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Abstract Although understanding nutrient limitation of primary productivity in lakes is among the oldest research priorities in limnology, there have been few broad‐scale studies of the characteristics of phosphorus (P)‐, nitrogen (N)‐, and co‐limited lakes and their environmental context. By analyzing 3342 US lakes with concurrent P, N, and chlorophylla(Chla) samples, we showed that US lakes are predominantly co‐limited (43%) or P‐limited (41%). Majorities of lakes were P‐limited in the Northeast, Upper Midwest, and Southeast, and co‐limitation was most prevalent in the interior and western United States. N‐limitation (16%) was more prevalent than P‐limitation in the Great Basin and Central Plains. Nutrient limitation was related to lake, watershed, and regional variables, including Chlaconcentration, watershed soil, and wet nitrate deposition. N and P concentrations interactively affected nutrient–chlorophyll relationships, which differed by nutrient limitation. Our study demonstrates the value of considering P, N, and environmental context in nutrient limitation and nutrient–chlorophyll relationships.
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Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales: Joint nutrient-productivity model
Empirical nutrient models that describe lake nutrient, productivity, and water clarity relationships among lakes play a prominent role in limnology. Landscape-based regressions are also used to understand macroscale variability of lake nutrients, clarity, and productivity (hereafter referred to as nutrient-productivity). Predictions from both models are used to inform eutrophication management globally. To date, these two classes of models are generally conducted separately, which ignores the known dependencies among nutrient-productivity variables. We present a statistical model that integrates nutrient-productivity and landscape-based regressions—where lake nutrients, productivity, and clarity variables are modeled jointly. We fitted a joint nutrient-productivity model to over 7000 lakes with three nutrients (total phosphorus, total nitrogen, nitrate concentrations), chlorophyll a concentrations, and Secchi disk depth as response variables and landscape features as predictor variables. Because lakes in different regions respond to landscape features differently, we focused our analysis on two subregions with different dominant land uses, the agricultural Midwest and the forested Northeast U.S. Predictive performance was enhanced by modeling nutrientproductivity variables jointly. We also found strong evidence that nutrient-productivity variables were coupled, and that only nitrate may be decoupled from other nutrient-productivity variables in the forested region. We speculate that these regional differences may be related to differences in the strength of biogeochemical cycles and stoichiometric controls between these regions. Jointly modeling nutrient-productivity variables in lakes effectively integrates the two dominant approaches for studying lakes nutrient-productivity relationships and provides novel insight into macroscale patterns of the coupling of nutrients, chlorophyll, and water clarity in lakes.
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- PAR ID:
- 10076361
- Date Published:
- Journal Name:
- Limnology and Oceanography
- ISSN:
- 0024-3590
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1002/lno.10944
