Prediction maps produced by species distribution models (SDMs) influence decision-making in resource management or designation of land in conservation planning. Many studies have compared the prediction accuracy of different SDM modeling methods, but few have quantified the similarity among prediction maps. There has also been little systematic exploration of how the relative importance of different predictor variables varies among model types and affects map similarity. Our objective was to expand the evaluation of SDM performance for 45 plant species in southern California to better understand how map predictions vary among model types, and to explain what factors may affect spatial correspondence, including the selection and relative importance of different environmental variables. Four types of models were tested. Correlation among maps was highest between generalized linear models (GLMs) and generalized additive models (GAMs) and lowest between classification trees and GAMs or GLMs. Correlation between Random Forests (RFs) and GAMs was the same as between RFs and classification trees. Spatial correspondence among maps was influenced the most by model prediction accuracy (AUC) and species prevalence; map correspondence was highest when accuracy was high and prevalence was intermediate (average prevalence for all species was 0.124). Species functional type and the selection of climate variables also influenced map correspondence. For most (but not all) species, climate variables were more important than terrain or soil in predicting their distributions. Environmental variable selection varied according to modeling method, but the largest differences were between RFs and GLMs or GAMs. Although prediction accuracy was equal for GLMs, GAMs, and RFs, the differences in spatial predictions suggest that it may be important to evaluate the results of more than one model to estimate the range of spatial uncertainty before making planning decisions based on map outputs. This may be particularly important if models have low accuracy or if species prevalence is not intermediate.

Periodic wildfire is an important natural process in Mediterranean-climate ecosystems, but increasing fire recurrence threatens the fragile ecology of these regions. Because most fires are human-caused, we investigated how human population patterns affect fire frequency. Prior research in California suggests the relationship between population density and fire frequency is not linear. There are few human ignitions in areas with low population density, so fire frequency is low. As population density increases, human ignitions and fire frequency also increase, but beyond a density threshold, the relationship becomes negative as fuels become sparser and fire suppression resources are concentrated. We tested whether this hypothesis also applies to the other Mediterranean-climate ecosystems of the world. We used global satellite databases of population, fire activity, and land cover to evaluate the spatial relationship between humans and fire in the world’s five Mediterranean-climate ecosystems. Both the mean and median population densities were consistently and substantially higher in areas with than without fire, but fire again peaked at intermediate population densities, which suggests that the spatial relationship is complex and nonlinear. Some land-cover types burned more frequently than expected, but no systematic differences were observed across the five regions. The consistent association between higher population densities and fire suggests that regardless of differences between land-cover types, natural fire regimes, or overall population, the presence of people in Mediterranean-climate regions strongly affects the frequency of fires; thus, population growth in areas now sparsely settled presents a conservation concern. Considering the sensitivity of plant species to repeated burning and the global conservation significance of Mediterranean-climate ecosystems, conservation planning needs to consider the human influence on fire frequency. Fine-scale spatial analysis of relationships between people and fire may help identify areas where increases in fire frequency will threaten ecologically valuable areas.

As wildfires have increased in frequency and extent, so have the number of homes developed in the wildland–urban interface. In California, the predominant approach to mitigating fire risk is construction of fuel breaks, but there has been little empirical study of their role in controlling large fires. We constructed a spatial database of fuel breaks on the Los Padres National Forest in southern California to better understand characteristics of fuel breaks that affect the behaviour of large fires and to map where fires and fuel breaks most commonly intersect. We evaluated whether fires stopped or crossed over fuel breaks over a 28-year period and compared the outcomes with physical characteristics of the sites, weather and firefighting activities during the fire event. Many fuel breaks never intersected fires, but others intersected several, primarily in historically fire-prone areas. Fires stopped at fuel breaks 46% of the time, almost invariably owing to fire suppression activities. Firefighter access to treatments, smaller fires and longer fuel breaks were significant direct influences, and younger vegetation and fuel break maintenance indirectly improved the outcome by facilitating firefighter access. This study illustrates the importance of strategic location of fuel breaks because they have been most effective where they provided access for firefighting activities.

In many coniferous forests of the western United States, wildland fuel accumulation and projected climate conditions increase the likelihood that fires will become larger and more intense. Fuels treatments and prescribed fire are widely recommended, but there is uncertainty regarding their ability to reduce the severity of subsequent fires at a landscape scale. Our objective was to investigate the interactions among landscape-scale fire regimes, fuels treatments and fire weather in the southern Sierra Nevada, California. We used a spatially dynamic model of wildfire, succession and fuels management to simulate long-term (50 years), broad-scale (across 2.2 × 106 ha) effects of fuels treatments. We simulated thin-from-below treatments followed by prescribed fire under current weather conditions and under more severe weather. Simulated fuels management minimised the mortality of large, old trees, maintained total landscape plant biomass and extended fire rotation, but effects varied based on elevation, type of treatment and fire regime. The simulated area treated had a greater effect than treatment intensity, and effects were strongest where more fires intersected treatments and when simulated weather conditions were more severe. In conclusion, fuels treatments in conifer forests potentially minimise the ecological effects of high-severity fire at a landscape scale provided that 8% of the landscape is treated every 5 years, especially if future fire weather conditions are more severe than those in recent years.

Greehouse gas emissions have significantly altered global climate, and will continue to do so in the future.  Increases in the frequency, duration, and/or severity of drought and heat stress associated with climate change could fundamentally alter the composition, structure, and biogeography of forests in many regions.  Of particular concern are potential increases in tree mortality associated with climate-induced physiological stress and interactions with other climate-mediated processes such as insect outbreaks and wildfire.  Despite the risk, existing projections of tree mortality are based on models that lack functionally realitic mortality mechanisms, and there has been no attempt to track observations of climate-driven tree mortality globally.  Here we present the first global assessment of recent tree mortality attributed to drought and heat stress.  Although episodic mortality occurs in the absense of climate change, studies compiled here suggest that at least some of the world’s forested ecosystems already may be responding to climate change and raise concern that forests may become increasingly vulnerable to higher background tree mortality rates and die-off in response to future warming and drought, even in environments that are not normally considered water-limited.  This further suggests risk to ecosystem services, including the loss of sequestered forest carbon and associated atmospheric feedbacks.  Our review also identifies key information gaps and scientific uncertainties that currently hinder our ability to predict tree mortality in response to climate change and emphasize the need for a globally coordinated observation system.  Overall, our review reveals the potential for amplified tree mortality due to drought and heat in forests worldwide.

CBI will develop and apply a forest management decision-support system (DSS) for forest resilience planning in the southern Sierra Nevada that integrates the latest science on how vegetation, terrain, climate, and weather interact to influence fire risks and forest resilience. The interdisciplinary team led by CBI includes ecological modelers, forest ecologists, fire scientists, physicists, and statisticians. The core of the DSS will be a Forest Resilience Model built using EEMS (Ecosystem Evaluation Modeling System; Sheehan and Gough 2016). The DSS will be tested, refined, and applied to resilience planning in that portion of the modeling region of greatest concern to the interagency Sequoia Regional Partnership, which is working to restore ecologically resilient conditions in and near Sequoia National Forest and Sequoia-Kings Canyon National Park.

The resilience model evaluates forest resilience to fire, drought, and other factors based on landscape conditions. The DSS will allow managers to simulate fuel-reduction treatments, evaluate their effects on a range of risks and resources (e.g., fire, sequoias, fisher habitat), project the impacts into the future, and assess levels of uncertainty.  The DSS and component models will help managers understand how, in concert with terrain and weather, vegetation structure influences fire behavior and forest resilience. Importantly, the DSS will for the first time consider how fire-atmosphere coupling affects fire in models to support forest planning. This will apply how vegetation structure influences fire via both fuel arrangements and air flows, and thus more accurately reflect the full picture of how vegetation treatments may affect fire and fire effects on the landscape.

The DSS will be further refined and applied to resilience planning by the Sequoia Regional Partnership, whose primary focus is reducing fire risks to giant sequoia groves, fishers, and human communities.  

External Team members include: Joe Werne (NorthWest Research Associates NWRA), Christopher Wikle (Department of Statistics, University of Missouri) and David Marvin (SALO Science).   

Map of project study area.

Efforts are underway in Sonoma County to provide critical information to facilitate strategic, ecologically-sensitive fuel management across the region for the long-term resilience of its communities and watersheds. The Sonoma County Wildfire Resilience Decision Support Framework is part of a county-wide coordinated initiative to prioritize actions and investments by local agencies implementing the Sonoma County Community Wildfire Protection Plan.

Two online decision-support tools make up the Decision Support Framework:

The Wildfire Resilience Planner: Strategic Planning at the Landscape Scale

Sonoma Water, Conservation Biology Institute (CBI), Ag Innovations, Pepperwood Preserve, Tukman Geospatial, Digital Mapping Solutions have created the Sonoma County Wildfire Resilience Planner, an online decision support tool for prioritizing locations to reduce wildfire fuels to protect lives and property, community infrastructure, ecosystem services, and biodiversity. The tool encourages collaborative planning of projects on public and private land, helping to leverage individual efforts for a unified and strategic approach to fuels management. The Wildfire Resilience Planner is available for use at https://sonoma.resilienceplanner.org/. For more information or to provide feedback, please contact Molly Oshun, Molly.Oshun@scwa.ca.gov or Deanne DiPietro, deanne.dipietro@consbio.org.

Above: the Sonoma County Wildfire Resilience Planner provides the user with the spatial data and analysis tools to identify high-priority locations for wildland fuels management.

The Wildfire Fuel Mapper: Property-Specific Information for Fuels Management

The University of California Cooperative Extension, Pepperwood Preserve, and Tukman Geospatial have developed the Wildfire Fuel Mapper, on online tool that provides landowners and managers with maps and information for designing and implementing projects to reduce wildland fuels. For more information contact Stephanie Larson slarson@ucanr.edu or Kai Foster kfoster@pepperwoodpreserve.org.

Conservation Biology Institute and the Resource Conservation District of the Santa Monica Mountains are working in partnership with local land management agencies and communities to increase wildfire resilience in the Santa Monica Mountains region. The Program has the following tasks:

Raising awareness about wildfire risk in the local communities

Helping homeowners prepare for wildfire

Mapping and planning the control of flammable invasive weeds in the Woolsey Fire footprint

Modeling and research to inform planning and decision making

The Santa Monica Mountains Woolsey Fire Recovery and Adaptation Program is funded by the National Fish and Wildlife Foundation.

As the Sierra Nevada town of Paradise rebuilds after the devastating Camp Fire of 2018, the community has an opportunity to incorporate strategies to increase its resilience to fire and climate change, enhance the safety and well-being of its residents, and at the same time care for the surrounding natural areas that make it a beautiful place to live.

CBI and the The Nature Conservancy helped Paradise seize this opportunity when the Paradise Recreation and Park District asked us to help them explore community design principles that could provide all of these benefits. The CBI team created geographic models of “Wildfire Risk Reduction Buffers” between the structures and the surrounding wildlands to reduce exposure of homes to wildfire risks. These buffers, which can be made up of parklands, orchards, and other low fire-risk land uses, can be managed to provide many benefits, including buffering homes from ignition, providing safe-haven refuges for residents to escape from fire, strategically-placed staging areas for fire-fighters, recreational access to open space, and protecting natural habitat from the effects of an encroaching urban landscape.

The team combined spatial data about the landscape with local knowledge to prioritize locations for fire risk-reduction and analyzed ignition risks and co-benefits with and without the buffers. The resulting maps illustrate the potential for local partnerships to make a real difference in the town’s future. Through innovative thinking about the role of land use planning, the community of Paradise is changing its approach to living with fire and providing a model for fire-prone communities everywhere.

CBI is working in collaboration with Oregon State University, the University of Minnesota, and the University of Colorado Boulder on a project designed to help improve our understanding of post-fire community resilience. Central to the project will be the development of an RFID sensor network which will help support post-fire assessments of water infrastructure damage. These sensors will be deployed across a community’s freshwater pipeline network and will transmit data (e.g., temperature reached, pipeline material, exposure duration) that will help determine whether or not toxins have started leaching from the pipes into the freshwater supply. The current phase of the project focuses on Santa Rosa and Paradise in California where the 2017 Tubbs Fire and the 2018 Camp Fire caused damage to the water distribution systems, resulting in contaminated water within the system. 

To help support this effort, CBI has developed a web application called the Wildfire Vulnerability Explorer, which can be accessed at https://wildfirevulnerability.eemsonline.org. This application allows users to explore a set of spatially explicit models developed for Santa Rosa and Paradise that identify areas likely to be vulnerable to water contamination exposure following a large-scale fire event. Estimates of vulnerability are based on three primary factors: the probability of water contamination, socioeconomic sensitivity, and adaptive capacity. The Wildfire Vulnerability Explorer brings this information together in an interactive map in order to help officials with both pre-fire planning and post-fire prioritization of recovery efforts – by identifying communities that are the most vulnerable to water contamination exposure, efforts can be taken to better plan for and direct resources to those areas.  

Additional information about the project is available on the OSU project page at the link below:     

Sensor Technology for Improved Wildland Urban Interface (WUI) Fire Resilience  

Funding for the project was provided by the Alfred P. Sloan Foundation.

Photo courtesy of NASA (https://earthobservatory.nasa.gov/images/144225/camp-fire-rages-in-california): Camp Fire in Paradise, California, which is one of the project study areas.