Ecological insights from three decades of animal movement tracking across a changing Arctic

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Using movement ecology to investigate meningeal worm risk in moose, Alces alces

Anthropogenic habitat change and moderating climatic conditions have enabled the northward geographic expansion of white-tailed deer, Odocoileus virginianus, and of the parasitic nematode (meningeal worm) it carries, Parelaphostrongylus tenuis. This expansion can have consequences in dead-end host species for other ungulates because meningeal worm reduces health, causes morbidity or direct mortality, and has been attributed to population declines. In northeastern Minnesota, which marks the southern extent of the bioclimatic range for moose (Alces alces), the moose population has declined more than 50% in the last decade, with studies detecting P. tenuis in 25–45% of necropsied animals. We assessed the factors that most commonly are associated with meningeal worm infection by linking moose movement ecology with known P. tenuis infection status from necropsy. We outfitted moose with GPS collars to assess their space use and cause-specific mortality. Upon death of the subject animal, we performed a necropsy to determine the cause of death and document meningeal worm infection. We then created statistical models to assess the relationship between meningeal worm infection and exposure to hypothesized factors of infection risk based on the space use of each moose by season. Predictors included land cover types, deer space use and density, environmental conditions, and demographics of individual moose (age and sex). Moose with autumn home ranges that included more upland shrub/conifer, and individuals with high proportions of wet environments, regardless of season, had increased infection risk. In contrast, the strongest relationships we found showed that high proportions of mixed and conifer forest within spring home ranges resulted in reduced risk of infection. The spring models showed the strongest relationships between exposure and infection, potentially due to moose foraging on ground vegetation during spring. By incorporating movement of moose into disease ecology, we were able to take a top-down approach to test hypothesized components of infection risk with actual spatial and temporal exposure of individual necropsied moose. The probability of infection for moose was not influenced by deer density, although deer densities did not vary greatly within the study area (2–4 deer/km2), highlighting the importance of also considering both moose space use and environmental conditions in understanding infection risk. We suggest management strategies that use a combination of deer and land management prescriptions designed to limit contact rates in susceptible populations.

Extinction vortex dynamics of top predators isolated by urbanization

Extinction risk is elevated in small, isolated populations due to demographic and genetic interactions. Therefore, it is critical to model these processes realistically in population viability analyses (PVA) to inform local management and contribute to a greater understanding of mechanisms within the extinction vortex. We conducted PVA's for two small mountain lion populations isolated by urbanization in southern California to predict population growth, extinction probability, and loss of genetic diversity with empirical data. Specifically, we (1) provide the first PVA for isolated mountain lions in the Santa Ana Mountains (SAM) that considers both demographic and genetic risk factors and (2) test the hypothesis that variation in abundance and mortality between the SAM and Santa Monica Mountains (SMM) result in differences in population growth, loss of heterozygosity, and extinction probability. Our models predicted 16-21% probability of local extinction in the SAM due purely to demographic processes over 50 yr with current low levels or no immigration. Our models also predicted that genetic diversity will further erode in the SAM such that concern regarding inbreeding depression is warranted unless gene flow is increased, and that if inbreeding depression occurs, rapid local extinction will be highly likely. Dynamics of the two populations were broadly similar, but they also exhibited differences driven by larger population size and higher mortality in the SAM. Density-independent scenarios predicted a rapidly increasing population in the SMM, whereas growth potential did not differ from a stable trend in the SAM. Demographic extinction probability and loss of heterozygosity were greater in the SMM for density-dependent scenarios without immigration. However, higher levels of immigration had stronger, positive influences on both demographic viability and retention of genetic diversity in the SMM driven by lower abundance and higher adult survival. Our results elucidate demographic and genetic threats to small populations within the extinction vortex, and how these vary relative to demographic structure. Importantly, simulating seemingly attainable increases in connectivity was sufficient to greatly reduce extinction probability. Our work highlights that conservation of large carnivores is achievable within urbanized landscapes, but requires land protection, connectivity, and strategies to promote coexistence with humans.

Navigating snowscapes: scale-dependent responses of mountain sheep to snowpack properties

Winters are limiting for many terrestrial animals due to energy deficits brought on by resource scarcity and the increased metabolic costs of thermoregulation and traveling through snow. A better understanding of how animals respond to snow conditions is needed to predict the impacts of climate change on wildlife. We compared the performance of remotely sensed and modeled snow products as predictors of winter movements at multiple spatial and temporal scales using a data set of 20,544 locations from 30 GPS-collared Dall sheep (Ovis dalli dalli) in Lake Clark National Park and Preserve, Alaska, USA from 2005 to 2008. We used daily 500-m MODIS normalized difference snow index (NDSI), and multi-resolution snow depth and density outputs from a snowpack evolution model (SnowModel), as covariates in step selection functions. We predicted that modeled snow depth would perform best across all scales of selection due to more informative spatiotemporal variation and relevance to animal movement. Our results indicated that adding any of the evaluated snow metrics substantially improved model performance and helped characterize winter Dall sheep movements. As expected, SnowModel-simulated snow depth outperformed NDSI at fine-to-moderate scales of selection (step scales < 112 h). At the finest scale, Dall sheep selected for snow depths below mean chest height (<54 cm) when in low-density snows (100 kg/m³ ), which may have facilitated access to ground forage and reduced energy expenditure while traveling. However, sheep selected for higher snow densities (>300 kg/m³ ) at snow depths above chest height, which likely further reduced energy expenditure by limiting hoof penetration in deeper snows. At moderate-to-coarse scales (112-896 h step scales), however, NDSI was the best-performing snow covariate. Thus, the use of publicly available, remotely sensed, snow cover products can substantially improve models of animal movement, particularly in cases where movement distances exceed the MODIS 500-m grid threshold. However, remote sensing products may require substantial data thinning due to cloud cover, potentially limiting its power in cases where complex models are necessary. Snowpack evolution models such as SnowModel offer users increased flexibility at the expense of added complexity, but can provide critical insights into fine-scale responses to rapidly changing snow properties.

Spatial processes decouple management from objectives in a heterogeneous landscape: predator control as a case study

Predator control is often implemented with the intent of disrupting top-down regulation in sensitive prey populations. However, ambiguity surrounding the efficacy of predator management, as well as the strength of top-down effects of predators in general, is often exacerbated by the spatially implicit analytical approaches used in assessing data with explicit spatial structure. Here, we highlight the importance of considering spatial context in the case of a predator control study in south-central Utah. We assessed the spatial match between aerial removal risk in coyotes (Canis latrans) and mule deer (Odocoileus hemionus) resource selection during parturition using a spatially explicit, multi-level Bayesian model. With our model, we were able to evaluate spatial congruence between management action (i.e., coyote removal) and objective (i.e., parturient deer site selection) at two distinct scales: the level of the management unit and the individual coyote removal. In the case of the former, our results indicated substantial spatial heterogeneity in expected congruence between removal risk and parturient deer site selection across large areas, and is a reflection of logistical constraints acting on the management strategy and differences in space use between the two species. At the level of the individual removal, we demonstrated that the potential management benefits of a removed coyote were highly variable across all individuals removed and in many cases, spatially distinct from parturient deer resource selection. Our methods and results provide a means of evaluating where we might anticipate an impact of predator control, while emphasizing the need to weight individual removals based on spatial proximity to management objectives in any assessment of large-scale predator control. Although we highlight the importance of spatial context in assessments of predator control strategy, we believe our methods are readily generalizable in any management or large-scale experimental framework where spatial context is likely an important driver of outcomes.

Interactions between demography, genetics, and landscape connectivity increase extinction probability for a small population of large carnivores in a major metropolitan area

The extinction vortex is a theoretical model describing the process by which extinction risk is elevated in small, isolated populations owing to interactions between environmental, demographic, and genetic factors. However, empirical demonstrations of these interactions have been elusive. We modelled the dynamics of a small mountain lion population isolated by anthropogenic barriers in greater Los Angeles, California, to evaluate the influence of demographic, genetic, and landscape factors on extinction probability. The population exhibited strong survival and reproduction, and the model predicted stable median population growth and a 15% probability of extinction over 50 years in the absence of inbreeding depression. However, our model also predicted the population will lose 40-57% of its heterozygosity in 50 years. When we reduced demographic parameters proportional to reductions documented in another wild population of mountain lions that experienced inbreeding depression, extinction probability rose to 99.7%. Simulating greater landscape connectivity by increasing immigration to greater than or equal to one migrant per generation appears sufficient to largely maintain genetic diversity and reduce extinction probability. We provide empirical support for the central tenet of the extinction vortex as interactions between genetics and demography greatly increased extinction probability relative to the risk from demographic and environmental stochasticity alone. Our modelling approach realistically integrates demographic and genetic data to provide a comprehensive assessment of factors threatening small populations.

A protected area influences genotype-specific survival and the structure of a Canis hybrid zone

It is widely recognized that protected areas can strongly influence ecological systems and that hybridization is an important conservation issue. However, previous studies have not explicitly considered the influence of protected areas on hybridization dynamics. Eastern wolves are a species of special concern and their distribution is largely restricted to a protected population in Algonquin Provincial Park (APP), Ontario, Canada, where they are the numerically dominant canid. We studied intrinsic and extrinsic factors influencing survival and cause-specific mortality of hybrid and parental canids in the three-species hybrid zone between eastern wolves, eastern coyotes, and gray wolves in and adjacent to APP. Mortality risk for eastern wolves in areas adjacent to APP was significantly higher than for other sympatric Canis types outside of APP, and for eastern wolves and other canids within APP. Outside of APP, the annual mortality rate of all canids by harvest (24%) was higher than for other causes of death (4-7%). Furthermore, eastern wolves (hazard ratio = 3.5) and nonresidents (transients and dispersing animals, hazard ratio = 2.7) were more likely to die from harvest relative to other Canis types and residents, respectively. Thus, eastern wolves dispersing from APP were especially vulnerable to harvest mortality. For residents, eastern wolf survival was more negatively influenced by increased road density than for other Canis types, further highlighting the sensitivity of eastern wolves to human disturbance. A cycle of dispersal from APP followed by high rates of mortality and hybridization appears to maintain eastern wolves at low density adjacent to APP, limiting the potential for expansion beyond the protected area. However, high survival and numerical dominance of eastern wolves within APP suggest that protected areas can allow rare hybridizing species to persist even if their demographic performance is compromised and barriers to hybridization are largely absent in the adjacent matrix.

Problem-solving approach to clinical education

A problem-solving method to provide appropriate clinical learning experiences was developed for physical therapy students enrolled in their first year of professional course work. Clinicians from selected facilities were asked to participate in a clinical rotation over a two-quarter period. Using a problem-solving format, each clinician was responsible for a two-hour presentation relating to a disease or disability. Each rotation was repeated weekly for seven different groups of 10 students. During the rotation, the clinician presented a patient with a particular disability or disease and worked with the students to identify patient problems, establish treatment goals, and discuss methods used to achieve the goals. The difficulties encountered with the clinical experiences and the positive aspects of the experiences are discussed.