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多参数之间的关系 PAM 测量和碳的结合,一种原位方法。

Multi-parametric relationships between PAM measurements and carbon incorporation, an in situ approach.

机构信息

Université de Caen Basse-Normandie, BIOMEA FRE3484 CNRS, Caen, France.

出版信息

PLoS One. 2012;7(7):e40284. doi: 10.1371/journal.pone.0040284. Epub 2012 Jul 20.

DOI:10.1371/journal.pone.0040284
PMID:22911698
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3401225/
Abstract

Primary production (PP) in the English Channel was measured using (13)C uptake and compared to the electron transport rate (ETR) measured using PAM (pulse amplitude modulated fluorometer). The relationship between carbon incorporation (P(obs)) and ETR was not linear but logarithmic. This result can be explained by alternative electron sinks at high irradiance which protect the phytoplankton from photoinhibition. A multi-parametric model was developed to estimate PP by ETR. This approach highlighted the importance of taking physicochemical parameters like incident light and nutrient concentrations into account. The variation in the ETR/P(obs) ratio as a function of the light revealed different trends which were characterized by three parameters (R(max), the maximum value of ETR/P(obs); E(Rmax), the light intensity at which R(max) is measured; γ the initial slope of the curve). Based on the values of these three parameters, data were divided into six groups which were highly dependent on the seasons and on the physicochemical conditions. Using the multi-parametric model which we defined by P(obs) and ETR measurements at low frequencies, the high frequency measurements of ETR enabled us to estimate the primary production capacity between November 2009 and December 2010 at high temporal and spatial scales.

摘要

采用(13)C 吸收法对英吉利海峡的初级生产力(PP)进行了测量,并与使用 PAM(脉冲振幅调制荧光计)测量的电子传递速率(ETR)进行了比较。碳掺入量(P(obs))与 ETR 之间的关系不是线性的,而是对数的。这一结果可以用高光强下替代电子汇来解释,这些电子汇可以保护浮游植物免受光抑制。开发了一种多参数模型,通过 ETR 估算 PP。这种方法强调了考虑入射光和营养浓度等物理化学参数的重要性。作为光函数的 ETR/P(obs)比值的变化揭示了不同的趋势,这些趋势由三个参数(R(max),ETR/P(obs)的最大值;E(Rmax),测量 R(max)时的光强;γ,曲线的初始斜率)来描述。基于这三个参数的值,数据被分为六组,这些组高度依赖于季节和物理化学条件。使用我们通过低频率的 P(obs)和 ETR 测量来定义的多参数模型,高频 ETR 测量使我们能够在 2009 年 11 月至 2010 年 12 月之间以高时间和空间尺度估算初级生产力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/726c/3401225/49ca441989ab/pone.0040284.g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/726c/3401225/49ca441989ab/pone.0040284.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/726c/3401225/05fd24fdf1fa/pone.0040284.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/726c/3401225/49ca441989ab/pone.0040284.g009.jpg

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