Back to CIG Back to CSES
Back to CDG

Search

View All Publications

Go To Publication by Year:

View Publications by Topic:

Agriculture

Air Quality

Aquatic Ecosystems and Fisheries

Background Papers

Climate: Atmospheric Modeling

Climate: Coupled Atmosphere-Ocean Modeling

Climate: Diagnostics

Climate: Global Climate

Climate: Ocean Modeling

Climate: PNW Climate

Coastal Ecosystems

Coastal Environments

Data Analysis and Sharing

Fact Sheets

Forecasts and Applications

Forest Ecosystems

Human Health

Hydrology and Water Resources

Integrated Assessment

Program Documents

Science Advisory Reports

Societal Dimensions

Theses and Dissertations

View Publications by Author:

Search the Publication Abstracts:


Other CSES Links:

About CSES

CSES Personnel

Data / Links

Publications

Welcome to the publications directory for the Climate Impacts Group and the Climate Dynamics Group. Please contact the web administrator for assistance with any of these publications.


View: Abstract

Spatial and temporal variability in forest growth in the Olympic Mountains, Washington: Sensitivity to climatic variability

Holman, M.L., and D.L. Peterson. 2006. Spatial and temporal variability in forest growth in the Olympic Mountains, Washington: Sensitivity to climatic variability. Canadian Journal of Forest Resources 36:92-104.

Abstract

We compared annual basal area increment (BAI) at different spatial scales among all size classes and species at diverse locations in the wet western and dry northeastern Olympic Mountains. Weak growth correlations at small spatial scales (average R = 0.084–0.406) suggest that trees are responding to local growth conditions. However, significant positive growth correlations between geographically adjacent forest types (R = 0.440–0.852) and between watersheds (R = 0.430) indicate that there is a common overarching growth-limiting factor (e.g., climate) that affects tree growth over large areas.

The Sitka spruce (Picea sitchensis (Bong.) Carrière) forest type is the most sensitive to environmental change with the highest mean sensitivity (0.345), the highest potential for annual growth change (mean BAI = 0.0047 m2), and the highest growth variability (coefficient of variation = 0.498). In addition, this forest type is most likely to exhibit extreme positive growth responses (4.2% of years have BAI values 2 standard deviations above the mean). Low elevation coniferous forests are relatively sensitive to changes in growth-limiting factors (in contrast to the traditional view) and may play an important role in storing carbon in a warmer climate.