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Record W4406256905 · doi:10.1088/2752-664x/ada8b2

A comparison of the effects of beaver ponds and forest harvest on stream methylmercury in boreal watersheds

2025· article· en· W4406256905 on OpenAlex
Wai Ying Lam, Robert Mackereth, Celine Marie-Emanuelle Lajoie, Karen A. Kidd, Carl P. J. Mitchell

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Research Ecology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsMinistry of Natural Resources and ForestryThe Scarborough HospitalMcMaster UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaJarislowsky FoundationCanada Foundation for InnovationCentre for Environmental Research in the Anthropocene, University of Toronto Scarborough
KeywordsBeaverTaigaMethylmercuryEnvironmental scienceBorealGeographyEcologyHydrology (agriculture)ForestryPhysical geographyBiologyGeology

Abstract

fetched live from OpenAlex

Abstract Beaver ponds and forest harvest are common disturbances in the Canadian boreal forest that result in major changes to catchment hydrology and thus also influence the mobilization and methylation of mercury (Hg). Though both beaver ponds and forest harvest frequently occur in the same watersheds, the possible interactive effects are not well understood. To evaluate the comparative effects of these two disturbances, this study examined in-stream total mercury and methylmercury (MeHg) across 7 stream reaches in the central Canadian boreal forest. Results showed that downstream-to-upstream MeHg concentration ratios were more highly correlated to the presence of beaver ponds than to the presence of forest harvest. However, MeHg concentrations upstream of ponds were higher in streams within harvested watersheds; these streams demonstrated a weaker correlation between beaver pond presence and downstream-to-upstream MeHg concentration ratios. Understanding these comparative and cumulative effects of beaver ponds and forest harvest will allow forest managers to consider how harvest activity could affect downstream MeHg in areas with high beaver activity.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.316
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it