Reconciling carbon (C) sequestration with biodiversity conservation remains a key challenge for sustainable forest management, as C–biodiversity relationships vary across taxa and contexts. We evaluated how botanical composition, forest structure, C pools, and land use predict species richness of insects, birds, and bats across mature temperate forests in southern Québec, Canada. Generalized linear models were fitted for insects and birds, while bat data were analyzed descriptively due to low and uneven richness. Botanical composition and forest structure were the most consistent predictors across groups. Insects responded strongly to vegetation structure and C allocation, with richness decreasing with shrub density and mineral soil C but increasing with the soil:above-ground C ratio and distance from infrastructure. Bird richness increased with herbaceous cover and wetland area, emphasizing the value of open and moist habitats. Across taxa, C pools acted as secondary but complementary predictors. Based on observational analyses, our results show that C–biodiversity relationships are compartment-specific and taxon-sensitive, and suggest that maintaining structural complexity, diverse vegetation strata, wetland habitats, and soil C pools may help align biodiversity conservation with C sequestration objectives in temperate forests.

Abstract Arboreal small mammals are of particular concern due to their reliance on forest habitats, which are declining, notably in Africa. Most dormice species (Rodentia, Gliridae) are arboreal or semi-arboreal and may serve as indicators of forest habitat quality. However, the ecological requirements of several African dormice species remain poorly understood. We aimed to understand what factors drive the use of microhabitat features and which features are selected by woodland dormice Graphiurus murinus in a riverine Combretum forest in South Africa. We hypothesized that season, individual traits, residency status, connectivity, and vegetation structure and cover influence microhabitat choice. We collected capture–mark–recapture data across four seasons and assessed microhabitat features using a grid of 192 traps set at various heights. Generalized linear and generalized mixed models and comparative tests were used to assess microhabitat use and selection. Dormice were less captured during winter and where only same-sex individuals were present. Microhabitats with a higher number of dormice neighbours and those with animals with longer residency time were more frequently used. Dormice used more well-connected areas, trunks and canopies; favouring higher, denser and more connected vegetation cover. The species predominantly utilized Combretum caffrum , Rhus spp., and Gymnosporia heterophylla , preferring the latter two tree species. The significance of riverine Combretum forest structure for dormice microhabitat use and selection was evident. We suggest management practices potentially relevant to maintain dormice populations (e.g., preventing vegetation gaps larger than 50% per 100 m 2 ) by balancing potential alterations on forest density and structure (e.g., climate change).

Mosquito-borne diseases such as malaria, dengue, Zika, and chikungunya continue to pose major global health challenges, particularly across tropical and subtropical regions. While the role of climate, human mobility, and land use change in shaping disease transmission has been widely studied, the influence of forest vegetation structure on mosquito dispersal remains underexplored. Forests can simultaneously act as natural barriers, through dense canopy cover, lower temperatures, and reduced light, and as facilitators when fragmented or disturbed, creating transitional ecotones conducive to vector survival and flight. Recent research integrating landscape ecology, entomology, and remote sensing has revealed that vegetation heterogeneity, canopy height, and microclimate gradients directly mediate mosquito flight range, host-seeking behavior, and pathogen transmission potential. For example, Anopheles species often exploit partially cleared forest edges, while Aedes mosquitoes thrive in peri-urban forest mosaics that combine vegetation cover with artificial breeding habitats. Using Light Detection and Ranging (LiDAR)-based canopy measurements, Normalized Difference Vegetation Index (NDVI) modeling, and mark–release–recapture experiments, scientists are quantifying how vegetation structure predicts vector mobility across landscapes. This review synthesizes current knowledge (2021–2025) on how forest attributes modulate mosquito dispersal and vector-borne disease risks, emphasizing tropical ecosystems in Africa, South America, and Southeast Asia. We discuss mechanistic pathways linking vegetation and vector ecology, evaluate forest management implications for disease prevention, and identify future research priorities integrating remote sensing and ecological modeling.

Quantifying community-level trait shifts, driven by species turnover and intraspecific trait variation (ITV), is essential for understanding environmental filtering and elucidating community assembly and species coexistence. While well-studied in seed plants, the relative roles of these processes in ferns-a key component of forest understories-remain poorly understood. Here, we evaluated how topographic, soil, and overstory biotic factors influence the functional traits of understory fern communities at a local scale in a subtropical forest. We measured six key functional traits across 45 fern species in 121 plots of 10 m × 10 m. We found that trait-environment models based on species turnover alone (CWM_fixed) had consistently higher explanatory power than models that included ITV (CWM_specific) (mean pseudo-R² = 0.56 vs. 0.23). Variance partitioning revealed that trait-environment relationships were primarily driven by the unique effects of environmental factors rather than their shared variance, identifying soil properties and overstory biotic structure as distinct, independent drivers of community functional composition (explaining 23.0% and 17.7% of variance for plant growth and resource-use strategies, respectively). Our results highlight two key insights: (1) the understory fern community responds to environmental filters primarily through species turnover (compositional shifts) rather than widespread intraspecific trait variation; (2) soil phosphorus and forest structure act as critical filters that together shape community-level functional traits of ferns.

The global push to advance smart and digital forestry relies on emerging technologies to support efficient, AI-assisted, and data-driven forest management, but many forest operations occur in remote forests where reliable internet connectivity is unavailable. Low Earth Orbit (LEO) satellite constellations such as Starlink may provide reliable connectivity where cellular networks are unavailable. The performance of LEO-based solutions remains poorly understood under forest canopies, and empirical evaluations linking canopy characteristics to connectivity performance are largely lacking. In this study, the effect of forest vegetation on Starlink performance below the canopy was evaluated by placing a satellite receiver at thirty randomly selected permanent single tree inventory plots on the University of Idaho Experimental Forest and measuring connection success, connection time, and upload and download speeds along 50 m transects in all cardinal directions. LiDAR-derived stand density index (SDI), leaf area index (LAI), rumple index (RI), and vegetation cover (VC) were used to quantify canopy structure. Principal Component Analysis and survival analysis showed that higher values of PC1, primarily driven by SDI, LAI, and RI, reduced the probability of establishing a connection. Linear regression analysis indicated that higher SDI increased connection time, indicating that denser stands slowed or prevented connectivity. Linear mixed-effects models demonstrated that internet speed primarily declined with increasing distance, with download and upload rates dropping beyond 40 m from the router. LAI, RI, and VC did not influence connection time or speed, suggesting that overall stand density rather than leaf area per unit ground area has a greater impact on signal obstruction. Overall, dense forest structure and distance are the main constraints on LEO satellite connectivity and performance, and understanding these limitations supports the development and deployment of satellite-based networking to advance smart forestry operations. These results provide one of the first quantitative assessments of LEO satellite connectivity constraints in operational forest conditions, offering practical guidance for deploying satellite-based networks to support smart forestry applications in remote environments.

Southwest China’s karst region has developed a dam- and reservoir-dense pattern in which cascaded hydropower on mainstem rivers coexists with small hydropower on tributaries, forming a foundation for the region’s low-carbon energy supply. Under China’s “dual-carbon” targets and a strengthening ecological civilization agenda, it is urgent to clarify the mechanisms driving habitat quality (HQ) change under compound disturbances from cascaded hydropower, urbanization, and related pressures—especially the nonlinear pathway through which engineering disturbance propagates to ecological responses via land-use restructuring. To address this need, we develop a Cascade disturbance–Land restructuring–Habitat response chain framework and integrate an InVEST–IntPLUS–OPGD modeling approach to capture HQ dynamics in the Wujiang River Basin (1980–2020), attribute the interactive effects of coupled natural–social drivers, and project ecological responses under alternative 2035 scenarios. Results show that: (1) The basin maintained a stable ecological matrix, with forest land and cropland consistently >82.5% and forest cover near 50%, while construction land increased by 972.15 km2 and water bodies by 354.23 km2 (2) Mean HQ stayed high and declined by only 1.42%, with high and medium–high HQ dominating (>65%). HQ degradation is concentrated in urban expansion areas and reservoir shorelines, whereas most mountainous/forested regions remain stable; and (3) HQ spatial differentiation is mainly shaped by the synergy between forest structure and NDVI, while nonlinear urbanization edge effects impose stronger stress than hydropower development itself. Scenario simulations further indicate that a water protection pathway can enhance HQ by building integrated “water–forest” corridors that promote blue–green synergy. Overall, this study supports improved trade-off design between energy supply and ecological protection in vulnerable karst regions.

This study explored the relationships between geological substrate and the structural and compositional attributes of mixed beech ( Fagus sylvatica L.), fir ( Abies alba Mill.), and spruce (Picea abies [L.] Karst.) forests on Mt. Konjuh in northeastern Bosnia and Herzegovina. Research was conducted on 81 experimental plots established across three dominant substrates: limestone, peridotite, and chert. Stand structure, diversity, and spatial organization were assessed using the Shannon diversity index, Pretzsch’s species profile index, Gini coefficient, and the Clark–Evans and Füldner indices. The analyses revealed consistent differences among substrates, suggesting that geological conditions influence forest structure and diversity. Higher diversity and vertical heterogeneity were generally associated with limestone, while stands on peridotite and chert exhibited simpler but more balanced structures. All forest types displayed a reverse J-shaped diameter distribution, indicating uneven-aged composition and ongoing natural regeneration. Spatial patterns showed a tendency toward clustering of beech and spruce and higher species mingling on limestone. Overall, mixed beech–fir–spruce forests on Mt. Konjuh appear to be stable ecosystems whose structure and diversity are shaped by an interplay of geological, edaphic, and ecological factors. The results highlight the relevance of site-specific and adaptive silvicultural approaches that account for local variability in substrate and stand conditions.

Individual tree segmentation is critical for automated forest inventory systems, enabling detailed individual tree records that support precision forest management. While current airborne LiDAR systems can acquire high-density, high-accuracy point clouds of dense forests, significant challenges remain in analyzing the diversity of forest samples across different regions. An improved method of instance segmentation using a Mamba-Enhanced Sparse Convolutional Neural Network is proposed to address the problem of misallocation caused by ambiguous boundaries and overlapping canopies of individual trees. An innovative offset prediction method further reduces the high error rate in low-canopy datasets. On the basis of a variety of features, the designed network customizes the HDBSCAN clustering algorithm and the W-KNN neighborhood search algorithm for fine-grained instance segmentation to achieve optimal performance. To address the lack of block coherence in the FOR-instance dataset and to reduce redundant noisy trees in some regions, this work develops a novel pipeline to simulate real woodland scenes and evaluates the robustness of the network in composite forests. Extensive validation on real and benchmark data demonstrates the method’s superior generalization capability, yielding robust segmentation results across varied forest structures. The most marked gains are achieved in low-canopy settings, confirming the method’s enhanced ability to handle complex structural overlaps. Our method provides a more comprehensive solution for the inventory management of structurally heterogeneous or regionally diverse woodlands, thereby enhancing both the automation and precision of forest resource assessment.

Abstract Centuries of timber production have homogenized many forests by reducing variation in canopy density and deadwood availability, with far‐reaching consequences for biodiversity and trophic interactions. Recent studies indicate that increasing structural heterogeneity through canopy gap creation and deadwood enrichment can promote biodiversity and support tree regeneration. These management practices may also influence tree performance, among others assessed by folivory and leaf fluctuating asymmetry, which indicate how well trees resist leaf damage and maintain developmental stability under environmental stress. However, it remains unknown whether such management enables trees to mitigate folivory and developmental instability, especially across macroclimatic gradients such as elevation. We conducted a large‐scale experiment in Germany across 11 pairs of forests: one structurally homogeneous control forest and one experimentally heterogenized forest, where canopy gaps and deadwood were created to increase between‐patch structural heterogeneity. The forests spanned an elevation gradient from 38 to 1143 m. Across all forest pairs, we sampled 19,656 leaves from 1404 European beech ( Fagus sylvatica L.) trees. We quantified folivory, leaf fluctuating asymmetry, microclimatic conditions (temperature, vapour pressure deficit) and biotic pressures (predation, parasitism, competition). Experimental enhancement of structural heterogeneity reduced folivory overall but increased leaf fluctuating asymmetry. Folivory increased with elevation, while leaf fluctuating asymmetry declined, producing an inverse relationship: At low elevations, structural enhancement reduced folivory but increased asymmetry, whereas at high elevations it increased folivory but reduced asymmetry. Microclimatic variables explained variation in both folivory and leaf asymmetry more consistently than biotic pressures. These findings extend the stress‐gradient framework by showing that identical management interventions can yield opposite outcomes depending on the macroclimatic gradient associated with elevation. Thus, integrating elevation and climate context into forest management seems to be crucial for maintaining the resilience of temperate forests under global change. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Investigating Amazonian intense wind gusts and their environments is essential to better understand the drivers and impacts of severe convection that can reshape forest structure, increase tree mortality, and threaten ecosystems and communities. This study presents the first multi‐decadal (2000–2024) assessment of intense convective wind gusts across the entire Brazilian Amazon, using hourly observations from surface weather stations. Intense gusts occur frequently across the Amazon, particularly during the dry‐to‐wet transition months of September and October, peaking in the mid‐ to late afternoon. Thermodynamic factors favor intense gust generation during the dry and transition seasons, with environments characterized by higher downdraft convective available potential energy, steeper low‐level lapse rates, and higher lifting condensation levels, particularly in southern Amazon.

ABSTRACT Vegetation Optical Depth (VOD) data, derived from satellite microwave observations, are sensitive to above-ground biomass (AGB) and vegetation water content. While VOD is extensively used for global AGB estimation, its relationship with forest structural attributes in boreal forests remains inadequately understood, particularly during the growing season. This study explores the dependencies between forest structural attributes, including height, basal area, volume, Leaf area index, and AGB, and L- and X-band VOD during the growing season in boreal forests in Finland and Sweden. The analysis revealed that L-VOD values increased with increasing values of height, basal area, volume, and LAI (R = 0.37–0.55); conversely, X-VOD values did not exhibit a significant relationship within our study area. Our study revealed a weak to moderate relationship between forest structure and VOD within managed boreal forests. Additionally, the sensitivity of the relationship between VOD and forest structural attributes varied between summer months, with the strongest correlations observed in June for L- and X-VOD. Both VOD bands showed variability beyond the explanatory capacity of forest structural attributes, including AGB. This consideration should be taken into account when developing AGB products for boreal forests and using L- and X-band VOD datasets.

Even-aged forests are still predominant across Europe. However, due to the higher resilience and resistance of uneven-aged forests to disturbances and climate change, their proportion is expected to increase both in Europe and globally. The primary objective of this study is to demonstrate the feasibility of distinguishing between uneven- and even-aged forest stand structures on National Forest Inventory (NFI) permanent sample plots solely based on freely available, national airborne low-resolution laser scanning data, without the use of field-based estimates or measurements. Forest structure was described and classified based on canopy closure, dominant height, and canopy height diversity derived from the canopy height model (CHM) and voxel-based metrics calculated from the point cloud. Comparable results were obtained using both approaches for assessing forest structural diversity: canopy height diversity derived from the canopy height model ( CHD CHM ) and from voxel-based metrics ( CHD V ). However, differences in vertical diversity between uneven- and even-aged stands were more pronounced when using CHM-based metrics. Therefore, we conclude that in areas with low-density laser scanning data, CHM analysis represents a more suitable method for evaluating the vertical heterogeneity of forest stand structures. The CHD CHM values were estimated at 1.71 for uneven-aged forests, with values of 1.24 and 1.54 observed in mature even-aged forests. In comparison, CHD V values were 2.50 for uneven-aged forests, while mature even-aged forests showed values of 2.18 and 2.24.

One of the most popular approaches in functional plant ecology is the study of CSR strategies based on Grime’s theory. However, this approach to the study of epiphytes has not been used yet. We assumed that the response of epiphytes to disturbances would be different than that of terrestrial plants. Namely, this would lead to a decrease in epiphytes with the competitive (C) strategy and an increase in the number of stress-tolerants (S) in disturbed forests. We found that in primary forests, representatives of the Orchidaceae family dominate in terms of species number, while in disturbed forests, Orchidaceae and Polypodiaceae dominate. Epiphytes demonstrate a tendency to a more pronounced C- strategy than tropical forest trees and to a more R- strategy than terrestrial herbs. At the same time, most epiphytes gravitate toward the radical S- strategy. In the primary forest, epiphytes adhering to competitive, ruderal, and mixed strategies are widely represented. Representatives of these strategies disappear in secondary forests so that predominantly (S) stress-tolerant and one (C) competitive species remain. In the studied secondary formations of tropical forest, the lower forest layer is occupied by succulent orchids and ferns. Undisturbed tropical forest is characterized by the presence of sciophytic and mid-stem epiphytes. Disturbance of the tropical forest structure leads to the loss of epiphytic species of the lower synusiae, while the advantage passes to stress-tolerant succulents. Thus, the change in the functional diversity of epiphytes is directly related to the change in the structure and layering of the forest canopy

Abstract European forests have been intensively managed for the provision of renewable materials and are a valuable asset for climate change mitigation, adaptation, and biodiversity conservation. Forest harvesting fundamentally alters the physical structure and composition of forests, with consequences for climate regulation services. It can impact the land surface temperature (LST) both diurnally and seasonally, but the net LST impact of historical forest harvesting activities in Europe is as yet unknown. This study integrates satellite-derived data for LSTs and forest harvesting for the period 2004–2023 to unravel spatial and temporal patterns of the surface temperature response to harvesting disturbances in Europe. We find a consistent diurnal asymmetry: harvesting induces daytime warming alongside nighttime cooling across all seasons and forest types. However, the magnitude, net effect, and temporal evolution have strong heterogeneity. Regionally, daytime warming dominates in Southern Europe (+0.075 ± 0.007 °C, mean ± standard error; +0.719 °C at the 90th percentile), peaking in the summer (+0.103 ± 0.010 °C; +0.823 °C), while Eastern Europe shows the strongest annual nighttime cooling (−0.060 ± 0.005 °C; −0.937 °C). The response is weaker in Western Europe. Seasonally, net daily cooling prevails in the spring, whereas net warming dominates in the summer. The forest composition modulates the response: needleleaf forests show the strongest diurnal contrast, broadleaf forests exhibit the weakest daytime signal, and mixed forests display spring daytime cooling. After harvesting, most regions transition from initial postharvest warming toward longer-term cooling or neutrality after one or two decades, with the postharvest pattern varying regionally and by forest type. Overall, this study elucidates strong spatiotemporal variations in net microclimate responses to forest harvesting across Europe, driven by geography, seasonality, and forest composition. By explicitly characterizing how forest harvesting alters surface temperature across space and time, these findings contribute to improved region-specific forest management strategies that can better balance timber production with climate regulation and biodiversity conservation under changing environmental conditions.

The online version contains supplementary material available at 10.1007/s10021-026-01047-1.

Abstract Invasive, non-native plants frequently restructure ecosystems by homogenizing vegetation and altering trophic interactions, but the ecological consequences of invader removal are less predictable. Removal can redistribute light, nutrients and detrital resources, initiating community reassembly that extends beyond vegetation recovery and may facilitate secondary invasions. We used a single-site invasive-removal field study to examine how management of European buckthorn ( Rhamnus cathartica L.) reshaped vegetation structure, litter accumulation and faunal communities in a post-industrial forest preserve in western New York, USA. Across 18 plots representing managed, not-treated and regrown buckthorn conditions, we quantified herbaceous vegetation, leaf litter biomass and the abundance of arthropods, pollinators and small mammals. Rhamnus cathartica removal was associated with a tenfold increase in herbaceous plant cover and species richness, producing structurally complex understories and higher arthropod and pollinator abundance. However, managed plots also supported three- to fivefold higher densities of the invasive European fire ant ( Myrmica rubra [Linnaeus, 1758]) – corresponding with increased leaf litter in managed plots. Ant abundance was positively associated with thicker, more persistent litter layers rather than canopy openness, and increasing M. rubra density, in turn, corresponded with reduced pollinator abundance. Detritivore and rodent responses were more closely linked to vegetation structure and litter conditions than to ant abundance.

Our understanding of the viability of primates in anthropogenically fragmented habitats is undermined by the long timeframes for the effects of fragmentation to manifest. Studying primates in natural forest islands can better reveal the limits to habitat viability in the face of fragmentation. We present a study of a group of Azara's owl monkeys (Aotus azarae) occupying a 0.53ha forest "island", the smallest such forest island and territory ever documented for the genus Aotus. We radio collared one individual and then, for ten months, collected ecological and behavioural data on the island and the group (123 scans, 44 observation days). We also collected forest structure data on the island. While the group did successfully establish itself on the island, the pair did not have an offspring during the birth season. The pair predominantly engaged in resting behaviour in close proximity to each other. Furthermore, the adult male of the group was characterised by eye deformities and bodily injuries, and eventually died nine months after we identified him. These results suggest that, while the forest island may be habitable in the short term, it may not have been sufficient for the long-term survival and reproduction. We propose that this forest island could act as a population sink, where individuals that are not competitive in the highly saturated gallery forest can reside temporarily. Our study shows the importance of considering not only presence/absence, but also behaviour and life history to consider the effects of forest island viability, especially in the face of future scenarios of anthropogenic fragmentation.

Deadwood fungi are extremely diverse and crucial for carbon turnover in forests. To achieve multifunctional forests, we need to better understand the relationships between diversity, management, and ecosystem processes. We tested the effects of forest structure, i.e. canopy cover and deadwood enrichment, on fungal diversity and mass loss of European beech and Scots pine. We additionally assessed the effects of fungal diversity on mass loss. We expected deadwood enrichment to better explain fungal diversity, while canopy cover, alongside fungal diversity, would best explain mass loss. Overall, host tree species was more important than forest structure in explaining diversity. Beech fungal diversity was higher under closed canopies, while pine fungal diversity increased with some types of deadwood enrichment. Surprisingly, beech mass loss was higher in stands without deadwood enrichment, but also where tree crowns were added. Pine mass loss was not affected by forest structure. Effects of fungal diversity on mass loss were significantly related to fungal community composition in pine. Our findings emphasize the need for diverse tree hosts at the forest landscape-scale. However, contrasting diversity and decomposition effects between host trees indicate that stand-scale management strategies should be tailored to tree species to maintain diversity and decomposition processes.

Annotated datasets are essential for training and evaluating machine learning models in forest ecology. This dataset provides high-resolution, annotated LiDAR point clouds of 674 individual trees from 12 forest plots in the Shivalik Range of northern Haryana, India, representing 24 species. Data were acquired using Terrestrial Laser Scanning (TLS) and Airborne Laser Scanning (ALS), include field-measured attributes such as species identity and Diameter at Breast Height (DBH), and terrestrial and aerial RGB imagery. TLS point clouds were georeferenced and co-registered with centimetre-level accuracy, enabling precise integration with ALS data. The dataset includes segmented individual trees and wood–leaf classifications, suitable for applications such as tree morphology analysis, biomass estimation, and species classification. To support benchmarking, outputs from established classification algorithms (LeWoS, TLSeparation, CANUPO, and Random Forest) are included. As one of the first open-access LiDAR datasets from Indian tropical forests, it provides critical reference data for developing and validating forest structure models. It can also aid biomass mapping efforts in support of large-scale missions such as NASA-ISRO’s NISAR and ESA’s BIOMASS.

The California Prescribed Fire Monitoring Program dataset (2019–2024) provides comprehensive ecological monitoring data from prescribed fire treatments across California’s diverse forest ecosystems. This dataset encompasses forest structure and cover, fuel loads, and post-fire recovery metrics, collected using a standardized protocol, from over 36 disparate sites (114 burn units, 972 plots, and 1,838 total surveys). Data collected during pre-fire, immediate, and multi-year post-fire sampling episodes allow for robust analysis of prescribed fire effects across variable environmental conditions. The monitoring framework captures key ecological indicators, including tree mortality, fuel consumption, understory vegetation response, species composition, and regeneration. This dataset can address critical knowledge gaps regarding prescribed fire effectiveness for ecological restoration, hazardous fuel reduction, and ecosystem resilience objectives. These data can support evidence-based fire management decisions, validate fire effects models, and establish baseline reference conditions for future prescribed fire implementation throughout California’s fire-prone landscapes.