Inferring processes of cultural transmission: the critical role of rare variants in distinguishing neutrality from novelty biases

Neutral evolution assumes that there are no selective forces distinguishing different variants in a population. Despite this striking assumption, many recent studies have sought to assess whether neutrality can provide a good description of different episodes of cultural change. One approach has been to test whether neutral predictions are consistent with observed progeny distributions, recording the number of variants that have produced a given number of new instances within a specified time interval: a classic example is the distribution of baby names. Using an overlapping generations model we show that these distributions consist of two phases: a power law phase with a constant exponent of -3/2, followed by an exponential cut-off for variants with very large numbers of progeny. Maximum likelihood estimations of the model parameters provide a direct way to establish whether observed empirical patterns are consistent with neutral evolution. We apply our approach to a complete data set of baby names from Australia. Crucially we show that analyses based on only the most popular variants, as is often the case in studies of cultural evolution, can provide misleading evidence for underlying transmission hypotheses. While neutrality provides a plausible description of progeny distributions of abundant variants, rare variants deviate from neutrality. Further, we develop a simulation framework that allows for the detection of alternative cultural transmission processes. We show that anti-novelty bias is able to replicate the complete progeny distribution of the Australian data set

Translucent windows: How uncertainty in competitive interactions impacts detection of community pattern

Trait variation and similarity among coexisting species can provide a window into the mechanisms that maintain their coexistence. Recent theoretical explorations suggest that competitive interactions will lead to groups, or clusters, of species with similar traits. However, theoretical predictions typically assume complete knowledge of the map between competition and measured traits. These assumptions limit the plausible application of these patterns for inferring competitive interactions in nature. Here we relax these restrictions and find that the clustering pattern is robust to contributions of unknown or unobserved niche axes. However, it may not be visible unless measured traits are close proxies for niche strategies. We conclude that patterns along single niche axes may reveal properties of interspecific competition in nature, but detecting these patterns requires natural history expertise firmly tying traits to niches.Comment: Main text: 18 pages, 6 figures. Appendices: A-G, 6 supplementary figures. This is the peer reviewed version of the article of the same title which has been accepted for publication at Ecology Letters. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archivin

Non-Perturbative Tachyon Potential from the Wilsonian Renormalization Group

The derivative expansion of the Wilsonian renormalization group generates additional terms in the effective beta-functions not present in the perturbative approach. Applied to the nonlinear sigma model, to lowest order the vanishing of the beta-function for the tachyon field generates an equation analogous to that found in open string field theory. Although the nonlinear term depends on the cut-off function, this arbitrariness can be removed by a rescaling of the tachyon field.Comment: 6 pages, further references adde

Stability criteria for the consumption and exchange of essential resources

Models of consumer effects on a shared resource environment have helped clarify how the interplay of consumer traits and resource supply impact stable coexistence. Recent models generalize this picture to include the exchange of resources alongside resource competition. These models exemplify the fact that although consumers shape the resource environment, the outcome of consumer interactions is context-dependent: such models can have either stable or unstable equilibria, depending on the resource supply. However, these recent models focus on a simplified version of microbial metabolism where the depletion of resources always leads to consumer growth. Here, we model an arbitrarily large system of consumers governed by Liebig’s law, where species require and deplete multiple resources, but each consumer’s growth rate is only limited by a single one of these resources. Resources that are taken up but not incorporated into new biomass are leaked back into the environment, possibly transformed by intracellular reactions, thereby tying the mismatch between depletion and growth to cross-feeding. For this set of dynamics, we show that feasible equilibria can be either stable or unstable, again depending on the resource environment. We identify special consumption and production networks which protect the community from instability when resources are scarce. Using simulations, we demonstrate that the qualitative stability patterns derived analytically apply to a broader class of network structures and resource inflow profiles, including cases where multiple species coexist on only one externally supplied resource. Our stability criteria bear some resemblance to classic stability results for pairwise interactions, but also demonstrate how environmental context can shape coexistence patterns when resource limitation and exchange are modeled directly

PhylOTU: a high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data.

Microbial diversity is typically characterized by clustering ribosomal RNA (SSU-rRNA) sequences into operational taxonomic units (OTUs). Targeted sequencing of environmental SSU-rRNA markers via PCR may fail to detect OTUs due to biases in priming and amplification. Analysis of shotgun sequenced environmental DNA, known as metagenomics, avoids amplification bias but generates fragmentary, non-overlapping sequence reads that cannot be clustered by existing OTU-finding methods. To circumvent these limitations, we developed PhylOTU, a computational workflow that identifies OTUs from metagenomic SSU-rRNA sequence data through the use of phylogenetic principles and probabilistic sequence profiles. Using simulated metagenomic data, we quantified the accuracy with which PhylOTU clusters reads into OTUs. Comparisons of PCR and shotgun sequenced SSU-rRNA markers derived from the global open ocean revealed that while PCR libraries identify more OTUs per sequenced residue, metagenomic libraries recover a greater taxonomic diversity of OTUs. In addition, we discover novel species, genera and families in the metagenomic libraries, including OTUs from phyla missed by analysis of PCR sequences. Taken together, these results suggest that PhylOTU enables characterization of part of the biosphere currently hidden from PCR-based surveys of diversity

Backbones of evolutionary history test biodiversity theory for microbes

Identifying the ecological and evolutionary mechanisms that determine biological diversity is a central question in ecology. In microbial ecology, phylogenetic diversity is an increasingly common and relevant means of quantifying community diversity, particularly given the challenges in defining unambiguous species units from environmental sequence data. We explore patterns of phylogenetic diversity across multiple bacterial communities drawn from different habitats and compare these data to evolutionary trees generated using theoretical models of biodiversity. We have two central findings. First, although on finer scales the empirical trees are highly idiosyncratic, on coarse scales the backbone of these trees is simple and robust, consistent across habitats, and displays bursts of diversification dotted throughout. Second, we find that these data demonstrate a clear departure from the predictions of standard neutral theories of biodiversity and that an alternative family of generalized models provides a qualitatively better description. Together, these results lay the groundwork for a theoretical framework to connect ecological mechanisms to observed phylogenetic patterns in microbial communities.Freely available online through the PNAS open access option. This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by the National Academy of Sciences. The published article can be found at: http://www.pnas.org/Keywords: coalescent theory, macroecology, phylogeny, microbial biodiversit