Will climate change overwhelm fire management capacity?

Using anomalies calculated from General Circulation Model (GCM) climate predictions we developed scenarios of future fire weather, fuel moisture and fire occurrence and used these as the inputs to a fire growth and suppression simulation model for the province of Ontario, Canada. The goal of this study was to combine GCM predictions with the fire growth and suppression model to examine potential changes in area burned in Ontario due to climate change, while accounting for the large fire suppression activities of the Ontario Ministry of Natural Resources (OMNR). Results indicate a doubling of area burned in the Intensive and Measured fire management zones of Ontario by the decade of 2040 and an eightfold increase in area burned by the end of the 21st century in the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 scenario; smaller increases were found for the A1b and B1 scenarios. These changes are driven by increased fire weather conducive to large fire growth, and increases in the number of fires escaping initial attack: for the Canadian GCM's business-as-usual (A2) scenario, escaped fire frequency increased by 34% by 2040 and 92% by the end of the 21st century. Incorporating more detail on large fire growth than previous studies, our model predicts higher area burned under climate change than do these previous studies, as large numbers of high-intensity fires overwhelm suppression capacity.     

Modeling mammal response to fire based on species’ traits

Fire has shaped ecological communities worldwide for millennia, but impacts of fire on individual species are often poorly understood. We performed a meta-analysis to predict which traits, habitat, or study variables and fire characteristics affect how mammal species respond to fire. We modeled effect sizes of measures of population abundance or occupancy as a function of various combinations of these traits and variables with phylogenetic least squares regression. Nine of 115 modeled species (7.83%) returned statistically significant effect sizes, suggesting most mammals are resilient to fire. The top-ranked model predicted a negative impact of fire on species with lower reproductive rates, regardless of fire type (estimate = –0.68), a positive impact of burrowing in prescribed fires (estimate = 1.46) but not wildfires, and a positive impact of average fire return interval for wildfires (estimate = 0.93) but not prescribed fires. If a species’ International Union for Conservation of Nature Red List assessment includes fire as a known or possible threat, the species was predicted to respond negatively to wildfire relative to prescribed fire (estimate = –2.84). These findings provide evidence of experts’ abilities to predict whether fire is a threat to a mammal species and the ability of managers to meet the needs of fire-threatened species through prescribed fire. Where empirical data are lacking, our methods provide a basis for predicting mammal responses to fire and thus can guide conservation actions or interventions in species or communities.     

Comparing modern and presettlement forest dynamics of a subboreal wilderness: does spruce budworm enhance fire risk?

Insect disturbance is often thought to increase fire risk through enhanced fuel loadings, particularly in coniferous forest ecosystems. Yet insect disturbances also affect successional pathways and landscape structure that interact with fire disturbances (and vice-versa) over longer time scales. We applied a landscape succession and disturbance model (LANDIS-II) to evaluate the relative strength of interactions between spruce budworm (Choristoneura fumiferana) outbreaks and fire disturbances in the Boundary Waters Canoe Area (BWCA) in northern Minnesota (USA). Disturbance interactions were evaluated for two different scenarios: presettlement forests and fire regimes vs. contemporary forests and fire regimes. Forest composition under the contemporary scenario trended toward mixtures of deciduous species (primarily Betula papyrifera and Populus spp.) and shade-tolerant conifers (Picea mariana, Abies balsamea, Thuja occidentalis), with disturbances dominated by a combination of budworm defoliation and high-severity fires. The presettlement scenario retained comparatively more "big pines" (i.e., Pinus strobus, P. resinosa) and tamarack (L. laricina), and experienced less budworm disturbance and a comparatively less-severe fire regime. Spruce budworm disturbance decreased area burned and fire severity under both scenarios when averaged across the entire 300-year simulations. Contrary to past research, area burned and fire severity during outbreak decades were each similar to that observed in non-outbreak decades. Our analyses suggest budworm disturbances within forests of the BWCA have a comparatively weak effect on long-term forest composition due to a combination of characteristics. These include strict host specificity, fine-scaled patchiness created by defoliation damage, and advance regeneration of its primary host, balsam fir (A. balsamea) that allows its host to persist despite repeated disturbances. Understanding the nature of the three-way interaction between budworm, fire, and composition has important ramifications for both fire mitigation strategies and ecosystem restoration initiatives. We conclude that budworm disturbance can partially mitigate long-term future fire risk by periodically reducing live ladder fuel within the mixed forest types of the BWCA but will do little to reverse the compositional trends caused in part by reduced fire rotations.     

Modelling forest–savanna mosaic dynamics in man-influenced environments: effects of fire,climate and soil heterogeneity

Forests and savannas are the major ecotypes in humid tropical regions. Under present climatic conditions, forest is in a phase of natural expansion over savanna, but traditional human activities, especially fires, have strongly influenced the succession. We here present a new model, FORSAT, dedicated to the forest–savanna mosaic on a landscape scale and based on stochastic modelling of key processes (fire and succession cycle) and consistent with common field data. The model is validated by comparison between the qualitative emergent behaviour of the model and results of biogeographical field studies. Three types of forest succession are shown: progression of the forest edge, formation and coalescence of clumps in savanna and global afforestation of savanna. The parameters (frequency of savanna fires, climate and soil fertility) appear to have comparable effects and there is a sharp threshold between a forest edge progression scenario and the cluster formation one. Moreover, pioneer seed dispersal pattern and recruitment are determinant: peaked curves near a seed source and far dispersal combine to increase the fitness of the pioneers.