Telecoupled landscapes: Spatial effects of external financial inflows on Africa’s biodiversity

Fire and habitat loss are major drivers of biodiversity change in tropical forests, yet their combined effects on functional traits remain poorly understood. We investigated how fire severity, fire extent, and forest cover jointly influence bird dietary traits across 15 Atlantic Forest landscapes in southeastern Brazil, each containing paired burned and unburned forest sites (30 sampling units). Birds were surveyed using point count methods, and community trait structure was quantified using community-weighted means (CWM) and variances (CWV) derived from continuous dietary traits (e.g., proportional use of different food resources), estimated through a nonparametric bootstrapping approach. We used generalized linear mixed models to assess the effects of fire and forest cover on these trait metrics. Both CWM and CWV were influenced by fire disturbance, with responses strongly modulated by forest cover, revealing non-additive and synergistic effects. Under high fire disturbance and low forest cover, trait convergence—expressed as reduced variability in fruit, nectar, and invertebrate consumption—indicating strong environmental filtering. Conversely, increased variance in seed consumption in burned forests suggested trait divergence consistent with limiting similarity under enhanced post-fire resource heterogeneity. These findings demonstrate that environmental filtering and limiting similarity can coexist along disturbance gradients, depending on both trait identity and landscape context. Our results highlight the value of trait-based approaches for detecting functional responses beyond species richness and reinforce the need to integrate fire management with habitat conservation to maintain functional integrity (i.e., the retention of community trait structure) in fire-susceptible tropical forests.

The interactions between land use and water quality play critical roles in shaping benthic macroinvertebrate biodiversity in rivers. However, existing studies struggle to effectively identify nonlinear interactions between land use and water quality. This study integrates Random Forest and SHapley Additive exPlanations to create a robust framework that identifies the nonlinear interactions among variables. Applied to the Fu River basin, a primary tributary of Poyang Lake, China, our framework identified season-specific drivers: Ammonia Nitrogen and Shannon's diversity landscape index dominated community dynamics in the wet season, while Hydrogen ion concentration and Forest were key in the dry season. Interactive analyses revealed that during the wet season, total phosphorus (TP) and cropland cover formed the most influential pair, with synergistic effects (i.e., combined impact > sum of individual effects). Notably, cropland coverage modulated TP’s impact on benthic diversity: low cropland cover favored positive effects of TP, which diminished as TP concentrations increased to 0.04 mg/L, whereas high cropland cover triggered negative effects that intensified with rising TP and stabilized at 0.10 mg/L. During the dry season, conductivity (Cond) and forest cover emerged as the most impactful pair, also exhibiting synergistic effects. Forest cover modulated Cond’s influence on benthic diversity: under high forest cover, low Cond exerted positive effects that weakened with increasing Cond to 60 μs/cm; under low forest cover, moderate Cond induced increasingly negative effects that plateaued at 80 μs/cm. This study provides a robust approach to decipher context-dependent environmental interactions, offering valuable insights for river ecological conservation and adaptive management. • Decoded nonlinear interactions of water quality/land use on benthic biodiversity in rivers. • NH 3 -N & SHDI/pH & forest dominate the biodiversity during wet/dry season. • TP-Cropland/Conductivity-Forest synergy amplifies impacts during wet/dry season.

Drought-induced damage detection in Iberian Scots pine forests through satellite remote sensing

Solitary bees are important pollinators and maintain biodiversity in agricultural landscapes, yet their populations are declining due to habitat loss, intensive farming and pesticide use. Organic farming offers a sustainable alternative to conventional systems, benefiting pollinators through reduced chemical inputs and greater habitat diversity. While effects on social bees such as honeybees and bumblebees are well documented, little is known about how farming practices and landscapes influence communities of cavity-nesting solitary bees. We investigated these effects across 17 sites in Germany using standardized cavity nests (“bee hotels”). This approach enabled us to assess number of brood cells, species diversity, the abundance of females and males and the proportion of undeveloped bees, revealing how solitary bee populations respond to different farming systems and landscape features. Landscape composition was analyzed within a 500 m radius to quantify the extent of organic farming and forest cover within the bees’ foraging range. We found that organic farming had a beneficial effect on solitary bee brood cells and female production. Organic landscapes were positively correlated with increase in bee abundance, species richness, and diversity, while forest cover had no strong effects. Still at the landscape level, the abundance of both females and males increased with the extent of organic farming, while at the local scale, the abundance of both sexes was higher in organic farms than in conventional sites. The findings highlight the potential ecological benefit of organic farming in supporting cavity nesting solitary bee populations and underscore its potential to mitigate biodiversity loss in agriculture. • Organic farming enhances cavity-nesting solitary bee communities, increasing abundance, species richness, and diversity across agricultural landscapes. • Both female and male solitary bees respond positively to organic management, with higher abundances at local (farm) and landscape scales. • Landscape-level organic farming extent is a key driver of solitary bee population metrics Forest cover showed no strong influence on cavity-nesting solitary bee abundance or diversity in agricultural settings. • Organic farming has clear potential to mitigate biodiversity loss, supporting solitary bees in intensively managed agroecosystems.

Effective forest management and climate adaptation require a detailed understanding of tree species-specific disturbance dynamics. In recent years forest disturbances in Central Europe have intensified, driven by rising temperatures and recurring droughts. In Germany, drought and windthrow events since 2018 have triggered unprecedented Forest Canopy Cover Loss (FCCL). Here, we present the first national-scale assessment of FCCL for dominant tree species in Germany from 2018 to 2024, based on multi-temporal remote sensing data. We produced a dominant tree species map for 2016 by majority-voting on annual Sentinel-2 tree species classifications (2016–2024) and filtering with forest structure data. This yields a robust baseline for ten dominant species classes (F1-scores > 0.90 for nine pure-species classes). We quantified FCCL, derived from Sentinel-2 and Landsat time series at monthly intervals and 10 m resolution, by aggregating species-specific canopy loss pixels across different temporal (monthly, annual) and spatial (district, state, and national) scales. FCCL predominantly affected coniferous species: Spruce-dominated forests accounted for 4497 km² (51.3 % of total FCCL), corresponding to 18.6 % of initial spruce area, with peak FCCL in 2020–2021 and a distinct late-summer peak. Pine ranked second with 1893 km² (21.6 % of total FCCL and 7.4 % relative). Deciduous species such as beech and oak were less affected, with total FCCL below 300 km² each and relative declines of 1 %. Spatial hotspots of spruce FCCL were concentrated in central low mountain ranges. Our results provide a tree species-specific overview of forest loss dynamics in Germany, revealing tree species-dependent FCCL since 2018, thus supporting long-term forest management and adaptation to climate change. • First assessment of tree species-specific forest canopy cover loss in Germany • New 2016 dominant tree species map derived from multi-annual Sentinel-2 satellite data • Spruce-dominated forests experience the greatest forest canopy cover loss • Pine losses rank second, while beech and oak forests remain more stable • Species-specific disturbance patterns guide climate-adaptive forest management

Extractive activities drive land transformation in many mineralised river basins. However, linking these changes to observable and attributable water-quality outcomes remains methodologically challenging. This study applies an integrated monitoring framework to examine how multi-decadal Land-use and land-cover change (LULC) translates into spatially differentiated river water quality in the Ankobra River basin, Ghana. Using harmonised Landsat and Sentinel imagery, LULC dynamics was reconstructed for 1986, 2002, 2016, and 2025. Field-based measurements of key physico-chemical water-quality parameters were collected to support the analysis. Spatial interpolation using Ordinary Kriging and redundancy analysis was then applied to assess the extent to which land-use composition explains the observed variation in water quality. The results showed a shift from forest-dominated land cover towards agriculture, settlement, and mining-related disturbance during the study period. Bareland/Mining expanded from less than 1% of the basin in 1986 to approximately 3.7% by 2025 (>100 km2), while combined forest cover declined overall throughout the study period. Water-quality patterns exhibited strong spatial gradients, with turbidity ranging from approximately 114 to more than 1000 NTU and total suspended solids (TSS) from around 100 to nearly 3000 mg L-1. Redundancy analysis indicated that land-use composition explained approximately 47.5% of the variance in water quality, with the mining-related land cover exerting the strongest influence (F=13.66, p<0.001) and showing robust positive associations with turbidity and TSS. Closed forest cover displayed a significant buffering effect, while agricultural land use did not show significant association on the spatial scale examined. These findings demonstrate how integrated Earth observation and field data can move sustainability assessment beyond descriptive convergence towards diagnostic clarity. The analytical framework offers a transparent and scalable approach for prioritising regulatory attention and monitoring in extractive landscapes where environmental pressures are spatially uneven and governance capacity is constrained.

Climate change and pest outbreaks are increasingly threatening conifer-dominated forests in Northern Europe, highlighting the need for greater species diversity to improve resilience. This study assessed early establishment success of six tree species: European aspen ( Populus tremula ), hybrid aspen ( P. tremula × P. tremuloides ), silver birch ( Betula pendula ), Norway spruce ( Picea abies ), Scots pine ( Pinus sylvestris ), and hybrid poplar ( P. trichocarpa × P. maximowiczii ), across seven sites in southern Sweden. Sites were categorized as either forest land (continuous forest cover >100 years) or forested arable land (former arable land afforested with Norway spruce for 40–70 years). Over three years, we monitored survival, height, and diameter growth. All experimental sites were fenced to exclude browsing. Wood ash was applied to a subset of hybrid poplars to assess its effect on establishment in acidic soils. Our results showed that hybrid aspen, birch, and European aspen had high survival and growth on forest land. On forested arable land, untreated Norway spruce, Scots pine, and hybrid poplar showed low survival, likely due to competition from dense vegetation. However, ash-treated poplar improved survival to approximately 80% and showed strong growth on forested arable sites. Principal Component Analysis indicated overall higher establishment success on forest land for most species, whereas hybrid poplar performed similarly on forest and forested arable land when wood ash was applied. These findings underscore the importance of matching species to site conditions during early establishment and provide empirical evidence to inform species selection for forest regeneration under similar site conditions in southern Sweden. • Site type strongly influenced establishment success of broadleaved trees. • Hybrid aspen and silver birch had the highest survival and early growth on forest land. • Norway spruce and Scots pine performed poorly on forested arable land. • European aspen performed similarly at both site types, demonstrating flexibility. • Results highlight species-site matching for reforestation in southern Sweden.

Assessing long-term urban ecological quality using the remote sensing ecological index: A case study of the Klang River Basin, Malaysia

Perceptions, sustainability and forest cover associated to public programs for coffee production in the Sierra de Zongolica, Mexico

The expansion and intensification of agriculture are widely recognized as major drivers of biodiversity loss. While research has primarily focused on deforestation frontiers, few studies have linked spatial-temporal land-cover dynamics to the organizational arrangements of agro-industrial supply chains. This study addresses this gap by analyzing land-use systems in the Upper Parana Atlantic Forest in Argentina, a priority biodiversity hotspot. We identify trends and patterns of agricultural and forest land-use change over the past two decades. We interpret these patterns in relation to the territorial integration of agro-industrial supply chains, using secondary data sources. We divided the study area into hexagonal cells of approximately 100 km². Interannual trends in native forest cover and dominant land uses were analyzed from 2000 to 2019. Trends were estimated by regressing the proportional area of land-cover classes derived from the MapBiomas Trinational Atlantic Forest against calendar year. To explore landscape homogenization, we regressed Shannon land-cover diversity indices over time. Our results reveal two contrasting spatial configurations. Some landscapes are dominated by a single land use, showing increasing homogenization. Others maintain a diversity of land uses and remain heterogeneous. These configurations seem closely associated with transaction modalities between primary producers and agro-industrial actors. In turn, these arrangements influence their impacts on native forest cover and habitat conservation outside protected areas. Understanding how agro-industrial supply chains are territorially embedded is critical for identifying incentives to foster more sustainable land-use trajectories and support biodiversity conservation, like the design of effective governance systems for Other Effective Area-Based Conservation Measures (OECMs).

ABSTRACT Michoacán possesses extensive forest cover yet has undergone rapid and sustained land use transformations driven by illegal logging and the expansion of the ‘avocado strip’. This study utilized Random Forest (RF) classification of Landsat imagery (1986–2025) to analyze landscape dynamics, identifying Near-Infrared (NIR) and Shortwave Infrared 2 (SWIR 2) bands as the most critical predictors. Change detection analysis revealed severe deforestation: dry forest declined by 4,344 km2 and evergreen forest by 1,698 km2, fueling a corresponding increase in exposed soils (3,270 km2) and croplands (2,158 km2). To assess ecological impacts, MaxEnt was employed to model the distribution of 35 vulnerable species (16 Near Threatened, 10 Vulnerable, and 9 Endangered) with Nighttime Land Surface Temperature in December emerging as the most influential variable. The biodiversity assessment (2000–2025) indicated that the Reddish Egret (Egretta rufescens) suffered the greatest loss of potential distribution area (exceeding 50%), while the Grey Plover (Pluvialis squatarola) and the Mexican Ground Pit Viper (Agkistrodon bilineatus) exhibited the greatest gains (approximately 50% increase). Given that these threatened ecosystems are poorly represented within current protected areas, these findings underscore an urgent need to integrate conservation strategies into regions undergoing intense agricultural conversion to mitigate further biodiversity loss.

In the southwestern Brazilian Amazon, palm-dwelling triatomines maintain sylvatic transmission cycles of Trypanosoma cruzi, the causative agent of Chagas disease, and Trypanosoma rangeli, a related non-pathogenic parasite. Deforestation can reduce biodiversity and increase pathogen prevalence in triatomine populations; however, the effects of landscape structure on triatomine infection patterns remain poorly understood. Here, we address this knowledge gap by examining how forest cover and proximity to human dwellings influence triatomine infection patterns across gradients of deforestation. Field surveys were conducted in 2022 and 2024 in 20 landscape units in Cruzeiro do Sul, Acre state, Brazil, where triatomines were collected from palm trees located at varying distances from inhabited households. Distances and land-use composition were quantified from high-resolution drone and satellite imagery, while parasite infections were identified using molecular assays. Bayesian binomial mixed-effects models revealed contrasting responses between parasites. T. cruzi infection probability was higher in more deforested landscapes and was further modulated by palm-household distance, with the strongest effects observed for palms closer to dwellings. In contrast, T. rangeli infection showed no supported association with forest cover or distance to households. Blood meal analysis revealed frequent feeding on sylvatic hosts, particularly marsupials, and detected human blood in a nymph collected only 33 m from a household; T. cruzi infections detected in the study were exclusively assigned to TcI discrete typing unit, a lineage commonly associated with sylvatic transmission. These findings demonstrate that deforestation reshapes host-vector-parasite interactions in palm-based systems, increasing spillover risk at the sylvatic-human interface without requiring domiciliated triatomines.

Camouflage is a common plant strategy to avoid herbivory in sparsely vegetated environments. In temperate deciduous forests, leaf mottling is hypothesized to camouflage the nutrient-rich leaves of spring-active understory plants against the sparsely vegetated background of leaf litter. However, tests of this hypothesis remain limited to few species at small spatial scales. I used texture metrics to quantify leaf mottling variation across gradients in canopy cover (as a proxy for leaf background) and deer abundance (as a proxy for herbivore pressure) in five Erythronium species in central and eastern North America. Inter- and intraspecific leaf mottling roughness and evenness were quantified from iNaturalist community science observations. I then used ANOVA and multiple regression to determine whether mottling increased with canopy cover and deer abundance, as expected from the camouflage hypothesis. Mottling roughness and evenness were greatest in Erythronium species known to occur in forests and diminished (i.e., leaves became less mottled) in prairie and woodland species. Mottling also varied intraspecifically for three species (and nearly so for a fourth), tending to increase with greater canopy cover. This mottling-canopy-cover relationship was strongest in areas of high to very high deer abundance. Greater Erythronium leaf mottling with canopy cover and deer abundance indicates that this trait may act as an herbivore avoidance strategy in forests. While mottling has also been hypothesized to facilitate photoprotection in high-light environments, minimal leaf mottling in prairie and woodland species suggests photoprotection is an unlikely mechanism for the genus studied here.

Carbon emissions trading systems have become increasingly prevalent amid rising global climate concerns and serve as key market-based tools for sustainable transformation. Agriculture is central to advancing China's "dual carbon" strategy, requiring both emission control and reduction, while rapid digital agricultural development enables more precise carbon monitoring and management. This study examines whether China's pilot carbon emissions trading pilot policy improves the eco-efficiency of digital agriculture. Using the dynamic data envelopment analysis (DEA)-Malmquist index method, we construct an evaluative framework to measure digital agricultural eco-efficiency, and based on panel data from 30 Chinese provinces over the period 2011-2022, we employ a difference-in-differences (DID) model to identify the policy effects. The empirical findings demonstrate that the ecological efficiency of China's digital agriculture has successfully increased because of the implementation of the pilot policy for carbon emissions trading, and this conclusion passes several robustness tests. Heterogeneity analysis indicates that the effects of the policy vary across regions and different levels of development of digital agricultural eco-efficiency. According to the results of the mediating effect analysis, the pilot carbon emissions trading pilot policy increases forest coverage, which in turn increases digital agricultural eco-efficiency. The results of this research offer guidance for promoting environmentally sustainable agricultural development in China and for supporting international initiatives aimed at lowering agricultural greenhouse gas emissions.

<bold></bold> We investigated how landscape patterns influence water quality across the Lower Niger River Basin, Nigeria, using multi-scale spatial analysis, contributing to Sustainable Development Goal 6 (Clean Water and Sanitation). Land use composition and configuration metrics were quantified within 5 km and 10 km buffer zones, and their effects on water quality were examined using stepwise multiple linear regression. Results showed that cropland fragmentation was the most significant driver of water quality degradation, strongly associated with elevated biochemical oxygen demand (BOD) and nitrite concentrations, particularly at the 10 km scale, indicating cumulative watershed effects. Urban-related metrics exhibited localized impacts, with built-up patch density influencing total dissolved solids (TDS) and BOD at the 5 km scale. Forest cover was generally linked to improved water quality, although fragmentation reduced its buffering capacity. Overall, configuration metrics outperformed composition metrics in explaining water quality variation, highlighting the importance of spatial arrangement in addition to land cover extent. These findings demonstrate that landscape fragmentation from agriculture and urban expansion exerts strong, scale-dependent effects on water quality. Integrating landscape configuration into watershed management can support evidence-based strategies for improving water quality and achieving SDG 6 in rapidly changing Afro-tropical river systems.

National forest cover change baselines for six countries of the Congo basin using open-source solutions and sample-based area estimates (2015–2023)

Forest cover restoration is urgently needed in a semi-arid district of West Bengal, where land degradation endangers environmental stability and community welfare. The present study introduces and validates a robust, data-driven framework using machine learning to isolate optimal sites for afforestation, aiming to enhance climate adaptability and create sustainable, forest-centric livelihood opportunities. The methodology is structured as a sequential, hybrid workflow. Initially, an unsupervised K-Means clustering algorithm was applied to a suite of eleven environmental variables derived from SRTM, Landsat, and national geospatial databases to perform an exploratory delineation of potential zones. This was followed by a meticulous training data generation were manually digitized through high-resolution visual validation on Google Earth Pro. This dataset then served as the basis for training two supervised algorithms: RF and XGBoost. A rigorous comparative evaluation confirmed the superior predictive power of the Random Forest model, which achieved an overall accuracy of 89.1% and Area Under the ROC Curve (AUC) of 0.9508. An interpretability analysis using SHAP further revealed that slope, soil moisture, and elevation were the most critical determinants of suitable area. The primary outcome is spatially explicit suitability map with 20.9% area of the district as potentially suitable for afforestation that serves as a decision-support tool, enabling policymakers and community stakeholders to implement strategic and effective afforestation programs in the study area.

Magombera and Kimboza forests in Tanzania are small lowland fragments on the eastern foothills of the Udzungwa and Uluguru mountains, respectively. In July–August of 2023 and 2024, we conducted surveys of the forest birds in the forests, using mist nets, opportunistic observations and audio playback. We recorded 58 species in Magombera and 69 in Kimboza including 7 and 12 species new to the sites, respectively. This increases the total number of species to 71 in Magombera and 89 in Kimboza. The majority are widespread in forest habitats in Tanzania, and are either forest generalists or forest visitors, with the number of species belonging to these categories similar in the two forests. More than twice as many obligate forest specialists are known from Kimboza Forest, compared to Magombera Forest, including seven with their main distribution in the Eastern African coastal forests. We identify three possible explanations for these differences: less field work has been carried out in Magombera; differences in forest community structure and floristic composition; and distance from coastal forests. We also recorded more seasonal altitudinal migrants (species and individuals), from nearby mountain areas, in Kimboza relatively to Magombera. This difference is possibly due to the loss of lowland forest in the Uluguru Mountains where the migrants would ‘winter’ previously, whilst in the Udzungwas a continuous forest cover still exists down to 300 m, providing a lowland forest retreat for altitudinal migrants. Instead, migrants from the Ulugurus appear to have to move through at least 11 km of open land to isolated lowland forests in the foothills, such as Kimboza Forest.

ABSTRACT This study analyzes long-term forest cover dynamics and associated socio-ecological drivers in the Okwangwo Division of Cross River National Park (CRNP), Nigeria, between 1987 and 2022, contributing to SDGs 15, 13, and 11 on sustainable ecosystems and community-centered environmental governance. Using a mixed-methods framework, we combined remote-sensing analysis with community-based data collection to assess land-cover change, its drivers, and implications for local livelihoods and conservation governance. Landsat imagery for four time periods was classified into Dense Forest, Sparse Forest, Bare Land, and Water Bodies using a CART–Random Forest model, achieving 99.5% overall accuracy (Kappa = 0.98). Structured surveys, participatory mapping, and focus group discussions were conducted with 200 respondents across four forest-adjacent communities to capture socio-economic characteristics, forest-use practices, and local ecological knowledge. Results show that Dense Forest expanded by 52.4% from 1987 to 2013 but declined slightly (1.8%) from 2013 to 2022, indicating renewed pressure after earlier conservation gains. Sparse Forest decreased by 44.1% overall, while Bare Land declined until 2013 but increased sharply thereafter (+60.4%). Water Bodies experienced the most severe decline (–82.7%). Community data reveal high dependence on farming and forest resources, low educational attainment, and strong cultural attachment to forest landscapes. Respondents demonstrated strong awareness of vegetation change, consistently attributing degradation to agricultural expansion, logging, fuelwood extraction, and persistent governance challenges. By integrating geospatial analysis with indigenous knowledge, the study highlights the importance of adaptive, community-inclusive conservation strategies aligned with local livelihoods and monitoring capacities. Findings underscore the need for strengthened protected area governance, improved resource management, and culturally grounded approaches to sustainable forest conservation in CRNP.