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Ford, A. T.

Publications and source records attributed to Ford, A. T..

3 recordsLinked to original sources

Clarifying space use concepts in ecology: range vs. occurrence distributions

Quantifying animal movements is necessary for answering a wide array of research questions in ecology and conservation biology. Consequently, ecologists have made considerable efforts to identify the best way to estimate an animals home range, and many methods of estimating home ranges have arisen over the past half century. Most of these methods fall into two distinct categories of estimators that have only recently been described in statistical detail: those that measure range distributions (methods such as Kernel Density Estimation that quantify the long-run behavior of a movement process that features restricted space use) and those that measure occurrence distributions (methods such as Brownian Bridge Movement Models and the Correlated Random Walk Library that quantify uncertainty in an animal movement path during a specific period of observation). In this paper, we use theory, simulations, and empirical analysis to demonstrate the importance of applying these two classes of space use estimators appropriately and distinctly. Conflating range and occurrence distributions can have serious consequences for ecological inference and conservation practice. For example, in most situations, home-range estimates quantified using occurrence estimators are too small, and this problem is exacerbated by ongoing improvements in tracking technology that enable more frequent and more accurate data on animal movements. We encourage researchers to use range estimators to estimate the area of home ranges and occurrence estimators to answer other questions in movement ecology, such as when and where an animal crosses a linear feature, visits a location of interest, or interacts with other animals. Open Research StatementTracking data on Aepyceros melampus, Beatragus hunteri, Bycanistes bucinator, Cerdocyon thous, Eulemur rufifrons, Glyptemys insculpta, Gyps coprotheres, Madoqua guentheri, Ovis canadensis, Propithecus verreauxi, Sus scrofa, and Ursus arctos are publicly archived in the Dryad repository (Noonan et al. 2018; https://doi.org/10.5061/dryad.v5051j2), as are data from Procapra gutturosa (Fleming et al. 2014a; https://doi.org/10.5061/dryad.45157). Data on Panthera onca were taken from (Morato et al. 2018). Additional data are publicly archived in the Movebank repository under the following identifiers: Canis latrans, 8159699; Canis lupus, 8159399; Chrysocyon brachyurus, 18156143; Felis silvestris, 40386102; Gyps africanus, 2919708; Lepus europaeus, 25727477; Martes pennanti, 2964494; Panthera leo, 220229; Papio cynocephalus, 222027; Syncerus caffer, 1764627; Tapirus terrestris, 443607536; Torgos tracheliotus, 2919708; and Ursus americanus, 8170674.

ecology↗

Macroecological variation in movement profiles: body size does not explain it all

Animals couple habitats by three types of movement: dispersal, migration, and foraging, which dynamically link populations, communities, and ecosystems. Spatial distances of movement tend to correlate with each other, reflecting shared allometric scaling with body size, but may diverge due to biomechanical, phylogenetic, and ecological constraints. While these constraints have been investigated within specific taxa, the macroecological and macroevolutionary constraints on movement distances, and causes of those constraints, are still unknown. Here, we synthesized distances of all three movement types across 300+ vertebrate species, and investigated how the relationships between movement types and body size were modified by movement medium, taxonomy, and trophic guild (carnivore, herbivore, etc.). We found that the strength of relationships between movement types and body size varied among environments, taxa, and trophic guilds. Movement profiles interacted with physiological, taxonomic, and ecological traits to depart from expected body mass scaling. Overall, we find that there are systematic patterns to movement distances, and that movement types with very distinct ecological consequences (foraging, migration) can be correlated and subject to similar constraints. This implies that the scales of population dynamics in ecological communities are not entirely determined by the environment and likely reflect general biomechanical, evolutionary and metabolic constraints.

ecology↗

Towns and Trails Drive Carnivore Connectivity using a Step Selection Approach

Global increases in human activity threaten connectivity of animal populations. Protection and restoration of animal movement corridors requires robust models to forecast the effects of human activity on connectivity. Recent advances in the field of animal movement ecology and step selection functions offer new approaches for estimating connectivity. We show how a combination of hidden Markov movement models and step selection functions can be used to simulate realistic movement paths with multiple behavioral states. Simulated paths can be used to generate utilization distributions and estimate changes in connectivity for multiple land use scenarios. We applied movement models to 20 years of grizzly bear (Ursus arctos) and gray wolf (Canis lupus) data collected in and around Banff National Park, Canada. These carnivores avoided areas near towns in all seasons, avoided areas of high trail density in most seasons, and campgrounds during summer and fall. We simulated movement paths for three landscape scenarios: reference conditions with no anthropogenic development, current conditions, and future conditions with expanded town footprints and trail networks. We counted the number of paths that crossed valley-wide, digital transects through mountain tourist towns of Banff and Canmore, Alberta. We divided current and future crossing rates by the reference crossing rates to estimate connectivity. Current connectivity rates ranged between 7 and 45% of reference values with an average of 21% for grizzly bears and 25% for wolves. Potential town expansion and increased development of trails further decreased connectivity an average of 6% in future scenarios. Anthropogenic developments reduced the amount of available high quality large carnivore habitat in the Bow Valley by an average of 14% under current conditions and 16% under future conditions. Our approach for estimating connectivity provides a robust and flexible method for combining movement models with step selection analyses to estimate connectivity for a variety of species.

ecology↗