Terrestrial carbon contribution to lake food webs: could the classical stable isotope approach be misleading?
Bibliographic record
Abstract
Carbon stable isotope analyses have been widely used to estimate terrestrial carbon contribution to lake secondary production. In such approaches, phytoplankton is tacitly assumed as a single, isotopically homogenous source. Such assumption might be valid if (i) zooplankton do not feed selectively on specific algal taxa within bulk phytoplankton, or (ii) although zooplankton do feed selectively, the variability in the δ13C values amongst the different algal taxa is small compared with the variability between the δ13C values of bulk phytoplankton and terrestrial end-members. In a summer field study of six coastal lakes of British Columbia, Canada, we tested these assumptions using gut pigments and stable isotope measures on zooplankton and particulate organic matter. Results revealed that filter-feeding cladocerans positively selected cryptophytes, shown to be substantially 13C-enriched compared with bulk phytoplankton and even with the terrestrial end-member. Comparing a classical two-source mixing model and a model that accounted for algal isotopic heterogeneity, we showed that the use of a classical two-source model can result in an overestimation of terrestrial contribution to zooplankton secondary production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".