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• W2116366937 abstract "With expanded interests in sustaining productivity under changing climate, management, and disturbance regimes, we sought a means of mapping the potential productivity of forests across the state of Oregon in the Pacific Northwest, USA. We chose the mapping tool 3-PG, a simplified physiologically based process model that can be driven with monthly averaged climatic data (DAYMET) and estimates of soil fertility based on soil nitrogen content. Maximum periodic mean increment (MAI, m 3 ·ha –1 ·year –1 ), a measure of the forest's productive potential, was generated by the 3-PG spatial model and mapped at 1-km 2 resolution for the most widely distributed tree species, Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco). Maximum MAI is linearly correlated with yield table site indices and therefore comparable with field-derived estimates of site indices obtained from measurement of tree heights and ages at 5263 federal forest survey points. The model predicted 100-year site index (SI) reasonably well (R 2 = 0.55; RMSE = 9.1), considering the difference in spatial resolution between the modeled (1 km 2 ) and field-measured SI (<0.1 ha) and that field plots were offset for confidentiality by 1–3 km. We created a map of the differences between modeled and field-measured SI and found that the 3000 points within ±6 m error were relatively evenly distributed across Oregon. Improving the accuracy in modeling and mapping forest productivity using 3-PG will likely require refinements in soil surveys, the quality of climatic data, the location of field plots, and the model functions and species parameters." @default.
• W2116366937 created "2016-06-24" @default.
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• W2116366937 date "2005-07-01" @default.
• W2116366937 modified "2023-10-18" @default.
• W2116366937 title "Predicting site index with a physiologically based growth model across Oregon, USA" @default.
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• W2116366937 doi "https://doi.org/10.1139/x05-089" @default.
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