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Record W6929668926 · doi:10.5061/dryad.j0t179b

Data from: Local adaptation of trees at the range margins impact range shifts in the face of climate change

2018· dataset· en· W6929668926 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2018
Typedataset
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsUniversité de SherbrookeMinistère des Ressources naturelles et des Forêts (Québec)Université du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
Fundersnot available
KeywordsRange (aeronautics)Climate changeLocal adaptationMicrositeNichePropaguleMargin (machine learning)Global changeAdaptation (eye)

Abstract

fetched live from OpenAlex

The ability of tree species to track their climatic niche at rates comparable to global warming is concerning, particularly if they are constrained by local adaptation. If a species is locally adapted at its range margin it could be beneficial for range expansion as it ensures that the genotypes colonizing new areas are the fittest because environmental conditions are more similar to the current ones. In trees, local adaptation can slow range expansion when climate change happens much faster than their ability to migrate. We investigate experimentally a series of factors thought to constrain the seedling phase at the leading edge of the distribution of a dominant tree species, sugar maple (Acer saccharum Marshall.). We established a seed transplant experiment using six provenances, representing the latitudinal species range, and transplanted them to 12 sites within, at, and beyond the current northern species range margin. Northern provenances currently provide the best opportunity for establishment beyond the actual range, where climatic conditions are more similar than those of the warmer central or southern portions of the species range. While establishment was highest within the species range, survival rates were comparable to those at the range margin and beyond, regardless of provenance. We also find that the local climate is the most influential factor for early seedling establishment and survival; however, a lack of suitable microsites also significantly constrained recruitment. Our study highlights the complex interaction between provenance, climate, and microsite conditions that are required to ensure successful seedling recruitment. While sugar maple is currently displaying evidence for local adaptation to facilitate range shifts, it could risk maladaptation in the future if the local climate warms beyond threshold required to ensure seed germination and a lack of favourable microsite conditions beyond the range.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.482
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0030.002
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 head0.047
GPT teacher head0.294
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2018
Admission routes1
Has abstractyes

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