A sampling theory for asymmetric communities

Effects of nutrient supply, herbivory, and host community on fungal endophyte diversity

The microbes contained within free-living organisms can alter host growth, reproduction, and interactions with the environment. In turn, processes occurring at larger scales determine the local biotic and abiotic environment of each host that may affect the diversity and composition of the microbiome community. Here, we examine variation in the diversity and composition of the foliar fungal microbiome in the grass host, Andropogon gerardii, across four mesic prairies in the central United States. Composition of fungal endophyte communities differed among sites and among individuals within a site, but was not consistently affected by experimental manipulation of nutrient supply to hosts (A. gerardii) or herbivore reduction via fencing. In contrast, mean fungal diversity was similar among sites but was limited by total plant biomass at the plot scale. Our work demonstrates that distributed experiments motivated by ecological theory are a powerful tool to unravel the multiscale processes governing microbial community composition and diversity.

Altitudinal limits of Eastern Himalayan birds are created by competition past and present

The degree to which interspecific competition structures diverse communities is an oft-debated topic. An approach to answering this question is to examine spatial patterns of coexistence among putatively competing species. The degree to which interspecies competition predominates in a community can have important effects on our ability predict the response of that community to perturbations, most notably climate change, when shifting species’ ranges may result in novel species assemblages. We present a study on the avifauna of the Eastern Himalayas. We hypothesize that in a community where competitive interactions predominate, there will be a relationship between pairwise altitudinal overlaps and morphological differences between species. Moreover, we hypothesize that both morphological traits and altitudinal traits depart from a Brownian motion evolution model, resulting in species trait covariances having a phylogenetic component. We find a significant relationship between morphological dissimilarity and altitudinal overlaps of species pairs. We also find that closely related species are significantly more altitudinally stratified than a null model would predict. However, as more distantly related species pairs are included in the analysis, this pattern disappears, indicating that competitive interactions predominate only in closely related species. This is further suggested by the fact that altitudinal ranges themselves are phylogenetically overdispersed at the genus level, as are morphological traits. This effect disappears when the entire phylogeny is examined, with morphology and altitude being phylogenetically underdispersed. Model fitting suggests that individual clades have evolved towards local clade-specific fitness peaks, while within-clade results show evidence of niche partitioning. We interpret these results as a tension between competition on shorter time scales and selection on longer time scales, where competition forces closely-related species away from fitness peaks in order to allow for niche separation and hence coexistence, suggesting that this effect is partially responsible for the recent diversification of Eastern Himalayan avifauna.

Theoretical conditions for the coexistence of viral strains with differences in phenotypic traits: a bifurcation analysis

We investigate the dynamics of a wild-type viral strain which generates mutant strains differing in phenotypic properties for infectivity, virulence and mutation rates. We study, by means of a mathematical model and bifurcation analysis, conditions under which the wild-type and mutant viruses, which compete for the same host cells, can coexist. The coexistence conditions are formulated in terms of the basic reproductive numbers of the strains, a maximum value of the mutation rate and the virulence of the pathogens. The analysis reveals that parameter space can be divided into five regions, each with distinct dynamics, that are organized around degenerate Bogdanov-Takens and zero-Hopf bifurcations, the latter of which gives rise to a curve of transcritical bifurcations of periodic orbits. These results provide new insights into the conditions by which viral populations may contain multiple coexisting strains in a stable manner.

A Multiscale Approach to Plant Disease Using the Metacommunity Concept

Plant disease arises from the interaction of processes occurring at multiple spatial and temporal scales. With new tools such as next-generation sequencing, we are learning about the diversity of microbes circulating within and among plant populations and often coinhabiting host individuals. The proliferation of pathogenic microbes depends on single-species dynamics and multispecies interactions occurring within and among host cells, the spatial organization and genetic landscape of hosts, the frequency and mode of transmission among hosts and host populations, and the abiotic environmental context. Here, we examine empirical evidence from these multiple scales to assess the utility of metacommunity theory, a theoretical framework developed for free-living organisms to further our understanding of and assist in predicting plant-pathogen infection and spread. We suggest that deeper understanding of disease dynamics can arise through the application of this conceptual framework at scales ranging from individual cells to landscapes. In addition, we use this multiscale theoretical perspective to synthesize existing knowledge, generate novel hypotheses, and point toward promising future opportunities for the study of plant pathogens in natural populations.

The community ecology of pathogens: coinfection, coexistence and community composition

Disease and community ecology share conceptual and theoretical lineages, and there has been a resurgence of interest in strengthening links between these fields. Building on recent syntheses focused on the effects of host community composition on single pathogen systems, we examine pathogen (microparasite) communities using a stochastic metacommunity model as a starting point to bridge community and disease ecology perspectives. Such models incorporate the effects of core community processes, such as ecological drift, selection and dispersal, but have not been extended to incorporate host-pathogen interactions, such as immunosuppression or synergistic mortality, that are central to disease ecology. We use a two-pathogen susceptible-infected (SI) model to fill these gaps in the metacommunity approach; however, SI models can be intractable for examining species-diverse, spatially structured systems. By placing disease into a framework developed for community ecology, our synthesis highlights areas ripe for progress, including a theoretical framework that incorporates host dynamics, spatial structuring and evolutionary processes, as well as the data needed to test the predictions of such a model. Our synthesis points the way for this framework and demonstrates that a deeper understanding of pathogen community dynamics will emerge from approaches working at the interface of disease and community ecology.

When can species abundance data reveal non-neutrality?

Species abundance distributions (SAD) are probably ecology's most well-known empirical pattern, and over the last decades many models have been proposed to explain their shape. There is no consensus over which model is correct, because the degree to which different processes can be discerned from SAD patterns has not yet been rigorously quantified. We present a power calculation to quantify our ability to detect deviations from neutrality using species abundance data. We study non-neutral stochastic community models, and show that the presence of non-neutral processes is detectable if sample size is large enough and/or the amplitude of the effect is strong enough. Our framework can be used for any candidate community model that can be simulated on a computer, and determines both the sampling effort required to distinguish between alternative processes, and a range for the strength of non-neutral processes in communities whose patterns are statistically consistent with neutral theory. We find that even data sets of the scale of the 50 Ha forest plot on Barro Colorado Island, Panama, are unlikely to be large enough to detect deviations from neutrality caused by competitive interactions alone, though the presence of multiple non-neutral processes with contrasting effects on abundance distributions may be detectable.

How do habitat filtering and niche conservatism affect community composition at different taxonomic resolutions?

Understanding how local species assembly depends on the regional biogeographic and environmental context is a challenging task in community ecology. In spatially implicit neutral models, a single immigration parameter, I(k), represents the flux of immigrants from a regional pool that compete with local offspring for establishment in communities. This flux counterbalances the effect of local stochastic extinctions to maintain local species diversity. If some species within the regional pool are not adapted to the local environment (habitat filtering), the migrant flux is reduced beyond that of the neutral model, such that habitat filtering influences the value of I(k) in non-neutral situations. Here, we propose a novel model in which immigrants from the regional pool are filtered according to their habitat preferences and the local environment, while taxa potentially retain habitat preferences from their ancestors (niche conservatism). Using both analytical reasoning and simulations, we demonstrate that I(k) is expected to be constant when estimated based on the community composition at several taxonomic levels, not only under neutral assumptions, but also when habitat filtering occurs, unless there is substantial niche conservatism. In the latter case, I(k) is expected to decrease when estimated based on the composition at species to genus and family levels, thus allowing a signature of niche conservatism to be detected by simply comparing I(k) estimates across taxonomic levels. We applied this approach to three rain forest data sets from South India and Central America and found no significant signature of niche conservatism when I(k) was compared across taxonomic levels, except at the family level in South India. We further observed more limited immigration in South Indian forests, supporting the hypothesis of a greater impact of habitat filtering and heterogeneity there than in Central America. Our results highlight the relevance of studying variations of I(k) in space and across taxonomic levels to test hypotheses about the ecological and evolutionary drivers of biodiversity patterns.

Multivariate Moran process with Lotka-Volterra phenomenology

For a population with any given number of types, we construct a new multivariate Moran process with frequency-dependent selection and establish, analytically, a correspondence to equilibrium Lotka-Volterra phenomenology. This correspondence, on the one hand, allows us to infer the phenomenology of our Moran process based on much simpler Lokta-Volterra phenomenology and, on the other, allows us to study Lotka-Volterra dynamics within the finite populations of a Moran process. Applications to community ecology, population genetics, and evolutionary game theory are discussed.