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Development and evaluation of predictive habitat models to assist the conservation planning of a threatened lucanid beetle, Hoplogonus simsoni, in north-east Tasmania |
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| Authors: | Jeff M Meggs Sarah A Munks Ross Corkrey |
| Institution: | a Forest Practices Board, 30 Patrick Street, Hobart, Tasmania, 7000 Australia b Department of Zoology, University of Tasmania, Sandy Bay, Tasmania, 7005 Australia c Lighthouse Research Station, George Street, Cromarty Ross-shire, IV11 8VJ UK |
| Abstract: | The use of predictive habitat distribution models by land managers in the conservation management of threatened species is increasing. Few models, however, are subsequently field-checked and evaluated. This study evaluates the statistical strength and usefulness for conservation purposes of three predictive habitat models developed for a threatened stag beetle, Hoplogonus simsoni, found in the wet eucalypt forests and mixed/rainforests of north-east Tasmania. The relationship between various environmental variables for which spatial (GIS) information was available and the density, frequency of occurrence and presence/absence of the species was investigated using generalised linear modelling. Models developed were coupled with the GIS data to develop maps of predicted occurrence within the species’ range, grouped into categories of habitat quality. The models found that altitude, aspect, slope, distance to nearest stream and overstorey tree height were significantly associated with the occurrence of the species. Evaluation of the statistical strength of the models with independent data of species’ occurrence collected at 95 sites found that the density model performed poorly with little correlation between predicted and observed densities of the species. The frequency of occurrence model, however, showed a moderate ability to predict both species’ abundance and presence/absence. The presence/absence model had a similar discriminatory ability in predicting presence or absence of H. simsoni, but also showed some potential as an indirect predictor of species’ abundance. Assuming a correlation between relative abundance and habitat quality, the frequency of occurrence predictive model appeared to be the better and more direct discriminator of high quality habitat relative to the other models. The value of species’ habitat models and the need to evaluate their utility in the development of conservation strategies are discussed. |
| Keywords: | Predictive modelling Habitat modelling Model evaluation GIS Threatened species Forestry Invertebrates |
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