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Woody‐tissue respiration

2002· article· en· W2170303553 on OpenAlexaff
M. P. Lavigne

Bibliographic record

VenueNew Phytologist · 2002
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsCanadian Forest Service
Fundersnot available
KeywordsRespirationBeechEcosystemDeciduousTerrestrial ecosystemEnvironmental scienceForest ecologyBiologyRespiration rateAtmospheric sciencesBotanyEcologyPhysics

Abstract

fetched live from OpenAlex

The complete accounting of carbon entering and exiting forest ecosystems is a vital task, and Damesin et al. have examined the contribution of woody-tissue respiration to this, as reported on pp. 159–172 in this issue. However, scaling up from tree measurements to estimations at the stand level is fraught with difficulties. The sizeable effort put into determining volume and surface area of branches was an important component of the study. What was noteworthy? First, it was found that branch respiration rate differs from stem respiration rate at all times of the year, with the direction and magnitude of the difference depending on the base for expressing the fluxes. Sprugel (1990) and Maier et al. (1998) reported similar findings, but this is the first such report for a deciduous species. Damesin et al. show that as a consequence of these differences between stems and branches, the common practice of using measurements of stem respiration to estimate branch respiration leads to underestimates when sapwood volume is the basis for scaling, or overestimates when surface area is the basis. The second point of note was that branch respiration appears to make about the same contribution to ecosystem respiration as does stem respiration in the beech ecosystem, because of both higher specific rates and the large amount of respiring branch matter. Partly because of the relatively high flux from branches, the above-ground, woody-tissue respiration contributed a large fraction of total ecosystem respiration in the beech ecosystem in comparison to previous reports for coniferous forests (e.g. Ryan et al. (1996), Lavigne et al. (1997)). The authors found that one third of ecosystem respiration is derived from woody-tissues in their beech forest whereas values of 15% and less are typical in coniferous ecosystems. Assuming that the present results are typical of deciduous forests, then measurements of woody-tissue respiration are essential in studies having as an objective the complete accounting of C entering and exiting the ecosystem. Increasingly chamber measurements are taken at sites where the eddy covariance method is used to estimate net ecosystem exchange, for the purpose of explaining the observed exchange between ecosystem and atmosphere. Damesin et al. have shown that woody-tissue respiration deserves as much attention as other fluxes, such as soil respiration, that branch respiration should be measured in addition to stem respiration, and that allometric relationships established by harvesting a sample of trees at the site should facilitate the scaling of woody tissue respiration.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.010

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 head0.065
GPT teacher head0.314
Teacher spread0.249 · 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

Citations2
Published2002
Admission routes1
Has abstractyes

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