Attributes of Upper Mississippi River System contiguous forest areas

Floodplain forests are important features of river systems as they create habitat for a variety of wildlife species as well as influence water quality by sequestering nutrients. The ecological conditions found within forested areas can vary greatly from place to place, contributing to spatial variability in species diversity, animal use of the floodplain, and other ecological functions. For this reason, it is important for managers and researchers to identify and map existing forest conditions for use in restoration practices or research studies.  

A number of forest attributes have been identified as useful in predicting the local ecological conditions found within forested areas.  For example, attributes related to the size, shape and configuration of forest patches have been linked to susceptibility to invasion by exotic species, animal and plant dispersal patterns, population distributions, and species diversity (Zuidema and others, 1996; Laurance and others, 2001; Weathers and others, 2001; Lindenmayer and Franklin 2002; Harper and others, 2005; Ramaharitra 2006). In floodplain forests, patterns of inundation have been shown to influence local soil conditions as well as plant species composition and diversity (De Jager and others, 2012). Knowing the land-use history of forest areas has also been shown to be important in understanding present day ecological conditions of forested areas (Turner and others, 2004).  

To support floodplain forest research and management actions on the Upper Mississippi River System (UMRS), we identified contiguous forested areas (i.e., areas of forest cover that were separated from each other by other land or water cover types) in the floodplain and calculated a wide range of attributes that define basic ecosystem conditions within such forested areas. The data allows users to query on a set of attributes (e.g., size, shape, inundation characteristics, etc.) to visualize the distribution of various ecological conditions. In addition, the data allows for future data analyses of relationships among different ecological conditions and other data, such as animal and plant population distributions.