Multi-scale Mexican spotted owl (<Emphasis Type="Italic">Strix occidentalis lucida</Emphasis>) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

Context

Organisms commonly respond to their environment across a range of scales, however many habitat selection studies still conduct selection analyses using a single-scale framework. The adoption of multi-scale modeling frameworks in habitat selection studies can improve the effectiveness of these studies and provide greater insights into scale-dependent relationships between species and specific habitat components.

Objectives

Our study assessed multi-scale nest/roost habitat selection of the federally “Threatened” Mexican spotted owl (Strix occidentalis lucida) in northern Arizona, USA in an effort to provide improved conservation and management strategies for this subspecies.

Methods

We conducted multi-scale habitat modeling to assess habitat selection by Mexican spotted owls using survey data collected by the USFS. Each selected covariate was included in multi-scale models at their “characteristic scale” and we used an all-subsets approach and model selection framework to assess habitat selection.

Results

The “characteristic scale” identified for each covariate varied considerably among covariates and results from multi-scale models indicated that percent canopy cover and slope were the most important covariates with respect to habitat selection by Mexican spotted owls. Multi-scale models consistently outperformed their analogous single-scale counterparts with respect to the proportion of deviance explained and model predictive performance.

Conclusions

Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective conservation and management strategies.

     

Multi-level,multi-scale habitat selection by a wide-ranging,federally threatened snake

Context

Although multi-scale approaches are commonly used to assess wildlife-habitat relationships, few studies have examined selection at multiple spatial scales within different hierarchical levels/orders of selection [sensu Johnson’s (1980) orders of selection]. Failure to account for multi-scale relationships within a single level of selection may lead to misleading inferences and predictions.

Objectives

We examined habitat selection of the federally threatened eastern indigo snake (Drymarchon couperi) in peninsular Florida at the level of the home range (Level II selection) and individual telemetry location (Level III selection) to identify influential habitat covariates and predict relative probability of selection.

Methods

Within each level, we identified the characteristic scale for each habitat covariate to create multi-scale resource selection functions. We used home range selection functions to model Level II selection and paired logistic regression to model Level III selection.

Results

At both levels, EIS selected undeveloped upland land covers and habitat edges while avoiding urban land covers. Selection was generally strongest at the finest scales with the exception of Level II urban edge which was avoided at a broad scale indicating avoidance of urbanized land covers rather than urban edge per se.

Conclusions

Our study illustrates how characteristic scales may vary within a single level of selection and demonstrates the utility of multi-level, scale-optimized habitat selection analyses. We emphasize the importance of maintaining large mosaics of natural habitats for eastern indigo snake conservation.

     

Using step and path selection functions for estimating resistance to movement: pumas as a case study

Context

GPS telemetry collars and their ability to acquire accurate and consistently frequent locations have increased the use of step selection functions (SSFs) and path selection functions (PathSFs) for studying animal movement and estimating resistance. However, previously published SSFs and PathSFs often do not accommodate multiple scales or multi-scale modeling.

Objectives

We present a method that allows multiple scales to be analyzed with SSF and PathSF models. We also explore the sensitivity of model results and resistance surfaces to whether SSFs or PathSFs are used, scale, prediction framework, and GPS collar sampling interval.

Methods

We use 5-min GPS collar data from pumas (Puma concolor) in southern California to model SSFs and PathSFs at multiple scales, to predict resistance using two prediction frameworks (paired and unpaired), and to explore potential bias from GPS collar sampling intervals.

Results

Regression coefficients were extremely sensitive to scale and pumas exhibited multiple scales of selection during movement. We found PathSFs produced stronger regression coefficients, larger resistance values, and superior model performance than SSFs. We observed more heterogeneous surfaces when resistance was predicted in a paired framework compared with an unpaired framework. Lastly, we observed bias in habitat use and resistance results when using a GPS collar sampling interval longer than 5 min.

Conclusions

The methods presented provide a novel way to model multi-scale habitat selection and resistance from movement data. Due to the sensitivity of resistance surfaces to method, scale, and GPS schedule, care should be used when modeling corridors for conservation purposes using these methods.

     

Seasonal and temporal changes in species use of the landscape: how do they impact the inferences from multi-scale habitat modeling?

Context

Multi-scale approaches to habitat modeling have been shown to provide more accurate understanding and predictions of species-habitat associations. It remains however unexplored how spatial and temporal variations in habitat use may affect multi-scale habitat modeling.

Objectives

We aimed at assessing how seasonal and temporal differences in species habitat use and distribution impact operational scales, variable influence, habitat suitability spatial patterns, and performance of multi-scale models.

Methods

We evaluated the environmental factors driving brown bear habitat relationships in the Cantabrian Range (Spain) based on species presence records (ground observations) for the period 2000–2010, LiDAR data on forest structure, and seasonal estimates of foraging resources. We separately developed multi-scale habitat models for (i) each season (spring, summer, fall and winter) (ii) two sub-periods with different population status: 2000–2004 (with brown bear distribution restricted to the main population nuclei) and 2005–2010 (with expanding bear population and range); and (iii) the entire 2000–2010 period.

Results

Scales of effect remained considerably stable across seasonal and temporal variations, but not the influence of certain environmental variables. The predictive ability of multi-scale models was lower in the seasons or periods in which populations used larger areas and a broader variety of environmental conditions. Seasonal estimates of foraging resources, together with LiDAR data, appeared to improve the performance of multi-scale habitat models.

Conclusions

We highlight that the understanding of multi-scale behavioral responses of species to spatial patterns that continually shift over time may be essential to unravel habitat relationships and produce reliable estimates of species distributions.

     

Resource depletion versus landscape complementation: habitat selection by a multiple central place forager

Context

The spatial distribution of non-substitutable resources implies diverging predictions for animal movement patterns. At broad scales, animals should respond to landscape complementation by selecting areas where resource patches are close-by to minimize movement costs. Yet at fine scales, central place effects lead to the depletion of patches that are close to one another and that should ultimately be avoided by consumers.

Objectives

We developed a multi-scale resource selection framework to test whether animal movement is driven by landscape complementation or resource depletion and identify at which spatial scale these processes are relevant from an animal’s perspective.

Methods

During the dry season, surface water and forage are non-substitutable resources for African elephants. Eight family herds were tracked using GPS loggers in Hwange National Park, Zimbabwe. We explained habitat selection during foraging trips by mapping surface water at two scales with gaussian kernels of varying widths placed over each waterhole.

Results

Unexpectedly, elephants select areas with low waterhole density at both fine scales (< 1 km) and broad scales (5–7 km). Selection is stronger when elephants forage far away from water, even more so as the dry season progresses.

Conclusions

Elephant selection of low waterhole density areas suggests that resource depletion around multiple central places is the main driver of their habitat selection. By identifying the scale at which animals respond to waterhole distribution we provide a template for water management in arid and semi-arid landscapes that can be tailored to match the requirements and mobility of free ranging wild or domestic species.

     

Multi-scale prediction of landscape resistance for tiger dispersal in central India

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.

     

Shaken but not stirred: multiscale habitat suitability modeling of sympatric marten species (<Emphasis Type="Italic">Martes martes</Emphasis> and <Emphasis Type="Italic">Martes foina</Emphasis>) in the northern Iberian Peninsula

Context

Multispecies and multiscale habitat suitability models (HSM) are important to identify the environmental variables and scales influencing habitat selection and facilitate the comparison of closely related species with different ecological requirements.

Objectives

This study explores the multiscale relationships of habitat suitability for the pine (Martes martes) and stone marten (M. foina) in northern Spain to evaluate differences in habitat selection and scaling, and to determine if there is habitat niche displacement when both species coexist.

Methods

We combined bivariate scaling and maximum entropy modeling to compare the multiscale habitat selection of the two martens. To optimize the HSM, the performance of three sampling bias correction methods at four spatial scales was explored. HSMs were compared to explore niche differentiation between species through a niche identity test.

Results

The comparison among HSMs resulted in the detection of a significant niche divergence between species. The pine marten was positively associated with cooler mountainous areas, low levels of human disturbance, high proportion of natural forests and well-connected forestry plantations, and medium-extent agroforestry mosaics. The stone marten was positively related to the density of urban areas, the proportion and extensiveness of croplands, the existence of some scrub cover and semi-continuous grasslands.

Conclusions

This study outlines the influence of the spatial scale and the importance of the sampling bias corrections in HSM, and to our knowledge, it is the first comparing multiscale habitat selection and niche divergence of two related marten species. This study provides a useful methodological framework for multispecies and multiscale comparatives.

     

Extent-dependent habitat selection in a migratory large herbivore: road avoidance across scales

Context

In southwestern Alberta, human development, including roads, is encroaching on the landscape and into the range of a partially migratory population of elk (Cervus elaphus).

Objectives

To quantify factors influencing among- and within-home-range selection of winter range in this population.

Methods

We studied individual habitat selection and road avoidance at two biologically relevant spatial scales. We outlined availability extents for 107 individual elk-years based on observed fall migration distance, and based on a minimum convex polygon around winter telemetry relocations. To model the response by elk to road disturbance, we fit a habitat-selection model to each elk-year at each of the two availability extents, and examined population-level and individual variation in space-use. We then evaluated the relationship between inferred selection at the two scales and the functional response in selection.

Results

Roads had a ubiquitous influence on elk across scales. Elk, individually and as a population, avoided roads when migrating to their winter range and within this seasonal home range. Individual elk that avoided roads more strongly relative to the population did so at both scales of analysis.Further, the avoidance of low-use roads decreased with increasing road density. These results support bottom-up habitat-selection patterns (i.e., scale-independent) and functional response in habitat selection.

Conclusions

Overall, using a multi-scale habitat selection analysis, we show that road avoidance is a major determinant of elk space-use behaviour across multiple scales. Consequently, any new road construction or increases in road-use intensity could have detrimental effects on migratory elk populations by restricting space-use.

     

Predicting species-habitat relationships: does body size matter?

Context

Allometric scaling laws are foundational to structuring processes from cellular to ecosystem levels. The idea that allometric relationships underlie species characteristic selection scales, the spatial scales at which species respond to landscape features, has recently been investigated, however, supporting empirical evidence is scarce.

Objectives

Lack of pattern can be explained by inaccurate estimation, low power, confounding factors, or absence of a relationship. In this paper, we evaluate the relationship between body size and species characteristic selection scales after overcoming limitations of previous study designs.

Methods

We conducted 1328 avian point counts across the state of Nebraska using the robust sampling design to account for imperfect detection. We used Bayesian latent indicator scale selection with N-mixture models to estimate species’ characteristic selection scales of six habitat features for 86 species. We propagated the uncertainty associated with assigning characteristic scales to a model of the relationship between body size and characteristic spatial scales.

Results

Species characteristic scales varied across habitat predictors, and varied in the uncertainty associated with selecting single characteristic scales. After propagating uncertainty our results do not support a relationship between species’ body size and the spatial scales at which they respond to landscape features.

Conclusions

As species abundance integrates birth, death, immigration, and emigration processes, each of which are influenced by ecological processes manifesting at various scales, we question whether a general allometric relationship should be expected. Our results suggest that selection may act on responses to specific environmental features, rather than responses to spatial scale per se.

     

Influences of scale on bat habitat relationships in a forested landscape in Nicaragua

Context

Scale dependence of bat habitat selection is poorly known with few studies evaluating relationships among landscape metrics such as class versus landscape, or metrics that measure composition or configuration. This knowledge can inform conservation approaches to mitigate habitat loss and fragmentation.

Objectives

We evaluated scale dependence of habitat associations and scaling patterns of landscape metrics in relation to bat occurrence or capture rate in forests of southwestern Nicaragua.

Methods

We captured 1537 bats at 35 locations and measured landscape and class metrics across 10 spatial scales (100–1000 m) surrounding capture locations. We conducted univariate scaling across the 10 scales and identified scales and variables most related to bat occurrence or capture rate.

Results

Edge and patch density, at both landscape and class levels, were the most important variables across species. Feeding guilds varied in their response to metrics. Certain landscape and configuration metrics were most influential at fine (100 m) and/or broad (1000 m) spatial scales while most class and composition metrics were influential at intermediate scales.

Conclusions

These results provide insight into the scale dependence of habitat associations of bat species and the influence of fine and broad scales on habitat associations. The effects of scale, examined in our study and others from fine (100 m) to broad (5 km) indicate habitat relationships for bats may be more informative at larger scales. Our results suggest there could be general differences in scale relationships for different groups of landscape metrics, which deserves further evaluation in other taxonomic groups.

     

Grain-dependent functional responses in habitat selection

Context

Spatial scale is an important consideration for understanding how animals select habitat, and multi-scalar designs in resource selection studies have become increasingly common. Despite this, examination of functional responses in habitat selection at multiple scales is rare. The perceptual range of an animal changes as a function of vegetation association, suggesting that use, selection and functional responses may all be habitat- and scale-dependent.

Objectives

Our objective was to determine how varying grain size affects our interpretation of functional response in habitat selection and to elucidate scalar and landscape effects on habitat selection.

Methods

We quantified the functional response of GPS-collared, female white-tailed deer (Odocoileus virginianus, n = 18) in Riding Mountain National Park, Canada, to different habitat types. Functional responses were quantified at multiple spatial scales by regressing proportion of habitat used against proportion of habitat available at different buffer radii (ranging from 75–1000 m radius) surrounding used (telemetry) locations and available points within the individual’s seasonal home range. We examined how functional responses changed as a function of grain by plotting grain size against the slope of the functional response.

Results

We detected functional responses in most habitat types. As expected, functional responses tended to converge towards 1 (use proportional to availability) at large buffer sizes; however, the relationship between scale and functional response was typically non-linear and depended on habitat type.

Conclusions

We conclude that a multi-scalar approach to modelling animal functional responses in habitat selection is important for understanding patterns in animal behaviour and resource use.

     

Habitat connectivity and complexity underpin fish community structure across a seascape of tropical macroalgae meadows

Context

In heterogeneous landscapes, local patterns of community structure are a product of the habitat size and condition within a patch interacting with adjacent habitat patches of varying composition and quantity. While evidence for local versus landscape factors have been found in terrestrial biomes, support for such multi-scale effects shaping marine ecological communities is equivocal.

Objectives

We investigated whether within-patch habitat condition can override seascape context to explain the community structure of macroalgae-associated reef fishes across a tropical seascape.

Methods

We mapped the distribution and abundance of a diverse family of reef fishes (Labridae) occupying macroalgae meadows within a tropical reef ecosystem, and using best-subsets model selection, investigated the potential for habitat structural connectivity and/or local habitat quality for predicting variations in fish community structure across the seascape.

Results

Local habitat quality (canopy structure, hard habitat complexity) and area of coral-dominated habitat within 500 m of a macroalgal meadow provided the best predictors of fish community structure. However, the specific importance of a given predictor varied with fish life history stage and functional trophic group. Interestingly, macroalgae meadow area was among the least important predictors.

Conclusions

Given the complex interplay between local habitat quality and spatial context effects on fish biodiversity, our study reveals the multi-scale predictors that should be used in spatial conservation and management approaches for tropical fish diversity. Moreover, our findings question the ubiquity of habitat area effects in patchy landscapes, and cautions against a sole reliance on habitat quantity in spatial management.

     

One size does not fit all: European bison habitat selection across herds and spatial scales

Context

Understanding habitat selection can be challenging for species surviving in small populations, but is needed for landscape-scale conservation planning.

Objectives

We assessed how European bison (Bison bonasus) habitat selection, and particularly forest use, varies across subpopulations and spatial scales.

Methods

We gathered the most comprehensive European bison occurrence dataset to date, from five free-ranging herds in Poland. We compared these data to a high-resolution forest map and modelled the influence of environmental and human-pressure variables on habitat selection.

Results

Around 65% of European bison occurrences were in forests, with cows showing a slightly higher forest association than bulls. Forest association did not change markedly across spatial scales, yet differed strongly among herds. Modelling European bison habitat suitability confirmed forest preference, but also showed strong differences in habitat selection among herds. Some herds used open areas heavily and actively selected for them. Similarly, human-pressure variables were important in all herds, but some herds avoided human-dominated areas more than others.

Conclusions

Assessing European bison habitat across multiple herds revealed a more generalist habitat use pattern than when studying individual herds only. Our results highlight that conflicts with land use and people could be substantial if bison are released in human-dominated landscapes. Future restoration efforts should target areas with low road and human population density, regardless of the degree of forest cover. More broadly, our study highlights the importance of considering multiple subpopulations and spatial scales in conservation planning.

     

Multi-scale network analysis shows scale-dependency of significance of individual protected areas for connectivity

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.

     

Stop using dichotomous terms to reference observations of scale-dependent habitat selection

Context

Many studies dichotomize habitat selection into “local” or “landscape” effects, with little explanation regarding what each represents. Ambiguous use of these terms across studies may confound observations of selection operating across different spatiotemporal resolutions and impede synthesis of scale-dependent habitat selection.

Objective

To examine the consistency of use of the terms “local” and “landscape” level habitat selection and evaluate potential implications for conservation science.

Methods

We reviewed 136 multi-level studies observing local and/or landscape effects. From each study, we identified which of Johnson’s (Ecology 61:65–71, 1980) selection orders was observed at the local and landscape scale. We assessed consistency in the selection order observed at each scale.

Results

At the local scale, 54% of studies observed 3rd order selection and 38% of studies observed 4th order selection. At the landscape scale, 64% of studies observed 2nd order selection, while only 8% of studies observed 1st order selection. Overlap also occurred; 2nd order selection was observed at the local scale in 8% of studies, while 3rd and 4th order selection was observed at the landscape scale in 24 and 3% of studies, respectively.

Conclusions

Selection orders observed at local and landscape scales are inconsistent across studies, making comparisons and synthesis difficult. This inconsistency makes the terms “local” and “landscape” meaningless, and may lead to misidentification of limiting factor(s) most important for conservation efforts. Dichotomous terms should no longer be used in reference to levels of selection, but in reference to specific explanatory variables whose characteristic scale(s) best fit the appropriate definition.

     

Using remote-sensing data to assess habitat selection of a declining passerine at two spatial scales

Context

Detailed information on habitat needs is integral to identify conservation measures for declining species. However, field data on habitat structure is typically limited in extent. Remote sensing has the potential to overcome these limitations of field-based studies.

Objective

We aimed to assess abiotic and biotic characteristics of territories used by the declining wood warbler (Phylloscopus sibilatrix), a forest-interior migratory passerine, at two spatial scales by evaluating a priori expectations of habitat selection patterns.

Methods

First, territories established by males before pairing, referred to as pre-breeding territories, were compared to pseudo-absence control areas located in the wider forested landscape (first spatial scale, N_territories = 66, N_controls = 66). Second, breeding territories of paired wood warblers were compared to true-absence control areas located immediately close-by in the forest (second spatial scale, N_territories = 78, N_controls = 78). Habitat variables predominantly described forest structure and were mainly based on first and last pulse lidar (light detection and ranging) data.

Results

Occurrence of pre-breeding territories was related to vegetation height, vertical diversity and stratification, canopy cover, inclination and solar radiation. Occurrence of breeding territories was associated to vegetation height, vertical diversity and inclination.

Conclusions

Territory selection at the two spatial scales addressed was governed by similar factors. With respect to conservation, habitat suitability for wood warblers could be retained by maintaining a shifting mosaic of stand ages and structures at large spatial scales. Moreover, leaf-off lidar variables have the potential to contribute to understanding the ecological niche of species in predominantly deciduous forests.

     

Landscape-scale distribution of tree roosts of the northern long-eared bat in Mammoth Cave National Park,USA

Context

The roosting habits of many temperate zone bats are well documented at microhabitat scales, but fewer studies have included multi-scale assessments of landscape patterns in bat roost site selection.

Objectives

To identify and assess at the landscape-scale the location of spring and early season maternity roosts of female northern long-eared bats (Myotis septentrionalis) from 2015 to 2016 at Mammoth Cave National Park (MACA), Kentucky, USA.

Methods

We used mist-nets and radiotelemetry to catch and track bats to roost trees across the landscape of MACA. Data on roosting sites were evaluated using spatial point pattern analysis to examine distributional trends of roosts. A variety of spatial covariates were used to model the effect of landscape pattern, including: forest type, elevation, and proximity to hibernacula, water, and road corridors.

Results

Data indicate that roost locations of female northern long-eared bats in MACA were typically situated within 2000 m of known winter hibernacula, occurring more often at higher elevations in mesic upland deciduous forests, and in close proximity to water sources and roads. We present hypotheses to account for the patterns observed in relation to landscape features and habitat resources in the Park.

Conclusions

Our data indicate that a more comprehensive understanding of habitat requirements which includes empirically-based, landscape-scale patterns, and not solely considerations at stand or local levels, could lead to better informed management policies targeting conservation of maternity habitat of forest-dwelling bats, including the northern long-eared bat, a species in decline throughout much of its distribution in North America.

     

Assessing wild bees in perennial bioenergy landscapes: effects of bioenergy crop composition,landscape configuration,and bioenergy crop area

Context

Wild bee populations are currently under threat, which has led to recent efforts to increase pollinator habitat in North America. Simultaneously, U.S. federal energy policies are beginning to encourage perennial bioenergy cropping (PBC) systems, which have the potential to support native bees.

Objectives

Our objective was to explore the potentially interactive effects of crop composition, total PBC area, and PBC patches in different landscape configurations.

Methods

Using a spatially-explicit modeling approach, the Lonsdorf model, we simulated the impacts of three perennial bioenergy crops (PBC: willow, switchgrass, and prairie), three scenarios with different total PBC area (11.7, 23.5 and 28.8% of agricultural land converted to PBC) and two types of landscape configurations (PBC in clustered landscape patterns that represent realistic future configurations or in dispersed neutral landscape models) on a nest abundance index in an Illinois landscape.

Results

Our modeling results suggest that crop composition and PBC area are particularly important for bee nest abundance, whereas landscape configuration is associated with bee nest abundance at the local scale but less so at the regional scale.

Conclusions

Strategies to enhance wild bee habitat should therefore emphasize the crop composition and amount of PBC.

     

Modeling relative habitat suitability of southern Florida for invasive Burmese pythons (<Emphasis Type="Italic">Python molurus bivittatus</Emphasis>)

Context

Invasive Burmese pythons are altering the ecology of southern Florida and their distribution is expanding northward. Understanding their habitat use is an important step in understanding the pathways of the invasion.

Objectives

This study identifies key landscape variables in predicting relative habitat suitability for pythons at the present stage of invasion through presence-only ecological niche modeling using geographical sampling bias correction.

Methods

We used 2014 presence-only observations from the EDDMapS database and three landscape variables to model habitat suitability: fine-scale land cover, home range-level land cover, and distance to open freshwater or wetland. Ten geographical sampling bias correction scenarios based on road presence and sampling effort were evaluated to improve the efficacy of modeling.

Results

The best performing models treated road presence as a binary factor rather than a continuous decrease in sampling effort with distance from roads. Home range-level cover contributed the most to the final prediction, followed by proximity to water and fine-scale land cover. Estuarine habitat and freshwater wetlands were the most important variables to contribute to python habitat suitability at both the home range-level and fine-scale. Suitability was highest within 30 m of open freshwater and wetlands.

Conclusions

This study provides quantifiable, predictive relationships between habitat types and python presence at the current stage of invasion. This knowledge can elucidate future targeted studies of python habitat use and behavior and help inform management efforts. Furthermore, it illustrates how estimates of relative habitat suitability derived from MaxEnt can be improved by both multi-scale perspectives on habitat and consideration of a variety of bias correction scenarios for selecting background points.