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Mapping and imputing potential productivity of Pacific Northwest forests using climate variables

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https://ir.library.oregonstate.edu/concern/articles/4q77fr87x

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  • Regional estimation of potential forest productivity is important to diverse applications, including biofuels supply, carbon sequestration, and projections of forest growth. Using PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate and productivity data measured on a grid of 3356 Forest Inventory and Analysis plots in Oregon and Washington, we evaluated four possible imputation methods to estimate potential forest productivity: nearest neighbour, multiple linear regression, thin plate spline functions, and a spatial autoregressive model. Productivity, measured by potential mean annual increment at culmination, is explained by the interaction of annual temperature, precipitation, and climate moisture index. The data were randomly divided into 2237 reference plots and 1119 target plots 30 times. Each imputation method was evaluated by calculating the coefficient of determination, bias, and root mean square error of both the target and reference data set and was also tested for evidence of spatial autocorrelation. Potential forest productivity maps of culmination potential mean annual increment were produced for all Oregon and Washington timberland.
  • L'estimation regionale de la productivite forestiere potentielle est importante pour diverses applications, y compris les stocks de biocarburants, la sequestration du carbone et les projections de la croissance forestiere. A l'aide des donnees climatiques PRISM (Parameter-elevation Regressions on Independent Slopes Model) et des donnees de productivite mesurees sur une grille de 3356 placettes du programme d'analyse et d'invcntaire forestiers dans les Etats de l'Oregon et de Washington, nous evaluons quatre methodes d'imputation pour estimer la productivite forestiere potentielle :le plus proche voisin, la regression lineaire multiple, les fonctions dinterpolation spline et un modele spatial autoregressif. Mesuree par I'accroisscmeru annuel moyen potentiel (AAMP) maximum, la productivite est expliquee par I'interaction de la temperature annuelle, des precipitations et de I'indice d'humidite du climat. Les donnees ont etc repartics au hasard dans 2237 placettes de reference et 1119 placettes cibles une trentaine de fois. En plus d'etre testee pour la presence d'autocorrelation spatiale, chaque methode d'imputation a ete evaluee a l'aide du coefficient de determination, du biais et de l'erreur quadratique moyenne calculecs pour les ensembles de donnees cibles et de reference. Les cartes de productivite forestiere potentielle de I' AAMP maximum ont ete produites pour I'ensemble du territoire forestier exploitable des Etats de l'Oregon et de Washington.
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  • Latta, G., H. Temesgen, and T. M. Barrett. 2009. Mapping and imputing potential productivity of Pacific Northwest forests using climate variables. Canadian Journal of Forest Research 39: 1197-1207, doi: 10.1139/X09-046.
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  • 39
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