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Record W2010201288 · doi:10.1111/oik.01386

Plant–pollinator interactions and phenological change: what can we learn about climate impacts from experiments and observations?

2014· article· en· W2010201288 on OpenAlex

Why this work is in the frame

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

Bibliographic record

VenueOikos · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPollinatorPhenologyPollinationClimate changeEcologyBiologyPopulationPlant reproductionPollen

Abstract

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Climate change can affect plant–pollinator interactions in a variety of ways, but much of the research attention has focused on whether independent shifts in phenology will alter temporal overlap between plants and pollinators. Here I review the research on plant–pollinator mismatch, assessing the potential for observational and experimental approaches to address particular aspects of the problem. Recent, primarily observational studies suggest that phenologies of co‐occurring plants and pollinators tend to respond similarly to environmental cues, but that nevertheless, certain pairs of interacting species are showing independent shifts in phenology. Only in a few cases, however, have these independent shifts been shown to affect population vital rates (specifically, seed production by plants) but this largely reflects a lack of research. Compared to the few long‐term studies of pollination in natural plant populations, experimental manipulations of phenology have yielded relatively optimistic conclusions about effects of phenological shifts on plant reproduction, and I discuss how issues of scale and frequency‐dependence in pollinator behaviour affect the interpretation of these ‘temporal transplant’ experiments. Comparable research on the impacts of mismatch on pollinator populations is so far lacking, but both observational studies and focused experiments have the potential to improve our forecasts of pollinator responses to changing phenologies. Finally, while there is now evidence that plant–pollinator mismatch can affect seed production by plants, it is still unclear whether this phenological impact will be the primary way in which climate change affects plant–pollinator interactions. It would be useful to test the direct effects of changing climate on pollinator population persistence, and to compare the importance of phenological mismatch with other threats to pollination.

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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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.238

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 head0.138
GPT teacher head0.273
Teacher spread0.136 · 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

Quick stats

Citations303
Published2014
Admission routes1
Has abstractyes

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