Predicting Dispersal and Conflict Risk for Wolf Recolonization in Colorado

Authors

Mark A. Ditmer, USDA Forest ServiceFollow
George Wittemyer, Colorado State UniversityFollow
Katherine A. Zeller, USFS Rocky Mountain Research Station
Stewart W. Breck, USDA/APHIS/WS National Wildlife Research CenterFollow
Robert J. Fletcher Jr., University of Florida
Kevin R. Crooks, Aldo Leopold Wilderness Research Institute, Missoula, Montana

Document Type

Article

Date of this Version

2023

Citation

Journal of Applied Ecology (2023) 60: 2,327–2,339

doi: 10.1111/1365-2664.14504

Managing editor: Rachakonda Sreekar

Comments

United States government work

and

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (CC BY-NC-ND 4.0)

Abstract

1. The colonization of suitable yet unoccupied habitat due to natural dispersal or human introduction can benefit recovery of threatened species. Predicting habitat suitability and conflict potential of colonization areas can facilitate conservation planning.

2. Planning for reintroduction of gray wolves (Canis lupus) to the United States state of Colorado is underway. Assessing which occupancy sites minimize the likelihood of human-wolf conflict during dispersal events and seasonal movements is critical to the success of this initiative.

3. We used a spatial absorbing Markov chain (SAMC) framework, which extends random walk theory and probabilistically accounts for both movement behavior and mortality risk, to compare the viability of potential occupancy sites (public lands > 500 km² to minimally meet wolf pack range area). The SAMC framework produced spatially explicit predictions of wolf dispersal, philopatry and conflict risk ahead of recolonization prior to reintroduction efforts. Our SAMC model included: (1) movement resistance based on terrain, roads and housing density; (2) mortality risk and potential conflict (absorption) based on livestock presence, social tolerance, land ownership and state boundaries; and (3) site fidelity based on habitat quality. Using this model, we compared 21 public land units by deriving predictions of: (A) relative survival time outside each site, (B) intensity of use and retention time within each site, and (C) the probability of use on adjacent public lands. We also predicted and mapped potential conflict hot spots associated with each site.

4. Among the units assessed, a complex of United States Forest Service Wilderness areas near Aspen, chiefly the Hunter-Fryingpan and Collegiate Peaks Wilderness areas, had the best overall rankings when comparing predictions of each metric. The area balances high-quality, well-connected habitat with relatively low livestock density and high social tolerance.

5. Synthesis and applications. Our findings highlight the utility of the SAMC framework for assessing colonization areas and the capacity to identify locations for effective proactive management, especially of conflict prone species. The flexibility of the SAMC framework enables predicting likely areas of philopatry and human-wildlife conflict using spatially explicit metrics which can improve the success of conservation translocations and management of species with changing geographic extents.