Predicting avian patch occupancy in a fragmented landscape: do we know more than we think?
Abstract
A recent and controversial topic in landscape ecology is whether populations of species respond to habitat fragmentation in a general fashion. Empirical research has provided mixed support, resulting in controversy about the use of general rules in landscape management. Rather than simply assessing post hoc whether individual species follow such rules, a priori testing could shed light on their accuracy and utility for predicting species response to landscape change. We aim to create an a priori model that predicts the presence or absence of multiple species in habitat patches. Our goal is to balance general theory with relevant species life-history traits to obtain high prediction accuracy. To increase the utility of this work, we aim to use accessible methods that can be applied using readily available inexpensive resources. The classification tree patch-occupancy model we create for birds is based on habitat suitability, minimum area requirements, dispersal potential of each species and overall landscape connectivity. To test our model we apply it to the South East Queensland region, Australia, for 17 bird species with varying dispersal potential and habitat specialization. We test the accuracy of our predictions using presence-absence information for 55 vegetation patches. Overall we achieve Cohen's kappa of 0.33, or 'fair' agreement between the model predictions and test data sets, and generally a very high level of absence prediction accuracy. Habitat specialization appeared to influence the accuracy of the model for different species. We also compare the a priori model to the statistically derived model for each species. Although this 'optimal model' generally differed from our original predictive model, the process revealed ways in which it could be improved for future attempts. Synthesis and applications. Our study demonstrates that ecological generalizations alongside basic resources (a vegetation map and some species-specific information) can provide conservative accuracy for predicting species occupancy in remnant vegetation patches. We show that the process of testing and developing models based on general rules could provide basic tools for conservation managers to understand the impact of current or planned landscape change on wildlife populations.