An Algal Specific Growth Rate Relation Model to Assess Dynamical Brown Tide Disasters

DOI

10.2991/jrarc.2017.7.2.5How to use a DOI?

Keywords

Nutrient; temperature; coupling effect; Aureococcus anophagefferens; brown tide; hazard degree dynamic assessment

Abstract

This paper considers the coupling effect of nutrient and temperature on algal growth. We propose an algal specific growth rate relation model to assess dynamical brown tide disasters caused by Aureococcus Anophagefferens. To verify the model, we processed data from coastal waters along Qinhuangdao, China, during January 2014 to December 2014, where GIS spatial analysis tools were used to process satellite data on nutrient, chlorophyll a, and temperature, and then calculated the hazard degree of Aureococcus Anophagefferens brown tide. The results show that (1) the suggested model is in accordance with Shelford’s law of tolerance, which states that each species thrives best at a particular value of an environmental variable (the optimum) and cannot survive when the value is either too low or too high; (2) the coastal water along Qinhuangdao was more likely prone to brown tide blooms from May to July than the other months of the year in 2014; (3) the hazard degree of Aureococcus Anophagefferens in areas near the shore was higher than that in areas far from the shore in the same months. These findings would provide a technical basis to effective response to brown tide disasters in Qinhuangdao coastal waters.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Shiyong Wen
AU  - Yongfeng Zhang
AU  - Wanlei Zhang
AU  - Zizhu Wang
AU  - Ye Tian
AU  - Yongjian Liu
AU  - Jianhua Zhao
PY  - 2017
DA  - 2017/07/03
TI  - An Algal Specific Growth Rate Relation Model to Assess Dynamical Brown Tide Disasters
JO  - Journal of Risk Analysis and Crisis Response
SP  - 88
EP  - 99
VL  - 7
IS  - 2
SN  - 2210-8505
UR  - https://doi.org/10.2991/jrarc.2017.7.2.5
DO  - 10.2991/jrarc.2017.7.2.5
ID  - Wen2017
ER  -