An Integrated Habitat Classification and Map of the Lake Erie Basin

Dynamic Habitat Classification Concept

Physical habitat can be defined as combination of a range of physical and energy characteristics that meet the needs of a species and/or biological community for a given life stage and can be delineated geographically (Mackey 2005). This definition is a fundamental underpinning of the dynamic habitat classification approach, where the intersection of appropriate physical, chemical, and biological characteristics needed to support the needs of a specific species, biological community, or ecological function can be used to identify and delineate potential “habitat”.

Dynamic Habitat Classification - Physical and chemical attributes are overlain by biological data layers to develop physical and chemical habitat affinities. Physical, chemical, and biological environmental characteristics are integrated and classified using statistical and/or geospatial analyses to generate dynamic habitat maps (or polygons) as a function of the species, community, or ecological function of interest.

Figure 1. Dynamic habitat mapping concept. Physical and chemical attributes are overlain by biological data layers to develop physical and chemical habitat affinities. Physical and chemical habitats are then integrated and classified using statistical or geospatial analyses with biological data to generate dynamic habitat maps (or polygons) as a function of the species, community, or ecological function of interest. (Scudder Mackey – University of Windsor)

Given the complex and dynamic nature of Lake Erie basin habitats, a dynamic habitat classification scheme was developed based on multiple integrated geospatial data layers that contain information on physical, chemical, and biological attributes within each of the natural environmental zones. For a given species or biological community, there are a range of physical, chemical, and biological attributes that when grouped together meet the needs of a specific organism or community for a given life stage. Areas where all of these environmental characteristics intersect can be used to identify and delineate potential habitat.

This approach allows us to identify and group physical and chemical attributes that may influence habitat distribution and function. Appropriate biological datasets and/or screens can then be compared with these attributes to develop physical-biological-habitat linkages and to assess habitat utilization.

In aquatic systems, static classification systems map individual habitats as fixed entities that do not reflect spatial and temporal variability. The dynamic habitat classification approach addresses this limitation by considering both the three-dimensional and dynamic nature of aquatic habitats. Moreover, a dynamic approach preserves the original geospatial data layers for future inquiries and allows for periodic updates as new data become available. The linkage of these geospatial data layers and associated classification schemes at regional scales creates a defacto high-level hierarchical classification scheme across the entire basin.