Robust predictive models of the distribution of forest biota are important tools for the management of forest biodiversity. To build robust models, it is essential to understand the environmental processes which control species distribution and hence choose appropriate predictor variables. Requirements for modelling the environmental niche of plant species include: environmentally stratified survey data of the vegetation and associated environmental measurements, an understanding of ecological theory, robust statistical models and geographical representation of the models. These requirements can be satisfied in different ways, many of which are discussed. The choice of modelling technique and curve fitting function should be related to ecological theory. Prediction becomes increasingly robust and less location-specific as the predictor variables become more process-oriented and relevant to biological processes. However, the need to use predictors for which estimates are available for unsampled regions may limit the choice to less direct variables. In this context we examine the performance of two modelling techniques: Generalised Linear Modelling (GLM) and Generalised Additive Modelling (GAM). Trees are ideal to study, because their size and immobility make for ease of collecting data and they provide important habitat for fauna and understorey herbs and as such are useful for predicting the distribution of some other biota. The data set includes 8377 sites in south-eastern Australia, with presence/absence data for trees and seven environmental predictors. A detailed comparison is described for Eucalyptus cypellocarpa . The influence of ‘naughty noughts’, or zero values beyond the range of a species, can distor the response function, giving positive predictions where the species is known to be absent. The model is improved by restricting the data to a suitable range. GAM has advantages over GLM due to the flexible nature of the non-parametric smoothing function. Different response curves can produce divergent predictions of species occurrence, particularly at the limits of species distribution. Conservation evaluation often requires making predictions in unsampled areas, and so the assumption of particular shapes of response curve could lead to significant errors in the estimation of the conservation value of these areas.
Forest Ecology and Management – Elsevier
Published: Sep 1, 1996
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera