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首页> 美国政府科技报告 >Phytoplankton Productivity Across Prairie Saline Lakes of the Great Plains (USA): A Step Toward Deciphering Patterns Through Lake Classification Models
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Phytoplankton Productivity Across Prairie Saline Lakes of the Great Plains (USA): A Step Toward Deciphering Patterns Through Lake Classification Models

机译：大平原草原盐湖的浮游植物生产力（美国）：通过湖泊分类模型解释模式的一步

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We investigated patterns of primary production across prairie saline lakes in the central and northern Great Plains of the United States. Based on comparative lake sampling in 2004, seasonal predictors of algal primary productivity were identified within subsets of similar lakes using a combination of Akaike's information criterion (AIC) and classification and regression trees (CART). These models indicated complex patterns of nutrient limitation by nitrogen (N), phosphorus (P), and iron (Fe) within different lake groups. Nutrient enrichment assays (control, + Fe, + N, + P, + N + P) were performed in spring and summer of 2006 to determine if phytoplankton in selected lakes followed predicted patterns of nutrient limitation. Both the comparative lake sampling and experimental results indicated that N limitation was widespread in these prairie lakes, with evidence for secondary P limitation in certain lakes. In the experiments, iron did not stimulate primary production. Our results suggest that given the diverse geochemical nature of these lakes, classification models that separate saline lakes into subsets may be an effective method for improving predictions of algal production.

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