Journal
ECOLOGICAL MODELLING
Volume 220, Issue 15, Pages 1787-1796Publisher
ELSEVIER
DOI: 10.1016/j.ecolmodel.2009.04.029
Keywords
3-PG model; Regression-tree analysis; Climate change; US Forest Inventory and Analysis; Sitka spruce; Ponderosa pine; Western juniper; Lodgepole pine; Douglas-fir; Western hemlock
Categories
Funding
- National Aeronautics and Space Administration [NNG04GK26G]
- Canadian NSERC [336174-06]
Ask authors/readers for more resources
Although long-lived tree species experience considerable environmental variation over their life spans, their geographical distributions reflect sensitivity mainly to mean monthly climatic conditions. We introduce an approach that incorporates a physiologically based growth model to illustrate how a half-dozen tree species differ in their responses to monthly variation in four climatic-related variables: water availability, deviations from an optimum temperature, atmospheric humidity deficits, and the frequency frost. Rather than use climatic data directly to correlate with a species' distribution, we assess the relative constraints of each of the four variables as they affect predicted monthly photosynthesis for Douglas-fir, the most widely distributed species in the region. We apply an automated regression-tree analysis to create a suite of rules, which differentially rank the relative importance of the four climatic modifiers for each species, and provide a basis for predicting a species' presence or absence on 3737 distributed U.S. Forest Services' Forest Inventory and Analysis (FIA) field survey plots. Results of this generalized rule-based approach were encouraging, with weighted accuracy, which combines the prediction of both presence and absence on FIA survey plots, averaging 87%. A wider sampling of climatic conditions throughout the full range of a species' distribution should improve the basis for creating rules and the possibility of predicting future shifts in the geographic distribution of species. (C) 2009 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available