Land use planning and wildfire risk mitigation: an analysis of wildfire-burned subdivisions using high-resolution remote sensing imagery and GIS data

This paper evaluates risk factors that influence the probability that a house will burn from wildfire. A logistic regression is used to analyse data processed from pre-fire and post-fire IKONOS images and other geo-referenced data. The dependent variable is the probability that a given house will burn. A total of 12 independent variables are evaluated: vegetation density; area of defensible space; adjacency of a parcel to public lands; proximity of a house to fire station; road width; road type; parcel size; subdivision morphology; assessed value; elevation; slope and aspect. Model results generally support dominant land use planning and design strategies for wildfire risk reduction including vegetation treatments, site selection with respect to topography, and improving access to fire stations.     

Social learning in a policy-mandated collaboration: community wildfire protection planning in the eastern United States

Policies such as the US Healthy Forests Restoration Act (HFRA) mandate collaboration in planning to create benefits such as social learning and shared understanding among partners. However, some question the ability of top-down policy to foster successful local collaboration. Through in-depth interviews and document analysis, this paper investigates social learning and transformative learning in three case studies of Community Wildfire Protection Planning (CWPP), a policy-mandated collaboration under HFRA. Not all CWPP groups engaged in social learning. Those that did learned most about organisational priorities and values through communicative learning. Few participants gained new skills or knowledge through instrumental learning. CWPP groups had to commit to learning, but the design of the collaborative-mandate influenced the type of learning that was most likely to occur. This research suggests a potential role for top-down policy in setting the structural context for learning at the local level, but also confirms the importance of collaborative context and process in fostering social learning.     

Influences on stakeholder support for a wildfire early warning system in a UK protected area

Projected increases in wildfire risk and impacts to human populations in the UK have prompted the installation of expanded management approaches such as early warning systems (EWSs). Newer iterations of wildfire EWSs help mitigate risk through rapid detection, often using high-resolution monitoring technology and instantaneous information collection. While existing research suggests that local social context plays an important role in the effective application of EWSs, little is known about factors that contribute to stakeholder support for these technocratic systems and their successful implementation in protected areas. This study examines support for an EWS in Northumberland National Park, UK, using focus groups with a broad range of local stakeholders. We found that diverse stakeholder understandings of wildfire, different perceptions of wildfire risk, and varied identification of values at risk collectively help explain mixed support for the EWS. Mixed support also was an outgrowth of distrust between several stakeholder groups, indicating a need for improved communication regarding wildfire risk management across stakeholder groups. Results suggest that EWSs adopted in multi-use protected areas shared by a range of stakeholder are most likely to be successful when stakeholders have shared understandings of the hazard and opportunities for collective planning to address its risks. We conclude that EWSs are a viable approach to wildfire risk reduction, but there needs to be a critical consideration of pre-existing stakeholder dynamics for effective EWS implementation.     

Climatic Change, Wildfire, and Conservation

Abstract:  Climatic variability is a dominant factor affecting large wildfires in the western United States, an observation supported by palaeoecological data on charcoal in lake sediments and reconstructions from fire-scarred trees. Although current fire management focuses on fuel reductions to bring fuel loadings back to their historical ranges, at the regional scale extreme fire weather is still the dominant influence on area burned and fire severity. Current forecasting tools are limited to short-term predictions of fire weather, but increased understanding of large-scale oceanic and atmospheric patterns in the Pacific Ocean (e.g., El Niño Southern Oscillation, Pacific Decadal Oscillation) may improve our ability to predict climatic variability at seasonal to annual leads. Associations between these quasi-periodic patterns and fire occurrence, though evident in some regions, have been difficult to establish in others. Increased temperature in the future will likely extend fire seasons throughout the western United States, with more fires occurring earlier and later than is currently typical, and will increase the total area burned in some regions. If climatic change increases the amplitude and duration of extreme fire weather, we can expect significant changes in the distribution and abundance of dominant plant species in some ecosystems, which would thus affect habitat of some sensitive plant and animal species. Some species that are sensitive to fire may decline, whereas the distribution and abundance of species favored by fire may be enhanced. The effects of climatic change will partially depend on the extent to which resource management modifies vegetation structure and fuels.     

Road Erosion and Delivery Index (READI): A Model for Evaluating Unpaved Road Erosion and Stream Sediment Delivery

The Road Erosion and Delivery Index (READI) is a new geographic information system–based model to assess erosion and delivery of water and sediment from unpaved road networks to streams. READI quantifies the effectiveness of existing road surfacing and drain placements in reducing road sediment delivery and guides upgrades to optimize future reductions. Roads are draped on a digital elevation model and parsed into hydrologically distinct segments. Segments are further divided by engineered drainage structures. For each segment, a kinematic wave approximation generates runoff hydrographs for specified storms, with discharge directly to streams at road–stream crossings and onto overland‐flow plumes at other discharge points. Plumes are attenuated by soil infiltration, which limits their length, with delivery occurring if plumes intersect streams. Sediment production and sediment delivery can be calculated as a relative dimensionless index. READI predicts only a small proportion of new drains and new surfacing results in the majority of sediment delivery reductions. The model illustrates how the spatial relationships between road and stream networks, controlled by topography and network geometries, influence patterns of road–stream connectivity. READI was applied in seven northern California basins. The model was also applied in a recent burn area to examine how reduced hillslope infiltration can result in increased hydrologic connectivity and sediment delivery.     

Patterns of preference and practice: bridging actors in wildfire response networks in the American Northwest

The roles of bridging actors in emergency response networks can be important to disaster response outcomes. This paper is based on an evaluation of wildfire preparedness and response networks in 21 large‐scale wildfire events in the wildland—urban interface near national forests in the American Northwest. The study investigated how key individuals in responder networks anticipated seeking out specific people in perceived bridging roles prior to the occurrence of wildfires, and then captured who in fact assumed these roles during actual large‐scale events. It examines two plausible, but contradictory, bodies of theory—similarity and dissimilarity—that suggest who people might seek out as bridgers and who they would really go to during a disaster. Roughly one‐half of all pre‐fire nominations were consistent with similarity. Yet, while similarity is a reliable indicator of how people expect to organise, it does not hold up for how they organise during the real incident.     

Community support for wildfire mitigation at Peavine Métis Settlement,Alberta, Canada

This paper presents the findings of a study that explored public support for wildfire mitigation programmes implemented in Peavine Métis Settlement, an Indigenous community located in Alberta, Canada. Data were collected in a community-based study using interviews, focus groups and participant observation over a 4-year period. Results showed that support for the wildfire mitigation programme was influenced by local leadership, economics, community capacity and land and home ownership. The communal nature of land and home ownership on the settlement influenced support for wildfire mitigation that was conducted by the settlement at both the residential and community levels. Employment opportunities available in the community for settlement members for wildfire mitigation activities also increased support for the local wildfire mitigation programme. A local Aboriginal leader skilled in wildfire mitigation and existing community capacity was also seen as vital to settlement member support for the programme.     

Satellite-Derived Mean Fire Return Intervals As Indicators Of Change In Siberia (1995–2002)

Under current climate change scenarios, temperatures in Siberia are expected to increase, and consequently, fire is also expected to increase. Potential climate-induced change is difficult to assess in Siberia because ground-based fire data are not complete. This investigation introduces a method by which potential climate-induced change can be remotely evaluated. Mean fire return intervals are established for 58 ecosystems across Siberia using eight years of satellite-based area burned data (1995 to 2002). Mean fire return intervals should decrease under current climate change scenarios, however the results do not currently demonstrate consistent evidence of fire-induced change. The overall boreal forest mean fire return interval is lower than the published mean, inferring increased fire. Most notably, using satellite data to calculate mean fire return intervals in individual ecosystems for the entire population of fire is shown to be a viable method by which potential climate-induced land cover change can be evaluated.     

Regional governance and hazard information: the role of co-ordinated risk assessment and regional spatial accounting in wildfire hazard mitigation

With the threat of wildfire hanging over many communities in the Western and Southern United States, wildfire mitigation is evolving into a significant public responsibility for rural and urban edge county governments. Regional governance is an important piece of the effort to reduce wildfire risks although still weakly developed as a policy arena. This project explores two dimensions in which planning support systems can support regional governance: assessing patterns of wildfire risk accumulation; and, evaluating land use planning alternatives and their effects on cumulative risk levels. These tools are examined for regional governance using a prototype planning information system, the Alternative Growth Futures (AGF) tool, a scenario-building approach developed at the University of Colorado Denver. The project develops a hybrid urban growth model that integrates logistic regression techniques and methods for simulation of growth alternatives. This model is used to evaluate the attractiveness of undeveloped building sites with respect to natural amenities, distance to primary urban services and site characteristics such as slope. The model and scenario-testing framework are reasonably robust and suggest that regional spatial accounting methods have potential as a framework for inter-governmental and public discussion around wildfire planning.