Incorporating productivity as a measure of fitness into models of breeding area quality of Arctic peregrine falcons

Using empirical location data from individuals to model habitat quality and species distributions is valuable towards understanding habitat use of wildlife, especially for conservation and management planning. Incorporating measures of reproductive success or survival into these models helps address the role of vital rates (a surrogate of fitness) in affecting a species’ distribution. We used 24-year datasets of Arctic peregrine falcon (Falco peregrinus tundrius) nest-site locations and productivity from the Colville River Special Area, Alaska, USA to model suitability of breeding habitat and the relative quality of used and potential nest sites. We used zero-inflated negative binomial regression models and covariates describing nest-site productivity, area of surrounding prey habitat, geology, topography, and land-cover type to model and predict intensity of Arctic peregrine falcon nest-site use along the Colville River, and developed a predictive map of intensity of nest-site use. Regions of higher predicted intensity of use were characterized by steeper slopes, greater area of prey habitat, and higher average productivity, which are likely attributed to minimizing predation risk, gaining advantages for hunting, having sufficient prey resources, site quality, and overall fitness. Including productivity in intensity of nest-site use models improved the models, supporting our supposition that adding a fitness parameter enhanced the predictive capability of the species distribution model. Areas predicted to have higher intensity of use by our model can be used to focus efforts of continued protection of areas with frequently occupied and productive nest sites, and conversely, identify areas where protection of nest sites is likely to have few conservation benefits.