Spatial Variation in Nutrient and Water Color Effects on Lake Chlorophyll at Macroscales.
Spatial Variation in Nutrient and Water Color Effects on Lake Chlorophyll at Macroscales.
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DOI：
10.1371/journal.pone.0164592
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Wagner T
中科院分区：
文献类型：
--
作者：
Fergus CE;Finley AO;Soranno PA;Wagner T
营养-水颜色模式是一个框架，通过将湖泊初级生产力与营养物质和水色(溶解有机碳的有色成分)联系起来，来表征湖泊的营养状态。总磷(TP)是一种限制性营养物质，水色是一种强光衰减器，它们影响着湖泊的叶绿素a浓度(CHL)。但是，以前的研究表明，这些关系是高度可变的，这可能与湖泊和集水区地貌、进入系统的营养物质和碳的形式以及湖泊群落组成的差异有关。由于这些因素中的许多因素在空间上有所不同，因此湖泊营养物质和水色与CHL的关系很可能表现出空间自相关性，因此，与较远的湖泊相比，彼此较近的湖泊具有类似的关系。将这种空间相关性包括在模型中可能会改善CHL预测，并澄清营养-水色范例在分布于不同景观环境的湖泊中的应用情况。然而，很少有研究明确研究总磷和水色共同影响湖泊CHL的空间异质性。在这项研究中，我们使用空间变化系数模型(SVC)研究了800多个北温带湖泊中TP和水色与CHL的空间变化，SVC是一种稳健的统计方法，应用贝叶斯框架来探索空间变化和尺度相关的关系。我们发现，TP和水色关系在空间上是自相关的，并且与不随空间变化的模型相比，允许这些关系在空间上随单个湖泊的变化而变化改善了模型的拟合度和预测性能。不同湖泊总磷对叶绿素含量的影响程度不同，总磷含量每增加1μg/L，整个湖泊的叶绿素含量就会增加2~24μg/L。对于大多数湖泊来说，水色与叶绿素含量没有相关性，但也有一些地区的水色具有正效应，即单位水色增加导致叶绿素含量增加2μg/L，而其他地方则有负面影响，即单位水色增加导致叶绿素含量减少2μg/L。此外，对于我们研究的湖泊，捕捉TP和水色效应变化的空间尺度是不同的。在中等距离(~20公里)观察到的TP-CHL关系的变化与在区域距离(~200公里)观察到的水色-CHL关系的变化相比。这些结果表明，总磷和水色对湖泊CHL的影响存在着湖与湖之间的差异，这种变化是有空间结构的。量化这些关系中的空间结构有助于我们进一步理解这些关系在宏观尺度上的变异性，并将改进对叶绿素a的模型预测，以更好地满足湖泊管理目标。
The nutrient-water color paradigm is a framework to characterize lake trophic status by relating lake primary productivity to both nutrients and water color, the colored component of dissolved organic carbon. Total phosphorus (TP), a limiting nutrient, and water color, a strong light attenuator, influence lake chlorophyll a concentrations (CHL). But, these relationships have been shown in previous studies to be highly variable, which may be related to differences in lake and catchment geomorphology, the forms of nutrients and carbon entering the system, and lake community composition. Because many of these factors vary across space it is likely that lake nutrient and water color relationships with CHL exhibit spatial autocorrelation, such that lakes near one another have similar relationships compared to lakes further away. Including this spatial dependency in models may improve CHL predictions and clarify how well the nutrient-water color paradigm applies to lakes distributed across diverse landscape settings. However, few studies have explicitly examined spatial heterogeneity in the effects of TP and water color together on lake CHL. In this study, we examined spatial variation in TP and water color relationships with CHL in over 800 north temperate lakes using spatially-varying coefficient models (SVC), a robust statistical method that applies a Bayesian framework to explore space-varying and scale-dependent relationships. We found that TP and water color relationships were spatially autocorrelated and that allowing for these relationships to vary by individual lakes over space improved the model fit and predictive performance as compared to models that did not vary over space. The magnitudes of TP effects on CHL differed across lakes such that a 1 μg/L increase in TP resulted in increased CHL ranging from 2–24 μg/L across lake locations. Water color was not related to CHL for the majority of lakes, but there were some locations where water color had a positive effect such that a unit increase in water color resulted in a 2 μg/L increase in CHL and other locations where it had a negative effect such that a unit increase in water color resulted in a 2 μg/L decrease in CHL. In addition, the spatial scales that captured variation in TP and water color effects were different for our study lakes. Variation in TP–CHL relationships was observed at intermediate distances (~20 km) compared to variation in water color–CHL relationships that was observed at regional distances (~200 km). These results demonstrate that there are lake-to-lake differences in the effects of TP and water color on lake CHL and that this variation is spatially structured. Quantifying spatial structure in these relationships furthers our understanding of the variability in these relationships at macroscales and would improve model prediction of chlorophyll a to better meet lake management goals.
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