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ARS Home » Southeast Area » Booneville, Arkansas » Dale Bumpers Small Farms Research Center » Research » Publications at this Location » Publication #123708


item Ares, Adrian
item Brauer, David

Submitted to: North American Agroforestry Conference
Publication Type: Abstract Only
Publication Acceptance Date: 6/1/2001
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Farm-level simulators such as the Agroforestry Estate Model use as inputs either yield tables developed for a particular system or outputs from forest modeling tools. Forest models rely upon a set of assumptions on site index, stem diameter (DBH) distribution, wood production and tree mortality, which may or may not apply to agroforestry systems. Differences may arise because of the effects on tree growth and understory yield of different spacings and configurations, fertilizer and grazing regimes, and tree-understory relationships as well. We examined data from published or ongoing field trials to determine trends in tree growth and understory yields in silvopastoral systems with southern pines in the United States. Tree DBH and height were generally higher in systems with improved pastures than in those with spontaneous grasses. Effects of understory characteristics were more marked on DBH than on height and, therefore, DBH-height relationships differed among systems. Sigmoidal models predicted that tree height will peak at different age depending on tree spacing. These changes may affect the accuracy of site indices and wood yield predictions generated by forest models. Fertilizer regimes and tree spacing also affected tree growth but grazing usually did not. Stem diameter distributions were similar in unthinned systems with different configurations and Gaussian functions fitted them well. Forage fields or livestock gains tend to be relatively constant during early stages of the system and decrease lately. The relationship between understory growth and basal area/canopy cover is forage dependent and could be fitted with segmented regression models. Additional data will allow to refine agroforestry economic analysis for the United States.