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Influence of climate variability on the productivity and distribution of Ponderosa Pine ecosystems in the Pacific Northwest: Combination of a process-based modela nd a 102-year high resolution climate data set.

Objective

1. To assess the influence of climate variability on the annual productivity of Ponderosa pine ecosystems in the Pacific Northwest over the past 100 years

2. To explain how climate variability limits the current distribution of ponderosa pine in the region.

Approach

We propose first to test a physiologically-based mechanistic model, 3-PGS, that uses satellite-derived data to assess canopy leaf area indices (LAI), to predict current growth and climatic limitations of ponderosa pine across a steep gradient in precipitation that runs along the eastern boundary of the Cascade Mountains in Oregon and Washington. We will then use a form of the model (3-PG) that simulates net ecosystem productivity (NEP = net carbon uptake from the atmosphere), maximum LAI and growth using a 102-year synthesized climatic data set provided by the Oregon Climate Service. The climate data set was produced from station data and gridded at 4 km using a well-known model, PRISM, that accounts for complex effects, including abrupt rain shadows to the lee of mountains. We will estimate additional climate variables necessary to drive the model, using tested methods, and sample down to 1 km grid scale. This sophistication in topographic analysis is critical in a region where precipitation decreases from >1000 to < 300 mm in 50 km. Both forms of the mechanistic physiological model have already been tested at our AmeriFlux ponderosa pine site, and across southern Oregon. Prior to running the model across the region, we will compare the estimated climate with data sets we acquired from our pine sites over the past 10 years.