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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #228544
Title: A multi-species, process based vegetation simulation module to simulate successional forest regrowth after forest disturbance in daily time step hydrological transport models

Author
item MACDONALD, J - LAKEHEAD UNIVERSITY
item Kiniry, James
item PUTZ, GORDON - UNIV SASKATCHEWAN
item PREPAS, ELLIE - UNIV SASKATCHEWAN

Submitted to: Journal of Environmental Engineering and Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/13/2008
Publication Date: 7/11/2008
Citation: Macdonald, J.D., Kiniry, J.R., Putz, G., Prepas, E.E. 2008. A multi-species, process based vegetation simulation module to simulate successional forest regrowth after forest disturbance in daily time step hydrological transport models. Journal of Environmental Engineering and Science. 7:S127-S143.

Interpretive Summary: SWAT is a hydrology model often used to simulate various landscapes. When applying to forests, more detail is needed for the complex plant communities often present. We modified the growth model in SWAT to provide a more precise description of forest growth dynamics, by integrating a multi-species growth model, ALMANACBF. We collected field data to develop parameters for the multi-species growth model. The biomass, leaf area index and light interception was measured on hummock tops and in depressions of three sites that differed in pre-harvest forest stand composition. Our results demonstrate that on the hummocky terrain of the Boreal Plain, there are important variations in vegetation recovery after disturbance among different ecosites and among landscape positions. LIDAR imagery and targeted sampling of obvious landscape variations was effective in correcting vegetation cover estimates to account for differences in cover observed between depressions and hummocks in a variety of sites.

Technical Abstract: To accurately simulate watershed hydrology after forest harvest using SWAT, it is important to understand the factors that potentially make certain sites more sensitive to disturbance. The growth model in SWAT has been modified to provide a more precise description of forest growth dynamics, by integrating a multi-species growth model, ALMANACBF. We observed significant differences in percent cover of vegetation, biomass and leaf area index among sites representing differing pre-harvest forest stands and associated with topography, between hummocks and depressions. Our results demonstrate that on the hummocky terrain of the Boreal Plain, there are important variations in vegetation recovery after disturbance among different ecosites and among landscape positions. LIDAR imagery and targeted sampling of obvious landscape variations was effective in correcting vegetation cover estimates to account for differences in cover observed between depressions and hummocks in a variety of sites.