Influences on koala habitat selection across four local government areas on the far north coast of NSW

Conserving habitats crucial for threatened koala (Phascolarctos cinereus) populations requires rating habitat quality from a fine spatial scale to patches, landscapes and then regions. The koala has a specialized diet focused on the leaves of a suite of Eucalyptus species. We asked: what are the key regional influences on habitat selection by koalas in the far north coast of New South Wales? We addressed this question by investigating the multi-scale factors, and within-scale and cross-scale interactions, that influence koala habitat selection and distribution across four local government areas on the far north coast of New South Wales. We assembled and analysed a large data set of tree selection, identified by the presence of scats, in a wide range of randomly selected 5 × 5 km grids across the region. This resulted in more than 9000 trees surveyed for evidence of koala use from 302 field sites, together with associated biophysical site features. The dominant factor influencing habitat use and koala occurrence was the distribution of five Eucalyptus species. Koalas were more likely to use medium-sized trees of these species where they occurred on soils with high levels of Colwell phosphorous. We also identified new interactions among the distribution of preferred tree species and soil phosphorous, and their distribution with the amount of suitable habitat in the surrounding landscape. Our study confirmed that non-preferred species of eucalypts and non-eucalypts are extensively used by koalas and form important components of koala habitat. This finding lends support to restoring a mosaic of koala-preferred tree species and other species recognized for their value as shelter. Our study has provided the ecological foundation for developing a novel regional-scale approach to the conservation of koalas, with adaptability to other wildlife species.     

Knowledge-based models for predicting species occurrence in arable conditions

This paper explores the potential of rule-based habitat models to predict the occurrence of some common species in arable conditions. Models were developed for 10 arable plant species, 7 Hemiptera species, 8 carabid species and for 5 bird species whose ecology was sufficiently known. Rule sets linking species occurrence to environmental variables were produced using available literature and expert knowledge about ecological requirements of the selected species. Environmental variables described the nature and condition of habitats at various scales, ranging from vegetation quadrat to the landscape in a 1 km radius of species sampling sites. The performance of the 34 models developed was assessed in two areas of England. Results show the rule-based habitat models developed for arable plants and birds were not very successful with Cohen's k values often <0.4 for plants and very close to 0 for all bird species. Conversely, rule-based models performed surprisingly well for carabids and Hemiptera with k values on average >0.4. This suggests that ecological knowledge on these invertebrate species is more complete than we expected. The effect of species prevalence on model performance and the potential application of knowledge-based habitat models in the context of biodiversity assessment are discussed.     

Evaluation of comparative protein modeling by MODELLER

We evaluate 3D models of human nucleoside diphosphate kinase, mouse cellular retinoic acid binding protein I, and human eosinophil neurotoxin that were calculated by MODELLER , a program for comparative protein modeling by satisfaction of spatial restraints. The models have good stereochemistry and are at least as similar to the crystallographic structures as the closest template structures. The largest errors occur in the regions that were not aligned correctly or where the template structures are not similar to the correct structure. These regions correspond predominantly to exposed loops, insertions of any length, and non-conserved side chains. When a template structure with more than 40% sequence identity to the target protein is available, the model is likely to have about 90% of the mainchain atoms modeled with an rms deviation from the X-ray structure of ≈ 1 Å, in large part because the templates are likely to be that similar to the X-ray structure of the target. This rms deviation is comparable to the overall differences between refined NMR and X-ray crystallography structures of the same protein. © 1995 Wiley-Liss, Inc.