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10 Aug 2023
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Coexistence of many species under a random competition-colonization trade-off

Assembly in metacommunities driven by a competition-colonization tradeoff: more species in, more species out

Recommended by based on reviews by Canan Karakoç and 1 anonymous reviewer

The output of a community model depends on how you set its parameters. Thus, analyses of specific parameter settings hardwire the results to specific ecological scenarios. Because more general answers are often of interest, one tradition is to give models a statistical treatment: one summarizes how model parameters vary across species, and then predicts how changing the summary, instead of the individual parameters themselves, would change model output. Arguably the best-known example is the work initiated by May, showing that the properties of a community matrix, encoding effects species have on each other near their equilibrium, determine stability (1,2). More recently, this statistical treatment has also been applied to one of community ecology’s more prickly and slippery subjects: community assembly, which deals with the question “Given some regional species pool, which species will be able to persist together at some local ecosystem?”. Summaries of how species grow and interact in this regional pool predict the fraction of survivors and their relative abundances, the kind of dynamics, and various kinds of stability (3,4). One common characteristic of such statistical treatments is the assumption of disorder: if species do not interact in too structured ways, simple and therefore powerful predictions ensue that often stand up to scrutiny in relatively ordered systems. 
In their recent preprint, Miller, Clenet, et al. (5) subscribe to this tradition and consider tractable assembly scenarios (6) to study the outcome of assembly in a metacommunity. They recover a result of remarkable simplicity: roughly half of the species pool makes it into the final assemblage. Their vehicle is Tilman’s classic metacommunity model (7), where colonization rates are traded off with competitive ability. More precisely, in this model, one ranks species according to their colonization rate and attributes a greater competitive strength to lower-ranked species, which makes competition strictly hierarchical and thus departs from the disorder usually imposed by statistical approaches. The authors then leverage the simplicity of the species interaction network implied by this recursive setting to analytically probe how many species survive assembly. This turns out to be a fixed fraction that is distributed according to a Binomial with a mean of 0.5. While these results should not be extrapolated beyond the system at hand (4), they are important for two reasons. First, they imply that, within the framework of metacommunities driven by competition-colonization tradeoffs, richer species pools will produce richer communities: there is no upper bound on species richness, other than the one set by the raw material available for assembly. Second, this conclusion does not rely on simulation or equation solving and is, therefore, a hopeful sign of the palatability of the problem, if formalized in the right way. Their paper then shows that varying some of the settings does not change the main conclusion: changing how colonization rates distribute across species, and therefore the nature of the tradeoff, or the order with which species invade seems not to disrupt the big picture. Only when invaders are created “de novo” during assembly, a scenario akin to “de novo” mutation, a smaller fraction of species will survive assembly. 
As always, logical extensions of this study involve complicating the model and then looking if the results stay on par. The manuscript cites switching to other kinds of competition-colonization tradeoffs, and the addition of spatial heterogeneity as two potential avenues for further research. While certainly of merit, alternative albeit more bumpy roads would encompass models with radically different behavior. Most notably, one wonders how priority effects would play out. The current analysis shows that different invasion orders always lead to the same final composition, and therefore the same final species richness, confirming earlier results from models with similar structures (6). In models with priority effects, different invasion orders will surely lead to different compositions at the end. However, if one only cares about how many (and not which) species survive, it is unsure how much priority effects will qualitatively affect assembly. Because priority effects are varied in their topological manifestation (8), an important first step will be to evaluate which kinds of priority effects are compliant with formal analysis. 
1. May, R. M. (1972). Will a Large Complex System be Stable? Nature 238, 413–414.

2. Allesina, S. & Tang, S. (2015). The stability–complexity relationship at age 40: a random matrix perspective. Population Ecology, 57, 63–75.

3. Bunin, G. (2016). Interaction patterns and diversity in assembled ecological communities. Preprint at

4. Barbier, M., Arnoldi, J.-F., Bunin, G. & Loreau, M. (2018). Generic assembly patterns in complex ecological communities. Proceeding of the National Academy of Sciences, 115, 2156–2161.

5. Miller, Z. R., Clenet, M., Libera, K. D., Massol, F. & Allesina, S. (2023). Coexistence of many species under a random competition-colonization trade-off. bioRxiv 2023.03.23.533867, ver 3 peer-reviewed and recommended by PCI Ecology.

6. Serván, C. A. & Allesina, S. (2021). Tractable models of ecological assembly. Ecology Letters, 24, 1029–1037.

7. Tilman, D. (1994). Competition and Biodiversity in Spatially Structured Habitats. Ecology, 75, 2–16.

8. Song, C., Fukami, T. & Saavedra, S. (2021). Untangling the complexity of priority effects in multispecies communities. Ecolygy Letters, 24, 2301–2313.

Coexistence of many species under a random competition-colonization trade-offZachary R. Miller, Maxime Clenet, Katja Della Libera, François Massol, Stefano Allesina<p>The competition-colonization trade-off is a well-studied coexistence mechanism for metacommunities. In this setting, it is believed that coexistence of all species requires their traits to satisfy restrictive conditions limiting their similarit...Biodiversity, Coexistence, Colonization, Community ecology, Competition, Population ecology, Spatial ecology, Metacommunities & Metapopulations, Theoretical ecologyFrederik De Laender2023-03-30 20:42:48 View
27 May 2019
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Community size affects the signals of ecological drift and selection on biodiversity

Toward an empirical synthesis on the niche versus stochastic debate

Recommended by based on reviews by Kevin Cazelles and Romain Bertrand

As far back as Clements [1] and Gleason [2], the historical schism between deterministic and stochastic perspectives has divided ecologists. Deterministic theories tend to emphasize niche-based processes such as environmental filtering and species interactions as the main drivers of species distribution in nature, while stochastic theories mainly focus on chance colonization, random extinctions and ecological drift [3]. Although the old days when ecologists were fighting fiercely over null models and their adequacy to capture niche-based processes is over [4], the ghost of that debate between deterministic and stochastic perspectives came back to haunt ecologists in the form of the ‘environment versus space’ debate with the development of metacommunity theory [5]. While interest in that question led to meaningful syntheses of metacommunity dynamics in natural systems [6], it also illustrated how context-dependant the answer was [7]. One of the next frontiers in metacommunity ecology is to identify the underlying drivers of this observed context-dependency in the relative importance of ecological processus [7, 8].
Reflecting on seminal work by Robert MacArthur emphasizing different processes at different spatial scales [9, 10] (the so-called ‘MacArthur paradox’), Chase and Myers proposed in 2011 that a key in solving the deterministic versus stochastic debate was probably to turn our attention to how the relative importance of local processes changes across spatial scales [3]. Scale-dependance is a well-acknowledged challenge in ecology, hampering empirical syntheses and comparisons between studies [11-14]. Embracing the scale-dependance of ecological processes would not only lead to stronger syntheses and consolidation of current knowledge, it could also help resolve many current debates or apparent contradictions [11, 15, 16].
The timely study by Siqueira et al. [17] fits well within this historical context by exploring the relative importance of ecological drift and selection across a gradient of community size (number of individuals in a given community). More specifically, they tested the hypothesis that small communities are more dissimilar among each other because of ecological drift compared to large communities, which are mainly structured by niche selection [17]. That smaller populations or communities should be more affected by drift is a mathematical given [18], but the main questions are i) for a given community size how important is ecological drift relative to other processes, and ii) how small does a community have to be before random assembly dominates? The authors answer these questions using an extensive stream dataset with a community size gradient sampled from 200 streams in two climatic regions (Brazil and Finland). Combining linear models with recent null model approaches to measure deviations from random expectations [19], they show that, as expected based on theory and recent experimental work, smaller communities tend to have higher β-diversity, and that those β-diversity patterns could not be distinguished from random assembly processes [17]. Spatial turnover among larger communities is mainly driven by niche-based processes related to species sorting or dispersal dynamics [17]. Given the current environmental context, with many anthropogenic perturbations leading to reduced community size, it is legitimate to wonder, as the authors do, whether we are moving toward a more stochastic and thus less predictable world with obvious implications for the conservation of biodiversity [17].
The real strength of the study by Siqueira et al. [17], in my opinion, is in the inclusion of stream data from boreal and tropical regions. Interestingly and most importantly, the largest communities in the tropical streams are as large as the smallest communities in the boreal streams. This is where the study should really have us reflect on the notions of context-dependency in observed patterns because the negative relationship between community size and β-diversity was only observed in the tropical streams, but not in the boreal streams [17]. This interesting nonlinearity in the response means that a study that would have investigated the drift versus niche-based question only in Finland would have found very different results from the same study in Brazil. Only by integrating such a large scale gradient of community sizes together could the authors show the actual shape of the relationship, which is the first step toward building a comprehensive synthesis on a debate that has challenged ecologists for almost a century.


[1] Clements, F. E. (1936). Nature and structure of the climax. Journal of ecology, 24(1), 252-284. doi: 10.2307/2256278
[2] Gleason, H. A. (1917). The structure and development of the plant association. Bulletin of the Torrey Botanical Club, 44(10), 463-481. doi: 10.2307/2479596
[3] Chase, J. M., and Myers, J. A. (2011). Disentangling the importance of ecological niches from stochastic processes across scales. Philosophical transactions of the Royal Society B: Biological sciences, 366(1576), 2351-2363. doi: 10.1098/rstb.2011.0063
[4] Diamond, J. M., and Gilpin, M. E. (1982). Examination of the “null” model of Connor and Simberloff for species co-occurrences on islands. Oecologia, 52(1), 64-74. doi: 10.1007/BF00349013
[5] Leibold M. A., et al. (2004). The metacommunity concept: a framework for multi‐scale community ecology. Ecology letters, 7(7), 601-613. doi: 10.1111/j.1461-0248.2004.00608.x
[6] Cottenie, K. (2005). Integrating environmental and spatial processes in ecological community dynamics. Ecology letters, 8(11), 1175-1182. doi: 10.1111/j.1461-0248.2005.00820.x
[7] Leibold, M. A. and Chase, J. M. (2018). Metacommunity Ecology. Monographs in Population Biology, vol. 59. Princeton University Press. [8] Vellend, M. (2010). Conceptual synthesis in community ecology. The Quarterly review of biology, 85(2), 183-206. doi: 10.1086/652373
[9] MacArthur, R. H., and Wilson, E. O. (1963). An equilibrium theory of insular zoogeography. Evolution, 17(4), 373-387. doi: 10.1111/j.1558-5646.1963.tb03295.x
[10] MacArthur, R. H., and Levins, R. (1967). The limiting similarity, convergence, and divergence of coexisting species. The American Naturalist, 101(921), 377-385. doi: 10.1086/282505
[11] Viana, D. S., and Chase, J. M. (2019). Spatial scale modulates the inference of metacommunity assembly processes. Ecology, 100(2), e02576. doi: 10.1002/ecy.2576
[12] Chave, J. (2013). The problem of pattern and scale in ecology: what have we learned in 20 years?. Ecology letters, 16, 4-16. doi: 10.1111/ele.12048
[13] Patrick, C. J., and Yuan, L. L. (2019). The challenges that spatial context present for synthesizing community ecology across scales. Oikos, 128(3), 297-308. doi: 10.1111/oik.05802
[14] Chase, J. M., and Knight, T. M. (2013). Scale‐dependent effect sizes of ecological drivers on biodiversity: why standardised sampling is not enough. Ecology letters, 16, 17-26. doi: 10.1111/ele.12112
[15] Horváth, Z., Ptacnik, R., Vad, C. F., and Chase, J. M. (2019). Habitat loss over six decades accelerates regional and local biodiversity loss via changing landscape connectance. Ecology letters, 22(6), 1019-1027. doi: 10.1111/ele.13260
[16] Chase, J. M, Gooriah, L., May, F., Ryberg, W. A, Schuler, M. S, Craven, D., and Knight, T. M. (2019). A framework for disentangling ecological mechanisms underlying the island species–area relationship. Frontiers of Biogeography, 11(1). doi: 10.21425/F5FBG40844.
[17] Siqueira T., Saito V. S., Bini L. M., Melo A. S., Petsch D. K. , Landeiro V. L., Tolonen K. T., Jyrkänkallio-Mikkola J., Soininen J. and Heino J. (2019). Community size affects the signals of ecological drift and niche selection on biodiversity. bioRxiv 515098, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/515098
[18] Hastings A., Gross L. J. eds. (2012). Encyclopedia of theoretical ecology (University of California Press, Berkeley).
[19] Chase, J. M., Kraft, N. J., Smith, K. G., Vellend, M., and Inouye, B. D. (2011). Using null models to disentangle variation in community dissimilarity from variation in α‐diversity. Ecosphere, 2(2), 1-11. doi: 10.1890/ES10-00117.1

Community size affects the signals of ecological drift and selection on biodiversityTadeu Siqueira, Victor S. Saito, Luis M. Bini, Adriano S. Melo, Danielle K. Petsch, Victor L. Landeiro, Kimmo T. Tolonen, Jenny Jyrkänkallio-Mikkola, Janne Soininen, Jani Heino<p>Ecological drift can override the effects of deterministic niche selection on small populations and drive the assembly of small communities. We tested the hypothesis that smaller local communities are more dissimilar among each other because of...Biodiversity, Coexistence, Community ecology, Competition, Conservation biology, Dispersal & Migration, Freshwater ecology, Spatial ecology, Metacommunities & MetapopulationsEric Harvey2019-01-09 19:06:21 View
27 Apr 2021
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Joint species distributions reveal the combined effects of host plants, abiotic factors and species competition as drivers of species abundances in fruit flies

Understanding the interplay between host-specificity, environmental conditions and competition through the sound application of Joint Species Distribution Models

Recommended by ORCID_LOGO based on reviews by Joaquín Calatayud and Carsten Dormann

Understanding why and how species coexist in local communities is one of the central questions in ecology. There is general agreement that species distribution and coexistence are determined by a number of key mechanisms, including the environmental requirements of species, dispersal, evolutionary constraints, resource availability and selection, metapopulation dynamics, and biotic interactions (e.g. Soberón & Nakamura 2009; Colwell & Rangel 2009; Ricklefs 2015). These factors are however intricately intertwined in a scale-structured fashion (Hortal et al. 2010; D’Amen et al. 2017), making it particularly difficult to tease apart the effects of each one of them. This could be addressed by the novel field of Joint Species Distribution Modelling (JSDM; Okasvainen & Abrego 2020), as it allows assessing the effects of several sets of factors and the co-occurrence and/or covariation in abundances of potentially interacting species at the same time (Pollock et al. 2014; Ovaskainen et al. 2016; Dormann et al. 2018). However, the development of JSDM has been hampered by the general lack of good-quality detailed data on species co-occurrences and abundances (see Hortal et al. 2015).

Facon et al. (2021) use a particularly large compilation of field surveys to study the abundance and co-occurrence of Tephritidae fruit flies in c. 400 orchards, gardens and natural areas throughout the island of Réunion. Further, they combine such information with lab data on their host-selection fundamental niche (i.e. in the absence of competitors), codifying traits of female choice and larval performances in 21 host species. They use Poisson Log-Normal models, a type of mixed model that allows one to jointly model the random effects associated with all species, and retrieve the covariations in abundance that are not explained by environmental conditions or differences in sampling effort. Then, they use a series of models to evaluate the effects on these matrices of ecological covariates (date, elevation, habitat, climate and host plant), species interactions (by comparing with a constrained residual variance-covariance matrix) and the species’ host-selection fundamental niches (through separate models for each fly species).

The eight Tephritidae species inhabiting Réunion include both generalists and specialists in Solanaceae and Cucurbitaceae with a known history of interspecific competition. Facon et al. (2021) use a comprehensive JSDM approach to assess the effects of different factors separately and altogether. This allows them to identify large effects of plant hosts and the fundamental host-selection niche on species co-occurrence, but also to show that ecological covariates and weak –though not negligible– species interactions are necessary to account for all residual variance in the matrix of joint species abundances per site. Further, they also find evidence that the fitness per host measured in the lab has a strong influence on the abundances in each host plant in the field for specialist species, but not for generalists. Indeed, the stronger effects of competitive exclusion were found in pairs of Cucurbitaceae specialist species. However, these analyses fail to provide solid grounds to assess why generalists are rarely found in Cucurbitaceae and Solanaceae. Although they argue that this may be due to Connell’s (1980) ghost of competition past (past competition that led to current niche differentiation), further data on the evolutionary history of these fruit flies is needed to assess this hypothesis.

Finding evidence for the effects of competitive interactions on species’ occurrences and spatial distributions is often difficult, perhaps because these effects occur over longer time scales than the ones usually studied by ecologists (Yackulic 2017). The work by Facon and colleagues shows that weak effects of competition can be detected also at the short ecological timescales that determine coexistence in local communities, under the virtuous combination of good-quality data and sound analytical designs that account for several aspects of species’ niches, their biotopes and their joint population responses. This adds a new dimension to the application of Hutchinson’s (1978) niche framework to understand the spatial dynamics of species and communities (see also Colwell & Rangel 2009), although further advances to incorporate dispersal-driven metacommunity dynamics (see, e.g., Ovaskainen et al. 2016; Leibold et al. 2017) are certainly needed. Nonetheless, this work shows the potential value of in-depth analyses of species coexistence based on combining good-quality field data with well-thought out JSDM applications. If many studies like this are conducted, it is likely that the uprising field of Joint Species Distribution Modelling will improve our understanding of the hierarchical relationships between the different factors affecting species coexistence in ecological communities in the near future.



Colwell RK, Rangel TF (2009) Hutchinson’s duality: The once and future niche. Proceedings of the National Academy of Sciences, 106, 19651–19658.

Connell JH (1980) Diversity and the Coevolution of Competitors, or the Ghost of Competition Past. Oikos, 35, 131–138.

D’Amen M, Rahbek C, Zimmermann NE, Guisan A (2017) Spatial predictions at the community level: from current approaches to future frameworks. Biological Reviews, 92, 169–187.

Dormann CF, Bobrowski M, Dehling DM, Harris DJ, Hartig F, Lischke H, Moretti MD, Pagel J, Pinkert S, Schleuning M, Schmidt SI, Sheppard CS, Steinbauer MJ, Zeuss D, Kraan C (2018) Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions. Global Ecology and Biogeography, 27, 1004–1016.

Facon B, Hafsi A, Masselière MC de la, Robin S, Massol F, Dubart M, Chiquet J, Frago E, Chiroleu F, Duyck P-F, Ravigné V (2021) Joint species distributions reveal the combined effects of host plants, abiotic factors and species competition as drivers of community structure in fruit flies. bioRxiv, 2020.12.07.414326. ver. 4 peer-reviewed and recommended by Peer community in Ecology.

Hortal J, de Bello F, Diniz-Filho JAF, Lewinsohn TM, Lobo JM, Ladle RJ (2015) Seven Shortfalls that Beset Large-Scale Knowledge of Biodiversity. Annual Review of Ecology, Evolution, and Systematics, 46, 523–549.

Hortal J, Roura‐Pascual N, Sanders NJ, Rahbek C (2010) Understanding (insect) species distributions across spatial scales. Ecography, 33, 51–53.

Hutchinson, G.E. (1978) An introduction to population biology. Yale University Press, New Haven, CT.

Leibold MA, Chase JM, Ernest SKM (2017) Community assembly and the functioning of ecosystems: how metacommunity processes alter ecosystems attributes. Ecology, 98, 909–919.

Ovaskainen O, Abrego N (2020) Joint Species Distribution Modelling: With Applications in R. Cambridge University Press, Cambridge.

Ovaskainen O, Roy DB, Fox R, Anderson BJ (2016) Uncovering hidden spatial structure in species communities with spatially explicit joint species distribution models. Methods in Ecology and Evolution, 7, 428–436.

Pollock LJ, Tingley R, Morris WK, Golding N, O’Hara RB, Parris KM, Vesk PA, McCarthy MA (2014) Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM). Methods in Ecology and Evolution, 5, 397–406.

Ricklefs RE (2015) Intrinsic dynamics of the regional community. Ecology Letters, 18, 497–503.

Soberón J, Nakamura M (2009) Niches and distributional areas: Concepts, methods, and assumptions. Proceedings of the National Academy of Sciences, 106, 19644–19650.

Yackulic CB (2017) Competitive exclusion over broad spatial extents is a slow process: evidence and implications for species distribution modeling. Ecography, 40, 305–313.

Joint species distributions reveal the combined effects of host plants, abiotic factors and species competition as drivers of species abundances in fruit fliesBenoit Facon, Abir Hafsi, Maud Charlery de la Masselière, Stéphane Robin, François Massol, Maxime Dubart, Julien Chiquet, Enric Frago, Frédéric Chiroleu, Pierre-François Duyck & Virginie Ravigné<p style="text-align: justify;">The relative importance of ecological factors and species interactions for phytophagous insect species distributions has long been a controversial issue. Using field abundances of eight sympatric Tephritid fruit fli...Biodiversity, Coexistence, Community ecology, Competition, Herbivory, Interaction networks, Species distributionsJoaquín Hortal Carsten Dormann, Joaquín Calatayud2020-12-08 06:44:25 View
01 Apr 2019
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The inherent multidimensionality of temporal variability: How common and rare species shape stability patterns

Diversity-Stability and the Structure of Perturbations

Recommended by ORCID_LOGO and based on reviews by Frederic Barraquand and 1 anonymous reviewer

In his 1972 paper “Will a Large Complex System Be Stable?” [1], May challenges the idea that large communities are more stable than small ones. This was the beginning of a fundamental debate that still structures an entire research area in ecology: the diversity-stability debate [2]. The most salient strength of May’s work was to use a mathematical argument to refute an idea based on the observations that simple communities are less stable than large ones. Using the formalism of dynamical systems and a major results on the distribution of the eigen values for random matrices, May demonstrated that the addition of random interactions destabilizes ecological communities and thus, rich communities with a higher number of interactions should be less stable. But May also noted that his mathematical argument holds true only if ecological interactions are randomly distributed and thus concluded that this must not be true! This is how the contradiction between mathematics and empirical observations led to new developments in the study of ecological networks.
Since 1972, the theoretical corpus of ecology has advanced, building on the formalism of dynamical systems, ecologists have revealed that ecological interactions are indeed not randomly distributed [3,4], but general rules are still missing and we are far from understanding what determine the exact network topology of a given community. One promising avenue is to understand the relationship between different facets of the concept of stability [5,6]. Indeed, the classical approach to determine whether a system is stable is qualitative: if a system returns to its equilibrium when it is slightly moved away from it, then the system is considered stable. But there are several other aspects that are worth scrutinizing. For instance, when a system returns to its equilibrium, one can characterize the corresponding transient dynamics [7,8], that is asking fundamental questions such as: what is the trajectory of return? How long does it take to return to the equilibrium? Another fundamental question is whether the system remains qualitatively stable when the distributions of interactions strengths change? From a biological standpoint, all of these questions matter as all these aspects of stability may partially explain the actual structure of ecological networks, and hence, frameworks that integrate several facets of stability are much needed.
The study by Arnoldi et al. [9] is a significant step towards such a framework. The strength of their formalism is threefold. First, instead of considering separately the system and its perturbations, they considering the fluctuations of a perturbed ecological systems and thus, perturbations are parts of the ecological system. Second, they use of a broad definition of perturbation that encompasses the types of perturbations (whether the individual respond synchronously or not), their intensity and their direction (how the perturbations are correlated across species). Third, they quantify the instability of the system using variability which integrates the consequences of perturbations over the whole set of species of a community: such a measure is comparable across communities and accounts for the trivial effect of the perturbations on the system dynamics.
Using this framework, the authors show that interactions within a stable community leads to a general relationship between variability and the abundance of individually perturbed species: if individuals of species respond in synchrony to a perturbation, then the more abundant the species perturbed the higher the variability of the system, but the relationship is reverse when individual respond asynchronously. A direct implications of these results for the classical debate is that the diversity-stability relationship is negative for the former type of perturbations (as in May’s seminal paper) but positive for the latter type. Hence, the rigorous work of Arnoldi and colleagues sheds a new light upon the classical debate: the nature of the perturbation regime prevailing within a community affects the slope of the diversity-stability relationships and given the vast diversity of ecological communities, this may very well be one of the reasons why the debate still endures.
From a historical perspective, it is interesting that ecologists have gone from looking at random webs to structured webs and now, in a sense, Arnoldi et al. are unpacking the role of differentially structured perturbations. The work they achieved will doubtlessly be followed by further theoretical investigations. One natural research avenue is to revisit the role of the topology of ecological networks with this framework: how the distribution of interactions and their strength affect the general relationship they unravel? Finally, this study demonstrate that the impact of the abundance of a species on the variability of the system depends on the nature of the perturbation regime and so the distribution of species abundances within a community should be determined by the prevailing perturbation regime which is a prediction that remains to be tested.


[1] May, Robert M (1972). Will a Large Complex System Be Stable? Nature 238, 413–414. doi: 10.1038/238413a0
[2] McCann, Kevin Shear (2000). The Diversity–Stability Debate. Nature 405, 228–233. doi: 10.1038/35012234
[3] Rooney, Neil, Kevin McCann, Gabriel Gellner, and John C. Moore (2006). Structural Asymmetry and the Stability of Diverse Food Webs. Nature 442, 265–269. doi: 10.1038/nature04887
[4] Jacquet, Claire, Charlotte Moritz, Lyne Morissette, Pierre Legagneux, François Massol, Philippe Archambault, and Dominique Gravel (2016). No Complexity–Stability Relationship in Empirical Ecosystems. Nature Communications 7, 12573. doi: 10.1038/ncomms12573
[5] Donohue, Ian, Helmut Hillebrand, José M. Montoya, Owen L. Petchey, Stuart L. Pimm, Mike S. Fowler, Kevin Healy, et al. (2016). Navigating the Complexity of Ecological Stability. Ecology Letters 19, 1172–1185. doi: 10.1111/ele.12648
[6] Arnoldi, Jean-François, and Bart Haegeman (2016). Unifying Dynamical and Structural Stability of Equilibria. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science 472, 20150874. doi: 10.1098/rspa.2015.0874
[7] Caswell, Hal, and Michael G. Neubert (2005). Reactivity and Transient Dynamics of Discrete-Time Ecological Systems. Journal of Difference Equations and Applications 11, 295–310. doi: 10.1080/10236190412331335382
[8] Arnoldi, J-F., M. Loreau, and B. Haegeman (2016). Resilience, Reactivity and Variability: A Mathematical Comparison of Ecological Stability Measures. Journal of Theoretical Biology 389, 47–59. doi: 10.1016/j.jtbi.2015.10.012
[9] Arnoldi, Jean-Francois, Michel Loreau, and Bart Haegeman. (2019). The Inherent Multidimensionality of Temporal Variability: How Common and Rare Species Shape Stability Patterns.” BioRxiv, 431296, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/431296

The inherent multidimensionality of temporal variability: How common and rare species shape stability patternsJean-François Arnoldi, Michel Loreau, Bart Haegeman<p>Empirical knowledge of ecosystem stability and diversity-stability relationships is mostly based on the analysis of temporal variability of population and ecosystem properties. Variability, however, often depends on external factors that act as...Biodiversity, Coexistence, Community ecology, Competition, Interaction networks, Theoretical ecologyKevin Cazelles2018-10-02 14:01:03 View
10 Jan 2024
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Beyond variance: simple random distributions are not a good proxy for intraspecific variability in systems with environmental structure

Two paradigms for intraspecific variability

Recommended by ORCID_LOGO based on reviews by Simon Blanchet and Bart Haegeman

Community ecology usually concerns itself with understanding the causes and consequences of diversity at a given taxonomic resolution, most classically at the species level. Yet there is no doubt that diversity exists at all scales, and phenotypic variability within a taxon can be comparable to differences between taxa, as observed from bacteria to fish and trees. The question that motivates an active and growing body of work (e.g. Raffard et al 2019) is not so much whether intraspecific variability matters, but what we get wrong by ignoring it and how to incorporate it into our understanding of communities. There is no established way to think about diversity at multiple nested taxonomic levels, and it is tempting to summarize intraspecific variability simply by measuring species mean and variance in any trait and metric.

In this study, Girard-Tercieux et al (2023a) propose that, to understand its impact on community-level outcomes and in particular on species coexistence, we should carefully distinguish between two ways of thinking about intraspecific variability:

-"unstructured" variation, where every individual's features are like an independent random draw from a species-specific distribution, for instance, due to genetic lottery and developmental accidents

-"structured" variation that is due to each individual encountering a different but enduring microenvironment.

The latter type of variability may still appear complex and random-like when the environment is high-dimensional (i.e. multifaceted, with many different factors contributing to each individual's performance and development). Thus, it is not necessarily "structured" in the sense of being easily understood -- we may need to measure more aspects of the environment than is practical if we want to fully predict these variations.

What distinguishes this "structured" variability is that it is, in a loose sense, inheritable: individuals from the same species that grow in the same microenvironment will have the same performance, in a repeatable fashion. Thus, if each species is best at exploiting at least a fraction of environmental conditions, it is likely to avoid extinction by competition, except in the unlucky case of no propagule reaching any of the favorable sites.
By contrast, drawing each individual's preferences and performance randomly at each generation (from its own species distribution, but independently from other and past individuals) leads to stochastic dynamics, so-called ecological drift, that easily induce a large number of species extinctions.

The core intuition, that the complex spatial structure and high-dimensional nature of the environment plays a key explanatory role in species coexistence, is a running thread through several of the authors' work (e.g. Clark et al 2010), clearly inspired by their focus on tropical forests. This study, by tackling the question of intraspecific determinants of interspecific outcomes, makes a compelling addition to this line of investigation, coming as a theoretical companion to a more data-oriented study (Girard-Tercieux et al 2023b). But I believe it raises a question that is even broader in scope.

This kind of intraspecific variability, due to different individuals growing in different microenvironments, is perhaps most relevant for trees and other sessile organisms, but the distinction made here between "unstructured" and "structured" variability can likely be extended to many other ecological settings.

In my understanding, what matters most in "structured" variability is not so much it stemming from a fixed environment, but rather it being maintained across generations, rather than possibly lost by drift. This difference between variability in the form of "frozen" randomness and in the form of stochastic drift over time is highly relevant in other theoretical fields (e.g. in physics, where it is the difference between a disordered solid and a liquid), and thus, I expect that it is a meaningful distinction to make throughout community ecology.


James S. Clark, David Bell, Chengjin Chu, Benoit Courbaud, Michael Dietze, Michelle Hersh, Janneke HilleRisLambers et al. (2010) "High‐dimensional coexistence based on individual variation: a synthesis of evidence." Ecological Monographs 80, no. 4 : 569-608.

Camille Girard-Tercieux, Ghislain Vieilledent, Adam Clark, James S. Clark, Benoît Courbaud, Claire Fortunel, Georges Kunstler, Raphaël Pélissier, Nadja Rüger, Isabelle Maréchaux (2023a) "Beyond variance: simple random distributions are not a good proxy for intraspecific variability in systems with environmental structure." bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Ecology.

Camille Girard‐Tercieux, Isabelle Maréchaux, Adam T. Clark, James S. Clark, Benoît Courbaud, Claire Fortunel, Joannès Guillemot et al. (2023b) "Rethinking the nature of intraspecific variability and its consequences on species coexistence." Ecology and Evolution 13, no. 3 : e9860.

Allan Raffard, Frédéric Santoul, Julien Cucherousset, and Simon Blanchet. (2019) "The community and ecosystem consequences of intraspecific diversity: A meta‐analysis." Biological Reviews 94, no. 2: 648-661.

Beyond variance: simple random distributions are not a good proxy for intraspecific variability in systems with environmental structureCamille Girard-Tercieux, Ghislain Vieilledent, Adam Clark, James S. Clark, Benoit Courbaud, Claire Fortunel, Georges Kunstler, Raphaël Pélissier, Nadja Rüger, Isabelle Maréchaux<p>The role of intraspecific variability (IV) in shaping community dynamics and species coexistence has been intensively discussed over the past decade and modelling studies have played an important role in that respect. However, these studies oft...Biodiversity, Coexistence, Community ecology, Competition, Theoretical ecologyMatthieu Barbier2022-08-07 12:51:30 View
21 Nov 2023
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Pathogen community composition and co-infection patterns in a wild community of rodents

Reservoirs of pestilence: what pathogen and rodent community analyses can tell us about transmission risk

Recommended by ORCID_LOGO based on reviews by Adrian Diaz, Romain Pigeault and 1 anonymous reviewer

Rodents are well known as one of the main animal groups responsible for human-transmitted pathogens. As such, it seems logical to try and survey what kinds of pathogenic microbes might be harboured by wild rodents, in order to establish some baseline surveillance and prevent future zoonotic outbreaks (Bernstein et al., 2022). This is exactly what Abbate et al. (2023) endeavoured and their findings are intimidating. Based on quite a large sampling effort, they collected more than 700 rodents of seven species around two villages in northeastern France. They looked for molecular markers indicative of viral and bacterial infections and proceeded to analyze their pathogen communities using multivariate techniques.

Variation in the prevalence of the different pathogens was found among host species, with e.g. signs of CPXV more prevalent in Cricetidae while some Mycoplasma strains were more prevalent in Muridae. Co-circulation of pathogens was found in all species, with some evidencing signs of up to 12 different pathogen taxa. The diversity of co-circulating pathogens was markedly different between host species and higher in adult hosts, but not affected by sex. The dataset also evinced some slight differences between habitats, with meadows harbouring a little more diversity of rodent pathogens than forests. Less intuitively, some pathogen associations seemed quite repeatable, such as the positive association of Bartonella spp. with CPXV in the montane water vole. The study allowed the authors to test several associations already described in the literature, including associations between different hemotropic Mycoplasma species.

I strongly invite colleagues interested in zoonoses, emerging pandemics and more generally One Health to read the paper of Abbate et al. (2023) and try to replicate them across the world. To prevent the next sanitary crises, monitoring rodents, and more generally vertebrates, population demographics is a necessary and enlightening step (Johnson et al., 2020), but insufficient. Following the lead of colleagues working on rodent ectoparasites (Krasnov et al., 2014), we need more surveys like the one described by Abbate et al. (2023) to understand the importance of the dilution effect in the prevalence and transmission of microbial pathogens (Andreazzi et al., 2023) and the formation of epidemics. We also need other similar studies to assess the potential of different rodent species to carry pathogens more or less capable of infecting other mammalian species (Morand et al., 2015), in other places in the world.


Abbate, J. L., Galan, M., Razzauti, M., Sironen, T., Voutilainen, L., Henttonen, H., Gasqui, P., Cosson, J.-F. & Charbonnel, N. (2023) Pathogen community composition and co-infection patterns in a wild community of rodents. BioRxiv, ver.4 peer-reviewed and recommended by Peer Community in Ecology. 

Andreazzi, C. S., Martinez-Vaquero, L. A., Winck, G. R., Cardoso, T. S., Teixeira, B. R., Xavier, S. C. C., Gentile, R., Jansen, A. M. & D'Andrea, P. S. (2023) Vegetation cover and biodiversity reduce parasite infection in wild hosts across ecological levels and scales. Ecography, 2023, e06579.
Bernstein, A. S., Ando, A. W., Loch-Temzelides, T., Vale, M. M., Li, B. V., Li, H., Busch, J., Chapman, C. A., Kinnaird, M., Nowak, K., Castro, M. C., Zambrana-Torrelio, C., Ahumada, J. A., Xiao, L., Roehrdanz, P., Kaufman, L., Hannah, L., Daszak, P., Pimm, S. L. & Dobson, A. P. (2022) The costs and benefits of primary prevention of zoonotic pandemics. Science Advances, 8, eabl4183.
Johnson, C. K., Hitchens, P. L., Pandit, P. S., Rushmore, J., Evans, T. S., Young, C. C. W. & Doyle, M. M. (2020) Global shifts in mammalian population trends reveal key predictors of virus spillover risk. Proceedings of the Royal Society B: Biological Sciences, 287, 20192736.
Krasnov, B. R., Pilosof, S., Stanko, M., Morand, S., Korallo-Vinarskaya, N. P., Vinarski, M. V. & Poulin, R. (2014) Co-occurrence and phylogenetic distance in communities of mammalian ectoparasites: limiting similarity versus environmental filtering. Oikos, 123, 63-70.
Morand, S., Bordes, F., Chen, H.-W., Claude, J., Cosson, J.-F., Galan, M., Czirjak, G. Á., Greenwood, A. D., Latinne, A., Michaux, J. & Ribas, A. (2015) Global parasite and Rattus rodent invasions: The consequences for rodent-borne diseases. Integrative Zoology, 10, 409-423.

Pathogen community composition and co-infection patterns in a wild community of rodentsJessica Lee Abbate, Maxime Galan, Maria Razzauti, Tarja Sironen, Liina Voutilainen, Heikki Henttonen, Patrick Gasqui, Jean-François Cosson, Nathalie Charbonnel<p style="text-align: justify;">Rodents are major reservoirs of pathogens that can cause disease in humans and livestock. It is therefore important to know what pathogens naturally circulate in rodent populations, and to understand the factors tha...Biodiversity, Coexistence, Community ecology, Eco-immunology & Immunity, Epidemiology, Host-parasite interactions, Population ecology, Species distributionsFrancois Massol2020-02-11 12:42:28 View
06 Sep 2019
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Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition

On the importance of temporal meta-community dynamics for our understanding of assembly processes

Recommended by ORCID_LOGO based on reviews by Joaquín Hortal and 2 anonymous reviewers

The processes that trigger community assembly are still in the centre of ecological interest. While prior work mostly focused on spatial patterns of co-occurrence within a meta-community framework [reviewed in 1, 2] recent studies also include temporal patterns of community composition [e.g. 3, 4, 5, 6]. In this preprint [7], Franck Jabot and co-workers extend they prior approaches to quasi neutral community assembly [8, 9, 10] and develop an analytical framework of spatial and temporal diversity turnover. A simple and heuristic path model for beta diversity and an extended ecological drift model serve as starting points. The model can be seen as a counterpart to Ulrich et al. [5]. These authors implemented competitive hierarchies into their neutral meta-community model while the present paper focuses on environmental filtering. Most important, the model and parameterization of four empirical data sets on aquatic plant and animal meta-communities used by Jabot et al. returned a consistent high influence of environmental stochasticity on species turnover. Of course, this major result does not come to a surprise. As typical for this kind of models it depends also to a good deal on the initial model settings. It nevertheless makes a strong conceptual point for the importance of environmental variability over dispersal and richness effects. One interesting side effect regards the impact of richness differences (ΔS). Jabot et al. interpret this as a ‘nuisance variable’ as they do not have a stringent explanation. Of course, it might be a pure statistical bias introduced by the Soerensen metric of turnover that is normalized by richness. However, I suspect that there is more behind the ΔS effect. Richness differences are generally associated with respective differences in total abundances and introduce source – sink dynamics that inevitably shape subsequent colonization – extinction processes. It would be interesting to see whether ΔS alone is able to trigger observed patterns of community assembly and community composition. Such an analysis would require partitioning of species turnover into richness and nestedness effects [11]. I encourage Jabot et al. to undertake such an effort.
The present paper is also another call to include temporal population variability into metapopulation models for a better understanding of the dynamics and triggering of community assembly. In a next step, competitive interactions should be included into the model to infer the relative importance of both factors.


[1] Götzenberger, L. et al. (2012). Ecological assembly rules in plant communities—approaches, patterns and prospects. Biological reviews, 87(1), 111-127. doi: 10.1111/j.1469-185X.2011.00187.x
[2] Ulrich, W., & Gotelli, N. J. (2013). Pattern detection in null model analysis. Oikos, 122(1), 2-18. doi: 10.1111/j.1600-0706.2012.20325.x
[3] Grilli, J., Barabás, G., Michalska-Smith, M. J., & Allesina, S. (2017). Higher-order interactions stabilize dynamics in competitive network models. Nature, 548(7666), 210. doi: 10.1038/nature23273
[4] Nuvoloni, F. M., Feres, R. J. F., & Gilbert, B. (2016). Species turnover through time: colonization and extinction dynamics across metacommunities. The American Naturalist, 187(6), 786-796. doi: 10.1086/686150
[5] Ulrich, W., Jabot, F., & Gotelli, N. J. (2017). Competitive interactions change the pattern of species co‐occurrences under neutral dispersal. Oikos, 126(1), 91-100. doi: 10.1111/oik.03392
[6] Dobramysl, U., Mobilia, M., Pleimling, M., & Täuber, U. C. (2018). Stochastic population dynamics in spatially extended predator–prey systems. Journal of Physics A: Mathematical and Theoretical, 51(6), 063001. doi: 10.1088/1751-8121/aa95c7
[7] Jabot, F., Laroche, F., Massol, F., Arthaud, F., Crabot, J., Dubart, M., Blanchet, S., Munoz, F., David, P., and Datry, T. (2019). Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition. bioRxiv, 480335, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/480335
[8] Jabot, F., & Chave, J. (2011). Analyzing tropical forest tree species abundance distributions using a nonneutral model and through approximate Bayesian inference. The American Naturalist, 178(2), E37-E47. doi: 10.1086/660829
[9] Jabot, F., & Lohier, T. (2016). Non‐random correlation of species dynamics in tropical tree communities. Oikos, 125(12), 1733-1742. doi: 10.1111/oik.03103
[10] Datry, T., Bonada, N., & Heino, J. (2016). Towards understanding the organisation of metacommunities in highly dynamic ecological systems. Oikos, 125(2), 149-159. doi: 10.1111/oik.02922
[11] Baselga, A. (2010). Partitioning the turnover and nestedness components of beta diversity. Global ecology and biogeography, 19(1), 134-143. doi: 10.1111/j.1466-8238.2009.00490.x

Assessing metacommunity processes through signatures in spatiotemporal turnover of community compositionFranck Jabot, Fabien Laroche, Francois Massol, Florent Arthaud, Julie Crabot, Maxime Dubart, Simon Blanchet, Francois Munoz, Patrice David, Thibault Datry<p>Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and still consists mostly of r...Biodiversity, Coexistence, Community ecology, Spatial ecology, Metacommunities & MetapopulationsWerner Ulrich2018-11-29 14:58:54 View
29 Aug 2023
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Provision of essential resources as a persistence strategy in food webs

High-order interactions in food webs may strongly impact persistence of species

Recommended by ORCID_LOGO based on reviews by Jean-Christophe POGGIALE and 1 anonymous reviewer

Michael Raatz (2023) provides here a relevant exploration of higher-order interactions, i.e. interactions involving more than two related species (Terry et al. 2019), in the case of food web and competition interactions. More precisely, he shows by modeling that essential resources may significantly mediate focal species' persistence. Simultaneously, the provision of essential resources may strongly affect the resulting community structure, by driving to extinction first the predator and then, depending on the higher-order interaction, potentially also the associated competitor. 

Today, all ecologists should be aware of the potential effects of high-order interactions on species' (and likely on ecosystem's) fate (Golubski et al. 2016, Grilli et al. 2017). Yet, we should soon be prepared to include any high-order interaction into any interaction network (i.e. not only between species, but also between species and abiotic components, and between biotic, anthropogenic and abiotic components too). For this purpose, we will need innovative approaches such as hypergraphs (Golubski et al. 2016) and discrete-event models (Gaucherel and Pommereau 2019, Thomas et al. 2022) able to manage highly complex interactions, with numerous interacting components and variables. Such a rigorous study is a necessary and preliminary step in taking into account such a higher complexity. 


Gaucherel, C. and F. Pommereau. 2019. Using discrete systems to exhaustively characterize the dynamics of an integrated ecosystem. Methods in Ecology and Evolution 00:1–13.

Golubski, A. J., E. E. Westlund, J. Vandermeer, and M. Pascual. 2016. Ecological Networks over the Edge: Hypergraph Trait-Mediated Indirect Interaction (TMII) Structure trends in Ecology & Evolution 31:344-354.

Grilli, J., G. Barabas, M. J. Michalska-Smith, and S. Allesina. 2017. Higher-order interactions stabilize dynamics in competitive network models. Nature 548:210-213.

Raatz, M. 2023. Provision of essential resources as a persistence strategy in food webs. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology.

Terry, J. C. D., R. J. Morris, and M. B. Bonsall. 2019. Interaction modifications lead to greater robustness than pairwise non-trophic effects in food webs. Journal of Animal Ecology 88:1732-1742.

Thomas, C., M. Cosme, C. Gaucherel, and F. Pommereau. 2022. Model-checking ecological state-transition graphs. PLoS Computational Biology 18:e1009657.

Provision of essential resources as a persistence strategy in food websMichael Raatz<p style="text-align: justify;">Pairwise interactions in food webs, including those between predator and prey are often modulated by a third species. Such higher-order interactions are important structural components of natural food webs that can ...Biodiversity, Coexistence, Competition, Ecological stoichiometry, Food webs, Interaction networks, Theoretical ecologyCédric Gaucherel2023-02-23 17:48:26 View
06 Nov 2023
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Influence of mimicry on extinction risk in Aculeata: a theoretical approach

Mullerian and Batesian mimicry can influence population and community dynamics

Recommended by based on reviews by Jesus Bellver and 1 anonymous reviewer

Mimicry between species has long attracted the attention of scientists. Over a century ago, Bates first proposed that palatable species should gain a benefit by resembling unpalatable species (Bates 1862). Not long after, Müller suggested that there could also be a mutual advantage for two unpalatable species to mimic one another to reduce predator error (Müller 1879). These forms of mimicry, Batesian and Müllerian, are now widely studied, providing broad insights into behaviour, ecology and evolution.

Numerous taxa, including both invertebrates and vertebrates, show examples of Batesian or Müllerian mimicry. Bees and wasps provide a particularly interesting case due to the differences in defence between females and males of the same species. While both males and females may display warning colours, only females can sting and inject venom to cause pain and allow escape from predators. Therefore, males are palatable mimics and can resemble females of their own species or females of another species (dual sex-limited mimicry). This asymmetry in defence could have impacts on both population structure and community assembly, yet research into mimicry largely focuses on systems without sex differences.

Here, Boutin and colleagues (2023) use a differential equations model to explore the effect of mimicry on population structure and community assembly for sex-limited defended species. Specifically, they address three questions, 1) how do female noxiousness and sex-ratio influence the extinction risk of a single species?; 2) what is the effect of mimicry on species co-existence? and 3) how does dual sex-limited mimicry influence species co-existence? Their results reveal contexts in which populations with undefended males can persist, the benefit of Müllerian mimicry for species coexistence and that dual sex-limited mimicry can have a destabilising impact on species coexistence.

The results not only contribute to our understanding of how mimicry is maintained in natural systems but also demonstrate how changes in relative abundance or population structure of one species could impact another species. Further insight into the population and community dynamics of insects is particularly important given the current population declines (Goulson 2019; Seibold et al 2019).


Bates, H. W. 1862. Contributions to the insect fauna of the Amazon Valley, Lepidoptera: Heliconidae. Trans. Linn. Soc. Lond. 23:495- 566.

Boutin, M., Costa, M., Fontaine, C., Perrard, A., Llaurens, V. 2022 Influence of sex-limited mimicry on extinction risk in Aculeata: a theoretical approach. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology.

Goulson, D. 2019. The insect apocalypse, and why it matters. Curr. Biol. 29: R967-R971.

Müller, F. 1879. Ituna and Thyridia; a remarkable case of mimicry in butterflies. Trans. Roy. Entom. Roc. 1879:20-29.

Seibold, S., Gossner, M. M., Simons, N. K., Blüthgen, N., Müller, J., Ambarlı, D., ... & Weisser, W. W. 2019. Arthropod decline in grasslands and forests is associated with landscape-level drivers. Nature, 574: 671-674.

Influence of mimicry on extinction risk in Aculeata: a theoretical approachMaxime Boutin, Manon Costa, Colin Fontaine, Adrien Perrard, Violaine Llaurens<p style="text-align: justify;">Positive ecological interactions, such as mutualism, can play a role in community structure and species co-existence. A well-documented case of mutualistic interaction is Mullerian mimicry, the convergence of colour...Biodiversity, Coexistence, Eco-evolutionary dynamics, Evolutionary ecology, Facilitation & MutualismAmanda Franklin2022-10-25 19:11:55 View
11 Mar 2021
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Size-dependent eco-evolutionary feedbacks in fisheries

“Hidden” natural selection and the evolution of body size in harvested stocks

Recommended by based on reviews by Jean-François Arnoldi and 1 anonymous reviewer

Humans are exploiting biological resources since thousands of years. Exploitation of biological resources has become particularly intense since the beginning of the 20th century and the steep increase in the worldwide human population size. Marine and freshwater fishes are not exception to that rule, and they have been (and continue to be) strongly harvested as a source of proteins for humans. For some species, fishery has been so intense that natural stocks have virtually collapsed in only a few decades. The worst example begin that of the Northwest Atlantic cod that has declined by more than 95% of its historical biomasses in only 20-30 years of intensive exploitation (Frank et al. 2005). These rapid and steep changes in biomasses have huge impacts on the entire ecosystems since species targeted by fisheries are often at the top of trophic chains (Frank et al. 2005). 

Beyond demographic impacts, fisheries also have evolutionary impacts on populations, which can also indirectly alter ecosystems (Uusi-Heikkilä et al. 2015; Palkovacs et al. 2018). Fishermen generally focus on the largest specimens, and hence exert a strong selective pressure against these largest fish (which is called “harvest selection”). There is now ample evidence that harvest selection can lead to rapid evolutionary changes in natural populations toward small individuals (Kuparinen & Festa-Bianchet 2017). These evolutionary changes are of course undesirable from a human perspective, and have attracted many scientific questions. Nonetheless, the consequence of harvest selection is not always observable in natural populations, and there are cases in which no phenotypic change (or on the contrary an increase in mean body size) has been observed after intense harvest pressures. In a conceptual Essay, Edeline and Loeuille (Edeline & Loeuille 2020) propose novel ideas to explain why the evolutionary consequences of harvest selection can be so diverse, and how a cross talk between ecological and evolutionary dynamics can explain patterns observed in natural stocks.

 The general and novel concept proposed by Edeline and Loeuille is actually as old as Darwin’s book; The Origin of Species (Darwin 1859). It is based on the simple idea that natural selection acting on harvested populations can actually be strong, and counter-balance (or on the contrary reinforce) the evolutionary consequence of harvest selection. Although simple, the idea that natural and harvest selection are jointly shaping contemporary evolution of exploited populations lead to various and sometimes complex scenarios that can (i) explain unresolved empirical patterns and (ii) refine predictions regarding the long-term viability of exploited populations. 

The Edeline and Loeuille’s crafty inspiration is that natural selection acting on exploited populations is itself an indirect consequence of harvest (Edeline & Loeuille 2020). They suggest that, by modifying the size structure of populations (a key parameter for ecological interactions), harvest indirectly alters interactions between populations and their biotic environment through competition and predation, which changes the ecological theatre and hence the selective pressures acting back to populations. They named this process “size-dependent eco-evolutionary feedback loops” and develop several scenarios in which these feedback loops ultimately deviate the evolutionary outcome of harvest selection from expectation. The scenarios they explore are based on strong theoretical knowledge, and range from simple ones in which a single species (the harvest species) is evolving to more complex (and realistic) ones in which multiple (e.g. the harvest species and its prey) species are co-evolving.

I will not come into the details of each scenario here, and I will let the readers (re-)discovering the complex beauty of biological life and natural selection. Nonetheless, I will emphasize the importance of considering these eco-evolutionary processes altogether to fully grasp the response of exploited populations. Edeline and Loeuille convincingly demonstrate that reduced body size due to harvest selection is obviously not the only response of exploited fish populations when natural selection is jointly considered (Edeline & Loeuille 2020). On the contrary, they show that –under some realistic ecological circumstances relaxing exploitative competition due to reduced population densities- natural selection can act antagonistically, and hence favour stable body size in exploited populations. Although this seems further desirable from a human perspective than a downsizing of exploited populations, it is actually mere window dressing as Edeline and Loeuille further showed that this response is accompanied by an erosion of the evolvability –and hence a lowest probability of long-term persistence- of these exploited populations.

Humans, by exploiting biological resources, are breaking the relative equilibrium of complex entities, and the response of populations to this disturbance is itself often complex and heterogeneous. In this Essay, Edeline and Loeuille provide –under simple terms- the theoretical and conceptual bases required to improve predictions regarding the evolutionary responses of natural populations to exploitation by humans (Edeline & Loeuille 2020). An important next step will be to generate data and methods allowing confronting the empirical reality to these novel concepts (e.g. (Monk et al. 2021), so as to identify the most likely evolutionary scenarios sustaining biological responses of exploited populations, and hence to set the best management plans for the long-term sustainability of these populations.


Darwin, C. (1859). On the Origin of Species by Means of Natural Selection. John Murray, London.

Edeline, E. & Loeuille, N. (2021) Size-dependent eco-evolutionary feedbacks in fisheries. bioRxiv, 2020.04.03.022905, ver. 4 peer-reviewed and recommended by PCI Ecology. doi:

Frank, K.T., Petrie, B., Choi, J. S. & Leggett, W.C. (2005). Trophic Cascades in a Formerly Cod-Dominated Ecosystem. Science, 308, 1621–1623. doi:

Kuparinen, A. & Festa-Bianchet, M. (2017). Harvest-induced evolution: insights from aquatic and terrestrial systems. Philos. Trans. R. Soc. B Biol. Sci., 372, 20160036. doi:

Monk, C.T., Bekkevold, D., Klefoth, T., Pagel, T., Palmer, M. & Arlinghaus, R. (2021). The battle between harvest and natural selection creates small and shy fish. Proc. Natl. Acad. Sci., 118, e2009451118. doi: 

Palkovacs, E.P., Moritsch, M.M., Contolini, G.M. & Pelletier, F. (2018). Ecology of harvest-driven trait changes and implications for ecosystem management. Front. Ecol. Environ., 16, 20–28. doi:

Uusi-Heikkilä, S., Whiteley, A.R., Kuparinen, A., Matsumura, S., Venturelli, P.A., Wolter, C., et al. (2015). The evolutionary legacy of size-selective harvesting extends from genes to populations. Evol. Appl., 8, 597–620. doi:

Size-dependent eco-evolutionary feedbacks in fisheriesEric Edeline and Nicolas Loeuille<p>Harvesting may drive body downsizing along with population declines and decreased harvesting yields. These changes are commonly construed as direct consequences of harvest selection, where small-bodied, early-reproducing individuals are immedia...Biodiversity, Community ecology, Competition, Eco-evolutionary dynamics, Evolutionary ecology, Food webs, Interaction networks, Life history, Population ecology, Theoretical ecologySimon Blanchet2020-04-03 16:14:05 View