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Record W4293109690 · doi:10.1111/oik.09265

Simultaneous niche expansion and contraction in plant–pollinator networks under drought

2022· article· en· W4293109690 on OpenAlexaff
Connor Morozumi, Xingwen Loy, Victoria Reynolds, Annie Schiffer, Beth M. L. Morrison, Berry J. Brosi

Bibliographic record

VenueOikos · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsBishop's University
Fundersnot available
KeywordsPollinatorNicheEcologyInterspecific competitionForagingEcological networkNiche differentiationBiologyClimate changeEcological nicheCompetition (biology)Abundance (ecology)PollinationEcosystemHabitatPollen

Abstract

fetched live from OpenAlex

Global climate change threatens to substantially rearrange species interactions, yet we lack clear predictions on how these changes will cascade through communities. Many perturbations associated with climate change, such as droughts, will change resource levels, with consequences for species interactions and thus ecological network structure. Diet theory predicts foraging niche expansion when preferred resources are scarce, yet under severe resource reduction interspecific competition could alternatively increase niche partitioning. Such niche expansion and/or contraction could profoundly shape ecological network structure following perturbations, but whether these predictions hold at the community level is unclear. We studied the impacts of drought on plant–pollinator networks in long‐lived perennial plant communities in which drought affects flower and floral reward production. We assessed whether drought effects on available floral resources altered pollinator dietary niche breadth to drive higher network‐level generalization. Accounting for interaction abundance and species turnover, we compared plant–pollinator networks in two drought years and three non‐drought years. We found that drought restructured plant–pollinator networks, resulting in more generalization in terms of presence–absence of links, yet more specialization when accounting for quantitative network intensities. Our results support the application of diet theory to understanding how perturbations may impact ecological network structure.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.210

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 head0.023
GPT teacher head0.206
Teacher spread0.183 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations8
Published2022
Admission routes1
Has abstractyes

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