Balancing preservation of material and the need for analytical accuracy: Mass requirements of Sphagnum moss from herbarium collections for trace element analysis
Bibliographic record
Abstract
Sphagnum mosses have been used in some of the earliest works in biomonitoring of atmospheric deposition of trace elements (TEs). Since their adoption into the field the Sphagnaceae have become one of the foremost biomonitors. When taken as contemporary samples, these mosses have allowed us to identify spatial variations as well as trends and major changes in atmospheric deposition due to changing policy, technology, industry, and land use. While long term monitoring programs, such as the European Moss Survey, allow us to track these changes through time, these ongoing studies only reach as far back as their start dates. In the case of the European Moss Survey this was 1990. The use of materials already collected and archived in herbaria provides a low-cost method for retrospective analysis of atmospheric deposition of TEs. The critical advantage of herbarium specimens over other historical monitoring method is their high temporal resolution, as their exact collection date is known. Once collected, stored, and protected from atmospheric dust, the concentrations of non-volatile TEs present remain effectively unchanged. The oldest herbarium records can predate industrialisation, but most have records from the beginning of industrialisation, with the frequency of collection increasing in the modern era. Using only the top 2 cm of herbarium specimens of Sphagnum mosses (S. fuscum, S. angustifolium, S. capillifolium, S. magellanicum) found in Canadian ombrotrophic bogs, we will be creating historical reconstructions of atmospheric deposition in northern Alberta since the 1940s and southern Ontario since 1860’s. The first objective is to determine how best to balance preservation of the limited herbarium material available while also using sufficient material to achieve suitable levels of analytical accuracy. As TE analyses using ICP-MS are destructive and some specimens have immeasurable value from a natural history perspective, as little material as possible should be taken for analysis. Grinding of the sample was avoided, to minimize sample loss and the risk of contamination. We compared the measured concentrations obtained with ICP-MS as a function of the mass of Sphagnum digested, using selected herbarium samples as well as two certified, Standard Reference Materials (NIST 1515 and HB36-M2). These analyses allow us to determine the optimal amount of material necessary to balance the analytical accuracy and preservation of material of 4 species of Sphagnum mosses from Alberta over the last 80 years. The results will be compared with the data already available for TE concentrations in age-dated peat cores from the same region.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".