Title
Identifying the factors determining blooms of cyanobacteria in a set of shallow lakes.
Abstract
There is a strong interest in developing a capacity to predict the occurrence of cyanobacteria blooms in lakes and to identify the measures to be taken to reduce water quality problems associated with the occurrence of potentially harmful taxa. Here we conducted a weekly to bi-weekly monitoring program on five shallow eutrophic lakes during two years, with the aim of gathering data on total cyanobacterial abundance, as estimated from marker pigments determined by HPLC analysis of phytoplankton extracts. We also determined bloom composition and measured weather and limnological variables. The most frequently identified taxa were Aphanizomenon flos-aquae, Microcystis aeruginosa, Planktothrix agardhii and Anabaena spp. We used the data base composed of a total of 306 observations and an adaptive regression trees method, the boosted regression tree (BRT), to develop predictive models of bloom occurrence and composition, based on environmental conditions. Data processing with BRT enabled the design of satisfactory prediction models of cyanobacterial abundance and of the occurrence of the main taxa. Phosphorus (total and soluble reactive phosphate), dissolved inorganic nitrogen, epilimnion temperature, photoperiod and euphotic depth were among the best predictive variables, contributing for at least 10% in the models, and their relative contribution varied in accordance with the ecological traits of the taxa considered. Meteorological factors (wind, rainfall, surface irradiance) had a significant role in species selection. Such results may contribute to designing measures for bloom management in shallow lakes.
Year
DOI
Venue
2016
10.1016/j.ecoinf.2016.05.003
Ecological Informatics
Keywords
Field
DocType
Eutrophication,Modelling,Boosted regression trees,Lake management
Algal bloom,Phytoplankton,Microcystis,Ecology,Bloom,Computer science,Epilimnion,Microcystis aeruginosa,Eutrophication,Aphanizomenon
Journal
Volume
ISSN
Citations 
34
1574-9541
0
PageRank 
References 
Authors
0.34
0
11
Name
Order
Citations
PageRank
J.-P. Descy100.34
Fabien Leprieur220.74
S. Pirlot300.34
B. Leporcq400.34
J. Van Wichelen500.34
A. Peretyatko600.34
S. Teissier700.34
G. A. Codd800.34
Ludwig Triest921.07
W. Vyverman1000.34
A. Wilmotte1100.34