Habitat selection by Dall's sheep is influenced by multiple factors including direct and indirect climate effects.

Arctic and boreal environments are changing rapidly, which could decouple behavioral and demographic traits of animals from the resource pulses that have shaped their evolution. Dall's sheep (Ovis dalli dalli) in northwestern regions of the USA and Canada, survive long, severe winters and reproduce during summers with short growing seasons. We sought to understand the vulnerability of Dall's sheep to a changing climate in Lake Clark National Park and Preserve, Alaska, USA. We developed ecological hypotheses about nutritional needs, security from predators, energetic costs of movement, and thermal shelter to describe habitat selection during winter, spring, and summer and evaluated habitat and climate variables that reflected these hypotheses. We used the synoptic model of animal space use to estimate parameters of habitat selection by individual females and calculated likelihoods for ecological hypotheses within seasonal models. Our results showed that seasonal habitat selection was influenced by multiple ecological requirements simultaneously. Across all seasons, sheep selected steep rugged areas near escape terrain for security from predators. During winter and spring, sheep selected habitats with increased forage and security, moderated thermal conditions, and lowered energetic costs of movement. During summer, nutritional needs and security influenced habitat selection. Climate directly influenced habitat selection during the spring lambing period when sheep selected areas with lower snow depths, less snow cover, and higher air temperatures. Indirectly, climate is linked to the expansion of shrub/scrub vegetation, which was significantly avoided in all seasons. Dall's sheep balance resource selection to meet multiple needs across seasons and such behaviors are finely tuned to patterns of phenology and climate. Direct and indirect effects of a changing climate may reduce their ability to balance their needs and lead to continued population declines. However, several management approaches could promote resiliency of alpine habitats that support Dall's sheep populations.

Modeling Caribou Movements: Seasonal Ranges and Migration Routes of the Central Arctic Herd.

Migration is an important component of the life history of many animals, but persistence of large-scale terrestrial migrations is being challenged by environmental changes that fragment habitats and create obstacles to animal movements. In northern Alaska, the Central Arctic herd (CAH) of barren-ground caribou (Rangifer tarandus granti) is known to migrate over large distances, but the herd's seasonal distributions and migratory movements are not well documented. From 2003-2007, we used GPS radio-collars to determine seasonal ranges and migration routes of 54 female caribou from the CAH. We calculated Brownian bridges to model fall and spring migrations for each year and used the mean of these over all 4 years to identify areas that were used repeatedly. Annual estimates of sizes of seasonal ranges determined by 90% fixed kernel utilization distributions were similar between summer and winter (X̅ = 27,929 SE = 1,064 and X̅ = 26,585 SE = 4912 km2, respectively). Overlap between consecutive summer and winter ranges varied from 3.3-18.3%. Percent overlap between summer ranges used during consecutive years (X̅ = 62.4% SE = 3.7%) was higher than for winter ranges (X̅ = 42.8% SE = 5.9%). Caribou used multiple migration routes each year, but some areas were used by caribou during all years, suggesting that these areas should be managed to allow for continued utilization by caribou. Restoring migration routes after they have been disturbed or fragmented is challenging. However, prior knowledge of movements and threats may facilitate maintenance of migratory paths and seasonal ranges necessary for long-term persistence of migratory species.

A piecewise linear modeling approach for testing competing theories of habitat selection: an example with mule deer in northern winter ranges.

Habitat selection fundamentally drives the distribution of organisms across landscapes; density-dependent habitat selection (DDHS) is considered a central component of ecological theories explaining habitat use and population regulation. A preponderance of DDHS theories is based on ideal distributions, such that organisms select habitat according to either the ideal free, despotic, or pre-emptive distributions. Models that can be used to simultaneously test competing DDHS theories are desirable to help improve our understanding of habitat selection. We developed hierarchical, piecewise linear models that allow for simultaneous testing of DDHS theories and accommodate densities from multiple habitats and regional populations, environmental covariates, and random effects. We demonstrate the use of these models with data on mule deer (Odocoileus hemionus) abundance and net energy costs in different snow depths within winter ranges of five regional populations in western Idaho, USA. Regional population density explained 40% of the variation in population growth, and we found that deer were ideal free in winter ranges. Deer occupied habitats with lowest net energy costs at higher densities and at a higher rate than compared to habitats with intermediate and high energy costs. The proportion of a regional population in low energy cost habitat the previous year accounted for a significant amount of variation in population growth (17%), demonstrating the importance of winter habitat selection in regulating deer populations. These linear models are most appropriate for empirical data collected from centralized habitat patches within the local range of a species where individuals are either year-round residents or migratory (but have already arrived from migration).

Analyzing animal movements using Brownian bridges.

By studying animal movements, researchers can gain insight into many of the ecological characteristics and processes important for understanding population-level dynamics. We developed a Brownian bridge movement model (BBMM) for estimating the expected movement path of an animal, using discrete location data obtained at relatively short time intervals. The BBMM is based on the properties of a conditional random walk between successive pairs of locations, dependent on the time between locations, the distance between locations, and the Brownian motion variance that is related to the animal's mobility. We describe two critical developments that enable widespread use of the BBMM, including a derivation of the model when location data are measured with error and a maximum likelihood approach for estimating the Brownian motion variance. After the BBMM is fitted to location data, an estimate of the animal's probability of occurrence can be generated for an area during the time of observation. To illustrate potential applications, we provide three examples: estimating animal home ranges, estimating animal migration routes, and evaluating the influence of fine-scale resource selection on animal movement patterns.

Contribution of the Natura 2000 network to biodiversity conservation in Italy.

The Natura 2000 network is the most important conservation effort being implemented in Europe. Nevertheless, no comprehensive and systematic region-or nationwide evaluation of the effectiveness of the network has been conducted. We used habitat suitability models and extent of occurrence of 468 species of vertebrates to evaluate the contribution of the Natura 2000 network to biodiversity conservation in Italy. We also estimated the population size of 101 species inside the Natura 2000 network to assess its capacity to maintain or improve the population status of listed species. In general the Italian Natura 2000 did not seem to integrate existing protected areas well. The Natura 2000 network increased from 11% to 20% the area devoted to conservation in Italy and the coverage provided to areas with high biodiversity. Nevertheless, some areas with high numbers of species were devoid of conservation areas, and more than 50% of the highly irreplaceable areas were not considered in the system. Moreover, the Natura 2000 network cannot maintain 44-80% (depending on the taxa considered) of the species in a "favorable conservation status" under World Conservation Union Red List criteria. The Natura 2000 network is probably stronger than the results of our analyses suggest. The system is based on a site-specific expert-based strategy and is driven by direct and detailed knowledge of local diversity. Nevertheless, if Natura 2000 is taken to represent the final point of all the EU conservation policies, it will inevitably fail. Its role in conservation could be enhanced by integrating the Natura 2000 system into a more general strategy that considers natural processes and the ecological and evolutionary mechanisms underlying these processes.

Selecting the best home range model: an information-theoretic approach.

Choosing an appropriate home range model is important for describing space use by animals and understanding the ecological processes affecting animal movement. Traditional approaches for choosing among home range models have not resulted in general, consistent, and unambiguous criteria that can be applied to individual data sets. We present a new application of information-theoretic model selection that overcomes many of the limitations of traditional approaches, as follows. (1) It alleviates the need to know the true home range to assess home range models, thus allowing performance to be evaluated with data on individual animals. (2) The best model can be chosen from a set of candidate models with the proper balance between fit and complexity. (3) If candidate home range models are based on underlying ecological processes, researchers can use the selected model not only to describe the home range, but also to infer the importance of various ecological processes affecting animal movements within the home range.