Use statistical machine learning to detect nutrient thresholds in Microcystis blooms and microcystin management-Reference-Cited by-同舟云学术

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Use statistical machine learning to detect nutrient thresholds in Microcystis blooms and microcystin management

Published:2020-04 Issue: Volume:94 Page:101807
ISSN:1568-9883
Container-title:Harmful Algae
language:en
Short-container-title:Harmful Algae

Author:

Shan Kun,Wang Xiaoxiao,Yang Hong,Zhou Botian^ORCID,Song Lirong^ORCID,Shang Mingsheng

Funder

Chongqing Science and Technology Commission

National Key Scientific and Technological Project of China

National Basic Research Program of China

Publisher

Elsevier BV

Subject

Plant Science,Aquatic Science

Reference75 articles.

1. Bayesian calibration of mechanistic aquatic biogeochemical models and benefits for environmental management;Arhonditsis;J. Mar. Syst.,2008

2. Iron uptake and toxin synthesis in the bloom-forming Microcystis aeruginosa under iron limitation;Alexova;Environ. Microbiol.,2011

3. Land use patterns, ecoregion, and microcystin relationships in US lakes and reservoirs: a preliminary evaluation;Beaver;Harmful Algae,2014

4. Environmental factors influencing the quantitative distribution of microcystin and common potentially toxigenic cyanobacteria in US lakes and reservoirs;Beaver;Harmful Algae,2018

5. Long-term monitoring reveals carbon–nitrogen metabolism key to microcystin production in eutrophic lakes;Beversdorf;Front. Microbiol.,2015

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