Bioclimate envelope model predictions for natural resource management: dealing with uncertainty
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Date
2010
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of Applied Ecology
Abstract
Bioclimate envelope models are widely used to predict the potential distribution of species under
climate change, but they are conceptually also suitable to match policies and practices to anticipated
or observed climate change, for example through species choice in reforestation. Projections of bioclimate
envelope models, however, come with large uncertainties due to different climate change
scenarios, modelling methods and other factors.
2. In this paper we present a novel approach to evaluate uncertainty in model-based recommendations
for natural resource management. Rather than evaluating variability in modelling results as a
whole, we extract a particular statistic of interest from multiple model runs, e.g. species suitability
for a particular reforestation site. Then, this statistic is subjected to analysis of variance, aiming to
narrow the range of projections that practitioners need to consider.
3. In four case studies for western Canada we evaluate five sources of uncertainty with two to five
treatment levels, including modelling methods, interpolation type for climate data, inclusion of
topo-edaphic variables, choice of general circulation models, and choice of emission scenarios. As
dependent variables, we evaluate changes to tree species habitat and ecosystem distributions under
144 treatment combinations.
4. For these case studies, we find that the inclusion of topo-edaphic variables as predictors reduces
projected habitat shifts by a quarter, and general circulation models had major main effects. Our
contrasting modelling approaches primarily contributed to uncertainty through interaction terms
with climate change predictions, i.e. the methods behaved differently for particular climate change
scenarios (e.g. warm&moist scenarios) but similar for others.
5. Synthesis and applications. Partitioning of variance components helps with the interpretation of
modelling results and reveals how models can most efficiently be improved. Quantifying variance
components for main effects and interactions among sources of uncertainty also offers researchers
the opportunity to filter out biologically and statistically unreasonable modelling results, providing
practitioners with an improved range of predictions for climate-informed natural resource
management.
Description
Keywords
Climate change, Species distribution models, Trembling aspen
Citation
Mbogga, M. S., Wang, X., & Hamann, A. (2010). Bioclimate envelope model predictions for natural resource management: dealing with uncertainty. Journal of Applied Ecology, 47(4), 731-740. doi: 10.1111/j.1365-2664.2010.01830.x