Estimating Mountain Lion Abundance in Arizona Using Statistical Population Reconstruction

Abstract

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.

Statistical Population Reconstruction of Moose (Alces alces) in Northeastern Minnesota using Integrated Population Models

“…This method simultaneously estimates multiple demographic parameters (e.g., annual abundance, recruitment, and survival) and their uncertainties throughout time, and can be used to provide separate estimates for different sexes and age classes. Such models have already been used to estimate abundance and trends of wildlife species, such as American marten (Martes americana), black bears (Ursus americanus), and mountain lions (Puma concolor) [6][7][8].…”

Statistical population reconstruction of moose (Alces alces) in northeastern Minnesota using integrated population models

“…This method simultaneously estimates multiple demographic parameters (e.g., annual abundance, recruitment, and survival) and their uncertainties throughout time, and can be used to provide separate estimates for different sexes and age classes. Such models have previously been used to estimate abundance and trends of wildlife species, such as American marten (Martes americana), black bears (Ursus americanus), and mountain lions (Puma concolor) [6][7][8].…”

Long‐Term Evaluation of Cougar Density and Application of Risk Analysis for Harvest Management

“…Cougar density is derived primarily using 3 techniques: population abundance divided by a generalized study area (Choate et al 2006, Lambert et al 2006, Robinson and DeSimone 2011), using global positioning systems (GPS) locations and demographic data from collared cougars to define specific sex and age class contributions within a defined study area (Cooley et al 2009, Rinehart et al 2014, this study), and spatially explicit capture‐recapture (SECR; Russell et al 2012, Robinson et al 2014, Proffitt et al 2015). Other estimates of abundance may be derived from population reconstruction of hunter‐harvest data (Howard et al 2020) or indexing density using a reciprocal of female home ranges (Stoner et al 2018); time‐to‐detection (Loonam et al 2021) and modified mark‐resight (Alldredge et al 2019, Murphy et al 2019) models represent viable alternatives that are becoming more common. Each approach can provide robust or beneficial estimates, but the inconsistency between methodologies and definitions impede direct comparison of results.…”