Long-term vegetation monitoring in experimental forests: Example of a functional research network in the Pacific Northwest, USA

Background/Question/Methods

Thornton T. Munger, the first Pacific Northwest Research Station Director for the Forest Service, established the first long-term forest research plots in the Pacific Northwest USA in 1910 to better understand growth and timber yield of Douglas-fir (Pseudotsuga menziesii) trees.  The location of these plots would eventually become part of the Wind River Experimental Forest, established in 1934.  Today, the network of long-term vegetation monitoring plots has expanded to 137 sites, including 4 experimental forests (Cascade Head, H. J. Andrews, Pringle Falls, Wind River), 15 Research Natural Areas, one national monument (Mount St. Helens), and two national parks (Olympic and Mount Rainier). Data from these plots have made significant and wide-ranging contributions to science and land manage­ment, including quantifying regional tim­ber growth and yield, defining old-growth forest for inventory and planning, under­standing habitat needs for threatened and endangered species, and validating com­puter simulation models of forest dynamics and processes including assessing effects of wildfire, logging, and climate change.

Results/Conclusions

Maintaining a long-term monitoring program that spans both the lifecycle of forests and generations of investigators can be challenging.  Key to the success of this network include: (1) measures of vegetation that are basic enough to allow flexibility of use for diverse science inquiry; (2) capacity for data collection protocols to evolve as our ecological understanding evolves, without losing the potential value of earlier data;  (3) intergenerational training of new leaders that help “carry the torch” over time; (4) diverse sources of funding to help get through lean economic years; (5) continuous building and strengthening of partnerships among scientists, forests, agencies, and other ecological networks; and (6) use of a formal standardized system for data management and archiving. Future success may also depend on institutionalizing this network in ways that can further increase and strengthen important linkages with the broader science community so that this network continues to provide relevant and useful science information for generations to come.