Forest Accelerated Succession Experiment
Forest Accelerated Succession Experiment
Our primary objective is to provide an improved understanding of the biological and climatic controls over carbon (C) and energy cycles during and after a successional shift from a mature aspen to a young mixed confer/deciduous forest ecosystem that will be widely distributed across the upper Great Lakes region in coming decades. In Spring 2008, we implemented the Forest Accelerated Succession ExperimenT (FASET) by stem girdling all aspen and birch (>6,700 trees, ~35% canopy LAI) within a 39 ha area. A suite of ongoing ecological and meteorological measurements conducted in treatment and control stands before (2007) and after (2008 onwards) the succession treatment are used to quantify effects of climate, species composition, and canopy structure on the forest C cycle. We have established paired treatment and control plots, and surveyed a 25 m grid system within our treatment plots, begun operation of a eddy-covariance tower within the 33 ha treatment plot, conducted intercomparisons of carbon exchange and N allocation between treatment and control plots, remote sensed forest canopy structure, and begun or continued collaborative projects with investigators utilizing this project as a platform for further studies.
Our overarching hypothesis is that forest NEP across much of the upper Great Lakes region will increase following transition from aspen dominated ecosystems to those of later-successional species with biologically and structurally more complex canopies. Specific hypotheses: a) Tree mortality will prompt a short-term reduction in NEP. A rapid recovery and stabilization of NEP above that of the control forest will be linked to the magnitude of N leaching losses and the pattern of redistribution of available N. Stands with more species and structurally diverse canopies and greater allocation of N to photosynthetic tissues will have higher NEP. b) Successional change will increase spatial variation in microclimate and nutrient distribution, both of which constrain landscape-level variability in C storage.
Study Site Overview
The UMBS Forest Ecosystem STudy (UMBS-FEST) occupies >200 ha of mostly forested landscape along the south shore of Douglas Lake, Michigan (Cheboygan County). Within this landscape, ~35 ha of forest has been experimentally manipulated to accelerate a successional change already occurring on the landscape: the senescence of early-successional aspen and birch trees, and their replacement by longer-lived oak, maple, and pine. Aspen and birch were the principal colonizers of extensive cutover and burned lands throughout the upper Great Lakes region about a century ago, and today forests dominated by these species cover >100,000 km2 in the region.
Most of our data collection occurs in permanent plots distributed among reference (unmanipulated) and treatment (accelerated succession) areas of the landscape. Plots in the treatment area are quantitatively paired with reference plots of similar tree species composition, based on a principal components analysis of leaf litterfall. See the map below, which identifies these plot pairs with common symbols.
The central, 1.1 ha plots surrounding the two eddy flux towers accommodate our most intensive measurements. Line power supports an array of electronic equipment continuously measuring air and soil climatic parameters, incoming radiation and other components of the energy budget, and water vapor and CO2 gradients extending from the forest floor up through the forest canopy. The 1.1 ha plots are also home to the most intensive biometric measurements in our studies. Within these two plots, we make measurements of tree biomass production, chemistry, and belowground processes on and adjacent to individual trees, in order to understand fine-scale spatial variation in the processes that scale up to drive stand- and landscape-level ecosystem functions like water use, C storage, and N retention. We replicate many process measurements within and between the spatially extensive 0.08 ha plots to quantify stand-level variation in biogeochemical cycling, and to understand the aggregated effects of forest succession on biogeochemistry across multiple stand types.