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Record W4311165645 · doi:10.1101/2022.11.30.518597

Costs and benefits of maternal nest choice: tradeoffs between brood survival and thermal stress for small carpenter bees

2022· preprint· en· W4311165645 on OpenAlexafffund
JL deHaan, Jesse Maretzki, Adonis Skandalis, Glenn J. Tattersall, MH Richards

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsBrock University
FundersNatural Sciences and Engineering Research Council of CanadaBrock University
KeywordsBroodNest (protein structural motif)BiologyJuvenileOffspringEcologyForagingPredationPregnancy

Abstract

fetched live from OpenAlex

Abstract Nest site selection is a crucial decision for bees because where mothers construct their nests influences the developmental environment of their offspring. Small carpenter bees ( Ceratina calcarata ) nest in sun or shade, suggesting that maternal decisions about nest sites are influenced by thermal conditions that influence juvenile growth and survival. We investigated the costs and benefits to mothers and their offspring of warmer or cooler nest sites using a field experiment in which mothers and newly founded nests were placed in sunny or shady habitats. Maternal costs and benefits in sunny and shady treatments were quantified by comparing brood provisioning behaviour, nest size, number of brood cells, and offspring survival rates. Juvenile costs and benefits were quantified as body size, high temperature tolerance (CT max ), metabolic rate, and pupal duration. The major maternal benefit of nesting in sun was significantly lower rates of total nest failure (caused by predation, parasitism or abandonment), which led to sun mothers producing 3.2 brood on average, while shade mothers produced only 2.9. However, sun nesting entailed costs to brood, which were significantly smaller, less likely to survive to adulthood and had significantly elevated CT max . This suggests that juvenile bees in sun nests bees experienced thermal stress during development, causing them to shunt resources from growth to thermoprotection, at the cost of smaller size and higher mortality. Pupae raised in a thermal-gradient “BeeCR” machine developed significantly faster at warmer average temperatures, which may be an additional benefit of sun nesting. Overall, our results highlight a tradeoff between maternal benefits and offspring costs when mothers choose nest sites, in which maternal fitness is enhanced by nesting in sun, despite significant physiological costs to offspring, due to the necessity for thermoprotective responses. Thinking through pandemic research The first lockdowns of the COVID-19 pandemic began as we prepared to enter the second field season of this study in 2020. Student research halted overnight. Lab access and travel were restricted. With limited access to field sites and no access to lab equipment, we brainstormed alternative approaches that would repeat, if not replicate, our main experiments of 2019 and fulfill degree requirements for JL de Haan’s MSc in a satisfying way. Our 2019 results had provided convincing evidence developmental temperature has long-term impacts on C. calcarata physiology, so we thought about which physiological measurements would be feasible outside the lab. Authors MH Richards and GJ Tattersall suggested collecting more measurements of CT max : the Peltier plate device required running water, but a portable water pump and a bucket allowed the apparatus to be set up anywhere. No calibration of instruments was required, and the only maintenance was to change the water in the bucket after a few hours of use. Thus, a student’s home basement became a laboratory. To investigate how temperatures affect developmental rate, we needed to raise bees in controlled environments, but incubators were not available. Author A Skandalis suggested repurposing a gradient PCR unit as a portable insect incubator (“The BeeCR”). The idea was tested successfully at home in 20202, so a larger study was done by J Maretzki in 2021 when undergraduate lab access was permitted again. Two outcomes of our pandemic pivot produced long-term benefits for our research. The BeeCR is a flexible, inexpensive, easy-to-use incubator perfectly suited for raising small insects at multiple simultaneous sets of variable temperatures. And the ease with which “field” sites could be established in our backyards demonstrates how amenable small carpenter bees are to field manipulations, suggesting this is a model species for addressing a variety of ecological and physiological questions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.045
GPT teacher head0.214
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2022
Admission routes2
Has abstractyes

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