Scholarlink

<p>Phytoplankton blooms, defined as a periods of high biomass, are key indicators of climate-driven ocean responses. Shifts in their timing and magnitude can substantially alter the marine ecosystem, yet the environmental regimes governing bloom development remain poorly constrained. We analyzed long-term environmental data (2003–2023) from the Central Yellow Sea (CYS) to decode the drivers of the spring phytoplankton bloom (SPB), which is defined into four developmental stages based on changes in chlorophyll-<i>a</i> (Chl-<i>a</i>). A machine-learning decision tree (DT) was employed to identify specific quantitative critical thresholds associated with each phase. Results show that the SPB initial stage represented low-light intensity in early-April. The peak stage was determined by strong-light intensity; thus, the Chl-<i>a</i> increased rapidly in mid-April. The decline stage corresponded to a high sea surface temperature (SST<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\:&gt;\)</EquationSource> </InlineEquation>14.40 °C) in May, while the termination stage indicated no SPB occurrence after late-May due to very-high SST (<InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\:&gt;\)</EquationSource> </InlineEquation>17.27 °C). We classified four SPB types from phenology and discussed the unique environmental characteristics of each type. SPB peak timing is set by the coupled physical oceanic structure (SST-mixing-light), whereas atmospheric inputs modulate bloom magnitude. The study provides a consistent baseline and a physically interpretable phenology-threshold approach for integrated interpretation of timing and conditions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Decoding environmental regimes and spring phytoplankton bloom occurrence in the central Yellow Sea

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月28日

查看全文
  • Ji-Yeon Baek,
  • Jisun Shin,
  • Hyun-Jin Yang,
  • Yingjun Zhang,
  • Chuanmin Hu,
  • Young-Heon Jo

摘要

Phytoplankton blooms, defined as a periods of high biomass, are key indicators of climate-driven ocean responses. Shifts in their timing and magnitude can substantially alter the marine ecosystem, yet the environmental regimes governing bloom development remain poorly constrained. We analyzed long-term environmental data (2003–2023) from the Central Yellow Sea (CYS) to decode the drivers of the spring phytoplankton bloom (SPB), which is defined into four developmental stages based on changes in chlorophyll-a (Chl-a). A machine-learning decision tree (DT) was employed to identify specific quantitative critical thresholds associated with each phase. Results show that the SPB initial stage represented low-light intensity in early-April. The peak stage was determined by strong-light intensity; thus, the Chl-a increased rapidly in mid-April. The decline stage corresponded to a high sea surface temperature (SST \(\:>\) 14.40 °C) in May, while the termination stage indicated no SPB occurrence after late-May due to very-high SST ( \(\:>\) 17.27 °C). We classified four SPB types from phenology and discussed the unique environmental characteristics of each type. SPB peak timing is set by the coupled physical oceanic structure (SST-mixing-light), whereas atmospheric inputs modulate bloom magnitude. The study provides a consistent baseline and a physically interpretable phenology-threshold approach for integrated interpretation of timing and conditions.