evolutives. Conclusions
Nos r´esultats mettent en ´evidence la possibilit´e de variations temporelles des patrons de di-versit´e-d´ependance lors des radiations ´evolutives, appelant au d´eveloppement de mod`eles ph´enom´enologiques diversit´e-d´ependants par intervalles temporels. Ils montrent un rˆole pr´epond´erant de la sp´eciation dans la diversit´e-d´ependance des taux de diversification, l’ex-tinction “de fond” ´etant globalement ind´ependante de la diversit´e (hormis pour un niveau maximal de diversit´e, associ´e `a un pic d’extinction). Ces extinctions en phases (2) et (3), cl´es dans la diversification, proviennent principalement de l’hybridation ou de l’exclusion comp´etitive d’esp`eces incipientes en contact secondaire avec leur esp`ece m`ere, r´epondant ainsi aux principes de divergence et d’extinction propos´es par Darwin (Fig. 0).
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Etat de publication
Ce manuscrit est en cours de r´edaction. Il devrait ˆetre soumis sous un format court `a un journal g´en´eraliste, apr`es ach`evement du travail d’interpr´etation des r´esultats et analyse (en cours) de toutes leurs implications.
Revisiting Darwin’s principles of divergence and extinction : controls of speciation and extinction rates during clade diversification
Fanny Gascuel1,2,3, Amaury Lambert1,4, and R´egis Ferri`ere2,5
1 Center for Interdisciplinary Research in Biology, CNRS UMR 7241, Coll`ege de France, Paris, France ;
2 Institut de Biologie de l’ ´Ecole Normale Sup´erieure, CNRS UMR 8197, ´Ecole Normale Sup´erieure, Paris, France ;
3 Sorbonne Universit´es, UPMC Univ Paris 06, ED 227, Paris, France ;
4 Sorbonne Universit´es, UPMC Univ Paris 06, CNRS UMR 7599, Laboratoire Probabilit´es et Mod`eles Al´eatoires, Paris, France ;
5 Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, USA ;
Abstract
In On The Origin Of Species, Charles Darwin hypothesized that species diversification is driven by the ‘principle of divergence’ and extinction : new species begin as emerging varieties ; the ones that survive the ‘struggle for existence’ are populations that evolve more distinct characteristics and resource use, to the point where they may cause their ancestor’s and some of their close relatives’ extinction. According to Darwin, this combination of cha-racter divergence and population extinction drives cladogenesis–the splitting of one ancestral species into multiple descendants. Largely because Darwin’s principles were agnostic to the genetic basis of reproductive isolation and downplayed the role of the abiotic environment in speciation and extinction, they were rejected by twentieth century biologists. Now Darwin’s principles are receiving renewed interest as environmental, fossil and molecular data together offer unprecedented opportunities to explore how ecology and evolution interact and jointly shape the history and patterns of species diversity. We used numerical simulations of a model of clade diversification to investigate Darwin’s principles when ecological, genetic, and abiotic environmental factors interact. Clade diversification begins with a phase of geographic adaptive radiation, which delays the action of Darwin’s principle until the reproductively isolated descendants of a common ancestral lineage start interacting. The second phase generates diversification patterns similar to Darwin’s principle. Diversity accumulates at a
constant rate in a process of ‘ecological niche self-structuring’–the sharing of the ecological space surrounding each environmental optimum by multiple species, through reductions in geographic ranges, population sizes and levels of adaptation ; but the extinction rate is high, resulting primarily from competitive exclusion and hybridization of incipient species with their mother species. This diversification phase is driven by the interplay between adaptation, competition and the abiotic landscape dynamics, the latter being the major determinant of speciation and extinction rates. When local diversity reaches levels at which competition prevents dispersal from seeding new populations, the range of species shrinks in a ‘geographic ratchet’ that triggers negative diversity-dependence of speciation rates. These results reveal how ecological interactions interact with genetic processes and abiotic factors to scale up and influence the macroevolutionary rates of speciation and extinction ; they help reconcile conflicting evidence on the role of competition and trait evolution in clade diversification, and caution against the notion of ecological limits to macroevolution.
Keywords : macroevolution, diversification rate, ecological speciation, competition, adap-tive radiation, eco-evolutionary feedbacks, macroecological patterns, character displacement, genetic incompatibility, dynamic landscape.
Introduction
Darwin’s celebrated ‘principle of descent with modification’ (Darwin, 1859) is the basis of our understanding of microevolution–adaptive modifications within populations driven over time by natural selection. Darwin’s approach to macroevolution (the diversification of clades and taxonomical units above species level) revolved around another related hypothesis, the ‘principle of divergence’ and extinction (Darwin, 1859; Reznick et Ricklefs, 2009). According to this hypothesis, competitive interactions (Darwin’s ‘struggle for existence’) are strongest among closely related populations or species ; these interactions promote the differentiation (character divergence) of populations and the exclusion (extinction) of competitively inferior ones. In Darwin’s view of macroevolution, reproductive isolation is a by-product, and the physical environment (e.g. geographic barriers arising or disappearing between populations)
is of minor importance.
The Modern synthesis rejected Darwin’s view, minimized the role of competition in species origination, and emphasized the interaction of abiotic factors (e.g. geographic fluctuations of the landscape) and genetic mechanisms of reproductive isolation in driving the macroevolu-tionary dynamics of diversification (Dobzhansky, 1937; Mayr, 1942, 1994). Renewed interest in Darwin’s principles was garnered by empirical support for the role of competition in adap-tive radiations (Schluter, 2000b; Losos, 2000), the role of character displacement in speciation (Hoskin et al., 2005; Rundle et Nosil, 2005), and ubiquitous diversification slowdown (puta-tive consequence of competition for limiting resources ; Phillimore et Price, 2008). However, conflicting evidence and alternative explanations exist. First geographic speciation may play a major role in adaptive radiations (Sim˜oes et al., 2016). Secondly, species interactions can result in phenotypic convergence, rather than divergence, across entire radiations (Tobias et al., 2014). Third, diversification slowdown may be unrelated to ecological niche filling (Moen et Morlon, 2014) ; in fact, whether and how diversifying clades become self-limited is not understood (Ricklefs, 2010). Emerging eco-evolutionary theory (Schoener, 2011) empha-sizes that phenotypic diversification itself can create niche space among interacting species (Geritz et al., 1998; Doebeli et Dieckmann, 2000; Ferriere et al., 2002; Bonsall et al., 2004; Scheffer et van Nes, 2006; Voje et al., 2015), but we know little about how eco-evolutionary feedbacks interact with geographic factors and other large-scale abiotic environmental dri-vers to shape speciation and extinction rates over a clade’s history. Finally, Darwin’s proposal for the cause of extinction has yet to be evaluated (Reznick et Ricklefs, 2009). Analyses of extinction in the fossil record have been dominated by a focus on mass extinction events ; in contrast, Darwin’s interactive extinctions would fuel the process of ‘background extinc-tion’, whose biotic and abiotic controls remain poorly understood (Reznick et Ricklefs, 2009; Quental et Marshall, 2013).
We implemented Darwin’s ‘struggle for existence’ (competition for non-evolving resources) in a spatially and genetically explicit model of clade diversification. Although the biological realism of macroevolutionary models can always be questioned, this approach has the ability to identify critical factors and parameters (Gavrilets et Losos, 2009). In silico experiments on the model allowed us to identify the mechanisms controlling the diversification process. We investigated how patterns of variation in speciation and extinction rates with species
di-versity are shaped by key underlying ecological and genetic variables. Then, we analysed how these evolutionary processes are affected by different biotic (in particular competitive interac-tions) and abiotic factors, and how these effects translate onto the emergent macroecological patterns of species diversity and abundance.
Model overview
We use a refined version of the individual-based eco-evolutionary model of species diver-sification introduced in Aguil´ee et al. (2011, 2013) and Gascuel et al. (2015), which links macroevolutionary dynamics to organismal, ecological, and environmental processes (detai-led in Appendix 1). The model scales up from local ecological interactions and individual dispersal, integrates mechanisms of reproductive isolation both pre-zygotic (by assortative mating) and post-zygotic (by genetic incompatibilities), and represents geological events on a slow timescale as an alternation of geographic isolation (allopatry) and contact between populations. Heritable traits of individuals, such as body size or reproductive mode, influence their life history and ecological interactions and thus shape the ecological state of the com-munity, which in turn generates selection driving trait evolution. The feedback between the population trait distribution and the state of the ecological system causes phenotypic evo-lution. Species emerge from sets of non-reproductively isolated subpopulations, the latter representing groups of phenotypically similar individuals inhabiting the same geographical site ; ‘population’ referring here to the set of all subpopulations of the same species in a given geographical site. Speciation can occur either through reversible pre-zygotic repro-ductive isolation driven by the joint evolution of assortative mating and phenotypic traits (‘magic traits for speciation’ driving ecological speciation ; Schluter, 1998, 2001; Doebeli et Dieckmann, 2003; Schluter, 2009; Servedio et al., 2011; Thibert-Plante et Gavrilets, 2013), or through irreversible post-zygotic isolation driven by genetic incompatibilities that build up between populations through mutation (Dobzhansky, 1937; Mayr, 1942). Sympatric specia-tion due to disruptive selecspecia-tion at the environmental optima (Dieckmann et Doebeli, 1999) is impeded by polygenic trait inheritance (Gavrilets, 2003; Waxman et Gavrilets, 2005). We implement these processes over a spatially explicit, dynamic landscape : the metacommunity is distributed over multiple (nine) sites in a two-dimensional landscape, in which environ-mental resources and/or conditions vary, gradient-like, in both dimensions, each site being
caracterized by a different environmental optimum (Fig. 1.a-b). The landscape is dynamic, as geographical barriers can arise between adjacent sites, thereby preventing migration and gene flow, and also disappear. These rounds of fusion and fragmentation of sites lead to repeated phases of sympatry and allopatry between local communities. Physical barriers to dispersal favor phenotypic divergence between populations, and hence create opportunities for allopa-tric speciation, whereas secondary contacts create opportunities for character displacement and reinforcement. The history of species origination and species loss thus emerges from the joint operation of the individual-level biotic and patch-level abiotic processes.
We investigated the role of key ecological and genetic variables underpinning patterns of varia-tion in speciavaria-tion and extincvaria-tion rates : species’ geographic range (number of sites occupied, i.e. number of populations), populations’ abundance, degree of populations’ maladaptation relative to the local environmental optimum, intensity of interspecific competition (which depends on the abundance and ecological similarity of individuals from other species inha-biting the same site), assortative mating, maximum risk of hybridization with populations from other species (in the same or other geographical sites–figuring the risk of hybridization in case of secondary contact ; conditioned on the absence of reproductive isolation due to genetic incompatibilities), and phenotypic divergence from parental species (which influences competition strength and hybridization risk at secondary contact).
We considered variation in three biotic factors affecting diversification : the influence of ge-netic incompatibility on reproductive isolation (i.e. the number of loci carrying incompatible alleles needed to generate reproductive isolation), resource abundance (i.e. the maximum of the resource distribution kernel), and the scaled competition width (i.e. the width of the com-petition kernel compared to that of the resource distribution kernel ; Doebeli et Dieckmann, 2003). We also explored the effect of three abiotic factors : the pace of landscape dynamics, the mean isolation time between adjacent geographical sites, and rate of local catastrophes (which beget the extinction of all the populations of a random geographical site). Detailed information on simulations, variables and factors are provided in Appendix 2.
Results
The model reveals a general pattern of diversification in three major phases, labelled(1),(1)
a
Time = 8,000 Time = 30,000 Time = 100,000
b c ● 0 10 20 30 40 50 60 Time (generations) Number of species 0 40000 80000 (1) (2) (3) d ● 0.0000 0.00 10 Number of species Speciation rat e 0 20 40 60 (1) (2) (3) e ● 0.0000 0.00 10 Number of species Extinction rat e 0 20 40 60 (1) (2) (3) f 95% 50%
Figure 1 – Macroevolutionary patterns of species diversification. a, Example of diver-sification in space and time : populations (vertical bars, whose height show their abundance) of all species, in all geographical sites (4 sites in a ; 9 sites everywhere else), at three moments in time. The phenotypes of species (bars) and the optima of sites (floor) are colored based on the two-dimensional palette b representing the ecological space (with black dots showing the optima of the 9 geographical sites). c Phylogenetic tree of extant and extinct species, with colors showing the average phenotype along each branch, as shown in b. d Species richness through time. e, Diversity-dependence of speciation rates. f, Diversity-Diversity-dependence of extinction rates. Time is measured in number of generations from the common ancestor’s introduction in the landscape. In d-f, black lines give median values over 50 simulation replicates, purple areas give 95% and 50% confidence intervals, and the three temporal phases(1)-(3)are highlighted by grey shadings. Parameter values as in Table A.1.
Exposing a single ancestral species to new environmental opportunities ignites diversification with an adaptive radiation, associated with high rates of speciation (diversification phase(1); Fig. 1.a,d-f). This initial radiation is driven by character divergence resulting from adapta-tion to local environmental optima (Fig. 2.c). The rate of diversificaadapta-tion in phase(1)is indeed chiefly determined by local resource abundance (greater resource implies larger population size hence stronger directional selection in each site ; zoom in Fig. A.5.c). In contrast, inter-specific competition contributes little to the initial adaptive radiation (zoom in Fig. A.5.b). This phase may however be affected by the build-up of genetic incompatibilities among al-lopatric populations, which can generate reproductive isolation before ecological speciation (zoom in Fig. A.5.a). Provided the time spent by colonizing populations in isolation of each other is long enough (Fig. A.11.a-c), the initial radiation will fill up all available environ-mental optima (Fig. 1.a,d) with maximally differentiated and locally adapted species (Fig. 2.b-d).
Diversification, however, does not stop with leading species to sit at each of the environ-mental optima : the initial radiation is followed by a gradual increase in species diversity (diversification phase (2)), which may lead to the coexistence of many more species than the total number of environmental optima (Fig.1.a,c-d). This occurs through a process of ‘niche self-structuring’ (Scheffer et van Nes, 2006) that ‘de-adapts’ the clade from local en-vironmental optima (Fig.2.c), concomitantly with reductions in species’ geographic ranges and population sizes (Fig.2.a-b). To assess the role of competition-driven divergence and extinction in phase (2), we compared variation in all the process variables between species that are about to speciate, species about to go extinct, and species undergoing neither spe-ciation nor extinction (which we call ‘static’). The birth of a new species requires that the mother species be distributed over two sites or more (Fig. 2.a) : when two of these sites enter a period of geographic isolation, the two populations may diverge through adaptation to-ward each local environmental optimum. Phenotypic divergence causes ecological speciation, potentially completed at secondary contact through reinforcement, leading to the evolution of stronger assortative mating (Fig. 2.g). When sites are isolated again, the two incipient species may coexist in each site, and hence start differentiating again. As this sequence of landscape fusion-fragmentation (i.e. species sympatry-allopatry) repeats itself through time and between different pairs of sites, species multiply at a constant rate (Fig. 1.d-e) and
di-Number of sit
es
A
bundance per sit
e Maladapt ation Pheno typic dis tance t o par ent Max h ybr idization pr obability Int er specif ic compe tition Assor tativ e mating ● 0 1 2 3 4 5 (1) (2) (3) a ● 50 70 90 11 0 130 b ● 0.1 0.5 0.9 c ● 0 0.5 1 1.5 d ● 0 0.002 0.005 e ● 0 0.1 0.2 f ● 0 10 30 50 0.3 0.7 1.1 1.5 g Number of species ● (1) (2) (3) ● ● ● ● ● ● 0 10 30 50 Number of species Figure 2 – Diversity-dependence of key variables underlying evolu-tionary rates. Simulations were repli-cated 50 times. Left column : median values (black lines), 95% and 50% confi-dence intervals (purple areas), compu-ted over all species. Right column : me-dian values for species about to speciate (in the next 200 generations ; blue), about to go extinct (in the next 200 generations ; red), and for ‘static’ spe-cies (neither speciation nor extinction in the next 2,000 generations ; orange). The three temporal phases (1)-(3) are highlighted by grey shadings, as on Fig. 1. Parameter values as in Table A.1.
versity increases across the landscape (‘species pump’ process, well explained and illustrated in Aguil´ee et al., 2013).
This sequence of landscape fusion-fragmentation also fuels extinction (Fig. 1.f). The distri-bution of species age at extinction indicates that at any time during clade diversification, most species going extinct are young species (Fig. A.4). Young species tend to be little dif-ferentiated from their mother species, and insufficient character divergence is indeed key to extinction (Fig. 2.d). First, the rapid rise of interspecific competition intensity (Fig. 2.f) esta-blishes the condition for competitive exclusion of poorly differentiated species when exposed to secondary contact. Second, limited divergence may cause reinforcement to fail when sites are reconnected ; nascent species may then be lost by hybridization with their mother species (Fig. 2.d-e), even though stronger homogamy evolves among all species throughout clade diversification (Fig. 2.g). Eventually, species doomed to extinction are maladapted and have low abundance (Fig. 2.d-c) : because they originate from mother species adapted to other environmental optima, their phenotypes tend to stand at the margins of the environmental conditions in their new habitat. These two factors may however not be the direct cause of extinctions. In fact, the abundance of species destined to extinction is typically more than half the abundance of static species (Fig. 2.b), which shows that extinction is not merely induced by populations stochastically drifting to critically low size. In summary, the process of extinction is mainly driven by competitive exclusion and hybridization, whereby poorly differentiated, single-site species are eliminated at secondary contact with their mother spe-cies. These processes may be supplemented by extinctions resulting from the maladaptation and low abundance of incipient species.
The influence of biotic and abiotic factors on speciation and extinction rates in phase (2) is revealed in Fig. 3, Fig. A.6.a1-f1, a2-f2 and figures in Appendix 5. The pace of landscape dynamics appears to be the chief determinant of both rates. Site fission creates the oppor-tunity for the divergence of a new species (Fig. A.10.a), while exposing poorly differentiated populations to the risk of local extinction by maladaptation (Fig. A.10.c). Site fusion exposes poorly differentiated, single-site populations to competitive exclusion and hybridization (Fig. A.10.d-e). Competition width and resource abundance also influence evolutionary rates in phase (2) (Fig. 3.b1-c1, b2-c2, Fig. A.5 and Fig. A.6.b1-c1). Large competition width in-creases interspecific competition (Fig. A.8.f), limiting the persistence of new populations
(Fig. A.8.a-b), resulting in lower speciation rates. This process has however little effect on extinction rates in phase (2) (Fig. 3.b2) : the influence of increased competitive exclusion seems compensated by lower hybridization risk at secondary contact, resulting from stronger assortative mating (Fig. A.8.e,g). Higher resource abundance increases the persistence and differentiation of new populations (Fig. A.9.a,b,d), and hence the rate of speciation (Fig. 3.c1). It also slightly decreases the extinction rate (Fig. 3.c2), even though hybridization probabilities at secondary contact are higher due to lower assortative mating (Fig. A.9.e,g). Eventually, the build-up of genetic incompatibilities has a significant negative effect on the extinction rate (Fig. 3.a2 and Fig. A.6.a2) : reproductive isolation induced by low numbers of genetic incompatibilities opposes hybridization with the mother species at secondary contact (Fig. A.7.e). Speciation rat e Extinction rat e Genetic incompatibility 2.5e+01 4e+00 ● 0 0 0 2e−04 4e−04 6e−04 a1 ● 0 0 0 20 40 60 80 100 0 2e−04 4e−04 6e−04 a2 Number of species Competition width 7.5e−01 2.5e−01 ● 0 0 b1 ● 0 0 0 20 40 60 80 100 b2 Number of species Resource abundance 7.5e+01 3.8e+02 ● 0 0 c1 ● 0 0 0 20 40 60 80 100 c2 Number of species Pace of landscape dynamics 1.4e−04 9.9e−06 ● 0 0 d1 ● 0 0 0 20 40 60 80 100 d2 Number of species Time in isolation 5.2e+01 9.9e+01 ● 0 0 e1 ● 0 0 0 20 40 60 80 100 e2 Number of species Local catastrophes 5e−04 0e+00 ● 0 0 f1 ● 0 0 0 20 40 60 80 100 f2 Number of species
Figure 3 – Effet of different biotic and abiotic factors on patterns of diversity-dependence of speciation and extinction rates. Median values over 50 simulation replicates. Parameter values changed for each factor : git (number of mutations inducing genetic incompa-tibility ; a1-a2), σC/σK (scaled competition width ; b1-b2), K (maximum local carrying capacity ;
c1-c2), 1/(1/f + 1/c) (with f the rate of geographic barrier appearance and c their rate of disap-pearance ;d1-d2), f /(c + f ) (e1-e2), and cr (rate of local catastrophes ;f1-f2). Results from different parameter values are shown on a blue to red gradient (with extreme values given above the plots), respectively leading to lower/higher species richness at steady state. Other parameter values as in Table A.1.
During the third phase of diversification ((3), Fig. 1.d-f), speciation events leave both species confined to a single site (Fig. 2.a) : the plateau in species’ local maladaptation (Fig. 2.c) and the strong interspecific competition (Fig. 2.f) prevent recolonization and the establishment of new populations when sites become reconnected. The few speciation events occurring wi-thin one site only (Fig. 2.a) may result from the (rare) ephemeral phenotypic differentiation of subpopulations of an abundant species standing close to a local environmental optimum (Fig. 2.b-c). The ‘geographic ratchet’, whereby species range shrinks irremediably as diver-sity increases, reveals itself in the negative diverdiver-sity-dependence of the speciation rate (Fig. 1.e). This pattern is enhanced by conditions of low resources (which reduces the chance of