Projects | Alex M. Chubaty

Habitat Connectivity

Mon, 16 Apr 2018 20:41:21 -0600

Boreal forest ecosystem forecasts

Fri, 13 Apr 2018 20:37:16 -0600

Working with Eliot McIntire’s group at the Pacific Forestry Centre, we are integrating various simulation models dealing with forest vegetation dynamics, fire, insect disturbance, and wildlife populations, to inform decision making in these management areas.

Eruptive Insect Dynamics

Fri, 13 Apr 2018 20:37:16 -0600

Several of Canada’s most economically and ecologically important forest pests – forest tent caterpillar (Malacosoma disstria), spruce budworm (Choristoneura fumiferana), and mountain pine beetle (Dendroctonus ponderosae) – share a defining trait: their populations are governed by eruptive, nonlinear density-dependent processes that periodically push local densities from endemic to outbreak levels. Understanding how these dynamics unfold across space and time is central to anticipating where and when outbreaks will occur, how long they will persist, and under what conditions they will collapse.

Working with Barry Cooke and collaborators, we use long-term defoliation and aerial-survey records to characterize the periodicity, synchrony, and triggers of insect outbreaks across Canada. Time-series analyses reveal that broad-scale regional cycles often emerge from asynchronous local eruptions rather than from coherent climatic forcing, and that outbreak timing is inherently difficult to predict from environmental drivers alone. Recent work extends these methods to mountain pine beetle, where intensive monitoring data have allowed us to diagnose the density-dependent feedbacks underlying outbreak expansion – and, in Alberta, the engineered collapse of an ongoing outbreak through sustained green-tree removal.

This research complements the and the broader work, providing the population-dynamic foundation on which spatially explicit forecasts of insect disturbance are built.

LandWeb: historic range of variation in western boreal forests

Fri, 13 Apr 2018 20:37:16 -0600

LandWeb was initially developed with Eliot McIntire’s group at the Pacific Forestry Centre and with funding contributions through .

A summary of the results is available at .

Ongoing work explores model dynamics, sensitivity, and further refinements.

GitHub:

Simulating mountain pine beetle eastward spread

Fri, 13 Apr 2018 20:37:16 -0600

The continued eastward spread of mountain pine beetle (Dendroctonus ponderosae Hopk.; MPB) now threatens the boreal forests of eastern Alberta, Saskatchewan, and beyond. Predicting the outbreak and spread dynamics of this insect in jack pine, and to evaluate control measures to mitigate a potentially devastating loss of forest habitat and timber supply requires not only a complex understanding of the various inputs to this system and their interactions (e.g., MPB population dynamics, climate impacts, landscape features) but also the technical capacity to run large-scale spatial simulation models, and to update them quickly as new data are acquired and new models are developed.

Nonlinear density-dependent dynamics of mountain pine beetle (MPB) recruitment means that MPB spread to Saskatchewan and beyond is primarily a “numbers game”, and this has sharp consequences for pest management thresholds. The nonlinear dependency of survival rate on temperature means that eruptive potential is regulated secondarily by climate, and this has consequences for the efficacy of pest management through “direct control”. Through simulation we distinguish the conditions under which MPB spread can be significantly slowed. Preliminary results indicate that the prognosis for pest management in the lodgepole pine of the Rocky Mountains Foothills region is distinctly different that of boreal jack pine.

Simulations of MPB population recruitment and spread were developed using the (Spatial Discrete Event Simulation) platform. SpaDES facilitates a tight coupling of simulation and data within a modular framework that allows easy updates to model components. Furthermore, our development cycle follows current best practices for reproducible computing workflows and, where possible, we have followed an “Open-Access” model for software platform and simulation model development.