Book chapters in press

Following a visit to the US last year and meeting Chad Hanson and Dominick Dellasala as part of a study into the use of ecological knowledge in fire management, I was invited to contribute chapters to their recent book on the Ecological importance of mixed severity fires. The book is expected to be published in June 2015.

Berry, L.E and Sitters, H, 2015, ‘Case study: the ecology of mixed severity fire in mountain ash forests’, in Dellasala DA & Hanson CT (eds), The Ecological importance of mixed severity fires, Elsevier, In Press.

DellaSala, D.A, Hanson, C.T, Baker. W., Hutto, R.L., Odion, D.E., Berry, L.E., Abrams, R., Heneberg, P. and Sitters. H, 2015, ‘Flight of the Phoenix: Coexisting with Higher-Severity Fires’ in Dellasala DA & Hanson CT (eds), The Ecological importance of mixed severity fires, Elsevier, In Press.

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Paper in press – Predicting the occurrence of fire refuges

Berry, L.E., Driscoll, D.A., Stein, J.A., Blanchard, W., Banks, S.C., Bradstock, R.A. and Lindenmayer, D. B., 2015, Identifying the location of fire refuges in wet forest ecosystems, Ecological Applications


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 which 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 which 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 generalised linear modelling, variogram analysis and receiver operating characteristics and area under the curve analysis (ROC AUC).

We found that the amount of unburnt 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.