The condition of Swiss lakes has improved thanks to stricter protection measures, but less than expected. A new method developed by Eawag for calculating biomass production in lakes provides explanations and a basis for further...
The condition of Swiss lakes has improved thanks to stricter protection measures, but less than expected. A new method developed by Eawag for calculating biomass production in lakes provides explanations and a basis for further water protection measures.
Net ecosystem production of lakes estimated from hypolimnetic organic carbon sinks
This study presents a novel concept for estimating net ecosystem production (NEP), the export of organic carbon (OC) from the productive surface layer to the deep‐water (hypolimnion) of 11 seasonally stratified lakes, varying in depth and trophic state. As oxygen remineralizes settling OC at a constant ratio, NEP is equivalent to the areal hypolimnetic mineralization rate (AHM) plus burial in the sediment. Two major interferences have to be considered, however. First, OC from terrestrial sources, not originating from primary production, consumes a fraction of oxidants. Second, sediment diagenetic processes of lakes in trophic transition (e.g., undergoing eutrophication or reoligotrophication) that are not in quasi‐steady‐state with actual fluxes of OC from the productive surface layer, bias the NEP estimation. In these cases, the flux of reduced substances diffusing from the sediment must be subtracted. This results in some overestimation for lakes with high allochthonous loads, and slight underestimation in lakes that are not in quasi‐steady‐state, because the actual sediment burial of autochthonous OC is small but not negligible. The presented approach requires data from routinely available monitoring and thus can be applied to historic data. The temporal integration over the productive season makes the estimation of NEP robust. Based on a historic 47 years long data record of Lake Geneva, NEP estimations (∼70 gC m-2) from AHM rates agree well with P and N export budgets from the productive surface zone, which help to verify and constrain the uncertainty of the estimates.
Primary and net ecosystem production in a large lake diagnosed from high‐resolution oxygen measurements
The rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) provide quantitative information about the cycling of carbon and energy in aquatic ecosystems. In lakes, metabolic rates are often diagnosed from diel oxygen fluctuations recorded with high‐resolution sondes. This requires that the imprint of ecosystem metabolism can be separated from that of physical processes. Here, we quantified the vertical and temporal variability of the metabolic rates of a deep, large, mesotrophic lake (Lake Geneva, Switzerland–France) by using a 6‐month record (April-October 2019) of high‐frequency, depth‐resolved (0-30 m) dissolved oxygen measurements. Two new alternative methods (in the time and frequency domain) were used to filter low‐frequency basin‐scale internal motions from the oxygen signal. Both methods proved successful and yielded consistent metabolic estimates showing net autotrophy (NEP = GPP - R = 55 mmol m-2 day-1) over the sampling period and depth interval, with GPP (235 mmol m-2 day-1) exceeding R (180 mmol m-2 day-1). They also revealed significant temporal variability, with at least two short‐lived blooms occurring during calm periods, and a vertical partitioning of metabolism, with stronger diel cycles and positive NEP in the upper ∼10 m and negative NEP below, where the diel oxygen signal was dominated by internal motions. The proposed methods expand the range of applicability of the diel oxygen technique to large lakes hosting energetic, low‐frequency internal motions, offering new possibilities for unveiling the rich spatiotemporal metabolism dynamics in these systems.
Fernández Castro, B.; Chmiel, H. E.; Minaudo, C.; Krishna, S.; Perolo, P.; Rasconi, S.; Wüest, A. (2021) Primary and net ecosystem production in a large lake diagnosed from high‐resolution oxygen measurements, Water Resources Research, 57(5), e2020WR029283 (24 pp.), doi:10.1029/2020WR029283, Institutional Repository