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Concept
Trophic state index
Summary
The Trophic State Index (TSI) is a classification system designed to rate water bodies based on the amount of biological productivity they sustain. Although the term "trophic index" is commonly applied to lakes, any surface water body may be indexed.
The TSI of a water body is rated on a scale from zero to one hundred. Under the TSI scale, water bodies may be defined as:
oligotrophic (TSI 0–40, having the least amount of biological productivity, "good" water quality);
mesotrophic (TSI 40–60, having a moderate level of biological productivity, "fair" water quality); or
eutrophic to hypereutrophic (TSI 60–100, having the highest amount of biological productivity, "poor" water quality).
The quantities of nitrogen, phosphorus, and other biologically useful nutrients are the primary determinants of a water body's TSI. Nutrients such as nitrogen and phosphorus tend to be limiting resources in standing water bodies, so increased concentrations tend to result in increased plant growth, followed by corollary increases in subsequent trophic levels. Consequently, trophic index may sometimes be used to make a rough estimate of biological condition of water bodies.
Carlson's index was proposed by Robert Carlson in his 1977 seminal paper, "A trophic state index for lakes". It is one of the more commonly used trophic indices and is the trophic index used by the United States Environmental Protection Agency. The trophic state is defined as the total weight of biomass in a given water body at the time of measurement. Because they are of public concern, the Carlson index uses the algal biomass as
an objective classifier of a lake or other water body's trophic status. According to the US EPA, the Carlson Index should only be used with lakes that have relatively few rooted plants and non-algal turbidity sources.
Because they tend to correlate, three independent variables can be used to calculate the Carlson Index: chlorophyll pigments, total phosphorus and Secchi depth. Of these three, chlorophyll will probably yield the most accurate measures, as it is the most accurate predictor of biomass.
Official source
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