Realized niches explain spatial gradients in seasonal abundance of phytoplankton groups in the South China Sea

Wupeng Xiao, Lei Wang, Edward Laws, Yuyuan Xie, Jixin Chen, Xin Liu, Bingzhang Chen, Bangqin Huang

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

A basic albeit elusive goal of ocean science is to predict the structure of biological communities from the multitude of environmental conditions they experience. Estimates of the realized niche-based traits (realized traits) of phytoplankton species or functional groups in temperate seas have shown that response traits can help reveal the mechanisms responsible for structuring phytoplankton communities, but such approaches have not been tested in tropical and subtropical marginal seas. Here, we used decadal-scale studies of pigment-based phytoplankton groups and environmental conditions in the South China Sea to test whether realized traits could explain the biogeographic patterns of phytoplankton variability. We estimated the mean and breadth of the phytoplankton realized niches based on responses of the group-specific phytoplankton composition to key environmental factors, and we showed that variations of major phytoplankton groups in this system can be explained by different adaptive trade-offs to constraints imposed by temperature, irradiance, and nutrient concentrations. Differences in the patterns of trade-offs clearly separated the dominant groups from one another and generated four sets of realized traits that mirrored the observed biogeographic distribution patterns. The phytoplankton realized niches and their associated traits that we characterized in the present study could help to predict responses of phytoplankton to changes in environmental conditions in the South China Sea and could be incorporated into global biogeochemical models to anticipate shifts in community structure under future climate scenarios.

Original languageEnglish
Pages (from-to)223-239
Number of pages17
JournalProgress in Oceanography
Volume162
Early online date15 Mar 2018
DOIs
Publication statusPublished - 31 Mar 2018

Keywords

  • generalized additive models
  • MaxEnt modelling
  • phytoplankton
  • realized niches
  • realized traits
  • South China Sea

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