Another step towards grasping the complexity of the environmental response of traits
Trait plasticity and covariance along a continuous soil moisture gradient
One can only hope that one day, we will be able to evaluate how the ecological complexity surrounding natural populations affects their ability to adapt. This is more like a long term quest than a simple scientific aim. Many steps are heading in the right direction. This paper by Monroe and colleagues (2021) is one of them.
Many ecological and genetic mechanisms shape the evolutionary potential of phenotypic trait variation and many of them involve environmental heterogeneity (Pujol et al 2018). To date, we cannot look into these ecological and genetic mechanisms without oversimplifying their effects. We often look into trait variation one trait at a time albeit the variation of multiple phenotypic traits is often linked at the genetic or environmental level. As a consequence, we put our conclusions at risk by not accounting for the reciprocal impacts of trait changes upon each other (Teplitsky et al 2014). We also usually restrict the study of a continuous gradient of environmental conditions to a few conditions because it would otherwise be impossible to model its environmental effect. As a consequence, we miss the full picture of the continuous often nonlinear phenotypic plastic response. Whether the trait undergo threshold effect changes thereby remains obscured to us. Collectively, these issues impede our ability to understand how selection shapes the ecological strategy of organisms under variable environments.
In this paper, Monroe and colleagues (2021) propose an original approach that raised to these two challenges. They analysed phenotypic plastic changes in response to a continuous environment in a multidimensional trait space, namely the response of Brachypodium plant developmental and physiological traits to a continuous gradient of soil moisture. They used dry down experimental treatments to produce the continuous soil moisture gradient and compared the plant capacity to use water between annual B. distachyon and perennial B. sylvaticum. Their results revealed the best mathematical functions that model the nonlinear curvature of the continuous plastic response of Brachypodium plants. This work reinforces our view that nonlinear plastic responses can result in greater or lesser trait values at any stage of the environmental gradient that were unexpected on the basis of linear predictors (Gienapp and Brommer 2014). Their findings also imply that different threshold responses characterize different genotypes. These could otherwise have been missed by a classical approach. By shedding light on unforeseen interactions between traits that make their correlation vary along the nonlinear response, they were able to describe more accurately Brachypodium ecological strategies and the changes in evolutionary constraints along the soil moisture gradient.
Their empirical approach allows to test what environmental conditions maximises the opportunity for selection to shape trait variation. For example, it revealed unforeseen divergence in potentially adaptive mechanisms or life history strategies – and not just trait values – between annual and perennial species of Brachypodium. Behind every environmental variation of the constraints to the future evolutionary change of multiple traits, we can expect that the evolutionary history of the populations shaped their trait genetic correlations. Investigating the nonlinear signature of adaptive evolution across continuous environments will get us into uncharted territory.
Our ability to predict the adaptive potential of species is limited. With their approach of continuous environmental gradients beyond linearity, Monroe and collaborators (2021) improve our understanding of plant phenotypic responses and open a brand new range of exciting developments. As they mention: "the opportunity for scaling up" their approach is big. To illustrate this prospect, I can easily think of an example: the quantitative genetic random regression model. This model allows to use any degree of genetic relatedness in a wild population to estimate the genetic variation of phenotypic plastic reaction norms (Nussey et al 2007, Pujol and Galaud 2013). However, in this approach, only a few modalities of the environmental gradient are used to model nonlinear phenotypic plastic responses. From there, it is rather intuitive. Combining the best of these two approaches (continuity of genetic relatedness in the wild & continuity of environmental gradient in experiments) could open ground breaking new perspectives in research.
Gienapp P. & J.E. Brommer. 2014. Evolutionary dynamics in response to climate change. In: Charmentier A, Garant D, Kruuk LEB, editors. Quantitative genetics in the wild. Oxford: Oxford University Press, Oxford. pp. 254–273. doi: https://doi.org/10.1093/acprof:oso/9780199674237.003.0015
Monroe, J. G., Cai, H., and Des Marais, D. L. (2020). Trait plasticity and covariance along a continuous soil moisture gradient. bioRxiv, 2020.02.17.952853, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: https://doi.org/10.1101/2020.02.17.952853
Pujol et al. (2018). The missing response to selection in the wild. Trends in ecology & evolution, 33(5), 337-346. doi: https://doi.org/10.1016/j.tree.2018.02.007
Pujol, B., and Galaud, J. P. (2013). A practical guide to quantifying the effect of genes underlying adaptation in a mixed genomics and evolutionary ecology approach. Botany Letters, 160(3-4), 197-204. doi: https://doi.org/10.1080/12538078.2013.799045
Nussey, D. H., Wilson, A. J., and Brommer, J. E. (2007). The evolutionary ecology of individual phenotypic plasticity in wild populations. Journal of evolutionary biology, 20(3), 831-844. doi: https://doi.org/10.1111/j.1420-9101.2007.01300.x
Teplitsky et al. (2014). Assessing multivariate constraints to evolution across ten long-term avian studies. PLoS One, 9(3), e90444. doi: https://doi.org/10.1371/journal.pone.0090444
Benoit Pujol (2021) Another step towards grasping the complexity of the environmental response of traits . Peer Community in Evolutionary Biology, 100119. 10.24072/pci.evolbiol.100119
Evaluation round #2
DOI or URL of the preprint: 10.1101/2020.02.17.952853
Version of the preprint: 1
Author's Reply, None
Decision by Benoit Pujol and Rodrigo Medel, 20 Dec 2020
the reviewers found your revision had addressed their comments. I think your paper deserves to be recommended. I neverthelless would ask a last very minor revision. Please incorporate the last few revisions required by the reviewers. I will very likely be able to assess your revised preprint without sending it out for further review this time, which should be fast. Looking forward to receiving your revision (I guess rapidly since there is not that much to do) and writting the recommendation (conditional to your revision of the preprint).
Regards, Benoit Pujol
REF1 : I really appreciate this manuscrit; I found it interesting and inspirational. The authors answered perfectly well to all my concerns. I only have one last comment, please make sure that all the figures and tables in the appendix are referenced in the main text (e.g. Fig S2, Table S2).
REF 2 : This is an updated/corrected version of a manuscript I previously reviewed. I think the authors have made a huge effort to keep the narrative of the study (more) focused, and made the statistical and biological interpretations easier to follow for the readers. The experiment the authors set up is super elegant to test a multivariate response (plasticity and evolutionary) to environmental gradients, as opposed to setting the classic anova approach. I have gone through the rebuttal letter and it appears that the authors have addressed my comments/concerns.
If anything, I would ask them to add some insights into how life-history traits and/or the ecological/environmental context in which the species evolved might influence the plastic or genetic (evolvability) response when species/genotypes encounter a "new" environment (or dimension) of their environment. Other than that, I think this is a great piece of work, the kind I would use in any evolutionary ecology/ecological genetics module.
I´ve added my comments in the PDF version of the manuscript. End of reviewDownload recommender's annotations
Reviewed by anonymous reviewer, 26 Nov 2020
Reviewed by anonymous reviewer, 07 Dec 2020
Evaluation round #1
DOI or URL of the preprint: 10.1101/2020.02.17.952853
Author's Reply, None
Decision by Benoit Pujol and Rodrigo Medel, 04 Jun 2020
Dear J Grey Monroe and collaborators,
Thank you for submitting your preprint to PCI Evolutionary Biology for recommendation. Two anonymous reviewers, Rodrigo Medel (co-recommender) and I, carefully read your preprint. We found your text was elegantly written. You present an interesting perspective on the way "function-valued traits" influence the response to selection through genetic correlations and plasticity. We think that the main framework needs to be emphasized earlier in the introduction section. In its present form, most of the general context relies on particular issues related with the study system, plant variables, and soil moisture gradients. This is fine, but expanding the context/implication presented in the second paragraph throughout the paper would add substantially to the scope of this contribution. We found the experts’ reviews very thorough and thoughtful and agree with their comments. We all agree that your manuscript addresses an important question: considering the continuity and non-linearity of soil moisture effects on plant morpho-physiological traits. We also found this manuscript quite valuable and would be inclined towards recommending it after consideration of comments by the authors. We hope that you will find our feedback useful to revise your manuscript.
Here are additional points that we identified.
1. One motivation of the paper is to assess the benefit of considering the continuous variation of soil moisture when evaluating the environmental response of the phenotype. Your point is that it brings a formally neglected layer of information that brings us one step closer to a more realistic assessment. I fully agree with this but I’m concerned about the presentation of the contextual background and the presentation of the implications of your work in the discussion. My concern comes from the fact that you do not “add up” a layer of detailed information to an otherwise realistic background. You rather proof test whether adding this environment as a continuous variable brings up useful information and you do this in an experimental simplified biological set up in order to properly proof test your hypothesis. Indeed, you use an experiment, a limited number of genetic lineages and summarise the continuous variation of the soil moisture to 6 modalities. This is not independent from another concern: It is sometimes clear, and sometimes less clear throughout the manuscript whether your contribution is specifically about “soil moisture” or whether you address a general issue that concerns all environmental variables. You want to revisit the text of the paper to clarify these aspects throughout the preprint so that no confusion is possible. It will bring value to the paper because your valuable contribution will be more clearly identified by readers as a result (and referred to).
2. An important implication of your work is that using environmental variables that are not continuous does not allow to observe nonlinear phenotypic responses. Missing such exponential or logarithmic responses has implications when predicting plant responses, in particular in the current context of climate changes. I totally agree with this and you could actually elaborate a bit more on this aspect and acknowledge more precisely similar work claiming the same message (eg work by Nussey, Wilson, Brommer who you cite, in wild populations, etc.).
3. You use quantitative genetic approaches and that brings value to this paper. However, the paper lacks contextual background about this aspect. You do not clearly state what are the methods used to assess continuous environmental effects (eg random regression quantitative genetic models) and whether they were used to assess environmental effects on plants. What are the differences and similarities with your approach (the aim is clearly the same)?
We would ultimately accept to recommend this preprint provided that you address these concerns and the reviewers’ comments appropriately.
4. The contrasting patterns of evolutionary constraints between species are quite impressive. I wonder to what extent this contrasting pattern associates to the contrasting life-history strategies as the authors assume, or rather represent non-random phylogenetic signals unrelated to life-history strategies. While this is clearly beyond the focus of the manuscript it would be nice to have additional information on the strategies followed by other populations or sister species to give stronger support to the idea of life-history related genetic constraints.
Benoit Pujol and Rodrigo Medel