Modelling of wildlife fatality hotspots along the Snowy Mountain Highway in New South Wales, Australia
- Publication Type:
- Journal Article
- Citation:
- Biological Conservation, 2005, 126 (4), pp. 474 - 490
- Issue Date:
- 2005-12-01
Closed Access
| Filename | Description | Size | |||
|---|---|---|---|---|---|
 | 2010005924OK.pdf | 650.94 kB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
The effects of roads on the natural environment is of growing concern world-wide and foremost amongst these effects are the fatalities of wildlife killed in collisions with vehicles. Aside from animal welfare and human safety considerations, fatalities may have significant impacts on the population dynamics of species living adjacent to roads and thus can adversely affect the viability of local populations. As such, the need to quantify and mitigate road-based fatalities is paramount. With a vast expanse of roads it is imperative to identify where animals are most likely to be killed (i.e. hotspots) and what are the contributing factors. In order to identify hotspots, we develop a modelling approach for both presence and presence/absence data. We use data collected from the Snowy Mountain Highway in southern New South Wales, Australia, to compare the effectiveness of this approach for five species/groups of species. We observed that models of species killed in a clumped fashion were effective at identifying hotspots, while for species where fatalities were distributed evenly along the road the models were less effective. We recommend that where actual presence data exists spatial clustering is the preferred method of hotspot identification. Predictive models of presence/absence date should be constructed if the intention is to extrapolate to additional areas. The added benefit of predictive models are that they enable the identification of explanatory factors and this knowledge enables species-specific management strategies to be developed and implemented at hotspot locations. © 2005 Elsevier Ltd. All rights reserved.
Please use this identifier to cite or link to this item: