Evaluation of patch isolation metrics in mosaic landscapes for specialist vs. generalist dispersers

We examined the effects of matrix structure and movement responses of organisms on the relationships between 7 patch isolation metrics and patch immigration. Our analysis was based on simulating movement behaviour of two generic disperser types (specialist and generalist) across mosaic landscapes containing three landcover types: habitat, hospitable matrix and inhospitable matrix. Movement, mortality and boundary crossing probabilities of simulated individuals were linked to the landcover and boundary types in the landscapes. The results indicated that area-based isolation metrics generally predict patch immigration more reliably than distance-based isolation metrics. Relationships between patch isolation metrics and patch immigration varied between the two generic disperser types and were affected by matrix composition or matrix fragmentation. Patch immigration was always affected by matrix composition but not by matrix fragmentation. Our results do not encourage the generic use of patch isolation metrics as a substitute for patch immigration, in particular in metapopulation models where generic use may result in wrong projections of the survival probability of metapopulations. However, our examination of the factors affecting the predictive potential of patch isolation metrics should facilitate interpretation and comparison of existing patch isolation studies. Future patch isolation studies should include information about landscape structure and the dispersal distance and dispersal behaviour of the organism of interest.This revised version was published online in May 2005 with corrections to the Cover Date.     

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.     

Relative importance of habitat area and isolation for bird occurrence patterns in a naturally patchy landscape

There is debate among ecologists about whether total habitat area or patch arrangement contributes most to population and/or community responses to fragmented or patchy landscapes. We tested the relative effects of patch area and isolation for predicting bird occurrence in a naturally patchy landscape in the Bear River Mountains of Northern Utah, USA. We selected focal patches (mountain meadows) ranging in elevation from 1,920 to 2,860 m and in size from 0.6 to 182 ha. Breeding birds were sampled in each focal meadow during the summers of 2003 and 2004 using variable-distance point transects. Logistic regression and likelihood-based model selection were used to determine the relationship between likelihood of occurrence of three bird species (Brewer’s sparrow, vesper sparrow, and white-crowned sparrow) and area, isolation, and proximity metrics. We used model weights and model-averaged confidence intervals to assess the importance of each predictor variable. Plots of area versus isolation were used to evaluate complex relationships between the variables. We found that meadow area was the most important variable for explaining occurrence for two species, and that isolation was the most important for the other. We also found that the absolute distance was more appropriate for evaluating isolation responses than was the species-specific proximity metric. Our findings add clarity to the debate between ecologists regarding the relative importance of area and isolation in species responses to patchy landscapes.     

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.     

The behavior of landscape metrics commonly used in the study of habitat fragmentation

A meaningful interpretation of landscape metrics is possible only when the limitations of each measure are fully understood, the range of attainable values is known, and the user is aware of potential shifts in the range of values due to characteristics of landscape patches. To examine the behavior of landscape metrics, we generated artificial landscapes that mimicked fragmentation processes while controlling the size and shape of patches in the landscape and the mode of disturbance growth. We developed nine series of increasingly fragmented landscapes and used these to investigate the behavior of edge density, contagion, mean nearest neighbor distance, mean proximity index, perimeter-area fractal dimension, and mass fractal dimension. We found that most of the measures were highly correlated, especially contagion and edge density, which had a near-perfect inverse correspondence. Many of the measures were linearly-associated with increasing disturbance until the proportion of disturbance on the landscape was approximately 0.40, with non-linear associations at higher proportions. None of the measures was able to differentiate between landscape patterns characterized by dispersed versus aggregated patches. The highest attainable value of each measure was altered by either patch size or shape, and in some cases, by both attributes. We summarize our findings by discussing the utility of each metric.     

The relative impact of forest patch and landscape attributes on black howler monkey populations in the fragmented Lacandona rainforest, Mexico

Land-use change is forcing many animal populations to inhabit forest patches in which different processes can threaten their survival. Some threatening processes are mainly related to forest patch characteristics, but others depend principally on the landscape spatial context. Thus, the impact of both patch and landscape spatial attributes needs to be assessed to have a better understanding of the habitat spatial attributes that constraint the maintenance of populations in fragmented landscapes. Here, we evaluated the relative effect of three patch-scale (i.e., patch size, shape, and isolation) and five landscape-scale metrics (i.e., forest cover, fragmentation, edge density, mean inter-patch isolation distance, and matrix permeability) on population composition and structure of black howler monkeys (Alouatta pigra) in the Lacandona rainforest, Mexico. We measured the landscape-scale metrics at two spatial scales: within 100 and 500 ha landscapes. Our findings revealed that howler monkeys were more strongly affected by local-scale metrics. Smaller and more isolated forest patches showed a lower number of individuals but at higher densities. Population density also tended to be positively associated to matrices with higher proportion of secondary forests and arboreal crops (i.e. with greater permeability), most probably because these matrices can offer supplementary foods. The immature-to-female ratio also increased with matrix permeability, shape complexity, and edge density; habitat characteristics that can increase landscape connectivity and sources availability. The prevention of habitat loss and isolation, and the increment of matrix permeability are therefore needed for the conservation of this endangered Neotropical mammal.     

Sensitivity and effectiveness and of landscape metric scalograms in determining the characteristic scale of a hierarchically structured landscape

Landscape metric scalograms (the response curves of landscape metrics to changing grain size) have been used to illustrate the scale effects of metrics for real landscapes. However, whether they detect the characteristic scale of hierarchically structured landscapes remains uncertain. To address this question, the scalograms of 26 class-level metrics were systematically examined for a simple random landscape, seven hierarchical neutral landscapes, and the real landscape of the Xilin River Basin of Inner Mongolia, China. The results show that when the fraction of the focal patch type (P) is below a critical value (P _c), most metric scalograms are sensitive to change in single-scale and lower-level hierarchical structure and insensitive to change in higher-level hierarchical structure. The scalograms of only a few metrics measuring spatial aggregation and connectedness are sensitive to change in intermediate-level hierarchical structure. Most metric scalograms explicitly identify the characteristic scale of a single-scale landscape and fine or intermediate characteristic scales of a multi-scale landscape for both simulated and real landscapes. When P exceeds P _c, only some metrics detect scale and change in structure. The scalograms of total class area and Euclidean nearest-neighbor distance cannot detect scale or change in structure in either case. Landscape metric scalograms are useful for addressing scale issues, including illustrating the scale effects of spatial patterns, detecting multi-scale patterns, and developing possible scaling relations.

     

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.     

Statistical models of landscape pattern metrics,with applications to regional scale dynamic forest simulations

Forest managers in Canada need to model landscape pattern or spatial configurationoverlarge (100,000 km²) regions. This presents a scalingproblem, as landscape configuration is measured at a high spatial resolution,but a low spatial resolution is indicated for regional simulation. We present astatistical solution to this scaling problem by showing how a wide range oflandscape pattern metrics can be modelled from low resolution data. Our studyarea comprises about 75,000 km² of boreal mixedwoodforest in northeast Alberta, Canada. Within this area we gridded a sample of 84digital forest cover maps, each about 9500 ha in size, to aresolution of 1 ha and used FRAGSTATS to compute a suite oflandscape pattern metrics for each map. We then used multivariate dimensionreduction techniques and canonical correlation analysis to model therelationship between landscape pattern metrics and simpler stand table metricsthat are easily obtained from non-spatial forest inventories. These analyseswere performed on four habitat types common in boreal mixedwood forests: youngdeciduous, old deciduous, white spruce, and mixedwood types. Using only threelandscape variables obtained directly from stand attribute tables (totalhabitatarea, and the mean and standard deviation of habitat patch size), ourstatistical models explained more than 73% of the joint variation in fivelandscape pattern metrics (representing patch shape, forest interior habitat,and patch isolation). By PCA, these five indices captured much of the totalvariability in the rich set of landscape pattern metrics that FRAGSTATS cangenerate. The predictor variables and strengths of association were highlyconsistent across habitat classes. We illustrate the potential use of suchstatistical relationships by simulating the regional, cumulative effects ofwildfire and forest management on the spatial arrangement of forest patches,using non-spatial stand attribute tables.This revised version was published online in May 2005 with corrections to the Cover Date.     

Surface metrics: an alternative to patch metrics for the quantification of landscape structure

Modern landscape ecology is based on the patch mosaic paradigm, in which landscapes are conceptualized and analyzed as mosaics of discrete patches. While this model has been widely successful, there are many situations where it is more meaningful to model landscape structure based on continuous rather than discrete spatial heterogeneity. The growing field of surface metrology offers a variety of surface metrics for quantifying landscape gradients, yet these metrics are largely unknown and/or unused by landscape ecologists. In this paper, we describe a suite of surface metrics with potential for landscape ecological application. We assessed the redundancy among metrics and sought to find groups of similarly behaved metrics by examining metric performance across 264 sample landscapes in western Turkey. For comparative purposes and to evaluate the robustness of the observed patterns, we examined 16 different patch mosaic models and 18 different landscape gradient models of landscape structure. Surface metrics were highly redundant, but less so than patch metrics, and consistently aggregated into four cohesive clusters of similarly behaved metrics representing surface roughness, shape of the surface height distribution, and angular and radial surface texture. While the surface roughness metrics have strong analogs among the patch metrics, the other surface components are largely unique to landscape gradients. We contend that the surface properties we identified are nearly universal and have potential to offer new insights into landscape pattern–process relationships. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.     

The influence of thematic resolution on metric selection for biodiversity monitoring in agricultural landscapes

The objective of this paper is to investigate the relationship between landscape pattern metrics and agricultural biodiversity at the Temperate European scale, exploring the role of thematic resolution and a suite of biological and functional groups. Factor analyses to select landscape-level metrics were undertaken on 25 landscapes classified at four levels of thematic resolution. The landscapes were located within seven countries. The different resolutions were considered appropriate to taxonomic and functional group diversity. As class-level metrics are often better correlated to ecological response, the landscape-level metric subsets gained through exploratory analysis were additionally used to guide the selection of class-level metric subsets. Linear mixed models were then used to detect correlations between landscape- and class-level metrics and species richness values. Taxonomic groups with differing requirements (plants, birds, different arthropod groups) and also functional arthropod groups were examined. At the coarse scale of thematic resolution grain metrics (patch density, largest patch index) emerged as rough indicators for the different biological groups whilst at the fine scale a diversity metric (e.g. Simpson’s diversity index) was appropriate. The intermediate thematic resolution offered most promise for biodiversity monitoring. Metrics included largest patch index, edge density, nearest neighbour, the proximity index, circle and Simpson’s diversity index. We suggest two possible applications of these metrics in the context of biodiversity monitoring and the identification of biodiversity hot spots in European agricultural landscapes.     

Two measures of landscape-graph connectivity: assessment across gradients in area and configuration

Landscape connectivity is critical to species persistence in the face of habitat loss and fragmentation. Graph theory is a well-defined method for quantifying connectivity that has tremendous potential for ecology, but its application has been limited to a small number of conservation scenarios, each with a fixed proportion of habitat. Because it is important to distinguish changes in habitat configuration from changes in habitat area in assessing the potential impacts of fragmentation, we investigated two metrics that measure these different influences on connectivity. The first metric, graph diameter, has been advocated as a useful measure of habitat configuration. We propose a second area-based metric that combines information on the amount of connected habitat and the amount of habitat in the largest patch. We calculated each metric across gradients in habitat area and configuration using multifractal neutral landscapes. The results identify critical connectivity thresholds as a function of the level of fragmentation and a parallel is drawn between the behavior of graph theory metrics and those of percolation theory. The combination of the two metrics provides a means for targeting sites most at risk of suffering low potential connectivity as a result of habitat fragmentation.     

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.     

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.     

Measuring boundary convexity at multiple spatial scales using a linear “moving window” analysis: an application to coastal river otter habitat selection

Landscape metrics have been used to quantify ecological patterns and to evaluate relationships between animal presence/abundance and habitat at multiple spatial scales. However, many ecological flows occur in linear systems such as streams, or across patch/landscape boundaries (ecotones). Some organisms and flows may depend on the boundary shape, but metrics for defining linear boundary characteristics are scarce. While sinuosity and fractal dimension address some elements of shape, they fail to specify the dominate shape direction (convexity/concavity). We propose a method for measuring boundary convexity and assess its utility, along with sinuosity and fractal dimension, for predicting site selection by coastal river otters. First, we evaluate the characteristics of boundary convexity using a hypothetical boundary. Second, to compare convexity with other linear metrics boundary convexity, sinuosity and fractal dimension were calculated for the coastline of a set of islands in Prince William Sound, AK. Finally, we use logistic regression in an information-theoretic framework to assess site selection of river otters as a function of these linear metrics. Boundary convexity, fractal dimension and sinuosity are relatively uncorrelated at all scales. Otter latrine sites occurred at significantly more convex locations on the coastline than random sites. Using logistic regression and convexity values at the 100 m window-size, 69.5% of the latrine sites were correctly classified. Coastal terrestrial convexity appears to be a promising landscape-scale metric for predicting otter latrine sites. We suggest that boundary convexity may be an important landscape metric for describing species use or ecological flows at ecotones.     

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.     

Habitat attributes of landscape mosaics along a gradient of matrix development intensity: matrix management matters

The matrix is an important element of landscape mosaics that influences wildlife indirectly through its influence on habitat, and directly, if they live in or move through it. Therefore, to quantify and manage habitat quality for wildlife in modified landscapes, it is necessary to consider the characteristics of both patch and matrix elements of the whole landscape mosaic. To isolate matrix effects from the often simultaneous and confounding influence of patch and landscape characteristics, we identified nineteen 500 m radius landscapes in southeast Queensland, Australia with similar remnant forest patch attributes, habitat loss, and fragmentation, but exhibiting a marked gradient from rural through high-density suburban development of the matrix, quantified by a weighted road-length metric. We measured habitat disturbance, structure, and floristics in patch core, patch edge and matrix landscape elements to characterise how landscape habitat quality changes for small mammals. Correlation analyses identified that with increased matrix development intensity, human disturbance of core sites increased, predators and exotic plant species richness in matrix sites increased, and structural complexity (e.g. logs and stumps) in the matrix decreased. Ordination analyses showed landscape elements were most similar in habitat structure and floristics at low to moderate levels of matrix development, suggesting enhanced landscape habitat quality. Matrix development intensity was not, however, the greatest source of overall variation of habitat throughout landscapes. Many variables, such as landholder behaviour, complicate the relationship. For enhanced conservation outcomes the matrix needs to be managed to control disturbances and strategically plan for matrix habitat retention and restoration.     

Separating the effects of habitat area,fragmentation and matrix resistance on genetic differentiation in complex landscapes

Little is known about how variation in landscape mosaics affects genetic differentiation. The goal of this paper is to quantify the relative importance of habitat area and configuration, as well as the contrast in resistance between habitat and non-habitat, on genetic differentiation. We hypothesized that habitat configuration would be more influential than habitat area in influencing genetic differentiation. Population size is positively related to habitat area, and therefore habitat area should affect genetic drift, but not gene flow. In contrast, differential rates and patterns of gene flow across a landscape should be related to habitat configuration. Using spatially explicit, individual-based simulation modeling, we found that habitat configuration had stronger relationships with genetic differentiation than did habitat area, but there was a high degree of confounding between the effects of habitat area and configuration. We evaluated the predictive ability of six widely used landscape metrics and found that patch cohesion and correlation length of habitat are among the strongest individual predictors of genetic differentiation. Correlation length, patch density and clumpy are the most parsimonious set of variables to predict the magnitude of genetic differentiation in complex landscapes.     

The effects of the number,size and isolation of patches along a gradient of native vegetation cover: how can we increment habitat availability?

Habitat availability—or how much habitat species can reach at the landscape scale—depends primarily on the percentage of native cover. However, attributes of landscape configuration such as the number, size and isolation of habitat patches may have complementary effects on habitat availability, with implications for the management of landscapes. Here, we determined whether, and at which percentages of native cover, the number, size and isolation of patches contribute for habitat availability. We quantified habitat availability in 325 landscapes spread across the state of Rio de Janeiro, in the Atlantic Forest hotspot, with either high (>50 %), intermediate (50–30 %), low (30–10 %) or very low (<10 %) percentage of native cover, and for six hypothetical species differing in inter-patch dispersal ability. Above 50 % of native cover, the percentage of cover per se was the only determinant of habitat availability, but below 50 % the attributes of landscape configuration also contributed for habitat availability. The number of patches had a negative effect on habitat availability in landscapes with 50–10 % of native cover, whereas patch size had a positive effect in landscapes with <10 % of native cover. The different species generally responded to the same set of landscape attributes, although to different extents, potentially facilitating decision making for conservation. In landscapes with >50 % of native cover, conservation actions are probably sufficient to guarantee habitat availability, whereas in the remaining landscapes additional restoration efforts are needed, especially to reconnect and/or enlarge remaining habitat patches.