Linking an ecosystem model and a landscape model to study forest species response to climate warming

Abstract

No single model can address forest change from single tree to regional scales. We discuss a framework linking an ecosystem process model ( linkages) with a spatial landscape model ( landis) to examine forest species responses to climate warming for a large, heterogeneous landscape in northern Wisconsin, USA. Individual species response at the ecosystem scale was simulated with linkages, which integrates soil, climate and species data, stratified by ecoregions. Individual species biomass results, simulated by linkages at year 10, were quantified using an empirical equation as species establishment coefficients (0.0–1.0). These coefficients were used to parameterize landis, thus integrating ecosystem dynamics with large-scale landscape processes such as seed dispersal and fire disturbance. Species response to climate warming at the landscape scale was simulated with landis. landis was parameterized with information derived from a species level, forest classification map, and inventory data. This incorporates spatially-explicit seed source distributions. A standard landis run with natural fire disturbance regime and current climate was conducted for 400 years. To simulate the effects of climate change, the differences in species establishment coefficients from current and warmer climates were linearly interpolated over the first 100 years assuming climate warming will occur gradually over the next century. The model was then run for another 300 years to examine the consequences after warming. Across the landscape, the decline of boreal species and the increases of temperate species were observed in the simulation. The responses of northern temperate hardwood species vary among ecoregions depending on soil nutrient and water regimes. Simulation results indicate that boreal species disappear from the landscape in 200–300 years and approximately same amount of time for a southern species to become common. Warming can accelerate the re-colonization process for current species such as found for eastern hemlock, where moisture does not become limiting. However, the re-colonization is strongly affected by available seed source explicitly described on the landscape. These phenomena cannot be simulated with most gap models, which assume a random seed rain.