Population dynamics of harmful algal blooms in Lake Champlain: A tale of two phases

Ecoinformatics, National Ecological Observatory Network, Boulder, CO, USA
Department of Biology, University of Vermont, Burlington, VT, USA
Natural Resources, University of Vermont, Burlington, VT, USA
College of Natural Resources, North Carolina State University, Raleigh, NC, USA
DOI
10.7287/peerj.preprints.75v2
Subject Areas
Biodiversity, Ecology, Environmental Sciences, Mathematical Biology, Zoology
Keywords
density dependence, time series, population dynamics, Cyanobacteria, harmful algal blooms.
Copyright
© 2013 Hart et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Cite this article
Hart E, Gotelli N, Gorney R, Watzin M. 2013. Population dynamics of harmful algal blooms in Lake Champlain: A tale of two phases. PeerJ PrePrints 1:e75v2

Abstract

Understanding the dynamics of harmful algal blooms (HABs) in lakes can inform management strategies to reduce their economic and health impacts. Previous studies have analyzed spatially replicated samples from a single time or have fit phenomenological models to time series data. We fit mechanistic population models to test the effects of critical nutrient concentrations and the density of potential algal competitors on population growth parameters in HABs in Lake Champlain, U.S.A. We fit models to five years (2003-2006, 2008) of weekly cyanobacteria counts. Plankton dynamics exhibited two phases of population growth: an initial “bloom phase” of rapid population growth and a subsequent “post-bloom phase” of stochastic decline. Population growth rates in the bloom phase were strongly density dependent and increased with increasing TN:TP ratios. The post-bloom phase was largely stochastic and was not obviously related to nutrient concentrations. Because TN:TP was important only in the initial phase of population growth, correlative analyses of the relationship between cyanobacteria blooms and nutrient concentrations may be especially sensitive to when snapshot data are collected. Limiting nutrient inputs early in the season could be an effective management strategy for suppressing or reducing the bloom phase of cyanobacteria population growth.

Author Comment

This is version 2 of the manuscript after taking into account comments from readers. Plan is now to submit to peerJ

Supplemental Information

Supplemental Information 1

DOI: 10.7287/peerj.preprints.75v2/supp-1