Circuit theory emphasizes the importance of edge-crossing decisions in dispersal-scale movements of a forest passerine

Measuring landscape connectivity in ways that reflect an animal’s propensity or reluctance to move across a given landscape is key for planning effective conservation strategies. Resistance distance, based on circuit theory, is one such measure relevant for modeling how broad-scale animal movements over long time periods may lead to gene flow across the landscape. Despite the success of circuit theory in landscape genetic studies, its applicability to model finer-scale processes such as the movement patterns of individual animals within their breeding grounds (e.g., while prospecting for territories) has yet to be tested. Here, we applied both circuit models and least-cost models to understand the relationship between landscape connectivity and return time of Ovenbirds (Seiurus aurocapilla) that had been translocated at least 20 km from their home territory near Québec City, Canada. Using an iterative optimization process, we derived resistance values for three cover types (forest, edge, and open) that resulted in resistance distance values that best explained Ovenbird return times. We also identified the cover-type resistance values that yielded length of least-cost path estimates that best explained return times of the translocated birds. The circuit theory and least-cost path methods were equally supported by the data despite being based on different sets of resistance values. The optimal resistance values for calculating resistance distance indicated that for Ovenbirds, traversing a given distance of edge habitat presented a substantially greater resistance than that of open areas. On the other hand, optimized resistances of edge and open were very similar for calculating length of least-cost path. The circuit theory approach suggested that for an Ovenbird moving through fragmented habitat, the number of forest-open transitions (i.e., edge-crossings) that an individual must make is critical to understanding return times after translocation. The least-cost path approach, on the other hand, suggested that the birds strongly avoid all open areas, regardless of size. Circuit theory offers an important new approach for understanding landscapes from the perspective of individuals moving within their breeding range, at finer spatial scales and shorter time scales than have been previously considered.     

Genetic isolation by distance and landscape connectivity in the American marten (Martes americana)

Empirical studies of landscape connectivity are limited by the difficulty of directly measuring animal movement. ‘Indirect’ approaches involving genetic analyses provide a complementary tool to ‘direct’ methods such as capture–recapture or radio-tracking. Here the effect of landscape on dispersal was investigated in a forest-dwelling species, the American marten (Martes americana) using the genetic model of isolation by distance (IBD). This model assumes isotropic dispersal in a homogeneous environment and is characterized by increasing genetic differentiation among individuals separated by increasing geographic distances. The effect of landscape features on this genetic pattern was used to test for a departure from spatially homogeneous dispersal. This study was conducted on two populations in homogeneous vs. heterogeneous habitat in a harvested boreal forest in Ontario (Canada). A pattern of IBD was evidenced in the homogeneous landscape whereas no such pattern was found in the near-by harvested forest. To test whether landscape structure may be accountable for this difference, we used effective distances that take into account the effect of landscape features on marten movement instead of Euclidean distances in the model of isolation by distance. Effective distances computed using least-cost modeling were better correlated to genetic distances in both landscapes, thereby showing that the interaction between landscape features and dispersal in Martes americana may be detected through individual-based analyses of spatial genetic structure. However, the simplifying assumptions of genetic models and the low proportions in genetic differentiation explained by these models may limit their utility in quantifying the effect of landscape structure.     

Landscape resistance and American marten gene flow

Landscape heterogeneity can influence animal dispersal by causing a directional bias in dispersal rate, as certain landscape configurations might promote, impede, or prevent movement and gene flow. In forested landscapes, logging operations often contribute to heterogeneity that can reduce functional connectivity for some species. American martens (Martes americana) are one such species, as they are considered specialists of late-seral coniferous forests. We assessed marten gene flow to test the hypothesis that habitat management has maintained landscape connectivity for martens in the managed forests of Ontario, Canada. We genotyped 653 martens at 12 microsatellite loci, sampled from 29 sites across Ontario. We expected that if forest management has an effect on marten gene flow, we would see a correlation between effective resistance, estimated by circuit theory, and genetic distance, estimated by population graphs. Although we found a positive relationship between effective resistance and genetic distance (Mantel r = 0.249, P < 0.001), marten gene flow was better described by isolation by Euclidean distance (Mantel r = 0.410, P < 0.001). Our results suggest that managed forests in Ontario are well connected for marten and neither impede nor promote marten gene flow at the provincial scale.     

Independent effects of connectivity predict homing success by northern flying squirrel in a forest mosaic

Landscape composition and configuration, often termed as habitat loss and fragmentation, are predicted to reduce species population viability, partly due to the restriction of movement in the landscape. Unfortunately, measuring the effects of habitat loss and fragmentation on functional connectivity is challenging because these variables are confounded, and often the motivation for movement by target species is unknown. Our objective was to determine the independent effects of landscape connectivity from the perspective of a mature forest specialist—the northern flying squirrel (Glaucomys sabrinus). To standardize movement motivation, we translocated 119 squirrels, at varying distances (0.18–3.8 km) from their home range across landscapes representing gradients in both habitat loss and fragmentation. We measured the physical connectedness of mature forest using an index of connectivity (landscape coincidence probability). Patches were considered connected if they were within the mean gliding distance of a flying squirrel. Homing success increased in landscapes with a higher connectivity index. However, homing time was not strongly predicted by habitat amount, connectivity index, or mean nearest neighbour and was best explained as a simple function of sex and distance translocated. Our study shows support for the independent effects of landscape configuration on animal movement at a spatial scale that encompasses several home ranges. We conclude that connectivity of mature forest should be considered for the conservation of some mature forest specialists, even in forest mosaics where the distinction between habitat and movement corridors are less distinct.     

Landscape composition mediates movement and habitat selection in bobcats (<Emphasis Type="Italic">Lynx rufus</Emphasis>): implications for conservation planning

Context

The analysis of individual movement choices can be used to better understand population-level resource selection and inform management.

Objectives

We investigated movements and habitat selection of 13 bobcats in Vermont, USA, under the assumption individuals makes choices based upon their current location. Results were used to identify “movement-defined” corridors.

Methods

We used GPS-collars and GIS to estimate bobcat movement paths, and extracted statistics on land cover proportions, topography, fine-scale vegetation, roads, and streams within “used” and “available” space surrounding each movement path. Compositional analyses were used to determine habitat preferences with respect to landcover and topography; ratio tests were used to determine if used versus available ratios for vegetation, roads, and streams differed from 1. Results were used to create travel cost maps, a primary input for corridor analysis.

Results

Forested and scrub-rock land cover were most preferred for movement, while developed land cover was least preferred. Preference depended on the composition of the “available” landscape: Bobcats moved?>?3 times more quickly through forest and scrub-rock habitat when these habitats were surrounded by agriculture or development than when the available buffer was similarly composed. Overall, forest edge, wetland edge and higher stream densities were selected, while deep forest core and high road densities were not selected. Landscape-scale connectivity maps differed depending on whether habitat suitability, preference, or selection informed the travel cost map.

Conclusions

Both local and landscape scale land cover characteristics affect habitat preferences and travel speed of bobcats, which in turn can inform management and conservation activities.

     

Matrix is important for mammals in landscapes with small amounts of native forest habitat

Acknowledgment that the matrix matters in conserving wildlife in human-modified landscapes is increasing. However, the complex interactions of habitat loss, habitat fragmentation, habitat condition and land use have confounded attempts to disentangle the relative importance of properties of the landscape mosaic, including the matrix. To this end, we controlled for the amount of remnant forest habitat and the level of fragmentation to examine mammal species richness in human-modified landscapes of varying levels of matrix development intensity and patch attributes. We postulated seven alternative models of various patch habitat, landscape and matrix influences on mammal species richness and then tested these models using generalized linear mixed-effects models within an information theoretic framework. Matrix attributes were the most important determinants of terrestrial mammal species richness; matrix development intensity had a strong negative effect and vegetation structural complexity of the matrix had a strong positive effect. Distance to the nearest remnant forest habitat was relatively unimportant. Matrix habitat attributes are potentially a more important indicator of isolation of remnant forest patches than measures of distance to the nearest patch. We conclude that a structurally complex matrix within a human-modified landscape can provide supplementary habitat resources and increase the probability of movement across the landscape, thereby increasing mammal species richness in modified landscapes.     

Population genetic structure and landscape connectivity of the Eastern Yellowbelly Racer (<Emphasis Type="Italic">Coluber constrictor flaviventris</Emphasis>) in the contiguous tallgrass prairie of northeastern Kansas,USA

The tallgrass prairie of North America has undergone widespread habitat loss and fragmentation (<4% remains). The Flint Hills region of Kansas and Oklahoma is the largest tallgrass prairie remaining and therefore provides an opportunity to study the population genetic structure of grassland species in a relatively contiguous landscape and set a baseline for evaluating changes when the habitat is fragmented. We adopted a landscape genetics approach to identify how landscape structure affected dispersal, population genetic structure, and landscape connectivity of the Eastern Yellowbelly Racer (Coluber constrictor flaviventris) across a 13,500-km² landscape in northeastern Kansas, USA. The racer population had high allelic diversity, high heterozygosity, and was maintaining migration-drift equilibrium. Autocorrelation between genetic and geographic distance revealed that racers exhibited restricted dispersal within 3 km, and isolation-by-distance. Significant isolation-by-distance occurred at broad regional scales (>100 km), but because of sufficient gene flow between locations, we were unable to define discrete subpopulations using Bayesian clustering analyses. Resistance distance, which considers the permeability of habitats, did not explain significant variation in genetic distance beyond Euclidean distance alone, suggesting that racers are not currently influenced by landscape composition. In northeastern Kansas, racers appear to be an abundant and continuously distributed snake that perceives the landscape as well connected with no cover type currently impeding snake dispersal or gene flow.     

Making molehills out of mountains: landscape genetics of the Mojave desert tortoise

Heterogeneity in habitat often influences how organisms traverse the landscape matrix that connects populations. Understanding landscape connectivity is important to determine the ecological processes that influence those movements, which lead to evolutionary change due to gene flow. Here, we used landscape genetics and statistical models to evaluate hypotheses that could explain isolation among locations of the threatened Mojave desert tortoise (Gopherus agassizii). Within a causal modeling framework, we investigated three factors that can influence landscape connectivity: geographic distance, barriers to dispersal, and landscape friction. A statistical model of habitat suitability for the Mojave desert tortoise, based on topography, vegetation, and climate variables, was used as a proxy for landscape friction and barriers to dispersal. We quantified landscape friction with least-cost distances and with resistance distances among sampling locations. A set of diagnostic partial Mantel tests statistically separated the hypotheses of potential causes of genetic isolation. The best-supported model varied depending upon how landscape friction was quantified. Patterns of genetic structure were related to a combination of geographic distance and barriers as defined by least-cost distances, suggesting that mountain ranges and extremely low-elevation valleys influence connectivity at the regional scale beyond the tortoises’ ability to disperse. However, geographic distance was the only influence detected using resistance distances, which we attributed to fundamental differences between the two ways of quantifying friction. Landscape friction, as we measured it, did not influence the observed patterns of genetic distances using either quantification. Barriers and distance may be more valuable predictors of observed population structure for species like the desert tortoise, which has high dispersal capability and a long generation time.     

Finding the functional grain: comparing methods for scaling resistance surfaces

The influence of landscape features on the movement of an organism between two point locations is often measured as an effective distance. Typically, raster models of landscape resistance are used to calculate effective distance. Because organisms may experience landscape heterogeneity at different scales (i.e. functional grains), using a raster with too fine or too coarse a spatial grain (i.e. analysis grain) may lead to inaccurate estimates of effective distance. We adopted a simulation approach where the true functional grain and effective distance for a theoretical organism were defined and the analysis grains of landscape connectivity models were systematically changed. We used moving windows and grains of connectivity, a recently introduced landscape graph method that uses an irregular tessellation of the resistance surface to coarsen the landscape data. We then used least-cost path metrics to measure effective distance and found that matching the functional and analysis grain sizes was most accurate at recovering the expected effective distance, affirming the importance of multi-scale analysis. Moving window scaling with a maximum function (win.max) performed well when the majority of landscape structure influencing connectivity consisted of high resistance features. Moving window scaling with a minimum function (win.min) performed well when the relevant landscape structure consisted of low resistance regions. The grains of connectivity method performed well under all scenarios, avoiding an a priori choice of window function, which may be challenging in complex landscapes. Appendices are provided that demonstrate the use of grains of connectivity models.     

What size is a biologically relevant landscape?

The spatial extent at which landscape structure best predicts population response, called the scale of effect, varies across species. An ability to predict the scale of effect of a landscape using species traits would make landscape study design more efficient and would enable landscape managers to plan at the appropriate scale. We used an individual based simulation model to predict how species traits influence the scale of effect. Specifically, we tested the effects of dispersal distance, reproductive rate, and informed movement behavior on the radius at which percent habitat cover best predicts population abundance in a focal area. Scale of effect for species with random movement behavior was compared to scale of effect for species with three (cumulative) levels of information use during dispersal: habitat based settlement, conspecific density based settlement, and gap-avoidance during movement. Consistent with a common belief among researchers, dispersal distance had a strong, positive influence on scale of effect. A general guideline for empiricists is to expect the radius of a landscape to be 4?C9 times the median dispersal distance or 0.3?C0.5 times the maximum dispersal distance of a species. Informed dispersal led to greater increases in population size than did increased reproductive rate. Similarly, informed dispersal led to more strongly decreased scales of effect than did reproductive rate. Most notably, gap-avoidance resulted in scales that were 0.2?C0.5 times those of non-avoidant species. This is the first study to generate testable hypotheses concerning the mechanisms underlying the scale at which populations respond to the landscape.     

Effects of increasing landscape heterogeneity on local plant species richness: how much is enough?

Contemporary landscape ecology continues to explore the causes and consequences of landscape heterogeneity across a range of scales, and demands for the scientific underpinnings of landscape planning and management still remains high. The spatial distribution of resources can be a key element in determining habitat quality, and that in turn is directly related to the level of heterogeneity in the system. In this sense, forest habitat mosaics may be more affected by lack of heterogeneity than by structural fragmentation. Nonetheless, increasing spatial heterogeneity at a given spatial scale can also decrease habitat patch size, with potential negative consequences for specialist species. Such dual effect may lead to hump-backed shape relationships between species diversity and heterogeneity, leading to three related assumptions: (i) at low levels of heterogeneity, an increase in heterogeneity favours local and regional species richness, (ii) there is an optimum heterogeneity level at which a maximum number of species is reached, (iii) further increase in spatial heterogeneity has a negative effect on local and regional species richness, due to increasing adverse effects of habitat fragmentation. In this study, we investigated the existence of a hump-shaped relationship between local plant species richness and increasing forest landscape heterogeneity on a complex mosaic in the French Alps. Forest landscape heterogeneity was quantified with five independent criteria. We found significant quadratic relationships between local forest species richness and two heterogeneity criteria indicators, showing a slight decrease of forest species richness at very high heterogeneity levels. Species richness–landscape heterogeneity relationships varied according to the heterogeneity metrics involved and the type of species richness considered. Our results support the assumption that intermediate levels of heterogeneity may support more species than very high levels of heterogeneity, although we were not able to conclude for a systematic negative effect of very high levels of heterogeneity on local plant species richness.     

Movement behavior explains genetic differentiation in American black bears

Individual-based landscape genetic analyses provide empirically based models of gene flow. It would be valuable to verify the predictions of these models using independent data of a different type. Analyses using different data sources that produce consistent results provide strong support for the generality of the findings. Mating and dispersal movements are the mechanisms through which gene flow operates in animal populations. The best means to verify landscape genetic predictions would be to use movement data to independently predict landscape resistance. We used path-level, conditional logistic regression to predict landscape resistance for American black bear (Ursus americanus) in a landscape in which previous work predicted population connectivity using individual-based landscape genetics. We found consistent landscape factors influence genetic differentiation and movement path selection, with strong similarities between the predicted landscape resistance surfaces. Genetic differentiation in American black bear is driven by spring movement (mating and dispersal) in relation to residential development, roads, elevation and forest cover. Given the limited periods of the year when gene flow events primarily occur, models of landscape connectivity should carefully consider temporal changes in functional landscape resistance.     

Predicting carnivore occurrence with noninvasive surveys and occupancy modeling

Terrestrial carnivores typically have large home ranges and exist at low population densities, thus presenting challenges to wildlife researchers. We employed multiple, noninvasive survey methods—scat detection dogs, remote cameras, and hair snares—to collect detection–nondetection data for elusive American black bears (Ursus americanus), fishers (Martes pennanti), and bobcats (Lynx rufus) throughout the rugged Vermont landscape. We analyzed these data using occupancy modeling that explicitly incorporated detectability as well as habitat and landscape variables. For black bears, percentage of forested land within 5 km of survey sites was an important positive predictor of occupancy, and percentage of human developed land within 5 km was a negative predictor. Although the relationship was less clear for bobcats, occupancy appeared positively related to the percentage of both mixed forest and forested wetland habitat within 1 km of survey sites. The relationship between specific covariates and fisher occupancy was unclear, with no specific habitat or landscape variables directly related to occupancy. For all species, we used model averaging to predict occurrence across the study area. Receiver operating characteristic (ROC) analyses of our black bear and fisher models suggested that occupancy modeling efforts with data from noninvasive surveys could be useful for carnivore conservation and management, as they provide insights into habitat use at the regional and landscape scale without requiring capture or direct observation of study species.     

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.     

Patterns of abundance and movement in relation to landscape structure: a study of a common scarab (Canthon cyanellus cyanellus) in Southern Mexico

Few relevant data are available to analyze how landscape features affect the abundance and movement patterns of tropical insects. We used mark-release-recapture techniques to study the effects of landscape structure and composition on habitat preferences and movements of Canthon cyanellus cyanellus individuals, within a complex tropical deciduous forest landscape in South Mexico during 2004 and 2005. In total, 2,460 individuals of C. c. cyanellus were captured, including 1,225 females and 1,235 males, out of which 124 individuals (65 females and 59 males) were recaptured once, and 9 individuals (seven females and two males) were recaptured twice. The abundance of individuals was equally high in large forest fragments, small forest fragments and hedgerows, but the abundance in pastures was less than half of the abundance in the other habitat types. To disentangle the movement behaviour of the species from the spatially and temporally varying sampling effort, we applied a Bayesian state-space modelling framework with a diffusion based movement model. Males showed generally faster movement rate than females, and they moved faster within forests and hedgerows than within pastures. Contrary to the assumption of the diffusion model, individuals did not move in a continuous fashion, indicated by the large fraction of individuals that were recaptured in the site of release. However, the posterior predictive data did not deviate substantially from the real data in terms of the mean and maximum movement distances recorded, and in terms of the dependence of movement distance on time between captures. Our results suggest that an important component of the biota in Mexican agro-pasture landscapes can utilize contemporary landscape elements such as hedgerows or small forest fragments in addition to large fragments of remnant habitat. These habitats are still locally common in semi-natural ecosystems and require less intensive conservation management.     

Empirical estimation of dispersal resistance surfaces: a case study with red-cockaded woodpeckers

Persistence of wildlife populations depends on the degree to which landscape features facilitate animal movements between isolated habitat patches. Due to limited data availability, the effect of landscape features on animal dispersal is typically estimated using expert opinion. With sufficient data, however, resistance surfaces can be estimated empirically. After modeling suitable prospecting habitat using an extensive dataset from the federally endangered red-cockaded woodpecker (Picoides borealis), we used data from over 800 prospecting events from 34 radio-tagged birds to identify the best relationship between habitat suitability and resistance surfaces. Our results demonstrated that juvenile female P. borealis prospecting for new territories beyond their natal territories preferred to traverse through forests with tall canopy and minimal midstory vegetation. The non-linear relationship between habitat suitability and resistance surfaces was the most biologically relevant transformation, which in turn identified the specific forest composition that promoted and inhibited prospecting and dispersal behavior. These results corresponded with over 60 % of dispersal events from an independent dataset of short-distance dispersal events. This new understanding of P. borealis prospecting behavior will help to identify areas necessary for maintaining habitat connectivity and to implement effective management strategies. Our approach also provides a framework to not only estimate and evaluate resistance surfaces based on species-specific responses to intervening landscape features, but also addresses an often-neglected step, selecting a biologically relevant function to transform habitat suitability model into a resistance surface.     

Interpreting realized pollen flow in terms of pollinator travel paths and land-use resistance in heterogeneous landscapes

Widespread ecosystem change has led to declines in species world-wide. The loss of pollinators in particular constitutes a problem for ecosystem function and crop production. Understanding how landscape change affects pollinator movement, effective pollen flow, and plant and pollinator survival is therefore a global priority. In this study we investigated patterns of effective pollen flow, using wild cherry tree (Prunus avium) progeny arrays, to address two questions in three case studies: Do land-use types present different resistances to pollinator movement? Which pollinator travel path best explains the pollination data (straight lines, weighted straight lines, least cost paths or pair-wise resistance)? Trees and progeny arrays were genotyped and effective pollen flow and pollinator movement were estimated using the spatially explicit mating model. We found that pollinators did modify their travel paths in response to land-use type and arrangement, but the travel path that best described pollinator movement and the resistance rank of the land uses depended on the type and size of land-use patches and the landscape context. We propose a novel theoretical framework rooted in behavioural ecology, the resource model, for interpreting pollinator behaviour in heterogeneous landscapes. We conclude by discussing the importance and practicality of conservation and management strategies in which native and non-native land-use types together provide functional habitat and support ecosystem services across economic landscapes.     

Quantifying functional connectivity: Experimental evidence for patch-specific resistance in the Natterjack toad (Bufo calamita)

Despite the importance assigned to inter-patch movements in fragmented systems, the structure of landscape between suitable habitat patches, the matrix, is often considered as to be of minor interest, or totally ignored. Consequently, models predicting metapopulation dynamics typically assume that dispersal and movement abilities are independent of the composition of the matrix. The predictions of such models should be invalided if that crucial assumption is unverified. In order to test the hypothesis of a patch-specific resistance, we led an experimental study to assess the matrix effects on the movement ability of juvenile Natterjack toads (Bufo calamita). The movement behaviour of first year toadlets, the dispersal stage in this species, was investigated in an arena experiment. Toadlet mobility was assessed in five landscape components that were mimicked in the lab: sandy soil, road, forest, agricultural field, and pasture. We analysed several movement components including move length, speed, efficiency and turning angle distribution. Our results showed that movement ability was strongly affected by the land cover, even if body size modulated the behavioural responses of toadlets. Performances were the best in the arenas mimicking sand and roads, and the worst in the forest arena, toadlet moves being three to five times less effective in the latter. The mobility was intermediate in the two other arenas. We propose here a new method to quantify functional connectivity, based on quantitative estimates of relative values for resistance of landscape components. This method offers a reliable alternative for resistance value estimates to subjective expert advice or inference from genetic population structure.     

Quantifying functional connectivity: Experimental evidence for patch-specific resistance in the Natterjack toad (Bufo calamita)

Despite the importance assigned to inter-patch movements in fragmented systems, the structure of landscape between suitable habitat patches, the matrix, is often considered as to be of minor interest, or totally ignored. Consequently, models predicting metapopulation dynamics typically assume that dispersal and movement abilities are independent of the composition of the matrix. The predictions of such models should be invalided if that crucial assumption is unverified. In order to test the hypothesis of a patch-specific resistance, we led an experimental study to assess the matrix effects on the movement ability of juvenile Natterjack toads (Bufo calamita). The movement behaviour of first year toadlets, the dispersal stage in this species, was investigated in an arena experiment. Toadlet mobility was assessed in five landscape components that were mimicked in the lab: sandy soil, road, forest, agricultural field, and pasture. We analysed several movement components including move length, speed, efficiency and turning angle distribution. Our results showed that movement ability was strongly affected by the land cover, even if body size modulated the behavioural responses of toadlets. Performances were the best in the arenas mimicking sand and roads, and the worst in the forest arena, toadlet moves being three to five times less effective in the latter. The mobility was intermediate in the two other arenas. We propose here a new method to quantify functional connectivity, based on quantitative estimates of relative values for resistance of landscape components. This method offers a reliable alternative for resistance value estimates to subjective expert advice or inference from genetic population structure.