Cookies

We use cookies to ensure that we give you the best experience on our website. You can change your cookie settings at any time. Otherwise, we'll assume you're OK to continue.

Durham University

Department of Biosciences

Profile

Publication details for Professor Stephen G Willis

Collingham, Y.C., Huntley, B., Altwegg, R., Barnard, P., Beveridge, O.S., Gregory, R.D., Mason, L.R., Oschadleus, H.D., Simmons, R.E., Willis, S.G. & Green, R.E. (2014). Prediction of mean adult survival rates of southern African birds from demographic and ecological covariates. Ibis 156(4): 741-754.

Author(s) from Durham

Abstract

Estimates of annual survival rates of birds are valuable in a wide range of studies of population ecology and conservation. These include modelling studies to assess the impacts of climatic change or anthropogenic mortality for many species for which no reliable direct estimates of survival are available. We evaluate the performance of regression models in predicting adult survival rates of birds from values of demographic and ecological covariates available from textbooks and databases. We estimated adult survival for 67 species using dead recoveries of birds ringed in southern Africa and fitted regression models using five covariates: mean clutch size, mean body mass, mean age at first breeding, diet and migratory tendency. Models including these explanatory variables performed well in predicting adult survival in this set of species, both when phylogenetic relatedness of the species was taken into account using phylogenetic generalized least squares (51% of variation in logit survival explained) and when it was not (48%). Two independent validation tests also indicated good predictive power, as indicated by high correlations of observed with expected values in a leave-one-out cross validation test performed using data from the 67 species (35% of variation in logit survival explained), and when annual survival rates from independent mark-recapture studies of 38 southern African species were predicted from covariates and the regression using dead recoveries (48%). Clutch size and body mass were the most influential covariates, both with and without the inclusion of phylogenetic effects, and a regression model including only these two variables performed well in both of the validation tests (39 and 48% of variation in logit survival explained). Our regression models, including the version with only clutch size and body mass, are likely to perform well in predicting adult survival rate for southern African species for which direct survival estimates are not available.