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.

摘要：本研究以澳大利亚湿润山地森林为案例，旨在明确如何将火灾预测模拟模型解读为识别潜在火灾避难生境（fire refuges）的管理工具。我们采用2009年澳大利亚墨尔本东北方向奥沙纳西（O’Shannassy）与马隆达（Maroondah）集水区发生的大型野火后采集的火灾烈度数据，验证了Mackey等（2002）在上述集水区开发的基于地形的火灾预测模型性能。本研究的火灾烈度数据源自可持续与环境部（2009）制作的大比例尺地图，该地图基于SPOT卫星影像（SPOT satellite imagery）与归一化燃烧比（normalised-burnt ratio）生成。我们分析了现有火灾避难生境模型预测的避难生境出现概率与大型野火期间实际遭遇的火灾烈度之间的关联，同时探究了局地火灾烈度受周边景观火灾烈度影响的程度。本研究结合了多种统计方法，包括广义线性建模（generalised linear modelling）、变异函数分析（variogram analysis）以及受试者工作特征曲线与曲线下面积分析（ROC AUC）。

本研究发现，未燃烧生境的面积以及影响火灾避难生境留存与分布的因素，会随火灾情境发生变化。在极端火灾情境下，火灾避难生境的分布仅局限于景观中极度遮蔽、耐火的区域；此时火灾烈度格局主要由模型无法预测的随机因素决定。当火灾情境为中等强度时，景观物理属性似乎会调控火灾烈度的分布格局。

本研究表明，土地管理者可借助景观火灾预测模型，确定火灾避难生境大概率存在的宽泛气候与空间范围。在此范围内，需禁止采伐、道路修建及其他开发活动，以维系与火灾避难生境的建立及后续利用相关的生态过程。

采样方法：由于研究区域周边承受高强度采伐压力，本研究仅对奥沙纳西集水区与马隆达集水区进行采样，以排除采伐活动对火灾烈度的潜在影响。详见：Mackey, B., D. Lindenmayer, M. Gill, M. McCarthy, 及 J. Lindesay (2002)《野生动物、火灾与未来气候：森林生态系统分析》，CSIRO出版公司，科灵伍德；以及可持续与环境部（2009）《维多利亚州森林资产景观尺度火灾烈度评估遥感指南》，未出版技术手册，可持续与环境部，墨尔本。

研究范围：预测烈度值由Mackey等（2002）于2002年生成。火灾烈度数据由可持续与环境部（DSE，2009）于该区域2009年“黑色星期六”丛林大火后采集。

项目资助：本项目未直接获得任何来源的资助。Laurence Berry的研究资助来自澳大利亚研究理事会（ARC）发现奖学金，作为维多利亚州中部高地（VCH）长期研究项目的一部分。

用于交叉验证可持续与环境部（DSE，2009）火灾烈度数据的野外观测数据，由项目野外人员从维多利亚州中部高地（VCH）全境的长期监测站点采集，观测工作于2009年完成。2012年至2018年间，样地网络基础设施的建设经费由长期生态研究网络（LTERN）提供，该网络是陆地生态系统研究网络（TERN）下属的设施。陆地生态系统研究网络（TERN）由澳大利亚政府通过国家协同研究基础设施战略提供资助。