Interplay of immigration and coevolution constrains the structure of specialist-generalist communities

Interplay of immigration and coevolution constrains the structure of specialist-generalist communities | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Interplay of immigration and coevolution constrains the structure of specialist-generalist communities View ORCID Profile Vasco J. Lepori , View ORCID Profile Nicolas Loeuille , View ORCID Profile Rudolf P. Rohr doi: https://doi.org/10.1101/2025.08.27.670321 Vasco J. Lepori 1 Department of Biology – Ecology and Evolution, University of Fribourg , Chemin du Musée 10, CH-1700 Fribourg, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Vasco J. Lepori For correspondence: vasco.lepori{at}unifr.ch Nicolas Loeuille 2 Sorbonne Université, UPEC, CNRS, IRD, INRA, Institute of Ecology and Environmental Sciences, IEES , F-75005 Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nicolas Loeuille Rudolf P. Rohr 1 Department of Biology – Ecology and Evolution, University of Fribourg , Chemin du Musée 10, CH-1700 Fribourg, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Rudolf P. Rohr Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Species and populations in nature fall along a specialist-generalist continuum in habitat preferences and resource use. However, most studies focusing on assembly, niche packing and diversification have considered solely niche positions within a community. We study how the co-evolution of niche position and degree of specialization affects packing, coexistence, and properties of the resulting communities under different modes of community assembly. We observe that evolution can lead to diversification and spontaneous emergence of asymmetric configurations of generalist and specialist phenotypes. Moreover, there exist multiple alternative evolutionarily stable states, with either many specialists or fewer generalists, some of which are only locally uninvadable. Contingency on assembly history shows that both local evolutionary adaptation and dispersal processes influence community-level eco-evolutionary dynamics and the structure of communities. By comparing communities along a continuum of assembly modes going from pure coevolution to pure dispersal, we find that high rates of evolution constrain richness while promoting generalism, partly because pure evolutionary communities become trapped at local evolutionary optima. In contrast, communities shaped by strong immigration tend to be rich in specialist species. Finally, high rates of evolution decrease invasion success in mixed assembly scenarios, a pattern consistent with the phenomenon of community monopolization. 1 Introduction In nature, species and populations differ not only in their environmental optima, but also in the breadth and variability of the resources they consume and of environmental conditions they tolerate. This concept is encapsulated within the classical notion of an ecological niche, which can be characterized by both an optimum and a width around said optimum. In empirical investigations of niche width, species and populations are observed to span a spectrum from specialists to generalists in natural ecosystems ( Forister et al., 2015 ; Thomas et al., 2016 ; Hulburt, 1985 ). This variation affects their ecology, their ability to withstand environmental variability, and their likelihood of suffering from secondary extinctions ( Brodie et al., 2014 ). Both theoretical and empirical studies have underscored the dynamic nature of niche width and generalism, either due to genetic change or phenotypic plasticity, which play a role in adapting to environmental variation ( Kassen, 2002 ). Generalism can, for example, help buffer temporal environmental variability ( Reboud and Bell, 1997 ; Ketola et al., 2013 ), or act as a risk-spreading mechanism through diversification of resource use (the so-called portfolio effect or bet-hedging), though finding good empirical evidence for this effect is challenging ( Childs et al., 2010 ). Models of the evolution of consumer generalism have focused on consumer specialization on two resources (e.g. Egas et al. (2004) ; Kisdi (2002) ; Rueffler et al. (2007) ; Wickman et al. (2019) ). Many of these studies have stressed the effect of allocation tradeoffs in determining the generalism ultimately reached by a population. This idea is linked to Levins’ fitness set concept, which says that the curvature of the fitness values across different environments or resources (i.e. the fitness cost in habitat 1 in order to perform well in habitat 2) should determine whether species evolve towards high or low generalism ( Levins, 1962 ). This result was also evoked in the paper of Ackermann and Doebeli (2004) , who tackled this problem by representing generalism as the consumer niche width on a continuous resource axis, in a variation of the classical models of packing on a resource axis ( MacArthur, 1969 ; Dieckmann and Doebeli, 1999 ). Importantly, beyond the population-level, biotic interactions are also strongly intertwined with generalism, highlighting the need for studies that focus on generalism and specialization in a community context. Within trophic guilds, species compete for a finite amount of available resources, which ultimately set an upper limit to diversity ( MacArthur, 1969 ). Empirical examples show that niche filling reduces the potential for diversification in both natural ( Price et al., 2014 ) and experimental systems ( Brockhurst et al., 2007 ), while also decreasing the invasion success of newcomers ( Eisenhauer et al., 2013 ). At the same time, the more generalist a species, the more species it will indirectly interact with, and the more widespread its repercussions on the community. Parent et al. (2014) observed a reduction in niche breadth under heightened competition in an experiment using flour beetles. Similarly, Jones and Post (2013) demonstrated in alewife populations that increased competition leads to narrower population niche widths, but this effect can be mitigated by enhanced resource availability. Moreover, Robinson and Strauss (2020) showed that generalist herbivores exhibit narrower diet breadth in lowresource soils, and that this diet shift between substrates has a important consequences on the assembly and structure of the resulting community. Finally, Costa-Pereira et al. (2019) documented how niche widths in frogs increase given broader resource availability, and contracts when species diversity is higher. All these examples point to a tension emerging between resource availability, generalism, and diversity, ultimately affecting the number and character of the species making up a community in a given environmental context. We can thus regard generalism and richness as two sides of a same niche occupancy coin. Relatedly, in the modelling study of Barabás and D’Andrea (2016) , high intraspecific variation reduces community richness. However, as noted by Wickman et al. (2023) , Quantitative Genetics approaches are poorly equipped to deal with questions of evolutionary community assembly since species richness is fixed rather than an outcome of the model (but see promising recent advances by Wickman et al. (2023) and ( Lion et al., 2023 )). Given that both richness and degree of specialization are outcomes of ecological and evolutionary processes, understanding the determinants of community structure is an open research question. However, in order to fully tackle the question of community assembly, one must also consider the interplay between local evolutionary forces and dispersal ( Leibold et al., 2022b ; De Meester et al., 2016 ; Farkas et al., 2015 ). There is evidence that immigration influences evolutionary dynamics whilst evolution, in turn, affects invasions. For instance, rapid adaptive evolution in Daphnia magna lead to a cascading change in zooplankton community assembly and shift final community composition compared to communities with non-adapted Daphnia genotypes ( Pantel et al., 2015 ). Conversely, in a bacterial model system, diversification of a resident genotype was suppressed by invasion by a different strain, but only when invasion occurred early in the evolutionary process ( Fukami et al., 2007 ). In a competition context, the interplay of evolution and assembly has been discussed in light of the monopolization hypothesis. Monopolization can be thought of as an evolutionary analogue of priority effects, which occurs when rapid evolution of a resident species allows it to monopolize a free niche, thus preventing subsequent invasions by potential competitors. This concept has first been observed in natural communities ( De Meester et al., 2002 ; Gillespie, 2004 ), subsequently formalized at the community level in a series of theoretical articles ( Urban and De Meester, 2009 ; Loeuille and Leibold, 2008 ), and finally demonstrated in experimental settings ( Farkas et al., 2013 ; Pantel et al., 2015 ). This contingency on the order of events highlights the joint role of dispersal and evolution as drivers of community assembly. We set out to investigate this interplay in generalistspecialist communities, to uncover how evolving generalism and niche positions affect shifts in niche occupancy patterns under different scenarios. We study how alternative modes of community assembly affect the structure of such communities in a model of coevolution of niche position and specialization similar to that presented by Ackermann and Doebeli (2004) . By leveraging an Adaptive Dynamics evolutionary framework, community diversity becomes an emerging property of the assembly process: we expect to observe diversification for sufficiently large resource landscapes ( Doebeli and Dieckmann, 2000 ; Ackermann and Doebeli, 2004 ). However, it is unclear under which conditions greater resource availability will lead to one generalist phenotype or several specialist phenotypes. To assess how the modes of community assembly act on this tension, we contrast the properties of communities assembled by pure evolutionary and diversification dynamics with communities resulting from successive immigration events, as well as intermediate modes of assembly. Our findings highlight the joint role of evolution and immigration in shaping community structure and show that different assembly histories can lead to alternative evolutionary stable communities, including some which are asymmetrical coalitions of specialists and generalists. As some of states are locally stable endpoints of evolution, immigration events can shift the community to an alternative, more diverse state. As a result, evolutionary communities are poorer and more generalist than immigration communities, consistent with other studies ( Edwards et al., 2018 ). We also observe interactive effects when both forces simultaneously shape communities. In these mixed-assembly communities, higher rates of evolution lead to increased monopolization and reduced invasibility. 2 Model and Methods 2.1 Lotka Volterra model from a resource-consumer model We posit the following model, which we derive from a consumer-resource model by setting the resource to equilibrium (full derivation in the SM, following MacArthur (1972) ): Here x defines a location on the resource axis, while f i ( x ) = f ( x | µ i , σ i ) is the impact niche of consumer i (orange and purple curves in Figure 1 ) given by position µ and width σ , while ϕ ( x ) is the regeneration rate of the resource at a given location x . We could assume different shapes for the availability of resources, but will focus on the simple case of a uniform resource distribution bounded between [− R, R ], and zero everywhere else (boxcar function, in grey in figure 1 ). We recover the well-known Lotka-Volterra dynamics by defining r i := −m i + ∫ ϕ ( x ) f i ( x ) dx , which is the intrinsic growth rate given by how much resource is taken up, and α ij := ∫ f i ( x ) f j ( x ) dx which are the competition coefficients defined by the overlap in resource use (the more similar the resources used, the stronger the competition Macarthur and Levins (1967) ; Taper and Case (1992) ) Download figure Open in new tab Figure 1. The model. (a) consumption niches for a specialist (orange) and a generalist phenotype (purple). The intensity of competition between them ( α ij ) is given by the integral of the product of these two impact niches. Similarly, the intrinsic growth rate r i is given by the overlap between the orange or purple curve with the resource growth function (grey). (b) tradeoff shapes regulating the cost in niche amplitude to achieve a certain niche width. For a given tradeoff δ , the optimal niche width value that maximizes niche area is We model the specialism-generalism continuum as varying niche widths σ in the niche equation . A cost to being a generalist prevents the emergence of a Darwinian demon, a phenotype that could use any resource with great efficiency, out-competing all others. We materialize this cost as a trade-off between a consumer niche’s width σ and its maximum amplitude a . Such generalism-efficiency trade-offs have also been shown to exist in nature, for example in aphid parasitoids by Straub et al. (2011) , although they often remain elusive and difficult to demonstrate ( Kassen, 2002 ). Different hypotheses have been advanced to explain the genetic basis of this cost to generalism, such as antagonistic pleiotropy and mutation-accumulation ( Whitlock, 1996 ; Kawecki et al., 1997 ) or reduced evolvability ( Bono et al., 2020 ). We model both σ and a on the [0, 1] interval, and consider a flexible trade-off defined as ( σ ) δ + ( a ) δ = 1, so that a = (1 − σ δ ) 1 /δ . Smaller values of δ entail a greater cost to generalism: to achieve the same degree of niche width, a species loses out on much more niche height ( Figure 1 , right panel). Conversely, greater values of δ allow for generalism without sacrificing as much niche area. Under the approach of Levins (1962) , the fitness set (fitness values across different environments) must be convex for the benefits of generalism to surpass the associated costs. Similarly, under our model, performing better in many resources comes at the cost of performing less well in any single one of them. We thus expect selection for greater generalism at high values of δ , and diversification for smller values of δ . 2.2 Evolutionary dynamics The fitness function ω i of a mutant with traits in an Adaptive Dynamics framework is defined as its growth rate when rare in a community of residents j = 1, …, S . As such, it is intrinsically densityand frequency-dependent. where i ′ is a mutant of morph i and are the ecological equilibrium densities in the community. Adaptive dynamics assumes small mutations and a separation of timescales by considering ecological dynamics always resolved. Evolutionary dynamics over time then unfold following the canonical equation of Adaptive Dynamics ( Dieckmann and Law, 1996 ) where M is a constant encapsulating both the rate and the amplitude of mutations, and there is one equation per trait and per morph. We assume equal evolutionary rates M for the two traits (but we check robustness of this assumption in the S.M.). Furthermore, the coevolution of multiple traits would entail a covariance matrix which we here assume to be the identity matrix ( Metz, 2011 ; Leimar, 2009 ), corresponding to no genetic correlation between traits (position and width evolve independently). A singular strategy µ *, σ * corresponds to a point where both fitness gradients vanish (or a coalition of strategies where all fitness gradients in a polymorphic case) To evaluate evolutionary stability of the morph i , the Hessian matrix of second derivatives is calculated as The Hessian needs to be negative-definite (both eigenvalues of H i must be negative) for the strategy to be an uninvadable evolutionary endpoint in the morph i (ESS, Ackermann and Doebeli (2004) ; Leimar (2009) ), or else it is an invadable local minimum, where diversification can happen. In a first part, we explore evolutionary dynamics by numerically solving equation 4 in the polymorphic case until a stable configuration is reached, upon which we evaluate evolutionary stability (invasibility). If the point is a singular strategy but invadable, we add a new morph closely nearby (in line with the small mutations assumption) and proceed to reevaluate the evolutionary dynamics. We repeat this process until a fully uninvadable configuration is reached, that is, a point that is uninvadable in the neighborhood of all the resident morphs (if there are several). To find as many alternative solutions as possible, we restart simulations at randomized initial conditions varying both the initial richness level S and the traits of the initial community (both σ and µ are drawn from uniform distributions). 2.3 Community assembly trials In a second set of simulations, we compare how communities assembled by pure evolution and diversification (small mutations and branching) compare to immigration communities assembled by sequential invasions of migrants from a regional pool, and also intermediate communities shaped by both immigration from a regional pool and local coevolution. We assemble communities starting from S = 2 either by successive invasion or pure evolution. In the successive invasion scenario, arrivals are modeled as a Poisson process with rate λ , so that inter-arrival times are exponentially distributed. Newcomers are drawn from a regional pool according to sampling from a 2-D Uniform distribution µ ~ Uniform( −R, R ) and σ ~ Uniform(0, 1). They can invade the resident community if their invasion rate is positive, and can also make residents go extinct. At the other extreme of the spectrum, we generate evolutionary assemblages by pure adaptive evolution and diversification (i.e. small mutations) from low initial richness, following the procedure described earlier. Along this gradient, we generate intermediate communities by modulating the rate of immigration λ (number of arrivals per unit time), and the rate of evolution M along the evolution-immigration spectrum. We should note that in line with our Adaptive Dynamics approach, ecological processes are considered to be faster than both immigration and evolution (consecutive assembly scenario sensu Leibold et al. (2019) ). It is also worth spending a few lines on the link between ecological generalism and intraspecific trait variation (ITV). Population niche breadth could be partitioned into a within-phenotype component (individual generalism) and a between-phenotype component (individual variation, Futuyma and Moreno (1988) ). We focus on the former model, where a zero-width niche is not equivalent to all individuals exhibiting the mean trait but rather results in zero resource acquisition. The so-called Niche Variation Hypothesis posits that generalism and ITV are correlated, but evidence supporting it is mixed ( Bolnick et al., 2007 ; Meiri et al., 2005 ). 3 Results 3.1 Monomorphic evolutionary dynamics Results from the single-population scenario already highlight the emerging tension between generalism and richness; and the effects of resource availability and biological constraints on the evolution of generalism. Specifically, increased resources first lead to higher generalism evolution but eventually destabilize the strategy, leading to diversification ( Figure 2 ). At the same time, for a given resource availability, lower costs to generalism (greater δ values) lead to evolution of few generalists, while a high cost leads to diversification into multiple specialists. The niche position of the monomorphic singular strategy, as expected, settles around the resource optimum. Download figure Open in new tab Figure 2. Monomorphic evolutionary dynamics. (a) The vector field shows evolutionary trajectories leading to a singular strategy which is always located in the center of the resource domain µ * = 0, while the niche width strategy σ * depends on the resource width and the tradeoff shape. (b) larger resource availability promotes generalism at the singular strategy, and so do higher values of the tradeoff parameter δ . Here, every tile corresponds to one combination of resource and tradeoff values. We also note that larger niche availability eventually make the strategy invadable, causing diversification, while higher values of the tradeoff parameter δ make it a stable endpoint of evolution. 3.2 Past the branching point: polymorphic dynamics and evolutionary endpoints When the single-population strategy is evolutionary unstable, diversification ensues ( Geritz et al., 1998 ). Co-evolution of multiple morphs opens the door to interesting dynamics, including the emergence of generalist-specialist coexistence ( Figure 3 ). Moreover, we observe that trajectories are not fully deterministic (due to randomness in mutations) and allow multiple endpoints. These communities are alternative stable states along a trade-off between (mean) generalism and richness, with either many specialists or fewer generalist morphs. One example of alternative endpoints is illustrated in Figure 3 , where either a dimorphic coalition of strategies (specialist-generalist) or a triplet (two specialists and one generalist) is obtained for the same parameter set. Importantly, both of these configurations are locally evolutionary stable, meaning no further diversification ensues. The important difference lies in the two-morph coalition being invadable in certain regions of the fitness landscape unreachable via evolution by small mutation ( Figure 3 , lower panel). In other words, only the most species-rich of these attractors seem to be a globally uninvadable polymorphic strategy (an Evolutionary Stable Community or ESC sensu Edwards et al. (2018) ), while the undersaturated final states are local but non-global ESCs (see fitness landscapes in Figure 3 and Kremer and Klausmeier (2017) ). In Figure 4 , we show how species packing unfolds in increasingly wide resource landscapes with varying niche widths. There is an increase in evolutionary richness related to resource availability, but this relationship is nuanced by niche width evolution, and we observe a diversity of alternative evolutionary endpoints for each given resource width. As opposed to a typical fixed-width model where richness increases in monotonic fashion with larger resources, we observe a variety of states and alternate configurations. Moreover, our model gives rise to symmetry breaking in evolutionary communities (such as the generalist-specialist coalition in figure 3 ). Download figure Open in new tab Figure 3. Two alternative trajectories of evolution for a same parameter set. In panels (a-b), the x-axis represents time, while the y-axis shows niche positions and color represents niche widths. The final invasion landscape (c-d) pictures fitness as a function of mutant µ and σ . It shows that the 2-morph combination (a,c) is a non-global ESS which is only uninvadable in its neighborhood (small mutations assumption), but presents a positive invasion fitness area, marked in red and located down and left on the 2-dimensional invasion landscape on panel (c). On the other hand, the 3-morph coalition (b,d) is globally uninvadable, i.e. a strict Evolutionarily Stable Community sensu Edwards et al. (2018) . The parameters for this pair of simulations are the same and equal to δ = 2.0, resource width = 1.7. Download figure Open in new tab Figure 4. Frequency of alternative evolutionary endpoints and richness accumulation with resource availability. Our model exhibits a few alternative stable endpoints of evolution for a most parameter sets (resources and tradeoff), including asymmetric generalist-specialist pairs and coalitions. The same color depicts the number of morphs in a same coalition, e.g. teal corresponds to 3-morph strategies. Further, we connected qualitatively identical arrangements (in terms of richness, symmetry) across resource scenarios. The bottom chart shows the frequency with which we end up on one of the different configurations, starting from randomized conditions (varying S0, µ0, and ω0). We ran a large amount of simulations with different starting conditions to find the different attractors. However, note that frequencies are solely illustrative and are likely to depend on the exact simulation method. Tradeoff value for this figure: δ = 2.0. 3.3 Assembly mode effects on structure Finally, we show that modes of community assembly can alter community composition and structure. As mentioned earlier, there exist situations where coevolution reaches a point of stasis, but further assembly would be possible with immigration (equivalent to lifting the assumption of small mutations). Figure 5 compares the effects of different rates of both evolution and immigration. We first notice how communities that are purely shaped by immigration (lower right corner of Figure 5 ) exhibit high richness and high levels of specialism, as well as fast turnover. These communities exhibit stable coexistence ecologically, but are in evolutionary disequilibrium (they exhibit higher diversity than ESC and would lose diversity through evolutionary murders without a constant influx of immigrants). Over extremely long ecological times, these communities end up looking like saturated ESCs even in the absence of directional evolution (in yellow in Figure 6 ). Because the actual ESC is never reached without evolution, a certain turnover and variance over time is maintained, and these communities show oversaturation and overspecialization. Similarly, high-immigration, low-mutation communities can transiently show a pattern of oversaturation, but eventually reach an uninvadable ESC. Download figure Open in new tab Figure 5. Evolution and immigration jointly affect richness, average generalism. The heatmaps show properties of assembled communities along an immigration-evolution continuum. The left-most columns show strongly dispersal-limited communities governed by pure evolution, with those in the top-left corner of each panel having converged to resemble the ESC. Communities in the bottom right panel are non-evolutionary communities arising through successive invasion from migrants. We observe that higher evolution rates lead to lower richness (a), while the strong immigration increases specialization and richness (b). Parameters for this figure are: resource width = 1.8, δ = 1.0. Download figure Open in new tab Figure 6. Evolution and immigration interact to jointly affect community assembly. Changes in average generalism (a), mean strength of competition (b), and average richness (c) over time in communities assembled through different regimes of immigration and evolution. (d) fraction of successful invasion overtime for three different evolution rates. For a same level of immigration, faster evolution decreases the rate of invasion success. This shows a pattern of community monopolization where resident adaptation and diversification leads to occupation of available niches. Notice that the time axis is log-transformed. Parameters for all panels are resource width = 1.8, tradeoff δ = 1.0, and, for panel (d), immigration λ = 10. In contrast, communities assembled by pure diversification (upper left in Figure 5 ) tend to be highly generalist and characterized by low diversity. These communities are often trapped at undersaturated local evolutionary equilibria — an additional constraint adding to other familiar barriers to diversification ( Gavrilets, 2005 ). Taken together, these outcomes are consistent with higher maximum ecological packing than evolutionary diversity ( Edwards et al., 2018 ; Rubin et al., 2023 ; Shoresh et al., 2008 ). We show that this effect is conserved even when generalism is an evolutionary variable, and that it is reinforced by the existence of non-global ESCs. Conversely, the combination of immigration alongside evolution constitutes the most rapid route to achieving a globally uninvadable evolutionarily stable community. Finally, we observe the effect of evolution on the invasibility of communities that are subject to immigration ( Figure 6 ). We see that the fraction of successful immigration events decreases with time and richness, but evolution accelerates this process (for a given rate of immigration λ ). This reflects a typical pattern of community monopolization, where adaptation of residents hinders the establishment of later-arriving migrants. It is intriguing that an increase in generalism among residents does not appear to be the cause of this monopolization pattern. In fact, generalism tends to decline during this process, with a more rapid decrease observed in evolutionary communities. Nor is it due to higher richness, since richness accumulates faster in immigration communities. Instead, community monopolization appears to arise from the rapid divergence of niche positions µ , which results in the occupation of available niche spaces. This is evidenced by the more rapid decline in interspecific interaction strength found in mixed assembly communities (green) compared to non-evolutionary ones (yellow) at the same immigration rate ( Figure 6 , panel (b)). 4 Discussion We have investigated the effect of coevolution and immigration on the assembly and structure of communities with varying degrees of specialization. We have shown that both resource availability and biological trade-offs constrain the evolution of specialization affecting the tension between generalism and richness. At the community level, evolutionary dynamics admit several configurations, including specialist-generalist coexistence and locally stable evolutionary endpoints. Once we add immigration to the forces driving assembly, we observe that different regimes of assembly lead to a different succession of community states through time. Whilst evolutionary dynamics lead to a pattern of monopolization which makes the community less invasible, the highest richness levels and fully uninvadable communities are only reachable with some degree of immigration from outside. The existence of these community states which can only be reached through a mix of evolution and immigration represents an under-explored facet of the interaction between local adaptation and regional dispersal dynamics. The role of resource availability as one of the main determinants of generalism evolution is consistent with empirical evidence that high resource environments lead to wider niches ( Jones and Post, 2013 ; Costa-Pereira et al., 2019 ). Eventually, for a large enough resource axis, we observe a switch from the evolutionary emergence of a single generalist phenotype to a diversification into several morphs, with larger resource axes leading to higher diversity, consistent with the results from fixed-width niche packing models ( MacArthur, 1969 ; Case, 1981 ). In agreement with the results of Levins’ fitness set approach in genetics ( Levins, 1962 ), the shape of the set of fitness values across environments, here described by the cost parameter, modulates this tension and affects the degree of specialization: when biological constraints impose a strong cost to generalism, diversification is favored over a generalist phenotypes (for a same resource environment). Contrarily to the findings of several discrete resource models ( Egas et al., 2004 ; Wickman et al., 2019 ), we observe that the evolutionary emergence of a specialist-generalist pair is a possible outcome of evolutionary dynamics. Moreover, unlike in classical models of niche-packing, the resource-richness relationship is not linear or monotonic. Instead, we identify multiple possible evolutionary endpoints for a same set of parameters, characterized by either fewer generalist types or numerous specialist types. Such alternative stable states depend on the assembly history, including initial conditions, immigration and stochasticity in mutations, and have been observed in several other of models of trait evolution ( Kremer and Klausmeier, 2017 ; Yacine et al., 2021 ; Ferriere and Legendre, 2013 ). Empirical evidence also appears consistent with our findings, as a few of empirical studies have highlighted how assembly of communities through diversification is sensitive to immigration and can lead to different communities depending on the invaders’ order of arrival ( Fukami et al., 2007 ; Gillespie, 2004 ). We observe that, no matter how fast the rate of evolution, purely evolutionary communities cannot escape local optima, as an increase generalism leads to evolutionary deadends preventing diversification. This is strikingly concordant with experimental evidence showing that niche generalism reduces propensity for adaptive radiation in Pseudomonas ( Flohr et al., 2013 ). Evolutionary local maxima are a well-known concept at the level of genes and traits (the rugged landscape metaphor, Bank 2022 ), but not so at higher levels of organization or in the presence of density- and frequency-dependent selection. We thus can advance an additional explanation as to why purely evolutionary communities might be less diverse than their non-evolutionary analogs, a result which has been described in multiple models ( Shoresh et al., 2008 ; Edwards et al., 2018 ; Rubin et al., 2023 ). These less diverse communities are less likely to exhibit high ecosystem services and multi-functionality ( Cardinale, 2011 ; Hector and Bagchi, 2007 ; Maestre et al., 2012 ), but may exhibit more robust coexistence ( Lepori et al., 2024 ). On the other hand, even small amounts of immigration can critically shift the community away from local optima of evolution, similarly to how within-species gene flow can rescue populations from extinction ( Gomulkiewicz and Holt, 1995 ). It is worth noting that, here, immigration can shift community assembly even in the absence of large demographic influxes (invaders can grow from low densities). Finally, it is in mixed assembly scenarios that we observe the most rapid convergence to largely specialist, globally uninvadable Evolutionarily Stable Communities ( Edwards et al., 2018 ). This is concordant with evidence showing that immigration can help bring the adapted characters necessary to rapidly fill available niches ( Richards et al., 2021 ). In these mixed assembly regimes, the dynamics also display a typical pattern of niche monopolization where early evolution prevents successive invasion ( De Meester et al., 2002 ). We observe that higher rates of local evolution lead to a decrease in invasion success for a given rate of immigration. Consistently, empirical evidence from diversifying organisms at different scales shows how the filling of niches hinders both further diversification and immigration ( Fukami et al., 2007 ; Gillespie, 2004 ; Pantel et al., 2015 ). We postulate that, here, monopolization is mainly driven by niche partitioning given by the evolution of niche positions rather than increased richness or generalism, as those properties do not appear to increase simultaneously to the decrease in invasion success. However, broader investigation into community monopolization by increased generalism may reveal specific instances where this could be the case, for example if the cost to generalism evolution is particularly low or if niche widths adapt faster than niche positions. Our results help shed light on the conditions when generalism evolution is favored in a community context, as well as the interplay of evolution and migration in community assembly. We highlight an understudied aspect of assembly in the alternative evolutionary states and local attractors of community structure. Multistability, local optima and qualitative shifts at the community and ecosystem level are already well appreciated in community ecology, where they are known under the names of priority effects or tipping points ( Aguadé-Gorgorió et al., 2024 ; Dakos et al., 2019 ; Stroud et al., 2024 ), but are less studied the study of evolution. Given the accumulation of examples of ecoevolutionary dynamics, an important question is whether or not evolution maintains less diversity compared to communities based on ecological filtering, as several theoretical results seems to suggest ( Rubin et al., 2023 ; Edwards et al., 2018 ); an idea somewhat in contrast with the concept of evolutionary rescue over shorter time-scales ( Gomulkiewicz and Holt, 1995 ; Bell and Gonzalez, 2009 ). Our findings strengthen this prediction, but also warn against the oversimplification of considering a rigid dichotomy of evolutionary and non-evolutionary communities. Whilst Evolutionary Stable Communities provide a valuable theoretical framework showing a surprising consistency of patterns across models, we stress that the dynamics of assembly equally warrant significant consideration. Our results paint a diverse picture of processes happening along a continuum of assembly modes, including interaction effects between evolution and dispersal. In this light, some ESCs might only be attainable under very specific assembly regimes. Thus, we advocate for an integrative science of community assembly across scales and processes, both ecological and evolutionary ( Loeuille, 2019 ; Leibold et al., 2022a ). Further investigation is needed to fully disentangle the problem of evolution of specialization in rich communities. As far as theory is concerned, we have not considered a full metacommunity framework with patches varying in resource optima and widths. To study how specialist-generalist dynamics unfold together with local adaptation under such conditions would be an exciting extension to this work. Moreover, the pace and correlation between the evolution of niche position and width warrants further investigation. From an empirical standpoint, our findings suggest further community assembly experiments mixing local adaptation, diversification and immigration to be carried out in suitable experimental systems. Funder Information Declared Swiss National Science Foundation , 182386 Footnotes nicolas.loeuille{at}sorbonne-universite.fr , and rudolf.rohr{at}unifr.ch References ↵ Martin Ackermann and Michael Doebeli . Evolution of Niche Width and Adaptive Diversification . Evolution , 58 ( 12 ): 2599 – 2612 , 2004 . ISSN 1558-5646 . doi: 10.1111/j.0014-3820.2004.tb01614.x . OpenUrl CrossRef PubMed Web of Science ↵ Guim Aguadé-Gorgorió , Jean-François Arnoldi , Matthieu Barbier , and Sonia Kéfi . 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Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Interplay of immigration and coevolution constrains the structure of specialist-generalist communities Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Interplay of immigration and coevolution constrains the structure of specialist-generalist communities Vasco J. Lepori , Nicolas Loeuille , Rudolf P. Rohr bioRxiv 2025.08.27.670321; doi: https://doi.org/10.1101/2025.08.27.670321 Share This Article: Copy Citation Tools Interplay of immigration and coevolution constrains the structure of specialist-generalist communities Vasco J. Lepori , Nicolas Loeuille , Rudolf P. 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