Usefulness of coarse grain data on forest management to improve bird abundance models

Abstract

We tested the use of coarse grain data on forest management systems to improve habitat suitability models in predicting distribution and abundance of five bird species, nesting in broadleaf forests in Lombardy (Italy). They were the long‐tailed tit Aegithalos caudatus, marsh tit Poecile palustris, blue tit Cyanistes caeruleus, wood nuthatch Sitta europaea and short‐toed tree‐creeper Certhia brachydactyla. Bird data were collected from 4552 point counts from 1992 to 2002. To model the habitat suitability for each species, we used generalized linear models with negative binomial distribution and log link function. Environmental predictors were land‐use fractional covers, forest isolation, elevation, slope, aspect, and coarse grain data on forest management systems aggregated for administrative provinces. They were selected by a stepwise procedure based on the Bayesian Informative Criterion. Predictors on forest management system were useful to improve model fit for all cavity‐nesting species, which was also shown to be affected by forest isolation. The long‐tailed tit, which is not an obligate cavity nester, did not exhibit any preference with respect either to forest management or isolation.