Conservation planning with spatially explicit models: a case for horseshoe bats in complex mountain landscapes

Context

Context Bats are considered as an ecological indicator of habitat quality due to their sensitivity to human-induced ecosystem changes. Hence, we will focus the study on two indicator species of bats as a proxy to evaluate structure and composition of the landscape to analyze anthropic pressures driving changes in patterns.

Objectives

This study develops a spatially-explicit model to highlight key habitat nodes and corridors which are integral for maintaining functional landscape connectivity for bat movement. We focus on a complex mountain landscape and two bat species: greater (Rhinolophus ferrumequinum) and lesser (Rhinolophus hipposideros) horseshoe bats which are known to be sensitive to landscape composition and configuration.

Methods

Species distribution models are used to delineate high-quality foraging habitat for each species using opportunistic ultrasonic bat data. We then performed connectivity analysis combining (modelled) suitable foraging habitat and (known) roost sites. We use graph-theory and the deviation in the probability of connectivity to quantify resilience of the landscape connectivity to perturbations.

Results

Both species were confined to lowlands (<1000 m elevation) and avoided areas with high road densities. Greater horseshoe bats were more generalist than lesser horseshoe bats which tended to be associated with broadleaved and mixed forests.

Conclusions

The spatially-explicit models obtained were proven crucial for prioritizing foraging habitats, roost sites and key corridors for conservation. Hence, our results are being used by key stakeholders to help integrate conservation measures into forest management and conservation planning at the regional level. The approach used can be integrated into conservation initiatives elsewhere.

     

Synthetic Aperture Radar (SAR) images improve habitat suitability models

Context

The ability to detect ecological networks in landscapes is of utmost importance for managing biodiversity and planning corridors.

Objectives

The objective of this study was to evaluate the information provided by a synthetic aperture radar (SAR) image for landscape connectivity modeling compared to aerial photographs (APs).

Methods

We present a novel method that integrates habitat suitability derived from remote sensing imagery into a connectivity model to explain species abundance. More precisely, we compared how two resistance maps constructed using landscape and/or local metrics derived from AP or SAR imagery yield different connectivity values (based on graph theory), considering hedgerow networks and forest carabid beetle species as a model.

Results

We found that resistance maps using landscape and local metrics derived from SAR imagery improve landscape connectivity measures. The SAR model is the most informative, explaining 58% of the variance in forest carabid beetle abundance. This model calculates resistance values associated with homogeneous patches within hedgerows according to their suitability (canopy cover density and landscape grain) for the model species.

Conclusions

Our approach combines two important methods in landscape ecology: the construction of resistance maps and the use of buffers around sampling points to determine the importance of landscape factors. This study was carried out through an interdisciplinary approach involving remote sensing scientists and landscape ecologists. This study is a step forward in developing landscape metrics from satellites to monitor biodiversity.

     

The relative importance of local versus landscape variables on site occupancy in bats of the Brazilian Cerrado

Context

Species site-occupancy patterns may be influenced by habitat variables at both local and landscape scales. Although local habitat variables influence whether the site is suitable for a given species, the broader landscape context can also influence site occupancy, particularly for species that are sensitive to land-use change.

Objectives

To examine the relative importance of local versus landscape variables in explaining site occupancy of eight bat species within the Brazilian Cerrado, a Neotropical savanna that is experiencing widespread habitat loss and fragmentation.

Methods

Bats were surveyed within 16 forest patches over two years. We used a multi-model information-theoretic approach, adjusted for species detection bias, to assess whether landscape variables (percent cover and number of patches of natural vegetation within a 2- and 8-km radius of each forest site) or local site variables (canopy cover, understory height, number of trees, and number of lianas) best explained site occupancy in each species.

Results

Landscape variables were among the best models (ΔAIC_c or ΔQAIC_c < 2) for four species (top-ranked model for black myotis), whereas local variables were among the best for five species (top-ranked model for vampire bats). Neither local nor landscape variables explained site occupancy in two frugivorous species.

Conclusion

Species associated with a particular habitat type will not respond similarly to the amount, distribution or relative suitability of that habitat, or even at the same scale. This reinforces the challenge of species distribution modelling, especially in the context of forecasting species’ responses to future land-use or climate-change scenarios.

     

Bat richness and activity in heterogeneous landscapes: guild-specific and scale-dependent?

Context

The conversion of natural environments into agricultural land has profound effects on the composition of the landscape, often resulting in a mosaic of human-altered and natural habitats. The response to these changes may however vary among organisms. Bats are highly vagile, and their requirements often imply the use of distinct habitats, which they select responding to both landscape and local features.

Objectives

We aimed to identify which features influence bat richness and activity within Baixo Vouga Lagunar, a heterogeneous landscape located on the Central-North Portuguese coast, and to investigate if that influence varies across a gradient of focal scales.

Methods

We sampled bats acoustically, while simultaneously sampling insects with light traps. We assessed the relationships between species richness, bat activity, and activity of eco-morphological guilds with landscape and local features, across four scales.

Results

Our results revealed both scale- and guild-dependent responses of bats to landscape and local features. At broader scales we found positive associations between open-space foraging bats and habitat heterogeneity and between edge-space foraging bats and greater edge lengths. Woodland cover and water availability at an intermediate scale and weather conditions and insect abundance at a local scale were the factors that mostly influenced the response variables.

Conclusions

Globally, our results suggest that bats are sensitive to local resource availability and distribution, while simultaneously reacting to landscape features acting at coarser scales. Finally, our results suggest that the responses given by bats are guild-dependent, and some habitats act as keystone structures for bats within this mosaic.

     

The past and future of modeling forest dynamics: from growth and yield curves to forest landscape models

Context

Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent.

Objectives

We highlight milestones in the development of forest dynamics models and identify future research and application opportunities.

Methods

We reviewed milestones in the evolution of forest dynamics models from the 1930s to the present with emphasis on forest growth and yield models and forest landscape models We combined past trends with emerging issues to identify future needs.

Results

Historically, capacity to model forest dynamics at tree, stand, and landscape scales was constrained by available data for model calibration and validation; computing capacity; model applicability to real-world problems; and ability to integrate biological, social, and economic drivers of change. As computing and data resources improved, a new class of spatially explicit forest landscape models emerged.

Conclusions

We are at a point of great opportunity in development and application of forest dynamics models. Past limitations in computing capacity and in data suitable for model calibration or evaluation are becoming less restrictive. Forest landscape models, in particular, are ready to transition to a central role supporting forest management, planning, and policy decisions.

Recommendations

Transitioning forest landscape models to a central role in applied decision making will require greater attention to evaluating performance; building application support staffs; expanding the included drivers of change, and incorporating metrics for social and economic inputs and outputs.

     

Spatial determinants of Atlantic Forest loss and recovery in Brazil

Context

Despite continued forest cover losses in many parts of the world, Atlantic Forest, one of the largest of the Americas, is increasing in some locations. Economic factors are suggested as causes of forest gain, while enforcement has reduced deforestation.

Objectives

We examine three aspects of this issue: the relative importance of biophysical versus anthropogenic factors in driving forest dynamics; role of forest mean patch age influencing areas targeted for losses; and what future forest mean patch age mosaic we can expect (more forest cover and full forest maturity?).

Methods

Three land cover maps from 1990, 2000 and 2010, were used in the study. We selected six biophysical and six anthropogenic spatial determinants to analyze by means of weights of evidence, using Dinamica software.

Results

Results show that forest regrowth is influenced by multiple factors, working in synergy. Biophysical variables are related to forest gain while anthropogenic are associated with loss. Clear patterns of regrowth on pasture and sugarcane plantations occurred, especially near rivers and forest patches, on steeper slopes and with sufficient rainfall. Forest loss has targeted both older and newer forests. Future projections reveal forest gain in a slow pace, followed by specific ecosystem service losses, due to continuous trends of older mature forest loss.

Conclusions

Regrowth is linked to land abandonment, and to neighboring environmental conditions. It is important to question which mechanisms will guarantee and potentiate new regrowth, thus contributing to landscape restoration and reestablishment of ecosystem services in the Atlantic Forest.

     

Employing landscape metrics in an open population model to estimate demographic parameters of a grassland bird

Context

The importance of landscape context is increasingly recognized when studying relationships between populations. Recent advances in open population modeling allow the employment of landscape metrics to estimate demographic parameters underlying population variation through time and space.

Objectives

Our primary objectives were to (1) describe the influence of landscape metrics on demographic parameters in the grasshopper sparrow (Ammodramus savannarum) and (2) quantify the contributions of these demographic parameters in influencing variation in territory counts through time. We anticipated results would allow us to make recommendations for prioritizing site conservation for this grassland-obligate species of regional conservation concern.

Methods

We employed territory counts spanning 13 years from Massachusetts, USA in open population models to estimate the effects of landscape metrics, territory density, and site quality on three demographic parameters.

Results

The best model estimated highest initial numbers of territories in larger, more distant sites. Overall growth rates <1 were estimated during 1993–2005, while growth rates >1 were estimated in larger sites with a higher habitat quality index and low to medium relative density. Highest rates of annual immigration were estimated for larger sites. Growth rate explained the greatest proportion of variation in territory counts through time.

Conclusions

Open population models allowed us to identify the effects of landscape context on multiple grasshopper sparrow demographic parameters. We encourage further application of these and related models to grassland birds. Beyond maintaining grasslands in the region, we recommend the conservation of large, distant, and previously occupied sites to benefit regional populations.

     

Revision and application of the LINKAGES model to simulate forest growth in central hardwood landscapes in response to climate change

Context

Global climate change impacts forest growth and methods of modeling those impacts at the landscape scale are needed to forecast future forest species composition change and abundance. Changes in forest landscapes will affect ecosystem processes and services such as succession and disturbance, wildlife habitat, and production of forest products at regional, landscape and global scales.

Objectives

LINKAGES 2.2 was revised to create LINKAGES 3.0 and used it to evaluate tree species growth potential and total biomass production under alternative climate scenarios. This information is needed to understand species potential under future climate and to parameterize forest landscape models (FLMs) used to evaluate forest succession under climate change.

Methods

We simulated total tree biomass and responses of individual tree species in each of the 74 ecological subsections across the central hardwood region of the United States under current climate and projected climate at the end of the century from two general circulation models and two representative greenhouse gas concentration pathways.

Results

Forest composition and abundance varied by ecological subsection with more dramatic changes occurring with greater changes in temperature and precipitation and on soils with lower water holding capacity. Biomass production across the region followed patterns of soil quality.

Conclusions

Linkages 3.0 predicted realistic responses to soil and climate gradients and its application was a useful approach for considering growth potential and maximum growing space under future climates. We suggest Linkages 3.0 can also can used to inform parameter estimates in FLMs such as species establishment and maximum growing space.

     

Wood fibre value simulation model: a new tool to assist measuring changes in forest landscapes by evaluating forest inventory

Context

A challenging issue in landscape ecology is the evaluation of changes in a forest landscape following a disturbance. This evaluation usually entails examining changes in the forest inventory, which represents the best information available for a given forest region.

Objectives

Our aim was to extend existing methods used to evaluate forest inventory to include additional variables, such as value-based forest product options, wood fibre attributes, and ecosystem services. Inclusion of such variables in forest inventory evaluations would allow research results to be presented from an economic perspective, which is often required for policy development and forest management decision-making.

Methods

We developed a value-based framework to evaluate forest inventory and implemented it in the wood fibre value simulation model. We then used a local data set from Manitoba, Canada, to show how the model can be applied to the mapping of new inventory layers to facilitate the evaluation of landscape changes.

Results

Five new inventory layers are mapped including bioenergy and heating value that can be directly used for evaluating landscape changes, and wood density, fibre length, and pulp yield, which can be combined with total wood volume to derive new variables or indices to express changes in landscape conditions.

Conclusions

Our model can contribute to the assessment of landscape changes by indicating the values a forest can have when it is used for different conservation or utilization purposes. The model can also support improved decision-making with respect to the management of forest resources.

     

Assessing wild bees in perennial bioenergy landscapes: effects of bioenergy crop composition,landscape configuration,and bioenergy crop area

Context

Wild bee populations are currently under threat, which has led to recent efforts to increase pollinator habitat in North America. Simultaneously, U.S. federal energy policies are beginning to encourage perennial bioenergy cropping (PBC) systems, which have the potential to support native bees.

Objectives

Our objective was to explore the potentially interactive effects of crop composition, total PBC area, and PBC patches in different landscape configurations.

Methods

Using a spatially-explicit modeling approach, the Lonsdorf model, we simulated the impacts of three perennial bioenergy crops (PBC: willow, switchgrass, and prairie), three scenarios with different total PBC area (11.7, 23.5 and 28.8% of agricultural land converted to PBC) and two types of landscape configurations (PBC in clustered landscape patterns that represent realistic future configurations or in dispersed neutral landscape models) on a nest abundance index in an Illinois landscape.

Results

Our modeling results suggest that crop composition and PBC area are particularly important for bee nest abundance, whereas landscape configuration is associated with bee nest abundance at the local scale but less so at the regional scale.

Conclusions

Strategies to enhance wild bee habitat should therefore emphasize the crop composition and amount of PBC.

     

Multiple-scale prediction of forest loss risk across Borneo

Context

The forests of Borneo have among the highest biodiversity and also the highest forest loss rates on the planet.

Objectives

Our objectives were to: (1) compare multiple modelling approaches, (2) evaluate the utility of landscape composition and configuration as predictors, (3) assess the influence of the ratio of forest loss and persistence points in the training sample, (4) identify the multiple-scale drivers of recent forest loss and (5) predict future forest loss risk across Borneo.

Methods

We compared random forest machine learning and logistic regression in a multi-scale approach to model forest loss risk between 2000 and 2010 as a function of topographical variables and landscape structure, and applied the highest performing model to predict the spatial pattern of forest loss risk between 2010 and 2020. We utilized a naïve model as a null comparison and used the total operating characteristic AUC to assess model performance.

Results

Our analysis produced five main results. We found that: (1) random forest consistently outperformed logistic regression and the naïve model; (2) including landscape structure variables substantially improved predictions; (3) a ratio of occurrence to non-occurrence points in the training dataset that does not match the actual ratio in the landscape biases the predictions of both random forest and logistic regression; (4) forest loss risk differed between the three nations that comprise Borneo, with patterns in Kalimantan highly related to distance from the edge of the previous frontier of forest loss, while Malaysian Borneo showed a more diffuse pattern related to the structure of the landscape; (5) we predicted continuing very high rates of forest loss in the 2010–2020 period, and produced maps of the expected risk of forest loss across the full extent of Borneo.

Conclusions

These results confirm that multiple-scale modelling using landscape metrics as predictors in a random forest modelling framework is a powerful approach to landscape change modelling. There is immense immanent risk to Borneo’s forests, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo.

     

Spatial dynamics of coastal forest bird assemblages: the influence of landscape context,forest type,and structural connectivity

Context

Complex structural connectivity patterns can influence the distribution of animals in coastal landscapes, particularly those with relatively large home ranges, such as birds. To understand the nuanced nature of coastal forest avifauna, where there may be considerable overlap in assemblages of adjacent forest types, the concerted influence of regional landscape context and vegetative structural connectivity at multiple spatial scales warrants investigation.

Objectives

This study determined whether species compositions of coastal forest bird assemblages differ with regional landscape context or with forest type, and if this is influenced by structural connectivity patterns measured at multiple spatial scales.

Methods

Three replicate bird surveys were conducted in four coastal forest types at ten survey locations across two regional landscape contexts in northeast Australia. Structural connectivity patterns of 11 vegetation types were quantified at 3, 6, and 12 km spatial scales surrounding each survey location, and differences in bird species composition were evaluated using multivariate ordination analysis.

Results

Bird assemblages differed between regional landscape contexts and most coastal forest types, although Melaleuca woodland bird assemblages were similar to those of eucalypt woodlands and rainforests. Structural connectivity was primarily correlated with differences in bird species composition between regional landscape contexts, and correlation depended on vegetation type and spatial scale.

Conclusions

Spatial scale, landscape context, and structural connectivity have a combined influence on bird species composition. This suggests that effective management of coastal landscapes requires a holistic strategy that considers the size, shape, and configuration of all vegetative components at multiple spatial scales.

     

Using animal movement behavior to categorize land cover and predict consequences for connectivity and patch residence times

Context

Landscape-scale population dynamics are driven in part by movement within and dispersal among habitat patches. Predicting these processes requires information about how movement behavior varies among land cover types.

Objectives

We investigated how butterfly movement in a heterogeneous landscape varies within and between habitat and matrix land cover types, and the implications of these differences for within-patch residence times and among-patch connectivity.

Methods

We empirically measured movement behavior in the Baltimore checkerspot butterfly (Euphydryas phaeton) in three land cover classes that broadly constitute habitat and two classes that constitute matrix. We also measured habitat preference at boundaries. We predicted patch residence times and interpatch dispersal using movement parameters estimated separately for each habitat and matrix land cover subclass (5 categories), or for combined habitat and combined matrix land cover classes (2 categories). We evaluated the effects of including edge behavior on all metrics.

Results

Overall, movement was slower within habitat land cover types, and faster in matrix cover types. Butterflies at forest edges were biased to remain in open areas, and connectivity and patch residence times were most affected by behavior at structural edges. Differences in movement between matrix subclasses had a greater effect on predictions about connectivity than differences between habitat subclasses. Differences in movement among habitat subclasses had a greater effect on residence times.

Conclusions

Our findings highlight the importance of careful classification of movement and land cover in heterogeneous landscapes, and reveal how subtle differences in behavioral responses to land cover can affect landscape-scale outcomes.

     

Landscape metrics as a framework to measure the effect of landscape structure on the spread of invasive insect species

Context

With accelerated land-use change throughout the world, increased understanding of the relative effects of landscape composition and configuration on biological system and bioinvasion in particular, is needed to design effective management strategies. However, this topic is poorly understood in part because empirical studies often fail to account for large gradients of habitat complexity and offer insufficient or even no replication across habitats.

Objectives

The aim of this study was to disentangle the independent and interactive effects of landscape composition and landscape configuration on the establishment and spread of invasive insect species.

Methods

We explore a spatially-explicit, mechanistic modeling framework that allows for systematic investigation of the impact of changes in landscape composition and landscape configuration on establishment and spread of invasive insect species. Landscape metrics are used as an indicators of invasive insect establishment and spread.

Results

We showed that the presence of an Allee effect leads to a balance between the effectiveness of spread and invasion success. Spread is maximized at an intermediate dispersal level and inhibited at both low and high levels of dispersal. The landscape, by either increasing or mitigating the dispersal abilities of a species, can lead to a rate of spread under a dispersal threshold for which density and spread is at the highest.

Conclusion

Our study proposes that change in landscape structure is an additional explanation of the highly variable spread dynamics observed in natural and anthropogenic landscapes. Consequently, a landscape-scale perspective could significantly improve spread risk assessment and the design of control or containment strategies.

     

Occupancy pattern of a long-horned beetle in a variegated forest landscape: linkages between tree quality and forest cover across spatial scales

Context

Interactions between landscape-scale processes and fine-grained habitat heterogeneity are usually invoked to explain species occupancy in fragmented landscapes. In variegated landscapes, however, organisms face continuous variation in micro-habitat features, which makes necessary to consider ecologically meaningful estimates of habitat quality at different spatial scales.

Objectives

We evaluated the spatial scales at which forest cover and tree quality make the greatest contribution to the occupancy of the long-horned beetle Microplophorus magellanicus (Coleoptera: Cerambycidae) in a variegated forest landscape.

Methods

We used averaged data of tree quality (as derived from remote sensing estimates of the decay stage of single trees) and spatially independent pheromone-baited traps to model the occurrence probability as a function of multiple cross-scale combinations between forest cover and tree quality (with scales ranging between 50 and 400 m).

Results

Model support and performance increased monotonically with the increasing scale at which tree quality was measured. Forest cover was not significant, and did not exhibit scale-specific effects on the occurrence probability of M. magellanicus. The interactive effect between tree quality and forest cover was stronger than the independent (additive) effects of tree quality and particularly forest cover. Significant interactions included tree quality measured at spatial scales ≥200 m, but cross-scale interactions occurred only in four of the seven best-supported models.

Conclusions

M. magellanicus respond to the high-quality trees available in the landscape rather than to the amount of forest per se. Conservation of viable metapopulations of M. magellanicus should consider the quality of trees at spatial scales >200 m.

     

The influence of landscape relative to site and patch variables on primate distributions in the Colombian Llanos

Context

Primates are an important component of biodiversity in tropical regions. However, many studies on the effects of habitat change on primates ignore the relative influence of landscape composition and configuration.

Objectives

This study addresses the question: how important are landscape-scale forest area and composition relative to patch-scale (1–1080 ha) and site-scale (transect of 1 km) habitat variables for the occupancy and abundance of four primate species in the Colombian Llanos.

Methods

Using a randomly stratified survey design, 81 fragments were surveyed for primate occupancy and abundance. We used zero-inflated models to test the relative influence of landscape-scale, patch-scale and site-scale variables on occupancy and abundance for each species. A 95% confidence set of models was constructed using the cumulative Akaike weight for each model and the relative importance of each set of variables calculated for each primate species.

Results

Occupancy was determined by a combination of site-scale, patch-scale and landscape-scale variables but this varied substantially among the primate species.

Conclusion

Our study highlights the importance of managing primates at a range of scales that considers the relative importance of site-, patch- and landscape-scale variables.

     

Effects of bird and bat exclusion on coffee pest control at multiple spatial scales

Context

Despite the key role of biological control in agricultural landscapes, we still poorly understand how landscape structure modulates pest control at different spatial scales.

Objectives

Here we take an experimental approach to explore whether bird and bat exclusion affects pest control in sun coffee plantations, and whether this service is consistent at different spatial scales.

Methods

We experimentally excluded flying vertebrates from coffee plants in 32 sites in the Brazilian Atlantic Forest, encompassing a gradient of forest cover at landscape (2 km radius) and local (300 m) spatial scales, and quantified coffee leaf loss, as an indicator of herbivory, and fruit set.

Results

Leaf loss decreased with higher landscape forest cover, but this relation was significantly different between treatment and control plants depending on local forest cover. On the other hand, fruit set responded to the interaction between treatment and local forest cover but was not affected by landscape forest cover. More specifically, fruit set increased significantly with local forest cover in exclusion treatments and showed a non-significant decrease in open controls.

Conclusions

These results suggest that services provided by flying vertebrates are modulated by processes occurring at different spatial scales. We posit that in areas with high local forest cover flying vertebrates may establish negative interactions with predaceous arthropods (i.e. intraguild predation), but this would not be the case in areas with low local forest cover. We highlight the importance of employing a multi-scale analysis in systems where multiple species, which perceive the landscape differently, are providing ecosystem services.

     

Interactive effects of landscape-wide intensity of farming practices and landscape complexity on wild bee diversity

Context

The local intensity of farming practices is considered as an important driver of biodiversity in agricultural landscapes and its effect on biodiversity has been shown to interact with landscape complexity. But the influence of landscape-wide intensity of farming practices on biodiversity and its combined effect with landscape complexity have been little explored.

Objective

In this study, we tested the interactive effect of the landscape-wide intensity of farming practices and landscape complexity on the local species richness and abundance of farmland wild bee communities.

Methods

We captured wild bees in 96 crop fields and explored the effect of landscape-wide intensity of various farming practices along a gradient of landscape complexity (proportion of semi-natural habitats).

Results

We found that species richness and abundance of wild bees were more positively influenced by landscape complexity in highly insecticide-sprayed landscapes than in less intensively managed landscapes. In contrast, we found that the positive effect of landscape complexity on bee species richness only occurred in landscapes with low nitrogen inputs.

Conclusions

Our study demonstrates the interactive effects of landscape-wide farming intensity and landscape complexity in shaping the diversity of farmland wild bee communities. We conclude that the management of farming intensity at the landscape-scale could mitigate the effects of habitat loss on wild bee decline and would help to maintain pollination services in agricultural landscapes.

     

How does forest fragmentation affect tree communities? A critical case study in the biodiversity hotspot of New Caledonia

Context

The biodiversity hotspot for conservation of New Caledonia has facing high levels of forest fragmentation. Remnant forests are critical for biodiversity conservation and can help in understanding how does forest fragmentation affect tree communities.

Objective

Determine the effect of habitat configuration and availability on tree communities.

Methods

We mapped forest in a 60 km² landscape and sampled 93 tree communities in 52 forest fragments following stratified random sampling. At each sampling point, we inventoried all trees with a diameter at breast height ≥10 cm within a radius of 10 m. We then analysed the response of the composition, the structure and the richness of tree communities to the fragment size and isolation, distance from the edge, as well as the topographical position.

Results

Our results showed that the distance from the forest edge was the variable that explained the greatest observed variance in tree assemblages. We observed a decrease in the abundance and richness of animal-dispersed trees as well as a decrease in the abundance of large trees with increasing proximity to forest edges. Near forest edges we found a shift in species composition with a dominance of stress-tolerant pioneer species.

Conclusions

Edge-effects are likely to be the main processes that affect remnant forest tree communities after about a century of forest fragmentation. It results in retrogressive successions at the edges leading to a dominance of stress-tolerant species. The vegetation surrounding fragments should be protected to promote the long process of forest extension and subsequently reduce edge-effects.