A niche model to predict Microcystis bloom decline in Chaohu Lake, China

Zhicong Wang; Zhongjie Li; Dunhai Li

doi:10.1007/s00343-012-1254-0

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A niche model to predict Microcystis bloom decline in Chaohu Lake, China

Updated：2023-05-16

- A niche model to predict Microcystis bloom decline in Chaohu Lake, China
- Journal of Oceanology and Limnology Vol. 30, Issue 4, Pages: 587-594(2012)
- Affiliations：
  
  1. Institute of Hydrobiology Chinese Academy of Sciences
  2. Graduate University of Chinese Academy of Sciences
- Author bio：
- Funds：
- DOI：10.1007/s00343-012-1254-0
  CLC：
- Online First：02 July 2012，
  
  Published：2012
- Accepted：
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Wang, Z., Li, Z. & Li, D. A niche model to predict Microcystis bloom decline in Chaohu Lake, China., Chin. J. Ocean. Limnol. 30, 587–594 (2012). https://doi.org/10.1007/s00343-012-1254-0
DOI：

Wang, Z., Li, Z. & Li, D. A niche model to predict Microcystis bloom decline in Chaohu Lake, China., Chin. J. Ocean. Limnol. 30, 587–594 (2012). https://doi.org/10.1007/s00343-012-1254-0 DOI：

摘要

Abstract

Cyanobacterial blooms occur frequently in lakes due to eutrophication. Although a number of models have been proposed to forecast algal blooms

a good and applicable method is still lacking. This study explored a simple and effective mathematical-ecological model to evaluate the growth status and predict the population dynamics of Microcystis blooms. In this study

phytoplankton were collected and identified from 8 sampling sites in Chaohu Lake every month from July to October

2010. The niche breadth and niche overlap of common species were calculated using standard equations

and the potential relative growth rates of Microcystis were calculated as a weighted-value of niche overlap. In July

the potential relative growth rate was 2.79 (a.u.

arbitrary units) but then rapidly declined in the following months to −3.99 a.u. in September. A significant correlation (R =0.998

P <0.01) was found in the model between the net-increase in biomass of Microcystis in the field and the predicted values calculated by the niche model

we concluded that the niche model is suitable for forecasting the dynamics of Microcystis blooms. Redundancy analysis indicated that decreases in water temperature

dissolved oxygen and total dissolved phosphorus might be major factors underlying bloom decline. Based on the theory of community succession being caused by resource competition

the growth and decline of blooms can be predicted from a community structure. This may provide a basis for early warning and control of algal blooms.

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