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Record W6929646420 · doi:10.5061/dryad.w3r2280wr

Weak local adaptation to drought in seedlings of a widespread conifer

2024· dataset· en· W6929646420 on OpenAlexafffund

Bibliographic record

VenueDRYAD · 2024
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of British Columbia
FundersGenome Canada
KeywordsDrought toleranceIntraspecific competitionAdaptation (eye)Local adaptationClimate changePhenotypic plasticityGenetic variationDrought resistance

Abstract

fetched live from OpenAlex

Tree seedlings from populations native to drier regions are often assumed to be more drought tolerant than those from wetter provenances. However, intraspecific variation in drought tolerance has not been well characterized despite being critical for developing climate change mitigation and adaptation strategies, and for predicting the effects of drought on forests. We used a large-scale common-garden drought-to-death experiment to assess range-wide variation in drought tolerance measured by decline of photosynthetic efficiency, growth, and plastic responses to extreme summer drought in seedlings of 73 natural populations of the two main varieties of Douglas-fir (Pseudotsuga menziesii var. menziesii and var. glauca). Local adaptation to drought was weak in var. glauca and nearly absent in menziesii. Var. glauca showed higher tolerance to drought but slower growth than var. menziesii. Clinal variation in drought tolerance and growth species-wide was mainly associated with temperature rather than precipitation. A higher degree of plasticity for growth was observed in var. menziesii in response to extreme drought. Genetic variation for drought tolerance in seedlings within varieties is maintained primarily within populations. Selective breeding within populations may facilitate adaptation to drought more than assisted gene flow.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.135
Threshold uncertainty score0.798

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 head0.011
GPT teacher head0.252
Teacher spread0.240 · 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
Published2024
Admission routes2
Has abstractyes

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