Mountain lion habitat selection in Arizona

Nicholson, Kerry L.; Krausman, Paul R.; Smith, Thorry W.; Ballard, Warren B.; McKinney, T. D.

doi:10.1894/tal-62.1

Cited by 11 publications

(14 citation statements)

References 24 publications

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“…Recent research on mountain lion habitat selection across several sky island mountain ranges in Arizona found consistent selection for woody vegetation (Nicholson et al, 2014). All of the ecological systems that we evaluated in this study typically include woody vegetation, which might account for the lack of significant difference between use and availability in ecological systems.…”

mentioning

confidence: 74%

Assessing habitat relationships of mountain lions and their prey in the Davis Mountains, Texas

Dennison

Harveson

2016

The Southwestern Naturalist

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mentioning

confidence: 74%

Assessing habitat relationships of mountain lions and their prey in the Davis Mountains, Texas

Dennison

Harveson

2016

The Southwestern Naturalist

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“…To account for non‐harvest mortality causes, such as vehicle collisions, intra‐specific strife, and authorized removals by livestock operators, and to obtain an auxiliary estimate of harvest mortality rates, we obtained data on the fate of mountain lions that were monitored with GPS collars as part of several independent studies in Arizona conducted during 2003–2017 (Fig. ; McKinney et al ; Nicholson et al ; AZGFD, unpublished data). When a collar emitted a mortality signal or GPS data indicated a mortality, researchers investigated the cause of death for the animal.…”

Section: Methodsmentioning

confidence: 99%

Estimating Mountain Lion Abundance in Arizona Using Statistical Population Reconstruction

et al. 2019

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Directly monitoring abundance of cryptic species, such as mountain lions (Puma concolor), over large areas is a challenge for wildlife managers because traditional population estimation techniques may be impractical and expensive. We generated annual estimates of mountain lion abundance in Arizona, USA, for 2004–2018 by employing statistical population reconstruction methods, which use available age‐at‐harvest data and auxiliary information such as estimated survival rates, harvest probabilities, and hunter effort. Using PopRecon 2.0 software, we estimated that the statewide abundance of all mountain lions including kittens ranged from 1,848 (95% CI = 650–3,046) to 4,661 (95% CI = 393–9,030) during 2004–2018. Abundance for subadults and adults was more stable and precisely estimated, ranging from 1,166 (95% CI = 622–1,709) to 1,715 (95% CI = 872–2,558). Our results suggest a stable statewide mountain lion population. This approach provides a practical and cost‐effective option for monitoring Arizona's mountain lion population, and will improve the ability of managers to monitor the population annually to respond to changes in abundance and to evaluate factors that influence mountain lion abundance. © 2019 The Authors. Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.

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“…Distance to road was calculated using major roads data (i.e., a major highway primarily for through traffic usually on a continuous route and streets whose primary purpose is to serve the internal traffic movement within an area) obtained from Colorado Department of Transportation. Due to increased human activity around structures and roads, we expected cougars to move faster when closer to roofed structure and distance to nearest road [ 17 , 33 , 60 ]. However, females may respond less to structures and roads than males, given that there may be additional factors, such as food limitation and offspring, which drive them to tolerate human-modified landscapes [ 37 , 61 ].…”

Section: Methodsmentioning

confidence: 99%

Time-varying predatory behavior is primary predictor of fine-scale movement of wildland-urban cougars

et al. 2018

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BackgroundWhile 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.MethodsContemporary 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.ResultsWe 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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (10.1186/s40462-018-0140-6) contains supplementary material, which is available to authorized users.

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Mountain lion habitat selection in Arizona

Cited by 11 publications

References 24 publications

Assessing habitat relationships of mountain lions and their prey in the Davis Mountains, Texas

Assessing habitat relationships of mountain lions and their prey in the Davis Mountains, Texas

Estimating Mountain Lion Abundance in Arizona Using Statistical Population Reconstruction

Time-varying predatory behavior is primary predictor of fine-scale movement of wildland-urban cougars

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