| Literature DB >> 27004012 |
Michelle L Taylor1, Tom A R Price2, Alison Skeats1, Nina Wedell1.
Abstract
Multiple mating by females (polyandry) is a widespread behavior occurring in diverse taxa, species, and populations. Polyandry can also vary widely within species, and individual populations, so that both monandrous and polyandrous females occur together. Genetic differences can explain some of this intraspecific variation in polyandry, but environmental factors are also likely to play a role. One environmental factor that influences many fundamental biological processes is temperature. Higher temperatures have been shown to directly increase remating in laboratory studies of insects. In the longer term, high temperature could also help to drive the evolution of larger-scale patterns of behavior by changing the context-dependent balance of costs and benefits of polyandry across environments. We examined the relative influence of rearing and mating temperatures on female remating in populations of Drosophila pseudoobscura that show a latitudinal cline in polyandry in nature, using a range of ecologically relevant temperatures. We found that females of all genotypes remated more at cooler temperatures, which fits with the observation of higher average frequencies of polyandry at higher latitudes in this species. However, the impact of temperature was outweighed by the strong genetic control of remating in females in this species. It is likely that genetic factors provide the primary explanation for the latitudinal cline in polyandry in this species.Entities:
Keywords: Drosophila; environmental drivers; female behavior; genetic variation; pseudoobscura; sexual selection.
Year: 2015 PMID: 27004012 PMCID: PMC4797379 DOI: 10.1093/beheco/arv172
Source DB: PubMed Journal: Behav Ecol ISSN: 1045-2249 Impact factor: 2.671
Figure 1Minimum and maximum monthly temperatures in the 2 geographic locations relative to experimental temperatures. Climate data from 1981 to 2010 is from the archives of the National Oceanic and Atmospheric Administration.
Figure 2Experimental design to examine the effects of rearing and mating temperatures on female remating in 2 geographical populations of Drosophila pseudoobscura.
Logistic regression of polyandry (females remated = 1, not remated = 0) across 8 genotypes, 3 rearing temperatures, and 3 mating temperatures, with genotype and mating and rearing temperatures as predictors
| Model includes |
| ±SE |
|
|---|---|---|---|
| Constant | 0.312 | 0.696 | 0.654 |
| Genotype | 2.628 | 0.549 | 0.000 |
| Mating temperature | −0.083 | 0.024 | 0.000 |
| Rearing temperature | −0.029 | 0.024 | 0.226 |
| Model chi square (df 3) = 36.72, | |||
| Model | |||
B gives the slope of the regression of each individual variable (along with its SE and significance level), whereas chi square gives the significance of the overall model. df, degrees of freedom.
Figure 3The mean (± 1 SE) percentage of remated females (polyandry) in the highest polyandry lines (black lines) and lowest polyandry lines (gray lines) scored across 4 mating temperatures. Data from all genotypes are pooled within groups and data from the original baseline assay at 23 °C is included for comparison in the figure only.
Figure 4The mean (± 1 SE) percentage of remated females (polyandry) in Lewistown (black lines) and Show Low (gray lines) females across all temperature treatments. Individual genotypes are ranked and labeled by their baseline degree of polyandry that was scored in the first assay of all 26 genotypes at 23 °C.
Logistic regression of polyandry (females remated = 1, not remated = 0) across 8 genotypes, 3 rearing temperatures, and 3 mating temperatures, with mating latency and copulation duration of the first mating as predictors
| Model includes |
| ±SE |
|
|---|---|---|---|
| Constant | −1.54 | 0.138 | 0.000 |
| Mating latency | 0.003 | 0.004 | 0.499 |
| Copulation duration | 0.019 | 0.016 | 0.236 |
| Model chi square (df 2) = 1.893, | |||
| Model | |||
B gives the slope of the regression of each individual variable (along with its SE and significance level), whereas chi square gives the significance of the overall model. df, degrees of freedom.