[Show abstract][Hide abstract] ABSTRACT: Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., non-independence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.
[Show abstract][Hide abstract] ABSTRACT: The persistence of landscape-scale disturbance legacies in forested ecosystems depends in part on the nature and strength of feedback among disturbances, their effects, and subsequent recovery processes such as tree regeneration and canopy closure. We investigated factors affecting forest recovery rates over a 25-year time period in a large (6 million ha) landscape where geopolitical boundaries have resulted in important land management legacies (managed forests of Minnesota, USA; managed forests of Ontario, Canada; and a large unmanaged wilderness). Stand-replacing disturbance regimes were quantified across management zones, both inside and outside a central ecoregion, using a time series of classified land cover data constructed at 5-year intervals between 1975 and 2000. The temporally variable disturbance regime of the wilderness was characterized by fine-scaled canopy disturbances punctuated by less frequent large disturbance events (i.e., fire and blow down). The comparably consistent disturbance regimes of the managed forests of Minnesota and Ontario differed primarily in the size distribution of disturbances – principally clearcut harvesting. Using logistic regression we found that a combination of time since disturbance, mapped disturbance attributes, climate, and differences among management zones affected pixel-scale probabilities of forest recovery that reflect recovery rates. We conclude that the magnitude of divergence in landscape disturbance legacies of this region will be additionally reinforced by regional variations in the human and natural disturbance regimes and their interactions with forest recovery processes. Our analyses compliment traditional plot-scale studies that investigate post-disturbance recovery by (a) examining vegetation trends across a wide range of variability and (b) quantifying the cumulative effects of disturbances as they affect recovery rates over a broad spatial extent. Our findings therefore have implications for sustainable forestry, ecosystem-based management, and landscape disturbance and succession modeling.
Forest Ecology and Management 02/2014; 313:199–211. · 2.77 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: 1. Climate and land-use changes will require species to move large distances following shifts in their suitable habitats, which will frequently involve traversing intensively human-modified landscapes. Practitioners will therefore need to evaluate and act to enhance the degree to which habitat patches scattered throughout the landscape may function as stepping stones facilitating dispersal among otherwise isolated habitat areas.
2. We formulate a new generalized network model of habitat connectivity that accounts for the number of dispersing individuals and for long-distance dispersal processes across generations. By doing so, we bridge the gap between complex dynamic population models, which are generally too data demanding and hence difficult to apply in practical wide-scale decision-making, and simpler static connectivity models that only consider the amount of habitat that can be reached by a single average disperser during its life span.
3. We find that the loss of intermediate and sufficiently large stepping-stone habitat patches can cause a sharp decline in the distance that can be traversed by species (critical spatial thresholds) that cannot be effectively compensated by other factors previously regarded as crucial for long-distance dispersal (fat-tailed dispersal kernels, source population size).
4. We corroborate our findings by showing that our model largely outperforms previous connectivity models in explaining the large-scale range expansion of a forest bird species, the Black Woodpecker Dryocopus martius, over a 20-year period. 5. The capacity of species to exploit the opportunities created by networks of stepping-stone patches largely depends on species-specific life-history traits, suggesting that species assemblages traversing fragmented landscapes may be exposed to a spatial filtering process driving long-term changes in community composition.
6. Synthesis and applications. Previous static connectivity models seriously underestimate the importance of stepping-stone patches in sustaining rare but crucial dispersal events. We provide a conceptually broader model that shows that stepping stones (i) must be of sufficient size to be of conservation value, (ii) are particularly crucial for the spread of species (either native or invasive) or genotypes over long distances and (iii) can effectively reduce the isolation of the largest habitat blocks in reserves, therefore largely contributing to species persistence across wide spatial and temporal scales.
Journal of Applied Ecology 01/2014; 51(1):171-182. · 4.74 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Peripheral populations often experience more extreme environmental conditions than those in the centre of a species' range. Such extreme conditions include habitat loss, defined as a reduction in the amount of suitable habitat, as well as habitat fragmentation, which involves the breaking apart of habitat independent of habitat loss. The 'threshold hypothesis' predicts that organisms will be more affected by habitat fragmentation when the amount of habitat on the landscape is scarce (i.e., less than 30%) than when habitat is abundant, implying that habitat fragmentation may compound habitat loss through changes in patch size and configuration. Alternatively, the 'flexibility hypothesis' predicts that individuals may respond to increased habitat disturbance by altering their selection patterns and thereby reducing sensitivity to habitat loss and fragmentation. While the range of Canada lynx (Lynx canadensis) has contracted during recent decades, the relative importance of habitat loss and habitat fragmentation on this phenomenon is poorly understood. We used a habitat suitability model for lynx to identify suitable land cover in Ontario, and contrasted occupancy patterns across landscapes differing in cover, to test the 'threshold hypothesis' and 'flexibility hypothesis'. When suitable land cover was widely available, lynx avoided areas with less than 30% habitat and were unaffected by habitat fragmentation. However, on landscapes with minimal suitable land cover, lynx occurrence was not related to either habitat loss or habitat fragmentation, indicating support for the 'flexibility hypothesis'. We conclude that lynx are broadly affected by habitat loss, and not specifically by habitat fragmentation, although occurrence patterns are flexible and dependent on landscape condition. We suggest that lynx may alter their habitat selection patterns depending on local conditions, thereby reducing their sensitivity to anthropogenically-driven habitat alteration.
PLoS ONE 01/2014; 9(11):e113511. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Lichens can either disperse sexually through fungal spores or asexually through vegetative propagules and fragmentation. Understanding how genetic variation in lichens is distributed across a landscape can be useful to infer dispersal and establishment events in space and time as well as the conditions needed for this establishment. Most studies have sampled lichens across large spatial distances on the order of hundreds of kilometers, while here we sequence the internal transcribed spacer (ITS) for 113 samples of three Peltigera species sampling at a variety of small spatial scales. The maximum distance between sampled lichens was 3.7 km and minimum distance was approximately 20 cm. We find significant amounts of genetic diversity across all three species. For P. praetextata, two out of the three most common ITS genotypes exhibit spatial autocorrelation supporting short-range dispersal. Using rarefaction we estimate that all ITS genotypes in our sampling area have been found for P. praetextata and P. evansiana, but not P. canina. Comparing our results with other ITS data in the literature provides evidence for global dispersal for at least one sequence followed by the evolution of endemic haplotypes with wide dispersal and rare haplotypes with more local dispersal.
[Show abstract][Hide abstract] ABSTRACT: Bayesian state-space movement models have been proposed as a method of inferring behavioural states from movement paths (Morales et al. 2004), thereby providing insight into the behavioural processes from which patterns of animal space use arise in heterogeneous environments. It is not clear, however, how effective state-space models are at estimating behavioural states. We use stochastic simulations of two movement models to quantify how behavioural state movement characteristics affect classification error. State-space movement models can be a highly effective approach to estimating behavioural states from movement paths. Classification accuracy was contingent upon the degree of separation between the distributions that characterize the states (e.g. step length and turn angle distributions) and the relative frequency of the behavioural states. In the best case scenarios classification accuracy approached 100%, but was close to 0% when step length and turn angle distributions of each state were similar, or when one state was rare. Mean classification accuracy was uncorrelated with path length, but the variance in classification accuracy was inversely related to path length. Importantly, we find that classification accuracy can be predicted based on the separation between distributions that characterize the movement paths, thereby providing a method of estimating classification accuracy for real movement paths. We demonstrate this approach using radiotelemetry relocation data of 34 moose (Alces alces). We conclude that Bayesian state-space models offer powerful new opportunities for inferring behavioural states from relocation data.
Methods in Ecology and Evolution 05/2013; 4(5):433-441. · 5.92 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Understanding the consequences of environmental change on populations is an essential prerequisite for informed management of ecosystems and landscapes. In lieu of quantifying fitness effects directly, which is often difficult, behavioural functional responses provide insight into how animals balance trade-offs, and into thresholds in responses to environmental change.Here, we explore this principle using the response of moose Alces alces L. to roads and restricted-access tracks as a case study. Because roads are associated with the conversion of conifer to mixed deciduous–conifer forest that provides better foraging opportunities, moose in Ontario favour areas of moderate road density at a landscape scale. At a finer scale, however, moose avoid roads. These opposing effects indicate a cost–benefit trade-off. We quantified behavioural responses of moose to roads using road-crossing rate. An expected distribution of crossing rates was derived from correlated random walk null model simulations.Moose exhibited a seasonally variable, nonlinear functional response in road-crossing rate at the within seasonal range scale. A pronounced response to roads was observed when road density reached approximate thresholds of 0·2 and 0·4 km km in summer and winter respectively. Road-crossing rate was proportional to road density, though crossing rates were higher in summer than winter. Crossing rates were best explained by the interaction between mean movement rate and road density. Seasonal differences in road-crossing rate arise from seasonal differences in movement rate and seasonal range area, but not road density within seasonal ranges. Within the protected park, moose did not appear to respond to tracks. Our analysis implies that for the majority of the landscape outside of protected areas the response of moose to roads is pronounced.Synthesis and applications. Identifying thresholds in nonlinear responses to landscape modification is a key management objective as they represent transition zones where small changes can have disproportionately large effects on wildlife populations. We establish these thresholds for moose and roads, but find no response to tracks, implying that the effects of tracks can be mitigated by restricting access to them. We discuss the implications of this work on the problem of moose–vehicle collisions.
Journal of Applied Ecology 04/2013; 50(2):286-294. · 4.74 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).
[Show abstract][Hide abstract] ABSTRACT: Woodpecker species have significantly expanded their ranges in the last decades of the twentieth century in Mediterranean Europe, which seems to be closely related to forest maturation following large-scale decline in traditional uses. Here we assess the explicit role of forest landscape connectivity in the colonization of the Great Spotted Woodpecker (Dendrocopos major) and the Black Woodpecker (Dryocopus martius) in Catalonia (NE Spain). For this purpose we combined data on breeding bird atlas (10 × 10 km; 1980–2000) and forest inventories (c. 1 × 1 km, 2000). Forest connectivity was measured through graph theory and habitat availability metrics (inter- and intra-patch connectivity) according to species median natal dispersal distances. The best regressions from a set of alternative models were selected based on AICc. Results showed that connectivity between areas of mature forests [diameter at breast height (dbh) ≥ 35 cm] affected Black Woodpecker colonization events. The probability of colonization of the Great Spotted Woodpecker was greater at localities near the sources of colonization in 1980 and with a high connectivity with other less developed forest patches (dbh < 35 cm). The spatial grain at which landscape connectivity was measured influenced the model performance according to the species dispersal abilities, with the species with the lower mobility (D. major) responding better to the forest connectivity patterns at finer spatial scales. Overall, it seems that both species could expand further in European Mediterranean forests in upcoming years but at slower rates if landscape connectivity according to species requirements does not continue to increase. Hence, a proactive and adaptive management should be carried out in order to preserve these species while considering the related major impacts of global change in Mediterranean Europe.
European Journal of Forest Research 01/2013; 132(1). · 1.96 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Available data show that future changes in global change drivers may lead to an increasing impact of fires on terrestrial ecosystems worldwide. Yet, fire regime changes in highly humanised fire-prone regions are difficult to predict because fire effects may be heavily mediated by human activities We investigated the role of fire suppression strategies in synergy with climate change on the resulting fire regimes in Catalonia (north-eastern Spain). We used a spatially-explicit fire-succession model at the landscape level to test whether the use of different firefighting opportunities related to observed reductions in fire spread rates and effective fire sizes, and hence changes in the fire regime. We calibrated this model with data from a period with weak firefighting and later assess the potential for suppression strategies to modify fire regimes expected under different levels of climate change. When comparing simulations with observed fire statistics from an eleven-year period with firefighting strategies in place, our results showed that, at least in two of the three sub-regions analysed, the observed fire regime could not be reproduced unless taking into account the effects of fire suppression. Fire regime descriptors were highly dependent on climate change scenarios, with a general trend, under baseline scenarios without fire suppression, to large-scale increases in area burnt. Fire suppression strategies had a strong capacity to compensate for climate change effects. However, strong active fire suppression was necessary to accomplish such compensation, while more opportunistic fire suppression strategies derived from recent fire history only had a variable, but generally weak, potential for compensation of enhanced fire impacts under climate change. The concept of fire regime in the Mediterranean is probably better interpreted as a highly dynamic process in which the main determinants of fire are rapidly modified by changes in landscape, climate and socioeconomic factors such as fire suppression strategies.
PLoS ONE 01/2013; 8(5):e62392. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Aim: We investigate first whether fire regimes resulting from the combination of climate change and fire-fighting policy may affect species distributions in Mediterranean landscapes, and second to what extent distributional dynamics may be constrained by the spatial legacy of historical land use. Location: Catalonia (north-eastern Spain). Methods: We modelled the distributional responses of 64 forest and open-habitat bird species to nine fire-regime scenarios, defined by combining different levels of climate change and fire suppression efficiency. A fire-succession model was used to stochastically simulate land-cover changes between 2000 and 2050 under these scenarios. We used species distribution models to predict habitat suitability and occupancy dynamics under either no dispersal or full dispersal assumptions. Results: Under many simulated scenarios, the succession from shrubland to forest dominated over the creation of new low-vegetation areas derived from wildfires. Consequently, open-habitat specialists were the group most affected by losses of suitable habitat. Fire regimes obtained under scenarios including high fire suppression efficiency resulted in a larger number of bird species experiencing reductions in their distribution area. Main conclusions: Anthropogenic factors, such as historical land-use change and fire suppression, can drive regional distribution dynamics in directions opposite to those expected from climatic trends. This raises the question of what drivers and interactions should be given priority in the prediction of biodiversity responses to global change at the regional scale.
Journal of Biogeography 01/2013; · 4.86 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: 1. Variation in forest gap size and duration are a result of spatial contiguity and continuity of gap infilling and tree mortality over time, which influences both species recruitment and successional pathways. 2. As many gaps in boreal forests are small, their size and duration will affect the conditions influencing species recruitment. We investigate the spatial dynamics of these gaps (i.e. those which are persistent, ephemeral, expanding, displaced or disappearing) and tested whether gap spatio-temporal patterns are consistent over different temporal periods (1998—2003 and 2003—2007). 3. Forest canopy gaps were reconstructed for three plots (10, 10 and 6 ha in size) in southern boreal mixedwood forests around Lake Duparquet, north-western Quebec (Canada), using a time series of high-resolution canopy surface profiles from three light and ranging detection (lidar) system surveys during a 9-year window. High-resolution images were used to individually identify early and late successional gap makers. Dynamic changes in canopy gaps over a 9-year period were investigated by implementing concepts of random set theory within a temporal GIS framework. Mortality was higher on the gap edges than in the forest interior, and shade tolerant species were more likely to be gap makers than shade intolerant species. Edge trees that died causing the expansion of gaps were much smaller than trees creating new gaps. Although the overall gap size distribution was consistent over the 9 years studied, the proportion of the total area opening and closing varied between periods. Independent analyses of time windows show an abundance of small gaps (below 40 cm²) appearing and disappearing; however, analysis of spatial contiguity shows that the majority (over 80%) of gaps of all sizes were displaced and/or expanded. 4. Synthesis. Contrary to the previous perception that small gaps are ephemeral, which would favour the recruitment of late successional species, our findings indicate that gap displacement and expansion may be a mechanism explaining the maintenance of favourable conditions for the recruitment of shade intolerant individuals, which has been previously observed in high-latitude old-growth boreal forests.
Journal of Ecology 09/2012; 100(5):1257-1268. · 5.69 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Understanding how landscape heterogeneity constrains gene flow and the spread of adaptive genetic variation is important for biological conservation given current global change. However, the integration of population genetics, landscape ecology and spatial statistics remains an interdisciplinary challenge at the levels of concepts and methods. We present a conceptual framework to relate the spatial distribution of genetic variation to the processes of gene flow and adaptation as regulated by spatial heterogeneity of the environment, while explicitly considering the spatial and temporal dynamics of landscapes, organisms and their genes. When selecting the appropriate analytical methods, it is necessary to consider the effects of multiple processes and the nature of population genetic data. Our framework relates key landscape genetics questions to four levels of analysis: (i) node-based methods, which model the spatial distribution of alleles at sampling locations (nodes) from local site characteristics; these methods are suitable for modeling adaptive genetic variation while accounting for the presence of spatial autocorrelation. (ii) Link-based methods, which model the probability of gene flow between two patches (link) and relate neutral molecular marker data to landscape heterogeneity; these methods are suitable for modeling neutral genetic variation but are subject to inferential problems, which may be alleviated by reducing links based on a network model of the population. (iii) Neighborhood-based methods, which model the connectivity of a focal patch with all other patches in its local neighborhood; these methods provide a link to metapopulation theory and landscape connectivity modeling and may allow the integration of node- and link-based information, but applications in landscape genetics are still limited. (iv) Boundary-based methods, which delineate genetically homogeneous populations and infer the location of genetic boundaries; these methods are suitable for testing for barrier effects of landscape features in a hypothesis-testing framework. We conclude that the power to detect the effect of landscape heterogeneity on the spatial distribution of genetic variation can be increased by explicit consideration of underlying assumptions and choice of an appropriate analytical approach depending on the research question.
[Show abstract][Hide abstract] ABSTRACT: Aim Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.Location Europe, North America and South America.Methods The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with pre-defined distributions and amounts of niche overlap to evaluate several ordination and species distribution modelling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.Results We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographical space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.Main conclusions The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate for studying niche differences between species, subspecies or intra-specific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intra-specific lineage has changed over time.
Global Ecology and Biogeography. 03/2012; 21(4):481 - 497.
[Show abstract][Hide abstract] ABSTRACT: Factors affecting the distribution and abundance of animals are of substantial interest, and across most of their southern range, populations of moose (Alces alces (L., 1758)) are declining, presumably because of climate change. Conditions favouring moose population decline versus numerical increase in select areas of the range are not well understood. During 2006–2009, we tested the hypothesis that moose in southern Ontario formed a viable population near the species’ southern range limit, despite occurrence of climate patterns apparently deleterious for population growth. Our study upheld each of our predictions: (i) high pregnancy rate (83.0%) and annual female survival rate (0.899 (0.859, 0.941; 95% CI)), indicating that the population was increasing (λ = 1.16); (ii) female moose having blood-based condition indices within normal range, despite larger than expected home-range size; and (iii) levels of genetic differentiation indicating that the population was part of a larger metapopulation of moose in the region. We surmise that moose in southern Ontario currently are not subject to the prevalent continental decline, likely owing to favourable site-specific climatic conditions. Future research should elaborate on why select southern moose populations are increasing and whether they will ultimately succumb to die off as effects of climate change become increasingly pronounced.
Canadian Journal of Zoology 03/2012; 90(3):422-434. · 1.50 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.
[Show abstract][Hide abstract] ABSTRACT: Landscape connectivity is a multi-scalar concept
allowing the investigation of how the interaction
between species movement abilities and landscape
structure affects species survival, gene flow and other
key ecological processes in fragmented landscapes.
This requires the determination of functional connectivity
which is the end result of a complex combination
of multiple factors such as habitat amount and
arrangement, matrix quality and permeability, species
perceptions and dispersal behaviour, population density,
etc. Functional connectivity quantification necessitates
also the consideration of the impacts and
constraints imposed by the increasing rates of landscape
and environmental change, which are ultimately
driven by socioeconomic factors and are likely to
continue putting more pressures on both managed and
[Show abstract][Hide abstract] ABSTRACT: To further our understanding of invasive species’ novel distributions, knowledge of invasive species’ relationships with environmental variables at multiple spatial scales is paramount. Here, we investigate which environmental variables and which spatial scales best explain the invasive mute swan’s (Cygnus olor) distribution in southern Ontario (Canada). Specifically we model mute swan distribution changes according to ecologically-relevant spatial scales: average territory size radius, 140 m; median dispersal distance of cygnets, 3,000 m; and average activity distance of males, 8,000 m. For individual spatial scales, global models using variables measured at each particular scale result in the highest Akaike weights, AUC, and Cohen’s Kappa values. Yet composite models (models combining variables measured at different scales) elicit the best models, as determined by higher Akaike weights and high AUC and Cohen’s Kappa values. Overall, percent water, waterbody perimeter density, temperature, precipitation, and road density are positively correlated with mute swan distribution, while percent forest and elevation are negatively correlated at all scales of analysis. Only percent water and annual precipitation are more influential in determining mute swan distribution at the 3,000 and 8,000 m zone scales than the territory scale. While most species distribution models are performed at a single scale, the results of our study suggest that composite models reflecting a species’ ecological needs provide models of better fit with similar, if not better, predictive accuracy. When analyzing species distributions, we also recommend that ecologists consider the scale of the underlying landscape processes and the effect that this may have on their modelling outcomes.