Modelling the population dynamics of the Mt. Graham red squirrel: Can we predict its future in a changing environment with multiple threats?

• Published in: Biological conservation 2006-07, Vol.131 (1), p.121-131
• Main Authors: Rushton, S.P., Wood, D.J.A., Lurz, P.W.W., Koprowski, J.L.
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied ecology; Arizona; Biological and medical sciences; Conservation; Conservation, protection and management of environment and wildlife; Endangered species; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Introduced species; Methods and techniques (sampling, tagging, trapping, modelling...); Parks, reserves, wildlife conservation. Endangered species: population survey and restocking; Sciurus aberti; SEPM; Tamiasciurus hudsonicus grahamensis
• ISSN: 0006-3207; 1873-2917
• DOI: 10.1016/j.biocon.2006.02.010

The Mt. Graham red squirrel ( Tamiasciurus hudsonicus grahamensis; MGRS) is among the most critically endangered mammals in the United States and is isolated on the periphery of the species’ range, potentially increasing its conservation priority. To investigate potential threats to the population and provide a tool for land managers, we developed a spatially explicit population dynamics model. We tested model predictions using available range-wide data from the literature and field work specific to the MGRS. A general model input data set using mean life history values overpredicted MGRS abundance. However, we found significant correlation with known squirrel abundance using a general data set with curtailed fecundity and survival. A model with MGRS-specific data provided the best fit to observed population size. We investigated potential impacts of two major threats to the MGRS: competition from introduced Abert’s squirrels ( Sciurus aberti) and increased levels of predation. Predation and particularly competition could have significant effects on the future population of the MGRS. Careful attention must be used to model the viability of fringe populations as peripheral populations can have a different life history than populations found in the range core.