Global land change from 1982 to 2016

Radar vegetation indices for monitoring surface vegetation: Developments, challenges, and trends

Monitoring surface vegetation is essential for environmental protection, disaster prevention, and carbon sequestration in forests. However, optical remote-sensing methods and their derivative technologies typically fail to fully meet this requirement due to constraints such as lighting and weather. Radar vegetation indices (RVIs), developed based on microwave remote-sensing data, describe the dielectric properties and morphological structure of vegetation and have been applied for vegetation monitoring at various scales. This technical review is the first to systematically summarize RVIs; it analyzes and discusses their principles, developments, categories and applications, and provides a comprehensive guide for their use. Additionally, the challenges faced by RVIs, as well as their applicability, were analyzed, and future improvements and development trends were carefully projected. The selection of RVIs must consider the type of data used, the terrain and location of the study area, and the major vegetation types. The effectiveness of RVIs applied to vegetation monitoring can be affected by various factors, including index performance, sensor type, study area, and data type and quality. These factors reduce the reliability and robustness of results, as well as guide the improvement direction of RVIs. The development of technologies, such as artificial intelligence, in remote sensing offers new possibilities for RVIs, enabling the removal of background scattering, improvement in interpretation accuracy, and reduction in application thresholds. Additionally, the development trends in high resolution, multi-polarization, multi-base, multi-dimensional, and networked synthetic aperture radar (SAR) and their satellite platforms offer data support for the next generation of RVIs. The rapid development of RVIs strongly supports the use of surface vegetation monitoring and terrestrial ecosystem research.

Spatial variation of anthropogenic disturbances within watersheds determines dissolved organic matter composition exported to oceans

Global land-use changes alter the delivery of fluvial dissolved organic matter (DOM) along land-to-sea continuum. To study how spatial variations in watershed anthropogenic disturbances control chemodiversity and reactivity of DOM exported to oceans, we used fluorescent and ultra-high-resolution mass spectrometry to investigate spatial and seasonal variations of DOM properties along two subtropical coastal rivers with contrasting anthropogenic land-use distributions (North and West tributaries of Jiulong River, southeast China). Dissolved organic carbon (DOC) concentration and humic- and protein-like fluorescent DOM (FDOM) intensities were high in the mixed urban-agricultural impacted upper North River and lower West River. DOM molecular signatures suggested that the urban-sourced DOM is dominated by bio-labile, S-rich compounds, whereas the agricultural-sourced DOM is characterized by a mixture of bio-labile CHONS and bio-refractory CHON. This anthropogenic-induced spatial variation in DOM signatures was especially prominent during the dry season. Molecular analysis indicated that heteroatomic-containing (phosphorus-sulfur-nitrogen) DOM compounds are more biologically degradable, whereas most of the heteroatom-depleted and highly unsaturated CHO was stable during transport. Due to a longer transit distance and reservoir impoundment in North River, the urban-sourced aliphatic compounds were largely microbially removed or transformed into bio-refractory components, resulting in lower DOC fluxes and an increase of recalcitrance in the DOM exported to the ocean. Conversely, shorter transit times for anthropogenic inputs from the middle/lower West River increased watershed yield and export fluxes of DOC with higher bio-lability. Our study documents that transit history plays a crucial role in assessing the fate of anthropogenic DOM along the land-to-ocean continuum.

Deforestation-induced runoff changes dominated by forest-climate feedbacks

Large-scale deforestation alters water availability through its direct effect on runoff generation and indirect effect through forest-climate feedbacks. However, these direct and indirect effects and their spatial variations are difficult to separate and poorly understood. Here, we develop an attribution framework that combines the Budyko theory and deforestation experiments with climate models, showing that widespread runoff reductions caused by the indirect effect of forest-climate feedbacks can largely offset the direct effect of reduced forest cover on runoff increases. The indirect effect dominates the hydrological responses to deforestation over 63% of deforested areas worldwide. This indirect effect arises from deforestation-induced reductions in precipitation and potential evapotranspiration, which decrease and increase runoff, respectively, leading to complex patterns of runoff responses. Our findings underscore the importance of forest-climate feedbacks for improved understanding and prediction of climate and hydrological changes caused by deforestation, with profound implications for sustainable management of forests and water resources.

Effects of landscape changes on water quality: A global meta-analysis

Landscape changes resulting from anthropogenic activities and climate changes severely impact surface water quality. A global perspective on understanding their relationship is a prerequisite for pursuing equity in water security and sustainable development. A sequent meta-analysis synthesizing 625 regional studies from 63 countries worldwide was conducted to analyze the impacts on water quality from changing landscape compositions in the catchment and explore the moderating factors and temporal evolution. Results exhibit that total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) in water are mostly concerned and highly responsive to landscape changes. Expansion of urban lands fundamentally degraded worldwide water quality over the past 20 years, of which the arid areas tended to suffer more harsh deterioration. Increasing forest cover, particularly low-latitude forests, significantly decreased the risk of water pollution, especially biological and heavy metal contamination, suggesting the importance of forest restoration in global urbanization. The effect size of agricultural land changes on water quality was spatially scale-dependent, decreasing and then increasing with the buffer radius expanding. Wetland coverage positively correlated with organic matter in water typified by COD, and the correlation coefficient peaked in the boreal areas (r=0.82, p<0.01). Overall, the global impacts of landscape changes on water quality have been intensifying since the 1990s. Nevertheless, knowledge gaps still exist in developing areas, especially in Africa and South America, where the water quality is sensitive to landscape changes and is expected to experience dramatic shifts in foreseeable future development. Our study revealed the worldwide consistency and heterogeneity between regions, thus serving as a research roadmap to address the quality-induced global water scarcity under landscape changes and to direct the management of land and water.

Rethinking ecological niches and geographic distributions in face of pervasive human influence in the Anthropocene

Species are distributed in predictable ways in geographic spaces. The three principal factors that determine geographic distributions of species are biotic interactions (B), abiotic conditions (A), and dispersal ability or mobility (M). A species is expected to be present in areas that are accessible to it and that contain suitable sets of abiotic and biotic conditions for it to persist. A species' probability of presence can be quantified as a combination of responses to B, A, and M via ecological niche modeling (ENM; also frequently referred to as species distribution modeling or SDM). This analytical approach has been used broadly in ecology and biogeography, as well as in conservation planning and decision-making, but commonly in the context of 'natural' settings. However, it is increasingly recognized that human impacts, including changes in climate, land cover, and ecosystem function, greatly influence species' geographic ranges. In this light, historical distinctions between natural and anthropogenic factors have become blurred, and a coupled human-natural landscape is recognized as the new norm. Therefore, B, A, and M (BAM) factors need to be reconsidered to understand and quantify species' distributions in a world with a pervasive signature of human impacts. Here, we present a framework, termed human-influenced BAM (Hi-BAM, for distributional ecology that (i) conceptualizes human impacts in the form of six drivers, and (ii) synthesizes previous studies to show how each driver modifies the natural BAM and species' distributions. Given the importance and prevalence of human impacts on species distributions globally, we also discuss implications of this framework for ENM/SDM methods, and explore strategies by which to incorporate increasing human impacts in the methodology. Human impacts are redefining biogeographic patterns; as such, future studies should incorporate signals of human impacts integrally in modeling and forecasting species' distributions.

Responses of precipitation and water vapor budget on the Chinese Loess Plateau to global land cover change forcing

There have been notable changes in precipitation patterns on the Loess Plateau (LP) of China in recent decades, and numerous attribution studies have focused on sea surface temperature anomalies and atmospheric circulation changes induced by aerosols and greenhouse gases emission. However, the influences of global land use and land cover change (LULCC) as an important forcing factor in the climate system on regional precipitation remains poorly understood. In this study, we quantified the impacts of LULCC on precipitation and the water vapor budget in the LP region, utilizing data from LULCC forcing experiments conducted by the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Although global LULCC forcing exerted a negative effect on long-term mean precipitation on the LP region from 1850 to 2014, the different response characteristics were detected during different time periods. The global LULCC caused a decrease of 14 mm in annual precipitation during the period of 1850-1960. Conversely, from 1961 to 2014, it led to an increase of 6.4 mm, which is largely attributed to the enhanced water vapor transport along the southern boundary and westerly belt of the LP region. Moreover, from the perspective of the net water vapor balance of the entire LP, although LULCC caused net water vapor export during both periods 1850-1960 and 1961-2014, the export during the latter period (0.20 × 104 kg s-1) was smaller than that during the former period (0.28 × 104 kg s-1), indicating that the global expansion of grassland and cropland, along with the continuous rise in the leaf area index from 1961 to 2014, contributed to retaining more water vapor within the LP, which in turn was more favorable for precipitation. These findings provide valuable insights into the reasons behind precipitation variations in the LP region, emphasizing that global vegetation restoration and greening play a significant role in improving precipitation in ecologically fragile areas.

Effects of climate change and human activities on vector-borne diseases

Vector-borne diseases are transmitted by haematophagous arthropods (for example, mosquitoes, ticks and sandflies) to humans and wild and domestic animals, with the largest burden on global public health disproportionately affecting people in tropical and subtropical areas. Because vectors are ectothermic, climate and weather alterations (for example, temperature, rainfall and humidity) can affect their reproduction, survival, geographic distribution and, consequently, ability to transmit pathogens. However, the effects of climate change on vector-borne diseases can be multifaceted and complex, sometimes with ambiguous consequences. In this Review, we discuss the potential effects of climate change, weather and other anthropogenic factors, including land use, human mobility and behaviour, as possible contributors to the redistribution of vectors and spread of vector-borne diseases worldwide.

Global evaluation of current and future threats to drylands and their vertebrate biodiversity

Drylands are often overlooked in broad conservation frameworks and development priorities and face increasing threats from human activities. Here we evaluated the formal degree of protection of global drylands, their land vertebrate biodiversity and current threats, and projected human-induced land-use changes to drylands under different future climate change and socioeconomic scenarios. Overall, drylands have lower protected-area coverage (12%) compared to non-drylands (21%). Consequently, most dryland vertebrates including many endemic and narrow-ranging species are inadequately protected (0-2% range coverage). Dryland vertebrates are threatened by varied anthropogenic factors-including agricultural and infrastructure development (that is, artificial structures, surfaces, roads and industrial sites). Alarmingly, by 2100 drylands are projected to experience some degree of land conversion in 95-100% of their current natural habitat due to urban, agricultural and alternative energy expansion. This loss of undisturbed dryland regions is expected across different socioeconomic pathways, even under optimistic scenarios characterized by progressive climate policies and moderate socioeconomic trends.

Impacts of urbanization on ecosystem carbon cycle: a case study of land use change in Tianjin metropolitan area

For the sustainable development of the city, in a study of Tianjin's rapid urbanization, we explore the complex interplay between land use change and the ecosystem carbon cycle from 2000 to 2020. Spatial analysis and profit-loss matrix calculations reveal contrasting ecological impacts: expansion of woodlands and grasslands enhances Net Primary Productivity (NPP) and reduces carbon emissions, while urban construction shows the opposite effect. Over 20 years, Tianjin's urban transformation led to a 16.91 GgC decline in NPP amidst a construction boom. However, post-2015 ecological policy shifts resulted in a significant net carbon uptake of 0.85 Gt, demonstrating the potential of policy interventions in mitigating environmental impacts of urbanization. This study underscores the importance of sustainable urban planning and ecological conservation strategies in highly urbanized settings.

Is the boom in staple crop production attributed to expanded cropland or improved yield? A comparative analysis between China and India

The characteristics of cropland development and the dynamics of food production in China and India, the world's largest agricultural and most populous countries, are of great importance to global food security. However, there is a notable lack of a thorough comparison between China and India in this regard. Here, we systematically compare the differences between China and India using cropping intensity and crop production data, including cropland area, harvested area, total staple crop (i.e., cereal crops, tuber crops and pulse crops) production and yield capacity. The results are mainly as follows: (1) Both China and India experienced an increasing trend in cropland area and harvested area from 2001 to 2021, especially notable in India. In China, the cropland area and harvested area increased by 11.76 % and 14.36 %, respectively, while in India, they witnessed a more substantial increase of 31.10 % and 49.32 %, respectively. (2) The cropping intensity underwent significant transformations, primarily shifting between non-cropland, single-cropping, and double-cropping. Northwestern China exhibited a clear trend of non-cropland converting to single-cropping, whereas northeastern China showed a distinct pattern of single-cropping changing to non-cropland. The interconversion between single-cropping and double-cropping was also frequently observed in the main food-producing regions. In India, the cropland expansion and the adoption of double-cropping are highly pronounced, extending widely across most of the country. (3) From 2001 to 2021, the total staple crop production in China and India increased by 34.12 % and 55.81 %, respectively. Despite the rapid growth in India's total staple crop production, it still amounts to only about half of China's. The major crops production also showed different trends, China's cereal crops production increased significantly, while tuber and pulse crops production declined, and India's production of cereal, tuber, and pulse crops has all increased (4) China's yield capacity has increased by 17.28 %, while India's has only grown by 4.35 %. Despite the rapid increase in India's total staple crop production, the yield gap with China has widened. The boost in China's total staple crop production mainly resulted from improved yield capacity, whereas India relied more on the cropland area expansion, especially the increase in harvested area. Our comprehensive comparison of China and India in cropland development and staple crop production contributes to a deep understanding of the differences in agricultural production between the two countries, and provides lessons for global food security and sustainable agricultural development.

Relative decline in density of Northern Hemisphere tree species in warm and arid regions of their climate niches

Although climate change is expected to drive tree species toward colder and wetter regions of their distribution, broadscale empirical evidence is lacking. One possibility is that past and present human activities in forests obscure or alter the effects of climate. Here, using data from more than two million monitored trees from 73 widely distributed species, we quantify changes in tree species density within their climatic niches across Northern Hemisphere forests. We observe a reduction in mean density across species, coupled with a tendency toward increasing tree size. However, the direction and magnitude of changes in density exhibit considerable variability between species, influenced by stand development that results from previous stand-level disturbances. Remarkably, when accounting for stand development, our findings show a significant change in density toward cold and wet climatic conditions for 43% of the species, compared to only 14% of species significantly changing their density toward warm and arid conditions in both early- and late-development stands. The observed changes in climate-driven density showed no clear association with species traits related to drought tolerance, recruitment and dispersal capacity, or resource use, nor with the temperature or aridity affiliation of the species, leaving the underlying mechanism uncertain. Forest conservation policies and associated management strategies might want to consider anticipated long-term species range shifts alongside the integration of contemporary within-distribution density changes.

Land use/cover drive functional patterns of bacterial communities in sediments of a subtropical river, China

The bacterial community in sediment serves as an important indicator for assessing the environmental health of river ecosystems. However, the response of bacterial community structure and function in river basin sediment to different land use/cover changes has not been widely studied. To characterize changes in the structure, composition, and function of bacterial communities under different types of land use/cover, we studied the bacterial communities and physicochemical properties of the surface sediments of rivers. Surface sediment in cropland and built-up areas was moderately polluted with cadmium and had high nitrogen and phosphorus levels, which disrupted the stability of bacterial communities. Significant differences in the α-diversity of bacterial communities were observed among different types of land use/cover. Bacterial α-diversity and energy sources were greater in woodlands than in cropland and built-up areas. The functional patterns of bacterial communities were shown that phosphorus levels and abundances of pathogenic bacteria and parasites were higher in cropland than in the other land use/cover types; Urban activities have resulted in the loss of the denitrification function and the accumulation of nitrogen in built-up areas, and bacteria in forested and agricultural areas play an important role in nitrogen degradation. Differences in heavy metal and nutrient inputs driven by land use/cover result in variation in the composition, structure, and function of bacterial communities.

Forest-to-Cropland Conversion Reshapes Microbial Hierarchical Interactions and Degrades Ecosystem Multifunctionality at a National Scale

Conversion from natural lands to cropland, primarily driven by agricultural expansion, could significantly alter soil microbiome worldwide; however, influences of forest-to-cropland conversion on microbial hierarchical interactions and ecosystem multifunctionality have not been fully understood. Here, we examined the effects of forest-to-cropland conversion on intratrophic and cross-trophic microbial interactions and soil ecosystem multifunctionality and further disclosed their underlying drivers at a national scale, using Illumina sequencing combined with high-throughput quantitative PCR techniques. The forest-to-cropland conversion significantly changed the structure of soil microbiome (including prokaryotic, fungal, and protistan communities) while it did not affect its alpha diversity. Both intrakingdom and interkingdom microbial networks revealed that the intratrophic and cross-trophic microbial interaction patterns generally tended to be more modular to resist environmental disturbance introduced from forest-to-cropland conversion, but this was insufficient for the cross-trophic interactions to maintain stability; hence, the protistan predation behaviors were still disturbed under such conversion. Moreover, key soil microbial clusters were declined during the forest-to-cropland conversion mainly because of the increased soil total phosphorus level, and this drove a great degradation of the ecosystem multifunctionality (by 207%) in cropland soils. Overall, these findings comprehensively implied the negative effects of forest-to-cropland conversion on the agroecosystem, from microbial hierarchical interactions to ecosystem multifunctionality.

Rubber plantations are impermeable to an avian understory specialist in Sri Lanka

BACKGROUND

Understanding how landscape characteristics affect animal movement is essential for conservation in human-dominated habitats. A fundamental question is how monoculture agroforests, including rubber and tea plantations, affect wildlife and its movement. Experimental translocations represent an important technique to assess animals' habitat selection while moving through agricultural matrices, especially when complemented with observations of birds' natural movements, and with "control" translocations, in which birds are moved within their natural habitat such as forest. Yet, experimental translocations have been little used for birds outside the Western Hemisphere.

METHODS

We conducted experimental translocations and home-range measurements on an understory forest specialist, Brown-capped Babbler (BCBA, Pellorneum fuscocapillus), and a forest generalist, Tickell's Blue Flycatcher (TBFL, Cyornis tickelliae). These species were studied in three rubber plantations, which also included some open areas mostly planted with tea, and in three forest reserves of Sri Lanka.

RESULTS

Four of the five BCBAs translocated within disturbed habitats (rubber plantations) could not return to their capture locations. However, all four individuals within undisturbed habitats (forest reserves) successfully returned to their point of origin within 10.5 daytime hours. In contrast, all TBFLs returned to their capture locations in both disturbed (n = 7) and undisturbed habitats (n = 3) within 11.3 daytime hours. A Cox-proportional survival model demonstrated that the percentage of rubber cover decreased return time, similar to the effect of open-area cover. The home range surveys (n = 13 for BCBA, n = 10 for TBFL) revealed that very little of the birds' natural home-ranges was covered by rubber (0.2% for BCBA, 13.1% for TBFL at 50% Kernel Density Estimates KDE). Home range size for BCBA was approximately half the size in disturbed habitats compared to undisturbed ones, although there was no significant difference between habitats for TBFL.

CONCLUSIONS

We conclude that rubber plantations can be impermeable to understory habitat specialist birds, and even generalist species may avoid them long-term. Our findings highlight the potential utility of strips of native vegetation, particularly those featuring understory layers, as corridors to facilitate the movement of forest specialists in landscapes dominated by rubber plantations and other types of disturbed habitats.

Global critical soil moisture thresholds of plant water stress

During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

The socioecological benefits and consequences of oil palm cultivation in its native range: The Sustainable Oil Palm in West Africa (SOPWA) Project

Agriculture is expanding rapidly across the tropics. While cultivation can boost socioeconomic conditions and food security, it also threatens native ecosystems. Oil palm (Elaeis guineensis), which is grown pantropically, is the most productive vegetable oil crop worldwide. The impacts of oil palm cultivation have been studied extensively in Southeast Asia and - to a lesser extent - in Latin America but, in comparison, very little is known about its impacts in Africa: oil palm's native range, and where cultivation is expanding rapidly. In this paper, we introduce a large-scale research programme - the Sustainable Oil Palm in West Africa (SOPWA) Project - that is evaluating the relative ecological impacts of oil palm cultivation under traditional (i.e., by local people) and industrial (i.e., by a large-scale corporation) management in Liberia. Our paper is twofold in focus. First, we use systematic mapping to appraise the literature on oil palm research in an African context, assessing the geographic and disciplinary focus of existing research. We found 757 publications occurring in 36 African countries. Studies tended to focus on the impacts of palm oil consumption on human health and wellbeing. We found no research that has evaluated the whole-ecosystem (i.e., multiple taxa and ecosystem functions) impacts of oil palm cultivation in Africa, a knowledge gap which the SOPWA Project directly addresses. Second, we describe the SOPWA Project's study design and-using canopy cover, ground vegetation cover, and soil temperature data as a case study-demonstrate its utility for assessing differences between areas of rainforest and oil palm agriculture. We outline the socioecological data collected by the SOPWA Project to date and describe the potential for future research, to encourage new collaborations and additional similar projects of its kind in West Africa. Increased research in Africa is needed urgently to understand the combined ecological and sociocultural impacts of oil palm and other agriculture in this unique region. This will help to ensure long-term sustainability of the oil palm industry-and, indeed, all tropical agricultural activity-in Africa.

Evolution of rates, patterns, and driving forces of green eco-spaces in a subtropical hilly region

Monitoring ecological resource change in mountainous and hilly areas (MHAs) is vital for theoretical and practical advancements of ecological resource utilization and management in complex ecosystems. The factors driving structural and functional changes in green eco-spaces (GES) in these areas are complex and uncertain, with notable spatial scale effects. However, analyzing the multi-scale driving mechanisms of ecological and socioeconomic factors at a fine spatiotemporal scale presents significant challenges. To address these challenges, we analyzed dynamic changes in GES and eco-socio-economic development in Shanghang County, a typical mountainous region in southern China. We used multiple linear regression and multi-scale geographically weighted regression model to identify key factors driving GES changes and their multi-scale effects at both global and local levels. Over the past two decades, the GES area in the study area has exhibited a consistent pattern of decline, characterized by phases of gradual decline (2000-2005), sharp decline (2005-2009), slow decline (2009-2019). Key global factors driving GES changes included elevation (ELE), slope (SLOPE), population density (PD), distance to settlements (SETTLE), and distance to administrative centers (ADMIN). These factors exhibited significant spatial heterogeneity and multi-scale effects on GES changes. Specifically, SETTLE, PD, SLOPE, and ELE consistently drove GES changes at the local level, while ADMIN only showed significant localized effects during 2005-2009. The synergy between SETTLE and SLOPE had a considerable impact on GES changes, increasing over time, whereas ELE and PD demonstrated a consistent trade-off effect. These findings provide detailed spatiotemporal insights into the driving mechanisms of natural ecological resources, offering crucial guidance for environmental management, land source management, regional economic development, and biodiversity conservation in Shanghang and analogous subtropical hilly regions worldwide.

Restoring ecological complexity in a changing environment

As land use leaves massive tracts of land vacant for recovery, restoration must undergo a substantial shift to incorporate a complexity perspective beyond the traditional community, biodiversity or functional views. With an interaction-function perspective, we may be able to achieve ecosystems with better chances to adapt to current environmental changes and, especially, to climate change. We explore combined approaches that include still unused and underexplored techniques that will soon go mainstream and produce massive amounts of information to address the complexity gap. As we understand how complexity reassembles after the end of agriculture, we will be able to design actions to restore or enhance it at unprecedented spatial scales while increasing its adaptability to environmental changes.

Canopy coverage, light, and moisture affect thermoregulatory trade-offs in an amphibian breeding habitat

When amphibians thermoregulate, they face a fundamental trade-off between the ability to maintain activity and an increased rate of dehydration at higher temperatures. Canopy coverage affects both the thermal and hydric conditions of the environment and can therefore influence amphibian thermoregulation. Frogs require proper conditions to thermoregulate to successfully grow, survive, and reproduce. But while we know how canopy and environmental variables typically affect operative temperature, less is known about effects on amphibian water loss rates. In this study, we measure the effect of canopy coverage on the conditions available for thermoregulation at a breeding pond of the California red-legged frog, Rana draytonii. We use agar frog models to estimate the thermal and hydric capacities frogs would experience in locations with different canopy coverage and microhabitats. At each site, we deployed models under four microhabitat treatments: wet/sun, wet/shade, dry/sun, and dry/shade. We modeled how environmental variables affected operative temperature and evaporative water loss from agar frogs. We found positive effects of air temperature, the sun treatment, and reduced canopy cover on operative temperature, and negative direct or indirect effects of these variables on evaporative water loss, consistent with the hypothesized trade-off between thermoregulatory behavior to increase temperature and the increased desiccation risk due to higher water loss. Additionally, our results indicate that the availability of wet microhabitats can allow frogs to reduce water loss, potentially mitigating the risk of desiccation when thermoregulating to achieve higher operative temperatures. Our findings suggest, that with access to proper microhabitats, amphibians can mitigate the fundamental trade-off and receive benefits of thermoregulating at high temperatures.

Soil organic carbon and nutrient characteristics of Anogeissus groves in old Opara forest reserve, Nigeria

Forest-savanna transition zones of West Africa are uniquely characterized by forest groves, forest patches, or forest islands, the importance of which for sustainable resource management and their potential for carbon sequestration and nutrient cycling is often underrated. Our study conducted a comparative analysis of the soil organic carbon and nutrient characteristics of the Anogeissus groves in the old Opara forest reserve and their adjoining arable lands. We established 30 sampling frames of 100 m × 100 m plots with 15 frames per land use type. For each sampling frame, six observation points were randomly selected, and composite soil samples were collected at soil depths of 0-20 cm and 20-50 cm per observation point. Our results showed Anogeissus groves and their adjoining arable lands to exist on similar landscapes while the groves have enriched soil morphological characteristics (e.g., soil color), higher soil organic carbon (SOC), and better nutrient characteristics. There were strong positive relationships between SOC, effective cation exchange capacity, total nitrogen, calcium, magnesium and calcium, zinc, electrical conductivity, and copper. The significant soil organic matter accumulation in the groves accounts for the overall improved soil characteristics over the adjoining arable lands. Preserving the groves and similar African ecosystems may be important in climate regulation, resources and biodiversity conservation, and ethnopharmacology for rural communities. Thus, a question arises: should more land be set aside for ecological conservation or for agricultural productivity?

Anthropogenic climate and land-use change drive short- and long-term biodiversity shifts across taxa

Climate change and habitat loss present serious threats to nature. Yet, due to a lack of historical land-use data, the potential for land-use change and baseline land-use conditions to interact with a changing climate to affect biodiversity remains largely unknown. Here, we use historical land use, climate data and species observation data to investigate the patterns and causes of biodiversity change in Great Britain. We show that anthropogenic climate change and land conversion have broadly led to increased richness, biotic homogenization and warmer-adapted communities of British birds, butterflies and plants over the long term (50+ years) and short term (20 years). Biodiversity change was found to be largely determined by baseline environmental conditions of land use and climate, especially over shorter timescales, suggesting that biodiversity change in recent periods could reflect an inertia derived from past environmental changes. Climate-land-use interactions were mostly related to long-term change in species richness and beta diversity across taxa. Semi-natural grasslands (in a broad sense, including meadows, pastures, lowland and upland heathlands and open wetlands) were associated with lower rates of biodiversity change, while their contribution to national-level biodiversity doubled over the long term. Our findings highlight the need to protect and restore natural and semi-natural habitats, alongside a fuller consideration of individual species' requirements beyond simple measures of species richness in biodiversity management and policy.

Impact of aridity rise and arid lands expansion on carbon-storing capacity, biodiversity loss, and ecosystem services

Drylands, comprising semi-arid, arid, and hyperarid regions, cover approximately 41% of the Earth's land surface and have expanded considerably in recent decades. Even under more optimistic scenarios, such as limiting global temperature rise to 1.5°C by 2100, semi-arid lands may increase by up to 38%. This study provides an overview of the state-of-the-art regarding changing aridity in arid regions, with a specific focus on its effects on the accumulation and availability of carbon (C), nitrogen (N), and phosphorus (P) in plant-soil systems. Additionally, we summarized the impacts of rising aridity on biodiversity, service provisioning, and feedback effects on climate change across scales. The expansion of arid ecosystems is linked to a decline in C and nutrient stocks, plant community biomass and diversity, thereby diminishing the capacity for recovery and maintaining adequate water-use efficiency by plants and microbes. Prolonged drought led to a -3.3% reduction in soil organic carbon (SOC) content (based on 148 drought-manipulation studies), a -8.7% decrease in plant litter input, a -13.0% decline in absolute litter decomposition, and a -5.7% decrease in litter decomposition rate. Moreover, a substantial positive feedback loop with global warming exists, primarily due to increased albedo. The loss of critical ecosystem services, including food production capacity and water resources, poses a severe challenge to the inhabitants of these regions. Increased aridity reduces SOC, nutrient, and water content. Aridity expansion and intensification exacerbate socio-economic disparities between economically rich and least developed countries, with significant opportunities for improvement through substantial investments in infrastructure and technology. By 2100, half the world's landmass may become dryland, characterized by severe conditions marked by limited C, N, and P resources, water scarcity, and substantial loss of native species biodiversity. These conditions pose formidable challenges for maintaining essential services, impacting human well-being and raising complex global and regional socio-political challenges.

Recolonization of secondary forests by a locally extinct Caribbean anole through the lens of range expansion theory

Disturbance and recovery dynamics are characteristic features of many ecosystems. Disturbance dynamics are widely studied in ecology and conservation biology. Still, we know less about the ecological processes that drive ecosystem recovery. The ecological processes that mediate ecosystem recovery stand at the intersection of many theoretical frameworks. Range expansion theory is one of these complementary frameworks that can provide unique insights into the population-level processes that mediate ecosystem recovery, particularly fauna recolonization. Although the biodiversity patterns that follow the fauna recolonization of recovering forests have been well described in the literature, the ecological processes at the population level that drive these patterns remain conspicuously unknown. In this study, we tested three fundamental predictions of range expansion theory during the recolonization of recovering forests in Puerto Rico by a shade specialist anole, Anolis gundlachi. Range expansion theory predicts that individuals at the early stages of recolonization (i.e., younger forests) would have a high prevalence of dispersive traits, experience less density dependence, and suffer less parasitism. To test these predictions, we conducted a chronosequence study applying space-for-time substitution where we compared phenotypic traits (i.e., body size, body condition, and relative limb size), population density, population growth rates, and Plasmodium parasitism rates among lizard populations living in young (<30 years), mid (~40-70 years), and old-growth forests (>75 years). Lizard populations in younger forests had lower densities, higher population growth rates, and lower rates of Plasmodium parasitism compared with old-growth forests. Still, while we found that individuals had larger body sizes, and longer forelimbs in young forests in one site, this result was not consistent among sites. This suggests a potential trade-off between the traits that provide a dispersal advantage during the initial stages of recolonization and those that are advantageous to establish in novel environmental conditions. Overall, our study emphasizes the suitability of range expansion theory to describe fauna recolonization but also highlights that the ecological processes that drive recolonization are time-dependent, complex, and nuanced.

Assessment of land use/ land cover change derived catchment hydrologic response: An integrated parsimonious hydrological modeling and alteration analysis based approach

Land use/land cover (LULC) change, often a consequence of natural or anthropogenic drivers, plays a decisive role in governing global catchment dynamics, and subsequent impact on regional hydrology. Insight into the complex relationship between the drivers of LULC change and catchment hydrology is of utmost importance to decision makers. Contemplating the dynamic rainfall-runoff response of the Indian catchments, this study proposes an integrated modeling-based approach to identify the drivers and relative contribution to catchment hydrology. The proposed approach was evaluated in the tropical climate Nagavali River Basin (NRB) (9512 km2) of India. The Soil and Water Assessment Tool (SWAT) hydrological model, which uses daily-scale rainfall, temperature, wind speed, relative humidity, solar radiation, and streamflow information was integrated with the Indicators of Hydrologic Alteration (IHA) technique to characterize the plausible changes in the flow regime of the NRB. Subsequently, the Partial Least Squares Regression (PLSR) based modeling analysis was performed to quantify the relative contribution of individual LULC components on the catchment water balance. The outcomes of the study revealed that forest land has been significantly converted to agricultural land (45-59%) across the NRB resulting in mean annual streamflow increase of 3.57 m3/s during the monsoon season. The affinity between land use class and streamflow revealed that barren land (CN = 83-87) exhibits the maximum positive response to streamflow followed by the built-up land (CN = 89-91) and fallow land (CN = 88-93). The period 1985-1995 experienced an increased ET scenario (911-1050 mm), while the recent period (2005-2020) experienced reduced ET scenario owing to conversion of forest to agricultural land. Certainly, the study endorses adopting the developed methodology for understanding the complex land use and catchment-scale hydrologic interactions across global-scales for early watershed management planning.

Telecoupling between urban expansion and forest ecosystem service loss through cultivated land displacement: A case study of Zhejiang Province, China

Urbanization can either directly occupy forests or indirectly lead to forest loss elsewhere through cultivated land displacement, resulting in further forest fragmentation and ecosystem service (ES) loss. However, the effects of urban expansion on forest area and ESs are unknown, and this is especially true for indirect effects. Taking Zhejiang Province, China, a typical deforested province, as an example, this study quantified the direct and indirect effects of urban expansion on forest area and five ESs (timber yield, water yield, carbon sequestration, soil conservation, and biodiversity) from 2000 to 2020, explored the relationship between forest structure (forest proportion, mean patch area, edge density, and mean euclidean nearest neighbor distance) change and ESs, and revealed the telecoupling of urban expansion and forest loss and cascade effects among urbanization, deforestation, forest structure, and ESs. The results indicated that the indirect forest loss (4.30%-6.15%) caused by cultivated land displacement due to urban expansion was larger than the direct forest loss (2.42%). Urban expansion has a greater negative impact on carbon sequestration (6.40%-8.20%), water yield (6.08%-7.78%), and biodiversity (5.79%-7.44%) than on timber yield (4.77%-6.17%) and soil conservation (4.43%-5.77%). The indirect forest ES loss was approximately 2.83-4.34 times greater than the direct forest ES loss. Most forest ESs showed a nonlinear significant positive correlation with changes in forest proportion and mean patch area and a significant nonlinear negative correlation with changes in edge density and mean Euclidean nearest neighbor distance (p < 0.05). There is telecoupling between urban expansion in one region and forest ES loss in other distant regions. This study contributes to guiding sustainable forest conservation and management globally.

Land degradation neutrality assessment and factors influencing it in China's arid and semiarid regions

The ecosystems in China's arid and semiarid regions are notably fragile and experiencing dramatic land degradation. At the 12th Conference of the Parties (COP12) to the United Nations Convention to Combat Desertification (UNCCD) in October 2015, a definition for land degradation neutrality (LDN) was proposed and subsequently integrated into the Sustainable Development Goals (SDGs). Research on LDN has developed in terms of conceptual framework constructions, quantitative assessments, and empirical studies. However, LDN and its drivers must be clarified in China's arid and semiarid regions since some representative processes have yet to be fully considered in the assessment. Here, we develop an LDN indicator system specialised for the area, assess their LDN status, and determine the impacts of human activities and climate change on LDN. Our research aims to refine the LDN indicator system tailored for China's arid and semiarid regions by incorporating the trends of wind and water erosion. We also identify the influence of human activity and climate change on LDN, which provides insightful strategies for ecological restoration and sustainable development in drylands with climate-sensitive ecosystems. The results show that: (1) In 2020, more than half of areas of China's arid and semiarid regions achieved LDN, with more pronounced success in the southeastern areas compared to the central regions. (2) For LDN drivers, elevation shows negligible influence on LDN, whereas increased temperature promotes LDN achievement. Conversely, factors like vapour pressure deficit and v-direction wind speed hinder it. In conclusion, China's arid and semiarid regions achieved LDN, and the dominant factor that substantially influences LDN varies across geographical zones, with higher wind speeds and elevated GDP levels generally obstructing LDN in most areas.

The large-scale expansion of rubber plantations in southern India: major impacts and the changing nature of drivers

This study investigates the major environmental and socio-economic impacts of an increase in the area of rubber plantations and the changing patterns of drivers of land use changes. Using a combination of geospatial techniques and socio-economic methods, we mainly analyzed the rate of increase in area under rubber plantations, the major impacts of land use changes, and the changing drivers of land use changes. Our results show that the area under rubber plantations has increased significantly within the study area, with the area under rubber plantations increasing from 30 to 74% of the total area within five decades. Impact assessment of land use changes based on household surveys showed significant improvement in the socio-economic conditions of the farmers, however, at the expense of severe environmental degradation. Our results also indicate that while areas under rubber plantations continue to increase, the drivers of land use changes have changed over time. Furthermore, it has been observed that in the past, many interventions prioritized social and economic development and placed less emphasis on the ecological stability of the region. Perceptions of farmers revealed that the effects of ecological fragility already affected the economic robustness of the whole area. Therefore, we conclude that government interventions to support additional rubber cultivation should also focus on ecosystem stabilization in order to minimize the risk of an ecological catastrophe that would significantly affect the economic prosperity of the region.

The success of ecological engineering projects on vegetation restoration in China strongly depends on climatic conditions

China has implemented extensive ecological engineering projects (EEPs) during recent decades to restore and enhance ecosystem functioning. However, the effectiveness of these interventions can vary due to factors such as local climate and specific project objectives. Here, we used two independent satellite remote sensing datasets, including the Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI) and vegetation optical depth from Ku-band (Ku-VOD), to investigate the vegetation trends in two hotspot regions of EEPs characterized by different climate conditions, i.e., the xeric/semi-xeric Loess Plateau and mesic southwest China. We found diverging vegetation greenness/biomass trend shift patterns in these two regions as a result of the combined effects of EEPs and climate variations, as indicated by changes in the Standardized Precipitation Evapotranspiration Index (SPEI). In the Loess Plateau, where no significant climate variations were observed, NDVI/Ku-VOD increased continuously after the implementation of key EEPs in 2000. Conversely, southwest China has experienced persistent drying since 2000, and vegetation greenness/biomass showed an increasing trend during the initial stages of ecological engineering implementation but subsequently reversed towards a decline due to the continued dry climatic conditions. We used the residual trend method to separate the influence of EEPs from climate variations on vegetation trends and found a positive effect of the ecological management practices in the Loess Plateau, yet a predominantly negative effect in the southwest China region, which means that projects implemented in southwest China did not lead to a long-term improvement in vegetation growth under the given climate conditions in southwest China. This adverse impact suggests that ecological engineering practices could potentially increase the ecosystem's vulnerability to droughts, owing to the increased transpirational water demands introduced by ecological engineering interventions. Our study highlights the importance of considering the expected occurrence and magnitude of climatic variability when implementing large-scale EEPs.

Global patterns of tree wood density

Wood density is a fundamental property related to tree biomechanics and hydraulic function while playing a crucial role in assessing vegetation carbon stocks by linking volumetric retrieval and a mass estimate. This study provides a high-resolution map of the global distribution of tree wood density at the 0.01° (~1 km) spatial resolution, derived from four decision trees machine learning models using a global database of 28,822 tree-level wood density measurements. An ensemble of four top-performing models combined with eight cross-validation strategies shows great consistency, providing wood density patterns with pronounced spatial heterogeneity. The global pattern shows lower wood density values in northern and northwestern Europe, Canadian forest regions and slightly higher values in Siberia forests, western United States, and southern China. In contrast, tropical regions, especially wet tropical areas, exhibit high wood density. Climatic predictors explain 49%-63% of spatial variations, followed by vegetation characteristics (25%-31%) and edaphic properties (11%-16%). Notably, leaf type (evergreen vs. deciduous) and leaf habit type (broadleaved vs. needleleaved) are the most dominant individual features among all selected predictive covariates. Wood density tends to be higher for angiosperm broadleaf trees compared to gymnosperm needleleaf trees, particularly for evergreen species. The distributions of wood density categorized by leaf types and leaf habit types have good agreement with the features observed in wood density measurements. This global map quantifying wood density distribution can help improve accurate predictions of forest carbon stocks, providing deeper insights into ecosystem functioning and carbon cycling such as forest vulnerability to hydraulic and thermal stresses in the context of future climate change.

The changing nature of groundwater in the global water cycle

In recent decades, climate change and other anthropogenic activities have substantially affected groundwater systems worldwide. These impacts include changes in groundwater recharge, discharge, flow, storage, and distribution. Climate-induced shifts are evident in altered recharge rates, greater groundwater contribution to streamflow in glacierized catchments, and enhanced groundwater flow in permafrost areas. Direct anthropogenic changes include groundwater withdrawal and injection, regional flow regime modification, water table and storage alterations, and redistribution of embedded groundwater in foods globally. Notably, groundwater extraction contributes to sea level rise, increasing the risk of groundwater inundation in coastal areas. The role of groundwater in the global water cycle is becoming more dynamic and complex. Quantifying these changes is essential to ensure sustainable supply of fresh groundwater resources for people and ecosystems.

Past dynamics and future prediction of the impacts of land use cover change and climate change on landscape ecological risk across the Mongolian plateau

Land use/land cover (LULC) change and climate change are interconnected factors that affect the ecological environment. However, there is a lack of quantification of the impacts of LULC change and climate change on landscape ecological risk under different shared socioeconomic pathways and representative concentration pathways (SSP-RCP) on the Mongolian Plateau (MP). To fill this knowledge gap and understand the current and future challenges facing the MP's land ecological system, we conducted an evaluation and prediction of the effects of LULC change and climate change on landscape ecological risk using the landscape loss index model and random forest method, considering eight SSP-RCP coupling scenarios. Firstly, we selected MCD12Q1 as the optimal LULC product for studying landscape changes on the MP, comparing it with four other LULC products. We analyzed the diverging patterns of LULC change over the past two decades and observed significant differences between Mongolia and Inner Mongolia. The latter experienced more intense and extensive LULC change during this period, despite similar climate changes. Secondly, we assessed changes in landscape ecological risk and identified the main drivers of these changes over the past two decades using a landscape index model and random forest method. The highest-risk zone has gradually expanded, with a 30% increase compared to 2001. Lastly, we investigated different characteristics of LULC change under different scenarios by examining future LULC products simulated by the FLUS model. We also simulated the dynamics of landscape ecological risks under these scenarios and proposed an adaptive development strategy to promote sustainable development in the MP. In terms of the impact of climate change on landscape ecological risk, we found that under the same SSP scenario, increasing RCP emission concentrations significantly increased the areas with high landscape ecological risk while decreasing areas with low risk. By integrating quantitative assessments and scenario-based modeling, our study provides valuable insights for informing sustainable land management and policy decisions in the region.

Designing mosaic landscapes for sustainable outcome: Evaluating land-use options on ecosystem service provisioning in southwestern Ghana

The landscape in southwestern Ghana faces rampant modification due to socio-economic activities, posing threats to ecosystem service provision and environmental sustainability. Addressing these threats involves empowering land-use actors to design landscapes that offer multiple benefits concurrently. This study employs a geodesign framework, integrating participatory ecosystem service assessment and spatial simulations. This geodesign framework aims to design the landscape in a collaborative manner in a way that supports multiple benefits concurrently, mitigating the threats posed by landscape modification. Reflecting on local land-use perceptions during a workshop, we developed land-use options and land management strategies based on selected land-cover types. We identified urban greens, open space restoration, rubber mixed-stands, mangrove restoration, selective-cutting land preparation, soil conservation, and relay cropping as land-use options to target selected land-cover types of shrubland, cropland, smallholder rubber, smallholder palm, wetland, and settlement. The land management strategies translated into landscape scenarios based on local need conditions. We generated the local need conditions which translated into the landscape scenarios by reflecting on the location of land-cover types, 'change-effect' conditions within rubber, settlement, and cropland, and 'no-change'conditions within cropland. Results indicate synergies between the created landscape scenarios and ecosystem service provisioning, with 'no-change' within cropland providing the highest synergy and 'change-effect' within rubber providing the least synergy. Spatial modeling of local perceptions forms the novelty of this study, as the fusion of participatory assessments and spatial modeling allows for a more holistic understanding of the landscape, its services, and the potential implications of different management strategies. The geodesign framework facilitated the design of the complex heterogeneous landscape to visualize possibilities of maximizing multiple benefits and can be used for future planning on the landscape.

Maternal greenness exposure and preterm birth in Brazil: A nationwide birth cohort study

In the dynamic landscape of maternal and child health, understanding the intricate interplay between environmental factors and pregnancy outcomes is of paramount importance. This study investigates the relationship between maternal greenness exposure and preterm births in Brazil using data spanning from 2010 to 2019. Satellite-derived indices, including the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were employed to assess greenness exposure during whole pregnancy in maternal residential area. Employing Cox proportional hazard models, we calculated the hazard ratios (HRs) with 95% confidence intervals (CIs) for changes in NDVI, while adjusting for individual and area-level covariates. In total, 24,010,250 live births were included. Prevalence of preterm birth was 11.5%, with a modest but statistically significant decreasing trend (p = 0.013) observed across the nation over the study period. The findings reveal a significant association between greenness exposure and a reduced risk of preterm birth. Specifically, for every 0.1 increase in NDVI, there was a 2.0% decrease in the risk of preterm birth (95%CI: 1.9%-2.2%). Stratified analyses based on maternal education and ethnicity indicated potential effect modifications, with stronger protective effects observed among younger mothers and those with less years of education. Sensitivity analyses using EVI yielded consistent results. In conclusion, this study suggests that higher maternal greenness exposure is linked to a decreased risk of preterm birth in Brazil. These findings imply that enhancing residential greenspaces could be a valuable public health strategy to promote maternal and child health in Brazil.

Effects of landscape pattern on land surface temperature in Nanchang, China

The composition and configuration of landscapes are critical important to design effective approaches to mitigate urban thermal environment in the urbanization process. In this research, land use maps and land surface temperature (LST) retrieval were derived in Nanchang city of central China based on product datasets and the thermal infrared band of Landsat. The results showed that the thermal environment of Nanchang had become worse over the past two decades, that is, the proportion of area of the extremely low temperature zone (ELTZ) decreased from 4.39 to 0.77% from 2001 to 2020, and that of medium temperature zone (MTZ) reduced by 20%, whereas those of the high temperature zone (HTZ) and the extremely high temperature zone (EHTZ) increased sharply after 2001, and by 2020, the area ratio increased by 11% and 7.16%, respectively. The agricultural land (AL) area decreased from 68.44 to 49.69%, was gradually replaced by construction land (CL). The CL occupied the largest proportion in EHTZ, HTZ and slight high temperature zone (SHTZ); water landscape (WL) and green land (GL) occupied the largest proportion in ELTZ, low temperature zone (LTZ); and AL occupied the largest proportion in SHTZ, MTZ, and slight low temperature zone (SLTZ). Landscape configuration also obviously impacted on LST. The model fitting was well (R = 0.87) between land use area and LST by multiple regression analysis. The significant correlation between LST and six landscape pattern indices of CL (p < 0.01) indicated that the larger percent (PLANT, R = 0.78) and the more concentrate (LPI, R = 0.73) of CL implied the higher LST, while the more fragment (NP, R = - 0.45), dispersed and complex shape (R = - 0.35) were benefit to relieve LST. Contrastively, the larger percent and the more concentrated and complex shape distribution of AL, GL and WL, the lower LST (p < 0.01). In addition, LST had closely correlation with landscape level indices such as aggregation degree (AI, R = 0.44) and diversity (SHDI, R = - 0.60) (p < 0.01).

Landscape evolution in China's key ecological function zones during 1990-2015

Landscape evolution has profound effects on ecosystems. Recently, some studies suggest that China has implemented plans leading in the greening of the world by mainly describing the changes based on satellite data. However, few studies have analyzed the policy effect on ecosystem improvement from the perspective of landscape pattern evolution. Among the numerous ecological policy plans, China's key ecological function zones plan is an important one. In this study, we focus on depicting the long-term and large-scale landscape evolution in China's key ecological function zones, which are accounting for 40.2% of China's land area, and include four-type ecoregions where ecosystems are fragile or important, to comprehensively explore the environmental influences of policy planning. For this purpose, we first described the landscape composition changes and conversion mechanisms in China's key ecological function zones from 1990 to 2015. Then we captured the detailed pattern evolution characteristics by landscape indices. The results show that these ecoregions were mostly evolving in an unfavorable direction in these 25 years, i.e. destruction of habitats and increment of fragmentation. Although greening areas increased based on other recent researches, the landscape pattern became worse, indicating it is necessary for the detailed analysis of landscape ecology and more accurate ecological planning. We also found the deterioration of the ecological environment had been uncharacteristically stopped or even improved in wind prevention and sand fixation ecoregions and biodiversity maintenance ecoregions after the implementation of this plan. Furthermore, we assumed that the policy is more prominent in these prohibiting sabotages and protecting areas with fragile ecological bases, which may be caused by the differentiated transfer payments in different ecoregions. Finally, some planning suggestions, such as stricter land use control, the regional balance of ecological transfer payments and deepening of ecological migration policies, etc., were proposed for promoting better future environmental changes.

Analysis of the spatiotemporal changes in global land cover from 2001 to 2020

Land cover changes have far-reaching effects on climate change and the evolution of ecological environments, making them important components of global change research. Based on MODIS land cover data (MCD12Q1), statistical parameters such as land cover dynamic degree, transition probability, and transition matrix were employed to analyse the spatiotemporal characteristics of global land cover changes from 2001 to 2020. The results indicated that land cover exhibits a latitudinal distribution in mid-latitude regions and a longitudinal distribution in high and low-latitude regions. During the study period, the areas of evergreen needleleaf forests, deciduous needleleaf forests, deciduous broadleaf forests, closed shrublands, and permanent wetlands exhibited fluctuating changes. Evergreen broadleaf forests and barren lands have decreased annually, whereas mixed forests, woody savannas, grasslands, urban and built-up areas, and cropland/natural vegetation mosaics have increased annually. In terms of the dynamic degree, the most significant changes occurred in deciduous broadleaf forests, closed shrublands, permanent wetlands, and cropland/natural vegetation mosaics. Additionally, there were significant variations in the types and regions of land cover changes and transitions. Evergreen needleleaf forests transitioned into grassland types, and the conversion between grassland types was the main transition from mid- to high- latitude regions. In tropical areas, evergreen broadleaf forests, open shrublands, and croplands have shifted towards grassland types as primary transitions. These findings provide significant implications for the in-depth exploration of land-atmosphere interactions, climate change, and numerical models.

Landscape changes in the Cerrado: Challenges of land clearing, fragmentation and land tenure for biological conservation

Land clearing, low levels of protection, and high biodiversity make the Brazilian Cerrado a hotspot for biological conservation. However, one of the most active agricultural frontiers in Brazil is located in this region. We thus aimed to evaluate the current trends of deforestation and fragmentation of the Cerrado, from 1986 to 2019; and the contribution of land tenure and farm size to the Cerrado conservation. We divided the Cerrado (∼2 Mkm2) into three sub-regions and calculated the distribution and size of the fragments; core areas and edge distance; isolation and importance of the smallest fragments for reducing isolation; and connectivity for the years 1986, 1997, 2008, and 2019. We then evaluated vegetation cover and landscape metrics for public lands and private farms. Since 1986, 22 % of the Cerrado's remnant vegetation was cleared and the number of fragments increased by 20 %. Currently, 10 % of the Cerrado vegetation is under the effect of a 30 m edge. Isolation increased in all the sub-regions and smaller fragments (>100 ha) are important for landscape configuration. 10.82 % of the vegetation is preserved in public lands and 57.9 % in private farms, where 377,901.5 km2 could be legally cleared. Compared to other Brazilian regions, the northern Cerrado is relatively well connected and less fragmented but land clearing still threatens biodiversity. Public lands are important for connectivity and habitat amount but play a minor role when compared to private lands. Our results highlight that avoiding further land clearing of the Cerrado is a challenge that requires the engagement of different stakeholders at different levels.

Driving model of land use change on the evolution of carbon stock: a case study of Chongqing, China

Terrestrialecosystems are significant carbon sinks and are crucial for understanding the regional and global carbon cycles, energy flow, and climate change. As land use change is a significant process affecting ecosystem carbon stocks and striving for land degradation neutrality (LDN), studying it is essential for comprehending the evolution of regional carbon sink functions and achieving sustainable development goals. The drastically diverse land use patterns in each of the study area's regions resulted in significant differences in carbon stock. This study explores the evolution traits of carbon stocks based on land use data and their driving mechanisms in Chongqing during the past 30 years by using spatial analysis, the InVEST model, and geographic probes. The results demonstrate that from 1990 to 2020, land degradation in Chongqing was made worse by the demand for land for construction land, but the strategy of converting cropland back to forests raised the carbon stock of forest land. The overall result is a decrease in total carbon stocks of 5.1078 Tg or 1.5%. The main pathway for carbon loss pathway in the evolution of carbon stock is the conversion of cropland to construction land, and the primary carbon compensation pathway is the conversion of grassland and cropland to forest land, with a spatial distribution characterized by "higher in the whole area and obvious local differences." The land use intensity index has the most significant influence on the evolution of carbon stock. Moreover, the interaction of pairwise factors played a more important role in affecting the evolution of carbon stocks than did each factor individually. The case study in this paper shows that land use change is a significant driving mechanism for the evolution of carbon stock, and the development of a driving model theory is appropriate for deciphering the trajectory of carbon stock evolution and offering research suggestions for other regions.

Spatio-temporal dynamics of land use transitions associated with human activities over Eurasian Steppe: Evidence from improved residual analysis

We presented a framework to evaluate the land use transformations over the Eurasian Steppe (EUS) driven by human activities from 2000 to 2020. Framework involves three main components: (1) evaluate the spatial-temporal dynamics of land use transitions by utilizing the land change modeler (LCM) and remote sensing data; (2) quantifying the individual contributions of climate change and human activities using improved residual trend analysis (IRTA) and pixel-based partial correlation coefficient (PCC); and (3) quantifying the contributions of land use transitions to Leaf Area Index Intensity (LAII) by using the linear regression. Research findings indicate an increase in cropland (+1.17 % = 104,217 km2) over EUS, while a - 0.80 % reduction over Uzbekistan and - 0.16 % over Tajikistan. From 2000 to 2020 a slight increase in grassland was observed over the EUS region by 0.05 %. The detailed findings confirm an increase (0.24 % = 21,248.62 km2) of grassland over the 1st half (2000-2010) and a decrease (-0.19 % = -16,490.50 km2) in the 2nd period (2011-2020), with a notable decline over Kazakhstan (-0.54 % = 13,690 km2), Tajikistan (-0.18 % = 1483 km2), and Volgograd (-0.79 % = 4346 km2). Area of surface water bodies has declined with an alarming rate over Kazakhstan (-0.40 % = 10,261 km2) and Uzbekistan (-2.22 % = 8943 km2). Additionally, dominant contributions of human activities to induced LULC transitions were observed over the Chinese region, Mongolia, Uzbekistan, and Volgograd regions, with approximately 87 %, 83 %, 92 %, and 47 %, respectively, causing effective transitions to 12,997 km2 of cropland, 24,645 km2 of grassland, 16,763 km2 of sparse vegetation in China, and 12,731.2 km2 to grassland and 15,356.1 km2 to sparse vegetation in Mongolia. Kazakhstan had mixed climate-human impact with human-driven transitions of 48,568 km2 of bare land to sparse vegetation, 27,741 km2 to grassland, and 49,789 km2 to cropland on the eastern sides. Southern regions near Uzbekistan had climatic dominancy, and 8472 km2 of water bodies turned into bare soil. LAII shows an increasing trend rate of 0.63 year-1, particularly over human-dominant regions. This study can guide knowledge of oscillations and reduce adverse impacts on ecosystems and their supply services.

Data-driven modeling on the global annual soil nitrous oxide emissions: Spatial pattern and attributes

Previous assessments generated divergent estimates of global terrestrial soil nitrous oxide (N2O) emission and its spatial distributions, which did not match the observed data well. The objectives of this study were to generate a global map of terrestrial soil N2O emissions based on field observations (n = 5549) and quantify the contribution of different variables for predicting the global variation of N2O emissions. We provided spatially explicit maps of annual soil N2O emission rates across forest, grassland and cropland using the random forest approach. The global mean soil N2O emission rate in our data-driven model was 0.059 ± 0.006 g N m-2 year-1, which was lower than the estimates from previous model ensembles. Soil N2O emissions were higher in the northern than southern hemisphere. The average annual soil N2O emission rate of cropland (0.094 ± 0.009 g N m-2 year-1) was higher than that of forest (0.039 ± 0.004 g N m-2 year-1) and grassland (0.045 ± 0.007 g N m-2 year-1). In addition, we found that soil nitrogen substrates dominated the changes in soil N2O emissions and the relative importance of nitrate, ammonium, and fertilizer in predicting soil N2O emissions was greater than that of mean annual temperature and precipitation. Our data-driven model results implied that previous process-based model may overestimate the global soil N2O emission rates due to limited validation data and incomplete assumptions on related-mechanisms. This study highlights the importance of global field observations in N2O emission estimation, which can provide an independent dataset to constrain previous process-based models for better prediction.

Past and projected future patterns of fractional vegetation coverage in China

With the intensifying climate change and the strengthening ecosystem management, quantifying the past and predicting the future influence of these two factors on vegetation change patterns in China need to be analyzed urgently. By constructing a framework model to accurately identify fractional vegetation coverage (FVC) change patterns, we found that FVC in China from 1982 to 2018 mainly showed linear increase (29.5 %) or Gaussian decrease (27.4 %). FVC variation was mainly affected by soil moisture in the Qi-North region and by vapor pressure deficit in other regions. The influence of environmental change on FVC, except for Yang-Qi region in the southwest (-2.0 %), played a positive role, and weakened from the middle (Hu-Yang region: 2.7 %) to the northwest (Qi-North region: 2.4 %) to the east (Hu-East region: 0.8 %). Based on five machine learning algorithms, it was predicted that under four Shared Socioeconomic Pathways (SSPs, including SSP126、SSP245、SSP370、SSP585) from 2019 to 2060, FVC would maintain an upward trend, except for the east, where FVC would rapidly decline after 2039. FVC in the eastern region experienced a transition from past growth to future decline, suggesting that the focus of future ecosystem management should be on this region.

Modelling and testing forest ecosystems condition account

We developed an application model based on the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework, endorsed by the United Nations Statistical Commission in 2021. This model enables mapping condition accounts for forest ecosystems using automated computation. We applied the model nationally in Spain between 2000 and 2015 to test its effectiveness. Our model follows five methodological steps to generate forest condition accounts: (i) definition and spatial delimitation of forest ecosystem types; (ii) selection of variables using the ecosystem condition typology encompassing physical, chemical, compositional, structural, functional, and landscape characteristics; (iii) establishment of reference levels, including lower (collapse) and upper (high ecosystem integrity) thresholds; (iv) aggregation of variables into condition index; and (v) calculation of a single condition index by rescaling the aggregated indicators between 0 and 1. The results obtained from the model provide valuable insights into the status and trends of individual condition indicators, as well as aggregated condition index values for forest ecosystems, in a spatially explicit manner. Overall, the condition of the forest ecosystems in Spain showed a slight increase, from 0.56 in 2000 to 0.58 in 2015. However, distinct trends were observed for each ecosystem type. For example, mixed Alpine and Macaronesia forests exhibited a significant improvement, while the continental Mediterranean coniferous forests did not show any change. This innovative approach to monitoring forest condition accounts has important potential applications in policy and decision-making processes. It can contribute to effective evidence-based nature conservation, ecosystem service management, and identifying restoration areas.

Mapping the spatial heterogeneity of global land use and land cover from 2020 to 2100 at a 1 km resolution

A fine global future land use/land cover (LULC) is critical for demonstrating the geographic heterogeneity of earth system dynamics and human-earth interaction. In this study, we produced a 1 km global future LULC dataset that takes into account future climate and socio-economic changes as well as the impact of simulated results of the former year on temporally adjacent periods. By incorporating the variations in climatic and socio-economic factors, we differentiated LULC suitability probabilities for historical and future periods across representative SSP-RCP scenarios. Then, by using an improved cellular automata model-PLUS to simulate the patch-level changes of various land classes, we iteratively downscaled water-basin-level LULC demands in various future scenarios to a spatial resolution of 1 km. Our dataset achieves a high degree of simulation accuracy (Kappa = 0.94, OA = 0.97, FoM = 0.10) and precisely captures the spatial-temporal heterogeneity of global LULC changes under the combined effects of climate change and socio-economic development. This robust and fine-scale LULC dataset provides valuable spatially-explicit information essential for earth system modeling and intricate dynamics between anthropogenic activities and the environment.

Analysis and simulation of the driving mechanism and ecological effects of land cover change in the Weihe River basin, China

Land cover change (LCC) is both a consequence and a cause of global environmental change. This paper attempts to construct a framework to reveal the driving mechanism and ecological effects of different ecological factors under LCC and to explore the ecological characteristics of future LCC. A rule-mining framework based on a land expansion analysis strategy (LEAS) in the patch-generating land use simulation (PLUS) model was used to analyze the drivers of LCC. Neighborhood analysis and ecological effect index were used to investigate multiple ecological effects of LCC. Remote sensing-based ecological indices (RSEI) and the PLUS and stepwise regression model were introduced to explore and predict the integrated ecological effect of LCC. Focusing on the Weihe River basin, study's main drivers of LCC were precipitation, temperature, elevation, population, water table depth, proximity to governments and motorways, GDP, and topsoil organic carbon were the main drivers of LCC. Change directionality were similar for the effects of greenness and biomass formation but opposite for summertime and wintertime temperature. In addition, the conversion of land cover types to cropland had the most significant integrated ecological effect, followed by forest, grassland-shrubland, and other types. The RSEI is predicted to rise to 0.77 in 2030, and the areas where the ecological quality grade will improve and decrease are concentrated on the east and west sides of Ziwuling Mountain, respectively. The findings of this study have practical significance for land management and ecological protection.

The kinetic Ising model encapsulates essential dynamics of land pattern change

A land pattern change represents a globally significant trend with implications for the environment, climate and societal well-being. While various methods have been developed to predict land change, our understanding of the underlying change processes remains inadequate. To address this issue, we investigate the suitability of the two-dimensional kinetic Ising model (IM), an idealized model from statistical mechanics, for simulating land change dynamics. We test the IM on a variety of patterns, each with different focus land type. Specifically, we investigate four sites characterized by distinct patterns, presumably driven by different physical processes. Each site is observed on eight occasions between 2001 and 2019. Given the observed pattern at the time ti we find two parameters of the IM such that the model-evolved land pattern at ti+1 resembles the observed land pattern at that time. The data support simulating seven such transitions per site. Our findings indicate that the IM produces approximate matches to the observed patterns in terms of layout, composition, texture and patch size distributions. Notably, the IM simulations even achieve a high degree of cell-scale pattern accuracy in two of the sites. Nevertheless, the IM has certain limitations, including its inability to model linear features, account for the formation of new large patches and handle pattern shifts.

Land Use and Land Cover Change Detection Using the Random Forest Approach: The Case of The Upper Blue Nile River Basin, Ethiopia

Monitoring land use change dynamics is critical for tackling food security, climate change, and biodiversity loss on a global scale. This study is designed to classify land use and land cover in the upper Blue Nile River Basin (BNRB) using a random forest (RF) algorithm. The Landsat images for Landsat 45, Landsat 7, and Landsat 8 are used for classification purposes. The study area is classified into seven land use/land cover classes: cultivated lands, bare lands, built-ups, forests, grazing lands, shrublands, and waterbodies. The accuracy of classified images is 83%, 85%, and 91% using the Kappa index of agreements. From 1983 to 2022 periods, cultivated lands and built-up areas increased by 47541 and 1777 km2, respectively, at the expense of grazing lands, shrublands, and forests. Furthermore, the area of water bodies has increased by 662 km2 due to the construction of small and large-scale irrigation and hydroelectric power generation dams. The main factors that determine agricultural land expansion are related to population growth. Therefore, land use and land cover change detection using a random forest is an important technique for multispectral satellite data classification to understand the optimal use of natural resources, conservation practices, and decision-making for sustainable development.

Quantifying the landscape changes within and outside the Dachigam National Park, Kashmir Himalaya, India using observations and models

Protected areas are the cornerstone of biodiversity and serve as a haven for biodiversity conservation. However, due to immense anthropic pressures and ongoing changes in climate, the protected reserves are under immense threat. Human interference through land system changes is a major precusor of fragmentation of landscapes resulting in the decline of Himalayan biodiversity. In this context, this research assessed land use land cover changes (LULCCs) and fragmentation within and outside the Dachigam National Park (DNP) using remote sensing data, GIS-based models and ground truth over the past 55 years (1965-2020). Landscape Fragmentation Tool (LFT) helped to compute edge effect, patchiness, perforation and core areas. The Land Change Modeller (LCM) of IDRISI TerrSet was used for simulating the future LULC for the years 2030, 2050, 2700 and 2100. The analysis of LULCCs showed that built-up and aquatic vegetation expanded by 326% and 174%, respectively in the vicinity of the DNP. The area under agriculture, scrub and pasture decreased primarily due to intensified land use activities. Within the DNP, the area under forest cover declined by 7%. A substantial decrease was observed in the core zone both within (39%) and outside (30%) the DNP indicative of fragmentation of natural habitats. LCM analysis projected 10% increase in the built-up extents besides forests, shrublands and pastures. This knowledge generated in this study shall form an important baseline for understanding and characterising the human-wildlife relationship, initiating long-term ecological research (LTER) on naturally vegetated and aquatic ecosystems (primarily Dal Lake) of the region.

Increased impact of the El Niño-Southern Oscillation on global vegetation under future warming environment

There are broad effects of vegetation changes on regional climate, carbon budget, the water cycle, and ecosystems' productivity. Therefore, further knowledge of the drivers of future vegetation changes is critical to mitigate the influences of global warming. The El Niño-Southern Oscillation (ENSO) is a major mode of interannual climate variability and is likely to affect vegetation on the global scale. Nonetheless, little is known about the causal impacts of ENSO on future vegetation cover with changes in land use and a warming environment. Here, we examined the connections between ENSO and vegetation using leaf area index (LAI) data over the period 2015-2100 from Coupled Modeling Intercomparison Project Phase 6. Our findings indicate that, compared with the historical period 1915-2000, the vegetated areas influenced by ENSO are projected to rise by approximately 55.2% and 20.7% during the twenty-first century of the scenarios SSP2-4.5 and SSP5-8.5, respectively. Though uncertainty for the causal link between ENSO and vegetation changes remains in several regions (i.e., parts of North America, southern Australia, and western Asia), ENSO signature on LAI variations is robust over northern Australia, Amazonia, and parts of Southeast Asia. These results indicate that the influences of ENSO on global vegetation may strengthen in the future.

The global wildland-urban interface

The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle1,2. It is where human-environmental conflicts and risks can be concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation and the spread of zoonotic diseases3. However, a global analysis of the WUI has been lacking. Here, we present a global map of the 2020 WUI at 10 m resolution using a globally consistent and validated approach based on remote sensing-derived datasets of building area4 and wildland vegetation5. We show that the WUI is a global phenomenon, identify many previously undocumented WUI hotspots and highlight the wide range of population density, land cover types and biomass levels in different parts of the global WUI. The WUI covers only 4.7% of the land surface but is home to nearly half its population (3.5 billion). The WUI is especially widespread in Europe (15% of the land area) and the temperate broadleaf and mixed forests biome (18%). Of all people living near 2003-2020 wildfires (0.4 billion), two thirds have their home in the WUI, most of them in Africa (150 million). Given that wildfire activity is predicted to increase because of climate change in many regions6, there is a need to understand housing growth and vegetation patterns as drivers of WUI change.

Modeling of land use/land cover dynamics using artificial neural network and cellular automata Markov chain algorithms in Goang watershed, Ethiopia

Land Use/Land Cover (LULC) change has inhibited sustainable development for the last millennia by affecting climate, biological cycles, and ecosystem services and functions. In this regard, understanding the historical and future patterns of LULC change plays a crucial role in implementing effective natural resource management. This study aimed to model and characterize the spatiotemporal trajectories of landscape change between the 1984 and 2060 periods. The satellite image spectral information was segmented into seven LULC classes using a hybrid approach of image spectral recognition. The supervised classification technique of Support Vector Machine (SVM) was used to classify the satellite images, whilst the Land Change Modeler (LCM) Module in TerrSet software was used to assess the historical trend and future simulation of LULC dynamics. To predict future landscape changes, transition potential maps were generated using a Multi-layer Perceptron (MLP) neural network algorithm. The findings of the study demonstrated that the Goang Watershed has experienced significant LULC change since 1984. During the 1984-2001, 2001-2022, and 1984-2022 periods, farmland showed a dramatic increasing trend with 7.5 km2/yr-1, 110.3 km2/yr-1, and 64.3 km2/yr-1, respectively. A similar trend was also observed in built-up areas with 0.5 km2/yr-1, 3.2 km2/yr-1, and 2 km2/yr-1. The expansion of farmland and built-up area was at the expense of forest, shrubland, and grasslands. With a business-as-usual scenario, the extent of farmland will continue to increase between 2022 and 2060 while rapid reduction is expected by forest, shrubland, and grasslands. The alarming rate of farmland and built-up area expansion will put significant pressure on biodiversity and ecosystem services in the area. As a result, eco-friendly conservation approaches should be implemented as soon as possible to maintain ecosystem health and encourage sustainable development.