On the calculation of lake metabolic rates: Diel O2 and 18/16O technique

Peeters, Frank; Hofmann, Hilmar; Fernández, Jorge Encinas

doi:10.1016/j.watres.2019.114990

Cited by 6 publications

(16 citation statements)

References 20 publications

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“…When physical and biogeochemical conditions are met, contrasting daytime photosynthesis and ecosystem respiration, as well as losses due to sedimentation and grazing, result in pronounced diel variations in O 2 concentrations within the productive zone. 11 Because IOPs are closely linked to the nature of water constituents, in particular to phytoplankton, this study specifically sought to detect high-frequency IOP measurements exhibiting diel variations similar to those observed in O 2 . To characterize diel signals in the data set, we first extracted average values observed in the productive and nonproductive layers across all profiles and for T w , O 2 , aLH676, c700, Sk, and bb700.…”

Section: Autonomous High-frequency Profilingmentioning

confidence: 99%

“…Simultaneous high-frequency measurements of different variables have also contributed to improve our understanding of aquatic ecosystems. For example, continuous CO 2 and O 2 data have provided key insights into lake metabolism, 11,12 and more generally linked biogeochemical processes (organic matter respiration, photosynthesis, carbonate precipitation, and dissolution) with hydrodynamics and air−water gas exchange.…”

Section: Introductionmentioning

confidence: 99%

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The Imprint of Primary Production on High-Frequency Profiles of Lake Optical Properties

Minaudo

Odermatt

Bouffard

et al. 2021

Environ. Sci. Technol.

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Water inherent optical properties (IOPs) contain integrative information on the optical constituents of surface waters. In lakes, IOP measurements have not been traditionally collected. This study describes how high-frequency IOP profiles can be used to document short-term physical and biogeochemical processes that ultimately influence the long-term trajectory of lake ecosystems. Between October 2018 and May 2020, we collected 1373 high-resolution hyperspectral IOP profiles in the uppermost 50 m of the large mesotrophic Lake Geneva (Switzerland−France), using an autonomous profiler. A data set of this size and content does not exist for any other lake. Results showed seasonal variations in the IOPs, following the expected dynamic of phytoplankton. We found systematic diel patterns in the IOPs. Phases of these diel cycles were consistent year-round, and amplitudes correlated to the diurnal variations of dissolved oxygen, clarifying the link between IOPs and phytoplankton metabolism. Diel amplitudes were largest in spring and summer under low wind condition. Wind-driven changes in thermal stratification impacted the dynamic of the IOPs, illustrating the potential of high-frequency profiles of water optical properties to increase our understanding of carbon cycling in lake ecosystems.

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Section: Autonomous High-frequency Profilingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Imprint of Primary Production on High-Frequency Profiles of Lake Optical Properties

Minaudo

Odermatt

Bouffard

et al. 2021

Environ. Sci. Technol.

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“…Primary production, the production of organic matter by autotrophs, is a fundamental ecosystem process and, combined with allochthonous inputs, determines the amount of energy available to higher trophic levels. In the pelagic regions of lakes and reservoirs, oxygenic primary production is typically determined using variants of two basic techniques: measuring the uptake of dissolved inorganic carbon or the production of dissolved oxygen (O 2 ) (Hall et al 2007, but see Peeters et al 2016, 2019 as examples of other approaches). These techniques can be applied either in situ or in laboratory incubations and can include measurements in bottles or open water.…”

mentioning

confidence: 99%

Estimating pelagic primary production in lakes: Comparison of ¹⁴C incubation and free‐water O₂ approaches

Lottig

Phillips

Batt

et al. 2021

Limnology & Ocean Methods

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Historically, estimates of pelagic primary production in lake ecosystems were made by measuring the uptake of carbon‐14 (14C)‐labeled inorganic carbon in samples incubated under laboratory or in situ conditions. However, incubation approaches are increasingly being replaced by methods that analyze diel changes in high‐frequency in situ data such as free‐water dissolved oxygen (O2). While there is a rich literature on the comparison of approaches for estimating primary production using incubations (e.g., 14C and O2 bottle experiments), as well for approaches using high‐frequency data (e.g., diel O2 and CO2 metabolism models), there are few direct comparisons of 14C incubations and free‐water O2 approaches for estimating primary production. We used 20 lake‐years of concurrent measurements of primary production quantified from high‐frequency free‐water O2 data and 14C incubations in four different lakes (4–7 years per lake) to compare these different approaches. Across all lakes, 61% of the 14C production estimates were within the 95% credible intervals of the free‐water O2 production estimates. Error‐in‐variable regressions support the assumption that 14C methods estimate a production value between gross primary production and net primary production and the bottle effect is constant across the entire range of production values considered here. There was little evidence that daily pelagic, epilimnetic estimates of primary production differed substantially based on the selection of free‐water O2 or 14C approaches in these lakes during summer stratified conditions.

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“…The false assumption that DO and 18 0 00 are at steady state introduces errors in the daily mean metabolic rares obtained with the steady state isotopic technique. These errors are assessed in Peeters et al (2019) clarifying the limitations of the applicability of the steady state isotopic technique.…”

mentioning

confidence: 99%

“…The main conclusion of Peeters et al (2019) is that the steady state isotopic techn ique may cause errors in the daily mean metabolic rates by up to a factor of 2.5. Estimated metabolic rates deviate from the true metabolic rates because DO and 18 0 00 are not steady but vary at sub-dai ly time scales and between days.…”

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confidence: 99%

Reply for comment on “on the calculation of lake metabolic rates: Diel O2 and 18/16O technique” by Peeters et al. [Water research 165 2019, 114990]

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On the calculation of lake metabolic rates: Diel O2 and 18/16O technique

Cited by 6 publications

References 20 publications

The Imprint of Primary Production on High-Frequency Profiles of Lake Optical Properties

The Imprint of Primary Production on High-Frequency Profiles of Lake Optical Properties

Estimating pelagic primary production in lakes: Comparison of ¹⁴C incubation and free‐water O₂ approaches

Reply for comment on “on the calculation of lake metabolic rates: Diel O2 and 18/16O technique” by Peeters et al. [Water research 165 2019, 114990]

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On the calculation of lake metabolic rates: Diel O2 and 18/16O technique

Cited by 6 publications

References 20 publications

The Imprint of Primary Production on High-Frequency Profiles of Lake Optical Properties

The Imprint of Primary Production on High-Frequency Profiles of Lake Optical Properties

Estimating pelagic primary production in lakes: Comparison of 14C incubation and free‐water O2 approaches

Reply for comment on “on the calculation of lake metabolic rates: Diel O2 and 18/16O technique” by Peeters et al. [Water research 165 2019, 114990]

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Estimating pelagic primary production in lakes: Comparison of ¹⁴C incubation and free‐water O₂ approaches