Heterogeneity of light use efficiency in a northern Wisconsin forest: implications for modeling net primary production with remote sensing

Light use efficiency (LUE) models are often used with remotely sensed data products to estimate net primary production (NPP) from local to global scales. However, data on the variability of the LUE coefficient, ɛ, on the landscape are minimal and sometimes conflicting. The objectives of this study were to (1) quantify and compare the variability of LUE among five forest cover types: aspen, northern hardwoods, red pine, forested wetland, and upland conifer; and (2) quantify the variability of ɛ between two years, 1999 and 2000, and relate differences to environmental conditions. The study site was in a northern temperate forest in Wisconsin, USA. Northern hardwood forests, primarily consisting of sugar maple, had the highest ɛ each year followed by aspen, red pine, forested wetlands, and upland conifer. NPP was estimated using radial growth measurements and published allometric equations. Absorbed photosynthetically active radiation (APAR) was estimated optically using a Li-Cor Plant Canopy Analyzer. Growing season ɛ of all forest cover types increased significantly from 0.42 in 1999 to 0.47 (gC MJ−1) in 2000. Annual ɛ of all forest cover types increased significantly from 0.33 in 1999 to 0.36 (gC MJ−1) in 2000. Growing season and annual ɛ differed significantly (p≤0.001) among forest cover types for each year. Future research should consider variations in LUE among mixtures of many land cover types, especially forested wetlands. Results from this study show that LUE models should consider species-specific efficiency factors rather than biome-specific factors. Remote sensing-based land cover classifications should also reflect species differences for this area if the classification map is used in estimating NPP with an LUE model.