Physical conditions driving the spatial and temporal variability in aquatic metabolism of a subtropical coastal lake
Bibliographic record
Abstract
We investigated the importance of meteorological and lake physical conditions for temporal, horizontal and vertical differences in the concentration of dissolved oxygen (DO) and water temperature, and the derived daily estimates of gross primary production (GPP), ecosystem respiration (R) and net ecosystem production (NEP). Our study was conducted in a subtropical and polymictic lake in Southern Brazil, during a spring–summer transition. Metabolic rates were determined from two sites using the open water oxygen technique. At the central deep site, oxygen sondes were deployed at three depths to assess patterns in vertical variability. During 10 days, an additional DO and temperature sonde was placed near the shoreline allowing us to compare metabolic differences in the surface layers between the central pelagic and littoral site. While GPP was similar, R was significantly higher at the shallower littoral site, causing NEP to be lower, although NEP was still positive. The littoral site had less diel changes in DO and higher daily variability in all metabolic rates. Variability in GPP and R at the littoral site was related to temperature, wind speed and rainfall suggesting that short-term variability in metabolic rates in shallow areas are sensitive to resuspension of sediments caused by a less stable water column. A clear vertical gradient was furthermore found for the metabolic rates at the central deep part of the lake, related to the light extinction, with highest GPP around 0.3 m and decreasing with depth, while respiration showed the inverse pattern. Below subsurface, respiration prevailed at 5.0 m depth and was uncoupled to primary production. Under conditions with high light and temperature, and low wind speeds, the mixing depth became shallower, in turn increasing the water column stability at the deep pelagic site, which resulted in higher mean light available and higher GPP in the water column. Our results confirm that deployment of sensors in different sites and depths allows for spatially, as well as temporally more representative estimates of lake metabolism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".