REGIONAL ESTIMATION OF NITROGEN MINERALIZATION IN FOREST ECOSYSTEMS USING GEOGRAPHIC INFORMATION SYSTEMS

Abstract

A knowledge-based geographic information system (GIS) model was developed and used to predict net nitrogen mineralization within forest ecosystems of the Midwestern Great Lakes region, USA (Illinois, Indiana, Michigan, Ohio, and Wisconsin). Climate, soil, and forest inventory data were used in conjunction with data relating initial N and lignin concentrations of leaf litter. Net N mineralization (Nnet) from leaf litter of forest ecosystems of the entire region was predicted as a function of litter quality (N:C ratio), annual actual evapotranspiration, soil texture, and litter production. Regional variation was evident in the model results: Nnet decreased from rates exceeding 120 kg·ha−1·yr−1 in the deciduous forest soils of southern Illinois, Indiana, and Ohio to 20 kg·ha−1·yr−1 in the coniferous forest soils of northern and eastern Michigan. Wisconsin’s forest soils had intermediate Nnet rates, predominantly 40–90 kg·ha−1·yr−1. The model was most sensitive to N concentration of litter, which indicated that litter quality of plant species is the most important factor controlling spatial distribution of N mineralization of ecosystems, even at the regional scale. The GIS model in this research provides a means for scaling between stand and regional scales. The model was a practical approach for estimating net N mineralization in forest ecosystems at the regional scale. Such models will become increasingly important in simulating the impacts of global environmental change on forest ecosystems.