rufous bristlebird habitat

To: Birding Aus <>
Subject: rufous bristlebird habitat
From: knightl <>
Date: Thu, 3 Jun 2004 21:18:41 +1000
The following paper is available from Lesley Gibson -

Spatial prediction of rufous bristlebird habitat in a coastal
heathland: a GIS-based approach
Gibson L.A.; Wilson B.A.; Cahill D.M.; Hill J.
Journal of Applied Ecology April 2004, vol. 41, no. 2, pp. 213-223

• To develop a conservation management plan for a species, knowledge of
its distribution and spatial arrangement of preferred habitat is
essential. This is a difficult task, especially when the species of
concern is in low abundance. In south-western Victoria, Australia,
populations of the rare rufous bristlebird Dasyornis broadbenti are
threatened by fragmentation of suitable habitat. In order to improve
the conservation status of this species, critical habitat requirements must be identified and a system of corridors must be established to
link known populations. A predictive spatial model of rufous
bristlebird habitat was developed in order to identify critical areas
requiring preservation, such as corridors for dispersal.
• Habitat models generated using generalized linear modelling
techniques can assist in delineating the specific habitat requirements of a species. Coupled with geographic information system (GIS) technology, these models can be extrapolated to produce maps displaying the spatial configuration of suitable habitat.
• Models were generated using logistic regression, with bristlebird
presence or absence as the dependent variable and landscape variables, extracted from both GIS data layers and multispectral digital imagery, as the predictors. A multimodel inference approach based on Akaike's information criterion was used and the resulting model was applied in a GIS to extrapolate predicted likelihood of occurrence across the entire area of concern. The predictive performance of the selected model was evaluated using the receiver operating characteristic (ROC) technique. A hierarchical partitioning protocol was used to identify the predictor variables most likely to influence variation in the dependent variable. Probability of species presence was used as an index of habitat
• Negative associations between rufous bristlebird presence and
increasing elevation, ‘distance to creek’, ‘distance to coast’ and sun
index were evident, suggesting a preference for areas relatively low in altitude, in close proximity to the coastal fringe and drainage lines, and receiving less direct sunlight. A positive association with increasing habitat complexity also suggested that this species prefers areas containing high vertical density of vegetation.
• The predictive performance of the selected model was shown to be high
(area under the curve 0·97), indicating a good fit of the model to the data. Hierarchical partitioning analysis showed that all the variables considered had significant independent contributions towards explaining the variation in the dependent variable. The proportion of the total
study area that was predicted as suitable habitat for the rufous
bristlebird (using probability of occurrence at a >= 0·5 level) was 16%.
• Synthesis and applications. The spatial model clearly delineated
areas predicted as highly suitable rufous bristlebird habitat, with
evidence of potential corridors linking coastal and inland populations via gullies. Conservation of this species will depend on management
actions that protect the critical habitats identified in the model. A
multiscale approach to the modelling process is recommended whereby a
spatially explicit model is first generated using landscape variables
extracted from a GIS, and a second model at site level is developed
using fine-scale habitat variables measured on the ground. Where there are constraints on the time and cost involved in measuring finer scale variables, the first step alone can be used for conservation planning.

Birding-Aus is now on the Web at
To unsubscribe from this mailing list, send the message 'unsubscribe
birding-aus' (no quotes, no Subject line)

<Prev in Thread] Current Thread [Next in Thread>

The University of NSW School of Computer and Engineering takes no responsibility for the contents of this archive. It is purely a compilation of material sent by many people to the birding-aus mailing list. It has not been checked for accuracy nor its content verified in any way. If you wish to get material removed from the archive or have other queries about the archive e-mail Andrew Taylor at this address: andrewt@cse.unsw.EDU.AU