10.5061/DRYAD.0RB1B
Daniel, Colin J.
University of Toronto
Ter-Mikaelian, Michael T.
Forest Research Institute
Wotton, B. Mike
University of Toronto
Rayfield, Bronwyn
Fortin, Marie-Josée
University of Toronto
Data from: Incorporating uncertainty into forest management planning:
timber harvest, wildfire and climate change in the boreal forest
Dryad
dataset
2018
stochastic
risk
Pinus banksiana
spatial
Holocene
Picea mariana
2018-06-21T00:00:00Z
2018-06-21T00:00:00Z
en
https://doi.org/10.1016/j.foreco.2017.06.039
10336752 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
In an effort to ensure the sustainability of their forests, boreal forest
managers often use forest planning models to make future projections of
timber supply and other key services, such as habitat for wildlife.
Projecting the fate of these services has proven to be challenging,
however, as major uncertainties exist regarding the principal drivers of
boreal ecosystem dynamics, including the future spatial and temporal
distribution of wildfire and timber harvesting. Existing forest planning
models are not well suited to dealing with this uncertainty because they
produce deterministic projections based on central tendencies of these
drivers. Here we present a new approach for incorporating uncertainty into
forest management planning, which we demonstrate using two landscapes in
the Canadian boreal forest. Our approach takes the assumptions contained
within the latest forest management plans for each of these landscapes,
including parameterizations of their deterministic forest planning models,
and converts these assumptions into equivalent parameterizations of a
stochastic, spatially-explicit state-and-transition simulation model
(STSM). We then use Monte Carlo simulations with the STSM to “stress-test”
the forest management plan with respect to a range of possible future
uncertainties, including uncertainties in future levels and patterns of
wildfire and timber harvest, along with the possible changes in wildfire
that might result from future climate change. Our analysis demonstrates
the importance of incorporating stochastic variability into projections of
future ecosystem condition. The STSM projections that acknowledged
variability in wildfire and timber harvest differed from the deterministic
forest planning model projections that were based solely on mean values.
Our analysis also suggests that there is an increased risk of shortfalls
in timber harvest, for both boreal landscapes, associated with future
projections for changes in wildfire due to climate change, and that
management strategies aimed at reducing the future level of timber harvest
offer an opportunity to mitigate these risks. We believe our approach
provides a new risk-based framework for incorporating uncertainty into
forest management, including the effects of climate change.
State-and-transition simulation model files for ST-Sim softwareAs outlined
in Appendix S1, this file contains all of the files required to run the
simulations in the paper using the ST-Sim
softwareforest-planning-stsm-2017-06-20.zip
Canada