Modeling configuration dynamics of harvested forest landscapes in the Canadian boreal plains

Habitat configuration has important implications for the persistence of faunal and floral populations at a variety of spatial scales. Forest harvesting alters habitat configurations. However, measuring and predicting such alterations remains challenging, in part because previously developed metrics of habitat configuration are often not statistically independent of habitat amount. Thus, their ability to measure independent effects of habitat configurations and habitat amount on ecosystem components such as wildlife populations has been limited. Here, we evaluate habitat configuration based on newly developed metrics that are independent of habitat amount but do not depend on regression residuals of abundance and configuration relationships on any population of landscapes. We use these new metrics to measure and predict changes in habitat configuration following forest harvesting in the boreal forest of Alberta, Canada. Our findings clearly demonstrate changes in habitat configuration resulting from forest harvesting can be predicted precisely with information about initial habitat patch structure and harvesting patterns. Because forest harvesting has significant implications for habitat configuration, accurately predicting these changes is critical for determining if forest harvesting strategies are sustainable for ecosystem components and processes. This study provides a set of novel, robust metrics for tracking landscape-scale changes in habitat configuration in harvested boreal forests.     

The sensitivity of least-cost habitat graphs to relative cost surface values

Maintaining and restoring connectivity among high-quality habitat patches is recognized as an important goal for the conservation of animal populations. To provide an efficient measure of potential connectivity pathways in heterogeneous landscapes, least-cost route analysis has been combined with graph-theoretical techniques. In this study we use spatially explicit least-cost habitat graphs to examine how matrix quality and spatial configuration influence assessments of habitat connectivity. We generated artificial landscapes comprised of three landcover types ranked consistently from low to high quality: inhospitable matrix, hospitable matrix, and habitat. We controlled the area and degree of fragmentation of each landcover in a factorial experiment for a total of 20 combinations replicated 100 times. In each landscape we compared eight sets of relative landcover qualities (cost values of 1 for habitat, between 1.5 and 150 for hospitable matrix, and 3–10,000 for inhospitable matrix). We found that the spatial location of least-cost routes was sensitive to differences in relative cost values assigned to landcover types and that the degree of sensitivity depended on the spatial structure of the landscape. Highest sensitivity was found in landscapes with fragmented habitat and between 20 and 50% hospitable matrix; sensitivity decreased as habitat fragmentation decreased and the amount of hospitable matrix increased. As a means of coping with this sensitivity, we propose identifying multiple low-cost routes between pairs of habitat patches that collectively delineate probable movement zones. These probable movement zones account for uncertainty in least-cost routes and may be more robust to variation in landcover cost values.     

Using network theory to prioritize management in a desert bighorn sheep metapopulation

Connectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.     

Measuring landscape connectivity: On the importance of within-patch connectivity

Context

Many connectivity metrics have been used to measure the connectivity of a landscape and to evaluate the effects of land-use changes and potential mitigation measures. However, there are still gaps in our understanding of how to accurately quantify landscape connectivity.

Objectives

A number of metrics only measure between-patch connectivity, i.e. the connectivity between different habitat patches, which can produce misleading results. This paper demonstrates that the inclusion of within-patch connectivity is important for accurate results.

Methods

The behavior of two metrics is compared: the Connectance Index (CONNECT), which measures only between-patch connectivity, and the effective mesh size (m_eff), which includes both within-patch and between-patch connectivity. The connectivity values of both metrics were calculated on a set of simulated landscapes. Twenty cities were then added to these landscapes to calculate the resulting changes in connectivity.

Results

We found that when using CONNECT counter-intuitive results occurred due to not including within-patch connectivity, such as scenarios where connectivity increased with increasing habitat loss and fragmentation. These counter-intuitive results were resolved when using m_eff. For example, landscapes with low habitat amount may be particularly sensitive to urban development, but this is not reflected by CONNECT.

Conclusions

Applying misleading results from metrics like CONNECT can have detrimental effects on natural ecosystems, because reductions in within-patch connectivity by human activities are neglected. Therefore, this paper provides evidence for the crucial need to consider the balance between within-patch connectivity and between-patch connectivity when calculating the connectivity of landscapes.

     

Quantifying landscape connectivity through the use of connectivity response curves

Habitat connectivity is an essential component of biodiversity conservation. Simulated landscapes were manipulated to quantify the impact of changes to the amount, fragmentation and dispersion of habitat on a widely applied landscape connectivity metric, the probability of connectivity index. Index results for different landscape scenarios were plotted against the dispersal distances used for their calculation to create connectivity response curves for each scenario. Understanding index response to controlled changes in landscape structure at a range of spatial scales can be used to give context to comparison of alternative landscape management scenarios. Increased amounts of habitat, decreased fragmentation and decreased inter-patch distances resulted in increased connectivity index values. Connectivity response curves demonstrated increases in assessed connectivity for scenarios with continuous corridors or “stepping stone” connectors. The sensitivity of connectivity response curves to controlled changes in landscape structure indicate that this approach is able to detect and distinguish between different types of landscape changes, but that delineation of habitat and method of quantifying dispersal probability incorporate assumptions that must be recognized when interpreting results to guide landscape management. Representing landscape connectivity in this manner allows for the impacts of alternative landscape management strategies to be compared visually through comparative plots, or statistically through the parameters that describe connectivity response curves.     

How should we measure landscape connectivity?

The methods for measuring landscape connectivity have never been compared or tested for their responses to habitat fragmentation. We simulated movement, mortality and boundary reactions across a wide range of landscape structures to analyze the response of landscape connectivity measures to habitat fragmentation. Landscape connectivity was measured as either dispersal success or search time, based on immigration into all habitat patches in the landscape. Both measures indicated higher connectivity in more fragmented landscapes, a potential for problematic conclusions for conservation plans. We introduce cell immigration as a new measure for landscape connectivity. Cell immigration is the rate of immigration into equal-sized habitat cells in the landscape. It includes both within- and between-patch movement, and shows a negative response to habitat fragmentation. This complies with intuition and existing theoretical work. This method for measuring connectivity is highly robust to reductions in sample size (i.e., number of habitat cells included in the estimate), and we hypothesize that it therefore should be amenable to use in empirical studies. The connectivity measures were weakly correlated to each other and are therefore generally not comparable. We also tested immigration into a single patch as an index of connectivity by comparing it to cell immigration over the landscape. This is essentially a comparison between patch-scale and landscape-scale measurement, and revealed some potential for patch immigration to predict connectivity at the landscape scale. However, this relationship depends on the size of the single patch, the dispersal characteristics of the species, and the amount of habitat in the landscape. We conclude that the response of connectivity measures to habitat fragmentation should be understood before deriving conclusions for conservation management.     

Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation

The loss of connectivity of natural areas is a major threat for wildlife dispersal and survival and for the conservation of biodiversity in general. Thus, there is an increasing interest in considering connectivity in landscape planning and habitat conservation. In this context, graph structures have been shown to be a powerful and effective way of both representing the landscape pattern as a network and performing complex analysis regarding landscape connectivity. Many indices have been used for connectivity analyses so far but comparatively very little efforts have been made to understand their behaviour and sensitivity to spatial changes, which seriously undermines their adequate interpretation and usefulness. We systematically compare a set of ten graph-based connectivity indices, evaluating their reaction to different types of change that can occur in the landscape (habitat patches loss, corridors loss, etc.) and their effectiveness for identifying which landscape elements are more critical for habitat conservation. Many of the available indices were found to present serious limitations that make them inadequate as a basis for conservation planning. We present a new index (IIC) that achieves all the properties of an ideal index according to our analysis. We suggest that the connectivity problem should be considered within the wider concept of habitat availability, which considers a habitat patch itself as a space where connectivity exists, integrating habitat amount and connectivity between habitat patches in a single measure.     

Measuring landscape configuration with normalized metrics

Natural and anthropogenic disturbances on natural landscapes reduce the abundance and alter the spatial arrangement of certain habitat types. Measuring and modeling such alterations, and their biological effects, remains challenging in part because many widely used configuration metrics are correlated with habitat amount. In this paper, we consider the sources of such correlation, and distinguish process or sample-based correlation from functional correlation that may be an artifact of the metrics themselves. Process correlation is not necessarily a serious problem for statistical inference, but functional correlation would be. We propose that functional correlation may be reduced by normalizing metrics by habitat abundance. We illustrate with normalized versions of total core area, mean nearest neighbor distance, and mean shape index, and show informally that the standard versions of these metrics should exhibit functional correlation. We evaluate the normalized metrics on samples of harvested and undisturbed forested landscapes, and on simulated landscapes generated with varying degrees of spatial autocorrelation. Normalization markedly reduced correlations with habitat abundance on natural landscapes, but not on simulated landscapes. The reasons for this appear to be a combination of differing variances in metric values within levels of habitat abundance, and of the precise form of the relationships between habitat abundance and the un-normalized metrics. In all cases, the normalization changes the ordering of landscapes by metric values across levels of habitat abundance. In consequence, normalized and standard metrics cannot both be accurate measures of configuration. We conclude that statistical modeling of ecological response data is needed to finally determine the merits of the normalizations.     

Modeling occupancy dynamics of a rare species,Franklin’s ground squirrel,with limited data: are simple connectivity metrics adequate?

Conservation of populations in fragmented habitats is often based on spatially realistic metapopulation theory, which predicts negative relationships between patch extinction and area and patch colonization and isolation. Cost-distance metrics have been developed to integrate habitat quality into measures of connectivity, and thus may improve predictive power of the area-isolation paradigm. Few studies use empirical data to compare predictive performance of complex cost-distance metrics to simple metrics relying on Euclidean distances. We used 3 years of presence–absence data to examine relative influence of habitat quality, habitat area, and connectivity on occupancy and extinction rates for Poliocitellus franklinii (Franklin’s ground squirrel), a rare grassland species of conservation concern. We calculated connectivity using nearest-neighbor (NN) and incidence function model (IFM) metrics based on Euclidean and cost-distances. Habitat quality, area, and connectivity were all positive predictors for occupancy, but only isolation was a positive predictor of extinction. P. franklinii does not appear to be a tallgrass prairie obligate, but the species distribution is limited by isolation of suitable grassland habitat. A simple NN metric measuring Euclidean distance between a target area and nearest occupied source outperformed IFM (Euclidean and cost-distance) in predicting occupancy and extinction for P. franklinii. Although NN metrics are criticized for considering only the contribution of the source nearest to a target, this simplicity may be acceptable when measuring connectivity for rare species with few occupied habitat patches within dispersal distance.     

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.

     

A comparison of metrics predicting landscape connectivity for a highly interactive species along an urban gradient in Colorado, USA

Many organisms persist in fragmented habitat where movement between patches is essential for long-term demographic and genetic stability. In the absence of direct observation of movement, connectivity or isolation metrics are useful to characterize potential patch-level connectivity. However, multiple metrics exist at varying levels of complexity, and empirical data on species distribution are rarely used to compare performance of metrics. We compared 12 connectivity metrics of varying degrees of complexity to determine which metric best predicts the distribution of prairie dog colonies along an urban gradient of 385 isolated habitat patches in Denver, Colorado, USA. We found that a modified version of the incidence function model including area-weighting of patches and a cost-weighted distance surface best predicted occupancy, where we assumed roads were fairly impermeable to movement, and low-lying drainages provided dispersal corridors. We also found this result to be robust to a range of cost weight parameters. Our results suggest that metrics should incorporate both patch area and the composition of the surrounding matrix. These results provide guidance for improved landscape habitat modeling in fragmented landscapes and can help identify target habitat for conservation and management of prairie dogs in urban systems.     

Landscape connectivity and animal behavior: functional grain as a key determinant for dispersal

Landscape connectivity can be viewed from two perspectives that could be considered as extremes of a gradient: functional connectivity (refers to how the behavior of a dispersing organism is affected by landscape structure and elements) and structural connectivity (depends on the spatial configuration of habitat patches in the landscape like vicinity or presence of barriers). Here we argue that dispersal behavior changes with landscape configuration stressing the evolutionary dimension that has often been ignored in landscape ecology. Our working hypothesis is that the functional grain of resource patches in the landscape is a crucial factor shaping individual movements, and therefore influencing landscape connectivity. Such changes are likely to occur on the short-term (some generations). We review empirical studies comparing dispersal behavior in landscapes differing in their fragmentation level, i.e., with variable resource grain. We show that behavioral variation affecting each of the three stages of the dispersal process (emigration, displacement or transfer in the matrix, and immigration) is indeed likely to occur according to selective pressures resulting from changes in the grain of the landscape (mortality or deferred costs). Accordingly, landscape connectivity results from the interaction between the dispersal behavior of individuals and the grain of each particular landscape. The existence of this interaction requires that connectivity estimates (being based on individual-based models, least cost distance algorithms, and structural connectivity metrics or even Euclidian distance) should be carefully evaluated for their applicability with respect to the required level of precision in species-specific and landscape information.     

Using patch isolation metrics to predict animal movement in binary landscapes

Habitat isolation can affect the distribution and abundance of wildlife, but it is an ambiguous attribute to measure. Presumably, isolation is a characteristic of a habitat patch that reflects how spatially inaccessible it is to dispersing organisms. We identified four isolation metrics (nearest-neighbor distance, Voronoi polygons, proximity index, and habitat buffers) that were representative of the different families of metrics that are commonly used in the literature to measure patch isolation. Using simulated data, we evaluated the ability of each isolation metric to predict animal dispersal. We examined the simulated movement of organisms in two types of landscapes: an artificially-generated point-pattern landscapes where patch size and shape were consistent and only the arrangement of patches varied, and realistic landscapes derived from a geographic information system (GIS) of forest-vegetation maps where patch size, shape, and isolation were variable. We tested the performance of the four isolation metrics by examining the strength of the correlation between observed immigration rate in the simulations and each patch isolation metric. We also evaluated whether each isolation metric would perform consistently under varying conditions of patch size/shape, total amount of habitat in the landscape, and proximity of the patch to the landscape edge. The results indicate that a commonly-used distance-based metric, nearest-neighbor distance, did not adequately predict immigration rate when patch size and shape were variable. Area-informed isolation metrics, such as the amount of available habitat within a given radius of a patch, were most successful at predicting immigration. Overall, the use of area-informed metrics is advocated despite the limitation that these metrics require parameterization to reflect the movement capacity of the organism studied.This revised version was published online in May 2005 with corrections to the Cover Date.     

Role of green roofs in urban connectivity,an exploratory approach using landscape graphs in the city of Paris,France

Green roofs provide many ecosystem services, but little is known about the way they contribute to urban functional connectivity. This paper has the following four objectives: (1) to compare the potential green roofs’ role to connectivity in relation to other urban green spaces, (2) to specify the green roofs contribution’s type, (3) to explore the influence of building height integration method and finally (4) to assess the impact on connectivity of simulated greening new roofs. Using a landscape graph approach, we modeled ecological networks of three species groups with different dispersion capacities in the Paris region (France). Then, we computed several connectivity metrics to assess the potential contribution of green roofs to functional connectivity. At a large scale (metropole scale), our results show that green roofs can slightly improve the global connectivity largely through the connections rather than the addition of habitat area. More than a stepping stone function, green roofs would have a dispersion flux function at a local scale. Furthermore, when the difficulty of crossing movement is exponential to the height of buildings, green roofs over 20 m high are mostly disconnected from the ecological networks. In addition to the green roof’s height, our analysis highlights the very strong role played by buildings’ configuration. This study raises promising directions for the integration of building height into the analysis of urban connectivity. Detailed research and long-term biological data from green roofs and green spaces are needed to confirm our results.     

Targeting and evaluating biodiversity conservation action within fragmented landscapes: an approach based on generic focal species and least-cost networks

The focus of biodiversity conservation is shifting to larger spatial scales in response to habitat fragmentation and the need to integrate multiple landscape objectives. Conservation strategies increasingly incorporate measures to combat fragmentation such as ecological networks. These are often based on assessment of landscape structure but such approaches fail to capitalise on the potential offered by more ecologically robust assessments of landscape function and connectivity. In this paper, we describe a modelling approach to identifying functional habitat networks and demonstrate its application to a fragmented landscape where policy initiatives seek to improve conditions for woodland biodiversity including increasing woodland cover. Functional habitat networks were defined by identifying suitable habitat and by modelling connectivity using least-cost approaches to account for matrix permeability. Generic focal species (GFS) profiles were developed, in consultation with stakeholders, to represent species with high and moderate sensitivity to fragmentation. We demonstrated how this form of analysis can be used to aid the spatial targeting of conservation actions. This ‘targeted’ action scenario was tested for effectiveness against comparable scenarios, which were based on random and clumped actions within the same landscape. We tested effectiveness using structural metrics, network-based metrics and a published functional connectivity indicator. Targeting actions within networks resulted in the highest mean woodland area and highest connectivity indicator value. Our approach provides an assessment of landscape function by recognising the importance of the landscape matrix. It provides a framework for the targeting and evaluation of alternative conservation options, offering a pragmatic, ecologically-robust solution to a current need in applied landscape ecology.     

Dispersal success on fractal landscapes: a consequence of lacunarity thresholds

Habitat fragmentation is expected to disrupt dispersal, and thus we explored how patch metrics of landscape structure, such as percolation thresholds used to define landscape connectivity, corresponded with dispersal success on neutral landscapes. We simulated dispersal as either a purely random process (random direction and random step lengths) or as an area-limited random walk (random direction, but movement limited to an adjacent cell at each dispersal step) and quantified dispersal success for 1000 individuals on random and fractal landscape maps across a range of habitat abundance and fragmentation. Dispersal success increased with the number of cells a disperser could search (m), but poor dispersers (m<5) searching via area-limited dispersal on fractal landscapes were more successful at locating suitable habitat than random dispersers on either random or fractal landscapes. Dispersal success was enhanced on fractal landscapes relative to random ones because of the greater spatial contagion of habitat. Dispersal success decreased proportionate to habitat loss for poor dispersers (m=1) on random landscapes, but exhibited an abrupt threshold at low levels of habitat abundance (p<0.1) for area-limited dispersers (m<10) on fractal landscapes. Conventional metrics of patch structure, including percolation, did not exhibit threshold behavior in the region of the dispersal threshold. A lacunarity analysis of the gap structure of landscape patterns, however, revealed a strong threshold in the variability of gap sizes at low levels of habitat abundance (p<0.1) in fractal landscapes, the same region in which abrupt declines in dispersal success were observed. The interpatch distances or gaps across which dispersers must move in search of suitable habitat should influence dispersal success, and our results suggest that there is a critical gap-size structure to fractal landscapes that interferes with the ability of dispersers to locate suitable habitat when habitat is rare. We suggest that the gap structure of landscapes is a more important determinant of dispersal than patch structure, although both are ultimately required to predict the ecological consequences of habitat fragmentation.     

Habitat connectivity for pollinator beetles using surface metrics

Measuring habitat connectivity in complex landscapes is a major focus of landscape ecology and conservation research. Most studies use a binary landscape or patch mosaic model for describing spatial heterogeneity and understanding pattern-process relationships. While the value of landscape gradient approaches proposed by McGarigal and Cushman are recognized, applications of these newly proposed three dimensional surface metrics remain under-used. We created a gradient map of habitat quality from several GIS layers and applied three dimensional surface metrics to measure connectivity between 67 locations in Indiana, USA surveyed for one group of ecosystem service providers, flower longicorn beetles (Cerambycidae: Lepturinae). The three dimensional surface metrics applied to the landscape gradient model showed great potential to explain the differences of lepturine assemblages among the 2,211 studied landscapes (between site pairs). Surface kurtosis and its interaction with geographic distance were among the most important metrics. This approach provided unique information about the landscape through four configuration metrics. There were some uniform trends of the responses of many species to some of surface metrics, however some species responded differently to other metrics. We suggest that three dimensional surface metrics applied to a habitat surface map created with insight into species requirements is a valuable approach to understanding the spatial dynamics of species, guilds, and ecosystem services.     

Interactive effects of area and connectivity on the diversity of tachinid parasitoids in highly fragmented landscapes

Although many empirical and theoretical studies have elucidated the effects of habitat fragmentation on the third trophic level, little attention has been paid to the impacts of this driver on more generalist groups of non-hymenopteran parasitoids. Here, we used the highly-diverse group of tachinid flies as an alternative model to test the effects of landscape fragmentation on insect parasitoids. Our aims were: (i) to evaluate the relative importance of habitat area and connectivity losses and their potential interaction on tachinid diversity, (ii) to test whether the effects of habitat fragmentation changes seasonally, and (iii) to further assess the effect of habitat diversity on tachinid diversity and whether different parasitoid-host associations modify the species richness response to fragmentation. In 2012 a pan-trap sampling was conducted in 18 semi-natural grasslands embedded in intensive agricultural landscapes along statistically orthogonal gradients of habitat area, connectivity and habitat diversity. We found an interaction between habitat area and connectivity indicating that tachinid abundance and species richness were more negatively affected by habitat loss in landscapes with low rather than with relatively large habitat connectivity. Although tachinid communities exhibited large within-year species turnover, we found that the effects of landscape fragmentation did not change seasonally. We found that habitat diversity and host association did not affect tachinid species diversity. Our results have important implications for biodiversity conservation as any attempts to mitigate the negative effects of habitat loss need to take the general level of habitat connectivity in the landscape into account.     

Connectivity providers for semi-aquatic vertebrates: the case of the endangered otter in Italy

Modeling habitat connectivity for conservation of semi-aquatic vertebrates is a particularly challenging task, due to the fine-scale and linear distribution of riverine habitats and to the capacity of species to move both on freshwater and terrestrial realms. We showed how the integrated analytical framework provided by the habitat availability (reachability) metrics and their fractions can be used to effectively evaluate the distinctive roles and contributions of both habitat patches (aquatic and riparian) and linkage areas (permeable land matrix) to the connectivity and functioning of a complex system composed of multiple river catchments. Analysis focused on the Eurasian otter (Lutra lutra L.), one of the most endangered mammals in Italy. We developed a network connectivity model based on suitable otter habitats and multiple least-cost paths between catchments. A graph analytical approach was used to identify critical nodes and links for the potential expansion and long-term viability of the species in the region. Our results showed that few basins concentrate most of the importance for sustaining the overall habitat connectivity, due to the extension of suitable habitats they contain, their strong connections with other basins, and their importance as stepping stones that uphold ecological fluxes between otherwise weakly connected habitats. The potential contribution of each basin to enhance the dispersal and expansion of otters in the area strongly depended on the key functional paths (sequences of links and nodes) among the catchments. We identified vacant basins that could be colonized by otters in the near future, and connecting areas in the intermediate matrix that might be preferentially used to conduct and promote dispersal movements and gene flow in the area. The novel approach here adopted could be easily extended to other semiaquatic species and catchment systems, offering a management strategy to preserve the hydrographic network as an integrated system, as well as a joint evaluation of the role of both the river courses and the matrix in between in a single landscape model.     

Integrating graph-based connectivity metrics into species distribution models

Species distribution models (SDMs) are commonly used in ecology to map the probability of species occurrence on the basis of predictive factors describing the physical environment. We propose an improvement on SDMs by using graph methods to quantify landscape connectivity. After (1) mapping the habitat suitable for a given species, this approach consists in (2) building a landscape graph, (3) computing patch-based connectivity metrics, (4) extrapolating the values of those metrics to any point of space, and (5) integrating those connectivity metrics into a predictive model of presence. For a given species, this method can be used to interpret the significance of the metrics in the models in terms of population structure. The method is illustrated here by the construction of an SDM for the European tree frog in the region of Franche-Comté (France). The results show that the connectivity metrics improve the explanatory power of the SDM and emphasize the important role of the habitat network.