Back

Caste-specific ageing emerges from the evolution of resource allocation in eusocial insects

Kreider, J. J.; Janzen, T.; Kramer, B. H.; Pen, I.

2026-06-19 evolutionary biology
10.64898/2026.06.16.732452 bioRxiv
Show abstract

Eusocial insects have extreme intraspecific lifespan variation, where queens are long-lived (up to 30 years) whereas workers only live for a few months or years at most. Several studies have invoked the disposable soma theory to explain the evolution of caste-specific ageing in eusocial insects, which proposes that senescence results from a resource allocation trade-off between maintenance vs. reproduction. An extension of this theory to eusocial insects is that caste-specific ageing could emerge from a resource allocation trade-off between castes. However, to date this idea has not been formalised in a theoretical model. Here, we present an individual-based model for the evolution of ageing in social insects. In our model, queens and workers die when their nutritional state becomes too low. The evolving trait in our model is the age-specific resource allocation of individual workers, who can allocate resources between themselves, other workers, and the queen. We find that lifespan differences between queens and workers emerge from the evolved resource allocation within colonies, which are within the range of empirically observed lifespans of queens and workers in monogynous eusocial insects. Caste-specific ageing evolves in our model because queens obtain large amounts of resources, which allows them to be long-lived and highly fertile, whereas workers evolve to give resources away to enhance the queens reproduction and thereby their own indirect fitness. We also observe that age polyethism emerges, where young workers nurse the brood and older workers forage. Overall, our model demonstrates that both caste-specific ageing and age-related worker division of labour emerge as a consequence of evolved within-colony resource allocation.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
Proceedings of the Royal Society B: Biological Sciences
393 papers in training set
Top 0.5%
9.5%
2
The American Naturalist
125 papers in training set
Top 0.2%
7.7%
3
Evolution
225 papers in training set
Top 0.6%
6.6%
4
Journal of Theoretical Biology
162 papers in training set
Top 0.5%
6.1%
5
Philosophical Transactions of the Royal Society B: Biological Sciences
72 papers in training set
Top 0.1%
5.4%
6
BMC Evolutionary Biology
18 papers in training set
Top 0.1%
5.4%
7
GENETICS
483 papers in training set
Top 1%
4.2%
8
Journal of Evolutionary Biology
110 papers in training set
Top 0.5%
4.2%
9
PLOS Computational Biology
1863 papers in training set
Top 8%
4.2%
50% of probability mass above
10
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 12%
4.2%
11
eLife
5828 papers in training set
Top 36%
3.1%
12
Biology Letters
76 papers in training set
Top 0.4%
2.6%
13
Nature Communications
5641 papers in training set
Top 39%
2.6%
14
Journal of The Royal Society Interface
235 papers in training set
Top 2%
2.1%
15
Genome Biology and Evolution
338 papers in training set
Top 2%
2.1%
16
Science Advances
1243 papers in training set
Top 21%
1.6%
17
Evolution Letters
85 papers in training set
Top 1%
1.5%
18
PLOS ONE
5266 papers in training set
Top 51%
1.5%
19
Scientific Reports
3612 papers in training set
Top 59%
1.5%
20
Royal Society Open Science
214 papers in training set
Top 4%
1.4%
21
npj Aging
22 papers in training set
Top 0.4%
1.1%
22
Oikos
84 papers in training set
Top 1%
1.1%
23
PLOS Biology
486 papers in training set
Top 10%
1.0%
24
G3: Genes|Genomes|Genetics
35 papers in training set
Top 0.3%
1.0%
25
PLOS Genetics
862 papers in training set
Top 11%
1.0%
26
Bulletin of Mathematical Biology
92 papers in training set
Top 1%
1.0%
27
Evolution, Medicine, and Public Health
14 papers in training set
Top 0.2%
0.8%
28
BMC Ecology and Evolution
51 papers in training set
Top 1%
0.8%
29
Functional Ecology
61 papers in training set
Top 1%
0.8%
30
Heredity
64 papers in training set
Top 1%
0.8%