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Record W2062598813 · doi:10.1242/jeb.063818

MATING STRATEGIES FOR A CHANGING WORLD

2011· article· en· W2062598813 on OpenAlexaff
Constance M. O’Connor

Bibliographic record

VenueJournal of Experimental Biology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMatingBiologyReproductionRed flour beetleEcologyOffspringZoologyInsectPregnancy

Abstract

fetched live from OpenAlex

When it comes to mating, it seems that you're damned if you do, and damned if you don't. Mating can transmit diseases, and mating partners might even injure or kill one another. Yet, for most animals, mating is necessary for reproduction, and mating with multiple partners can increase the number or quality of offspring. In this complicated world, what is the best strategy for maximizing the benefits while minimizing the costs of mating?As it turns out, the situation is even more complicated for female red flour beetles (Tribolium castaneum): the costs and benefits of different mating strategies are dependent on environmental conditions. Red flour beetles have been maintained in the laboratory at 30°C for over 30 years, which amounts to over 350 beetle generations, so these beetles are well adapted to life at 30°C. However, life at 34°C is significantly more stressful for the beetles, so how do the relative costs and benefits of different mating strategies change at a stressful temperature? Vera Grazer and Oliver Martin, from the Swiss Federal Institute of Technology Zurich, decided to address this question by measuring the survival and reproductive success of female red flour beetles at different temperatures.The researchers placed individual female beetles into small enclosures alone (virgin females that did not invest in reproduction), with a single male beetle (monogamous females that invested in reproduction with a single mate), or with multiple male beetles (polyandrous females that invested in reproduction with multiple mates) at both 30 and 34°C. After 1 week, the researchers removed the males from the enclosures, and monitored the females for an additional 9 weeks to assess their long-term survival, and to count the number of larvae that hatched for each female. Using this method, Grazer and Martin were able to quantify both the survival and reproductive success of females at both temperatures.The duo found that at the standard 30°C temperature, the virgin red flour beetles had the highest survival, with intermediate survival in the monogamous beetles, and the lowest survival in the polyandrous beetles. In other words, at the red flour beetle's adapted temperature, reproduction became increasingly costly for the females as the number of mates rose. The team also found that at 30°C there was no difference in the number of larvae produced by monogamous and polyandrous beetles. Therefore, at the standard temperature, it is clear that mating with multiple males carries a survival cost and does not confer any reproductive benefits for females.However, at 34°C, the survival differences disappeared. All of the ‘hot’ females survived for a reduced length of time relative to the beetles held at 30°C, and all of the ‘hot’ females survived for the same length of time, regardless of whether they were virgins, monogamous or polyandrous. What was even more exciting was that at 34°C the polyandrous beetles produced more larvae than monogamous beetles. Therefore, mating with multiple males does not carry an additional survival cost at higher temperatures, and results in increased reproductive success for female red flour beetles.This experiment elegantly demonstrates that both the costs and the benefits of polyandry are dependent on environmental conditions for female red flour beetles. As climate change and anthropogenic activity increases, wild populations are faced with rapid environmental change and environmental conditions that are quite different from those that populations are adapted to. The results of Grazer and Martin's experiment therefore have wide-reaching implications for wild populations across the globe. In this changing world, mating strategies will need to adapt.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.117
GPT teacher head0.342
Teacher spread0.225 · 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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