Does veg composition improve modelling?

Temperate woodlands in Australia have been disproportionately cleared following European settlement. Biodiversity decline in such systems may be reversed by restoring native vegetation on agricultural land. However, rebuilding functioning habitat will require an understanding of what determines the distribution of species in existing habitat.

Makysm Polyakov and colleagues used logistic regression of bird occurrence data from 240 sites across northern Victoria, to determine the probability of occurrence of 29 woodland-dependent bird species. They modelled occurrence as a function of both the extent (amount) and composition of native vegetation surrounding sites. The goal was to determine whether the predictive performance of models is improved by accounting for both extent and composition of native vegetation compared with models that characterise native vegetation by extent alone.

For nearly all bird species, accounting for vegetation composition in addition to extent (and weighting habitat variables by distance) improved the explanatory power of models, explaining on average 5.4 % (range 0–27.6 %) of the residual uncertainty in models that accounted for extent alone. Models that incorporate variation in vegetation composition can not only provide more accurate predictions of species occurrence, but also guide more appropriate restoration.

The research highlights the need for restoration activities to incorporate sites with fertile soils that support productive vegetation types. These models of woodland birds will be used to inform a spatially-explicit optimisation model for restoring native vegetation cover on agricultural land in this region. The goal of this work is to achieve biodiversity gains while minimizing losses to agricultural production.

Reference

Polyakov M, AD Rowles, JQ Radford, AF Bennett, G Park, A Roberts & David Pannell (2013). Using habitat extent and composition to predict the occurrence of woodland birds in fragmented landscapes. Landscape Ecology 28:329-341. http://link.springer.com/article/10.1007%2Fs10980-012-9831-3#

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