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Density-dependent individual variation in male attractiveness in a wild field cricket

Citation

Niemelä, Petri; Tiso, Stefano; Dingemanse, Niels (2021), Density-dependent individual variation in male attractiveness in a wild field cricket, Dryad, Dataset, https://doi.org/10.5061/dryad.83bk3j9qq

Abstract

Social environments modify a male’s ability to attract females and thus affect its fitness. Theory implies that an individual’s fitness should trade-off with its ability to cope with competition. Individuals are expected to solve this trade-off differently: some males should be more attractive at low but others instead at high density. This prediction has rarely been tested in the wild. We used an automated RFID-surveillance system to quantify for each hour of the day, over 30 days (i.e. almost the entire adult lifespan of our model organism), whether a male had attracted a female in its burrow. The data were collected across a range of naturally varying local densities in wild field crickets, G.campestris. We also estimated whether the shape of the relationship between attractiveness and density was under selection. At the population level, attractiveness increased from low to intermediate density, suggesting an Allee effect. Attractiveness subsequently declined at higher densities, for example, because of detrimental effects of increased competition. Opposite to expectations, males that were more attractive under low densities were also more attractive under higher densities. However, the increase in attractiveness with density varied among males, suggesting that Allee effects were individual-specific. Finally, selection was not acting on density-dependent attractiveness but males that lived longer acquired more mating partners. Our study reveals that social environments shape attractiveness in wild male insects, and imply the occurrence of individual-specific Allee effect that may be evolvable.

Methods

The data is collected by using automated RIFD-surveillance system. Data is processed so that for all individuals, one location data point was extracted for each hour.

Usage Notes

Explanation for the variables in the provided data sets:

Main data

  • Fitness = binary trait for whether a male was with a female in its focal burrow during the focal hour (1 = yes, 0 = no). Thus, this variable represents attractiveness.
  • Age = age for each focal male as days after molting to maturation.
  • Age_2 = squared age.
  • Max_ages = number of days each focal male was alive as adult.
  • Max_ages_2 = squared Max_age.
  • Distance_wall = distance of each burrow (in centimeters) from the edge of the study area.
  • Tag = identity of each male.
  • Datez = date since 201505-08, i.e. since the first maturation in a population was confirmed.
  • Burrow = identity of each burrow.
  • Hours = identity of each hour (i.e. 24 hours).
  • Max_100NEW max_700NEW = maximum experienced density of other males for each focal male within 100 – 700 centimeter distance from the focal burrow.
  • max_100NEW_2 max_700NEW_2 = squared Max_100NEW - max_700NEW.
  • d100NEW d700NEW = hourly density of other males for each male for each focal hour within 100 – 700 centimeter distance from the focal burrow the focal male was occupying.
  • d100NEW_2 – d700NEW_2 = squared d100NEW_2 – d700NEW_2.

Selection gradient data:

  • relative_unique_females = relative amount of unique females confronted in the same focal burrow throughout the data collection period for each focal male.
  • Intercept_stand = standardized BLUP for the intercept of the reaction norm.
  • Linear_stand = standardized BLUP for the linear slope of the reaction norm.
  • Quadratic_stand = standardized BLUP for the nonlinear slope of the reaction norm.
  • Survival_stand = standardized number of days alive after molting to maturation.
  • Tag = identity of each focal male.