Evaluating ecological resilience across wildfire suppression levels under climate and fuel treatment scenarios using landscape simulation modelling

Continued suppression of wildfires may allow more biomass to accumulate to foster even more intense fires. Enlightened fire management involves explicitly determining concurrent levels of suppression, wildland fire use (allowing some fires to burn) and fuel treatments to manage landscapes for ecological resilience. This study used the mechanistic landscape model FireBGCv2 to simulate ecological dynamics on three landscapes in the US northern Rocky Mountains to determine responses of seven management-oriented variables over a gradient of 10 fire suppression levels under two climate and four fuel treatment scenarios. We used a historical range and variation (HRV) time series of the seven variables individually and merged together as a Principal Components factor (PC1) to define the envelope that represents ecological resiliency and compared all simulations with the HRV base case. We found that under today’s climates, using the PC1 factor, ecological resilience was maintained while suppressing 30–90% of wildfires depending on the landscape. We also found fuel treatments might allow higher suppression levels to occur and still maintain resilience. Other findings indicate that each landscape must be individually evaluated to determine the right mix of wildfires, wildland fire use and fuel treatments depending on the response variables used to evaluate resilience.

Beyond wildfire: perspectives of climate, managed fire and policy in the USA

Climate–wildfire relationships have been widely addressed by the scientific community over the last two decades; however, the role of climate in managed fire in the US (i.e. prescribed fire and wildland fire use) has not yet been addressed. We hypothesised that if climate is an important component of managed fire, the fire community would already be aware of this and using climate information in order to mitigate risks associated with managed fires. We conducted 223 surveys with fire managers to ascertain how climate information is utilised in managed-fire decision-making. We found that wildland fire use managers consider climate to be an important aspect of managed fire and use various types of climate information, but prescribed-fire managers do not generally consider climate or use climate information in their planning activities. Survey responses also indicate a lack of agency training on climate information and decision-support tools. This is partly attributed to obstacles in US fire policy that inhibit widespread utilisation of climate information. We suggest these results are indicative of a broader conflict in US wildfire policy, which does not directly address climate despite two decades of scientific research showing climate plays a key role in wildfire regimes.

A Managerial Approach to Estimating Wildland Fire Use Workload

Increasing recognition of the role of fire in natural ecosystems has increased the use of wildland fire as a management tool. Although wildland fire use (WFU) has been practiced for decades, it is emerging as an organized program. As such, the analytics of WFU, from a management sciences perspective, are largely undeveloped at a time when there is a growing need to inform program managers and support modeling efforts aimed at more cost-effective fire management programs. Conventional initial attack modeling relates workload to fire perimeter; but, currently, there is no analog for WFU events. This article takes the first step in providing a companion estimation of WFU workload. WFU workload is estimated as a function of basic information on fire size and duration by using a regression tree analysis. Workload scores for wildland fire use management and monitoring were estimated separately. These estimates explained about 68 and 60% of the variation in the management and monitoring scores, respectively. The estimated scores were sensitive to fire size, although duration played an important role, especially on larger events. For example, fires in the same size class often received higher workload scores with increasing duration. Workload estimates from the management regression tree were then associated with average resource usage. The form of the association indicated that as workload estimates increased, average resource usage increased exponentially. Estimating workload scores as a function of size and duration, which are readily available from simulation models, and then associating the scores with resource usage supports efforts to address WFU effort and cost management.