A rapid approach to modeling species–habitat relationships Original Research Article

A basic element in the success of managing species of conservation concern is knowledge of the species’ habitat occupancy. Often, predictive species–habitat models are developed from GIS data sources that were intended for purposes other than predicting species habitat occupancy and are of inappropriate scale. In addition, the techniques used to quantify predictor variables from such data sources are often time consuming and cannot be repeated efficiently to reflect changing conditions. We used digital orthophotos and a grid cell classification scheme to develop an efficient technique to quantify predictor variables to model Florida scrub-jay habitat occupancy. We combined our classification scheme with a priori hypothesis development using expert knowledge and a previously published habitat suitability index and used an objective model selection procedure to choose candidate models. We classified a large area (43,000 ha) in a fraction of the time that would be required to map vegetation classes and were able to test models at varying scales using a grid-cell windowing process. Interpretation of the selected models confirmed existing knowledge of factors important to Florida scrub-jay habitat occupancy. The potential uses and advantages of using a grid cell classification scheme in conjunction with expert knowledge and an objective model selection procedure are discussed.