Context

A challenge devising revegetation strategies in fragmented landscapes is conserving for the widest spectrum of biodiversity. Habitat network reconstruction should improve landscape capacity to maintain species populations. However, the location of revegetation often fails to account for species occurrence and dispersal processes operating across spatial scales.

Objectives

Our objective was to integrate metapopulation theory with estimates of landscape capacity and dispersal pathways to highlight connectivity gaps. Maintenance of populations could thereby be facilitated through reconnecting habitat networks across regional and broader scales, with assumed benefit for the dispersal needs of less sensitive species.

Methods

Predicted occupancy and metapopulation capacity were calculated for a generic focal species derived from fragmentation-sensitive woodland birds, mammals and reptiles. A metapopulation connectivity analysis predicted regional dispersal links to identify likely routes through which individuals may move to contribute to the viability of the population. We used the revegetation programmes of the Brigalow–Nandewar Biolinks project, eastern New South Wales, Australia, to demonstrate our approach.

Results

Landscape capacity of the current landscape varied across the region. Low-value links between populations provided greatest opportunities for revegetation and improved landscape capacity. Where regional connectivity did not indicate a pathway between populations, broader scale connectivity provided guidance for revegetation.

Conclusions

The metapopulation-based model, coupled with a habitat dispersal network analysis, provided a platform to inform revegetation locations and better support biodiversity. Our approach has application for directing on-ground action to support viable populations, assess the impact of revegetation schemes or monitor the progress of staged implementations.

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.

Context

Many nearshore species are distributed in habitat patches connected only through larval dispersal. Genetic research has shown some spatial structure of such metapopulations and modeling studies have shed light onto possible patterns of connectivity and barriers. However, little is known about human impact on their spatial structure and patterns of connectivity.

Objectives

We examine the effects of fishing on the spatial and temporal dynamics of metapopulations of sedentary marine species (red sea urchin and red abalone) interconnected by larval dispersal.

Methods

We constructed a metapopulation model to simulate abalone and sea urchin metapopulations experiencing increasing levels of fishing mortality. We performed the modularity analysis on the yearly larval connectivity matrices produced by these simulations, and analyzed the changes of modularity and the formation of modules over time as indicators of spatial structure.

Results

The analysis revealed a strong modular spatial structure for abalone and a weak spatial signature for sea urchin. In abalone, under exploitation, modularity takes step-wise drops on the path to extinction, and modules breakdown into smaller fragments followed by module and later metapopulation collapse. In contrast, sea urchin showed high modularity variation, indicating high- and low-mixing years, but an abrupt collapse of the metapopulation under strong exploitation.

Conclusions

The results identify a disruption in larval connectivity and a pattern of collapse in highly modular nearshore metapopulations. These results highlight the ability of modularity to detect spatial structure in marine metapopulations, which varies among species, and to show early changes in the spatial structure of exploited metapopulations.

Context

Dispersal is essential for species persistence and landscape genetic studies are valuable tools for identifying potential barriers to dispersal. Macaws have been studied for decades in their natural habitat, but we still have no knowledge of how natural landscape features influence their dispersal.

Objectives

We tested for correlations between landscape resistance models and the current population genetic structure of macaws in continuous rainforest to explore natural barriers to their dispersal.

Methods

We studied scarlet macaws (Ara macao) over a 13,000 km² area of continuous primary Amazon rainforest in south-eastern Peru. Using remote sensing imagery from the Carnegie Airborne Observatory, we constructed landscape resistance surfaces in CIRCUITSCAPE based on elevation, canopy height and above-ground carbon distribution. We then used individual- and population-level genetic analyses to examine which landscape features influenced gene flow (genetic distance between individuals and populations).

Results

Across the lowland rainforest we found limited population genetic differentiation. However, a population from an intermountain valley of the Andes (Candamo) showed detectable genetic differentiation from two other populations (Tambopata) located 20–60 km away (F _ST = 0.008, P = 0.001–0.003). Landscape resistance models revealed that genetic distance between individuals was significantly positively related to elevation.

Conclusions

Our landscape resistance analysis suggests that mountain ridges between Candamo and Tambopata may limit gene flow in scarlet macaws. These results serve as baseline data for continued landscape studies of parrots, and will be useful for understanding the impacts of anthropogenic dispersal barriers in the future.

Context

Methods quantifying habitat patch importance for maintaining habitat network connectivity have been emphasized in helping to prioritize conservation actions. Functional connectivity is accepted as depending on landscape resistance, and several measures of functional inter-patch distance have been designed. However, how the inter-patch distance, i.e., based on least-cost path or multiple paths, influences the identification of key habitat patches has not been explored.

Objectives

We compared the prioritization of habitat patches according to least-cost distance (LCD) and resistance distance (RD), using common binary and probabilistic connectivity metrics.

Methods

Our comparison was based on a generic functional group of forest mammals with different dispersal distances, and was applied to two landscapes differing in their spatial extent and fragmentation level.

Results

We found that habitat patch prioritization did not depend on distance type when considering the role of patch as contributing to dispersal fluxes. However, the role of patch as a connector facilitating dispersal might be overestimated by LCD-based indices compared with RD for short- and medium-distance dispersal. In particular, when prioritization was based on dispersal probability, the consideration of alternatives routes identified the connectors that probably provided functional connectivity for species in the long term. However, the use of LCD might help identify landscape areas that need critical restoration to improve individual dispersal.

Conclusions

Our results provide new insights about the way that inter-patch distance is viewed changes the evaluation of functional connectivity. Accordingly, prioritization methods should be carefully selected according to assumptions about population functioning and conservation aims.

Context

The relative importance of habitat area and connectivity for species richness is often unknown. Connectivity effects may be confounded with area effects or they may be of minor importance as posited by the habitat-amount hypothesis.

Objectives

We studied effects of habitat area and connectivity of linear landscape elements for plant species richness at plot level. We hypothesized that connectivity of linear landscape elements, assessed by resistance distance, has a positive effect on species richness beyond the effect of area and, further, that the relative importance of connectivity varies among groups of species with different habitat preferences and dispersal syndromes.

Methods

We surveyed plant species richness in 50 plots (25 m²) located on open linear landscape elements (field margins, ditches) in eight study areas of 1 km² in agricultural landscapes of Northwest Germany. We calculated the area of linear landscape elements and assessed their connectivity using resistance distance within circular buffers (500 m) around the plots. Effects of area and connectivity on species richness were modelled with generalised linear mixed models.

Results

Species richness did not increase with area. Resistance distance had significant negative effects on total richness and on the richness of typical species of grasslands and wetlands. Regarding dispersal syndromes, resistance distance had negative effects on the richness of species with short-distance, long-distance and aquatic dispersal. The significant effects of resistance distance indicated that species richness increased with connectivity of the network of linear landscape elements.

Conclusions

Connectivity is more important for plant species richness in linear landscape elements than area. In particular, the richness of plant species that are dispersal limited and confined to semi-natural habitats benefits from connective networks of linear landscape elements in agricultural landscapes.

Context

Common species important for ecosystem restoration stand to lose as much genetic diversity from anthropogenic habitat fragmentation and climate change as rare species, but are rarely studied. Salt marshes, valuable ecosystems in widespread decline due to human development, are dominated by the foundational plant species black needlerush (Juncus roemerianus Scheele) in the northeastern Gulf of Mexico.

Objectives

We assessed genetic patterns in J. roemerianus by measuring genetic and genotypic diversity, and characterizing population structure. We examined population connectivity by delineating possible dispersal corridors, and identified landscape factors influencing population connectivity.

Methods

A panel of 19 microsatellite markers was used to genotype 576 samples from ten sites across the northeastern Gulf of Mexico from the Grand Bay National Estuarine Research Reserve (NERR) to the Apalachicola NERR. Genetic distances (F_ST and D_ch) were used in a least cost transect analysis (LCTA) within a hierarchical model selection framework.

Results

Genetic and genotypic diversity results were higher than expected based on life history literature, and samples structured into two large, admixed genetic clusters across the study area, indicating sexual reproduction may not be as rare as predicted in this clonal macrophyte. Digitized coastal transects buffered by 500 m may represent possible dispersal corridors, and developed land may significantly impede population connectivity in J. roemerianus.

Conclusions

Results have important implications for coastal restoration and management that seek to preserve adaptive potential by sustaining natural levels of genetic diversity and conserving population connectivity. Our methodology could be applied to other common, widespread and understudied species.

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.

Context

Quantifying gene flow in natural populations is a key topic in both evolutionary and conservation biology. Understanding the extent to which the landscape matrix facilitates or impedes gene flow is becoming a high priority in a context of worldwide habitat loss and fragmentation.

Objectives

Unexpectedly, a lower genetic diversity and a higher genetic structure have been previously observed in the less fragmented and the most forested habitat across four pine marten (Martes martes) populations in France. Our aim was to quantify the effect of landscape on the spatial distribution of genetic diversity in two populations in contrasting habitats.

Methods

We conducted an individual-based landscape genetics analysis in a highly fragmented rural plain (Bresse, n = 126) and in a highly forested (50 %) mountainous area (Ariège, n = 88) in France. We tested for isolation-by-resistance using least-cost distances and used a causal modeling approach on 16,384 landscape and 104 elevation resistance scenarios.

Results

Landscape structure influenced the genetic differentiation in Bresse, with vegetation providing more genetic connectivity over the study area than open areas, while roads and human buildings showed unexpected low resistance to gene flow. In Ariège, genetic differentiation was mainly associated with changes in elevation, with an optimal elevation for gene flow of around 1700 m, likely associated with changes in vegetation structure.

Conclusions

The pine marten seems to be able to cope with human-dominated landscapes and with fragmented forest landscapes, whereas elevation is the major driver of genetic differentiation in our mountainous landscape. Additionally, we highlight the importance of spatial replication in landscape genetics for deriving reliable conservation and management measures over the species distribution.

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.

Context

Landscape modification is an important driver of biodiversity declines, yet we lack insight into how ongoing landscape change and legacies of historical land use together shape biodiversity.

Objectives

We examined how a history of agricultural land use and current forest fragmentation influence the abundance of red-backed salamanders (Plethodon cinereus). We hypothesized that historical agriculture and fragmentation cause changes in habitat quality and landscape structure that limit abundance.

Methods

We measured salamander abundance at 95 forested sites in New York, USA, and we determined whether sites were agricultural fields within the last five decades. We used a structural equation model to estimate relationships between historical agriculture and salamander abundance mediated by changes in forest vegetation, microclimate, and landscape structure.

Results

Historical agriculture affected salamander abundance by altering forest vegetation at a local scale and forest cover at a landscape scale. Abundance was lowest at post-agricultural sites with low woody vegetation, leaf litter depth, and canopy cover. Post-agricultural sites had limited forest cover in the surrounding landscape historically, and salamander abundance was positively related to historical forest cover, suggesting that connectivity to source populations affects colonization of regenerating forests. Abundance was also negatively related to current forest fragmentation.

Conclusions

Historical land use can have legacy effects on animal abundance on par with effects of ongoing landscape change. We showed that associations between animal abundance and historical land use can be driven by altered site conditions and surrounding habitat area, indicating that restoration efforts should consider local site conditions and landscape context.

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.

Context

Barriers to dispersal influence the ability of individuals to expand into new areas and can ultimately define success of reintroduction programs. American marten (Martes americana) were reintroduced to the Upper Peninsula of Michigan, USA, from multiple, genetically differentiated source populations from 1955 to 1992. Previous research found multiple genetic clusters near release sites with little admixing, suggesting barriers to dispersal exist.

Objectives

We sought to identify whether the contact zones between genetic clusters coincided with landscape features hypothesized to influence M. americana dispersal. We also investigated whether the degree of landscape contiguity within each genetic cluster differed among clusters.

Methods

We mapped cluster boundaries in M. americana genetic assignment probabilities and used correlation length as a measure of landscape contiguity between genetic clusters. We then evaluated the effects of land cover and roads on spatial genetic structure using a spatial autoregressive model.

Results

We found that gene flow was facilitated by contiguous coniferous forest and low incidence of roads. However, the strength of those relationships varied by genetic cluster. Contact zones among some genetic clusters spatially coincided with areas of high road and low conifer contiguity, compared to within-clusters.

Conclusions

In contrast to landscape genetic analyses focused on identifying barriers to gene flow, we incorporated methods that are relatively novel in landscape genetics to quantify how landscape contiguity influences spatial genetic structure. Using this method we were able to identify landscape barriers to dispersal at the genetic cluster boundaries for a reintroduced species distributed continuously across the landscape.

Context

Land use changes have modified the extent and structure of native vegetation, resulting in fragmentation of native species habitat. Connectivity is increasingly seen as a requirement for effective conservation in these landscapes, but the question remains: ‘connectivity for which species?’.

Objective

The aim of this study was to develop and then apply a rapid, expert-based, dispersal guild approach where species are grouped on similar fine-scale dispersal behaviour (such as between scattered trees) and habitat characteristics.

Methods

Dispersal guilds were identified using clustering techniques to compare dispersal and habitat parameters elicited from experts. We modelled least-cost paths and corridors between patches and individual movement probabilities within these corridors for each of the dispersal guilds using Circuitscape. We demonstrate our approach with a case study in the Tasmanian Northern Midlands, Australia.

Results

The dispersal guild approach grouped the 12 species into five dispersal guilds. The connectivity modelling of those five guilds found that broadly dispersing species in this landscape, such as medium-sized carnivorous mammals, were unaffected by fragmentation while from the perspective of the three dispersal guilds made up of smaller mammals, the landscape appeared highly fragmented.

Conclusions

Our approach yields biologically defensible outputs that are broadly applicable, particularly for conservation planning where data and resources are limited. It is a useful first step in multi-species conservation planning which aims to identify those species most in need of conservation efforts.

Context

In a global context of erosion of biodiversity, the current environmental policy in Europe is oriented towards the creation and the preservation of ecological networks for wildlife. However, most of the management guidelines arose from a structural landscape diagnostic without truly taking into consideration species’ needs.

Objectives

We tested whether and how landscape elements influence the functional connectivity of landscapes for a forest specialist species, the European pine marten (Martes martes), in Northeastern France.

Methods

We collected pine marten scats and tissues from 13 evenly distributed study sites across the whole study area in order to test several types of barriers such as highways, waterways, and open agricultural fields. We crossed the results of several methods: spatial autocorrelation analysis, causal modelling framework, and clustering methods.

Results

The study indicates significant genetic differentiation among the sampling sites. A signal of isolation by distance was detected but disappeared after partialling out landscape or barrier resistance. The only model that was fully supported by causal modelling was the one identifying waterways as the main driver of genetic differentiation. Moreover, clustering analyses indicated the presence of genetic clusters, suggesting that pine marten spatial genetic pattern could be explained by the presence of waterways but also by their reluctance to cross open fields.

Conclusions

The current ecological network could thus be improved by increasing permeability of waterways, in particular navigation canals, and by maintaining and restoring forested corridors in agricultural plains.

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.

Context

The problem of how ecological mechanisms create and interact with patterns across different scales is fundamental not only for understanding ecological processes, but also for interpretations of ecological dynamics and the strategies that organisms adopt to cope with variability and cross-scale influences.

Objectives

Our objective was to determine the consistency of the role of individual habitat patches in pattern-process relationships (focusing on the potential for dispersal within a network of patches in a fragmented landscape) across a range of scales.

Methods

Network analysis was used to assess and compare the potential connectivity and spatial distribution of highland fynbos habitat in and between protected areas of the Western Cape of South Africa. Connectivity of fynbos patches was measured using ten maximum threshold distances, ranging from five to 50 km, based on the known average dispersal distances of fynbos endemic bird species.

Results

Network connectivity increased predictably with scale. More interestingly, however, the relative contributions of individual protected areas to network connectivity showed strong scale dependence.

Conclusions

Conservation approaches that rely on single-scale analyses of connectivity and context (e.g., based on data for a single species with a given dispersal distance) are inadequate to identify key land parcels. Landscape planning, and specifically the assessment of the value of individual areas for dispersal, must therefore be undertaken with a multi-scale approach. Developing a better understanding of scaling dependencies in fragmenting landscapes is of high importance for both ecological theory and conservation planning.

Context

Landscape and habitat filters are major drivers of biodiversity of small habitat islands by influencing dispersal and extinction events in plant metapopulations.

Objectives

We assessed the effects of landscape and habitat filters on the species richness, abundance and trait composition of grassland specialist and generalist plants in small habitat islands. We studied traits related to functional spatial connectivity (dispersal ability by wind and animals) and temporal connectivity (clonality and seed bank persistence) using model selection.

Methods

We sampled herbaceous plants, landscape (local and regional isolation) and habitat filters (inclination, woody encroachment and disturbance) in 82 grassland islands in Hungary.

Results

Isolation decreased the abundance of good disperser specialist plants due to the lack of directional vectors transferring seeds between suitable habitat patches. Clonality was an effective strategy, but persistent seed bank did not support the survival of specialist plants in isolated habitats. Generalist plants were unaffected by landscape filters due to their wide habitat breadth and high propagule availability. Clonal specialist plants could cope with increasing woody encroachment due to their high resistance against environmental changes; however, they could not cope with intensive disturbance. Steep slopes providing environmental heterogeneity had an overall positive effect on species richness.

Conclusions

Specialist plants were influenced by the interplay of landscape filters influencing their abundance and habitat filters affecting species richness. Landscape filtering by isolation influenced the abundance of specialist plants by regulating seed dispersal. Habitat filters sorted species that could establish and persist at a site by influencing microsite availability and quality.

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.