Taking a macroscale perspective to improve understanding of shallow lake total phosphorus and chlorophyll a

Hydrobiologia
By: , and 

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Abstract

We conducted a macroscale study of 2210 shallow lakes (mean depth ≤ 3 m or a maximum depth ≤ 5 m) in the Upper Midwestern and Northeastern USA. We asked the following: What are the patterns and drivers of shallow lake total phosphorus (TP), chlorophyll a (CHLa), and TP–CHLa relationships at the macroscale, how do these differ from those for 4360 non-shallow lakes, and do results differ by hydrologic connectivity class? Spatial patterns and Bayesian hierarchical models indicated that shallow lakes had higher TP and CHLa than non-shallow lakes, connected shallow lakes were more productive than unconnected shallow lakes, and there was regional variation in these patterns. Important predictors of TP and CHLa included lake-specific watershed:lake area ratio, forested land use/cover, and baseflow; unconnected lakes were more difficult to predict than connected lakes; and region-specific predictors were mostly unimportant. Shallow lake TP–CHLa relationships were less steep than for non-shallow lakes and these relationships varied regionally. Our results, combined with the facts that only 23% of lakes in the study extent have depth data and that shallow and unconnected lakes are undersampled, have important implications for estimates of lake contributions to global cycles that are based mainly on large (and deeper) lakes.

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Publication type Article
Publication Subtype Journal Article
Title Taking a macroscale perspective to improve understanding of shallow lake total phosphorus and chlorophyll a
Series title Hydrobiologia
DOI 10.1007/s10750-022-04811-1
Volume 849
Publication Date February 25, 2022
Year Published 2022
Language English
Publisher Springer
Contributing office(s) Coop Res Unit Leetown
Description 15 p.
First page 3663
Last page 3677
Country United States
State Connecticut, Illinois, Indiana, Iowa, Maine, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, Wisconsin
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