Neutral metacommunity models predict fish diversity patterns in Mississippi–Missouri basin

Muneepeerakul, Rachata; Bertuzzo, Enrico; Lynch, Heather J.; Fagan, William F.; Rinaldo, Andrea; Rodrı́guez-Iturbe, Ignacio

doi:10.1038/nature06813

Cited by 339 publications

(472 citation statements)

References 27 publications

(33 reference statements)

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“…As we were primarily interested in the relationship between the evolutionary dynamics of dispersal and diversity patterns, we focused on a simple spatial structure in which connectivity is similar between all patches, irrespective of their carrying capacity, a situation for which we could derive evolutionary predictions. Our model might be extended to more complex community networks in which the neutral expectations have already been derived and that better describe the spatial structure of some real metacommunities, such as dendritic networks for rivers [46,47]. The limiting step here would be to derive eco-evolutionary predictions about dispersal polymorphism in complex networks with variable connectivity among patches, a point that has been little explored up to now [48].…”

Section: (B) Neutral Predictions On Species Diversity Patternsmentioning

confidence: 99%

The evolution of the competition–dispersal trade-off affects α- and β-diversity in a heterogeneous metacommunity

et al. 2016

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Difference in dispersal ability is a key driver of species coexistence in metacommunities. However, the available frameworks for interpreting species diversity patterns in natura often overlook trade-offs and evolutionary constraints associated with dispersal. Here, we build a metacommunity model accounting for dispersal evolution and a competition-dispersal trade-off. Depending on the distribution of carrying capacities among communities, species dispersal values are distributed either around a single strategy (evolutionarily stable strategy, ESS), or around distinct strategies (evolutionary branching, EB). We show that limited dispersal generates spatial aggregation of dispersal traits in ESS and EB scenarios, and that the competition-dispersal trade-off strengthens the pattern in the EB scenario. Importantly, individuals in larger (respectively (resp.) smaller) communities tend to harbour lower (resp. higher) dispersal, especially under the EB scenario. We explore how dispersal evolution affects species diversity patterns by comparing those from our model to the predictions of a neutral metacommunity model. The most marked difference is detected under EB, with distinctive values of both aand b-diversity (e.g. the dissimilarity in species composition between small and large communities was significantly larger than neutral predictions). We conclude that, from an empirical perspective, jointly assessing community carrying capacity with species dispersal strategies should improve our understanding of diversity patterns in metacommunities.

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Section: (B) Neutral Predictions On Species Diversity Patternsmentioning

confidence: 99%

The evolution of the competition–dispersal trade-off affects α- and β-diversity in a heterogeneous metacommunity

et al. 2016

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“…Time series can, even if short, contain enough information for making inference if they describe the response to a major disturbance [29] or include several state variables [25]. Patterns were taken from experiments [29,36], targeted field studies [24], databases [28] and literature reviews [31]. The column 'patterns used' in table 1 indicates that the core of POM is creativity in identifying and combining patterns.…”

Section: A Mini-reviewmentioning

confidence: 99%

Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

Grimm

Railsback

2012

Phil. Trans. R. Soc. B

357

334

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Modern ecology recognizes that modelling systems across scales and at multiple levels-especially to link population and ecosystem dynamics to individual adaptive behaviour-is essential for making the science predictive. 'Pattern-oriented modelling' (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.

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“…The basic theoretical scheme of the spatially explicit model relates to recent advances in hydrochory, migration fronts and infection spreading (Campos et al 2006;Bertuzzo et al 2007;Muneepeerakul et al 2008). Nodal reactions describe the dynamics of cholera, described via a compartmental susceptibleinfective -recovered (SIR)-like model .…”

Section: Theoretical Approachmentioning

confidence: 99%

On spatially explicit models of cholera epidemics

Bertuzzo

Casagrandi

Gatto

et al. 2009

J. R. Soc. Interface.

164

162

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We generalize a recently proposed model for cholera epidemics that accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having different topologies. The vehicle of infection (Vibrio cholerae) is transported through the network links that are thought of as hydrological connections among susceptible communities. The mathematical tools used are borrowed from general schemes of reactive transport on river networks acting as the environmental matrix for the circulation and mixing of waterborne pathogens. Using the diffusion approximation, we analytically derive the speed of propagation for travelling fronts of epidemics on regular lattices (either one-dimensional or two-dimensional) endowed with uniform population density. Power laws are found that relate the propagation speed to the diffusion coefficient and the basic reproduction number. We numerically obtain the related, slower speed of epidemic spreading for more complex, yet realistic river structures such as Peano networks and optimal channel networks. The analysis of the limit case of uniformly distributed population sizes proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, the ratio between spreading and disease outbreak time scales proves the crucial parameter. The relevance of our results lies in the major differences potentially arising between the predictions of spatially explicit models and traditional compartmental models of the susceptible -infected -recovered (SIR)-like type. Our results suggest that in many cases of real-life epidemiological interest, time scales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models.

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Neutral metacommunity models predict fish diversity patterns in Mississippi–Missouri basin

Cited by 339 publications

References 27 publications

The evolution of the competition–dispersal trade-off affects α- and β-diversity in a heterogeneous metacommunity

The evolution of the competition–dispersal trade-off affects α- and β-diversity in a heterogeneous metacommunity

Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

On spatially explicit models of cholera epidemics

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