Future forest aboveground carbon dynamics in the central United States: the importance of forest demographic processes.

The Central Hardwood Forest (CHF) in the United States is currently a major carbon sink, there are uncertainties in how long the current carbon sink will persist and if the CHF will eventually become a carbon source. We used a multi-model ensemble to investigate aboveground carbon density of the CHF from 2010 to 2300 under current climate. Simulations were done using one representative model for each of the simple, intermediate, and complex demographic approaches (ED2, LANDIS PRO, and LINKAGES, respectively). All approaches agreed that the current carbon sink would persist at least to 2100. However, carbon dynamics after current carbon sink diminishes to zero differ for different demographic modelling approaches. Both the simple and the complex demographic approaches predicted prolonged periods of relatively stable carbon densities after 2100, with minor declines, until the end of simulations in 2300. In contrast, the intermediate demographic approach predicted the CHF would become a carbon source between 2110 and 2260, followed by another carbon sink period. The disagreement between these patterns can be partly explained by differences in the capacity of models to simulate gross growth (both birth and subsequent growth) and mortality of short-lived, relatively shade-intolerant tree species.

Integration of satellite imagery and forest inventory in mapping dominant and associated species at a regional scale.

To achieve the overall objective of restoring natural environment and sustainable resource usability, each forest management practice effect needs to be predicted using a simulation model. Previous simulation efforts were typically confined to public land. Comprehensive forest management practices entail incorporating interactions between public and private land. To make inclusion of private land into management planning feasible at the regional scale, this study uses a new method of combining Forest Inventory and Analysis (FIA) data with remotely sensed forest group data to retrieve detailed species composition and age information for the Missouri Ozark Highlands. Remote sensed forest group and land form data inferred from topography were integrated to produce distinct combinations (ecotypes). Forest types and size classes were assigned to ecotypes based on their proportions in the FIA data. Then tree species and tree age determined from FIA subplots stratified by forest type and size class were assigned to pixels for the entire study area. The resulting species composition map can improve simulation model performance in that it has spatially explicit and continuous information of dominant and associated species, and tree ages that are unavailable from either satellite imagery or forest inventory data. In addition, the resulting species map revealed that public land and private land in Ozark Highlands differ in species composition and stand size. Shortleaf pine is a co-dominant species in public land, whereas it becomes a minor species in private land. Public forest is older than private forest. Both public and private forests have deviated from historical forest condition in terms of species composition. Based on possible reasons causing the deviation discussed in this study, corresponding management avenues that can assist in restoring natural environment were recommended.