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Dryad

Data from: Vertical biogeography and realized niche traits of living coccolithophore community in the eastern Indian Ocean

Cite this dataset

Sun, Jun (2021). Data from: Vertical biogeography and realized niche traits of living coccolithophore community in the eastern Indian Ocean [Dataset]. Dryad. https://doi.org/10.5061/dryad.0zpc866v3

Abstract

Our investigations provided a broad view of annual-scale living coccolithophores in the quite under-sampled eastern Indian Ocean (EIO). The present study determined 7-year (2011-2018) living coccolithophore communities, as a major component in oligotrophic ecosystem, using polarized microscopic method. The ecologically important species Gephyrocapsa oceanica, Emiliania huxleyi, Algirosphaera robusta, Florisphaera profunda, Umbilicosphaera sibogae, and Umbellosphaera irregularis dominated the coccolithophore community out of 33 species. Annual mean coccolithophore abundance ranged 4306.1 - 11140.3 cells/L. Generally, coccolith detachment rates were enhanced with depth as seen from ratios of detached coccoliths and plated coccolithophores. We identified three types (upper-, middle-, lower-photic species) of vertical biogeography of coccolithophore taxa. To quantify the response of coccolithophores to environmental variables, we modeled univariate ecological realized niches of dominant species by applying ecological modelling method and acquired two niche traits: mean niche (μ) and breadth of niche (σ). The dataset can be further incorporated into climatic ecological models.

Methods

We conducted 7 cruises on the R/V “SHIYAN 1” or “SHIYAN 3” over the spring premonsoon period from Mar. 2011 to May. 2018 in the eastern Indian Ocean (EIO). Stations were designed along latitudinal or longitudinal transects (Figure 1). Seawater samples were taken from seven layers within the euphotic layer (0~5 m, 25 m, 50 m, 75 m, 100 m, 150 m, 200 m) using Niskin bottles on the CTD rosette system. Temperature (°C) and salinity data were determined from the Seabird Conductivity Temperature Depth (CTD) profiler. For nutrient measurement (only from 2015 to 2018), a total of 100 ml seawater was filtered on acid-cleaned 0.45 μm (diameter: 45 mm) acetate cellulose filters and then stored at -20°C. In the laboratory, after unfreezing samples, nutrient concentrations (NO3−, NO2−, PO43−, SiO32− and NH4+) (NH4+ data not shown here) were measured automatically using the machine (AA3, Bran+Luebbe). For chlorophyll a (chl a) collection, seawater (1000 ml) was pre-screened through 200 μm mesh for zooplankton removal, then filtered onto 25 mm Whatman GF/F filters and kept at -20°C. In 2012, 2015 and 2016, size-fractionated chl a (pico-chl a for 0.7 ~2 μm, nano-chl a for 2 ~ 20 μm, micro-chl a for 20 ~ 200 μm) samples were collected as follows: firstly, seawater samples were filtered through 20 μm mesh, subsequently filtered through 2 μm polycarbonate (PC) filter and Whatman GF/F filters with the same filtration. All chl a samples were measured using fluorescence method. We refer to the protocol of Parsons et al. (1984) to deal with chl a extraction and determination [Parsons et al., 1984].

Usage notes

The empty cell in the excel means missing value or not investigated data point.

Funding

Strategic Priority Research Program of Chinese Academy of Sciences, Award: Grant XDA20060500

National Natural Science Foundation of China, Award: 41876134

Science Fund for University Creative Research Groups in Tianjin, Award: TD12-5003

Tianjin 131 Innovation Team Program, Award: 20180314

Ministry of Education of the People's Republic of China, Award: T2014253

National Natural Science Foundation of China, Award: 41676112

National Natural Science Foundation of China, Award: 41276124

Strategic Priority Research Program of Chinese Academy of Sciences, Award: Grant XDA20060500

Science Fund for University Creative Research Groups in Tianjin, Award: TD12-5003

Tianjin 131 Innovation Team Program, Award: 20180314