taking the Yanhe river basin, a typical basin in a loess region, as a case study, we developed an ecological vulnerability assessment system as well as assessed the main drivers of ecological vulnerability for different time periods (1990, 2000, 2010 and 2018). Additionally, we classified each urban expansion region into three different patterns according to the landscape expansion index, and analyzed changes in the ecological vulnerability under these three diverse patterns. Finally, the Kruskal-Wallis rank sum test was applied to compare the factors for the different changes in ecological vulnerability across different urban expansion patterns. Our investigation also aimed to elucidate the impacts of different urban expansion patterns on ecological vulnerability and identify key physical-social-economic-climatic drivers. The results indicate that the ecological vulnerability index (EVI) of the study area is decreasing gradually from the peak value of 0.459 in 2000 to 0.383 in 2018. Habitat quality index is found to be the most influencing factor, followed by aridity index and building density (mean q of 0.53, 0.46, and 0.42, respectively). Our study also reveals that the outlying expansion areas have the greatest increase in EVI at 0.38, with edge and infill expansions at 0.31 and 0.27, respectively. It is also found that when the overall environment is improving, the outlying expansion areas have the smallest decrease in EVI. Initial ecological vulnerability and key drivers may explain this difference. Therefore, results of this study indicate that the ecological impacts of diverse urban expansion patterns are significantly different, among which outlying expansions should receive prioritized attention.

Habitat quality outweighs the human footprint in driving spatial patterns of Cetartiodactyla in the Kunlun-Pamir Plateau

The Human Footprint (HFP) and Habitat Quality (HQ) are critical factors influencing the species' distribution, yet their relation to biodiversity, particularly in mountainous regions, still remains inadequately understood. This study aims to identify the primary factor that affects the biodiversity by comparing the impact of the HFP and HQ on the species' richness of Cetartiodactyla in the Kunlun-Pamir Plateau and four protected areas: The Pamir Plateau Wetland Nature Reserve, Taxkorgan Wildlife Nature Reserve, Middle Kunlun Nature Reserve and Arjinshan Nature Reserve through multi-source satellite remote sensing product data. By integrating satellite data with the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST)HQ model and utilizing residual and linear regression analysis, we found that: (1) The Wildness Area (WA) predominantly underwent a transition to a Highly Modified Area (HMA) and Intact Area (IA), with a notable 12.02% rise in stable regions, while 58.51% rather experienced a negligible decrease. (2) From 1985 to 2020, the Kunlun-Pamir Plateau has seen increases in the forestland, water, cropland and shrubland, alongside declines in bare land and grassland, denoting considerable land cover changes. (3) The HQ degradation was significant, with 79.81% of the area showing degradation compared to a 10.65% improvement, varying across the nature reserves. (4) The species richness of Cetartiodactyla was better explained by HQ than by HFP on the Kunlun-Pamir Plateau (52.99% vs. 47.01%), as well as in the Arjinshan Nature Reserve (81.57%) and Middle Kunlun Nature Reserve (56.41%). In contrast, HFP was more explanatory in the Pamir Plateau Wetland Nature Reserve (88.89%) and the Taxkorgan Wildlife Nature Reserve (54.55%). Prioritizing the restoration of degraded habitats areas of the Kunlun Pamir Plateau could enhance Cetartiodactyla species richness. These findings provide valuable insights for the biodiversity management and conservation strategies in the mountainous regions.

Projecting LUCC dynamics and ecosystem services in an emerging urban agglomeration under SSP-RCP scenarios and their management implications

Improving our knowledge of future dynamics of ecosystem services (ESs) in the face of climate change and human activities provides a crucial foundation to navigate complex environmental challenges, which are essential to attaining sustainable development particularly in urban regions. However, an existing dearth persists in thoroughly forecasting the intricate interplay of trade-offs and synergies, as well as ecosystem services bundling under distinct future scenarios. This study adopts an integrated research framework to understand the spatiotemporal dynamics of ESs in the Changsha-Zhuzhou-Xiangtan Urban Agglomeration (CZTUA) under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (i.e., SSP126, SSP245 and SSP585). Our future scenarios suggest that the core urban area of CZTUA is projected to expand at the cost of forests and croplands by 2050. Furthermore, human-induced urbanization, particularly the high-intensity LUCC along the Xiangjiang river, significantly impacts ESs, resulting in lower ESs values. The trade-off effects between ESs are primarily observed between WY (water yield) and other ESs. Ecosystem service bundles (ESB) previously dominated by WY have significantly transitioned to CS (carbon storage)-HQ (habitat quality) bundle, especially in the urban core of CZTUA, which serves as an early warning of potential challenges related to water resources. Our study utilizes the latest climate and land use change predictions to evaluate ecosystems in urban agglomerations, and adopts a layered zoning strategy based on ESs, which provides decision-makers with reproducible tools to explore ecosystem changes.

Spatiotemporal variation and GeoDetector analysis of NDVI at the northern foothills of the Yinshan Mountains in Inner Mongolia over the past 40 years

The study of spatiotemporal variation and driving forces of the normalized difference vegetation index (NDVI) is conducive to regional ecosystem protection and natural resource management. Based on the 1982-2022 GIMMS NDVI data and 26 influencing variables, by using the Theil-Sen median slope analysis, Mann-Kendall (M - K) test method and GeoDetector model, we analyzed the spatial and temporal characteristics of vegetation cover and the driving factors of its spatial differentiation in the northern foothills of the Yinshan Mountains in Inner Mongolia. The NDVI showed a significantly increasing trend during 1982-2022, with a growth rate of 0.0091 per decade. It is further predicted that future change in NDVI will continue the 1982-2022 trend, and sustainable improvement will dominate in the future; however, 17.69 % of vegetation will degrade, that is, NDVI will degrade instead of improvement. The spatial distribution of the NDVI in the northern foothills of the study area was generally characterized by high in the east and low in the west. Annual precipitation (Pre), evapotranspiration (Evp), relative humidity (Rhu) and sunshine hours (Ssd) had >70 % explanatory power (73.5, 79.9, 79.0, and 74.9 %, respectively). The explanatory power of edaphic factors was >30 %, whereas anthropogenic and topographic factors had little influence on the spatial variation of NDVI, with an explanatory power of <30 %. Thus, climatic factors were the dominant factors influencing the spatial variability of NDVI in the study area. The results of the interaction detector analysis showed nonlinear strengthening for any two factors, and the interaction between Rhu and barometric pressure had the highest explanatory power. There were optimal ranges or characteristics of each factor that promoted vegetation growth. This study investigated the differences in the explanatory power of different factors on the NDVI and the optimal range of individual factors to promote vegetation growth, which can provide a basis for the development of vegetation resource management programs.

Artificial light at night reveals hotspots and rapid development of industrial activity in the Arctic

Climate warming enables easier access and operation in the Arctic, fostering industrial and urban development. However, there is no comprehensive pan-Arctic overview of industrial and urban development, which is crucial for the planning of sustainable development of the region. In this study, we utilize satellite-derived artificial light at night (ALAN) data to quantify the hotspots and the development of light-emitting human activity across the Arctic from 1992 to 2013. We find that out of 16.4 million km2 analyzed a total area of 839,710 km2 (5.14%) is lit by human activity with an annual increase of 4.8%. The European Arctic and the oil and gas extraction regions in Russia and Alaska are hotspots of ALAN with up to a third of the land area lit, while the Canadian Arctic remains dark to a large extent. On average, only 15% of lit area in the Arctic contains human settlement, indicating that artificial light is largely attributable to industrial human activity. With this study, we provide a standardized approach to spatially assess human industrial activity across the Arctic, independent from economic data. Our results provide a crucial baseline for sustainable development and conservation planning across the highly vulnerable Arctic region.

Unexpected response of terrestrial carbon sink to rural depopulation in China

China is experiencing large-scale rural-urban migration and rapid urbanization, which have had significant impact on terrestrial carbon sink. However, the impact of rural-urban migration and its accompanying urban expansion on the carbon sink is unclear. Based on multisource remote sensing product data for 2000-2020, the soil microbial respiration equation, relative contribution rate, and threshold analysis, we explored the impact of rural depopulation on the carbon sink and its threshold. The results revealed that the proportion of the rural population in China decreased from 63.91 % in 2000 to 36.11 % in 2020. Human pressure decreased by 1.82% in rural depopulation areas, which promoted vegetation restoration in rural areas (+8.45 %) and increased the carbon sink capacity. The net primary productivity (NPP) and net ecosystem productivity (NEP) of the vegetation in the rural areas increased at rates of 2.95 g C m-2 yr-1 and 2.44 g C m-2 yr-1. Strong rural depopulation enhanced the carbon sequestration potential, and the NEP was 1.5 times higher in areas with sharp rural depopulation than in areas with mild rural depopulation. In addition, the rural depopulation was accompanied by urban expansion, and there was a positive correlation between the comprehensive urbanization level (CUL) and NEP in 75.29 % of urban areas. In the urban areas, the vegetation index increased by 88.42 %, and the urban green space partially compensated for the loss of carbon sink caused by urban expansion, with a growth rate of 4.96 g C m-2 yr-1. Changes in rural population have a nonlinear impact on the NEP. When the rural population exceeds 545.686 people/km2, an increase in the rural population will have a positive impact on the NEP. Our research shows that rural depopulation offers a potential opportunity to restore natural ecosystems and thus increase the carbon sequestration capacity.

Habitat Diversity Mitigates the Impacts of Human Pressure on Stream Biodiversity

Recent decades have witnessed substantial changes in freshwater biodiversity worldwide. Although research has shown that freshwater biodiversity can be shaped by changes in habitat diversity and human-induced pressure, the potentials for interaction between these drivers and freshwater biodiversity at large spatial extents remain unclear. To address these issues, we employed a spatially extensive multitrophic fish and insect database from 3323 stream sites across the United States, to investigate the ability of habitat diversity to modulate the effect of human pressure on the richness and abundance of fish and insects. We found evidence that high levels of habitat diversity were associated with increased richness and abundance of fish and insects (including whole-assemblage and individual trophic guilds). We also show that the effects of human pressure on the richness and abundance of fish and insects tend to become positive at high levels of habitat diversity. Where habitat diversity is low, human pressure strongly reduces insect richness and abundance, whereas these reductions are attenuated at high levels of habitat diversity. Structural equation modeling revealed that human pressure reduced habitat diversity, indirectly negatively affecting the richness and abundance of fish and insects. These findings illustrate that, in addition to promoting greater fish and insect biodiversity, habitat diversity may mitigate the deleterious effects of human pressures on these two stream assemblages. Overall, our study suggests that maintaining high levels of habitat diversity is a useful way to protect freshwater biodiversity from ongoing increases in human pressure. However, if human pressures continue to increase, this will reduce habitat diversity, further threatening stream assemblages.

Assessing the impact of human activities on ecosystem asset dynamics in the Yellow River Basin from 2001 to 2020

The intensification of human activities in the Yellow River Basin has significantly altered its ecosystems, challenging the sustainability of the region's ecosystem assets. This study constructs an ecosystem asset index for the period from 2001 to 2020, integrating it with human footprint maps to analyze the temporal and spatial dynamics of ecosystem assets and human activities within the basin, as well as their interrelationships. Our findings reveal significant improvement of ecosystem assets, mainly attributed to the conversion of farmland back into natural habitats, resulting in a 15,994 km2 increase in ecological land use. Notably, 45.88% of the basin has experienced concurrent growth in both human activities and ecosystem assets, with ecosystem assets expanding at a faster rate (22.61%) than human activities (17.25%). Areas with high-quality ecosystem assets are expanding, in contrast to areas with intense human activities, which are facing increased fragmentation. Despite a global escalation in threats from human activities to ecosystem assets, the local threat level within the Yellow River Basin has slightly diminished, indicating a trend towards stabilization. Results highlight the critical importance of integrating spatial and quality considerations into restoration efforts to enhance the overall condition of ecosystem assets, especially under increasing human pressures. Our work assesses the impact of human activities on the dynamics of ecosystem assets in the Yellow River Basin from 2001 to 2020, offering valuable insights for quality development in the region, may provide a scientific basis for general watershed ecological protection and sustainable management in a region heavily influenced by human activity but on a path to recovery.

Comparison of hunting site strategies of the common buzzard Buteo buteo in open landscapes and along expressways

Background

The expansion of human activities in their many forms increases the frequency, diversity, and scale of human-wildlife interactions. One such negative form is the expansion of road infrastructure, causing road kill and traffic-related noise as well as habitat loss and fragmentation. Even so, habitats around road infrastructure are attractive foraging areas that attract certain bird species. We assessed the impact of road infrastructure on the foraging strategies of the common buzzard Buteo buteo.

Methods

Birds were observed during two winter seasons in two land-use types, along an expressway and an open agricultural landscape. Individual birds were tracked for a 10-min sequence as a separate sample was analysed. The material, covering 1,220 min along the expressway, and 1,100 min in the agricultural landscape, was collected.

Results

Time spent by buzzards on medium-height sites was higher along the expressway than in farmland. Buzzards changed their hunting sites following the mean wind speed. Also, they more often changed their sites along the expressway than in farmland. The land-use types, snow cover, and the mean wind speed mediated the number of attacks on prey. These results illustrate the high plasticity of the buzzards' behaviour, which can adapt their hunting strategies to both foraging locations (expressway and farmland) and weather conditions. Roadsides along expressways are attractive foraging areas for this diurnal raptor, so reducing the risk of vehicle collisions with this and other birds of prey may require targeted planning efforts.

Spatiotemporal distribution and transport flux of organophosphate esters in the sediment of the Yangtze River

The Yangtze River Basin is an important area for organophosphate esters (OPEs) consumption and emission. Studies proved high OPE detection in Yangtze River water, but there is limited information about the spatiotemporal distribution and transport flux of OPEs in sediment. The present study investigated 16 OPEs in sediment from upstream to mid-downstream of the Yangtze River. The mean concentration of OPEs was 84.30 ng/g, and alkyl-OPEs was the primary component. Great specific surface area and high content of organic carbon significantly increased OPE concentration in Three Gorges Reservoir (TGR) by physical adsorption and chemical bonds (p < 0.05), making TGR the most contaminated area in mainstream. No significant differences in OPE constituents were found in seasonal distribution. Four potential sources of OPEs were identified by principal component analysis and self-organizing maps, and traffic emissions were the dominant source for OPEs. The hazard quotient model results indicated that aryl-OPEs showed moderate risks in the mainstream of Yangtze River, alkyl-OPEs and Cl-OPEs showed low risks. TGR was a significant sink of OPEs in Yangtze River and buried 7.41 tons of OPEs in 2020, a total of 14.87 tons of OPE were transported into the sea by sediment.