Response of lake metabolism to catchment inputs inferred using high‐frequency lake and stream data from across the northern hemisphere

Author:

Corman Jessica R.1ORCID,Zwart Jacob A.2ORCID,Klug Jennifer3ORCID,Bruesewitz Denise A.4ORCID,de Eyto Elvira5ORCID,Klaus Marcus6ORCID,Knoll Lesley B.7ORCID,Rusak James A.89ORCID,Vanni Michael J.7ORCID,Alfonso María Belén10ORCID,Fernandez Rocio Luz11ORCID,Yao Huaxia12ORCID,Austnes Kari13ORCID,Couture Raoul‐Marie14ORCID,de Wit Heleen A.13ORCID,Karlsson Jan15ORCID,Laas Alo16ORCID

Affiliation:

1. School of Natural Resources University of Nebraska–Lincoln Lincoln Nebraska USA

2. Integrated Information Dissemination Division U.S. Geological Survey San Francisco California USA

3. Biology Department Fairfield University Fairfield Connecticut USA

4. Environmental Studies Department Colby College Waterville Maine USA

5. Fisheries Ecosystems Advisory Service Marine Institute Newport, Co. Mayo Ireland

6. Department of Forest Ecology and Management Swedish University of Agricultural Sciences Umeå Sweden

7. Department of Biology Miami University Oxford Ohio USA

8. Dorset Environmental Science Centre, Ontario Ministry of the Environment, Conservation and Parks Dorset Ontario Canada

9. Biology Department Queen's University Kingston Ontario Canada

10. Research Institute for Applied Mechanics Kyushu University Kasuga Fukuoka Prefecture Japan

11. National Scientific and Technical Research Council (CONICET) Santa Fe Argentina

12. Inland Waters Unit, Ontario Ministry of the Environment, Conservation and Parks Dorset Ontario Canada

13. Section for Catchment Biogeochemistry Norwegian Institute for Water Research Oslo Norway

14. Department of Chemistry Centre d'Études Nordiques, Université Laval Quebec Quebec Canada

15. Department of Ecology and Environmental Science Umeå University Umeå Sweden

16. Institute of Agricultural and Environmental Sciences Estonian University of Life Sciences Tartu Estonia

Abstract

AbstractIn lakes, the rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) are often controlled by resource availability. Herein, we explore how catchment vs. within lake predictors of metabolism compare using data from 16 lakes spanning 39°N to 64°N, a range of inflowing streams, and trophic status. For each lake, we combined stream loads of dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) with lake DOC, TN, and TP concentrations and high frequency in situ monitoring of dissolved oxygen. We found that stream load stoichiometry indicated lake stoichiometry for C : N and C : P (r2 = 0.74 and r2 = 0.84, respectively), but not for N : P (r2 = 0.04). As we found a strong positive correlation between TN and TP, we only used TP in our statistical models. For the catchment model, GPP and R were best predicted by DOC load, TP load, and load N : P (R2 = 0.85 and R2 = 0.82, respectively). For the lake model, GPP and R were best predicted by TP concentrations (R2 = 0.86 and R2 = 0.67, respectively). The inclusion of N : P in the catchment model, but not the lake model, suggests that both N and P regulate metabolism and that organisms may be responding more strongly to catchment inputs than lake resources. Our models predicted NEP poorly, though it is unclear why. Overall, our work stresses the importance of characterizing lake catchment loads to predict metabolic rates, a result that may be particularly important in catchments experiencing changing hydrologic regimes related to global environmental change.

Funder

Eesti Teadusagentuur

Kempestiftelserna

Miljødirektoratet

National Science Foundation

Svenska Forskningsrådet Formas

Publisher

Wiley

Subject

Aquatic Science,Oceanography

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