|Regionalization at the BNZ|
|Region Number||Area (hectares)||Predicted Mean Annual Temperature (oC)||Predicted Mean Annual Precipitation (mm)||Region Number||Area (hectares)||Predicted Mean Annual Temperature (oC)||Predicted Mean Annual Precipitation (mm)|
Vegetation zones have been developed by Gallant et al. (1995) for the state. Flemming (pers. comm.) has also developed vegetation zones based on bimonthly NDVI data sets for 1991. Because the zones developed by Flemming were based on NDVI data they do not represent standard divisions in the vegetation similar to the zones presented by Gallant et al. (1995). This may be the result of the difference between pixel size and community size on the landscape. For example the vegetation zone in which the BNZ LTER site is located has been describe as containing a large number of vegetation communities. The two primary classifications are called a Tall and Low Shrub/Spruce Woodland and an Open and Closed Spruce Forest. Both of these classes contain a large range of community types at smaller scales. This is true for the BCEF experimental forest and surrounding area.
The current regionalization research is attempting to define even in greater detail and accuracy the zones of Alaska, and to develop a basic understanding of process information that can be applied at all geographic levels of the classified zones.
One of our components in regionalization research is the development of a forest ecosystem model totally within a GIS (ARC/INFO) system. By programming the model using GRID in ARC/INFO, every grid cell is modeled. If the grid cell size is one hectare and you are modeling an area equal to 10,000 ha in size you have in essence run the model 10,000 times for that area.
As with all models various components of this one are still in a development stage\; but it can be briefly described. The forest ecosystem dynamics model is based on the nitrogen productivity concept for forest growth\; litterfall quality and microbial efficiency for forest floor decomposition, and forest regeneration based on a tree\'s sprouting or seed production capability. Climate and ecosystem level disturbances will be handled as restricted stochastic processes. The restriction will be based on known state factor relationships like climate and vegetation. The state factors are used to describe a broad scale classification of the landscape to define basic limitations for the randomly derived driving variables used in the model.
This study investigates the development of successional white spruce (Picea glauca (Moench) Voss) stands on the Tanana River floodplain in interior Alaska. Global climate change, predicted to be greatest at high latitudes, may have a major effect on landscape structure in boreal ecosystems through changes in physical controls over landscape processes. Alluvial floodplains are especially sensitive to climate parameters through modified patterns in response to changes in the hydrologic regime. Some of the most highly productive boreal forests occur on river floodplains such as along the Tanana River in interior Alaska. The vegetation consists of a mosaic of patches in various stages of succession. This landscape pattern reflects past and present disturbance history, and is closely linked to fluvial processes\; many of the fluvial geomorphic and successional processes occur on the same time scale. I examine fluvial controls over vegetation colonization and white spruce establishment at plot, stand, and landscape scales.
The temporal patterns of white spruce seedling establishment are described from permanent plot data and growth patterns of seedlings and saplings. Effects of flood events on seedling establishment and mortality are examined. Age structure of mature white spruce stands is determined, and spatial variability in age structure through succession is described. Hypotheses relating spatial variability in age structure to fluvial processes are tested. Relationships between river discharge rates and the development of depositional terraces suitable for plant colonization are examined. The age structure distribution of the landscape mosaic is constructed from historical aerial photography and estimated from tree-ring counts. A model developed from dendrochronological analysis of white spruce tree cores reconstructs the river discharge history.
Hammond, T. and J. Yarie. 1996. Spatial prediction of climatic state factor regions in Alaska. Ecoscience (In Press).