The study of the evolution of sociality is closely associated with the study of the evolution of sensory systems. Indeed, group life and sociality necessitate that individuals recognize each other and detect outsiders, as seen in eusocial insects such as Hymenoptera. While we know that antennal sense organs that are involved in olfactory perception are found in greater densities in social species of that group compared to solitary hymenopterans, whether this among-species correlation represents the consequence of social evolution leading to sensory evolution, or the opposite, is still questioned. Knowing more about how sociality and sensory abilities covary within a species would help us understand the evolutionary sequence. Studying a species that shows social plasticity, that is facultatively social, would further allow disentangling the cause and consequence of social evolution and sensory systems and the implication of plasticity in the process.

Boulton and Field (2022) studied a species of sweat bee that shows social plasticity, Halictus rubicundus. They studied populations at different latitudes in Great Britain: populations in the North are solitary, while populations in the south often show sociality, as they face a longer and warmer growing season, leading to the opportunity for two generations in a single year, a pre-condition for the presence of workers provisioning for the (second) brood. Using scanning electron microscope imaging, the authors compared the density of antennal sensilla types in these different populations (north, mid-latitude, south) to test for an association between sociality and olfactory perception capacities. They counted three distinct types of antennal sensilla: olfactory plates, olfactory hairs, and thermos/hygro-receptive pores, used to detect humidity, temperature and CO2. In addition, they took advantage of facultative sociality in this species by transplanting individuals from a northern population (solitary) to a southern location (where conditions favour sociality), to study how social plasticity is reflected (or not) in the density of antennal sensilla types. They tested the prediction that olfactory sensilla density is also developmentally plastic in this species.

Their results show that antennal sensilla counts differ between the 3 studied regions (north, mid-latitude, south), but not as predicted. Individuals in the southern population were not significantly different from the mid-latitude and northern ones in their count of olfactory plates and they had less, not more, thermos/hygro receptors than mid-latitude and northern individuals. Furthermore, mid-latitude individuals had more olfactory hairs than the ones from the northern population and did not differ from southern ones. The prediction was that the individuals expressing sociality would have the highest count of these olfactory hairs. This unpredicted pattern based on the latitude of sampling sites may be due to the effect of temperature during development, which was higher in the mid-latitude site than in the southern one. It could also be the result of a genotype-by-environment interaction, where the mid-latitude population has a different developmental response to temperature compared to the other populations, a difference that is genetically determined (a different “reaction norm”). Reciprocal transplant experiments coupled with temperature measurements directly on site would provide interesting information to help further dissect this intriguing pattern. 

Interestingly, where a sweat bee developed had a significant effect on their antennal sensilla counts: individuals originating from the North that developed in the south after transplantation had significantly more olfactory hairs on their antenna than individuals from the same Northern population that developed in the North. This is in accordance with the prediction that the characteristics of sensory organs can also be plastic. However, there was no difference in antennal characteristics depending on whether these transplanted bees became solitary or expressed the social phenotype (foundress or worker). This result further supports the hypothesis that temperature affects development in this species and that these sensory characteristics are also plastic, although independently of sociality. Overall, the work of Boulton and Field underscores the importance of including phenotypic plasticity in the study of the evolution of social behaviour and provides a robust and fruitful model system to explore this further.

References

Boulton RA, Field J (2022) Sensory plasticity in a socially plastic bee. bioRxiv, 2022.01.29.478030, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.01.29.478030

Spatial genetic structure, i.e. the non-random spatial distribution of genotypes, arises in populations because of different processes including spatially limited dispersal and selection. Knowledge on the spatial genetic structure of plant populations is important to assess biological parameters such as gene dispersal distances and the potential for local adaptations, as well as for applications in conservation management and breeding. In their work, Niskanen and colleagues demonstrate a multifaceted approach to characterise the spatial genetic structure in two replicate sites of a continuously distributed Scots pine population in South-Eastern Finland. They mapped and assessed the ages of 469 naturally regenerated adults and genotyped them using a SNP array which resulted in 157 325 filtered polymorphic SNPs. Their dataset is remarkably powerful because of the large numbers of both individuals and SNPs genotyped. This made it possible to characterise precisely the decay of genetic relatedness between individuals with spatial distance despite the extensive dispersal capacity of Scots pine through pollen, and ensuing expectations of an almost panmictic population.

The authors’ data analysis was particularly thorough. They demonstrated that two metrics of pairwise relatedness, the genomic relationship matrix (GRM, Yang et al. 2011) and the kinship coefficient (Loiselle et al. 1995) were strongly correlated and produced very similar inference of family relationships: >99% of pairs of individuals were unrelated, and the remainder exhibited 2nd (e.g., half-siblings) to 4th degree relatedness. Pairwise relatedness decayed with spatial distance which resulted in extremely weak but statistically significant spatial genetic structure in both sites, quantified as Sp=0.0005 and Sp=0.0008. These estimates are at least an order of magnitude lower than estimates in the literature obtained in more fragmented populations of the same species or in other conifers. Estimates of the neighbourhood size, the effective number of potentially mating individuals belonging to a within-population neighbourhood (Wright 1946), were relatively large with Nb=1680-3210 despite relatively short gene dispersal distances, σg = 36.5–71.3m, which illustrates the high effective density of the population. 

The authors showed the implications of their findings for selection. The capacity for local adaptation depends on dispersal distances and the strength of the selection coefficient. In the study population, the authors inferred that local adaptation can only occur if environmental heterogeneity occurs over a distance larger than approximately one kilometre (or larger, if considering long-distance dispersal). Interestingly, in Scots pine, no local adaptation has been described on similar geographic scales, in contrast to some other European or Mediterranean conifers (Scotti et al. 2023).

The authors’ results are relevant for the management of conservation and breeding. They showed that related individuals occurred within sites only and that they shared a higher number of rare alleles than unrelated ones. Since rare alleles are enriched in new and recessive deleterious variants, selecting related individuals could have negative consequences in breeding programmes. The authors also showed, in their response to reviewers, that their powerful dataset was not suitable to obtain a robust estimate of effective population size, Ne, based on the linkage disequilibrium method (Do et al. 2014). This illustrated that the estimation of Ne used for genetic indicators supported in international conservation policy (Hoban et al. 2020, CBD 2022) remains challenging in large and continuous populations (see also Santo-del-Blanco et al. 2023, Gargiulo et al. 2024).

References

CBD (2022) Kunming-Montreal Global Biodiversity Framework. https://www.cbd.int/doc/decisions/cop-15/cop-15-dec-04-en.pdf

Do C, Waples RS, Peel D, Macbeth GM, Tillett BJ, Ovenden JR (2014). NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data. Molecular Ecology Resources 14: 209–214. https://doi.org/10.1111/1755-0998.12157

Gargiulo R, Decroocq V, González-Martínez SC, Paz-Vinas I, Aury JM, Kupin IL, Plomion C, Schmitt S, Scotti I, Heuertz M (2024) Estimation of contemporary effective population size in plant populations: limitations of genomic datasets. Evolutionary Applications, in press, https://doi.org/10.1101/2023.07.18.549323

Hoban S, Bruford M, D’Urban Jackson J, Lopes-Fernandes M, Heuertz M, Hohenlohe PA, Paz-Vinas I, et al. (2020) Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biological Conservation 248: 108654. https://doi.org/10.1016/j.biocon.2020.108654

Loiselle BA, Sork VL, Nason J & Graham C (1995) Spatial genetic structure of a tropical understorey shrub, Psychotria officinalis (Rubiaceae). American Journal of Botany 82: 1420–1425. https://doi.org/10.1002/j.1537-2197.1995.tb12679.x

Santos-del-Blanco L, Olsson S, Budde KB, Grivet D, González-Martínez SC, Alía R, Robledo-Arnuncio JJ (2022). On the feasibility of estimating contemporary effective population size (Ne) for genetic conservation and monitoring of forest trees. Biological Conservation 273: 109704. https://doi.org/10.1016/j.biocon.2022.109704

Scotti I, Lalagüe H, Oddou-Muratorio S, Scotti-Saintagne C, Ruiz Daniels R, Grivet D, et al. (2023) Common microgeographical selection patterns revealed in four European conifers. Molecular Ecology 32: 393-411. https://doi.org/10.1111/mec.16750

Wright S (1946) Isolation by distance under diverse systems of mating. Genetics 31: 39–59. https://doi.org/10.1093/genetics/31.1.39

Yang J, Lee SH, Goddard ME & Visscher PM (2011) GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics 88: 76–82. https://www.cell.com/ajhg/pdf/S0002-9297(10)00598-7.pdf

Tropical biodiversity is immense, under enormous threat, and yet still poorly understood. Global climatic breakdown and habitat destruction are impacting on and removing this diversity before we can understand how the biota responds to such changes, or even fully appreciate what we are losing [1]. This is particularly the case for woody shrubs and trees [2] and for the flora of tropical Africa [3].  

Helmstetter et al. [4] have taken a significant step to improve our understanding of African tropical tree diversity in the context of past climatic change. They have done so by means of a remarkably in-depth analysis of one species of the tropical plant family Annonaceae: Annickia affinis [5]. A. affinis shows a distribution pattern in Africa found in various plant (but interestingly not animal) groups: a discontinuity between north and south of the equator [6]. There is no obvious physical barrier to cause this discontinuity, but it does correspond with present day distinct northern and southern rainy seasons. Various explanations have been proposed for this discontinuity, set out as hypotheses to be tested in this paper: climatic fluctuations resulting in changes in plant distributions in the Pleistocene, or differences in flowering times or in ecological niche between northerly and southerly populations. These explanations are not mutually exclusive, but they can be tested using phylogenetic inference – if you can sample variable enough sequence data from enough individuals – complemented with analysis of ecological niches and traits.  

Using targeted sequence capture, the authors amassed a dataset representing 351 nuclear markers for 112 individuals of A. affinis. This dataset is impressive for a number of reasons: First, sampling such a species across such a wide range in tropical Africa presents numerous challenges of itself. Second, the technical achievement of using this still relatively new sequencing technique with a custom set of baits designed specifically for this plant family [7] is also considerable. The result is a volume of data that just a few years ago would not have been feasible to collect, and which now offers the possibility to meaningfully analyse DNA sequence variation within a species across numerous independent loci of the nuclear genome. This is the future of our research field, and the authors have ably demonstrated some of its possibilities.  

Using this data, they performed on the one hand different population genetic clustering approaches, and on the other, different phylogenetic inference methods. I would draw attention to their use and comparison of coalescence and network-based approaches, which can account for the differences between gene trees that might be expected between populations of a single species. The results revealed four clades and a consistent sequence of divergences between them. The authors inferred past shifts in geographic range (using a continuous state phylogeographic model), depicting a biogeographic scenario involving a dispersal north over the north/south discontinuity; and demographic history, inferring in some (but not all) lineages increases in effective population size around the time of the last glacial maximum, suggestive of expansion from refugia. Using georeferenced specimen data, they compared ecological niches between populations, discovering that overlap was indeed smallest comparing north to south. Just the phenology results were effectively inconclusive: far better data on flowering times is needed than can currently be harvested from digitised herbarium specimens.  

Overall, the results add to the body of evidence for the impact of Pleistocene climatic changes on population structure, and for niche differences contributing to the present day north/south discontinuity. However, they also paint a complex picture of idiosyncratic lineage-specific responses, even within a single species. With the increasing accessibility of the techniques used here we can look forward to more such detailed analyses of independent clades necessary to test and to expand on these conclusions, better to understand the nature of our tropical plant diversity while there is still opportunity to preserve it for future generations.  

References

[1] Mace, G. M., Gittleman, J. L., and Purvis, A. (2003). Preserving the Tree of Life. Science, 300(5626), 1707–1709. doi: 10.1126/science.1085510
[2] Humphreys, A. M., Govaerts, R., Ficinski, S. Z., Nic Lughadha, E., and Vorontsova, M. S. (2019). Global dataset shows geography and life form predict modern plant extinction and rediscovery. Nature Ecology and Evolution, 3(7), 1043–1047. doi: 10.1038/s41559-019-0906-2
[3] Stévart, T., Dauby, G., Lowry, P. P., Blach-Overgaard, A., Droissart, V., Harris, D. J., Mackinder, B. A., Schatz, G. E., Sonké, B., Sosef, M. S. M., Svenning, J. C., Wieringa, J. J., and Couvreur, T. L. P. (2019). A third of the tropical African flora is potentially threatened with extinction. Science Advances, 5(11), eaax9444. doi: 10.1126/sciadv.aax9444
[4] Helmstetter, A. J., Amoussou, B. E. N., Bethune, K., Kandem, N. G., Kakaï, R. G., Sonké, B., and Couvreur, T. L. P. (2020). Phylogenomic approaches reveal how a climatic inversion and glacial refugia shape patterns of diversity in an African rain forest tree species. BioRxiv, 807727, ver. 3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/807727
[5] Versteegh, C. P. C., and Sosef, M. S. M. (2007). Revision of the African genus Annickia (Annonaceae). Systematics and Geography of Plants, 77, 91–118.
[6] Hardy, O. J., Born, C., Budde, K., Daïnou, K., Dauby, G., Duminil, J., Ewédjé, E.-E. B. K., Gomez, C., Heuertz, M., Koffi, G. K., Lowe, A. J., Micheneau, C., Ndiade-Bourobou, D., Piñeiro, R., and Poncet, V. (2013). Comparative phylogeography of African rain forest trees: A review of genetic signatures of vegetation history in the Guineo-Congolian region. Comptes Rendus Geoscience, 345(7), 284-296. doi: 10.1016/j.crte.2013.05.001
[7] Couvreur, T. L. P., Helmstetter, A. J., Koenen, E. J. M., Bethune, K., Brandão, R. D., Little, S. A., Sauquet, H., and Erkens, R. H. J. (2019). Phylogenomics of the Major Tropical Plant Family Annonaceae Using Targeted Enrichment of Nuclear Genes. Frontiers in Plant Science, 9. doi: 10.3389/fpls.2018.01941

150 years after Darwin published ‘Descent of man and selection in relation to sex’ (Darwin, 1871), the evolutionary mechanism that he laid out in his treatise continues to fascinate us. Sexual selection is responsible for some of the most spectacular traits among animals, and plants, and it appeals to our interest in all things reproductive and sexual (Bell, 1982). In addition, sexual selection poses some of the more intractable problems in evolutionary biology: Its realm encompasses traits that are subject to markedly different selection pressures, particularly when distinct, yet associated, traits tend to be associated with males, e.g. courtship signals, and with females, e.g. preferences (cf. Ah-King & Ahnesjo, 2013). While separate, such traits cannot evolve independently of each other (Arnqvist & Rowe, 2005), and complex feedback loops and correlations between them are predicted (Greenfield et al., 2014). Traditionally, sexual selection has been modelled under simplifying assumptions, and quantitative genetic approaches that avoided evolutionary dynamics have prevailed. New computing methods may be able to free the field from these constraints, and a trio of theoreticians (Chevalier, De Coligny & Labonne 2020) describe here a novel application of a ‘demo-genetic agent (or individual) based model’, a mouthful hereafter termed DG-ABM, for arriving at a holistic picture of the sexual selection trajectory. The application is built on the premise that traits, e.g. courtship, preference, gamete investment, competitiveness for mates, can influence the genetic architecture, e.g. correlations, of those traits. In turn, the genetic architecture can influence the expression and evolvability of the traits. Much of this influence occurs via demographic features, i.e. social environment, generated by behavioral interactions during sexual advertisement, courtship, mate guarding, parental care, post-mating dispersal, etc.
The authors provide a lengthy verbal description of their model, specifying the genomic and behavioral parameters that can be set and how a ‘run’ may be initialized. There is a link to an internet site where users can then enter their own parameter values and begin exploring hypotheses. Back in the article several simulations illustrate simple tests; e.g. how gamete investment and preference jointly evolve given certain survival costs. One obvious test would have been the preference – courtship genetic correlation that represents the core of Fisherian runaway selection, and it is regrettable that it was not examined under a range of demographic parameters. As presented the author’s DG-ABM appears particularly geared toward mating systems in ‘higher’ vertebrates, where couples form during a discrete mating season and are responsible for most reproduction. It is not clear how applicable the model could be to a full range of mating systems and nuances, including those in arthropods and other invertebrates as well as plants.
What is the likely value of the DG-ABM for sexual selection researchers? We will not be able to evaluate its potential impact until readers with specialized understanding of a question and taxon begin exploring and comparing their results with prior expectations. Of course, lack of congruence with earlier predictions would not invalidate the model. Hopefully, some of these specialists will have opportunities for comparing results with pertinent empirical data.

References

Ah-King, M. and Ahnesjo, I. 2013. The ‘sex role’ concept: An overview and evaluation Evolutionary Biology, 40, 461-470. doi: https://doi.org/10.1007/s11692-013-9226-7
Arnqvist, G. and Rowe, L. 2005. Sexual Conflict. Princeton University Press, Princeton. doi: https://doi.org/10.1515/9781400850600
Bell, G. 1982. The Masterpiece of Nature: The Evolution and Genetics of Sexuality. University of California Press, Berkeley.
Chevalier, L., De Coligny, F. and Labonne, J. (2020) A demogenetic individual based model for the evolution of traits and genome architecture under sexual selection. bioRxiv, 2020.04.01.014514, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: https://doi.org/10.1101/2020.04.01.014514
Darwin, C. 1871. The Descent of Man and Selection in Relation to Sex. J. Murray, London.
Greenfield, M.D., Alem, S., Limousin, D. and Bailey, N.W. 2014. The dilemma of Fisherian sexual selection: Mate choice for indirect benefits despite rarity and overall weakness of trait-preference genetic correlation. Evolution, 68, 3524-3536. doi: https://doi.org/10.1111/evo.12542

It has now been over a century since the American linguist Edward Sapir observed that there are no ‘primitive’ languages, stating ‘When it comes to linguistic form, Plato walks with the Macedonian swineherd, Confucius with the head-hunting savage of Assam’ (Sapir 1921, p. 104).  Nothing has been found among human groups since that would refute Sapir’s insight.  However, in interspecific comparisons among non-human animals, such equality is most definitely not the case, and scientists have asked what might account for some species being blessed with rich and complex communication while others seem to make do with a relatively undeveloped repertoire of signals.  Many of the investigations have focused on acoustic communications, as these are more easily identified as signals, measured, and demarcated than substrate vibrations, odors and optical displays.  But no consensus  has emerged explaining the ‘inequality among the lexicons’.

In the article ‘Colony size as the main driver of the evolution of song diversity and composition in weaverbirds’, Erwan Harscouet-Commecy and coauthors aimed to find definitive answers to the issue of interspecific differences in communication complexity.  The article considers two aspects of communication complexity, basic diversity – essentially the number of different sounds made by a species – and ‘composition’, a higher level measure centered on acoustically recognizable ‘types’ of sounds.  Sexual selection, social complexity, habitat and phylogeny are then examined as potential influences on communication.  Weaverbirds, the monophyletic family Ploceidae, including 122 species in 15 genera in sub-Saharan Africa and tropical Asia, was an eminently appropriate choice for the study.  The birds have diverse nesting and mating behavior and songs, and many have been investigated intensively.  For their analyses, the authors were quite rigorous in evaluating the species’ songs and in assessing the potential influences on song complexity.  Unexpectedly, they did not find that heightened sexual selection led to complex songs, but they note that the proxy used for sexual selection – a polygynous as opposed to a monogamous mating system – may be inaccurate.  Additionally, the strong pair bonding in monogamy may have actually selected for song complexity.  

What the authors did find was a very clear influence of social complexity, measured by colony size, and a secondary influence of phylogeny.  Questions do remain, such as the specific pathway – common genetic or common cultural heritage – along which phylogeny influences song complexity.  Another question one might raise is whether low song complexity in some species reflects reliance on other modalities of communication, e.g. plumage or movement displays.  But at present, the article appears as a gold standard for investigating the complexity of communication among animal species.    

References

Sapir, E. 1921.  Language: An Introduction to the Study of Speech.  New York: Harcourt, Brace.  ISBN 978-1-108-06378-4

E. Harscouet-Commecy, N. Adenot, A. Thetiot, N. Bresciani, D. Oschadleus, R. Covas, F. Rybak, C. Doutrelant (2024) Colony size as the main driver of the evolution of song diversity and composition in weaverbirds. OSF, ver.2 peer-reviewed and recommended by PCI Evol Biol https://doi.org/10.31219/osf.io/z5bgy_v2