Larger colony sizes favoured the evolution of more worker castes in ants

The size-complexity hypothesis is a leading explanation for the evolution of complex life on earth. It predicts that in lineages that have undergone a major transition in organismality, larger numbers of lower-level subunits select for increased division of labour. Current data from multicellular organisms and social insects support a positive correlation between the number of cells and number of cell types and between colony size and the number of castes. However, the implication of these results is unclear, because colony size and number of cells are correlated with other variables which may also influence selection for division of labour, and causality could be in either direction. Here, to resolve this problem, we tested multiple causal hypotheses using data from 794 ant species. We found that larger colony sizes favoured the evolution of increased division of labour, resulting in more worker castes and greater variation in worker size. By contrast, our results did not provide consistent support for alternative hypotheses regarding either queen mating frequency or number of queens per colony explaining variation in division of labour. Overall, our results provide strong support for the size-complexity hypothesis.

Authors

Institutions

Publication Details

Journal
Nature Ecology & Evolution
Published
2024-08-26
DOI
https://doi.org/10.1038/s41559-024-02512-7
Citations
22
Primary Topic
Insect and Arachnid Ecology and Behavior
Type
article
Field-Weighted Citation Impact
12.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Larger colony sizes favoured the evolution of more worker castes in ants

Philip A. Downing, Gijsbert D. A. Werner, Stuart A. West, Louis Bell‐Roberts et al.
22 citations
Nature Ecology & Evolution
Insect and Arachnid Ecology and Behavior
12.11
article

Larger colony sizes favoured the evolution of more worker castes in ants

Philip A. Downing, Gijsbert D. A. Werner, Stuart A. West, Louis Bell‐Roberts, Laura Ross, Juliet F. R. Turner
article en
22 citations

Abstract

The size-complexity hypothesis is a leading explanation for the evolution of complex life on earth. It predicts that in lineages that have undergone a major transition in organismality, larger numbers of lower-level subunits select for increased division of labour. Current data from multicellular organisms and social insects support a positive correlation between the number of cells and number of cell types and between colony size and the number of castes. However, the implication of these results is unclear, because colony size and number of cells are correlated with other variables which may also influence selection for division of labour, and causality could be in either direction. Here, to resolve this problem, we tested multiple causal hypotheses using data from 794 ant species. We found that larger colony sizes favoured the evolution of increased division of labour, resulting in more worker castes and greater variation in worker size. By contrast, our results did not provide consistent support for alternative hypotheses regarding either queen mating frequency or number of queens per colony explaining variation in division of labour. Overall, our results provide strong support for the size-complexity hypothesis.

Nature Ecology & EvolutionVol. 8(10)
University of Oxford (GB), Scientific Council for Government Policy (NL), University of Oulu (FI), University of Edinburgh (GB)
Directorate for Biological Sciences
Decent work and economic growth
Openalex Percentile: Top 1%
Insect and Arachnid Ecology and Behavior
12.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.