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Record W4386156818 · doi:10.1093/aobpla/plad061

Water deficit changes patterns of selection on floral signals and nectar rewards in the common morning glory

2023· article· en· W4386156818 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAoB Plants · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsSaint Mary's UniversityUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaVetenskapsrådet
KeywordsPollinatorNectarBiologyPollinationAbiotic componentSelection (genetic algorithm)EcologyPollen

Abstract

fetched live from OpenAlex

Abstract Understanding whether and how resource limitation alters phenotypic selection on floral traits is key to predict the evolution of plant–pollinator interactions under climate change. Two important resources predicted to decline with our changing climate are pollinators and water in the form of increased droughts. Most work, however, has studied these selective agents separately and in the case of water deficit, studies are rare. Here, we use the common morning glory (Ipomoea purpurea) to investigate the effects of experimental reduction in pollinator access and water availability on floral signals and nectar rewards and their effects on phenotypic selection on these traits. We conducted a manipulative experiment in a common garden, where we grew plants in three treatments: (1) pollinator restriction, (2) water reduction and (3) unmanipulated control. Plants in pollinator restriction and control treatments were well-watered compared to water deficit. We found that in contrast to pollinator restriction, water deficit had strong effects altering floral signals and nectar rewards but also differed in the direction and strength of selection on these traits compared to control plants. Water deficit increased the opportunity for selection, and selection in this treatment favoured lower nectar volumes and larger floral sizes, which might further alter pollinator visitation. In addition, well-watered plants, both in control and pollinator deficit, showed similar patterns of selection to increase nectar volume suggesting non-pollinator-mediated selection on nectar. Our study shows that floral traits may evolve in response to reduction in water access faster than to declines in pollinators and reinforces that abiotic factors can be important agents of selection for floral traits. Although only few experimental selection studies have manipulated access to biotic and abiotic resources, our results suggest that this approach is key for understanding how pollination systems may evolve under climate change.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.592

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 head0.070
GPT teacher head0.235
Teacher spread0.165 · 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