About the Data -- Ecology --
Aquatic Ecological Systems -- Classification
Aquatic Ecological System Classification
The Aquatic Ecological System (AES) classification is an example of an “environmental classification” that emphasizes a stream's relationship to its physical environment. Physical environmental factors are used to develop environmental classifications because they have been shown to constrain the observed range of aquatic ecological process and aquatic biotic communities (Maxwell and others, 1995; Frissel and others, 1986; Rosgen, 1994; Argent, 2002). The physical variables used in aquatic environmental classifications are correlated with the spatial scale of the classification unit and include measures of climate, physiography, bedrock and surficial geology, channel width, depth, gradient, bed form, and bank conditions. The actual variables in the classification scheme are often dependent on the spatial scale of the classification unit.
The AES types were derived through a multi-variate cluster analysis of the abundance and distribution patterns of bedrock and surficial geology, elevation, slope, and landform types within the watersheds. Expert feedback and review of the relations between the statistical clustering and known aquatic biodiversity and environmental regimes within the watersheds contributed to the final placement of watersheds into given AES types. The environmental variables used in the classification were chosen due to their strong effect on the distribution of aquatic biota, habitats, and the form, function, and evolutionary potential of aquatic systems at watershed level scales (Maxwell and others, 1995; Higgens and others, 2005).
For example, compare a river and its contributing tributaries at low elevation on flat soft calcareous bedrock to a similar river found at high elevations and gradients on hard acidic granite. Although the two river systems potentially have similar fish species, they likely host dissimilar invertebrate, macroinvertebrate, and algal communities due to these species' more restricted tolerance for differences in chemistry, substrate, gradient, and temperature conditions. Even shared aquatic species are expected to become locally adapted to the differences in environmental regimes, habitats, and the interacting species pool present in these two different AES system types. It is hypothesized that differences in conditions such as temperature regime, seasonal hydrology patterns (snow melt vs. rain pattern), nutrient and leaf litter inputs (coniferous riparian zones vs. deciduous riparian zone vegetation), substrate/gradient, floodplain access, and interactions between the species pool can lead over time to genetic differences in the subpopulations.
Although environmental classifications often associate specific taxa with their environmental types, a true “taxonomically derived classification” of the watersheds was not undertaken in the Connecticut River Watershed because comprehensive taxonomic sample data for the entire study area was not available and TNC wished to avoid the limitations of taxonomic classifications.
Taxonomic classifications that use strictly biological data or data about one type of organism (such as fishes) to classify rarely represent the complexity inherent in aquatic communities (Higgins and others, 1998). For example, stream systems are extremely dynamic, and their biological species composition can vary widely seasonally and over short temporal scales due to changes in environmental factors. The high temporal variation makes it difficult for researchers to obtain comprehensive collection data at sampling stations or compare data collected at different times. Existing taxonomic classifications of stream communities are almost always based on data collected from wadable streams, which biases their representation of ecological diversity in terms of stream size, gradient, and scale. In addition, historic data on distribution and abundance are rarely taken into account, unknown or unsampled biodiversity cannot be accounted for in the classification framework, and genetic diversity is usually not considered in taxonomic classifications (Higgins and others, 1998).
For more information on AESs, contact
Arlene Olivero at firstname.lastname@example.org
Argent, D.G., J.A. Bishop, J.R. Stauffer, Jr., R.F. Carline, W.L. Myers. 2002. Predicting freshwater fish distributions using landscape-level variables. Fisheries Research 1411:1-16.
Frisell, C.A., W.J. Liss, C.E Warren, and M.D. Hurley. 1986. A hierarchical framework for stream habitat classification: viewing streams in a watershed context. Environmental Management 10(2): 199-214.
Higgins, J.V., M. Lammert, M.T. Bryer, M.M. DePhilip, and D.H. Grossman. 1998. Freshwater Conservation in the Great Lakes Basin: Development and Application of an Aquatic Community Classification Framework. The Nature Conservancy, Great Lakes Program, Chicago, IL.
Higgins, J.V., M. Bryer, M. Khoury, and T. Fitzhugh. 2005. A Freshwater Classification Approach for Biodiversity Conservation Planning. Conservation Biology 9:432-445.
Maxwell, J.R., C.J. Edwards, M.E. Jensen, S.J. Paustian, H. Parrott, and D.M. Hill. 1995. A Hierarchical Framework of Aquatic Ecological Units in North America (Neararctic Zone). General Technical Report NC-176. St. Paul, MN: U.S. Department of Agriculture, Forest Service.
Rosgen, D.L. 1994. A classification of natural rivers. Catena 22: 169-99.