Loss of paired weapons leads to larger testes and a lighter load for dispersal
Data files
Jul 30, 2025 version files 36.41 KB
-
Manuscript_Data.csv
18.16 KB
-
ManuscriptAnalysis.R
15.74 KB
-
README.md
2.52 KB
Abstract
Reproduction is often costly for males, as it may require the growth of structural traits that aid in dispersal to find females, competition over mating opportunities, and ejaculate production. The growth of such traits can be energetically demanding, and these demands often arise concurrently during development. As such, these traits may be especially prone to resource allocation trade‐offs. Yet, such traits are rarely studied in tandem. We designed a study to improve understanding of investment dynamics in flight muscle, a dispersal trait; a sexually selected weapon used in mate competition; and testes used for sperm production. We used the leaf‐footed cactus bug, Narnia femorata (Hemiptera: Coreidae), a species where males use their hindleg as weapons to compete for matings. Males can naturally drop their limbs, and when hindlegs are lost during development, adult males do not grow a weapon. Existing studies have revealed that testes growth increases when investment in weapons ceases. Yet, this work only examined responses to the loss of a single hindleg and limited the scope of traits to testes. Here, we examined weapon loss at two levels and investigated a third trait: dispersal. We found that testes size increased stepwise with limb loss; the loss of one hindleg weapon increased testes mass by around 9%, and two legs increased it by 20%. This intriguing pattern suggests a direct, quantity‐specific trade‐off in tissue development across traits. We also detected only a limited increase in dispersal investment when males did not grow weapons. Yet, dispersal may still be enhanced for those that drop hind legs; those without the substantial weight of hind limbs may have the potential to disperse farther.
Data column descriptions; Manuscript_Data.csv:
- ID: Integer; Unique numerical identifier of each insect in the study
- Fam: String; Identified the parental pair of each individual, for inclusion in linear mixed models as a random effect
- MaleName: String; Unique string identifier of each insect in the study, including in order the project identifier (TMA), development order in clutch, Parental pair identifier, and alphabetical clutch identifier
- Soft: Bool; Identifies whether the individual exhibited a phenotype of small, soft, and highly melanated cuticle during rearing
- LookupName: String; Lookup value identifying the treatment of each individual. Individuals either "No Autotomy", "Single Autotomy", or "Double Autotomy"
- PronotumWidth: Decimal; Pronotum width of each individual in millimeters
- BodyMass: Decimal; Body mass of each individual in milligrams, does not include mass of testes, flight muscle, or any remaining weapons
- RHindLegArea: Decimal; Area of the right hind leg in millimeters squared, #N/A for double autotomy individuals
- DryTestesMass: Decimal; Mass of the both testes in milligrams, dried
- DryMuscleMass: Decimal; Mass of the flight muscle in milligrams, dried
- WeaponMass: Decimal; Mass of any remaining hind legs in milligrams, 0 for double autotomized individuals
- SingleLegMass: Decimal; Mass of a single hind leg in milligrams, #N/A for double autotomized, found in no autotomy individuals by dividing WeaponMass by 2
Missing values exist where body parts were lost during the course of the experiment, where data values were unusable, or in the case of RHindLegArea and SingleLegMass, where both hind legs were removed, and there is no mass of the single hind leg.
R script description; ManuscriptAnalysis.R:
Script containing all analyses conduced for this study. Script includes data transformations, model assumption tests, generalized linear mixed models, and path analysis, including model selection for path analysis. This script also includes code to generate all figures, except for the path figure (Figure 2), which was generated simply using Microsoft PowerPoint.
R version: 4.3.2
ggplot2 version: 3.5.1
dplyr version: 1.1.4
lmtest version: 0.9.40
ggpubr version: 0.6.0
rstatix 3.5.10.7.2
tidyverse version: 2.0.0
emmeans version: 1.8.9
lme4 version: 1.1.35.1
lavaan version: 0.6.19
AICcmodavg version: 2.3.3