Victorian Tall Eucalypt Forest Plot Network: Victorian Central highlands fire refuges project: Fire severity predictions and maps for the O'Shannassy and Maroonndah Water Catchments, Victoria, Australia, 2002-2009
Abstract: 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 tested the ability of a topographically based fire prediction model developed by Mackey et al (2002) in the O’Shannassy and Maroondah water catchments, NE north-east of Melbourne, Australia, with fire severity data collected following a large wildfire in 2009 in the same area. We derived our fire severity data from a larger map created by the Department of Sustainability and Environment (2009), using SPOT satellite imagery and the normalised-burnt ratio. 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.
Sampling method: As the region surrounding our study area is subject to heavy logging pressure, we chose to sample the O’Shannassy and Maroondah catchments only to remove any potential influence of logging on fire severity. See Mackey, B., D. Lindenmayer, M. Gill, M. McCarthy, and J. Lindesay (2002) Wildlife, Fire and Future Climate: A Forest Ecosystem Analysis. CSIRO Publishing, Collingwood and Department of Sustainability and Environment (2009) Remote sensing guideline for assessing landscape-scale fire severity in Victoria’s forest estate. Unpublished technical manual, Department of Sustainability and Environment, Melbourne.
Study extent: The predicted severity values were created in 2002 by Mackey et al (2002). The fire severity data were collected by DSE (2009) following the 2009 ‘Black Saturday’ bushfires in the region.
Project funding: This project was not directly funded by any sources. Laurence Berry was supported by an ARC discovery scholarship as part of the Victorian Central Highlands (VCH) long term research project.
Field observations used to cross-validate the DSE (2009) fire severity data were collected from long term monitoring sites across the VCH by project field staff. These observations were made in 2009. Between 2012 and 2018 the Plot Network infrstructure was funded as part of the Long Term Ecological Research Network (LTERN), a facility within the Terrestrial Ecosystem Research Network (TERN). TERN is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy.
Type
collection
Title
Victorian Tall Eucalypt Forest Plot Network: Victorian Central highlands fire refuges project: Fire severity predictions and maps for the O'Shannassy and Maroonndah Water Catchments, Victoria, Australia, 2002-2009
Alternate Title
Victorian Tall Eucalypt Forest Plot Network: Fire Severity Predictions And Maps, 2002–2009
Collection Type
Dataset
Access Privileges
Long Term Ecological Research Network
DOI - Digital Object Identifier
10.25911/5c45394931e9d
Metadata Language
English
Data Language
English
Brief Description
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.
Full Description
Abstract: 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 tested the ability of a topographically based fire prediction model developed by Mackey et al (2002) in the O’Shannassy and Maroondah water catchments, NE north-east of Melbourne, Australia, with fire severity data collected following a large wildfire in 2009 in the same area. We derived our fire severity data from a larger map created by the Department of Sustainability and Environment (2009), using SPOT satellite imagery and the normalised-burnt ratio. 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.
Sampling method: As the region surrounding our study area is subject to heavy logging pressure, we chose to sample the O’Shannassy and Maroondah catchments only to remove any potential influence of logging on fire severity. See Mackey, B., D. Lindenmayer, M. Gill, M. McCarthy, and J. Lindesay (2002) Wildlife, Fire and Future Climate: A Forest Ecosystem Analysis. CSIRO Publishing, Collingwood and Department of Sustainability and Environment (2009) Remote sensing guideline for assessing landscape-scale fire severity in Victoria’s forest estate. Unpublished technical manual, Department of Sustainability and Environment, Melbourne.
Study extent: The predicted severity values were created in 2002 by Mackey et al (2002). The fire severity data were collected by DSE (2009) following the 2009 ‘Black Saturday’ bushfires in the region.
Project funding: This project was not directly funded by any sources. Laurence Berry was supported by an ARC discovery scholarship as part of the Victorian Central Highlands (VCH) long term research project.
Field observations used to cross-validate the DSE (2009) fire severity data were collected from long term monitoring sites across the VCH by project field staff. These observations were made in 2009. Between 2012 and 2018 the Plot Network infrstructure was funded as part of the Long Term Ecological Research Network (LTERN), a facility within the Terrestrial Ecosystem Research Network (TERN). TERN is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy.
Methods
Assembling fire severity data
1
None
The fire severity data presented in this data package was originally created by DSE (2009) using the normalized-burn ratio from SPOT satellite data. We trimmed the DSE fire severity layer to within the extent of the O’Shannassy and Maroondah water catchments only. The file represents a raster grid with 20 x 20 m cells. Within each cell fire severity is recorded on a scale of 1-5. 1) high severity crown fire 2) crown scorch 3) moderate crown fire (canopy survives) 4) understorey burn only 5) no fire in the crown or the understorey.
Assembling predicted fire severity data
2
None
We sourced data which mapped the probability of an area being retained as a fire refuge for fauna vulnerable to the effects of fire (probability of area remaining unburnt), from a study published by Mackey et al. (2002). As the original data used to create their model was unavailable, we rasterised a high quality digital image of the final published map showing the predicted distribution of areas likely to remain unburnt following a fire. This was trimmed to within the extent of the O’Shannassy and Maroondah water catchments only. The grid cells produced were 20 m x 20 m and shared identical co-ordinates with the DSE fire severity grid cells. This enabled a direct comparison to be made. The predicted severity data takes the form of a scale from 1-9, with 1 being a low probability that a location will remain unburnt and 9 being a high probability that a location will remain unburnt. Both sets of data were merged to form a large table of co-ordinates, severity values and predicted values for each catchment. To add depth to our analyses we also added environmental variables to each grid cell; topographic wetness index (twi), elevation, precipitation and aspect. To conduct analyses of spatial autocorrelation, we also included a spatially lagged response variable (SLRV) in our dataset (fm4, fm8). These were calculated in ArcMap using the focal mean tool, which produces a severity value for each cell based on the mean severity values in the surrounding 4 (rook) and 8 (queen) cells.
File Descriptions
lvic_berry_fire_severity_maroondahcatchment_p363t617.csv
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lvic_berry_fire_severity_oshannassycatchment_p363t618.csv
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Contact Email
david.lindenmayer@anu.edu.au;
david.keith@environment.nsw.gov.au;
Laurence.berry@anu.edu.au;
david.keith@unsw.edu.au;
davoblair@nex.net.au
Contact Address
Fenner School of Environment & Society
ANU College of Medicine, Biology & Environment
rank Fenner Building 141
Linnaeus Way
CANBERRA, ACT, 0200
Australia
Contact Phone Number
+61 2 612 50654;
+61 439 660 996;
+61 2 9995 5000;
+61 2 6125 7653;
+61 427 770 593;
+61 2 9385 2111;
+61 427 856 498
Contact Fax Number
+61 2 6125 0746
Principal Investigator
David Lindenmayer
Supervisors
David Lindenmayer
Collaborators
Brendan Mackey;
Laurence Berry;
John Stein
Fields of Research
0501 - Ecological Applications;
0502 - Environmental Science and Management
Keywords
GCMD:Earth Science Services > Hazards Management > Hazards Planning;
LTERN Monitoring Theme:Fire;
LTERN Monitoring Theme:Fragmentation;
Victorian Tall Eucalypt Forest;
Fire Severity Predictions And Maps
Type of Research Activity
Strategic basic research
Date Coverage
2009
2002
Geospatial Location
O’Shannassy and Maroondah Water Catchments ~ approximately 80km NE of Melbourne in Victoria, Australia
text
northlimit = -37.584; southlimit = -37.6579; westlimit = 145.5; eastLimit = 145.7311
iso19139dcmiBox
Date of data creation
2015-05-31
Year of data publication
2015
Creator(s) for Citation
Lindenmayer
David
Blair
David
Keith
David
McBurney
Lachlan
Berry
Laurence
Publisher for Citation
Long Term Ecological Research Network (LTERN), ANU Data Commons, The Australian National University
Publications
Department of Sustainability and Environment (2009) Remote sensing guideline for assessing landscape-scale fire severity in Victoria’s forest estate. Unpublished technical manual., Department of Sustainability and Environment, Melbourne.
Remote sensing guideline for assessing landscape-scale fire severity in Victoria’s forest estate.
9780643090040
Mackey, B., D. Lindenmayer, M. Gill, M. McCarthy, and J. Lindesay. 2002. Wildlife, Fire and Future Climate: A Forest Ecosystem Analysis. CSIRO Publishing, Collingwood.
Wildlife, Fire and Future Climate: A Forest Ecosystem Analysis
isbn
Related Websites
ANU Open Research. Long Term Ecological Research Network (LTERN) collection.
http://hdl.handle.net/1885/130861
Other Related Identifiers
MorphoId:ltern2.288;
PackageId:363
Access Rights
If this data is accepted for publication, the metadata should be made live as soon as possible. However, the data should be embargoed until appropriate approval to publish has been received from whoever holds the rights to reproduce the fire severity data originally created by DSE 2009 (John Stein).
Approval to reproduce the Mackey et al (2002) data can be sought from David Lindenmayer, a co-author on the original paper.
These conditions must be included when licensing any derivative works.
Access Rights Type
Open
Rights held in and over the data
Creative Commons Licence (CC BY-SA) is assigned to this data. Details of the licence can be found at http://creativecommons.org.au/licences.
Licence Type
CC-BY-SA - Attribution-SharedAlice (Version 4.0)
Licence
LTERN Deed: 38
Date of execution: 2015-03-16
Original Licence:TERN-BY-SA-1_0
Retention Period
Indefinitely
Data Management Plan
No
Status: Published
Published to:
Published to:
- Australian National University
- Australian National Data Service
Related items
- hasAssociationWith:
Victorian Tall Eucalypt Forest Plot Network data packages, 1983-2018 [anudc:5557] - hasAssociationWith:
Laurence Berry [anudc:5602] - hasAssociationWith:
Brendan Mackey [anudc:5568] - hasAssociationWith:
John Stein [anudc:5597] - hasAssociationWith:
Professor David Lindenmayer [anudc:5580]