Trophic state index validation based on the phytoplankton functional group approach in Amazon floodplain lakes

Abstract

Many trophic indices have been constructed for temperate aquatic environments, but few have proved reliable for tropical environments. Indices constructed on the basis of nutrients may not be effective for describing the trophic state because the fractions of nitrogen and phosphorus differ in their potential to predict the nutrient limitation in tropical aquatic environments. We developed an index based on the phytoplankton Reynolds functional groups for an Amazonian floodplain lake from samples collected during 2 contrasting hydrological periods (rising and flushing) and compared it with the index initially proposed by Carlson in 1977 and further adapted to tropical environments by Toledo in 1990. The functional group and Carlson indices matched only 37% and 56% of the sample units collected during the rising and flushing periods, respectively. Our study confirms the difficulty of assessing trophic states using only phosphorus and chlorophyll a in tropical floodplain lakes. In this environment (1) nitrogen may significantly limit phytoplankton growth and (2) complex phytoplankton-nutrient relationships occur during the hydrological cycle that cannot be accounted for through a simple phosphorus and chlorophyll a formula.

Morphology-based functional groups as the best tool to characterize shallow lake-dwelling phytoplankton on an Amazonian floodplain

“…FG M are characteristic of eutrophic to hypereutrophic environments and small to medium-size water bodies (Reynolds et al, 2002;Padisák et al, 2009). FGs H1 and M were descriptors during the falling water period and reflected the conditions in the shallow eutrophic lakes on the Curuaí Floodplain (Bomfim et al, 2017; in submission).…”

Limnological perspectives on conservation of floodplain lakes in the Amazon basin

“…However, chlorophyll–nutrients relationships developed elsewhere may not apply to floodplain lakes with their large seasonal inflows and outflows. Bomfim et al (2019) provide a demonstration that phytoplankton functional groups are related to trophic status of Amazon floodplain lakes.…”

An Efficient Water Quality Prediction and Assessment Method Based on the Improved Deep Belief Network—Long Short-Term Memory Model

“…Another important index method for assessing water quality is TSI. In [22][23][24], the authors adopted the TSI based on transparency and combined it with the content of total phosphorus (TP) and chlorophyll (Chl-a) to calculate and classify the lake water quality into four basic types: lean nutrient type, medium nutrient type, eutrophic type, and excessive eutrophic type. In the future, an improved TSI index could be defined to evaluate the nutritional status of water quality more accurately.…”