|Abstract or Summary
- As global climate changes over the next century, forest productivity is expected to change as well. Using PRISM climate and productivity data measured on a grid of 3356 plots, we developed a simultaneous autoregressive (SAR) model to estimate the impacts of climate change on potential productivity of Pacific Northwest (PNW) forests of the United States. Productivity, measured by projected potential mean annual increment (PMAI) at culmination, is explained by the interaction of annual temperature, precipitation, and precipitation in excess of evapotranspiration through the growing season. By utilizing information regarding spatial error in the SAR model, the resulting spatial bias is reduced thereby improving the accuracy of the resulting maps. The model, coupled with climate change output from four generalized circulation models, was used to predict the productivity impacts of four different scenarios derived from the fourth IPCC special report on emissions, representing different future economic and environmental states of the world, viz., scenario A1B, A2, B1 (low growth, high economic development and low energy usage), and COMMIT. In these scenarios, regional average temperature is expected to increase from 0.5 to 4.5 ºC, while precipitation shows no clear trend over time. For the west and east side of the Cascade Mountains, respectively, PMAI increases: 7% and 20% under A1B scenario; 8% and 23% under scenario A2; 5% and 15% under scenario B1, and 2% and 5% under the COMMIT scenario. These projections should be viewed as potential changes in productivity, since they do not reflect the mitigating effects of any shifts in management or public policy. For managers and policy makers, the results suggest the relative magnitude of effects and the potential variability of impacts across a range of climate scenarios.