There are several important topics in the study of infectious diseases that have not been well explored due to technical difficulties. One such topic is pursued by Alizon et al. in “Modelling coinfections to detect within-host interactions from genotype combination prevalences” [1]. Both theory and several important examples have demonstrated that interactions among co-infecting strains can have outsized impacts on disease outcomes, transmission dynamics, and epidemiology. Unfortunately, empirical data on pathogen interactions and their outcomes is often correlational making results difficult to decipher.
The analytical framework developed by Alizon et al. [1] infers the presence and strength of pathogen interactions through their impact on transmission dynamics using a novel application of Approximate Bayesian Computation (ABC)-regression to epidemiological data. Traditional analytic approaches identify pathogen interactions when the observed distribution of pathogens among hosts differ from ‘neutral’ expectations. However, deviations from this expectation are not only a result of inter-strain interactions but can be caused by many ecological interactions, such as heterogeneity in host contact networks. To overcome this difficulty, Alizon et al [1] develop an analytical framework that incorporates explicit epidemiological models to allow inference of interactions among strains of Human Papillomaviruses (HPV) even with other ecological interactions that impact the distribution of strains among hosts. Alizon et al also demonstrate that using more of the available data, including the specific combination of strains present in hosts and knowledge of the connectivity of the hosts (i.e., super-spreaders), leads to more accurate inferences of the strength and direction of within-host interactions among coinfecting strains. This method successfully identified data generated from models with high and moderate inter-strain interaction intensity when the host population was homogeneous and was only slightly less successful when the host population was heterogeneous (super-spreaders present). By comparison, some previously published analytical methods could identify only some inter-strain interactions in datasets generated from models with homogeneous host populations, but host heterogeneity obscured these interactions.
This manuscript makes seamless connections between basic viral biology and its epidemiological consequences by tying them together with realistic models, illustrating the fundamental utility of biological modeling. This analytical framework provides crucial tools for experimentalists, facilitating collaborations with theoreticians to better understand the epidemiological consequences of co-infections. In addition, the method is simple enough to be applied by a broad base of experimentalists to the many pathogens where co-infections are common. Thus, this paper has the potential to impact several research fields and public health practice. Those attempting to apply this method should note the potential limitations noted by the authors. For example, it is not designed to detect the mechanisms of inter-strain interactions (there is no within host component of the models) but to identify the existence of interactions through patterns indicative of these interactions while ruling out other sources that could cause the pattern. This approach is likely to be most accurate when strain identification within hosts is precise and unbiased - which is unlikely in many systems where samples are taken only from symptomatic cases and strain detection is not sufficiently sensitive – and when host contact networks can be reasonably estimated. Importantly, a priori knowledge of the set of possible epidemiological models is needed for accurate parameter estimates, which may be true for several prominent pathogens, but not be so for many other pathogens and symbionts. We look forward to future extensions of this framework where this restriction is relaxed. Alizon et al. [1] have provided a framework that will facilitate theoretical and empirical work on the impact of coinfections on infectious disease and should shape future public health data collection standards.

References

[1] Alizon, S., Murall, C.L., Saulnier, E., & Sofonea, M.T. (2018). Detecting within-host interactions using genotype combination prevalence data. bioRxiv, 256586, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/256586

Understanding how livestock management is a source of social stress and disturbances for cattle is an important question with potential applications for animal welfare programs and sustainable development. In their article, Sosa and colleagues [1] first propose to evaluate the effects of individual characteristics on dyadic social relationships and on the social dynamics of four groups of cattle. Using network analyses, the authors provide an interesting and complete picture of dyadic interactions among groupmates. Although shown elsewhere, the authors demonstrate that individuals that are close in age and close in rank form stronger dyadic associations than other pairs. Second, the authors take advantage of some transfers of animals between groups -for management purposes- to assess how these transfers affect the social dynamics of groupmates. Their central finding is that the identity of transferred animals is a key-point. In particular, removing offspring strongly destabilizes the social relationships of mothers while adding a bull into a group also profoundly impacts female-female social relationships, as social networks before and after transfer of these key-animals are completely different. In addition, individuals, especially the young ones, that are transferred without familiar conspecifics take more time to socialize with their new group members than individuals transferred with familiar groupmates, generating a potential source of stress. Interestingly, the authors end up their article with some thoughts on the implications of their findings for animal welfare and ethics. This study provides additional evidence that empirical science has a major role to play in providing recommendations regarding societal questions such as livestock management and animal wellbeing.

References

[1] Sosa, S., Pelé, M., Debergue, E., Kuntz, C., Keller, B., Robic, F., Siegwalt-Baudin, F., Richer, C., Ramos, A., & Sueur C. (2018). Impact of group management and transfer on individual sociality in Highland cattle (Bos Taurus). arXiv:1805.11553v4 [q-bio.PE] peer-reviewed and recommended by PCI Ecol. https://arxiv.org/abs/1805.11553v4

Functional traits are “morpho-physio-phenological traits which impact fitness indirectly via their effects on growth, reproduction and survival” [1]. Most functional traits are defined at organ level, e.g. for leaves, roots and stems, and reflect key aspects of resource acquisition and resource use by organisms for their development and reproduction [2]. More rarely, some functional traits can be related to spatial development, such as vegetative height and lateral spread in plants.
Organ-level traits are especially popular because they can be measured in a standard way and easily compared over many plants. But these traits can broadly vary during the life of an organism. For instance, Roggy et al. [3] found that Leaf Mass Area can vary from 30 to 140 g.m^(-2) between seedling and adult stages for the canopy tree Dicorynia guianensis in French Guiana. Fortunel et al. [4] have also showed that developmental stages much contribute to functional trait variation within several Micropholis tree species in lowland Amazonia.
The way plants grow and invest resources into organs is variable during life and allows defining specific developmental sequences and architectural models [5,6]. There is clear ontogenic variation in leaf number, leaf properties and ramification patterns. Ontogenic variations reflect changing adaptation of an individual over its life, depending on the changing environmental conditions.
In this regard, measuring a single functional trait at organ level in adult trees should miss the variation of resource acquisition and use strategies over time. Thus we should built a more integrative approach of ecological development, also called “eco-devo” approach [7].
Although the ecological significance of ontogeny and developmental strategies is now well known, the extent to which it contributes to explain species survival and coexistence in communities is still broadly ignored in functional ecology. Levionnois et al. [8] investigated intraspecific variation of functional traits and growth trajectories in a typical, early-successional tree species in French Guiana, Amazonia. This species, Cecropia obtusa, is generalist regarding soil type and can be found on both white sand and ferralitic soil. The study examines whether there in intraspecific variation in functional traits and growth trajectories of C. obtusa in response to the contrasted soil types.
The tree communities observed on the two types of soils include species with distinctive functional trait values, that is, there are changes in species composition related to different species strategies along the classical wood and leaf economic spectra. The populations of C. obtusa found on the two soils showed some difference in functional traits, but it did not concern traits related to the main economic spectra. Conversely, the populations showed different growth strategies, in terms of spatial and temporal development.
The major lessons we can learn from the study are:
(i) Functional traits measured at organ level cannot reflect well how long-lived plants collect and invest resources during their life. The results show the potential of considering architectural and developmental traits together with organ-level functional traits, to better acknowledge the variation in ecological strategies over plant life, and thus to better understand community assembly processes.
(ii) What makes functional changes between communities differs when considering interspecific and intraspecific variation. Species turnover should encompass different corteges of soil specialists. These specialists are sorted along economic spectra, as shown in tropical rainforests and globally [2]. Conversely, a generalist species such as C. obtusa does occur on contrasted soil, which entails that it can accommodate the contrasted ecological conditions. However, the phenotypic adjustment is not related to how leaves and wood ensure photosynthesis, water and nutrient acquisition, but regards the way the resources are allocated to growth and reproduction over time.
The results of the study stress the need to better integrate growth strategies and ontogeny in the research agenda of functional ecology. We can anticipate that organ-level functional traits and growth trajectories will be more often considered together in ecological studies. The integration should help better understand the temporal niche of organisms, and how organisms can coexist in space and time with other organisms during their life. Recently, Klimešová et al. [9] have proposed standardized protocols for collecting plant modularity traits. Such effort to propose easy-to-measure traits representing plant development and ontogeny, with clear functional roles, should foster the awaited development of an “eco-devo” approach.

References

[1] Violle, C., Navas, M. L., Vile, D., Kazakou, E., Fortunel, C., Hummel, I., & Garnier, E. (2007). Let the concept of trait be functional!. Oikos, 116(5), 882-892. doi: 10.1111/j.0030-1299.2007.15559.x
[2] Díaz, S. et al. (2016). The global spectrum of plant form and function. Nature, 529(7585), 167-171. doi: 10.1038/nature16489
[3] Roggy, J. C., Nicolini, E., Imbert, P., Caraglio, Y., Bosc, A., & Heuret, P. (2005). Links between tree structure and functional leaf traits in the tropical forest tree Dicorynia guianensis Amshoff (Caesalpiniaceae). Annals of forest science, 62(6), 553-564. doi: 10.1051/forest:2005048
[4] Fortunel, C., Stahl, C., Heuret, P., Nicolini, E. & Baraloto, C. (2020). Disentangling the effects of environment and ontogeny on tree functional dimensions for congeneric species in tropical forests. New Phytologist. doi: 10.1111/nph.16393
[5] Barthélémy, D., & Caraglio, Y. (2007). Plant architecture: a dynamic, multilevel and comprehensive approach to plant form, structure and ontogeny. Annals of botany, 99(3), 375-407. doi: 10.1093/aob/mcl260
[6] Hallé, F., & Oldeman, R. A. (1975). An essay on the architecture and dynamics of growth of tropical trees. Kuala Lumpur: Penerbit Universiti Malaya.
[7] Sultan, S. E. (2007). Development in context: the timely emergence of eco-devo. Trends in Ecology & Evolution, 22(11), 575-582. doi: 10.1016/j.tree.2007.06.014
[8] Levionnois, S., Tysklind, N., Nicolini, E., Ferry, B., Troispoux, V., Le Moguedec, G., Morel, H., Stahl, C., Coste, S., Caron, H. & Heuret, P. (2020). Soil variation response is mediated by growth trajectories rather than functional traits in a widespread pioneer Neotropical tree. bioRxiv, 351197, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/351197
[9] Klimešová, J. et al. (2019). Handbook of standardized protocols for collecting plant modularity traits. Perspectives in Plant Ecology, Evolution and Systematics, 40, 125485. doi: 10.1016/j.ppees.2019.125485

Traditionally, dispersal has often been seen as “random” or “neutral” as Lowe & McPeek (2014) have put it. This simplistic view is likely due to dispersal being intrinsically difficult to measure empirically as well as “random” dispersal being a convenient simplifying assumption in theoretical work. Clobert et al. (2009), and many others, have highlighted how misleading this assumption is. Rather, dispersal seems to be usually a complex reaction norm, depending both on internal as well as external factors. One such internal factor is the sex of the dispersing individual. A recent review of the theoretical literature (Li & Kokko 2019) shows that while ideas explaining sex-biased dispersal go back over 40 years this state-dependency of dispersal is far from comprehensively understood.

Sevchik et al. (2021) tackle this challenge empirically in a bird species, the great-tailed grackle. In contrast to most bird species, where females disperse more than males, the authors report genetic evidence indicating male-biased dispersal. The authors argue that this difference can be explained by the great-tailed grackle’s social and mating-system.

Dispersal is a central life-history trait (Bonte & Dahirel 2017) with major consequences for ecological and evolutionary processes and patterns. Therefore, studies like Sevchik et al. (2021) are valuable contributions for advancing our understanding of spatial ecology and evolution. Importantly, Sevchik et al. also lead to way to a more open and reproducible science of ecology and evolution. The authors are among the pioneers of preregistering research in their field and their way of doing research should serve as a model for others.

References

Bonte, D. & Dahirel, M. (2017) Dispersal: a central and independent trait in life history. Oikos 126: 472-479. doi: https://doi.org/10.1111/oik.03801

Clobert, J., Le Galliard, J. F., Cote, J., Meylan, S. & Massot, M. (2009) Informed dispersal, heterogeneity in animal dispersal syndromes and the dynamics of spatially structured populations. Ecol. Lett.: 12, 197-209. doi: https://doi.org/10.1111/j.1461-0248.2008.01267.x

Li, X.-Y. & Kokko, H. (2019) Sex-biased dispersal: a review of the theory. Biol. Rev. 94: 721-736. doi: https://doi.org/10.1111/brv.12475

Lowe, W. H. & McPeek, M. A. (2014) Is dispersal neutral? Trends Ecol. Evol. 29: 444-450. doi: https://doi.org/10.1016/j.tree.2014.05.009

Sevchik, A., Logan, C. J., McCune, K. B., Blackwell, A., Rowney, C. & Lukas, D. (2021) Investigating sex differences in genetic relatedness in great-tailed grackles in Tempe, Arizona to infer potential sex biases in dispersal. EcoEvoRxiv, osf.io/t6beh, ver. 5 peer-reviewed and recommended by Peer community in Ecology. doi: https://doi.org/10.32942/osf.io/t6beh

In social species conflicts among group members typically lead to the formation of dominance hierarchies with dominant individuals outcompeting other groups members and, in some extreme cases, suppressing reproduction of subordinates. It has therefore been typically assumed that dominant individuals have a higher breeding success than subordinates. However, previous work on mammals (mostly primates) revealed high variation, with some populations showing no evidence for a link between female dominance reproductive success, and a meta-analysis on primates suggests that the strength of this relationship is stronger for species with a longer lifespan [1]. Therefore, there is now a need to understand 1) whether dominance and reproductive success are generally associated across social mammals (and beyond) and 2) which factors explains the variation in the strength (and possibly direction) of this relationship.
In their preregistration, Shivani et al. [2] plan to perform a meta-analysis on 86 social mammal species to address these two points. More specifically, they will investigate whether the relationship between female dominance and reproductive success vary according to life history traits (e.g. stronger for species with large litter size), ecological conditions (e.g. stronger when resources are limited) and the social environment (e.g. stronger for cooperative breeders than for plural breeders).
The two reviewers and I were particularly positive and enthusiastic about this preregistration and only had minor comments that were nicely addressed by the authors. We found the background well-grounded in the existing literature and that the predictions were therefore clear and well-motivated. The methods were particularly transparent with a nicely annotated R script and the authors even simulated a dataset with the same structure as the actual data in order to make sure that the coding of the data handling and statistical analyses were appropriate (without being tempted to look at model outputs from the true dataset).
Perhaps one limitation to keep in mind once we will have the chance to look at the outcome of this study if that the dataset may not be fully representative of social species with dominance hierarchies. For example, the current dataset contains only one aquatic mammal (Mirounga angustirostris) as far as I can see, which is likely due to a lack of knowledge on such systems. Furthermore, not only mammals exhibit dominance hierarchies and it will be interesting to see if the results of the proposed study hold for other social taxa (and if not, what may explain their differences).
That being said, the proposed study will already offer a much broader overview of the relationship between dominance and reproductive success in animal societies and a better understanding for its variation. The reviewers and I believe it will make an important contribution to the fields of socio-ecology and evolutionary ecology. I therefore strongly recommend this preregistration and we are particularly looking forward to seeing the outcome of this exciting study.

References

[1] Majolo, B., Lehmann, J., de Bortoli Vizioli, A., & Schino, G. (2012). Fitness‐related benefits of dominance in primates. American journal of physical anthropology, 147(4), 652-660. doi: 10.1002/ajpa.22031
[2] Shivani, Huchard, E., Lukas, D. (2020). Preregistration - The effect of dominance rank on female reproductive success in social mammals In principle acceptance by PCI Ecology of the version 1.2 on 07 July 2020. https://github.com/dieterlukas/FemaleDominanceReproductionMetaAnalysis/blob/trunk/PreregistrationMetaAnalysis_RankSuccess.Rmd