Predicting coexistence of plants subject to a tolerance-competition trade-off

Ecological trade-offs between species are often invoked to explain species coexistence in ecological communities. However, few mathematical models have been proposed for which coexistence conditions can be characterized explicitly in terms of a trade-off. Here we present a model of a plant community which allows such a characterization. In the model plant species compete for sites where each site has a fixed stress condition. Species differ both in stress tolerance and competitive ability. Stress tolerance is quantified as the fraction of sites with stress conditions low enough to allow establishment. Competitive ability is quantified as the propensity to win the competition for empty sites. We derive the deterministic, discrete-time dynamical system for the species abundances. We prove the conditions under which plant species can coexist in a stable equilibrium. We show that the coexistence conditions can be characterized graphically, clearly illustrating the trade-off between stress tolerance and competitive ability. We compare our model with a recently proposed, continuous-time dynamical system for a tolerance-fecundity trade-off in plant communities, and we show that this model is a special case of the continuous-time version of our model.Comment: To be published in Journal of Mathematical Biology. 30 pages, 5 figures, 5 appendice

The neutral theory of biodiversity with random fission speciation

International audienceThe neutral theory of biodiversity and biogeography emphasizes the importance of dispersal and speciation to macro-ecological diversity patterns. While the influence of dispersal has been studied quite extensively, the effect of speciation has not received much attention, even though it was already claimed at an early stage of neutral theory development that the mode of speciation would leave a signature on metacommunity structure. Here, we derive analytical expressions for the distribution of abundances according to the neutral model with recruitment (i.e., dispersal and establishment) limitation and random fission speciation which seems to be a more realistic description of (allopatric) speciation than the point mutation mode of speciation mostly used in neutral models. We find that the two modes of speciation behave qualitatively differently except when recruitment is strongly limited. Fitting the model to six large tropical tree data sets, we show that it performs worse than the original neutral model with point mutation speciation but yields more realistic predictions for speciation rates, species longevities, and rare species. Interestingly, we find that the metacommunity abundance distribution under random fission is identical to the broken-stick abundance distribution and thus provides a dynamical explanation for this grand old lady of abundance distributions

A dispersal-limited sampling theory for species and alleles

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74624/1/j.1461-0248.2005.00817.x.pd

Detecting local diversity-dependence in diversification

Whether there are ecological limits to species diversification is a hotly debated topic. Molecular phylogenies show slowdowns in lineage accumulation, suggesting that speciation rates decline with increasing diversity. A maximum-likelihood (ML) method to detect diversity-dependent (DD) diversification from phylogenetic branching times exists, but it assumes that diversity-dependence is a global phenomenon and therefore ignores that the underlying species interactions are mostly local, and not all species in the phylogeny co-occur locally. Here, we explore whether this ML method based on the nonspatial diversity-dependence model can detect local diversity-dependence, by applying it to phylogenies, simulated with a spatial stochastic model of local DD speciation, extinction, and dispersal between two local communities. We find that type I errors (falsely detecting diversity-dependence) are low, and the power to detect diversity-dependence is high when dispersal rates are not too low. Interestingly, when dispersal is high the power to detect diversity-dependence is even higher than in the nonspatial model. Moreover, estimates of intrinsic speciation rate, extinction rate, and ecological limit strongly depend on dispersal rate. We conclude that the nonspatial DD approach can be used to detect diversity-dependence in clades of species that live in not too disconnected areas, but parameter estimates must be interpreted cautiously

Phylogenetic congruence between subtropical trees and their associated fungi.

Recent studies have detected phylogenetic signals in pathogen-host networks for both soil-borne and leaf-infecting fungi, suggesting that pathogenic fungi may track or coevolve with their preferred hosts. However, a phylogenetically concordant relationship between multiple hosts and multiple fungi in has rarely been investigated. Using next-generation high-throughput DNA sequencing techniques, we analyzed fungal taxa associated with diseased leaves, rotten seeds, and infected seedlings of subtropical trees. We compared the topologies of the phylogenetic trees of the soil and foliar fungi based on the internal transcribed spacer (ITS) region with the phylogeny of host tree species based on matK, rbcL, atpB, and 5.8S genes. We identified 37 foliar and 103 soil pathogenic fungi belonging to the Ascomycota and Basidiomycota phyla and detected significantly nonrandom host-fungus combinations, which clustered on both the fungus phylogeny and the host phylogeny. The explicit evidence of congruent phylogenies between tree hosts and their potential fungal pathogens suggests either diffuse coevolution among the plant-fungal interaction networks or that the distribution of fungal species tracked spatially associated hosts with phylogenetically conserved traits and habitat preferences. Phylogenetic conservatism in plant-fungal interactions within a local community promotes host and parasite specificity, which is integral to the important role of fungi in promoting species coexistence and maintaining biodiversity of forest communities

Inferring state-dependent diversification rates using approximate Bayesian computation (ABC)

State-dependent speciation and extinction (SSE) models provide a framework for quantifying whether species traits have an impact on evolutionary rates and how this shapes the variation in species richness among clades in a phylogeny. However, SSE models are becoming increasingly complex, limiting the application of likelihood-based inference methods. Approximate Bayesian computation (ABC), a likelihood-free approach, is a potentially powerful alternative for estimating parameters. One of the key challenges in using ABC is the selection of efficient summary statistics, which can greatly affect the accuracy and precision of the parameter estimates. In state-dependent diversification models, summary statistics need to capture the complex relationships between rates of diversification and species traits. Here, we develop an ABC framework to estimate state-dependent speciation, extinction and transition rates in the BiSSE (binary state dependent speciation and extinction) model. Using different sets of candidate summary statistics, we then compare the inference ability of ABC with that of using likelihood-based maximum likelihood (ML) and Markov chain Monte Carlo (MCMC) methods. Our results show the ABC algorithm can accurately estimate state-dependent diversification rates for most of the model parameter sets we explored. The inference error of the parameters associated with the species-poor state is larger with ABC than in the likelihood estimations only when the speciation rate is highly asymmetric between the two states (λ1 / λ0 = 5). Furthermore, we find that the combination of normalized lineage-through-time (nLTT) statistics and phylogenetic signal in binary traits (Fitz and Purvis’s D) constitute efficient summary statistics for the ABC method. By providing insights into the selection of suitable summary statistics, our work aims to contribute to the use of the ABC approach in the development of complex state-dependent diversification models, for which a likelihood is not available.Competing Interest StatementThe authors have declared no competing interest

Identifying summary statistics for approximate Bayesian computation in a phylogenetic island biogeography model

Estimation of parameters of evolutionary island biogeography models, such as colonization and diversification rates, is important for a better understanding of island systems. A popular statistical inference framework is likelihood-based estimation of parameters using island species richness and phylogenetic data. Likelihood approaches require that the likelihood can be computed analytically or numerically, but with the increasing complexity of island biogeography models, this is often unfeasible. Simulation-based estimation methods may then be a promising alternative. One such method is approximate Bayesian computation (ABC), which compares summary statistics of the empirical data with the output of model simulations. However, ABC demands the definition of summary statistics that sufficiently describe the data, which is yet to be explored in island biogeography. Here, we propose a set of summary statistics and use it in an ABC framework for the estimation of parameters of an island biogeography model, DAISIE (Dynamic Assembly of Island biota through Speciation, Immigration and Extinction). For this model, likelihood-based inference is possible, which gives us the opportunity to assess the performance of the summary statistics. DAISIE currently only allows maximum likelihood estimation (MLE), so we additionally develop a likelihood-based Bayesian inference framework using Markov Chain Monte Carlo (MCMC) to enable comparison with the ABC results (i.e., making the same assumptions on prior distributions). We simulated phylogenies of island communities subject to colonization, speciation, and extinction using the DAISIE simulation model and compared the estimated parameters using the three inference approaches (MLE, MCMC and ABC). Our results show that the ABC algorithm performs well in estimating colonization and diversification rates, except when the species richness or amount of phylogenetic information from an island are low. We find that compared to island species diversity statistics, summary statistics that make use of phylogenetic and temporal patterns (e.g., the number of species through time) significantly improve ABC inference accuracy, especially in estimating colonization and anagenesis rates, as well as making inference converge considerably faster and perform better under the same number of iterations. Island biogeography is rapidly developing new simulation models that can explain the complexity of island biodiversity, and our study provides a set of informative summary statistics that can be used in island biogeography studies for which likelihood-based inference methods are not an option.Competing Interest StatementThe authors have declared no competing interest

Nucleotide Substitutions during Speciation may Explain Substitution Rate Variation

Abstract Although molecular mechanisms associated with the generation of mutations are highly conserved across taxa, there is widespread variation in mutation rates between evolutionary lineages. When phylogenies are reconstructed based on nucleotide sequences, such variation is typically accounted for by the assumption of a relaxed molecular clock, which is a statistical distribution of mutation rates without much underlying biological mechanism. Here, we propose that variation in accumulated mutations may be partly explained by an elevated mutation rate during speciation. Using simulations, we show how shifting mutations from branches to speciation events impacts inference of branching times in phylogenetic reconstruction. Furthermore, the resulting nucleotide alignments are better described by a relaxed than by a strict molecular clock. Thus, elevated mutation rates during speciation potentially explain part of the variation in substitution rates that is observed across the tree of life. [Molecular clock; phylogenetic reconstruction; speciation; substitution rate variation.