Nest selection by snow petrels Pagodroma nivea in East Antarctica Validating predictive habitat selection models at the continental scale

• Published in: Ecological Modelling
• Main Authors: Olivier, F, Wotherspoon, SJ
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier Science BV 2008
• Subjects: Biological Sciences; Zoology; Animal Behaviour; Antarctic; East Antarctica; Wilkes Land; Nivea; Antarc*; Antarctica; Snow Petrel; Snow Petrels
• Online Access: http://www.sciencedirect.com; https://doi.org/10.1016/j.ecolmodel.2007.08.006; http://ecite.utas.edu.au/54219

Little is known on the factors controlling distribution and abundance of snow petrels inAntarctica. Studying habitat selection through modeling may provide useful information onthe relationships between this species and its environment, especially relevant in a climatechange context, where habitat availabilitymay change.Validating the predictive capability ofhabitat selection models with independent data is a vital step in assessing the performanceof such models and their potential for predicting species distribution in poorly documentedareas.Fromthe results of ground surveys conducted in the Casey region (20022003,Wilkes Land,East Antarctica), habitat selection models based on a dataset of 4000 nests were created topredict the nesting distribution of snowpetrels as a function of topography and substrate. Inthis study, the Casey modelswere tested at Mawson, 3800km away from Casey. The locationand characteristics of approximately 7700 snow petrel nests were collected during groundsurveys (Summer 20042005). Using GIS, predictive maps of nest distribution were producedfor the Mawson region with the models derived from the Casey datasets and predictionswere compared to the observed data. Models performance was assessed using classificationmatrixes and Receiver operating characteristic (ROC) curves. Overall correct classificationrates for the Casey models varied from 57% to 90%. However, two geomorphologically differentsub-regions (coastal islands and inland mountains) were clearly distinguished in termsof habitat selection by Casey model predictions but also by the specific variations in coefficientsof terms in new models, derived from the Mawson data sets. Observed variations inthe snow petrel aggregations were found to be related to local habitat availability.We discuss the applicability of various types of models (GLM, CT) and investigate the effectof scale on the prediction of snow petrel habitats. While the Caseymodels created with datacollected at the nest scale did not perform well at Mawson due to regional variations in nestmicro-characteristics, the predictive performance of models created with data compiled ata coarser scale (habitat units) was satisfactory. Substrate type was the most robust predictorof nest presence between Casey and Mawson. This study demonstrate that it is possibleto predict at the large scale the presence of snow petrel nests based on simple predictorssuch as topography and substrate, which can be obtained from aerial photography. Suchmethodologies have valuable applications in the management and conservation of this toppredator and associated resources and may be applied to other Antarctic, Sub-Antarctic andlower latitudes species and in a variety of habitats.