Spatial Variations of Subsurface Chlorophyll Maxima During Thermal Stratification in a Large, Deep Subtropical Reservoir-Reference-Cited by-同舟云学术

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Spatial Variations of Subsurface Chlorophyll Maxima During Thermal Stratification in a Large, Deep Subtropical Reservoir

Published:2020-01-31 Issue:2 Volume:125 Page:
ISSN:2169-8953
Container-title:Journal of Geophysical Research: Biogeosciences
language:en
Short-container-title:J. Geophys. Res. Biogeosci.

Author:

Liu Miao¹²,Zhang Yunlin¹²^ORCID,Shi Kun¹²^ORCID,Melack John³,Zhang Yibo¹²,Zhou Yongqiang¹²^ORCID,Zhu Mengyuan¹²,Zhu Guangwei¹²,Wu Zhixu⁴,Liu Mingliang⁵

Affiliation:

1. Taihu Lake Laboratory Ecosystem Research Station, State Key Laboratory of Lake Science and EnvironmentNanjing Institute of Geography and Limnology, Chinese Academy of Sciences Nanjing China

2. University of Chinese Academy Sciences Beijing China

3. Bren School of Environmental Science and ManagementUniversity of California Santa Barbara CA USA

4. Hangzhou Bureau of Ecology and Environment, Chun'An Branch Hangzhou China

5. Institute of Environmental Protection Science Hangzhou China

Funder

National Natural Science Foundation of China

Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences

Publisher

American Geophysical Union (AGU)

Subject

Paleontology,Atmospheric Science,Soil Science,Water Science and Technology,Ecology,Aquatic Science,Forestry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019JG005480

Reference53 articles.

1. Mixing and the dynamics of the deep chlorophyll maximum in Lake Tahoe1

2. The Deep Chlorophyll Maximum in Lake Superior

3. Beneath the surface: Characteristics of oceanic ecosystems under weak mixing conditions – A theoretical investigation

4. Observations of pigment and particle distributions in the western North Atlantic from an autonomous float and ocean color satellite

5. The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: an extension of the Plankton Ecology Group (PEG) model

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