Biodiversity is unevenly distributed over time, space and the tree of life [1]. The fact that regions are richer than others as exemplified by the latitudinal diversity gradient has fascinated biologists as early as the first explorers travelled around the world [2]. Provincialism was one of the first general features of land biotic distributions noted by famous nineteenth century biologists like the phytogeographers J.D. Hooker and A. de Candolle, and the zoogeographers P.L. Sclater and A.R. Wallace [3]. When these explorers travelled among different places, they were struck by the differences in their biotas (e.g. [4]). The limited distributions of distinctive endemic forms suggested a history of local origin and constrained dispersal. Much biogeographic research has been devoted to identifying areas where groups of organisms originated and began their initial diversification [3]. Complementary efforts found evidence of both historical barriers that blocked the exchange of organisms between adjacent regions and historical corridors that allowed dispersal between currently isolated regions. The result has been a division of the Earth into a hierarchy of regions reflecting patterns of faunal and floral similarities (e.g. regions, subregions, provinces). Therefore a first ensuing question is: “how regional species pools have been assembled through time and space?”, which can be followed by a second question: “what are the ecological and evolutionary processes leading to differences in species richness among species pools?”.

To address these questions, the study of Calatayud et al. [5] developed and performed an interesting approach relying on phylogenetic data to identify regional and sub-regional pools of European beetles (using the iconic ground beetle genus Carabus). Specifically, they analysed the processes responsible for the assembly of species pools, by comparing the effects of dispersal barriers, niche similarities and phylogenetic history. They found that Europe could be divided in seven modules that group zoogeographically distinct regions with their associated faunas, and identified a transition zone matching the limit of the ice sheets at Last Glacial Maximum (19k years ago). Deviance of species co-occurrences across regions, across sub-regions and within each region was significantly explained, primarily by environmental niche similarity, and secondarily by spatial connectivity, except for northern regions. Interestingly, southern species pools are mostly separated by dispersal barriers, whereas northern species pools are mainly sorted by their environmental niches. Another important finding of Calatayud et al. [5] is that most phylogenetic structuration occurred during the Pleistocene, and they show how extreme recent historical events (Quaternary glaciations) can profoundly modify the composition and structure of geographic species pools, as opposed to studies showing the role of deep-time evolutionary processes.

The study of biogeographic assembly of species pools using phylogenies has never been more exciting and promising than today. Catalayud et al. [5] brings a nice study on the importance of Pleistocene glaciations along with geographical barriers and niche-based processes in structuring the regional faunas of European beetles. The successful development of powerful analytical tools in recent years, in conjunction with the rapid and massive increase in the availability of biological data (including molecular phylogenies, fossils, georeferrenced occurrences and ecological traits), will allow us to disentangle complex evolutionary histories. Although we still face important limitations in data availability and methodological shortcomings, the last decade has witnessed an improvement of our understanding of how historical and biotic triggers are intertwined on shaping the Earth’s stupendous biological diversity. I hope that the Catalayud et al.’s approach (and analytical framework) will help movement in that direction, and that it will provide interesting perspectives for future investigations of other regions. Applied to a European beetle radiation, they were able to tease apart the relative contributions of biotic (niche-based processes) versus abiotic (geographic barriers and climate change) factors.

References

[1] Rosenzweig ML. 1995. Species diversity in space and time. Cambridge: Cambridge University Press.
[2] Mittelbach GG, Schemske DW, Cornell HV, Allen AP, Brown JM et al. 2007. Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography. Ecology Letters. 10: 315–331. doi: 10.1111/j.1461-0248.2007.01020.x
[3] Lomolino MV, Riddle BR, Whittaker RJ and Brown JH. 2010. Biogeography, 4th edn. Sinauer Associates, Inc., Sunderland, MA.
[4] Wallace AR. 1876. The geographical distribution of animals: with a study of the relations of living and extinct faunas as elucidating the past changes of the earth's surface. New York: Harper and Brothers, Publishers.
[5] Calatayud J, Rodríguez MÁ, Molina-Venegas R, Leo M, Hórreo JL and Hortal J. 2018. Pleistocene climate change and the formation of regional species pools. bioRxiv 149617 ver. 4 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/149617

Studying the evolution of animal cognition is challenging because many environmental and species-related factors can be intertwined, which is further complicated when looking at deep-time evolution. Previous knowledge has emphasized the role of intraspecific interactions in affecting the socio-ecological environment shaping cognition. However, much less is known about such an effect at the interspecific level. Yet, the coexistence of different species in the same geographic area at a given time (sympatry) can impact the evolutionary history of species through character displacement due to biotic interactions. Trait evolution has been observed and tested with morphological external traits but more rarely with brain evolution. Compared to most species’ traits, brain evolution is even more delicate to assess since specific brain regions can be involved in different functions, may they be individual-based and social-based information processing. 

In a very original and thoroughly executed study, Robira & Perez-Lamarque (2023) addressed the question: How does the co-occurrence of congeneric species shape brain evolution and influence species diversification? By considering brain size as a proxy for cognition, they evaluated whether species sympatry impacted the evolution of cognition in frugivorous primates. Fruit resources are hard to find, not continuous through time, heterogeneously distributed across space, but can be predictable. Hence, cognition considerably shapes the foraging strategy and competition for food access can be fierce. Over long timescales, it remains unclear whether brain size and the pace of species diversification are linked in the context of sympatry, and if so how. Recent studies have found that larger brain sizes can be associated with higher diversification rates in birds (Sayol et al. 2019). Similarly, Robira & Perez-Lamarque (2023) thus wondered if the evolution of brain size in primates impacted their dynamic of species diversification, which has been suggested (Melchionna et al. 2020) but not tested.

Prior to anything, Robira & Perez-Lamarque (2023) had to retrace the evolutionary history of sympatry between frugivorous primate lineages through time using the primate tree of life, species’ extant distribution, and process-based models to estimate ancestral range evolution. To infer the effect of species sympatry on the evolution of cognition in frugivorous primates, the authors evaluated the support for phylogenetic models of brain size evolution accounting or not for species sympatry and investigated the directionality of the selection induced by sympatry on brain size evolution. Finally, to better understand the impact of cognition and interactions between primates on their evolutionary success, they tested for correlations between brain size or species’ sympatry and species diversification.

Robira & Perez-Lamarque (2023) found that the evolution of the whole brain or brain regions used in immediate information processing was best fitted with models not considering sympatry. By contrast, models considering species sympatry best predicted the evolution of brain regions related to long-term memory of interactions with the socio-ecological environment, with a decrease in their size along with stronger sympatry. Specifically, they found that sympatry was associated with a decrease in the relative size of the hippocampus and striatum, but had no significant effect on the neocortex, cerebellum, or overall brain size.

The hippocampus is a brain region that plays a crucial role in processing and memorizing spatiotemporal information, which is relevant for frugivorous primates in their foraging behavior. The study suggests that competition between sympatric species for limited food resources may lead to a more complex and unpredictable food distribution, which may in turn render cognitive foraging not advantageous and result in a selection for smaller brain regions involved in foraging. Niche partitioning and dietary specialization in sympatry may also impact cognitive abilities, with more specialized diets requiring lower cognitive abilities and smaller brain region sizes.

On the other hand, the absence of an effect of sympatry on brain regions involved in immediate sensory information processing, such as the cerebellum and neocortex, suggests that foragers do not exploit cues left out by sympatric heterospecific species, or they may discard environmental cues in favor of social cues.

This is a remarkable study that highlights the importance of considering the impact of ecological factors, such as sympatry, on the evolution of specific brain regions involved in cognitive processes, and the potential trade-offs in brain region size due to niche partitioning and dietary specialization in sympatry. Further research is needed to explore the mechanisms behind these effects and to test for the possible role of social cues in the evolution of brain regions. This study provides insights into the selective pressures that shape brain evolution in primates.

References

Melchionna M, Mondanaro A, Serio C, Castiglione S, Di Febbraro M, Rook L, Diniz-Filho JAF, Manzi G, Profico A, Sansalone G, Raia P (2020) Macroevolutionary trends of brain mass in Primates. Biological Journal of the Linnean Society, 129, 14–25. https://doi.org/10.1093/biolinnean/blz161

Robira B, Perez-Lamarque B (2023) Primate sympatry shapes the evolution of their brain architecture. bioRxiv, 2022.05.09.490912, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.05.09.490912

Sayol F, Lapiedra O, Ducatez S, Sol D (2019) Larger brains spur species diversification in birds. Evolution, 73, 2085–2093. https://doi.org/10.1111/evo.13811

Sometimes, important factors for explaining biological processes fall through the cracks, and it is only through careful modeling that their importance eventually comes out to light. In this study, Barroso and Dutheil introduce a new method based on the sequentially Markovian coalescent (SMC, Marjoran and Wall 2006) for jointly estimating local recombination and coalescent rates along a genome. Unlike previous SMC-based methods, however, their method can also co-estimate local patterns of variation in mutation rates. 

This is a powerful improvement which allows them to tackle questions about the reasons for the extensive variation in nucleotide diversity across the chromosomes of a species - a problem that has plagued the minds of population geneticists for decades (Begun and Aquadro 1992, Andolfatto 2007, McVicker et al., 2009, Pouyet and Gilbert 2021). The authors find that variation in de novo mutation rates appears to be the most important factor in determining nucleotide diversity in Drosophila melanogaster. Though seemingly contradicting previous attempts at addressing this problem (Comeron 2014), they take care to investigate and explain why that might be the case.

Barroso and Dutheil have also taken care to carefully explain the details of their new approach and have carried a very thorough set of analyses comparing competing explanations for patterns of nucleotide variation via causal modeling. The reviewers raised several issues involving choices made by the authors in their analysis of variance partitioning, the proper evaluation of the role of linked selection and the recombination rate estimates emerging from their model. These issues have all been extensively addressed by the authors, and their conclusions seem to remain robust. The study illustrates why the mutation landscape should not be ignored as an important determinant of local variation in genetic diversity, and opens up questions about the generalizability of these results to other organisms.

REFERENCES

Andolfatto, P. (2007). Hitchhiking effects of recurrent beneficial amino acid substitutions in the Drosophila melanogaster genome. Genome research, 17(12), 1755-1762. https://doi.org/10.1101/gr.6691007

Barroso, G. V., & Dutheil, J. Y. (2021). The landscape of nucleotide diversity in Drosophila melanogaster is shaped by mutation rate variation. bioRxiv, 2021.09.16.460667, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.09.16.460667

Begun, D. J., & Aquadro, C. F. (1992). Levels of naturally occurring DNA polymorphism correlate with recombination rates in D. melanogaster. Nature, 356(6369), 519-520. https://doi.org/10.1038/356519a0

Comeron, J. M. (2014). Background selection as baseline for nucleotide variation across the Drosophila genome. PLoS Genetics, 10(6), e1004434. https://doi.org/10.1371/journal.pgen.1004434

Marjoram, P., & Wall, J. D. (2006). Fast" coalescent" simulation. BMC genetics, 7, 1-9. https://doi.org/10.1186/1471-2156-7-16

McVicker, G., Gordon, D., Davis, C., & Green, P. (2009). Widespread genomic signatures of natural selection in hominid evolution. PLoS genetics, 5(5), e1000471. https://doi.org/10.1371/journal.pgen.1000471

Pouyet, F., & Gilbert, K. J. (2021). Towards an improved understanding of molecular evolution: the relative roles of selection, drift, and everything in between. Peer Community Journal, 1, e27. https://doi.org/10.24072/pcjournal.16

The evolution of mutualistic symbiosis is a puzzle that has fascinated evolutionary ecologist for quite a while. Data on transitions between symbiotic bacterial ways of life has evidenced shifts from mutualism towards parasitism and vice versa (Sachs et al., 2011), so there does not seem to be a strong determinism on those transitions. From the host’s perspective, mutualistic symbiosis implies at the very least some form of immune tolerance, which can be costly (e.g. Sorci, 2013). Empirical approaches thus raise very important questions: How can symbiosis turn from parasitism into mutualism when it seemingly needs such a strong alignment of selective pressures on both the host and the symbiont? And yet why is mutualistic symbiosis so widespread and so important to the evolution of macro-organisms (Margulis, 1998)?

While much of the theoretical literature on the evolution of symbiosis and mutualism has focused on either the stability of such relationships when non-mutualists can invade the host-symbiont system (e.g. Ferrière et al., 2007) or the effect of the mode of symbiont transmission on the evolutionary dynamics of mutualism (e.g. Genkai-Kato and Yamamura, 1999), the question remains whether and under which conditions parasitic symbiosis can turn into mutualism in the first place. Earlier results suggested that spatial demographic heterogeneity between host populations could be the leading determinant of evolution towards mutualism or parasitism (Hochberg et al., 2000). Here, Ledru et al. (2022) investigate this question in an innovative way by simulating host-symbiont evolutionary dynamics in a spatially explicit context. Their hypothesis is intuitive but its plausibility is difficult to gauge without a model: Does the evolution towards mutualism depend on the ability of the host and symbiont to evolve towards close-range dispersal in order to maintain clusters of efficient host-symbiont associations, thus outcompeting non-mutualists?

I strongly recommend reading this paper as the results obtained by the authors are very clear: competition strength and the cost of dispersal both affect the likelihood of the transition from parasitism to mutualism, and once mutualism has set in, symbiont trait values clearly segregate between highly dispersive parasites and philopatric mutualists. The demonstration of the plausibility of their hypothesis is accomplished with brio and thoroughness as the authors also examine the conditions under which the transition can be reversed, the impact of the spatial range of competition and the effect of mortality. Since high dispersal cost and strong, long-range competition appear to be the main factors driving the evolutionary transition towards mutualistic symbiosis, now is the time for empiricists to start investigating this question with spatial structure in mind.

References

Ferrière, R., Gauduchon, M. and Bronstein, J. L. (2007) Evolution and persistence of obligate mutualists and exploiters: competition for partners and evolutionary immunization. Ecology Letters, 10, 115-126. https://doi.org/10.1111/j.1461-0248.2006.01008.x

Genkai-Kato, M. and Yamamura, N. (1999) Evolution of mutualistic symbiosis without vertical transmission. Theoretical Population Biology, 55, 309-323. https://doi.org/10.1006/tpbi.1998.1407

Hochberg, M. E., Gomulkiewicz, R., Holt, R. D. and Thompson, J. N. (2000) Weak sinks could cradle mutualistic symbioses - strong sources should harbour parasitic symbioses. Journal of Evolutionary Biology, 13, 213-222. https://doi.org/10.1046/j.1420-9101.2000.00157.x

Ledru L, Garnier J, Rohr M, Noûs C and Ibanez S (2022) Mutualists construct the ecological conditions that trigger the transition from parasitism. bioRxiv, 2021.08.18.456759, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.08.18.456759

Margulis, L. (1998) Symbiotic planet: a new look at evolution, Basic Books, Amherst.

Sachs, J. L., Skophammer, R. G. and Regus, J. U. (2011) Evolutionary transitions in bacterial symbiosis. Proceedings of the National Academy of Sciences, 108, 10800-10807. https://doi.org/10.1073/pnas.1100304108

Sorci, G. (2013) Immunity, resistance and tolerance in bird–parasite interactions. Parasite Immunology, 35, 350-361. https://doi.org/10.1111/pim.12047

Plastic responses of organisms to their environment may be maladaptive in particular when organisms are exposed to new environments. Phenotypic plasticity may also have opposite effects on the adaptive response of organisms to environmental changes: whether phenotypic plasticity favors or hinders such adaptation depends on a balance between the ability of the population to respond to the change non-genetically in the short term, and the weakened genetic response to environmental change. These topics have received continued attention, particularly in the context of climate change (e.g., Chevin et al. 2013, Duputié et al., 2015, Vinton et al . 2022).

In their work, Ledru et al. focus on the adaptive nature of plastic behavior and on its consequences in a consumer-resource ecosystem. As they emphasize, previous works have found that plastic foraging promotes community stability, but these did not consider plasticity as an evolving trait, so Ledru et al. set out to test whether this conclusion holds when both plastic foraging and niche traits of consumers and resources evolve (though ultimately, their new conclusions may not all depend on plasticity evolving). Along the way, they first seek to clarify when such plasticity will evolve, and how it affects the evolution of the niche diversity of consumers and resources, before turning to the question of consumer persistence. 

The model is rather complex, as three traits are allowed to evolve, and the resource uptake expressed through plastic behavior has its own dynamics affected by some form of social learning. Classically, in models of niche evolution, a consumer's efficiency in exploiting a resource characterized by a trait y (here, the resource's individual niche trait), has been described in terms of location-scale (typically Gaussian) kernels, with mean x (the consumer's individual niche trait) specifying the most efficiently exploited resource, and with variance characterizing individual niche breadth. The evolution of the variance has been considered in some previous models but is assumed to be fixed here.  Rather, the new model considers the evolution of the distribution of resource traits, of the consumer's individual niche trait (which is not plastic), and of a "plastic foraging trait" that controls the relative time spent foraging plastically versus foraging randomly. When foraging plastically, the consumers modify their foraging effort towards the type of resource that maximizes their energy intake. in some previous models, the effect of variation in the extent of plastic foraging was already considered, but the evolution of allocation to a plastic foraging strategy versus random foraging was not considered. The model is formulated through reaction-diffusion equations, and its dynamics is investigated by numerical integration.

Foraging plasticity readily evolves, when resources vary widely enough, competition for resources is strong, and the cost of plasticity is weak. This means in particular that a large individual niche width of consumers selects for increased plastic foraging, as the evolution of plastic foraging leads to reduced niche overlap between consumers. The evolution of plastic foraging itself generally, though not always, favors the diversification of the niche traits of consumers and of resources. There is thus a positive feedback loop between plastic foraging and resource diversity. Ledru et al. conclude that the total niche width of the consumer population should also correlate with the evolution of plastic foraging, an implication which they relate to the so-called niche variation hypothesis and to empirical tests of it. 

The joint evolution of the consumer's individual niche trait and plastic foraging trait generates a striking pattern within populations: consumers whose individual niche trait is at an edge of the resource distribution forage more plastically. The authors observe that this relatively simple prediction has not been subjected to any empirical test. 

Returning to the question of consumer persistence, Ledru et al. evaluate this persistence when consumer mortality increases, and in response to either gradual or sudden environmental changes. These different perturbations all reduce the benefits of plastic foraging. The effect of plastic foraging on stability are complex, being negative or positive effect depending on the type of disturbance, and in particular the ecosystem has a lower sustainable rate of environmental change in the presence of plastic foraging. However, allowing the evolutionary regression of plastic foraging then has a comparatively positive effect on persistence.

Despite the substantial effort devoted to analyzing this complex model, relaxing some of its assumptions would likely reveal further complexities. Notably, the overall effect of plasticity on consumer persistence depends on effects already encountered in models of the adaptive response of single species to environmental change: a fast non-genetic response in the short term versus a weakened genetic response in the longer term. The overall balance between these opposite effects on adaptation may be difficult to predict robustly. In the case of a constant rate of environmental change, the results of the present model depend on a lag load between the trait changes of consumer and resource populations, and the extent of the lag may also depend on many factors, such as the extent of genetic variation (e.g., Bürger & Lynch, 1995) for niche traits in consumers and resources. Here, the same variance of mutational effects was assumed for all three evolving traits. Further, spatial environmental variation, a central issue in studies of adaptive responses to environmental changes (e.g., Parmesan, 2006, Zhu et al., 2012), was not considered. Finally, the rate of adjustment of effort by consumers with given niche trait and plastic foraging trait values was assumed proportional to the density of consumers with such trait values. This was justified as a way of accounting for the use of social cues during foraging, but to the extent that they occur, social effects could manifest themselves through other learning dynamics. 

In conclusion, Ledru et al. have addressed a broad range of questions, suggesting new empirical tests of behavioural patterns on one side, and recovering in the context of community response to environmental changes a complexity that could be expected from earlier works on adaptive responses of organisms but that has been overlooked by previous works on community effects of phenotypic plasticity.

References

Bürger, R. and Lynch, M. (1995), Evolution and extinction in a changing environment: a quantitative-genetic analysis. Evolution, 49: 151-163. https://doi.org/10.1111/j.1558-5646.1995.tb05967.x

Chevin, L.-M., Collins, S. and Lefèvre, F. (2013), Phenotypic plasticity and evolutionary demographic responses to climate change: taking theory out to the field. Funct Ecol, 27: 967-979. https://doi.org/10.1111/j.1365-2435.2012.02043.x

Duputié, A., Rutschmann, A., Ronce, O. and Chuine, I. (2015), Phenological plasticity will not help all species adapt to climate change. Glob Change Biol, 21: 3062-3073. https://doi-org.inee.bib.cnrs.fr/10.1111/gcb.12914

Ledru, L., Garnier, J., Guillot, O., Faou, E., & Ibanez, S. (2023). The evolutionary dynamics of plastic foraging and its ecological consequences: a resource-consumer model. EcoEvoRxiv, ver. 4 peer-reviewed and recommended by Peer Community In Evolutionary Biology. https://doi.org/10.32942/X2QG7M

Parmesan, C. (2006) Ecological and evolutionary responses to recent climate change
Annual Review of Ecology, Evolution, and Systematics 2006 37:1, 637-669. https://doi.org/10.1146/annurev.ecolsys.37.091305.110100

Vinton, A.C., Gascoigne, S.J.L., Sepil, I., Salguero-Gómez, R., (2022) Plasticity’s role in adaptive evolution depends on environmental change components. Trends in Ecology & Evolution, 37: 1067-1078.
https://doi.org/10.1016/j.tree.2022.08.008

Zhu, K., Woodall, C.W. and Clark, J.S. (2012), Failure to migrate: lack of tree range expansion in response to climate change. Glob Change Biol, 18: 1042-1052. https://doi.org/10.1111/j.1365-2486.2011.02571.x