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Peer-reviewedCC BY 4.0Royal Society Open Science

Latent variable modelling of condition and reproductive investment in Gryllus vocalis field crickets

  • Madison Von Deylen1
  • Agustí Muñoz-Garcia2
  • Ian M. Hamilton1,3
  • Susan N. Gershman4
4 affiliations
  1. 1Evolution, Ecology, and Organismal Biology, The Ohio State University 1 , Columbus, OH, USA
  2. 2Evolution, Ecology, and Organismal Biology, The Ohio State University at Mansfield 2 , Mansfield, OH, USA
  3. 3Mathematics, The Ohio State University 3 , Columbus, OH, USA
  4. 4Evolution, Ecology, and Organismal Biology, The Ohio State University at Marion 4 , Marion, OH, USA
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Abstract

‘Condition’ is often used to describe the underlying state or quality of an individual and is expected to influence traits essential for fitness. Variation in condition is therefore expected to contribute to differences in reproductive investment. However, both condition and reproductive investment are complex and multi-dimensional, making them difficult to quantify comprehensively. Instead, they are typically inferred using measurable traits, which may capture only limited aspects of these constructs. Herein, we use structural equation modelling to integrate multiple proxy measurements, quantify the influence of underlying condition and reproductive investment on proxies and examine the relationship between condition and reproductive investment. Using Gryllus vocalis field crickets, we constructed sex-specific models to account for differences in reproductive strategies and trait expression between males and females. Both models identified proxies that were significantly influenced by condition and reproductive investment, although the strength of this influence varied across traits, suggesting that some proxies are better indicators than others. Both models also revealed significant positive relationships between condition and reproductive investment. Overall, our results demonstrate that condition positively influences reproductive investment, while revealing that commonly used proxies vary in how well they reflect these underlying constructs.

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Cite

BibTeXRIS
BibTeX
@article{deylen2026latent,
  title = {{Latent variable modelling of condition and reproductive investment in Gryllus vocalis field crickets}},
  author = {Madison Von Deylen and Agustí Muñoz-Garcia and Ian M. Hamilton and Susan N. Gershman},
  journal = {Royal Society Open Science},
  year = {2026},
  month = oct,
  doi = {10.1098/rsos.261085},
  url = {https://royalsocietypublishing.org/rsos/article/13/10/261085/483893/Latent-variable-modelling-of-condition-and},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Latent variable modelling of condition and reproductive investment in Gryllus vocalis field crickets
AU  - Madison Von Deylen
AU  - Agustí Muñoz-Garcia
AU  - Ian M. Hamilton
AU  - Susan N. Gershman
PY  - 2026
DA  - 2026/10/07
JO  - Royal Society Open Science
DO  - 10.1098/rsos.261085
UR  - https://royalsocietypublishing.org/rsos/article/13/10/261085/483893/Latent-variable-modelling-of-condition-and
AB  - ‘Condition’ is often used to describe the underlying state or quality of an individual and is expected to influence traits essential for fitness. Variation in condition is therefore expected to contribute to differences in reproductive investment. However, both condition and reproductive investment are complex and multi-dimensional, making them difficult to quantify comprehensively. Instead, they are typically inferred using measurable traits, which may capture only limited aspects of these constructs. Herein, we use structural equation modelling to integrate multiple proxy measurements, quantify the influence of underlying condition and reproductive investment on proxies and examine the relationship between condition and reproductive investment. Using Gryllus vocalis field crickets, we constructed sex-specific models to account for differences in reproductive strategies and trait expression between males and females. Both models identified proxies that were significantly influenced by condition and reproductive investment, although the strength of this influence varied across traits, suggesting that some proxies are better indicators than others. Both models also revealed significant positive relationships between condition and reproductive investment. Overall, our results demonstrate that condition positively influences reproductive investment, while revealing that commonly used proxies vary in how well they reflect these underlying constructs.
SN  - 2054-5703
ER  -