Blowin’ in the wind: reciprocal airborne carbon fluxes between lakes and land This paper is based on the J.C. Stevenson Memorial Lecture presented at the Canadian Conference for Fisheries Research (CCFFR) in Ottawa, Ontario, 9–11 January 2009.
Bibliographic record
Abstract
Ecologists are increasingly interested in how disjunct habitats are connected through the cross-habitat movement of matter, prey, nutrients, and detritus and the implications for recipient systems. The study of lake ecosystems has been dominated by the study of pelagic (open-water) production and processes, though there is growing awareness of the role of terrestrial inputs and benthic trophic pathways. Here, we review the phenomena of airborne fluxes to and from lakes. We assemble published data on terrestrial particulate organic carbon (TPOC) deposition to lakes, insect production, and insect emergence and use these data to simulate how airborne lake-to-land and land-to-lake carbon flux is expected to scale with ecosystem size, while taking into account among-lake variability in emergence and TPOC deposition. Emergent insect flux to land increases as a function of lake size, while TPOC deposition to lakes decreases as a function of lake size. TPOC deposition exceeds insect emergence in small lakes, while in large lakes, insect emergence exceeds TPOC deposition. We present a general framework for considering directional fluxes across habitat boundaries. Furthermore, our results highlight the overarching role of ecosystem geometry in determining insect emergence, airborne carbon deposition, and net carbon flux between adjacent ecosystems.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".