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Record W3000735519 · doi:10.1111/1365-2745.13326

Soil abiotic and biotic properties constrain the establishment of a dominant temperate tree into boreal forests

2020· article· en· W3000735519 on OpenAlexafffund
Alexis Carteron, Vlad Parasquive, Florence Blanchard, Xavier Guilbeault‐Mayers, Benjamin L. Turner, Mark Vellend, Étienne Laliberté

Bibliographic record

VenueJournal of Ecology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversité de SherbrookeUniversité de Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaUniversité de Montréal
KeywordsEdaphicAbiotic componentTemperate rainforestBiotic componentEnvironmental scienceTemperate forestEcologyTemperate climateSoil waterRange (aeronautics)TaigaBorealBiologyEcosystem

Abstract

fetched live from OpenAlex

Abstract Climate warming is expected to cause the poleward and upward elevational expansion of temperate plant species, but non‐climatic factors such as soils could constrain this range expansion. However, the extent to which edaphic constraints on range expansion have an abiotic (e.g. soil chemistry) or biotic (e.g. micro‐organisms) origin remains undetermined. We conducted greenhouse experiments to test if the survival and growth of a major North American temperate tree species, Acer saccharum (sugar maple), is independently or jointly constrained by abiotic and biotic properties of field‐collected soils from within and beyond the species' elevational range. Abiotic factors, particularly low base cation concentrations, were major constraints to seedling establishment in boreal forest soils (beyond the range edge), but insufficient arbuscular mycorrhizal fungal inoculum (biotic factor) also strongly reduced seedling performance in these soils. Synthesis. Our results suggest that forecasting future changes in forest composition under climate warming requires consideration of soil properties as well as the mycorrhizal status of tree species.

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 score0.014
Threshold uncertainty score0.291

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 studies0.0000.001
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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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

Citations56
Published2020
Admission routes2
Has abstractyes

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