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Record W4391889000 · doi:10.1093/evlett/qrad070

Evolutionary adaptation to climate change

2024· article· en· W4391889000 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvolution Letters · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNovo Nordisk FondenCentre National de la Recherche ScientifiqueNovo NordiskJane ja Aatos Erkon Säätiö
KeywordsAdaptation (eye)Climate changeClimate change adaptationEvolutionary biologyEcologyBiologyNeuroscience

Abstract

fetched live from OpenAlex

When the notion of climate change emerged over 200 years ago, few speculated as to the impact of rising atmospheric temperatures on biological life. Tens of decades later, research clearly demonstrates that the impact of climate change on life on Earth is enormous, ongoing, and with foreseen effects lasting well into the next century. Responses to climate change have been widely documented. However, the breadth of phenotypic traits involved with evolutionary adaptation to climate change remains unclear. In addition, it is difficult to identify the genetic and/or epigenetic bases of phenotypes adaptive to climate change, in part because it often is not clear whether this change is plastic, genetic, or some combination of the two. Adaptive responses to climate-driven selection also interact with other processes driving genetic changes in general, including demography as well as selection driven by other factors. In this Special Issue, we explore the factors that will impact the overall outcome of climate change adaptation. Our contributions explain that traits involved in climate change adaptation include not only classic phenomena, such as range shifts and environmentally dependent sex determination, but also often overlooked phenomena such as social and sexual conflicts and the expression of stress hormones. We learn how climate-driven selection can be mediated via both natural and sexual selection, effectively influencing key fitness-related traits such as offspring growth and fertility as well as evolutionary potential. Finally, we explore the limits and opportunities for predicting adaptive responses to climate change. This contribution forms the basis of 10 actions that we believe will improve predictions of when and how organisms may adapt genetically to climate change. We anticipate that this Special Issue will inform novel investigations into how the effects of climate change unfold from phenotypes to genotypes, particularly as methodologies increasingly allow researchers to study selection in field experiments.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0260.027

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 head0.029
GPT teacher head0.246
Teacher spread0.216 · 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