Dataset Information

Multi-scale habitat assessment of pronghorn migration routes.

ABSTRACT: We studied the habitat selection of pronghorn (Antilocapra americana) during seasonal migration; an important period in an animal's annual cycle associated with broad-scale movements. We further decompose our understanding of migration habitat itself as the product of both broad- and fine-scale behavioral decisions and take a multi-scale approach to assess pronghorn spring and fall migration across the transboundary Northern Sagebrush Steppe region. We used a hierarchical habitat selection framework to assess a suite of natural and anthropogenic features that have been shown to influence selection patterns of pronghorn at both broad (migratory neighborhood) and fine (migratory pathway) scales. We then combined single-scale predictions into a scale-integrated step selection function (ISSF) map to assess its effectiveness in predicting migration route habitat. During spring, pronghorn selected for native grasslands, areas of high forage productivity (NDVI), and avoided human activity (i.e., roads and oil and natural gas wells). During fall, pronghorn selected for native grasslands, larger streams and rivers, and avoided roads. We detected avoidance of paved roads, unpaved roads, and wells at broad spatial scales, but no response to these features at fine scales. In other words, migratory pronghorn responded more strongly to anthropogenic features when selecting a broad neighborhood through which to migrate than when selecting individual steps along their migratory pathway. Our results demonstrate that scales of migratory route selection are hierarchically nested within each other from broader (second-order) to finer scales (third-order). In addition, we found other variables during particular migratory periods (i.e., native grasslands in spring) were selected for across scales indicating their importance for pronghorn. The mapping of ungulate migration habitat is a topic of high conservation relevance. In some applications, corridors are mapped according to telemetry location data from a sample of animals, with the assumption that the sample adequately represents habitat for the entire population. Our use of multi-scale modelling to predict resource selection during migration shows promise and may offer another relevant alternative for use in future conservation planning and land management decisions where telemetry-based sampling is unavailable or incomplete.

SUBMITTER: Jakes AF

PROVIDER: S-EPMC7717543 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Multi-scale habitat assessment of pronghorn migration routes.

Jakes Andrew F AF DeCesare Nicholas J NJ Jones Paul F PF Gates C Cormack CC Story Scott J SJ Olimb Sarah K SK Kunkel Kyran E KE Hebblewhite Mark M

PloS one 20201204 12

We studied the habitat selection of pronghorn (Antilocapra americana) during seasonal migration; an important period in an animal's annual cycle associated with broad-scale movements. We further decompose our understanding of migration habitat itself as the product of both broad- and fine-scale behavioral decisions and take a multi-scale approach to assess pronghorn spring and fall migration across the transboundary Northern Sagebrush Steppe region. We used a hierarchical habitat selection frame ...[more]

PMID: 33275623

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Project description:Increased understanding of the influence of habitat (e.g., composition, patch size) and intrinsic (e.g., age, birth mass) factors on survival of neonatal pronghorn (Antilocapra americana) is a prerequisite to successful management programs, particularly as they relate to population dynamics and the role of population models in adaptive species management. Nevertheless, few studies have presented empirical data quantifying the influence of habitat variables on survival of neonatal pronghorn. During 2002-2005, we captured and radiocollared 116 neonates across two sites in western South Dakota. We documented 31 deaths during our study, of which coyote (Canis latrans) predation (n = 15) was the leading cause of mortality. We used known fate analysis in Program MARK to investigate the influence of intrinsic and habitat variables on neonatal survival. We generated a priori models that we grouped into habitat and intrinsic effects. The highest-ranking model indicated that neonate mortality was best explained by site, percent grassland, and open water habitat; 90-day survival (0.80; 90% CI = 0.71-0.88) declined 23% when grassland and water increased from 80.1 to 92.3% and 0.36 to 0.40%, respectively, across 50% natal home ranges. Further, our results indicated that grassland patch size and shrub density were important predictors of neonate survival; neonate survival declined 17% when shrub density declined from 5.0 to 2.5 patches per 100 ha. Excluding the site covariates, intrinsic factors (i.e., sex, age, birth mass, year, parturition date) were not important predictors of survival of neonatal pronghorns. Further, neonatal survival may depend on available land cover and interspersion of habitats. We have demonstrated that maintaining minimum and maximum thresholds for habitat factors (e.g., percentages of grassland and open water patches, density of shrub patches) throughout natal home ranges will in turn, ensure relatively high (>0.50) neonatal survival rates, especially as they relate to coyote predation. Thus, landscape level variables (particularly percentages of open water, grassland habitats, and shrub density) should be incorporated into the development or implementation of pronghorn management plans across sagebrush steppe communities of the western Dakotas, and potentially elsewhere within the geographic range of pronghorn.

Project description:Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m - 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the potential to become a standard tool for supporting landscape-scale decision-making as relevant data and open source, user-friendly, and peer-reviewed software become widely available.

Project description:Distribution models are increasingly being used to understand how landscape and climatic changes are affecting the processes driving spatial and temporal distributions of plants and animals. However, many modeling efforts ignore the dynamic processes that drive distributional patterns at different scales, which may result in misleading inference about the factors influencing species distributions. Current occupancy models allow estimation of occupancy at different scales and, separately, estimation of immigration and emigration. However, joint estimation of local extinction, colonization, and occupancy within a multi-scale model is currently unpublished. We extended multi-scale models to account for the dynamic processes governing species distributions, while concurrently modeling local-scale availability. We fit the model to data for lark buntings and chestnut-collared longspurs in the Great Plains, USA, collected under the Integrated Monitoring in Bird Conservation Regions program. We investigate how the amount of grassland and shrubland and annual vegetation conditions affect bird occupancy dynamics and local vegetation structure affects fine-scale occupancy. Buntings were prevalent and longspurs rare in our study area, but both species were locally prevalent when present. Buntings colonized sites with preferred habitat configurations, longspurs colonized a wider range of landscape conditions, and site persistence of both was higher at sites with greener vegetation. Turnover rates were high for both species, quantifying the nomadic behavior of the species. Our model allows researchers to jointly investigate temporal dynamics of species distributions and hierarchical habitat use. Our results indicate that grassland birds respond to different covariates at landscape and local scales suggesting different conservation goals at each scale. High turnover rates of these species highlight the need to account for the dynamics of nomadic species, and our model can help inform how to coordinate management efforts to provide appropriate habitat configurations at the landscape scale and provide habitat targets for local managers.

Project description:The evaluation of conservative treatments' efficacy on natural building stones are usually based on standard recommendation routines finalized to evaluate compatibility and harmfulness of products in turn of the substrate. However, the visualization and the quantification of products inside pore structure of natural stones is not immediate through standard tests, so that imaging and advanced techniques are recently proposed in material conservation field to improve knowledge on penetration depth, modification of pore-air interface at different scale and monitor dynamic absorption processes. Moreover, natural stones are usually characterized by complex structure, which changes due to conservative treatments have to be inspected at different scale (from micrometer to nanometer). In this prospective, the assessment of laboratory practices able to integrate multiscale methods and give back a complete overview on interaction between new conservative formulates and natural stones is of high interest. In this paper, we propose a methodological routine for efficacy assessment of conservative products, incorporating classical and innovative nondestructive techniques. Validation of the workflow has been verified on a high porous natural stone treated with new hybrid formulates appropriately customized for conservation issues. •The study intends to add new insights on problems related to consolidation of high porous carbonate stone, application methods in consolidating natural stones and methods to evaluate efficacy of new products.•A multi-scale laboratory investigation procedure is proposed by integrating standard and innovative nondestructive methods. Merits and limits of each applied method are discussed during validation.•The possibility to incorporate standard routines and/or substitute destructive testing with non-destructive ones seem to be a valid alternative to evaluate efficiency and monitor behavior of stones treated with consolidating products.

Project description:BackgroundHabitat selection and its adaptive outcomes are crucial features for animal life-history strategies. Nevertheless, congruence between habitat preferences and breeding success has been rarely demonstrated, which may result from the single-scale evaluation of animal choices. As habitat selection is a complex multi-scale process in many groups of animal species, investigating adaptiveness of habitat selection in a multi-scale framework is crucial. In this study, we explore whether habitat preferences acting at different spatial scales enhance the fitness of bird species, and check the appropriateness of single vs. multi-scale models. We expected that variables found to be more important for habitat selection at individual scale(s), would coherently play a major role in affecting nest survival at the same scale(s).MethodsWe considered habitat preferences of two Rallidae species, little crake (Zapornia parva) and water rail (Rallus aquaticus), at three spatial scales (landscape, territory, and nest-site) and related them to nest survival. Single-scale versus multi-scale models (GLS and glmmPQL) were compared to check which model better described adaptiveness of habitat preferences. Consistency between the effect of variables on habitat selection and on nest survival was checked to investigate their adaptive value.ResultsIn both species, multi-scale models for nest survival were more supported than single-scale ones. In little crake, the multi-scale model indicated vegetation density and water depth at the territory scale, as well as vegetation height at nest-site scale, as the most important variables. The first two variables were among the most important for nest survival and habitat selection, and the coherent effects suggested the adaptive value of habitat preferences. In water rail, the multi-scale model of nest survival showed vegetation density at territory scale and extent of emergent vegetation within landscape scale as the most important ones, although we found a consistent effect with the habitat selection model (and hence evidence for adaptiveness) only for the former.DiscussionOur work suggests caution when interpreting adaptiveness of habitat preferences at a single spatial scale because such an approach may under- or over-estimate the importance of habitat factors. As an example, we found evidence only for a weak effect of water depth at territory scale on little crake nest survival; however, according to the multi-scale analysis, such effect turned out to be important and appeared highly adaptive. Therefore, multi-scale approaches to the study of adaptive explanations for habitat selection mechanisms should be promoted.

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Multi-scale habitat assessment of pronghorn migration routes.

Publications

Multi-scale habitat assessment of pronghorn migration routes.

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