Outbreaks of forest insects are a significant agent of disturbance in Canada’s boreal and mixed-wood forests that affect forest landscape structure, including the accumulation of combustible fuels. As a result of repeated defoliation over consecutive years, defoliation by the spruce budworm (SBW; Choristoneura fumiferana) creates large patches of dead fir or spruce that have the potential to affect fire activity. Although it is generally believed that forest insects affect fire activity, how they have such an influence, and how this affect varies through time, remains equivocal. Expected northward expansion of multiple species of forest insect pest in combination with forecast climate-related increases in forest fire activity in the boreal forest means that there a a great deal of uncertainty regarding future disturbance interactions, their effects on forest composition and connectivity, and consequent ecosystem service provisioning.

In this research, we are seeking to better understand how historical defoliation by the spruce budworm affects fire risk including the probability of ignition, the probability of escape from initial control, and final fire size, in combination with multiple spatial and temporal covariates (e.g., weather and climate).

Recently, we completed a project modelling the relationship between historical fire ignitions and defoliation in Ontario using a a series of generalized additive logistic regression models. Using these models we contrasted fire-defoliation relationships between spring and summer fire seasons, as well as between ecoregions in eastern and western Ontario. We found that, in general, spruce budworm activity increases the risk of ignition 8-10 years after defoliation occurred, but decreases this risk immediately following defoliation (< 1 year).

The long term goal of this research is to produce predictive spatial models that can be used in combination with forecasted future climate and fire weather to predict changes in fire risk in response to changing forest landscapes and insect-induced changes to fuel structure and connectivity. 

Students:  Sophie Wilkinson, Franck Gandiaga, Kennedy Korkola, Clara Risk, Doriana Romualdi, Jack Goldman, Léo Jourdan

Collaborators:  Mike Wotton (UToronto), Jen Beverly (UAlberta), Laura Chasmer (ULeth), Jon Boucher (CFS)

Recent publications
Fettig CJ, Runyon JB, Homicz CS, James PMA, Ulyshen MD. (in press) Fire and Insect Interactions in North American Forests. Current Forestry Reports

Risk C & James PMA. 2022. Optimal cross-validation strategies for selection of spatial models in the Canadian Forest Fire Weather Index System. Earth and Space Science. 9(2), e2021EA002019.

James PMA, Robert, LE, Wotton BM, Martel D, Fleming RA. 2016. Lagged cumulative spruce budworm defoliation affects the risk of fire ignition in Ontario, Canada. Ecological Applications. 27(2): 532-544

Population outbreaks affect spatial demographic variation which can influence population genetic inference. Current models that aim to understand the spatial, temporal, and landscape genetic dynamics of outbreaking populations risk making incorrect conclusions regarding landscape connectivity, dispersal capacity, and adaptation. The goal of this research theme is to characterize how demographic context affects neutral and adaptive population genetic patterns and to develop new approaches that take this context into account. This work primarily focuses on outbreaking forest insect pests such as the spruce budworm. However, long-lived species (e.g., turtles) also present novel demographic contexts that confound traditional approaches to population genetic inference.

Spruce budworm
The spruce budworm (SBW; Choristoneura fumiferana) is a lepidopteran forest pest that devastates huge areas of spruce and fir forest during its periodic outbreaks. SBW outbreak dynamics are shaped by the complex interactions among climate, forest structure, communities of natural enemies, and dispersal. Despite the significance of movement to the spatial dynamics of SBW outbreaks, little is known about SBW dispersal, how it varies with spatial context and over course of an outbreak, and how it affects spatial synchrony in outbreak dynamics. This research applies tools and methods from spatial population genetics to characterize genetic connectivity among outbreak patches in the current outbreak in eastern north America. Using this information on genetic connectivity, and how it varies within and among years, we will infer patterns of gene flow and dispersal and how it varies as a function of intervening land-cover (isolation by resistance) and local environmental conditions (isolation by environment). Concurrently, we are developing dispersal models using predicted phenology (BioSIM) and demographic data collected from pheromone traps (adult males). Together, this work will increase our knowledge of how SBW movement varies in different forest and landscape contexts and will be used to improve simulation models that predict insect population dynamics and forecast future outbreak risk. This work will also address the important question of the potential efficacy  of currently proposed early intervention strategies.

Check out our photo gallery illustrating our sampling network and developing results. 

Students:  JP Fontenelle, Morgane Henry

Collaborators:  Rob Johns (CFS, AFC), Brian Leung, Jeremy Larroque

Recent Publications

Larroque J, Wittische J, James PMA. 2022. Quantifying and predicting population connectivity of an outbreaking forest insect pest. Landscape Ecology. 37(3), 763-778.

Landry M, Kneeshaw D, James PMA, Kembel S. 2022. Spruce budworm gut bacterial communities vary among sites and host tree species in a boreal landscape. Journal of Biogeography. 49(2), 299-309

Legault S, Wittische J, Cusson M, Brodeur J, James PMA. 2021. Genetic evidence of large-scale population connectivity in spruce budworm parasitoids. Molecular Ecology. 30(22), 5658-5673

Larroque J, Johns R, Canape J, Morin B, James PMA. 2020. Spatial genetic structure at the leading edge of a spruce budworm outbreak: the role of dispersal in outbreak spread. Forest Ecology and Management 461, 117965

Researchers are often faced with questions at spatial and temporal scales that exceed our manipulative capacities. For example, understanding the long term consequences of climate change or different forest management regimes on forest dynamics requires data at spatial and temporal scales much larger than are usually feasible in traditional ecological studies. Spatially explicit simulation modelling can be used to address these questions, with the caveat that models are not reality, but instead represent a simplified version of reality containing the main processes in which we are interested. In this way, simulation models should be considered as a way for us to observe the consequences of our assumptions about how systems work even when direct manipulation and observation may not be possible.

This research theme focuses on the long term consequences of forest management on landscape composition and configuration and how these spatial patterns affect habitat availability, landscape connectivity, and biodiversity conservation. Using spatially explicit simulation models and the SELES simulation platform, we examine how interactions between the spatial legacies created by forest management policies affect other ecological processes such as climate, fire and insect disturbance, forest succession, as well as community and population dynamics. 

Much of the other ongoing research in the lab will contribute new parameters, sub-models, and conceptual frameworks to current models of forest ecosystem dynamics and will improve their capacity to evaluate the sustainability of current land-management practices.