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- Corman, Jessica R., et al.
(författare)
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Response of lake metabolism to catchment inputs inferred using high-frequency lake and stream data from across the northern hemisphere
- 2023
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Ingår i: Limnology and Oceanography. - : John Wiley & Sons. - 0024-3590 .- 1939-5590. ; 68:12, s. 2617-2631
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Tidskriftsartikel (refereegranskat)abstract
- In 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.
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| 2. |
- Côté, Marianne, et al.
(författare)
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Towards modeling data-poor lakes at the regional scale using parameters from data-rich lakes and relationships to lake characteristics
- 2023
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Ingår i: Inland Waters. - : Taylor & Francis. - 2044-2041 .- 2044-205X. ; 13:3, s. 388-401
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Tidskriftsartikel (refereegranskat)abstract
- Lakes pivotal for recreation and economically relevant activities are often remote and not well studied, which hinders the application of predictive lake models for their management. Here, we provide an approach to simulate—by means of the process-oriented model MyLake—water temperature, ice cover duration, dissolved oxygen, and light attenuation in 198 data-poor lakes based on parameters obtained for a subgroup of 12 data-rich lakes and morphometric data. Specifically, the model is first calibrated using a genetic algorithm on well-studied lakes. Simple relationships between the fitted parameters and lake-catchment morphometric properties are then derived, and the results of simulations using fitted and derived parameters are compared. The loss in goodness-of-fit, expressed as root mean square error (RMSE) incurred by using estimated rather than calibrated parameters, is 0.17 °C for water temperature and 0.82 mg L−1 for dissolved oxygen. These general relationships are then used to provide the model parameters for 198 data-poor lakes distributed throughout Sweden and to model these lakes. Overall, this proof of concept allows simulating lakes selected based on their relevance for lake management rather than based on the availability of extensive field datasets.
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