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.

     

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.

     

Analyzing land use change to identify migration corridors of African elephants (<Emphasis Type="Italic">Loxodonta africana</Emphasis>) in the Kenyan-Tanzanian borderlands

Context

East African ecosystems are characterized by the migrations of large herbivores that are highly vulnerable to the recent development of anthropogenic land use change.

Objectives

We analyzed land cover changes in the Kenyan-Tanzanian borderlands of the greater Amboseli ecosystem to evaluate landscape connectivity using African elephants as an indicator species.

Methods

We used multi-temporal Landsat imagery and a post classification approach to monitor land cover changes over a 43-year period. GIS based methods were accompanied by a literature review for spatial data on land cover changes and elephant migrations.

Results

Land cover changed considerably between 1975 and 2017. Wood- and bushlands declined by 16.3% while open grasslands increased throughout the study region (+?10.3%). Agricultural expansion was observed (+?12.2%) occupying important wildlife habitats and narrowing migration corridors. This development has led to the isolation of Nairobi National Park which was previously part of a large contiguous ecosystem. Eight migration corridors were identified of which only one is formally protected. Two others are almost completely blocked by agriculture and three are expected to become endangered under continuing land use changes.

Conclusions

Landscape connectivity is still viable for this ecosystem (except for Nairobi National Park). However, the current situation is very fragile as anthropogenic land use changes are threatening most of the identified large mammal migration corridors. Sustainable land use planning with regard to important wildlife habitats and connecting corridors is a crucial task for further conservation work to safeguard a viable future for wildlife populations in the Kenyan-Tanzanian borderlands.

     

A multi-method approach to delineate and validate migratory corridors

Context

Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models.

Objectives

We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania.

Methods

We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type.

Results

Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use.

Conclusions

The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.

     

How does habitat fragmentation affect the biodiversity and ecosystem functioning relationship?

Context

The relationship between biodiversity and ecosystem functioning (BEF) has been a central topic in ecology for more than 20 years. While experimental and theoretical studies have produced much knowledge of how biodiversity affects ecosystem functioning, it remains poorly understood how habitat fragmentation affects the BEF relationship.

Objectives

To develop a framework that connects habitat fragmentation to the BEF relationship from a landscape perspective.

Methods

We reviewed the literature on habitat fragmentation, BEF, and related fields, and developed a framework to analyze how habitat fragmentation affects the BEF relationship through altering biodiversity, environmental conditions, and both, based on the pattern-process-scale perspective in landscape ecology.

Results

Our synthesis of the literature suggests that habitat fragmentation can alter BEF relationship through several processes. First, habitat fragmentation causes the non-random loss of species that make major contributions to ecosystem functioning (decreasing sampling effect), and reduces mutualistic interactions (decreasing complementarity effects) regardless of the changes in species richness. Second, environmental conditions within patches and ecological flows among patches vary significantly with the degree of fragmentation, which potentially contributes to and modulates the BEF relationship.

Conclusions

Habitat fragmentation can affect the BEF relationship directly by altering community composition, as well as indirectly by changing environmental conditions within and among habitat patches on both local and landscape levels. The BEF relationship obtained from small plots and over short time periods may not fully represent that in real landscapes that are fragmented, dynamic, and continuously influenced by myriad human activities on different scales in time and space.

     

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.

     

Multi-scale habitat selection modeling: a review and outlook

Context

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

Objectives

Our goals in this review are to describe the conceptual origins of multi-scale habitat selection modeling, evaluate the current state-of-the-science, and suggest ways forward to improve analysis of scale-dependent habitat selection.

Methods

We reviewed more than 800 papers on habitat selection from 23 major ecological journals published between 2009 and 2014 and recorded a number of characteristics, such as whether they addressed habitat selection at multiple scales, what attributes of scale were evaluated, and what analytical methods were utilized.

Results

Our results show that despite widespread recognition of the importance of multi-scale analyses of habitat relationships, a large majority of published habitat ecology papers do not address multiple spatial or temporal scales. We also found that scale optimization, which is critical to assess scale dependence, is done in less than 5 % of all habitat selection modeling papers and less than 25 % of papers that address “multi-scale” habitat analysis broadly defined.

Conclusions

Our review confirms the existence of a powerful conceptual foundation for multi-scale habitat selection modeling, but that the majority of studies on wildlife habitat are still not adopting multi-scale frameworks. Most importantly, our review points to the need for wider adoption of a formal scale optimization of organism response to environmental variables.

     

Revision and application of the LINKAGES model to simulate forest growth in central hardwood landscapes in response to climate change

Context

Global climate change impacts forest growth and methods of modeling those impacts at the landscape scale are needed to forecast future forest species composition change and abundance. Changes in forest landscapes will affect ecosystem processes and services such as succession and disturbance, wildlife habitat, and production of forest products at regional, landscape and global scales.

Objectives

LINKAGES 2.2 was revised to create LINKAGES 3.0 and used it to evaluate tree species growth potential and total biomass production under alternative climate scenarios. This information is needed to understand species potential under future climate and to parameterize forest landscape models (FLMs) used to evaluate forest succession under climate change.

Methods

We simulated total tree biomass and responses of individual tree species in each of the 74 ecological subsections across the central hardwood region of the United States under current climate and projected climate at the end of the century from two general circulation models and two representative greenhouse gas concentration pathways.

Results

Forest composition and abundance varied by ecological subsection with more dramatic changes occurring with greater changes in temperature and precipitation and on soils with lower water holding capacity. Biomass production across the region followed patterns of soil quality.

Conclusions

Linkages 3.0 predicted realistic responses to soil and climate gradients and its application was a useful approach for considering growth potential and maximum growing space under future climates. We suggest Linkages 3.0 can also can used to inform parameter estimates in FLMs such as species establishment and maximum growing space.

     

A bird’s eye view: using circuit theory to study urban landscape connectivity for birds

Context

Connectivity is fundamental to understanding how landscape form influences ecological function. However, uncertainties persist due to the difficulty and expense of gathering empirical data to drive or to validate connectivity models, especially in urban areas, where relationships are multifaceted and the habitat matrix cannot be considered to be binary.

Objectives

This research used circuit theory to model urban bird flows (i.e. ‘current’), and compared results to observed abundance. The aims were to explore the ability of this approach to predict wildlife flows and to test relationships between modelled connectivity and variation in abundance.

Methods

Circuitscape was used to model functional connectivity in Bedford, Luton/Dunstable, and Milton Keynes, UK, for great tits (Parus major) and blue tits (Cyanistes caeruleus), drawing parameters from published studies of woodland bird flows in urban environments. Model performance was then tested against observed abundance data.

Results

Modelled current showed a weak yet positive agreement with combined abundance for P. major and C. caeruleus. Weaker correlations were found for other woodland species, suggesting the approach may be expandable if re-parameterised.

Conclusions

Trees provide suitable habitat for urban woodland bird species, but their location in large, contiguous patches and corridors along barriers also facilitates connectivity networks throughout the urban matrix. Urban connectivity studies are well-served by the advantages of circuit theory approaches, and benefit from the empirical study of wildlife flows in these landscapes to parameterise this type of modelling more explicitly. Such results can prove informative and beneficial in designing urban green space and new developments.

     

Accessible habitat delineated by a highway predicts landscape-scale effects of habitat loss in an amphibian community

Context

Habitat loss and habitat fragmentation negatively affect amphibian populations. Roads impact amphibian species through barrier effects and traffic mortality. The landscape variable ‘accessible habitat’ considers the combined effects of habitat loss and roads on populations.

Objectives

The aim was to test whether accessible habitat was a better predictor of amphibian species richness than separate measures of road effects and habitat loss. I assessed how accessible habitat and local habitat variables determine species richness and community composition.

Methods

Frog and tadpole surveys were conducted at 52 wetlands in a peri-urban area of eastern Australia. Accessible habitat was delineated using a highway. Regressions were used to examine relationships between species richness and eleven landscape and local habitat variables. Redundancy analysis was used to examine relationships between community composition and accessible habitat and local habitat variables.

Results

Best-ranked models of species richness included both landscape and local habitat variables. There were positive relationships between species richness and accessible habitat and distance to the highway, and uncertain relationships with proportion cover of native vegetation and road density. There were negative relationships between species richness and concreted wetlands and wetland electrical conductivity. Four species were positively associated with accessible habitat, whereas all species were negatively associated with wetland type.

Conclusions

Barrier effects caused by the highway and habitat loss have negatively affected the amphibian community. Local habitat variables had strong relationships with species richness and community composition, highlighting the importance of both availability and quality of habitat for amphibian conservation near major roads.

     

Integrating land cover structure and functioning to predict biodiversity patterns: a hierarchical modelling framework designed for ecosystem management

Context

Land-use/land-cover (LU/LC) dynamics is one of the main drivers of global environmental change. In the last years, aerial and satellite imagery have been increasingly used to monitor the spatial extent of changes in LU/LC, deriving relevant biophysical parameters (i.e. primary productivity, climate and habitat structure) that have clear implications in determining spatial and temporal patterns of biodiversity, landscape composition and ecosystem services.

Objectives

An innovative hierarchical modelling framework was developed in order to address the influence of nested attributes of LU/LC on community-based ecological indicators.

Methods

Founded in the principles of the spatially explicit stochastic dynamic methodology (StDM), the proposed methodological advances are supported by the added value of integrating bottom-up interactions between multi-scaled drivers.

Results

The dynamics of biophysical multi-attributes of fine-scale subsystem properties are incorporated to inform dynamic patterns at upper hierarchical levels. Since the most relevant trends associated with LU/LC changes are explicitly modelled within the StDM framework, the ecological indicators’ response can be predicted under different social-economic scenarios and site-specific management actions. A demonstrative application is described to illustrate the framework methodological steps, supporting the theoretic principles previously presented.

Conclusions

We outline the proposed multi-model framework as a promising tool to integrate relevant biophysical information to support ecosystem management and decision-making.

     

Linking ecosystem services,urban form and green space configuration using multivariate landscape metric analysis

Context

Landscape metrics represent powerful tools for quantifying landscape structure, but uncertainties persist around their interpretation. Urban settings add unique considerations, containing habitat structures driven by the surrounding built-up environment. Understanding urban ecosystems, however, should focus on the habitats rather than the matrix.

Objectives

We coupled a multivariate approach with landscape metric analysis to overcome existing shortcomings in interpretation. We then explored relationships between landscape characteristics and modelled ecosystem service provision.

Methods

We used principal component analysis and cluster analysis to isolate the most effective measures of landscape variability and then grouped habitat patches according to their attributes, independent of the surrounding urban form. We compared results to the modelled provision of three ecosystem services. Seven classes resulting from cluster analysis were separated primarily on patch area, and secondarily by measures of shape complexity and inter-patch distance.

Results

When compared to modelled ecosystem services, larger patches up to 10 ha in size consistently stored more carbon per area and supported more pollinators, while exhibiting a greater risk of soil erosion. Smaller, isolated patches showed the opposite, and patches larger than 10 ha exhibited no additional areal benefit.

Conclusions

Multivariate landscape metric analysis offers greater confidence and consistency than analysing landscape metrics individually. Independent classification avoids the influence of the urban matrix surrounding habitats of interest, and allows patches to be grouped according to their own attributes. Such a grouping is useful as it may correlate more strongly with the characteristics of landscape structure that directly affect ecosystem function.

     

Locating wildlife crossings for multispecies connectivity across linear infrastructures

Context

Linear transportation infrastructures traverse and separate wildlife populations, potentially leading to their short- and long-term decline at local and regional scales. To attenuate such effects, we need wildlife crossings suitable for a wide range of species.

Objectives

We propose a method for identifying the best locations for wildlife crossings along linear infrastructures so as to improve the connectivity of species with varying degrees of mobility and living in different habitats. We evaluate highway impacts on mammal species.

Methods

The study area is the Grésivaudan Valley, France. We used allometric relationships to create eight virtual species and model their connectivity networks, developing a nested method defining populations by daily travel distances and connecting them by dispersal. We tested the gain in connectivity for each species produced by 100 and 600 crossing locations respectively in crossable, i.e. with crossing infrastructures, and uncrossable highway scenarios. We identified the crossings that optimize the connectivity of the maximum number of species combining the results in multivariate analyses.

Results

Highly mobile species needing a large habitat area were the most sensitive to highways. The importance of locomotive performance in structuring the graphs decreased with highway impermeability. Depending on the species, the best locations improved connectivity by 0–10 and 2–75 % respectively in the crossable and uncrossable scenarios. Compromise locations were found for seven of the eight species in both scenarios.

Conclusions

This method could guide planners in identifying crossing locations to increase the connectivity of different species at regional scales over the long term.

     

Multi-scale assessment of human-induced changes to Amazonian instream habitats

Context

Land use change and forest degradation have myriad effects on tropical ecosystems. Yet their consequences for low-order streams remain very poorly understood, including in the world´s largest freshwater basin, the Amazon.

Objectives

Determine the degree to which physical and chemical characteristics of the instream habitat of low-order Amazonian streams change in response to past local- and catchment-level anthropogenic disturbances.

Methods

To do so, we collected field instream habitat (i.e., physical habitat and water quality) and landscape data from 99 stream sites in two eastern Brazilian Amazon regions. We used random forest regression trees to assess the relative importance of different predictor variables in determining changes in instream habitat response variables.

Results

Multiple drivers, operating at multiple spatial scales, were important in determining changes in the physical habitat and water quality of the sites. Although we found few similarities in modelled relationships between the two regions, we observed non-linear responses of specific instream characteristics to landscape change; for example 20 % of catchment deforestation resulted in consistently warmer streams.

Conclusions

Our results highlight the importance of local riparian and catchment-scale forest cover in shaping instream physical environments, but also underscore the importance of other land use changes and activities, such as road crossings and upstream agriculture intensification. In contrast to the property-scale focus of the Brazilian Forest code, which governs environmental regulations on private land, our results reinforce the importance of catchment-wide management strategies to protect stream ecosystem integrity.

     

Habitat amount and quality,not patch size,determine persistence of a woodland-dependent mammal in an agricultural landscape

Context

The classical theory of island biogeography explains loss of species in fragmented landscapes as an effect of remnant patch size and isolation. Recently this has been challenged by the habitat amount and habitat continuum hypotheses, according to which persistence in modified landscapes is related to total habitat amount rather than habitat configuration or the ability of species to use all habitats to varying degrees. Distinguishing between these theories is essential for effective conservation planning in modified landscapes.

Objective

Identify which factors of habitat type, amount and configuration predict the persistence of a keystone woodland specialist, the eastern bettong Bettongia gaimardi, in a fragmented landscape.

Method

In the Midlands region of Tasmania we carried out camera surveys at 62 sites in summer and winter. We included habitat and landscape features to model whether habitat amount or patch size and isolation influenced the presence of the eastern bettong, and to measure effects of habitat quality.

Results

Habitat amount within a 1 km buffer was a better predictor of occupancy than patch size and isolation. Occupancy was also affected by habitat quality, indicated by density of regenerating stems.

Conclusion

Our results support the habitat amount hypothesis as a better predictor of presence. For a species that is able to cross the matrix between remnant patches and utilise multiple patches, the island biogeography concept does not explain habitat use in fragmented landscapes. Our results emphasize the value of small remnant patches for conservation of the eastern bettong, provided those patches are in good condition.

     

Past and predicted future effects of housing growth on open space conservation opportunity areas and habitat connectivity around National Wildlife Refuges

Context

Housing growth can alter suitability of matrix habitats around protected areas, strongly affecting movements of organisms and, consequently, threatening connectivity of protected area networks.

Objectives

Our goal was to quantify distribution and growth of housing around the U.S. Fish and Wildlife Service National Wildlife Refuge System. This is important information for conservation planning, particularly given promotion of habitat connectivity as a climate change adaptation measure.

Methods

We quantified housing growth from 1940 to 2000 and projected future growth to 2030 within three distances from refuges, identifying very low housing density open space, “opportunity areas” (contiguous areas with <6.17 houses/km²), both nationally and by USFWS administrative region. Additionally, we quantified number and area of habitat corridors within these opportunity areas in 2000.

Results

Our results indicated that the number and area of open space opportunity areas generally decreased with increasing distance from refuges and with the passage of time. Furthermore, total area in habitat corridors was much lower than in opportunity areas. In addition, the number of corridors sometimes exceeded number of opportunity areas as a result of habitat fragmentation, indicating corridors are likely vulnerable to land use change. Finally, regional differences were strong and indicated some refuges may have experienced so much housing growth already that they are effectively too isolated to adapt to climate change, while others may require extensive habitat restoration work.

Conclusions

Wildlife refuges are increasingly isolated by residential housing development, potentially constraining the movement of wildlife and, therefore, their ability to adapt to a changing climate.

     

Time-delayed influence of urban landscape change on the susceptibility of koalas to chlamydiosis

Context

Infectious diseases are important in the dynamics of many wildlife populations, but there is limited understanding of how landscape change influences susceptibility to disease.

Objectives

We aimed to quantify the time-delayed influence of spatial and temporal components of landscape change and climate variability on the prevalence of chlamydiosis in koala (Phascolarctos cinereus) populations in southeast Queensland, Australia.

Methods

We used data collected over 14 years (n = 9078 records) from a koala hospital along with time-lagged measures of landscape change and rainfall to conduct spatial and temporal analyses of the influence of landscape and environmental variables on prevalence of chlamydiosis and koala body condition.

Results

Areas with more suitable habitat were associated with higher levels of disease prevalence and better body condition, indicating that koalas were less likely to be impacted by chlamydiosis. More intact landscapes with higher proportions of total habitat are associated with a reduction in prevalence of chlamydiosis and a decrease in body condition. Increased annual rainfall contributed to a decrease in prevalence of chlamydiosis and an increase in body condition. Urbanization was associated with an increase in disease, however the effects of urban landscape change and climate variability on chlamydiosis may not manifest until several years later when overt disease impacts the population via effects upon body condition and reproductive success.

Conclusions

Our study highlights the importance of effects of landscape change and climate variability on disease prevalence in wildlife. This recognition is essential for long-term conservation planning, especially as disease often interacts with other threats.

     

Effects of landscape structure and temporal habitat dynamics on wintering mallard abundance

Context

Management of wintering waterfowl in North America requires adaptability because constant landscape and environmental change challenges existing management strategies regarding waterfowl habitat use at large spatial scales. Migratory waterfowl including mallards (Anas platyrhynchos) use the lower Mississippi Alluvial Valley (MAV) for wintering habitat, making this an important area of emphasis for improving wetland conservation strategies, while enhancing the understanding of landscape-use patterns.

Objectives

We used aerial survey data collected in the Arkansas portion of the MAV (ARMAV) to explain the abundance and distribution of mallards in relation to variable landscape conditions.

Methods

We used two-stage, hierarchical spatio-temporal models with a random spatial effect to identify covariates related to changes in mallard abundance and distribution within and among years.

Results

We found distinct spatio-temporal patterns existed for mallard distributions across the ARMAV and these distributions are dependent on the surrounding landscape structure and changing environmental conditions. Models performing best indicated seasonal surface water extent, rice field, wetland and fallow (uncultivated) fields positively influenced mallard presence. Rice fields, surface water and weather were found to influence mallard abundance. Additionally, the results suggest weather and changing surface water affects mallard presence and abundance throughout the winter.

Conclusions

Using novel datasets to identify which environmental factors drive changes in regional wildlife distribution and abundance can improve management by providing managers additional information to manage land over landscapes spanning private and public lands. We suggest our analytical approach may be informative in other areas and for other wildlife species.