Oral Presentation Freshwater Sciences 2023

Nutrient stoichiometry in lakes across Indiana (USA): regional patterns and relationships with phytoplankton (#337)

Lindsey M Rasnake 1 , Todd V Royer 1 , Sarah Powers 1
  1. Indiana University, Bloomington, INDIANA, United States

Stoichiometric imbalances among nitrogen (N), phosphorus (P), and silicon (Si) can contribute to the abundance of cyanobacteria, potentially leading to increased harmful algal blooms (HABs) in lakes. There is extensive knowledge about N and P-related water quality effects, but the importance of Si is often overlooked in lake monitoring programs despite the critical role of Si for diatoms. In North America, lake monitoring programs typically quantify water quality by measuring nitrogen, phosphorus, and chlorophyll-a during mid to late summer, a period when cyanobacteria are often dominant in the plankton community and dissolved Si is often low. Using data from 320 lake sampling events by the Indiana Clean Lakes Program over four summers, we examined the connections between N:P:Si ratios and phytoplankton composition across a range of land use and lake types (reservoirs and natural stratified and unstratified lakes). Our goals were 1) to assess spatial patterns in nutrient stoichiometry across Indiana lakes in relation to dominant land use, and 2) explore the extent to which mid to late summer phytoplankton communities were associated with stoichiometric conditions favoring either siliceous or non-siliceous taxa. Lakes in the northern part of the state are predominantly surrounded by agriculture, which we expected to result in high N:Si ratios. Because samples were collected during late summer, we expected cyanobacteria to be abundant, including those with the potential to cause HABs. Preliminary analysis revealed nearly 99% of sampling events indicated P limitation relative to N and Si, and 80% of lakes were Si-limited relative to N. Non-toxigenic cyanobacteria and toxigenic cyanobacteria ranged in relative abundance from <1-86% and <1-95%, respectively. In this presentation we explore how the dominant phytoplankton groups may reflect stoichiometric conditions at the time of sampling and discuss implications for interpreting state-level monitoring data.