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Record W4393380490 · doi:10.1002/eco.2648

Increased tree water use with the development of a dense understory layer in a North American hardwood forest

2024· article· en· W4393380490 on OpenAlexafffund
Arielle Rasoanaivo, Claudele Ghotsa Mekontchou, Pascal Rochon, Philippe Nolet, Audrey Maheu

Bibliographic record

VenueEcohydrology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversité du Québec en Outaouais
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUnderstoryHardwoodTree (set theory)ForestryEnvironmental scienceAgroforestryHydrology (agriculture)GeographyGeologyEcologyCanopyArchaeologyMathematics

Abstract

fetched live from OpenAlex

Abstract The formation of a single species, recalcitrant understory vegetation layer can limit tree regeneration and, in the long term, modify the composition of forests. Few studies have investigated how recalcitrant vegetation influences competition for water resources although the formation of a dense understory is likely to modify the forest water balance. In eastern North American hardwood forests, the development of a dense understory layer of American beech ( Fagus grandifolia ) has been observed in stands dominated by sugar maple ( Acer saccharum ), a phenomenon that shares many characteristics associated with recalcitrant vegetation. Given that water availability is generally negatively correlated with stand density, we hypothesized that the formation of a dense understory beech layer increased competition for water resources, thus leading to reduced water use by sugar maple trees in beech‐dominated stands. Using thermal dissipation sensors, we measured sap flux density ( F d ) of two sugar maple trees at three beech‐dominated sites and three control sites. During the growing season, F d of sugar maple trees was significantly larger at beech‐dominated sites compared to control sites, indicating a greater rate of water use by sugar maples in stands with a dense understory beech layer. We provide two hypotheses to explain our results at the tree scale: (i) reduced cover by forest floor vegetation could limit transpiration by this layer, thus allowing increased water availability to supply transpiration by overstory trees, or (ii) increased tree transpiration rate could be a mechanism to satisfy nutrient requirements in beech‐dominated stands often associated with lower soil fertility.

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 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 score0.215
Threshold uncertainty score0.799

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.187
Teacher spread0.177 · 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 teacher head, 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
Published2024
Admission routes2
Has abstractyes

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