Phytoplankton biomass, dissolved organic matter, and temperature drive respiration in whole lake nutrient additions

Abstract

Lake respiration is supported by a mixture of autochthonous and allochthonous resources, but the relative significance and interaction of these sources are uncertain across gradients of primary production and organic matter inputs. We manipulated autochthonous resources by adding inorganic nitrogen and phosphorus to two lakes during three summers and monitored a third reference lake. Allochthonous resources were measured as fluorescent dissolved organic matter (FDOM). In the reference and two experimental lakes, daily estimates of respiration were made from continuously deployed oxygen sensors. Daily mean values of temperature and FDOM were determined from high‐frequency measurements along with daily measures of chlorophyll a, an index of phytoplankton biomass. We analyzed time series of respiration and tested models that used combinations of the independent variables chlorophyll, FDOM, and temperature. The best models included all three of the independent variables. Respiration increased twofold over the temperature range of 14.5–28.6°C. Respiration increased in association with phytoplankton blooms caused by the nutrient additions, but did not track blooms closely, because of large day‐to‐day variability. Respiration varied positively with FDOM that was primarily allochthonous and differed among lakes and years. We did not detect an interaction between chlorophyll and FDOM despite the large number of observations and range of chlorophyll and FDOM. Hydrologic, climatic, and land use changes are altering temperature and inputs of nutrients and organic matter to lakes. Our results indicate that these changes may lead to linear responses in ecosystem processes like respiration for the wide range of inputs represented in this study.

In‐Phase PDO and El Niño Events Enhance the Summer CO2 Emissions in Saline Lakes on the Qinghai‐Tibet Plateau

“…In addition, apart from the carbonate balance, variations in Ts and precipitation would regulate the bubble emissions, the photosynthetic and respiratory reactions of phytoplankton, and the CO 2 exchange effect from within the sediment‐lake interface, thereby affecting CO 2 exchange in the water‐air interface (Figure 3) (Jia et al., 2022; Sun et al., 2022). Rising Ts accelerated both the photosynthesis and respiration of phytoplankton, and the trade‐off between photosynthesis and respiration determines the uptake and release of C by phytoplankton in the lakes (J. Jia et al., 2021; Liang et al., 2021; Pace et al., 2021; Phillips, 2020; Zhang et al., 2022). Studies of terrestrial ecosystems have found that the leaf‐level photosynthetic rate increases with rising temperature until the temperature exceeds its thermal optima (approximately 23 ± 6°C), while the respiratory rate increased exponentially with the rising temperature (Bennett et al., 2021; Johnston et al., 2021; Ping et al., 2023).…”

“…Rising Ts accelerated both the photosynthesis and respiration of phytoplankton, and the trade-off between photosynthesis and respiration determines the uptake and release of C by phytoplankton in the lakes (J. Liang et al, 2021;Pace et al, 2021;Phillips, 2020;Zhang et al, 2022). Studies of terrestrial ecosystems have found that the leaf-level photosynthetic rate increases with rising temperature until the temperature exceeds its thermal optima (approximately 23 ± 6°C), while the respiratory rate increased exponentially with the rising temperature (Bennett et al, 2021;Johnston et al, 2021;Ping et al, 2023).…”

Persistent hot spots of CO2 and CH4 in coastal nearshore environments

“…We used FDOM as a proxy for allochthonous OC loading and chl a concentration as a proxy for autochthonous OC loading (Pace et al 2021). The temporal variables "time of day" and "day of year" were used to resolve diurnal and seasonal variability in the observed partial pressures.…”

DOC, grazers, and resilience of phytoplankton to enrichment

“… Data Availability Statement : Original field data and metadata were derived from the following resources available in the Environmental Data Initiative repository: Carpenter et al (2017 a , b ), Pace et al (2020 a , b ). Calculated data, R scripts, and ReadMe files are available in GitHub distributed by Zenodo: Carpenter and Arani (2021), Carpenter (2022 a , b ), Carpenter and Pace (2022 a , b ).…”