영양상태지수(trophic state index)을 이용한 수체 내 식물플랑크톤 제한요인 및 seston 조성의 유추 = Using Trophic State Index ( TSI ) Values to Draw Inferences Regarding Phytoplankton Limiting Factors and Seston Composition from Routine Water Quality Monitoring Data

다국어 초록 (Multilingual Abstract)

This paper describes a simple method that uses differences among Carlson's (1977) trophic state index (TSI) values based on total phosphorus (TP), chlorophyll a (CHL) and Secchi depth (SD) to draw inferences regarding the factors that are limiting to phytoplankton growth and the composition of lake seston. Examples are provided regarding seasonal and spatial patterns in a large subtropical lake (Lake Okeechobee, Florida, USA) and inter- and intro-lake variations from a multilake data set developed from published studies. Once an investigator has collected routine water quality data and established TSI values based on TP, CHL, and SD, a number of inferences can be made.
Additional information can be provided where it also is possible to calculate a TSI based on total nitrogen (TN). Where TSI (CHL)<<TSI (TP), some factor other than P is inferred to limit algal growth. If one also finds that TSI (CHL)<<TSI (SD), this is evidence that seston is dominated by very small (abiotic) particles, and that light may be limiting. In contrast, if TSI (CHL)<<TSI (TP) but TSI (CHL)>>TSI (SD), light attenuating particles are large (large filaments or colonies of algae), and the phytoplankton may be limited by zooplankton grazing. Other limiting conditions are inferred by different relationships between the TSI values. Results of this study indicate that the analysis is quite robust, and that it generally gives good agreement with conclusions based on more direct methods (e.g., nutrient-addition bioassays, zooplankton size data, zoo-plankton removal experiments). The TSI approach, when validated periodically with these more costly and time-intensive methods, provides an effective, low cost method for tracking long-term changes in pelagic structure and function with potential value in monitoring lake ecology and responses to management.