557 items found
Kullback–Leibler
Telemetry data
Kullback–Leibler
Telemetry data
Hierarchical model
Individual variation
Population-level
Predation
Telemetry
Wildland-urban interface
Hierarchical model
Individual variation
Population-level
Predation
Telemetry
Wildland-urban interface
Background
While many species have suffered from the detrimental impacts of increasing human population growth, some species, such as cougars (Puma concolor), have been observed using human-modified landscapes. However, human-modified habitat can be a source of both increased risk and increased food availability, particularly for large carnivores. Assessing preferential use of the landscape is important for managing wildlife and can be particularly useful in transitional habitats, such as at the wildland-urban interface. Preferential use is often evaluated using resource selection functions (RSFs), which are focused on quantifying habitat preference using either a temporally static framework or researcher-defined temporal delineations. Many applications of RSFs do not incorporate time-varying landscape availability or temporally-varying behavior, which may mask conflict and avoidance behavior.
Methods
Contemporary approaches to incorporate landscape availability into the assessment of habitat selection include spatio-temporal point process models, step selection functions, and continuous-time Markov chain (CTMC) models; in contrast with the other methods, the CTMC model allows for explicit inference on animal movement in continuous-time. We used a hierarchical version of the CTMC framework to model speed and directionality of fine-scale movement by a population of cougars inhabiting the Front Range of Colorado, U.S.A., an area exhibiting rapid population growth and increased recreational use, as a function of individual variation and time-varying responses to landscape covariates.
Results
We found evidence for individual- and daily temporal-variability in cougar response to landscape characteristics. Distance to nearest kill site emerged as the most important driver of movement at a population-level. We also detected seasonal differences in average response to elevation, heat loading, and distance to roads. Motility was also a function of amount of development, with cougars moving faster in developed areas than in undeveloped areas.
Conclusions
The time-varying framework allowed us to detect temporal variability that would be masked in a generalized linear model, and improved the within-sample predictive ability of the model. The high degree of individual variation suggests that, if agencies want to minimize human-wildlife conflict management options should be varied and flexible. However, due to the effect of recursive behavior on cougar movement, likely related to the location and timing of potential kill-sites, kill-site identification tools may be useful for identifying areas of potential conflict.
[show more]Canada lynx
Ski resorts
Snowmobiles
Space use
Winter recreation
Canada lynx
Ski resorts
Snowmobiles
Space use
Winter recreation
Behavior
Colorado
Intermountain West
Mule deer
Natural-gas development
<em>Odocoileus hemionus</em>
Resource selection
Spring migration
Behavior
Colorado
Intermountain West
Mule deer
Natural-gas development
<em>Odocoileus hemionus</em>
Resource selection
Spring migration
Colorado
Mule deer
Natural gas development
<em>Odocoileus hemionus</em>
Population dynamics
Predation
Survival
Colorado
Mule deer
Natural gas development
<em>Odocoileus hemionus</em>
Population dynamics
Predation
Survival
Metals -- Toxicology -- Colorado
Metals -- Toxicology -- Colorado
AIS
Boating
Inspection
AIS
Boating
Inspection
ANS
Boating
Inspections
Zebra mussels
Quagga mussels
ANS
Boating
Inspections
Zebra mussels
Quagga mussels
ANS
Fishing
ANS
Fishing
ANS
Fishing
ANS
Fishing