Landscape-Scale Forest Habitat Relationships to Tassel-Eared Squirrel Populations: Implications for Ponderosa Pine Forest Restoration

摘要

Pinus ponderosa (ponderosa pine) forest ecosystem restoration is a growing emphasis in the southwestern United States to address over 120 years of forest structure change, decreased forest health, and increased potential for disease and wildfire. Restoration treatments replicating pre-settlement conditions may reduce tree density by 98%, are detrimental to canopy-dependent wildlife such as tassel-eared squirrel (Sciurus aberti), particularly at the patch scale, and are of concern when apph'ed at the landscape scale. We examined S. aberti population dynamics in north-central Arizona, U.S.A., from 1999 to 2002 at nine 280-ha sites oriented along a landscape gradient of varying proportions (4.6-99.2%) of unlogged, high-quality (HQ) habitats within a matrix of intensively thinned low-quality habitat. Our objectives were to estimate S. aberti density, juvenile recruitment, and survival across this gradient; quantify patch- and landscape-scale habitat relationships to populations; evaluate possible habitat thresholds in squirrel population response; and develop forest management recommendations. In regression models, both patch-scale and landscape-scale parameters influenced squirrel populations. At the patch scale, number of interlocking canopy trees was added most frequently, whereas the proportion of HQ habitat was the landscape-scale variable added in five of seven models. Recruitment and survival at dense, HQ plots were inversely related to number of small, sapling-sized trees. Nonlinear thresholds in density and recruitment occurred when the proportion of HQ habitat at study sites was between 24 and 42%. Our study points to the importance of maintaining HQ habitat in mesoreserves on the landscape at or above this threshold range, as well as pursing a mix of forest management prescriptions in the matrix surrounding mesoreserves to achieve wildlife, forest restoration, and fire risk reduction objectives.