PCCGs implications for eco-evolutionary dynamics: toward focal-community eco-evolutionary dynamics
Evolutionary processes acting over micro- and macro-evolutionary scales are shaping the diversity of PCCGs. The PCCG diversity of a focal community is governed by its past demographic and evolutionary history, which encompasses geological processes (e.g. , isolation from a glacial refugee) and contemporary processes (e.g. , recent bottlenecks). If we assume that PCCGs are governing ecological dynamics, it appears that quantifying biodiversity from PCCGs is particularly relevant for predicting reciprocal feedbacks between ecological and evolutionary dynamics (Schoener 2011).
Considering PCCGs for measuring inclusive biodiversity and understanding eco-evolutionary dynamics constitutes a major conceptual shift, as this permits moving from a focal-species approach to a focal-community approach. Most studies investigating empirical eco-evolutionary feedbacks have considered feedbacks between evolutionary processes acting within a single species and ecosystem processes (Schoener 2011; De Meester et al. 2019; Hendry 2019); evolution alters gene frequencies and trait distribution within a species, which alters ecological dynamics, the laters potentially altering further the evolutionary dynamics of the focal species (Matthews et al. 2014, 2016). Contrastingly, very few studies have considered the possibility that evolution affects the genotypic (and trait) distribution of an entire focal community, with consequences for the dynamics of the community itself and the ecosystem, that themselves feedback to the gene pool of the focal community (but see, Norberget al. 2012; Aubree et al. 2019; Moorsel et al.2019). Thus, with PCCGs measured inclusively in a community, the “focal-species approach” traditionally used in most eco-evolutionary dynamics studies will naturally shift toward a “focal-community” perspective (De Meester et al. 2019; Hendry 2019; Govaert et al. 2021), making more realistic empirical eco-evolutionary studies. Here after, we detail three perspectives for exploring the implications of PCCGs for eco-evolutionary dynamics.
First, our basic premise is that spatial and temporal patterns of PCCG diversity must be uncovered in various communities to reveal the underlying evolutionary and demographic processes. While studies on patterns of intra- and interspecific diversity have often been partitioned, there is growing calls for merging knowledge from ecology and evolutionary biology into a single integrative framework (Hubbell 2001; Vellend 2005; Bolnick et al. 2011; Gaggiotti et al. 2018). In particular, Hubbell (2001) and Vellend (2005) proposed that spatial patterns of intraspecific (gene) diversity and interspecific (species) diversity can be understood through similar processes (natural selection/environmental filtering, gene flow/dispersal, genetic drift/ecological drift, mutation/speciation) acting over time in populations and communities. This was an important step toward the unification of empirical patterns of biodiversity (e.g., Taberletet al. 2012; Vellend et al. 2014; Laroche et al.2015; Fourtune et al. 2016; Manel et al. 2020). Nonetheless, in all these studies the two facets of diversity are still dichotomized (see also, Govaert et al. 2021). Here, by quantifying diversity of genes that transcend this dichotomic boundary, we take the alternative view that they actually form a continuum that must be analysed as a single entity; biodiversity . Spatial patterns of biodiversity can then be understood through processes derived from (meta-)population genetics: mutation acts on genes, which eventually leads to speciation; natural selection (indirectly) acts on genes, which eventually leads to different gene frequencies; gene flow acts on genes, which eventually homogenise the gene frequencies among local communities; and drift acts on genes, which eventually differentiate local communities. Population geneticists have developed a surge of theories and tools to infer processes over various time scales, which eases inferences (from patterns) of local and regional processes shaping biodiversity (Lowe et al.2017). In our opinion, a first important perspective would therefore be to reveal these patterns of PCCGs at different spatial and temporal scales, in different environmental contexts and taxonomic groups. Understanding patterns of PCCGs diversity allow for a thorough evaluation of the evolutionary processes governing gene frequencies in focal communities, and hence to relate the potential for eco-evolutionary dynamics to both adaptive (selection) and non-adaptive processes (gene flow, drift, mutation), since both can contribute to the evolution of traits in communities (Lowe et al.2017). This is in our opinion an important starting point as this contributes to embrace a more realistic perspective of empirical eco-evolutionary dynamics (Norberg et al.2012; De Meester et al. 2019).
Secondly, we suggest that considering PCCGs as a unit of biodiversity will provide a relevant substratum to move research on eco-evolutionary dynamics from a “focal-species” approach to a “focal-(meta-)community” approach (De Meester et al. 2019; Hendry 2019). We know from long-term BEF experiments in plants that (i) evolutionary dynamics are different among plant species having been seeded in plots with different levels of interspecific diversity (ecology-to-evolution,e.g., Moorsel et al. 2019), and (ii) that the evolution of some plants within plots with different levels of interspecific diversity alters plant productivity under some conditions (evolution-to-ecology, e.g. , van Moorsel et al. 2018). This really looks like an eco-evolutionary dynamics occurring at the community level, and theoretical models of BEFs are now integrating the potential for community evolution as a driver/modulator of ecological functions and their stability (e.g., Loeuille 2010; Aubree et al. 2020). Eco-evolutionary dynamics involving the evolution of communities have been further suggested in experiments manipulating microorganisms (e.g., Gravelet al. 2010; Lawrence et al. 2012; Faillace & Morin 2017), but these studies remain limited by the difficulty to simultaneously track gene frequencies for a substantial number of species. Quantifying diversity from PCCGs inherently allows for such a tracking and therefore breaks down a major wall (to quote Loreauet al. 2022). This genetic tracking can be done in the wild, and alternatively it becomes possible to assemble focal (meta-)communities -in common gardens, Matthews et al.2011- varying according to their PCCGs diversity, and then to track over time the consequences of this diversity on ecological processes, and reciprocally the consequences of the later on PCCGs diversity.
Finally, a PCCGs approach allows identifying the genetic sequences that matter for ecology (Skovmand et al. 2018) and their distribution in (meta-)communities. It has long been argued that phenotype is pivotal for linking ecological and evolutionary dynamics. While we agree with that statement, phenotypic diversity includes both an environmental (non-heritable) and a genetic component, the latter being central for eco-evolutionary dynamics. By assuming that functional genes are sustaining (at least partly) phenotypic variation among individuals and species, the PCCGs approach overcomes the shortcoming of including non-heritable components into the eco-evolutionary equation, and allows to focus more tightly on the “genes that matter”. Classical genome-wide-association approaches (GWAs) can be used to relate genomic (SNP) diversity at the community level and any ecological process to identify the gene(s) that is/are the most tightly linked to the process (Rudman et al.2018). Important variants for ecological processes may be concentrated in a single species or multiple species, and may be spread (or not) over multiple genes. In the same way, gene complementarity may arise when two or more variants are beneficial to each other for ecological processes, which would underlie the importance of (synergistic or antagonistic) “genomic interactions” for ecological processes. These questions remain -up to our knowledge- largely unexplored even theoretically, although they may reveal whether genes in a community are complementary, or whether a few of them are driving ecological processes. Because we propose an approach using genes extremely well known by functional biologists, a deeper understanding of the molecular mechanisms sustaining these gene-function relationships is possible. For instance, it has recently been shown that epigenetic marks play a pivotal role for controlling the sitter/rover behaviour associated to the for gene inD. melanogaster(Anreiter et al. 2017). The toolbox of functional biologists may be transferred to functional ecologists for improving the mechanistic linkage that exists between genes and ecological dynamics.