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A fuzzy logic decision support model for climate-driven biomass loss risk in western Oregon and Washington

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Sheehan T, Bachelet D (2019) A fuzzy logic decision support model for climate-driven biomass loss risk in western Oregon and Washington. PLoS ONE 14(10): e0222051. https://doi.org/10.1371/journal.pone.0222051

Summary

Dynamic global vegetation model (DGVM) projections are often put forth to aid resource managers in climate change-related decision making. However, interpreting model results and understanding their uncertainty can be difficult. Sources of uncertainty include embedded assumptions about atmospheric CO2 levels, uncertain climate projections driving DGVMs, and DGVM algorithm selection. For western Oregon and Washington, we implemented an Environmental Evaluation Modeling System (EEMS) decision support model using MC2 DGVM results to characterize biomass loss risk. MC2 results were driven by climate projections from 20 General Circulation Models (GCMs) and Earth System Models (ESMs), under Representative Concentration Pathways (RCPs) 4.5 [...]

Contacts

Author :
Tim Sheehan, Dominique Bachelet
Funding Agency :
Northwest CASC

Attached Files

Communities

  • National and Regional Climate Adaptation Science Centers
  • Northwest CASC

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citationTypeJournal Article
journalPublic Library of Science ONE (PLoS ONE)

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