Evaluating Spatiotemporal Resolution of Trace Element Concentrations and Pb Isotopic Compositions of Honeybees and Hive Products as Biomonitors for Urban Metal Distribution
Bibliographic record
Abstract
Abstract Assessing metal distributions in cities is an important aspect of urban environmental quality management. Western honeybees (Apis mellifera) and their products are biomonitors that can elucidate small‐scale metal distribution within a city. We compare range and variations in trace element (TE) concentrations and lead (Pb) isotopic compositions of honey, bee tissue, bee pollen, and propolis collected throughout Metro Vancouver (BC, Canada). Honey, bee, and bee pollen results have similar TE and isotopic trends; samples collected in urban and industrialized areas exhibit elevated concentrations of anthropogenically influenced TE (e.g., Pb, Zn, V, and Ti) and a less radiogenic Pb isotopic composition (i.e., lower 206Pb/207Pb and elevated 208Pb/206Pb) relative to their suburban and rural counterparts. For example, 206Pb/207Pb, 208Pb/206Pb in honey range from 1.126, 2.131 and 1.184, 2.063; extremes measured in honey from urban and suburban/rural areas, respectively. Except for propolis, measured and interpolated (kriged) results in all materials reflect the immediate zoning or land use setting near the hive, providing kilometer‐scale geospatial resolution, suitable for monitoring urban systems. Statistical analysis reveals that no systematic variations or intra‐ or inter‐annual trends exist in TE concentrations or Pb isotopic compositions, including among sampling and field methods (i.e., old vs. new hive equipment and honey from the brood nest box vs. honey super). The results of this systematic study using honeybees and hive products in Metro Vancouver provide a robust, current baseline for future comparison of local land use and environmental policy change.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".