Logging disrupts the ecology of molecules in headwater streams
Bibliographic record
Abstract
Global demand for wood products is increasing forest harvest. One understudied consequence of logging is that it accelerates mobilization of dissolved organic matter (DOM) from soils to aquatic ecosystems where it is more easily rereleased to the atmosphere. Here, we tested how logging changed DOM in headwaters of hardwood-dominated catchments in northern Ontario, Canada. We applied a before-after-control-impact experiment across four catchments for 3 y and measured DOM monthly during ice-free seasons. DOM concentration in streams from logged catchments quadrupled, on average, only for the first 2 mo postharvest, but resulting changes to the molecular composition of DOM persisted for at least 2 y. Ultrahigh-resolution mass spectrometry revealed that DOM composition within logged streams became more available for microbial use and chemically diverse than in controls, with novel highly unsaturated polyphenols, carboxylic-rich alicyclic, and nitrogen-containing formulae. The molecular composition of stream DOM measured fortnightly postharvest was most similar to the DOM composition of surrounding soils, likely due to increased hydrological connectivity. Alongside carbon being more likely to be released into the atmosphere, we estimate that selective logging increased the total flux of dissolved organic carbon in streams by 6.4% of the carbon extracted as timber. Although these estimates are short-lived, they should affect the millions of hectares that are logged annually. Carbon accounting of forestry, including as a natural climate solution, must now consider the transport and fate of DOM from land into water.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".