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Record W4295666975 · doi:10.5194/bg-19-4415-2022

Internal tree cycling and atmospheric archiving of mercury: examination with concentration and stable isotope analyses

2022· article· en· W4295666975 on OpenAlexaff
David S. McLagan, Harald Biester, Tomáš Navrátil, Stephan M. Kraemer, Lorenz Schwab

Bibliographic record

VenueBiogeosciences · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsThe Scarborough HospitalQueen's UniversityUniversity of Toronto
FundersTechnische Universität BraunschweigAustrian Science FundDeutsche Forschungsgemeinschaft
KeywordsMercury (programming language)Environmental chemistryCyclingChemistryIsotopeVolatilisationStable isotope ratioEnvironmental scienceForestry

Abstract

fetched live from OpenAlex

Trees predominantly take up mercury (Hg) from the atmosphere via stomatal assimilation of gaseous elemental Hg (GEM). Hg is oxidised in leaves/needles and transported to other tree anatomy including bole wood, where it can be stored long-term. Using Hg associated with growth rings facilitates archiving of historical GEM concentrations. Nonetheless, there are significant knowledge gaps on the cycling of Hg within trees. We investigate Hg archived in tree rings, internal tree Hg cycling, and differences in Hg uptake mechanisms in Norway spruce and European larch sampled within 1 km of a HgCl 2 -contaminated site using total Hg (THg) and Hg stable isotope analyses. Tree ring samples are indicative of significant increases in THg concentrations (up to 521 µg kg −1 ) from the background period (BGP; facility closed; 1992–present) to secondary industrial period (2ndIP; no HgCl 2 wood treatment; 1962–1992) to primary industrial period (1stIP; active HgCl 2 wood treatment; ≈ 1900–1962). Mass-dependent fractionation (MDF) Hg stable isotope data are shifted negative during industrial periods ( δ 202 Hg of 1stIP: −4.32 ± 0.15 ‰, 2ndIP: −4.04 ± 0.32 ‰, BGP: −2.83 ± 0.74 ‰; 1 SD). Even accounting for a ≈ −2.6 ‰ MDF shift associated with stomatal uptake, these data are indicative of emissions derived from industrial activity being enriched in lighter isotopes associated with HgCl 2 reduction and Hg 0 volatilisation. Similar MDF ( δ 202 Hg: −3.90 ± 0.30 ‰; 1 SD) in bark Hg (137 ± 105 µg kg −1 ) suggests that stomatal assimilation and downward transport is also the dominant uptake mechanism for bark Hg (reflective of negative stomatal-uptake MDF shift) rather than deposition to bark. THg was enriched in sapwood of all sampled trees across both tree species. This may indicate long-term storage of a fraction of Hg in sapwood or xylem solution. We also observed a small range of odd-isotope mass-independent fractionation (MIF). Differences in Δ 199 Hg between periods of different industrial activities were significant (Δ 199 Hg of 1stIP: 0.00 ± 0.03 ‰, 2ndIP: −0.06 ± 0.04 ‰, BGP: −0.13 ± 0.03 ‰; 1 SD), and we suggest MIF signatures are conserved during stomatal assimilation (reflect source MIF signatures). These data advance our understanding of the physiological processing of Hg within trees and provide critical direction to future research into the use of trees as archives for historical atmospheric Hg.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.274
Teacher spread0.247 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2022
Admission routes1
Has abstractyes

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