Testing spatial PVA models of Australian treecreepers (Aves : Climacteridae) in fragmented forest

Population viability analysis (PVA) and other stochastic population models are frequently built and often used, but rarely tested. Stochastic metapopu lation models of the White-throated Treecreeper (Cormobates leucophaea) and the Red-browed Treecreeper (Climacteris erythrops) were developed in a sys tem of 39 remnant patches of eucalypt forest in southeastern New South Wale s, Australia. Parameters of the model were estimated using data obtained ou tside the fragmented system. Field surveys of the patches were conducted to test the predicted probabilities of patch occupancy, which is one of few i nstances where stochastic population models have been tested with empirical data. The initial models underestimated the occupancy of the patches, and the models were modified using the results of the tests in conjunction with further information on the biology of the species. A number of different m odifications were made to determine changes that produced results that matc hed the observations. The best of these modifications made reasonable predi ctions, although this is not equivalent to a test with independent data bec ause the data were known prior to the modifications. The best-fitting modif ied models were tested by comparing the observed number of extinction and c olonization events to the predicted number. The models underestimated the o bserved number of events, although imperfect survey methods may have contri buted to these differences. The tests of the stochastic models contributed to their development by highlighting the nature of the predictive error. Th e modified models predicted that the White-throated Treecreeper would be li kely to persist over the next 100 years in most of the 39 patches. In contr ast, the Red-browed Treecreeper was predicted to become extinct in most pat ches within about 50 years of fragmentation. This study illustrates how spa tial patterns can be used to test the predictions of population dynamic mod els, although we note that the tests are limited by survey error and spatia l correlation in occupancy data.