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.

The rural cultural landscapes in the Yellow River Basin, as an important part of the blue-green infrastructure, not only provide ecological services and public spaces, but also carry the function of regional cultural inheritance. The spatial layout of rural cultural landscapes deeply aligns with the multi-level living circles of residents, and has a significant impact on the organization of landscape spaces and social ecological resilience in rural areas. This study took 14,502 administrative villages in 25 counties (cities and districts) along the Yellow River in Shandong Province as the research objects. Based on mobile phone signaling data, the boundaries of rural living circles at the three scales of towns, counties and cities were identified, and the accessibility evaluation indicators of six types of cultural landscape facilities were constructed in combination with POI data. The aim is to reveal the service level of rural cultural landscapes and their potential role in promoting health equity and resilience. The research shows: (1) The travel radius of rural living circles in the Yellow River region as a whole shows an increasing trend from upstream to downstream, with a concentric expansion feature centered on county towns. The average radius of township, county and municipal living circles is approximately 8 km, 13 km and 18 km respectively; (2) The overall accessibility of cultural landscape facilities shows a multi-center and ring-shaped distribution pattern. There are significant spatial differences in the spatial distribution of different types of facilities. Among them, landscape green spaces form a high accessibility zone with a relatively high degree of continuity relying on prefecture-level cities and county parks. Sports, leisure, science and education, and cultural facilities are concentratedly distributed in county towns and key towns. Cultural relics, ancient sites and scenic spots are scattered in a point-like manner due to historical evolution and natural conditions. The cultural facilities along the main stream of the Yellow River are arranged in a string-like pattern; (3) The results of geographically weighted regression (GWR) show that the effects of different facility types on the characteristics of living circles have significant spatial non-stationarity. The response degree in the middle section of the Yellow River region is relatively higher. The research results can provide quantitative support for the layout optimization of rural cultural landscape facilities and the construction of living circle systems in the Yellow River region.

Above-ground biomass estimation of Trees outside Forests is crucial as they play a significant role in carbon sequestration, biodiversity conservation, and microclimate regulation, especially in arid and semi-arid regions where tree cover is limited. The heterogeneous vegetation covers and highly scattered nature of trees add to the challenges in the accurate estimation of aboveground biomass employing remote sensing technology. This study aimed to estimate the AGB of TOF in the arid regional landscape of the Thar desert of Rajasthan, integrating Sentinel-1 (S1) SAR and Sentinel-2 (S2) optical datasets and field observations, applying the Random Forest (RF) model. The field calculated AGB in the sampled area ranged from a minimum of 0.19 t/ha to a maximum of 43.12 t/ha, with a mean of 8.03 t/ha. The backscattering coefficients at VV and VH polarizations and 5 SAR indices from S1 and the multispectral bands, vegetation indices, and biophysical variables from S2 were extracted as the predictor variables for the AGB model. After correlation and multi-collinearity analysis, three models were developed: the first model based on S1(M_S1), the second model with S2 (M_S2), and the third model is a combined model of S1 and S2 variables (M_S1S2). The correlation analysis revealed that the SAR indices have a higher relationship with field biomass. Further, the combined model (M_S1S2) achieved the highest accuracy (R² = 0.52, RMSE = 3.89 t/ha) in AGB estimation, followed by M_S1 (R² = 0.46) and M_S2 (R² = 0.43). The results of the study highlight the utility of Sentinel datasets and larger ecological plots at the landscape level in biomass mapping in sparsely vegetated arid environments. Moreover, the study highlights the ecological importance of TOF and emphasizes the need for biomass and carbon stock assessments in the ecologically sensitive arid regions.

This study examines how disruptive sustainable business models (DSBMs) drive sustainability transitions across micro, meso , and macro levels of socio-technical systems. Analyzing 29 case companies, the research identifies five key drivers of DSBM development and scaling: technological experimentation, entrepreneurial initiative, user-driven innovation, industry collaboration, and regulatory support. These drivers interact with seven critical factors: industry dynamics, organizational structure, geographical context, innovation ecosystems, regulatory environment, policy coherence, and market readiness that shape how DSBMs evolve from niche innovations to regime-level change. Drawing on and extending the Multi-Level Perspective (MLP) framework, the study demonstrates how firms actively couple business model innovation with institutional change across levels. The findings highlight that DSBMs achieve large-scale impact by leveraging policy mixes that destabilize unsustainable practices while supporting innovation scaling. The role of adaptive governance frameworks and cross-sectoral policy coherence is crucial for aligning DSBMs with global sustainability goals, such as the Paris Agreement. Moreover, the study offers a novel contribution by conceptualizing DSBMs as recursive and cross-scalar instruments of transition agency. This research contributes to the literature on sustainability transitions by integrating business model innovation more explicitly into MLP theory and providing evidence of how firm-level agency interacts with structural change. • Disruptive sustainable business models operate across niche, regime, and landscape levels. • Business model innovation drives sustainability transitions beyond technological change. • Policy fragmentation constrains the scaling of disruptive sustainable business models. • Adaptive governance enables firms to challenge and reconfigure unsustainable regimes. • Evidence from 29 firms reveals sector-specific transition pathways.

Wetland ecosystems, crucial for carbon sequestration and coastal hazard mitigation, have experienced tremendous losses in land surface area over the last century, primarily due to land reclamation. This has led to increased rates of land subsidence in regions with high levels of reclamation, causing heightened vulnerability in these areas under anticipated scenarios of climate induced sea-level rise. This study integrates multi-sensor satellite remote sensing (optical, thermal, and active microwave) with spatially explicit eddy covariance flux measurements to model gross primary productivity (GPP) in restored wetlands of California's Sacramento-San Joaquin Delta. GPP is a crucial process in this context, as it impacts the potential for wetlands to act as land carbon sinks and has been shown to reverse land subsidence in restored wetlands of previously reclaimed areas. Still, there remain gaps in understanding how vegetation vigor, wetland composition and structure, and environmental conditions individually and interactively impact carbon assimilation in these ecosystems. This research aims to understand how complementary remotely sensed signals from multiple satellite platforms across the electromagnetic spectrum combine to improve classical, optically based GPP models, while determining the relative importance of certain biotic and abiotic environmental conditions that regulate GPP. Using a Bayesian generalized additive modeling framework, we evaluated how vegetation vigor (NDVI), canopy structure and biomass density (microwave backscatter), and land surface temperature affect wetland GPP at 10-m spatial resolution over a five-year period. Our results reveal a strong hierarchical and complementary influence of these variables, with the highest GPP occurring in warm, well-watered, and densely vegetated conditions. The model explained on average 66% of GPP variability and provides a scalable, open-access framework for assessing carbon fluxes in wetland landscapes. These findings offer valuable insight into planning restoration, monitoring restoration outcomes, carbon accounting, and identifying coastal adaptation strategies for valuable blue carbon ecosystems. • We develop a wetland GPP model using eddy covariance and remote sensing data fusion. • Hierarchy of wetland GPP drivers revealed through remotely sensed observations. • Wetland GPP shows greatest sensitivity to interaction of drivers. • Hierarchical model enables informed upscaling of wetland GPP to landscape level.

ABSTRACT Parrots provide essential ecological functions that are critical to ecosystem health, yet they are among the most threatened avian orders. Southern palm cockatoos ( Probosciger aterrimus macgillivrayi ) are predicted to face severe population declines due to land clearing, altered fire regimes, and low reproductive success. Understanding the factors that drive species' occupancy at the landscape level is essential to inform effective conservation strategies, particularly in dynamic landscapes. This study used an occupancy modelling approach to examine landscape‐scale ecological factors influencing palm cockatoo presence across ~3000 km 2 within the Weipa Plateau, Cape York Peninsula, Australia. To determine palm cockatoo occupancy, 421 surveys were conducted at 142 sites in June–July 2024. Palm cockatoos were detected on 41 occasions across 34 sites. The estimated occupancy rate was 0.14 (± 11 SE) and estimated detectability was 0.25 (± 4 SE). Cumulative detection probability was estimated at 0.58 (± 0.29 SE) over three visits. Occupancy modelling identified distance from major watercourses and the density of a major food source, nonda plum ( Parinari nonda ), as the strongest predictors of palm cockatoo occupancy. This study demonstrates the utility of occupancy modelling to identify key drivers of habitat use at the landscape level for rare and difficult to study species. Crucially, it highlights the urgent need to conserve habitat along riparian corridors and areas of high‐resource availability in adjacent savanna woodlands to protect the current palm cockatoo population from further decline. Conservation efforts should prioritise these core habitat areas, particularly in the face of expanding mining operations and increasingly destructive fire patterns in the western Cape York Peninsula.

GIS-based analysis of field margin photovoltaic potential at the landscape level in northwestern Germany.

This study investigated the impact of social media engagement on customer satisfaction at Indo Zambia Bank in Lusaka, focusing on key service quality dimensions such as responsiveness, information reliability, engagement rate, efficiency, and ease of use. The research aimed to determine how these factors influenced customer perceptions and satisfaction levels in the digital banking landscape. A mixed-methods research approach was employed, combining quantitative data collected from a sample of 200 respondents through a structured questionnaire with qualitative insights from in-depth interviews with bank staff. The study utilized multiple regression analysis to assess the relationships between social media engagement variables and customer satisfaction. The findings revealed that responsiveness had a significant positive effect on customer satisfaction (β = 0.421, p < 0.01), indicating that timely responses to customer inquiries and complaints on social media platforms were crucial in shaping customer experiences. Information reliability also demonstrated a strong influence on satisfaction levels (β = 0.368, p < 0.01), emphasizing the importance of accurate, clear, and transparent communication in fostering customer trust. Additionally, engagement rate was found to be a significant predictor of customer satisfaction (β = 0.295, p < 0.05), suggesting that active and interactive social media strategies enhanced customer relationships and loyalty. Efficiency emerged as the strongest predictor (β = 1.122, p < 0.001), highlighting the necessity of streamlined processes for improving customer satisfaction. The overall model explained 91.6% (R² = 0.916) of the variance in customer satisfaction, confirming the substantial impact of social media engagement on banking customer experiences. The study concluded that Indo Zambia Bank’s social media presence is a vital tool for improving customer satisfaction by ensuring quick responsiveness, reliable information sharing, and increased engagement. However, limitations such as reliance on self-reported data and the exclusion of non-digital customers indicated the need for further research. Based on the findings, the study recommended that Indo Zambia Bank strengthen its digital communication strategies, invest in AI-driven customer support, and adopt a more interactive approach to social media marketing. These efforts would not only enhance customer satisfaction but also improve overall customer retention and brand loyalty in an increasingly digitalized banking environment.

Clear-cutting is detrimental to ectomycorrhizal fungi in a short time perspective, but long-term effects on species richness and community composition are uncertain. To evaluate ecological sustainability of rotation forestry, we examined to what extent communities similar to those in old forests develop within the time frame of a rotation period. We conducted DNA-based analyses of ectomycorrhizal fungal communities in > 1500 sites across Swedish boreal forests and used space for time substitution to analyse the development of species richness, community composition, and abundance with increasing stand age, ranging from recent clear-cuts to 200-yr-old forests. Ectomycorrhizal fungal species richness peaked in 30- to 40-yr-old secondary stands, but community composition remained altered in up to 100-yr-old stands. Certain species in the Atheliaceae family thrived in secondary forests, whereas many Cortinarius and Russula species linked to acidic and unfertile soils were more common in old, natural forests. While Swedish rotation forestry does not appear to decrease species richness, it will progressively change the composition of ectomycorrhizal fungal communities at the landscape level, with species characteristic of acidic and nutrient-poor old-growth boreal forests decreasing in abundance.

ABSTRACT Climate change and poor crop management threaten groundnut productivity in the semi-arid tropics (SATs). To address this, a field experiment was conducted at ICRISAT in Hyderabad, India, during 2016–17 and 2017–18. The study used two prevalent groundnut varieties, ICGV91114 and ICGV00351. It evaluated four paired-row (PR) systems with different planting geometries: PR1-20:20 cm/40 cm × 10 cm; PR2-25:25 cm/50 cm × 10 cm; PR3-20:20 cm/25 cm × 10 cm; PR4-15:15 cm/22.5 cm × 10 cm, along with the standard spacing PR5-30 cm × 10 cm. Results showed that ICGV00351 outperformed ICGV91114 in both years. Among planting geometry, pod yield, economic water productivity, and profitability were higher in PR2 than PR1. Similarly, the highest average soil moisture was recorded in PR2 i.e. 1.87–2.01 cm in the 0–30 cm soil depth in both years. This enhanced soil moisture in PR2 improved nutrient availability and uptake, resulting in higher leaf area index, biomass yield, water productivity, and net returns. Bayesian probability and bivariate plots further confirmed that PR2 was the most promising planting geometry, followed by PR1, compared to the normal sowing method. A random forest model trained on above-ground available data can predict pod yield with greater accuracy at the 75th day after sowing in PR2. The findings highlight the potential of paired-row planting to improve groundnut productivity and resilience in SAT landscapes. However, collaborative efforts among governments, research institutions, community organisations, and farmers are essential to scale up paired-row planting for groundnuts, to increase productivity at the landscape level and thereby support the livelihoods of smallholder farmers.

Semi-natural grasslands are among the most biodiversity-rich habitats in European agroecosystems, offering a broad spectrum of resources for many species, including plants, insects, and birds, potentially increasing the provision of key ecosystem services. Grassland biodiversity can be strongly influenced by both local- and landscape-level factors. Understanding how different biodiversity facets respond to biotic and abiotic factors across spatial scales remains challenging; yet this knowledge is essential for guiding management actions that support key ecological processes in agroecosystems. Here, we adopted a multi-taxa and multi-scale approach considering five groups: plants, bees, hoverflies, orthopterans, and birds. We assessed the effects of local management (annual mowing frequency, presence of uncut refuges) and landscape features (urban and agricultural cover, landscape heterogeneity) on taxonomic and functional diversity in managed grasslands. We found that multidiversity was positively associated with the presence of uncut refuges and with landscape heterogeneity, while it was negatively associated with urban and monoculture cover at the landscape level. The effect of mowing frequency was weak, potentially due to contrasting effects on different groups. Structural equation models showed that ecological effects varied across scales, groups, and biodiversity indicators: i) local scale management was particularly correlated with indicators of plants and hoverflies; ii) landscape scale factors had a stronger relationship with birds; iii) bees and orthopterans showed relationships at both local and landscape scales. Since different scales of agroecosystems management showed contrasting effects on different groups, we emphasize the importance of planning both local- and landscape-level management to embrace different facets of biodiversity. • Grasslands are among the most biodiversity-rich habitats in European agroecosystems. • Responses of different biodiversity facets are rarely analysed simultaneously. • Both local management and landscape factors influence grasslands multidiversity. • Ecological effects can vary across scales, groups, and biodiversity indicators. • Management should consider contrasting effects on different biodiversity facets.

Achieving net-zero greenhouse gas (GHG) emissions in agriculture is a central objective of climate policy frameworks such as the Paris Agreement. This study explored the feasibility and trade-offs of achieving net zero at the farm level by combining life cycle assessment with modeling of soil organic carbon (SOC) stocks. Four case-study farms, two crop and two dairy, in Italy, the United Kingdom (UK), France, and Germany, and 11 mitigation actions were assessed under two 20-year eco-design scenarios: one maintaining ≥90% of baseline productivity (PM), and one achieving net zero. The scenarios combined nature-based solutions (e.g., organic fertilization, cover crops) with technological interventions (e.g., feed additive, solar power). Estimated GHG emissions decreased greatly, but SOC sequestration alone was insufficient to achieve net zero while maintaining productivity. Under the PM scenario, the Italian, French, and German farms still emitted 51%, 62%, and 84% of baseline emissions, respectively. The UK crop farm achieved net zero under the PM scenario, but had the highest ecotoxicity impact per ha, 11% higher than that of the Italian crop farm. Mitigation effectiveness depended on soil- and crop-management practices, baseline GHG emissions, and carbon inputs. Assumptions about the 20-year amortization window, nutrient cycling, and indirect GHG emissions influenced trade-offs between environmental impacts and productivity. Net zero may be pursued more effectively through cooperation among farms at the landscape or sector level. Assessing the entire agricultural value chain, improving model calibration, and supporting long-term transitions through policies will be essential for developing climate mitigation actions adoptable across European agriculture.

Soil microbiota provide essential services to plants, but predicting or manipulating these benefits is difficult. Here, we investigated microbial benefits to legume crops at a landscape level to uncover factors that predict those services and can be modified by growers. We sampled cultivated soils across a 1000 km transect of production farms and experiment stations with cowpea cultivation. Bioinoculant practices and crop histories were evaluated. Soils were characterized using bacterial metabarcoding and physicochemical analysis, and soil microbial extracts were created to test the capacity of the microbiota to induce root nodulation and growth effects in six legume cultivars, including cowpea, soybean, and lima bean. Resident soil microbiota enhanced cowpea growth, whereas soybean and lima bean experienced negligible benefits. Grower application of bioinoculants was associated with altered microbial communities and enhanced root nodulation but did not affect crop growth. Soil nutrient makeup was correlated with changes in the resident microbial communities and growth benefits to plants, growth effects that were eliminated in sterile soil inoculation treatments, suggesting that they are microbially mediated. Our findings that both planting practices and abiotic soil factors can indirectly affect plant performance, mediated by restructuring of the soil microbial community, suggest how soils could be inexpensively modified to enhance microbial services.

Monitoring seasonal grass cover dynamics in a multi-use savanna rangeland is important for sustaining the coexistence of livestock and wildlife. Moreover, population growth is driving increased livestock production, which further limits resources for both livestock and wildlife. To better understand the effect of grazing on grass cover dynamics, we developed a multi-scale remote sensing approach to study the monthly variation in grass cover in two types of conservation areas: a wildlife sanctuary and a communal livestock grazing and wildlife conservancy. The study was carried out in a semi-arid region in Kenya during an exceptionally dry year of 2022 when grazing resources were limited. The Excess Greenness color index was first used to develop a model predicting green fractional vegetation cover (fCover) of field photographs. This model was then applied to upscale fCover to the landscape level using very-high-resolution Pléiades satellite data. The resulting fCover maps were subsequently used to predict grass cover from medium-resolution Sentinel-2 multispectral satellite imagery using Random Forest machine learning. The final model showed high predictive power of grass cover in May (R 2 = 0.96, root mean square error (RMSE) = 4.95%), while predictions were less accurate yet promising for January (R 2 = 0.67, RMSE = 7.1%). The monthly grass cover maps demonstrate differences between the two conservation areas; the grazing area experienced low grass cover throughout the year, whereas grass cover in the wildlife sanctuary was more driven by rainfall. The results demonstrate the usability of digital cameras as the basis for vegetation cover models. Furthermore, this method can be used for adaptive land management to monitor within-season resources for both livestock and wildlife. • Fractional grass cover can be upscaled from field to regional levels • Training data from one month was used to predict monthly variations in grass cover • Areas with higher grazing pressure had lower grass cover throughout the year • The wildlife sanctuary experienced a more natural fluctuation in grass cover

ABSTRACT Woody encroachment is a growing concern in dryland regions, threatening grassland ecosystems and generating complex social-ecological and management challenges. In the Argentine Dry Chaco, this process is particularly pronounced in paleochannel systems, which are ancient riverbeds historically covered by native grasses. Using a multilevel approach combining structural equation models and semi-structured interviews with small-scale campesino producers, we explored how livestock densities (cattle, goats, sheep), fire-use (frequency and return interval), aridity, and protection status influence vegetation cover, and which grassland recovery strategies are suggested by campesinos. We found that aridity was negatively associated with grass cover. At the landscape level, fire frequency is critical for maintaining grasslands. In contrast, at the local level, the role of fire varied with protection status: in protected areas, longer fire return intervals and extensive grazing maintained a mosaic of woodlands and grasslands, whereas in non-protected areas, frequent burning was required to control woody cover driven by fencing and higher livestock densities. Goat density had a strong negative effect on grasslands and a positive association with woodlands, reinforcing feedback on degradation under intensive grazing. Campesino producers recognized fire as a crucial tool for controlling woody encroachment, emphasizing knowledge loss and regulatory challenges. Local knowledge also revealed concerns about water scarcity and fencing, which limits livestock efficiency and promotes woody encroachment. Our findings emphasize that the locally adapted use of fire and grazing, informed by traditional knowledge of campesinos and local partners, is essential for controlling woody encroachment and restoring multifunctional grassland landscapes.

Urban parks play a crucial role in conserving biodiversity, particularly for sensitive taxa such as butterflies and moths. This study compared two areas within Chapultepec Forest Urban Park in Mexico City—differing in landscape features and levels of human activity— comparing whether these factors influence the temporal and spatial patterns of lepidopteran diversity and composition. Weekly surveys were conducted from October 2021 to July 2022 in two sections with contrasting visitor frequency. Methods included rank-abundance curves, species richness estimation, and alpha and beta diversity analyses using Hill’s numbers and dissimilarity components, respectively. Results revealed that the area with higher visitor traffic harbored greater Lepidopteran diversity (67% of all species), especially during the dry season, contradicting our initial hypothesis. In contrast, the less frequented area had lower species richness. Spatially, dissimilarity was below 50% (mainly due to nestedness), while abundance-based dissimilarity exceeded 50%, with balanced variation in abundance as the main contributor. Temporally, total dissimilarity was higher than 50%, showing an inverse trend to the spatial pattern: turnover and abundance gradients played a more significant role. Overall, the findings did not support our expectation that Lepidopteran diversity would be lower in more urbanized areas. Instead, greater diversity was found in zones with higher human activity. These results emphasize the need for long-term biodiversity monitoring and the implementation of conservation strategies to safeguard ecological stability in urban environments.

Low-gradient coastal stream systems support important landscape level ecological functions by connecting uplands and marshes directly to large tidal rivers, estuaries, and coastal waterbodies. In this study, we develop and evaluate innovative monitoring and assessment methods to support biological indicator development for waterbody types and taxa that lack nationally consistent and reliable approaches. Low-gradient tidal and non-tidal coastal stream systems are infrequently included in national and regional monitoring programs and may require different methods than freshwater streams (US EPA National Rivers and Streams Assessment) or large tidal rivers (US EPA National Coastal Condition Assessment). Results from this study demonstrate that stable isotopes of nitrogen (δ15N) bioindicators from a variety of biotic trophic levels can be used as an efficient and effective rapid monitoring tool for screening level assessment of biotic condition in low-gradient coastal systems. These stable isotope indicators also provide empirical field measurements for ground-truthing national indices which are derived from remotely sensed national landscape data layers. The δ15N biotic responses were consistently significant across all trophic levels and negatively correlated with landscape level stressor exposure conditions reflected in the national and regional scale indices. Verifying national multiscale indices with site-scale field measured bioindicators (δ15N) provides coastal managers, states, tribal, regional, and local watershed organizations confidence in using these national indices at local watershed and catchment scales for identifying and prioritizing protection of healthy coastal stream networks and watersheds, as well as targeting critical functional elements of watersheds for restoration efforts.

Rising temperatures and droughts are triggering forest die-off in climate warming hotspots such as the Mediterranean Basin. UAVs equipped with LiDAR and multispectral sensors offer a powerful tool for surveys of tree vigor at landscape level. We used UAV-acquired LiDAR data and multispectral camera imagery to segment individual tree crowns, classify species, and assess the health status in two drought-affected forests in northeastern Spain: a mixed Pinus pinaster–Quercus ilex forest and a Pinus halepensis forest. Individual trees were segmented and classified using object-based image analysis with the Random Forest algorithm incorporating spectral, structural, and topographic variables. Greenness indices (NDVI and EVI) were analyzed in relation to crown height, topography (slope and elevation) and solar radiation, and their interactions. Analyses showed satisfactory crown segmentation (F-Score = 0.85–0.86) and species classification (Overall accuracy = 0.86–0.99), though distinguishing spectrally similar classes remained challenging. Taller P. pinaster trees exhibited higher NDVI, while taller P. halepensis displayed higher NDVI values in dense neighborhoods and on gentle slopes. These findings highlight the potential of high-resolution UAV-based remote sensing for effective near-real-time detection and attribution of forest die-off. Future research should aim to improve algorithm accuracy and better integrate field-based validation across different forest types.

Biotic homogenization and differentiation are two possible outcomes of tropical forest fragmentation with ramifications for biodiversity conservation. The extent of either outcome may vary depending on spatial scale and heterogeneity of climate and habitats, but these relationships remain poorly understood for taxonomic, functional, and phylogenetic metrics of diversity. Our goal was to determine the extent to which fragmentation is associated with biotic homogenization and/or differentiation across multiple levels of diversity at landscape versus regional scales. We examined diversity and similarity of understory bird communities in northwestern Ecuador, an ecoregion characterized by climatic variation, habitat loss and fragmentation, and high levels of biodiversity and endemism. At the landscape level, fragmentation was associated with biotic differentiation of understory bird communities between formerly contiguous intact and fragmented humid forests. At the regional scale, we found taxonomic homogenization across climate zones and forest types: the bird community in the fragmented humid landscape was as similar to the nearby intact humid forest community (mean distance = 3.1 km) as it was to that of drier, seasonal intact forest 60 km away. Patterns of landscape-level differentiation and regional homogenization were present but substantially less pronounced for functional and phylogenetic diversity, indicating functional and phylogenetic redundancy despite turnover and abundance shifts among dominant species. Our results suggest fragmentation of tropical forest (associated with homogenization between humid and drier/seasonal forest) may have similar impacts on communities as climate drying, and while many species may be lost, fragmented communities may retain some functional and evolutionary resilience against environmental stressors.

Most production forests are managed primarily for timber production, leading to homogenous forests at landscape scale and reduced biodiversity. To explore whether silviculturally enhanced forest structural heterogeneity can promote biodiversity at landscape scale, we conducted a large-scale experiment in eight German forests. We manipulated structural β complexity, i.e., the heterogeneity of structural elements between forest patches, by experimentally introducing variation in canopy cover and different types of deadwood across 156 patches of 50 × 50 m each, to investigate its effects on biodiversity. Here we analyzed the response of soil nematode communities to heterogenization by assessing taxonomic and functional diversity across patch (α-diversity), site (γ-diversity), and between-patch (β-diversity) scales using Hill–Chao numbers as diversity indices. Additionally, we tested whether environmental variables correlate with nematode diversity responses. Our results show that functional diversity is more responsive than taxonomic diversity. Increases in β-diversity of common and dominant functional groups occurred simultaneously with declines in α- and γ-diversity. This pattern indicates that local community dissimilarity can rise without an increase in overall landscape-level richness and suggests a shift toward more specialized nematode communities in response to the interventions. Moreover, we found that certain site-specific conditions, such as soil texture and understory plant biomass, correlated with these effects. Overall, our findings reveal complex, scale-dependent responses of nematode diversity to changes in aboveground forest structure and highlight the need to further investigate the context dependence of forest biodiversity management to provide informed recommendations. This study represents an important first step toward understanding how to increase soil β-diversity through enhanced forest structural heterogeneity at management-relevant (i.e., landscape level) spatial scales. • Enhanced structural heterogeneity in forests affects soil nematode diversity • Effects vary across diversity facets, scales, and diversity orders • More functional diversity metrics were changed than taxonomic ones • β-diversity of common and dominant taxa/functional groups increased • β-diversity can increase while α- and γ-diversity decrease • Site-specific environmental conditions link to diversity changes