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.