紊流介導垂直營養鹽通量對臺灣東部黑潮區域植物性浮游生物體型大小結構的影響

Abstract

位於臺灣東部的黑潮海域中，由於海水表層水中營養鹽枯竭，浮游植物的生長必須依賴於水流擾動將深層營養鹽運送到表層。因此，垂直營養鹽通量對於貧營養鹽海域的浮游植物生態至關重要。本研究探討紊流介導的垂直營養鹽通量對浮游植物個體大小尺寸結構的影響，並將重點放在不受海底地形干擾和沿岸影響的測站。在2018年至2021年間的四個航次中，在臺灣東部的8個測站取得了32筆樣本。進行了浮游植物和營養鹽（溶解性無機氮（DIN）、磷酸鹽（PO_4））濃度的現場採樣，並在不同深度（5、10、30、50、100、150米）進行了測量。基於營養鹽測量的垂直剖面和CTD收集的水文資料，計算了每個深度的垂直營養鹽通量。為了定量浮游植物的尺寸結構，利用 FlowCAM^® 對3至200微米範圍內的浮游植物的影像進行分析，建立了歸一化生物尺寸頻譜（NBSS），並使用線性回歸分析浮游植物歸一化尺寸頻譜的斜率（NBSS-Slope）和擬合度（NBSS-r^2）如何受垂直紊流擴散率和垂直營養鹽通量的影響。 對於浮游植物NBSS斜率，在冷季和暖季以及不分季節的分析中都沒有顯著的相關性，這表明NBSS斜率對營養鹽通量變化的反應不明顯，模型的解釋能力極低。對於NBSS的擬合度，在冷季時，PO_4通量解釋的比DIN通量更多，而在暖季沒有顯著關係。在不分季節的分析中，營養鹽通量解釋的比垂直紊流擴散率更多且呈現顯著關係。這說明NBSS擬合度的高低，對垂直營養鹽通量的變化更具反應性，相較於垂直紊流擴散度來說還高。總結來說，垂直營養鹽通量與浮游植物NBSS之間的關係很弱。這可能歸因於營養鹽對浮游植物生長影響的時間滯後效應，很難通過同時採集的營養鹽通量和浮游植物樣本得到準確解釋。因此，在未來研究上，若利用詳細的時間序列數據進行研究可能會提供更精確的分析結果。

In the Kuroshio east of Taiwan, the nutrients in the surface layer of seawater are generally depleted, and the growth of phytoplankton relies on turbulence to transport subsurface nutrients to the surface layer. That is, vertical nutrient flux is crucial for phytoplankton production and ecology in this oligotrophic ocean. In this research, I investigate the impact of turbulence induced vertical nutrient flux on phytoplankton size structure, focusing on the selected stations in the open ocean void of topographic interference and coastal influences. Thirty-two samples from 8 stations in the Kuroshio east of Taiwan were sampled during four cruises between 2018 and 2021: May 2018, Nov 2018, Jul 2019, and Oct 2021. Field sampling for phytoplankton and nutrient (DIN, PO_4) concentrations at various depths (5, 10, 30, 50, 100, 150 meters) were conducted. Based on the vertical profile of nutrient measurements and hydrological data collected by the CTD, I calculated vertical nutrient flux (F = −k_ρ ∂C/∂z) at each depth, in which k_ρ is vertical turbulent diffusivity. To determine the size structure of phytoplankton community, I constructed the Normalized Biovolume Size Spectrum (NBSS) from the images analyses of nano- and micro- phytoplankton within the size range of 3 to 200 μm obtained by FlowCAM^®. The NBSS was calculated as logarithmically transformed B_s⁄∆s=aS^b. Using linear regression, I examined how the slope and r^2 of phytoplankton NBSS was affected by vertical turbulent diffusivity and vertical nutrient flux. For NBSS-slopes, I found no significant correlation in both the warm and cold season, as well as in the analysis pooling both seasons, indicating that the response of the NBSS-slope to nutrient flux variations was not evident and the model had low explanatory power. For the goodness of NBSS fit, PO_4 flux explained more variations compared to DIN flux in the cold season, while no significant relationship was found in the warm season. In the analysis pooling both seasons, nutrient flux explained more variations compared to vertical turbulent diffusivity. This indicates that the goodness of NBSS fit was slightly more responsive to changes in vertical nutrient flux compared to vertical turbulent diffusivity. In summary, the relationships between vertical nutrient flux and phytoplankton NBSS are weak. This might be attributed to the time-lag effect of nutrients on phytoplankton growth that is difficult to be revealed by the simultaneous sampling of nutrient flux and phytoplankton. Future studies utilizing detailed time-series data may offer a more precise analysis.