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Climate Impacts

ForestA major goal of Resource Monitoring and Assessment (RMA) research is to identify how inventory and monitoring data can be used to understand the effects of climate on the forest and rangeland condition.

The Pacific Northwest RMA program collects and analyzes long-term data at multiple spatial scales, ideal for predicting tree distribution, growth, and mortality in relation to regional climate gradients and potential shifts in climate. The RMA scientists also assess climate impacts to understory plant and lichen communities.

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  • Interior Alaska

    FIA has successfully annualized inventories in all states, including south coastal Alaska. However, only 16 percent (15 million acres) of Alaska’s forests statewide have been included in this effort because of the enormous logistical cost of surveying the remaining 80 million acres. A core inventory in interior Alaska would, by necessity, rely more heavily on remote-sensing techniques coupled with a subsample of ground plots. There is an FIA and NASA joint proof of concept pilot inventory scheduled in FY14 to estimate volume and forest carbon stocks in interior Alaska (Tanana) by integrating the 1/4th intensity grid with field, airborne, and satellite data.

  • Tree species distribution
    1. PNW-RMA researchers use FIA data to predict tree distribution, growth, and mortality in relation to regional climatic gradients.
    2. Multiple research projects are underway to improve our understanding of the constraints to migration in tree species in south-central and southeastern Alaska.
  • Plant associations

    Several scientists with PNW-RMA are assessing climatic impacts on forest and non-forest plant and lichen communities.

  • Tundra ecosystems
    1. PNW-RMA researchers in Alaska are evaluating how warming and snow manipulations impact tundra ecosystems, especially on the north slope of Alaska and other arctic tundra ecosystems.
    2. Other tundra ecosystem projects include characterizing environmental change in interior Alaska (1982-2012) using multi-temporal, multi-scale remote sensing data and field measurements.

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