Estimating Primary Production of Picophytoplankton Using the Carbon-Based Ocean Productivity Model: A Preliminary Study

Liang, Yantao; Zhang, Yongyu; Wang, Nannan; Luo, Tingwei; Zhang, Yao; Rivkin, Richard B.

doi:10.3389/fmicb.2017.01926

Cited by 24 publications

(16 citation statements)

References 62 publications

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“…A comparative analysis of phytoplankton and associative nutrients from which to ascertain the critical influencing factors of phytoplankton growth and development to establish a healthy, stable aquatic ecosystem could provide a scientific basis for long‐term research. Anthropogenic nutrient loading to aquatic ecosystems can influence the structure and function of phytoplankton communities (Browning et al, ); nevertheless, phytoplankton dynamics are not only affected by nutrients but are also affected by other factors, such as strong hydrodynamic conditions (Cao, Gao, Chu, & Wang, ; Cao, Liu, Chu, & Wang, ;Cao, Wang, et al, ; Wu, Lai, et al, ), high suspended solid (SS) concentrations (Cao, Wang, et al, ; Wu, Lai, et al, ), depth (Wu et al, ), transparency (Cao, Chu, et al, ; Wu et al, ), sunlight (Wu, Lai, et al, ), water temperature (Liang et al, ), and the radiant energy (Lewis, ; Wang et al, ). Although the environmental factors mentioned above have positive or negative effects on the structure, productivity, dynamics, and succession of phytoplankton community, nutrients play a key role in the growth of phytoplankton.…”

Section: Discussionmentioning

confidence: 99%

“…Primary productivity is dependent upon phytoplankton biomass, regulated by import, export, mortality, nutrient supply, and growth rate (Cloern, Foster, & Kleckner, ), and the phytoplankton growth rate is affected by sunlight (Wu, Lai, et al, ), temperature (Liang et al, ), water level (Cao, Wang, et al, ; Pęczuła & Szczurowska, ), flow velocity (Cao, Chu, et al, ), and nutrient concentration (Wang et al, ). In this study, we discussed the effects of nutrient and phytoplankton abundance on phytoplankton primary productivity.…”

Section: Discussionmentioning

confidence: 99%

“…Primary production, which represents phytoplankton biomass and growth rates (Wang et al, ), is sensitive to environmental change (Wu, He, et al, ). It is mainly regulated by various factors that include incident irradiance (Lewis, ; Wang et al, ), ice cover (Lewis, ), nonalgal light attenuation (Deng et al, ; Wu, Lai, Zhang, Cai, & Chen, ), mixing depth (Wu et al, ), temperature (Liang et al, ), and the nutrient supply (Browning et al, ; Dou, Tang, Yang, & Wang, ; Hagstrom & Levin, ; Ke, Tan, Ma, Huang, & Wang, ; Li, Ge, Wang, Zhou, & Hu, ; Liu et al, ; Wang et al, ; Wilkerson, Dugdale, Parker, Blaser, & Pimenta, ; Yin, Liu, & Harrison, ), especially for nutrient inputs that have a significant effect on phytoplankton growth and development as well as the biogeochemical cycles of watersheds (Browning et al, ; Li et al, ; Moore et al, ; Wen et al, ). In addition, nutrient inputs, particularly nitrogen (N) and phosphorus (P), to freshwater ecosystems have continued to increase due to progressively increasing anthropogenic activities resulting from rising populations, broadening economic development, and the greater demand for food and energy production in recent years (Cao, Wang, Liao, Sun, & Huang, ; Wilkerson et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Characteristics of phytoplankton community and water net primary productivity response to the nutrient status of the Poyang Lake and Gan River, China

et al. 2019

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Phytoplankton community characteristics and associative primary productivity, which reflect the ecological and nutritional status of water, are sensitive to environmental change. Particularly, nutrient inputs have a significant effect on phytoplankton growth and development as well as the biogeochemical cycle of watersheds. We investigated the phytoplankton community and nutrient status downstream from the Gan River into Poyang Lake. On a catchment scale, the phytoplankton communities and associative primary productivity from these two water bodies differed. The Poyang Lake phytoplankton community is composed of seven phyla of algae, whereas the Gan River is composed of six, the dominant phyla of phytoplankton being Bacillariophyta and Cryptophyta in Poyang Lake and Gan River, respectively. Phytoplankton abundance and primary productivity were significantly higher in Poyang Lake. Lower nitrogen (N) and phosphorous (P) concentrations and higher carbon (C) and silicon (Si) concentrations significantly affected the phytoplankton communities and primary productivity distribution in the entire Poyang Lake Basin. In this regard, we found a significant correlation between the phytoplankton community of the Gan River and P and N, whereas N and Si primarily regulated the phytoplankton community structure of Poyang Lake. Moreover, we found a significant correlation between DTN, Si/P, DIC/P, and primary productivity in the Gan River, whereas NH4+ jointly controlled primary productivity in Poyang Lake. Furthermore, the Margalef Richness Index (0.84–2.41) can be indicative of the environmental water quality status; and we determined that the most area of Poyang Lake and Gan River both were P restriction and moderately polluted, whereas the entrance of the Gan River into Poyang Lake was seriously polluted, which confirms that the Gan River is a main and crucial source of Poyang Lake pollution. Nanjishan Nature Reserve was already slightly eutrophic due to the high nutrient content and a large number of algae in the south‐east of Poyang Lake, but the Gan River had good river fluidity, so some areas of the Gan River were oligotrophic.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characteristics of phytoplankton community and water net primary productivity response to the nutrient status of the Poyang Lake and Gan River, China

et al. 2019

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“…Phytoplankton biomass and net primary production in temperate regions change with seasons (Behrenfeld et al, 2005; Tiselius et al, 2015). In the Baltic Proper, the spring bloom is comprised of mainly diatoms and dinoflagellates, but in recent decades a trend toward decreasing diatom biomass and increasing dinoflagellate dominance has been reported (Klais et al, 2011; Wasmund et al, 2011; Legrand et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

High Frequency Multi-Year Variability in Baltic Sea Microbial Plankton Stocks and Activities

et al. 2019

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Marine bacterioplankton are essential in global nutrient cycling and organic matter turnover. Time-series analyses, often at monthly sampling frequencies, have established the paramount role of abiotic and biotic variables in structuring bacterioplankton communities and productivities. However, fine-scale seasonal microbial activities, and underlying biological principles, are not fully understood. We report results from four consecutive years of high-frequency time-series sampling in the Baltic Proper. Pronounced temporal dynamics in most investigated microbial variables were observed, including bacterial heterotrophic production, plankton biomass, extracellular enzyme activities, substrate uptake rate constants of glucose, pyruvate, acetate, amino acids, and leucine, as well as nutrient limitation bioassays. Spring blooms consisting of diatoms and dinoflagellates were followed by elevated bacterial heterotrophic production and abundances. During summer, bacterial productivity estimates increased even further, coinciding with an initial cyanobacterial bloom in early July. However, bacterial abundances only increased following a second cyanobacterial bloom, peaking in August. Uptake rate constants for the different measured carbon compounds varied seasonally and inter-annually and were highly correlated to bacterial productivity estimates, temperature, and cyanobacterial abundances. Further, we detected nutrient limitation in response to environmental conditions in a multitude of microbial variables, such as elevated productivities in nutrient bioassays, changes in enzymatic activities, or substrate preferences. Variations among biotic variables often occurred on time scales of days to a few weeks, yet often spanning several sampling occasions. Such dynamics might not have been captured by sampling at monthly intervals, as compared to more predictable transitions in abiotic variables such as temperature or nutrient concentrations. Our study indicates that high resolution analyses of microbial biomass and productivity parameters can help out in the development of biogeochemical and food web models disentangling the microbial black box.

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“…They could affect the abundance and diversity of marine organisms ( Chassot et al, 2010 ; Buchan et al, 2014 ) and biogeochemical cycling ( Behrenfeld et al, 2005 ; Richardson and Jackson, 2007 ; Lomas et al, 2014 ; Marañón, 2015 ; Leblanc et al, 2018 ). Picophytoplankton (0.2–2 or 3 μm) and nanophytoplankton (2 or 3–20 μm) are ubiquitous and principal components of phytoplankton biomass and make an important contribution to primary production in the ocean ( Detmer and Bathmann, 1997 ; Kaiser et al, 2007 ; Vaulot et al, 2008 ; Wang et al, 2010 ; Liang et al, 2017 ), and these small phytoplankton also play important roles in biogeochemical cycling such as contributing to carbon export from the surface ocean ( Richardson and Jackson, 2007 ; Tang et al, 2014 ; Leblanc et al, 2018 ). To date, most of phytoplankton study focus on the shallower waters, little is known about the phytoplankton in the deep sea especially in the hadal zone.…”

Section: Introductionmentioning

confidence: 99%

Insight Into the Pico- and Nano-Phytoplankton Communities in the Deepest Biosphere, the Mariana Trench

Guo

Liang

et al. 2018

Front. Microbiol.

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As photoautotrophs, phytoplankton are generally present in the euphotic zone of the ocean, however, recently healthy phytoplankton cells were found to be also ubiquitous in the dark deep sea, i.e., at water depths between 2000 and 4000 m. The distributions of phytoplankton communities in much deeper waters, such as the hadal zone, are unclear. In this study, the vertical distribution of the pico- and nano-phytoplankton (PN) communities from the surface to 8320 m, including the epipelagic, mesopelagic, bathypelagic, and hadal zones, were investigated via both 18S and p23S rRNA gene analysis in the Challenger Deep of the Mariana Trench. The results showed that Dinoflagellata, Chrysophyceae, Haptophyta, Chlorophyta, Prochloraceae, Pseudanabaenaceae, Synechococcaceae, and Eustigmatophyceae, etc., were the predominant PN in the Mariana Trench. Redundancy analyses revealed that depth, followed by temperature, was the most important environmental factors correlated with vertical distribution of PN community. In the hadal zone, the PN community structure was considerably different from those in the shallower zones. Some PN communities, e.g., Eustigmatophyceae and Chrysophyceae, which have the heterotrophic characteristics, were sparse in shallower waters, while they were identified with high relative abundance (94.1% and 20.1%, respectively) at the depth of 8320 m. However, the dinoflagellates and Prochloraceae Prochlorococcus were detected throughout the entire water column. We proposed that vertical sinking, heterotrophic metabolism, and/or the transition to resting stage of phytoplankton might contribute to the presence of phytoplankton in the hadal zone. This study provided insight into the PN community in the Mariana Trench, implied the significance of phytoplankton in exporting organic matters from the euphotic to the hadal zone, and also hinted the possible existence of some undetermined energy metabolism (e.g., heterotrophy) of phytoplankton making themselves adapt and survive in the hadal environment.

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Estimating Primary Production of Picophytoplankton Using the Carbon-Based Ocean Productivity Model: A Preliminary Study

Cited by 24 publications

References 62 publications

Characteristics of phytoplankton community and water net primary productivity response to the nutrient status of the Poyang Lake and Gan River, China

Characteristics of phytoplankton community and water net primary productivity response to the nutrient status of the Poyang Lake and Gan River, China

High Frequency Multi-Year Variability in Baltic Sea Microbial Plankton Stocks and Activities

Insight Into the Pico- and Nano-Phytoplankton Communities in the Deepest Biosphere, the Mariana Trench

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