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.

     

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.

     

Integrating airborne lidar and satellite imagery to model habitat connectivity dynamics for spatial conservation prioritization

Context

The application of regional-level airborne lidar (light detection and ranging) data to characterize habitat patches and model habitat connectivity over large landscapes has not been well explored. Maintaining a connected network of habitat in the presence of anthropogenic disturbances is essential for regional-level conservation planning and the maintenance of biodiversity values.

Objectives

We quantified variation in connectivity following simulated changes in land cover and contrasted outcomes when different conservation priorities were emphasized.

Methods

First, we defined habitat patches using vegetation structural attributes identified via lidar. Second, habitat networks were constructed for different forest types and assessed using network connectivity metrics. And finally, land cover change scenarios were simulated using a series of habitat patch removals, representing the impact of implementing different spatial prioritization schemes.

Results

Networks for different forest structure types produced very different patch distributions. Conservation scenarios based on different schemes led to contrasting changes during land cover change simulations: the scheme prioritizing only habitat area resulted in immediate near-term losses in connectivity, whereas the scheme considering both habitat area and their spatial configurations maintained the overall connectivity most effectively. Adding climate constraints did not diminish or improve overall connectivity.

Conclusions

Both habitat area and habitat configuration should be considered in dynamic modeling of habitat connectivity under changing landscapes. This research provides a framework for integrating forest structure and cover attributes obtained from remote sensing data into network connectivity modeling, and may serve as a prototype for multi-criteria forest management and conservation planning.

     

Synergistic effects of climate and land cover: grassland birds are more vulnerable to climate change

Context

Climate change is not occurring over a homogeneous landscape and the quantity and quality of available land cover will likely affect the way species respond to climate change. The influence of land cover on species’ responses to climate change, however, is likely to differ depending on habitat type and composition.

Objectives

Our goal was to investigate responses of forest and grassland breeding birds to over 20 years of climate change across varying gradients of forest and grassland habitat. Specifically, we investigated whether (i) increasing amounts of available land cover modify responses of forest and grassland-dependent birds to changing climate and (ii) the effect of increasing land cover amount differs for forest and grassland birds.

Methods

We used Bayesian spatially-varying intercept models to evaluate species- and community-level responses of 30 forest and 10 grassland birds to climate change across varying amounts of their associated land cover types.

Results

Responses of forest birds to climate change were weak and constant across a gradient of forest cover. Conversely, grassland birds responded strongly to changing climatic conditions. Specifically, increasing temperatures led to higher probabilities of localized extinctions for grassland birds, and this effect was intensified in regions with low amounts of grassland cover.

Conclusions

Within the context of northeastern forests and grasslands, we conclude that forests serve as a possible buffer to the impacts of climate change on birds. Conversely, species occupying open, fragmented grassland areas might be particularly at risk of a changing climate due to the diminished buffering capacity of these ecosystems.

     

A tale of two wildfires; testing detection and prediction of invasive species distributions using models fit with topographic and spectral indices

Context

Developing species distribution models (SDMs) to detect invasive species cover and evaluate habitat suitability are high priorities for land managers.

Objectives

We tested SDMs fit with different variable combinations to provide guidelines for future invasive species model development based on transferability between landscapes.

Methods

Generalized linear model, boosted regression trees, multivariate adaptive regression splines, and Random Forests were fit with location data for high cheatgrass (Bromus tectorum) cover in situ for two post-burn sites independently using topographic indices, spectral indices derived from multiple dates of Landsat 8 satellite imagery, or both. Models developed for one site were applied to the other, using independent cheatgrass cover data from the respective ex situ site to test model transferability.

Results

Fitted models were statistically robust and comparable when fit with at least 200 cover plots in situ and transferred to the ex situ site. Only the Random Forests models were robust when fit with a small number of cover plots in situ.

Conclusions

Our study indicated spectral indices can be used in SDMs to estimate species cover across landscapes (e.g., both within the same Landsat scene and in an adjacent Landsat scene). Important considerations for transferability include the model employed, quantity of cover data used to train/test the models, and phenology of the species coupled with the timing of imagery. The results also suggest that when cover data are limited, SDMs fit with topographic indices are sufficient for evaluating cheatgrass habitat suitability in new post-disturbance landscapes; however, spectral indices can provide a more robust estimate for detection based on local phenology.

     

Assessing landscape functional connectivity in a forest carnivore using path selection functions

Context

Understanding connectivity patterns in relation to habitat fragmentation is essential to landscape management. However, connectivity is often judged from expert opinion or species occurrence patterns, with very few studies considering the actual movements of individuals. Path selection functions provide a promising tool to infer functional connectivity from animal movement data, but its practical application remains scanty.

Objectives

We aimed to describe functional connectivity patterns in a forest carnivore using path-level analysis, and to explore how connectivity is affected by land cover patterns and road networks.

Methods

We radiotracked 22 common genets in a mixed forest-agricultural landscape of southern Portugal. We developed path selection functions discriminating between observed and random paths in relation to landscape variables. These functions were used together with land cover information to map conductance surfaces.

Results

Genets moved preferentially within forest patches and close to riparian habitats. Functional connectivity declined with increasing road density, but increased with the proximity of culverts, viaducts and bridges. Functional connectivity was favoured by large forest patches, and by the presence of riparian areas providing corridors within open agricultural land. Roads reduced connectivity by dissecting forest patches, but had less effect on riparian corridors due to the presence of crossing structures.

Conclusions

Genet movements were jointly affected by the spatial distribution of suitable habitats, and the presence of a road network dissecting such habitats and creating obstacles in areas otherwise permeable to animal movement. Overall, the study showed the value of path-level analysis to assess functional connectivity patterns in human-modified landscapes.

     

Landscape and local effects on occupancy and densities of an endangered wood-warbler in an urbanizing landscape

Context

Golden-cheeked warblers (Setophaga chrysoparia), an endangered wood-warbler, breed exclusively in woodlands co-dominated by Ashe juniper (Juniperus ashei) in central Texas. Their breeding range is becoming increasingly urbanized and habitat loss and fragmentation are a main threat to the species’ viability.

Objectives

We investigated the effects of remotely sensed local habitat and landscape attributes on point occupancy and density of warblers in an urban preserve and produced a spatially explicit density map for the preserve using model-supported relationships.

Methods

We conducted 1507 point-count surveys during spring 2011–2014 across Balcones Canyonlands Preserve (BCP) to evaluate warbler habitat associations and predict density of males. We used hierarchical Bayesian models to estimate multiple components of detection probability and evaluate covariate effects on detection probability, point occupancy, and density.

Results

Point occupancy was positively related to landscape forest cover and local canopy cover; mean occupancy was 0.83. Density was influenced more by local than landscape factors. Density increased with greater amounts of juniper and mixed forest and decreased with more open edge. There was a weak negative relationship between density and landscape urban land cover.

Conclusions

Landscape composition and habitat structure were important determinants of warbler occupancy and density, and the large intact patches of juniper and mixed forest on BCP (>2100 ha) supported a high density of warblers. Increasing urbanization and fragmentation in the surrounding landscape will likely result in lower breeding density due to loss of juniper and mixed forest and increasing urban land cover and edge.

     

Assessing differences in connectivity based on habitat versus movement models for brown bears in the Carpathians

Context

Connectivity assessments typically rely on resistance surfaces derived from habitat models, assuming that higher-quality habitat facilitates movement. This assumption remains largely untested though, and it is unlikely that the same environmental factors determine both animal movements and habitat selection, potentially biasing connectivity assessments.

Objectives

We evaluated how much connectivity assessments differ when based on resistance surfaces from habitat versus movement models. In addition, we tested how sensitive connectivity assessments are with respect to the parameterization of the movement models.

Methods

We parameterized maximum entropy models to predict habitat suitability, and step selection functions to derive movement models for brown bear (Ursus arctos) in the northeastern Carpathians. We compared spatial patterns and distributions of resistance values derived from those models, and locations and characteristics of potential movement corridors.

Results

Brown bears preferred areas with high forest cover, close to forest edges, high topographic complexity, and with low human pressure in both habitat and movement models. However, resistance surfaces derived from the habitat models based on predictors measured at broad and medium scales tended to underestimate connectivity, as they predicted substantially higher resistance values for most of the study area, including corridors.

Conclusions

Our findings highlighted that connectivity assessments should be based on movement information if available, rather than generic habitat models. However, the parameterization of movement models is important, because the type of movement events considered, and the sampling method of environmental covariates can greatly affect connectivity assessments, and hence the predicted corridors.

     

Landscape heterogeneity and hydrological processes: a review of landscape-based hydrological models

Introduction

Landscapes and water are closely linked. Water shapes landscapes, and landscape heterogeneity in turn determines water storage, partitioning, and movement. Understanding hydrological processes from an ecological perspective is an exciting and fast-growing field of research.

Objectives

The motivation of this paper is to review advances in the interaction between landscape heterogeneity and hydrological processes, and propose a framework for synthesizing and moving forward.

Methods

Landscape heterogeneity, mainly topography and land cover, has been widely incorporated into existing hydrological models, but not in a systematic way. Topography, as one of the most important landscape traits, has been extensively used in hydrological models, but mostly to drive water flow downhill. Land cover heterogeneity, represented mostly by vegetation, is usually linked with evaporation and transpiration rather than runoff generation. Moreover, the proportion of different land cover types is usually the only index involved in hydrological models, leaving the influence of vegetation patterns and structure on hydrologic connectivity still largely unexplored. Additionally, moving from “what heterogeneity exists” to “why-type” questions probably offers us new insights into the nexus of landscape and water.

Conclusions

We believe that the principles of self-organization and co-evolution of landscape features shed light on the possibility to infer subsurface heterogeneity from a few observable landscapes, allowing us to simplify complexity to a few quantifiable metrics, and utilizing these metrics in models with sufficient heterogeneity but limited complexity. Landscape-based models can also be beneficial to improve our ability of prediction in ungauged basins and prediction in a changing environment (Panta Rhei, everything flows).

     

Effects of land use legacies and habitat fragmentation on salamander abundance

Context

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

Objectives

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

Methods

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

Results

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

Conclusions

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

     

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.

     

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.

     

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.

     

Landscape-scale modelling of agroforestry ecosystems services in Swiss orchards: a methodological approach

Context

Agroforestry systems in temperate Europe are known to provide both, provisioning and regulating ecosystem services (ES). Yet, it is poorly understood how these systems affect ES provision at a landscape scale in contrast to agricultural practises.

Objectives

This study aimed at developing a novel, spatially explicit model to assess and quantify bundles of provisioning and regulating ES provided by landscapes with and without agroforestry systems and to test the hypothesis that agroforestry landscapes provide higher amounts of regulating ES than landscapes dominated by monocropping.

Methods

Focussing on ES that are relevant for agroforestry and agricultural practices, we selected six provisioning and regulating ES—“biomass production”, “groundwater recharge”, “nutrient retention”, “soil preservation”, “carbon storage”, “habitat and gene pool protection”. Algorithms for quantifying these services were identified, tested, adapted, and applied in a traditional cherry orchard landscape in Switzerland, as a case study. Eight landscape test sites of 1 km?×?1 km, four dominated by agroforestry and four dominated by agriculture, were mapped and used as baseline for the model.

Results

We found that the provisioning ES, namely the annual biomass yield, was higher in landscape test sites with agriculture, while the regulating ES were better represented in landscape test sites with agroforestry. The differences were found to be statistically significant for the indicators annual biomass yield, groundwater recharge rate, nitrate leaching, annual carbon sequestration, flowering resources, and share of semi-natural habitats.

Conclusions

This approach provides an example for spatially explicit quantification of provisioning and regulating ES and is suitable for comparing different land use scenarii at landscape scale.

     

Vegetative and geomorphic complexity at tributary junctions on the Colorado and Dolores Rivers: a blueprint for riparian restoration

Context

Habitat complexity in rivers is linked to dynamic fluvial conditions acting at various spatial scales. On regulated rivers in the western United States, tributaries are regions of high energy and disturbance, providing important resource inputs for riparian ecosystems.

Objectives

This study investigated spatial patterns and extents of tributary influence on riparian habitat complexity in the near channel zone along regulated reaches of the Colorado (>?200 km) and Dolores Rivers (~?300 km) in the western United States. Because tributary confluences are regions of increased dynamism, we hypothesized that: (1) geomorphic and land cover complexity would be greatest close to tributary junctions and decrease with distance from tributaries; and (2) patterns in complexity would vary across different sized spatial units.

Methods

Using a combination of remote sensing and spatial analysis, we classified fluvial features and land cover classes to investigate patterns longitudinally at 10-, 25-, and 100-m spatial units in the near channel zone of two regulated rivers.

Results

Using change point analysis and randomization tests, we detected shifts in riparian habitat complexity closer to tributary junctions. Patterns varied across 10-, 25-, and 100-m spatial units in the near channel zone, with significance (p?≤?0.05) recorded for 10- and 25-m spatial units.

Conclusions

Tributary junctions deliver critical resource inputs on regulated systems, providing for increased geomorphic and land cover diversity upstream and downstream of tributaries. We found that patterns of response were non-linear and discontinuous, varying across spatial units and potentially influenced by the degree of mainstem flow regulation.

     

Additive and synergistic effects of land cover,land use and climate on insect biodiversity

Context

We address the issue of adapting landscapes for improved insect biodiversity conservation in a changing climate by assessing the importance of additive (main) and synergistic (interaction) effects of land cover and land use with climate.

Objectives

We test the hypotheses that ant richness (species and genus), abundance and diversity would vary according to land cover and land use intensity but that these effects would vary according to climate.

Methods

We used a 1000 m elevation gradient in eastern Australia (as a proxy for a climate gradient) and sampled ant biodiversity along this gradient from sites with variable land cover and land use.

Results

Main effects revealed: higher ant richness (species and genus) and diversity with greater native woody plant canopy cover; and lower species richness with higher cultivation and grazing intensity, bare ground and exotic plant groundcover. Interaction effects revealed: both the positive effects of native plant canopy cover on ant species richness and abundance, and the negative effects of exotic plant groundcover on species richness were greatest at sites with warmer and drier climates.

Conclusions

Impacts of climate change on insect biodiversity may be mitigated to some degree through landscape adaptation by increasing woody native vegetation cover and by reducing land use intensity, the cover of exotic vegetation and of bare ground. Evidence of synergistic effects suggests that landscape adaptation may be most effective in areas which are currently warmer and drier, or are projected to become so as a result of climate change.

     

Anuran responses to spatial patterns of agricultural landscapes in Argentina

Context

Amphibians are declining worldwide and land use change to agriculture is recognized as a leading cause. Argentina is undergoing an agriculturalization process with rapid changes in landscape structure.

Objectives

We evaluated anuran response to landscape composition and configuration in two landscapes of east-central Argentina with different degrees of agriculturalization. We identified sensitive species and evaluated landscape influence on communities and individual species at two spatial scales.

Methods

We compared anuran richness, frequency of occurrence, and activity between landscapes using call surveys data from 120 sampling points from 2007 to 2009. We evaluated anuran responses to landscape structure variables estimated within 250 and 500-m radius buffers using canonical correspondence analysis and multimodel inference from a set of candidate models.

Results

Anuran richness was lower in the landscape with greater level of agriculturalization with reduced amount of forest cover and stream length. This pattern was driven by the lower occurrence and calling activity of seven out of the sixteen recorded species. Four species responded positively to the amount of forest cover and stream habitat. Three species responded positively to forest cohesion and negatively to rural housing. Two responded negatively to crop area and diversity of cover classes.

Conclusions

Anurans within agricultural landscapes of east-central Argentina are responding to landscape structure. Responses varied depending on species and study scale. Life-history traits contribute to responses differences. Our study offers a better understanding of landscape effects on anurans and can be used for land management in other areas experiencing a similar agriculturalization process.

     

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.

     

Habitat functional response mitigates reduced foraging opportunity: implications for animal fitness and space use

Context

Animals selectively use landscapes to meet their energetic needs, and trade-offs in habitat use may depend on availability and environmental conditions. For example, habitat selection at high temperatures may favor thermal cover at the cost of reduced foraging efficiency under consistently warm conditions.

Objective

Our objective was to examine habitat selection and space use in distinct populations of moose (Alces alces). Hypothesizing that endotherm fitness is constrained by heat dissipation efficiency, we predicted that southerly populations would exhibit greater selection for thermal cover and reduced selection for foraging habitat.

Methods

We estimated individual step selection functions with shrinkage for 134 adult female moose in Minnesota, USA, and 64 in Ontario, Canada, to assess habitat selection with variation in temperature, time of day, and habitat availability. We averaged model coefficients within each site to quantify selection strength for habitats differing in forage availability and thermal cover.

Results

Moose in Ontario favored deciduous and mixedwood forest, indicating selection for foraging habitat across both diel and temperature. Habitat selection patterns of moose in Minnesota were more dynamic and indicated time- and temperature-dependent trade-offs between use of foraging habitat and thermal cover.

Conclusions

We detected a scale-dependent functional response in habitat selection driven by the trade-off between selection for foraging habitat and thermal cover. Landscape composition and internal state interact to produce complex patterns of space use, and animals exposed to increasingly high temperatures may mitigate fitness losses from reduced foraging efficiency by increasing selection for foraging habitat in sub-prime foraging landscapes.

     

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.