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Identifying the location of fire refuges in wet forest ecosystems

Berry, Laurence E., Driscoll, Don A., Stein, John A., Blanchard, Wade, Banks, Sam C., Bradstock, Ross A. and Lindenmayer, David B. 2015, Identifying the location of fire refuges in wet forest ecosystems, Ecological applications, vol. 25, no. 8, pp. 2337-2348, doi: 10.1890/14-1699.1.

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Title Identifying the location of fire refuges in wet forest ecosystems
Author(s) Berry, Laurence E.
Driscoll, Don A.ORCID iD for Driscoll, Don A. orcid.org/0000-0002-1560-5235
Stein, John A.
Blanchard, Wade
Banks, Sam C.
Bradstock, Ross A.
Lindenmayer, David B.
Journal name Ecological applications
Volume number 25
Issue number 8
Start page 2337
End page 2348
Total pages 12
Publisher Wiley
Place of publication London, Eng.
Publication date 2015-12
ISSN 1051-0761
Keyword(s) disturbance ecology
fire refuges
forest management
habitat fragmentation
high-severity fires
landscape modeling
model validation
topography
Victorian Central Highlands
australia
wet montane forest
Summary The increasing frequency of large, high-severity fires threatens the survival of old-growth specialist fauna in fire-prone forests. Within topographically diverse montane forests, areas that experience less severe or fewer fires compared with those prevailing in the landscape may present unique resource opportunities enabling old-growth specialist fauna to survive. Statistical landscape models that identify the extent and distribution of potential fire refuges may assist land managers to incorporate these areas into relevant biodiversity conservation strategies. We used a case study in an Australian wet montane forest to establish how predictive fire simulation models can be interpreted as management tools to identify potential fire refuges. We examined the relationship between the probability of fire refuge occurrence as predicted by an existing fire refuge model and fire severity experienced during a large wildfire. We also examined the extent to which local fire severity was influenced by fire severity in the surrounding landscape. We used a combination of statistical approaches, including generalized linear modeling, variogram analysis, and receiver operating characteristics and area under the curve analysis (ROC AUC). We found that the amount of unburned habitat and the factors influencing the retention and location of fire refuges varied with fire conditions. Under extreme fire conditions, the distribution of fire refuges was limited to only extremely sheltered, fire-resistant regions of the landscape. During extreme fire conditions, fire severity patterns were largely determined by stochastic factors that could not be predicted by the model. When fire conditions were moderate, physical landscape properties appeared to mediate fire severity distribution. Our study demonstrates that land managers can employ predictive landscape fire models to identify the broader climatic and spatial domain within which fire refuges are likely to be present. It is essential that within these envelopes, forest is protected from logging, roads, and other developments so that the ecological processes related to the establishment and subsequent use of fire refuges are maintained.
Language eng
DOI 10.1890/14-1699.1
Field of Research 050104 Landscape Ecology
Socio Economic Objective 970105 Expanding Knowledge in the Environmental Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, Ecological Society of America.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082294

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Citation counts: TR Web of Science Citation Count  Cited 8 times in TR Web of Science
Scopus Citation Count Cited 12 times in Scopus
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