Assessing landscape functional connectivity in a forest carnivore using path selection functions

Context

Understanding connectivity patterns in relation to habitat fragmentation is essential to landscape management. However, connectivity is often judged from expert opinion or species occurrence patterns, with very few studies considering the actual movements of individuals. Path selection functions provide a promising tool to infer functional connectivity from animal movement data, but its practical application remains scanty.

Objectives

We aimed to describe functional connectivity patterns in a forest carnivore using path-level analysis, and to explore how connectivity is affected by land cover patterns and road networks.

Methods

We radiotracked 22 common genets in a mixed forest-agricultural landscape of southern Portugal. We developed path selection functions discriminating between observed and random paths in relation to landscape variables. These functions were used together with land cover information to map conductance surfaces.

Results

Genets moved preferentially within forest patches and close to riparian habitats. Functional connectivity declined with increasing road density, but increased with the proximity of culverts, viaducts and bridges. Functional connectivity was favoured by large forest patches, and by the presence of riparian areas providing corridors within open agricultural land. Roads reduced connectivity by dissecting forest patches, but had less effect on riparian corridors due to the presence of crossing structures.

Conclusions

Genet movements were jointly affected by the spatial distribution of suitable habitats, and the presence of a road network dissecting such habitats and creating obstacles in areas otherwise permeable to animal movement. Overall, the study showed the value of path-level analysis to assess functional connectivity patterns in human-modified landscapes.

     

Assessing differences in connectivity based on habitat versus movement models for brown bears in the Carpathians

Context

Connectivity assessments typically rely on resistance surfaces derived from habitat models, assuming that higher-quality habitat facilitates movement. This assumption remains largely untested though, and it is unlikely that the same environmental factors determine both animal movements and habitat selection, potentially biasing connectivity assessments.

Objectives

We evaluated how much connectivity assessments differ when based on resistance surfaces from habitat versus movement models. In addition, we tested how sensitive connectivity assessments are with respect to the parameterization of the movement models.

Methods

We parameterized maximum entropy models to predict habitat suitability, and step selection functions to derive movement models for brown bear (Ursus arctos) in the northeastern Carpathians. We compared spatial patterns and distributions of resistance values derived from those models, and locations and characteristics of potential movement corridors.

Results

Brown bears preferred areas with high forest cover, close to forest edges, high topographic complexity, and with low human pressure in both habitat and movement models. However, resistance surfaces derived from the habitat models based on predictors measured at broad and medium scales tended to underestimate connectivity, as they predicted substantially higher resistance values for most of the study area, including corridors.

Conclusions

Our findings highlighted that connectivity assessments should be based on movement information if available, rather than generic habitat models. However, the parameterization of movement models is important, because the type of movement events considered, and the sampling method of environmental covariates can greatly affect connectivity assessments, and hence the predicted corridors.

     

Connecting models to movements: testing connectivity model predictions against empirical migration and dispersal data

Context

Connectivity has become a top conservation priority in response to landscape fragmentation. Many methods have been developed to identify areas of the landscape with high potential connectivity for wildlife movement. However, each makes different assumptions that may produce different predictions, and few comparative tests against empirical movement data are available.

Objectives

We compared predictive performance of the most-used connectivity models, cost-distance and circuit theory models. We hypothesized that cost-distance would better predict elk migration paths, while circuit theory would better predict wolverine dispersal paths, due to alignment of the methods’ assumptions with the movement ecology of each process.

Methods

We used each model to predict elk migration paths and wolverine dispersal paths in the Greater Yellowstone Ecosystem, then used telemetry data collected from actual movements to assess predictive performance. Methods for validating connectivity models against empirical data have not been standardized, thus we applied and compared four alternative methods.

Results

Our findings generally supported our hypotheses. Circuit theory models consistently predicted wolverine dispersal paths better than cost-distance, though cost-distance models predicted elk migration paths only slightly better than circuit theory. In most cases, our four validation methods supported similar conclusions, but provided complementary perspectives.

Conclusions

We reiterate suggestions that alignment of connectivity model assumptions with focal species movement ecology is an important consideration when selecting a modeling approach for conservation practice. Additional comparative tests are needed to better understand how relative model performance may vary across species, movement processes, and landscapes, and what this means for effective connectivity conservation.

     

Examining speed versus selection in connectivity models using elk migration as an example

Context

Landscape resistance is vital to connectivity modeling and frequently derived from resource selection functions (RSFs). RSFs estimate relative probability of use and tend to focus on understanding habitat preferences during slow, routine animal movements (e.g., foraging). Dispersal and migration, however, can produce rarer, faster movements, in which case models of movement speed rather than resource selection may be more realistic for identifying habitats that facilitate connectivity.

Objective

To compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection.

Methods

Using movement data from migrating elk, we evaluated continuous time Markov chain (CTMC) and movement-based RSF models (i.e., step selection functions [SSFs]). We applied circuit theory and shortest random path (SRP) algorithms to CTMC, SSF and null (i.e., flat) resistance surfaces to predict corridors between elk seasonal ranges. We evaluated prediction accuracy by comparing model predictions to empirical elk movements.

Results

All connectivity models predicted elk movements well, but models applied to CTMC resistance were more accurate than models applied to SSF and null resistance. Circuit theory models were more accurate on average than SRP models.

Conclusions

CTMC can be more realistic than SSFs for estimating resistance for fast movements, though SSFs may demonstrate some predictive ability when animals also move slowly through corridors (e.g., stopover use during migration). High null model accuracy suggests seasonal range data may also be critical for predicting direct migration routes. For animals that migrate or disperse across large landscapes, we recommend incorporating CTMC into the connectivity modeling toolkit.

     

Using multiple metrics to estimate seasonal landscape connectivity for Blanding’s turtles (<Emphasis Type="Italic">Emydoidea blandingii</Emphasis>) in a fragmented landscape

Context

Landscapes and animal behavior can exhibit temporal variability and connectivity estimates should consider this phenomenon. In many species, timing of activities such as nesting, mate searching, and hibernation occurs during distinct periods in which movement events may differ, along with physical characteristics of the surrounding landscape.

Objectives

We estimate movement, landscape conductance, and patch importance for a turtle species across two seasonal activity periods (spring, late summer) in a fragmented agricultural region. Three connectivity approaches are compared to identify their advantages and disadvantages.

Methods

A least-cost distance model, circuit-based approach, and patch-based index were used to collectively describe the potential functional connectivity of Blanding’s turtle (Emydoidea blandingii) across a multi-temporal scale in an agricultural region of south western Ontario.

Results

Connectivity decreased further into the active season exhibited through lower conductance of the landscape and fewer pathways, while the importance of habitat nodes shifted due to temporal variability in the number and distribution of nodes. Models provided different yet complimentary information, with least-cost models overestimating discrete pathways yet providing a secondary measure of landscape barriers. The circuit-based model estimated corridors of least resistance providing an overall characterization of the landscape, while patch-based indices provided key information on the importance of individual habitat patches.

Conclusion

Findings highlight the importance of including a temporal aspect in connectivity modelling as results demonstrate a change in functional connectivity over time. We also recommend employing multiple connectivity metrics to capture variation in movement behavior.

     

Movement patterns of three arboreal primates in a Neotropical moist forest explained by LiDAR-estimated canopy structure

Context

Many arboreal mammals in Neotropical forests are important seed dispersers that influence the spatial patterns of tree regeneration via their movement patterns, which in turn are determined by the canopy structure of the forest itself. However, the relationship between arboreal mammal movement and canopy structure is poorly understood, due in large part to the complexity of quantifying arboreal habitat structure.

Objectives

We relate detailed movement trajectories of three sympatric primate species to attributes of canopy structure derived from airborne light detection and ranging (LiDAR) in order to understand the role of structure in arboreal movement in the tropical moist forest of Barro Colorado Island, Panama.

Methods

We used high-resolution LiDAR to quantify three-dimensional attributes of the forest canopy of the entire island, high-resolution GPS tracking to map the movement patterns of the monkey species, and step selection functions to relate movement decisions to canopy attributes.

Results

We found that movement decisions were correlated with canopy height and distance to gaps, which indicate forest maturity and lateral connectivity, in all three species. In the two faster-moving species, step selection was also correlated with the thickness of the crown layer and the density of vegetation within the crown.

Conclusions

The correlations detected are fully in line with known differences in the locomotor adaptations and movement strategies of the study species, and directly reflect maximization of energetic efficiency and ability to escape from predators. Quantification of step selection in relation to structure thus provides insight into the ways in which arboreal animals use their environment.

     

Can we face different types of storms under the same umbrella? Efficiency and consistency of connectivity umbrellas across different patchy landscape patterns

Context

The umbrella approach applied to landscape connectivity is based on the principle that the conservation or restoration of the dispersal habitats for some species also can facilitate the movement of others. Species traits alone do not seem to be enough to identify good connectivity umbrella species, showing the need to investigate the influence of additional factors on this property.

Objectives

We test whether the potential of a species as a connectivity umbrella can be influenced by landscape composition and configuration.

Methods

We simulated movement routes for eight hypothetical species in artificial patchy landscapes with different levels of fragmentation, habitat amount and matrix permeability. We determined the effectiveness of the connectivity umbrella of the virtual species using pairwise intersections of important habitats for their movements in all landscapes.

Results

The connectivity umbrella performance of all species was affected by the interaction of fragmentation level and habitat amount. In general, species performance increased with decreasing fragmentation and increasing habitat amount. In most landscapes and considering the same dispersal threshold, species able to move more easily through the matrix showed higher umbrella performance than those for which the matrix offered greater resistance.

Conclusions

The connectivity umbrella is not a static feature that depends only on the species traits, but rather a dynamic property that also varies according to the landscape attributes. Therefore, we do not recommend spatial transferability of the connectivity umbrella species identified in a landscape to others that have divergent levels of fragmentation and habitat quantity.

     

Connectivity and habitat type shape divergent dispersal behavior in a desert-dwelling fish

Context

Dispersal has important fitness consequences for individuals, populations, and species. Despite growing theoretical insights into the evolution of dispersal, its behavioral underpinnings remain empirically understudied, limiting our understanding of the extent and impact of responses to landscape-level heterogeneity of environments, and increasing the risk of inferring species-level responses from biased population sampling.

Objectives

We asked if predictable ecological variation among naturally fragmented arid waterbodies is correlated with disparate dispersal responses of populations of the desert goby Chlamydogobius eremius, which naturally inhabits two habitat “types” (permanent springs, ephemeral rivers), and different levels of hydrological connectivity (high and low) that potentially convey different costs and benefits of dispersal.

Methods

To test for possible behavioral divergence between such populations, we experimentally compared the movement behaviors (correlates of emigration and exploration) of wild-caught fish. We used two biologically relevant spatial scales to test movement relevant to different stages of the dispersal process.

Results

Behavior differed at both spatial scales, suggesting that alternative dispersal strategies enable desert gobies to exploit diverse habitat patches. However, while emigration was best predicted by the connectivity (flood risk) of fish habitats, exploration was linked to their habitat type (spring versus river).

Conclusions

Our findings demonstrate that despite a complex picture of ecological variation, key landscape factors have an overarching effect on among-population variation in dispersal traits. Implications include the maintenance of within-species variation, potentially divergent evolutionary trajectories of naturally or anthropogenically isolated populations, and the direction of future experimental studies on the ecology and evolution of dispersal behavior.

     

Multi-scale prediction of landscape resistance for tiger dispersal in central India

Context

Connectivity models for animal movement frequently use resistance surfaces, but rarely incorporate actual movement data and multiple scale drivers of landscape resistance.

Objectives

Using GPS data, we developed a multi-scale model of landscape resistance for tiger (Panthera tigris) dispersal in central India and evaluated the performance, interpretation and predictions against single scale models.

Methods

Six dispersing tiger paths were subjected to a path level analysis with conditional logistic regression to parameterize a resistance surface. We evaluated for 21 scales of available habitat and selected the best scale for each variable. We derived a scale-optimized multivariate path selection function and predicted landscape resistance across the landscape.

Results

The tigers preferred to move along areas with forest cover at relatively high elevations along the ridges with rugged topography at broad scale, while avoiding areas with agriculture-village matrix at fine scale. We found that the scale that was most supported by Akaike’s information criterion was not always the scale that maximized the magnitude (effect size) of the relationship. Further, the multi-scale optimized model differed substantially from the single scale models in terms of variable importance, magnitude of coefficients and predictions of connectivity.

Conclusions

Our results demonstrate that the variables in landscape resistance models produce markedly different predictions of population connectivity depending on the scales of analyses and interpretation. Thus, scale optimization in parameterization is critical for appropriate inferences and sound management strategies.

     

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.

     

High value of ecological information for river connectivity restoration

Context

Efficient restoration of longitudinal river connectivity relies on barrier mitigation prioritization tools that incorporate stream network spatial structure to maximize ecological benefits given limited resources. Typically, ecological benefits of barrier mitigation are measured using proxies such as the amount of accessible riverine habitat.

Objectives

We developed an optimization approach for barrier mitigation planning which directly incorporates the ecology of managed taxa, and applied it to an urbanizing salmon-bearing watershed in Alaska.

Methods

A novel river connectivity metric that exploits information on the distribution and movement of managed taxon was embedded into a barrier prioritization framework to identify optimal mitigation actions given limited restoration budgets. The value of ecological information on managed taxa was estimated by comparing costs to achieve restoration targets across alternative barrier prioritization approaches.

Results

Barrier mitigation solutions informed by life history information outperformed those using only river connectivity proxies, demonstrating high value of ecological information for watershed restoration. In our study area, information on salmon ecology was typically valued at 0.8–1.2 M USD in costs savings to achieve a given benefit level relative to solutions derived only from stream network information, equating to 16–28% of the restoration budget.

Conclusions

Investing in ecological studies may achieve win–win outcomes of improved understanding of aquatic ecology and greater watershed restoration efficiency.

     

Influence of separating home range and dispersal movements on characterizing corridors and effective distances

Context

Corridors are usually delineated as areas of minimum cumulative resistance to movement through a resistance surface and characterized by their effective distance (accumulated resistance along the least-cost path). The results of these assessments depend on resistance values, which are typically derived from the inverse of habitat suitability models or from presence data of individuals within their home ranges, rather than from data on dispersal or exploratory movements.

Objective

Evaluate the extent to which corridor delineation and effective distance estimates may vary depending on whether home range locations or dispersal data are used to characterize species habitat selection and landscape resistance to movement.

Methods

We analyzed a large telemetry dataset (GPS collars) for the endangered Iberian lynx. We modeled corridors and effective distances three ways: (1) considering only GPS locations within home ranges, (2) considering only locations in dispersal or exploratory movements outside home ranges, and (3) considering all locations together.

Results

Delineated least-cost corridors followed similar trajectories and sometimes overlapped in the three models. The estimated effective distances were 42 % lower in the dispersal-based model than in the model based solely on home range use.

Conclusions

Models derived exclusively from locations within home ranges may provide lower connectivity estimates than models derived from dispersal locations, affecting estimates of resistance to move between habitat areas, even when the most likely movement routes are similar. Although dispersal data are costly to gather, they potentially provide more realistic assessments of the actual isolation of populations in heterogeneous landscapes.

     

A multi-scale assessment of population connectivity in African lions (<Emphasis Type="Italic">Panthera leo)</Emphasis> in response to landscape change

Context

Habitat loss and fragmentation are among the major drivers of population declines and extinction, particularly in large carnivores. Connectivity models provide practical tools for assessing fragmentation effects and developing mitigation or conservation responses. To be useful to conservation practitioners, connectivity models need to incorporate multiple scales and include realistic scenarios based on potential changes to habitat and anthropogenic pressures. This will help to prioritize conservation efforts in a changing landscape.

Objectives

The goal of our paper was to evaluate differences in population connectivity for lions (Panthera leo) across the Kavango-Zambezi Trans-frontier Conservation Area (KAZA) under different landscape change scenarios and a range of dispersal distances.

Methods

We used an empirically optimized resistance surface, based on analysis of movement pathways of dispersing lions in southern Africa to calculate resistant kernel connectivity. We assessed changes in connectivity across nine landscape change scenarios, under each of which we explored the behavior of lions with eight different dispersal abilities.

Results

Our results demonstrate that reductions in the extent of the protected area network and/or fencing protected areas will result in large declines in the extent of population connectivity, across all modeled dispersal abilities. Creation of corridors or erection of fences strategically placed to funnel dispersers between protected areas increased overall connectivity of the population.

Conclusions

Our results strongly suggest that the most effective means of maintaining long-term population connectivity of lions in the KAZA region involves retaining the current protected area network, augmented with protected corridors or strategic fencing to direct dispersing individuals towards suitable habitat and away from potential conflict areas.

     

A bird’s eye view: using circuit theory to study urban landscape connectivity for birds

Context

Connectivity is fundamental to understanding how landscape form influences ecological function. However, uncertainties persist due to the difficulty and expense of gathering empirical data to drive or to validate connectivity models, especially in urban areas, where relationships are multifaceted and the habitat matrix cannot be considered to be binary.

Objectives

This research used circuit theory to model urban bird flows (i.e. ‘current’), and compared results to observed abundance. The aims were to explore the ability of this approach to predict wildlife flows and to test relationships between modelled connectivity and variation in abundance.

Methods

Circuitscape was used to model functional connectivity in Bedford, Luton/Dunstable, and Milton Keynes, UK, for great tits (Parus major) and blue tits (Cyanistes caeruleus), drawing parameters from published studies of woodland bird flows in urban environments. Model performance was then tested against observed abundance data.

Results

Modelled current showed a weak yet positive agreement with combined abundance for P. major and C. caeruleus. Weaker correlations were found for other woodland species, suggesting the approach may be expandable if re-parameterised.

Conclusions

Trees provide suitable habitat for urban woodland bird species, but their location in large, contiguous patches and corridors along barriers also facilitates connectivity networks throughout the urban matrix. Urban connectivity studies are well-served by the advantages of circuit theory approaches, and benefit from the empirical study of wildlife flows in these landscapes to parameterise this type of modelling more explicitly. Such results can prove informative and beneficial in designing urban green space and new developments.

     

Dynamic surface water distributions influence wetland connectivity within a highly modified interior landscape

Context

Animal movements are inherently linked to landscape structure. Understanding this relationship for highly-mobile species requires documenting their responses to spatiotemporal variability of resources. To that end, characterizing movement behaviors and resource distributions using the principles of habitat connectivity facilitates coordinated landscape planning efforts within highly modified landscapes.

Objectives and methods

We tracked locations and movements for 156 dunlin (Calidris alpina) and 109 long-billed dowitchers (Limnodromus scolopaceus) overwintering in two regions with distinct water distributions in California’s Central Valley. We then compared residency rates, functional connectivity to other regions, and associations between movement distances and average habitat availability and structural connectivity of habitat at multiple temporal and spatial scales.

Results

A widespread yet highly variable regional water distribution was associated with lower residency rates and substantially higher functional connectivity to nearby regions when compared to a stable regional water distribution characterized by a large, contiguous wetland complex. Longer movements were associated with decreasing average availability and spatial aggregation of surface water. Movement models suggested shorebirds primarily responded to habitat availability at smaller scales (<?10 km) and structural connectivity at larger scales (≥?10 km).

Conclusions

Differences in movement behaviors suggested that wintering shorebirds will avoid long distance movements and remain resident within a wetland region when possible. Conservation and management efforts should reliably flood individual wetlands and agricultural lands from November to April and prioritize locations that maximize structural wetland connectivity and limit spatiotemporal variability of surface water throughout the Central Valley.

     

Enhancing connectivity in agroecosystems: focus on the best existing corridors or on new pathways?

Context

Restoring or establishing corridors between residual forest patches is one of the most adopted strategies for the conservation of animal populations and ecosystem processes in fragmented landscapes.

Objectives

This study aimed to assess whether it is more effective to focus restoration actions on existing corridors or to establish habitats in other strategic areas that can create new dispersal pathways to enhance connectivity.

Methods

We considered a real agroecosystem in northern Italy, based our analyses on graph-theory and habitat availability metrics, and focused on the Hazel Dormouse as the target species. We compared the connectivity increase resulting from (i) the simulated restoration of existing priority corridors, i.e., those with significant presence of forest but in which restoration actions would still result in considerable connectivity gains, or (ii) the simulated plantation of 30 hedgerows along new priority pathways, i.e., those areas with no current forest cover in which habitat creation would be more beneficial for connectivity.

Results

Implementing new priority pathways resulted in substantially larger connectivity gains (+?38%) than when restoration efforts were concentrated in improving already existing corridors (+?11%).

Conclusions

Establishing hedgerows along new pathways allowed enhancing the complementary and functionality of the full set of landscape corridors and proved more efficient than just strengthening the areas where dispersal flows were already concentrated. We demonstrated the importance of analytical procedures able to compare the effectiveness of different management strategies for enhancing connectivity. Our approach may be applied to multiple species sensitive to fragmentation in other heterogeneous landscapes and geographical contexts.

     

Evaluating static and dynamic landscape connectivity modelling using a 25-year remote sensing time series

Context

Despite calls for landscape connectivity research to account for spatiotemporal dynamics, studies have overwhelmingly evaluated the importance of habitats for connectivity at single or limited moments in time. Remote sensing time series represent a promising resource for studying connectivity within dynamic ecosystems. However, there is a critical need to assess how static and dynamic landscape connectivity modelling approaches compare for prioritising habitats for conservation within dynamic environments.

Objectives

To assess whether static landscape connectivity analyses can identify similar important areas for connectivity as analyses based on dynamic remotely sensed time series data.

Methods

We compared degree and betweenness centrality graph theory metric distributions from four static scenarios against equivalent results from a dynamic 25-year remotely sensed surface-water time series. Metrics were compared at multiple spatial aggregation scales across south-eastern Australia’s 1 million km² semi-arid Murray–Darling Basin and three sub-regions with varying levels of hydroclimatic variability and development.

Results

We revealed large differences between static and dynamic connectivity metric distributions that varied by static scenario, region, spatial scale and hydroclimatic conditions. Static and dynamic metrics showed particularly low overlap within unregulated and spatiotemporally variable regions, although similarities increased at coarse aggregation scales.

Conclusions

In regions that exhibit high spatiotemporal variability, static connectivity modelling approaches are unlikely to serve as effective surrogates for more data intensive approaches based on dynamic, remotely sensed data. Although this limitation may be moderated by spatially aggregating static connectivity outputs, our results highlight the value of remotely sensed time series for assessing connectivity in dynamic landscapes.

     

A multi-species approach for assessing the impact of land-cover changes on landscape connectivity

Context

Land-cover changes (LCCs) could impact wildlife populations through gains or losses of natural habitats and changes in the landscape mosaic. To assess such impacts, we need to focus on landscape connectivity from a diachronic perspective.

Objectives

We propose a method for assessing the impact of LCCs on landscape connectivity through a multi-species approach based on graph theory. To do this, we combine two approaches devised to spatialize the variation of multi-species connectivity and to quantify the importance of types of LCCs for single-species connectivity by highlighting the possible contradictory effects.

Methods

We begin with a list of landscape species and create virtual species with similar ecological requirements. We model the ecological network of these virtual species at two dates and compute the variation of a local and global connectivity metric to assess the impacts of the LCCs on their dispersal capacities.

Results

The spatial variation of multi-species connectivity showed that local impacts range from ?6.4% to +3.2%. The assessment of the impacts of types of LCCs showed a variation in global connectivity ranging from ?45.1% for open-area reptiles to +170.2% for natural open-area birds with low-dispersion capacities.

Conclusions

This generic approach can be reproduced in a large variety of spatial contexts by adapting the selection of the initial species. The proposed method could inform and guide conservation actions and landscape management strategies so as to enhance or maintain connectivity for species at a landscape scale.

     

Spatial configuration becomes more important with increasing habitat loss: a simulation study of environmentally-transmitted parasites

Context

Landscape changes can be an important modifier of disease. Habitat fragmentation commonly results in reduced connectivity in host populations and increased use of the remaining habitat. For environmentally transmitted parasites, this presents a possible trade-off between transmission potential at the local and global level.

Objectives

We quantify the effects of fragmentation on the transmission of an environmentally transmitted parasite, teasing apart the relative effects of habitat composition and configuration on both host movement behaviour and subsequent infection patterns.

Methods

We use a spatially-explicit epidemiological model to simulate the effects of habitat fragmentation, using, as an example, whipworm (Trichuris sp.) within a red colobus monkey population (Procolobus rufomitratus).

Results

We found that habitat fragmentation did not always lead to a trade-off between population connectivity and concentration of habitat use in host movement behaviour or in final population infection patterns. However, our simulation results suggest the spatial configuration of the remaining habitat became increasingly influential on behavioural and infection outcomes as habitat was removed. Additionally, we found common fragmentation metrics provided little ability to explain variation in propagation of infections.

Conclusions

Our results suggest an interaction between habitat configuration and composition should be considered when assessing disease related impacts of habitat fragmentation on environmentally transmitted parasites, especially in cases where habitat loss is high (≥?30%). We also propose that spatially-explicit simulations that capture a host’s response to fragmentation could aid in the development of novel landscape metrics targeted towards specific host-parasite-landscape systems.

     

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.