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首页> 外文期刊>Limnology >Prediction of the light attenuation coefficient through the Secchi disk depth: empirical modeling in two large Neotropical ecosystems
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Prediction of the light attenuation coefficient through the Secchi disk depth: empirical modeling in two large Neotropical ecosystems

机译：通过Secchi盘深度预测光衰减系数：两个大型新热带生态系统的经验模型

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摘要

The easiest way to evaluate water transparency is from the Secchi disk depth (SD). The behavior of radiation passing through water can also be quantified by the light attenuation coefficient (k) of photosynthetically active radiation (PAR), measured using quanta meters. Due to the high costs of quanta meters, k is usually predicted from SD. This prediction can be made using the index SD x k or using nonlinear models that correlate these variables. The aims of this study were to generate models predicting k through SD in two large Neotropical ecosystems (a reservoir and a floodplain) and to test whether 1.7, the index used worldwide, is adequate for predicting k in these ecosystems. The current paper also tested the effects of time (between seasons and among years) and space (between ecosystems and inside each ecosystem) upon such predictions. A standard 30-cm Secchi disk was used to measure SD. Simultaneously, PAR was measured at two depths to estimate k. A total data set of 2,136 measurements taken from 2001 to 2005 was used. The index generated, 2.26, was significantly different from 1.7 (t test, p < 0.01). This suggests that 1.7 is not adequate for Neotropical ecosystems. In general, both the index and the models generated differed across ecosystems and over time. In addition, the analysis showed that a nonlinear model (k = 2.00 x SD-0.76, N = 2,136) was more reliable for predictions.
机译：评估水透明度的最简单方法是使用Secchi盘深度（SD）。通过水的辐射的行为也可以通过使用光度计测量的光合有效辐射（PAR）的光衰减系数（k）来量化。由于量子计的高昂成本，通常可从SD预测k。可以使用索引SD x k或使用与这些变量相关的非线性模型进行此预测。这项研究的目的是在两个大型新热带生态系统（水库和洪泛区）中生成通过SD预测k的模型，并测试1.7（全世界使用的指数）是否足以预测这些生态系统中的k。本文还根据此类预测测试了时间（季节之间和年份之间）和空间（生态系统之间以及每个生态系统内部）的影响。使用标准的30厘米Secchi磁盘测量SD。同时，在两个深度测量PAR以估计k。使用了从2001年到2005年进行的总共2136次测量的数据集。生成的指数2.26与1.7显着不同（t检验，p <0.01）。这表明1.7对于新热带生态系统而言并不足够。总体而言，随着时间的推移，所生成的指数和模型在生态系统之间会有所不同。此外，分析表明，非线性模型（k = 2.00 x SD-0.76，N = 2,136）对于预测更为可靠。

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