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Abstract Depth regulates many attributes of aquatic ecosystems, but relatively few lakes are measured, and existing datasets are biased toward large lakes. To address this, we used a large dataset of maximum (Zmax;n = 16,831) and mean (Zmean;n = 5,881) depth observations to create new depth models, focusing on lakes < 1,000 ha. We then used the models to characterize patterns in lake basin shape and volume. We included terrain metrics, water temperature and reflectance, polygon attributes, and other predictors in a random forest model. Our final models generally outperformed existing models (Zmax; root mean square error [RMSE] = 8.0 m andZmean; RMSE = 3.0 m). Our models show that lake depth followed a Pareto distribution, with 2.8 orders of magnitude fewer lakes for an order of magnitude increase in depth. In addition, despite orders of magnitude variation in surface area, most size classes had a modal maximum depth of ~ 5 m. Concave (bowl‐shaped) lake basins represented 79% of all lakes, but lakes were more convex (funnel‐shaped) as surface area increased. Across the conterminous United States, 9.8% of all lake water was within the top meter of the water column, and 48% in the top 10 m. Excluding the Laurentian Great Lakes, we estimate the total volume in the conterminous United States is 1,057–1,294 km3, depending on whetherZmaxorZmeanwas modeled. Lake volume also exhibited substantial geographic variation, with high volumes in the upper Midwest, Northeast, and Florida and low volumes in the southwestern United States.
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First data on water mite (Acari, Hydrachnidia) assemblages of Point Rosa Marsh, Harrison Township, Michigan, USA,and their use as environmental bioindicators of aquatic health
Water mites are aquatic arachnids that have been used in Europe and Central America as bioindicators of ecological health in various freshwater ecosystems (including bogs). Water mites can be found in high densities in the Laurentian Great Lakes and adjacent habitats. Although they are abundant, water mites are generally not used in the assessment of aquatic habitats in the Great Lakes and are usually assigned to the “other” category in macroinvertebrate assessments. This is despite evidence of their utility as aquatic bioindicators. In the present study we consider water mites as bioindicators of the environmental health of Point Rosa marsh, a threatened marsh found on the US side of transboundary Lake St. Clair. The abundance of water mites in Point Rosa Marsh increased from 2017 to 2019 as lake water levels increased. Although increasing water levels in Lake St. Clair can be considered a negative event due to loss of irreplaceable coastal habitat by erosion with potential economic impacts, this present study indicates that water mite populations in Point Rosa Marsh increased during the same period (2017 to 2019). As a result of our study we: update the biodiversity of water mites from Lake St. Clair with new records compared to the last report from the lake over 45 years ago, first report on water mite assemblages at Point Rosa marsh at the Lake St. Clair Metropark on Lake St. Clair and the first demonstration of water mites used as bioindicators in the habitats of the Laurentian Great Lakes.
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- Award ID(s):
- 1735038
- PAR ID:
- 10467343
- Publisher / Repository:
- Acarologia
- Date Published:
- Journal Name:
- Acarologia
- Volume:
- 62
- Issue:
- 3
- ISSN:
- 0044-586X
- Page Range / eLocation ID:
- 653 to 665
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.24349/2m5p-c5ku
