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Small lakes dominate a random sample of regional lake characteristics
Author(s) -
HANSON PAUL C.,
CARPENTER STEPHEN R.,
CARDILLE JEFFREY A.,
COE MICHAEL T.,
WINSLOW LUKE A.
Publication year - 2007
Publication title -
freshwater biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.297
H-Index - 156
eISSN - 1365-2427
pISSN - 0046-5070
DOI - 10.1111/j.1365-2427.2007.01730.x
Subject(s) - dissolved organic carbon , environmental science , hydrology (agriculture) , surface water , physical geography , ecology , geography , geology , biology , geotechnical engineering , environmental engineering
Summary 1. Lakes are a prominent feature of the Northern Highland Lake District (NHLD) of Wisconsin, covering 13% of the landscape. Summarising the physical, chemical, or biological nature of NHLD lakes at a regional scale requires a representative sample of the full size distributions of lakes. In this study, we selected at random 168 lakes from the full size distribution of lakes in the NHLD and sampled each lake for a broad suite of limnological variables. 2. Most lakes were small. The median lake area was 1.1 ha, however, half of the surface area of water was in a relatively small number of lakes larger than 162 ha. Smaller lakes tended to be low in dissolved inorganic carbon (DIC) and high in dissolved organic carbon (DOC). Inclusion of small lakes (<4 ha) in the survey resulted in an acid neutralising capacity (ANC) median (76.5 μ Eq L −1 ) much lower than previous estimates, and a DOC median (10.1 mg L −1 ) about 50% higher than it would have been without the smaller lakes. Unlike DOC, total P tended to be evenly distributed across lake sizes. 3. The implications of these findings are that regional summaries of lake characteristics for the NHLD are influenced by the inclusion of small lakes in the sample, even though most of the water surface area is in lakes larger than 162 ha. Excluding small lakes introduces bias in the estimates of organic carbon and inorganic carbon values, for example. Similar biases may be introduced for lake characteristics at the global scale if small lakes are not sampled, because the size distribution of lakes globally is dominated in number by small lakes.