|O Neill, Katherine|
Submitted to: Ecological Society of America Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: March 1, 2007
Publication Date: March 17, 2007
Citation: O Neill, K.P., Feldhake, C.M. 2007. Optimizing tree spacing and row orientation for forage production in silvopastoral systems: Insights from a spatially-explicit light capture model. In: Proceedings of the Mid-Atlantic Ecological Society of America meeting, March 17-18-2007, York, Pennsylvania. 2007 CDROM. Technical Abstract: Silvopastoral management attempts to optimize the biophysical interactions between pasture species, woody perennials, and grazing animals to increase production efficiency and sustainability of the entire system. Detailed knowledge of resource capture, allocation, and distribution on a given site is required to design patterns of tree location and position relative to landscape features to synchronize forage quantity and nutritive value with grazing animal production requirements. We evaluate the use of a spatially-explicit, geometric-optimal light capture model (tRAYci) as a tool for assessing light capture and allocation within silvopastures. tRAYci was parameterized for two tree species commonly used in agroforestry systems that have different crown architectures and growth habits: black walnut (Juglans nigra) and white pine (Pinus strobus). Light reaching the ground surface (expressed as a percentage of above canopy radiation [ACR]) was estimated at 2,500 individual points within a simulated 0.5 ha plot and sensitivity analyses conducted to determine the effects of spacing, row orientation, and foliage density on the distribution of light availability for forage production. Spacing and orientation were varied in combination to maximize light availability within the plot in the range of 40-70% ACR, a range considered suitable for forage production. Results from this sensitivity analysis indicate that individual-based light capture models offer the potential for designing systems to optimize light allocation for tree and forage components of silvopastures by quantifying patchiness resulting from different tree distribution patterns.