Effects of Forestry and Beaver Reservoirs on Mercury Dynamics in Boreal Stream Food Webs
Bibliographic record
Abstract
Mercury (Hg) binds to organic matter (OM) within boreal forest soils. Land disturbances, such as forest harvesting, alter the export of OM and nutrients to nearby streams. This can affect the structure of stream communities and their food webs by changes to basal resource availability, and consumer reliance on these resources. It may also impact the uptake and biomagnification of Hg within streams. Beaver impoundments often co-occur with forestry and can similarly influence Hg in streams. However, their combined effects are unknown. Most research on the effects of forest harvesting on Hg have focused on abiotic factors with little attention given to Hg dynamics in food webs, particularly in Canada’s boreal. This thesis examined the effects of forest harvest on macroinvertebrate communities and leaf litter decomposition (Chapter 2), and on Hg bioaccumulation and biomagnification temporally and regionally across streams (Chapter 3) and upstream and downstream of beaver reservoirs in harvested and non-harvested landscapes (Chapter 4). In Chapter 2, no effects of harvest on leaf litter decomposition were observed, yet results suggested that effects on macroinvertebrate communities within harvested landscapes were site-specific and most severe (i.e., declines in diversity, evenness, and in sensitive taxa) in streams with narrow buffer zones and higher amounts of harvest within their watershed. Chapter 3 showed that Hg concentrations ([Hg]) in macroinvertebrates were elevated in harvested landscapes, likely because of higher [Hg] in food sources, and that streams afforded less protection are at greater risk of increased [Hg] in water and consumers. Chapter 4 revealed that while [Hg] of consumers and biomagnification rates were elevated in harvested landscapes upstream of reservoirs, they did not persist downstream, indicating that effects of reservoirs and harvest were not additive, and were instead site-specific. This thesis provides novel and impactful information on Hg cycling and may assist foresters to develop guidelines to minimize Hg risk to stream 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 | 0.000 |
| Scholarly communication | 0.001 | 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".