Global change‐driven effects on dissolved organic matter composition: Implications for food webs of northern lakes
Bibliographic record
Abstract
Northern ecosystems are experiencing some of the most dramatic impacts of global change on Earth. Rising temperatures, hydrological intensification, changes in atmospheric acid deposition and associated acidification recovery, and changes in vegetative cover are resulting in fundamental changes in terrestrial-aquatic biogeochemical linkages. The effects of global change are readily observed in alterations in the supply of dissolved organic matter (DOM)-the messenger between terrestrial and lake ecosystems-with potentially profound effects on the structure and function of lakes. Northern terrestrial ecosystems contain substantial stores of organic matter and filter or funnel DOM, affecting the timing and magnitude of DOM delivery to surface waters. This terrestrial DOM is processed in streams, rivers, and lakes, ultimately shifting its composition, stoichiometry, and bioavailability. Here, we explore the potential consequences of these global change-driven effects for lake food webs at northern latitudes. Notably, we provide evidence that increased allochthonous DOM supply to lakes is overwhelming increased autochthonous DOM supply that potentially results from earlier ice-out and a longer growing season. Furthermore, we assess the potential implications of this shift for the nutritional quality of autotrophs in terms of their stoichiometry, fatty acid composition, toxin production, and methylmercury concentration, and therefore, contaminant transfer through the food web. We conclude that global change in northern regions leads not only to reduced primary productivity but also to nutritionally poorer lake food webs, with discernible consequences for the trophic web to fish and humans.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".