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Optically-derived estimates of phytoplankton size class and taxonomic group biomass in the Eastern Subarctic Pacific Ocean

机译:北极亚太平洋东部浮游植物大小类别和分类群生物量的光学估算

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摘要

We evaluate several algorithms for the estimation of phytoplankton size class (PSC) and functional type (PFT) biomass from ship-based optical measurements in the Subarctic Northeast Pacific Ocean. Using underway measurements of particulate absorption and backscatter in surface waters, we derived estimates of PSC/PFT based on chlorophyll-a concentrations (Chl-a), particulate absorption spectra and the wavelength dependence of particulate backscatter. Optically-derived [Chl-a] and phytoplankton absorption measurements were validated against discrete calibration samples, while the derived PSC/PFT estimates were validated using size-fractionated Chl-a measurements and HPLC analysis of diagnostic photosynthetic pigments (DPA). Our results showflo that PSC/PFT algorithms based on [Chl-a] and particulate absorption spectra performed significantly better than the backscatter slope approach. These two more successful algorithms yielded estimates of phytoplankton size classes that agreed well with HPLC-derived DPA estimates (RMSE = 12.9%, and 16.6%, respectively) across a range of hydrographic and productivity regimes. Moreover, the [Chl-a] algorithm produced PSC estimates that agreed well with size-fractionated [Chl-a] measurements, and estimates of the biomass of specific phytoplankton groups that were consistent with values derived from HPLC. Based on these results, we suggest that simple [Chl-a] measurements should be more fully exploited to improve the classification of phytoplankton assemblages in the Northeast Pacific Ocean.
机译:我们评估了几种算法,用于根据北极北极东北太平洋基于船舶的光学测量结果来估算浮游植物大小等级(PSC)和功能类型(PFT)生物量。使用正在进行的地表水中颗粒吸收和反向散射的测量,我们基于叶绿素a浓度(Chl-a),颗粒吸收光谱和颗粒反向散射的波长依赖性得出了PSC / PFT的估计值。光学来源的[Chl-a]和浮游植物吸收测量值针对离散的校准样品进行了验证,而派生的PSC / PFT估计值则使用大小分级的Chl-a测量值和诊断性光合色素(DPA)的HPLC分析进行了验证。我们的结果表明,基于[Chl-a]和颗粒吸收光谱的PSC / PFT算法的性能明显优于反向散射斜率方法。这两个更成功的算法在一系列水文和生产力方案中得出的浮游植物大小类别的估计值与HPLC得出的DPA估计值(RMSE分别为12.9%和16.6%)非常吻合。此外,[Chl-a]算法产生的PSC估计值与大小分级的[Chl-a]测量值非常吻合,并且特定浮游植物组的生物量估计值与HPLC值一致。根据这些结果,我们建议应更充分地利用简单的[Chl-a]测量方法来改善东北太平洋浮游植物组合的分类。

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