Isotopic analysis of the sources of organic carbon for zooplankton in shallow subarctic and arctic waters
Bibliographic record
Abstract
Shallow high‐latitude lakes and ponds are usually characterized by an oligotrophic water column overlying a biomass‐rich, highly productive benthos. Their pelagic food webs often contain abundant zooplankton but the importance of benthic organic carbon versus seston as their food sources has been little explored. Our objectives were to measure the δ 13 C and δ 15 N isotopic signatures of pelagic and benthic particulate organic matter (POM) in shallow water bodies in northern Canada and to determine the relative transfer of this material to zooplankton and other aquatic invertebrates. Fluorescence analysis of colored dissolved organic matter (CDOM) indicated a relatively strong terrestrial carbon influence in five subarctic waterbodies whereas the CDOM in five arctic water columns contained mostly organic carbon of autochthonous origin. The isotopic signatures of planktonic POM and cohesive benthic microbial mats were distinctly different at all study sites, while non‐cohesive microbial mats often overlapped in their δ 13 C signals with the planktonic POM. Zooplankton isotopic signatures indicated a potential trophic link with different fractions of planktonic POM and the non‐cohesive mats whereas the cohesive mats did not appear to be used as a major carbon source. The zooplankton signals differed among species, indicating selective use of resources and niche partitioning. Most zooplankton had δ 13 C values that were intermediate between the values of putative food sources and that likely reflected selective feeding on components of the pelagic or benthic POM. The results emphasize the likely importance of benthic‐pelagic coupling in tundra ecosystems, including for species that are traditionally considered pelagic and previously thought to be dependent only on phytoplankton as their food source.
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 | 0.002 |
| 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) | 0.000 | 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".