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bioRxiv2017

Macroecology suggests cancer-causing papillomaviruses form non-neutral communities

Chronic infection by oncogenic Human papillomaviruses (HPVs) leads to cancers. Public health interventions, such as cancer screening and mass vaccination, radically change the ecological conditions encountered by circulating viruses. It is currently unclear how HPVs communities may respond to these environmental changes, because little is known about their ecology. Predicting the impact on viral diversity by the introduction of HPV vaccines requires answering the unresolved question of how HPVs interact. Although it is commonly believed that they do not interact (neutral theory), there are suggestions that HPV types may compete for resources or via the immune response (niche-based or non-neutral theory). Here, we applied for the first time established biodiversity measures and methods to epidemiological data in order to assess whether niche-partitioning or neutral processes are shaping HPV diversity patterns at the population level. We find that as infections progress toward cancer, HPVs communities become more uneven and a few HPVs play a stronger dominance role. By fitting species abundance distributions, we found that neutral models were always out-performed by non-neutral distributions, both in asymptomatic infections and in cancers. Our results suggest that temporally moving from a more even to a less even community implies an increase in competition, probably due to environmental changes linked to infection progression. More ecological thinking will be required to understand present-day interactions and to anticipate the future of the long lasting interactions between HPVs and humans.\n\nSIGNIFICANCE STATEMENTHuman papillomaviruses (HPVs) are very diverse. Infections by HPVs are very common and chronic infections may lead to cancers. The more oncogenic HPVs are now targetted by effective vaccines, and this has raised the question of whether there may be a viral replacement if these dominant types were removed. This is a medical version of a classical ecological controversy, namely how much biodiversity distributions and community dynamics are explained by neutral theory plays out across ecosystems. For HPVs, epidemiologic studies before and after the vaccination have led to the widespread belief that these viruses do not interact. Here, we apply different methods developed in macroecology to the best available epidemiologic data to address this issue. Consistently, we find that HPVs form non-neutral communities. Instead, competitive niche-partitioning process and dominance explain best HPVs communities. We also find that the vaccine might not change such competitive niche processes. Beyond clinical implications, this garners support that niche processes often best explain biodiversity patterns, even in human viral communities.

ecology↗
bioRxiv2017

Four fundamental processes of community assembly

A central aim of ecology is understanding the mechanisms of community assembly. To address this problem, community assembly is often modeled as a sampling process, in which species are selected from a pool of available species, possibly with effects of interspecific interactions, habitat filtering, and other ecological mechanisms. However, the fundamental stochastic sampling process by which species are selected from the pool remains unexplored. Here we demonstrate the distinctness of four canonical sampling processes, the Bernoulli, Plackett-Luce, multinomial, and fractional multinomial processes. Each process can be affected by ecological mechanisms or it can occur in their absence. Although all four of the processes are a priori plausible and the first two are widely used in ecological models, we show that the multinomial and fractional multinomial processes broadly underlie community assembly.

ecology↗
bioRxiv2017

Bottom-up and top-down control of dispersal across major organismal groups: a coordinated distributed experiment

Organisms rarely experience a homogeneous environment. Rather, ecological and evolutionary dynamics unfold in spatially structured and fragmented landscapes, with dispersal as the central process linking these dynamics across spatial scales. Because dispersal is a multi-causal and highly plastic life-history trait, finding general drivers that are of importance across species is challenging but highly relevant for ecological forecasting.\n\nWe here tested whether two fundamental ecological forces and main determinants of local population dynamics, top-down and bottom-up control, generally explain dispersal in spatially structured communities. In a coordinated distributed experiment spanning a wide range of actively dispersing organisms, from protozoa to vertebrates, we show that bottom-up control, that is resource limitation, consistently increased dispersal. While top-down control, that is predation risk, was an equally important dispersal driver as bottom-up control, its effect depended on prey and predator space use and whether dispersal occurred on land, in water or in the air: species that routinely use more space than their predators showed increased dispersal in response to predation, specifically in aquatic environments. After establishing these general causes of dispersal, we used a metacommunity model to show that bottom-up and top-down control of dispersal has important consequences for local population fluctuations as well as cascading effects on regional metacommunity dynamics. Context-dependent dispersal reduced local population fluctuations and desynchronized dynamics between communities, two effects that increase population and community stability.\n\nOur study provides unprecedented insights into the generality of the positive resource dependency of dispersal as well as a robust experimental test of current theory predicting that predator-induced dispersal is modulated by prey and predator space use. Our experimental and theoretical work highlights the critical importance of the multi-causal nature of dispersal as well as its cascading effects on regional community dynamics, which are specifically relevant to ecological forecasting.

ecology↗
bioRxiv2017

fluxweb: a package to easily estimate energy fluxes in food webs

O_LIUnderstanding how changes in biodiversity will impact the stability and functioning of ecosystems is a central challenge in ecology. Food-web approaches have been advocated to link community composition with ecosystem functioning by describing the fluxes of energy among species or trophic groups. However, estimating such fluxes remains problematic because current methods become unmanageable as network complexity increases.\nC_LIO_LIWe developed a generalisation of previous indirect estimation methods assuming a steady state system [1, 2, 3]: the model estimates energy fluxes in a top-down manner assuming system equilibrium; each nodes losses (consumption and physiological) balances its consumptive gains. Jointly, we provide theoretical and practical guidelines to use the fluxweb R package (available on CRAN at https://bit.ly/2OC0uKF).\nWe also present how the framework can merge with the allometric theory of ecology [4] to calculate fluxes based on easily obtainable organism-level data (i.e. body masses and species groups -eg, plants animals), opening its use to food webs of all complexities. Physiological losses (metabolic losses or losses due to death other than from predation within the food web) may be directly measured or estimated using allometric relationships based on the metabolic theory of ecology, and losses and gains due to predation are a function of ecological efficiencies that describe the proportion of energy that is used for biomass production.\nC_LIO_LIThe primary output is a matrix of fluxes among the nodes of the food web. These fluxes can be used to describe the role of a species, a function of interest (e.g. predation; total fluxes to predators), multiple functions, or total energy flux (system throughflow or multitrophic functioning). Additionally, the package includes functions to calculate network stability based on the Jacobian matrix, providing insight into how resilient the network is to small perturbations at steady state.\nC_LIO_LIOverall, fluxweb provides a flexible set of functions that greatly increase the feasibility of implementing food-web energetic approaches to more complex systems. As such, the package facilitates novel opportunities for mechanistically linking quantitative food webs and ecosystem functioning in real and dynamic natural landscapes.\nC_LI

ecology↗
bioRxiv2017

Going through the motions: incorporating movement analyses into disease research

Though epidemiology dates back to the 1700s, most mathematical representations of epidemics still use transmission rates averaged at the population scale, especially for wildlife diseases. In simplifying the contact process, we ignore the heterogeneities in host movements that complicate the real world, and overlook their impact on spatiotemporal patterns of disease burden. Movement ecology offers a set of tools that help unpack the transmission process, letting researchers more accurately model how animals within a population interact and spread pathogens. Analytical techniques from this growing field can also help expose the reverse process: how infection impacts movement behaviors, and therefore other ecological processes like feeding, reproduction, and dispersal. Here, we synthesize the contributions of movement ecology in disease research, with a particular focus on studies that have successfully used movement-based methods to quantify individual heterogeneity in exposure and transmission risk. Throughout, we highlight the rapid growth of both disease and movement ecology, and comment on promising but unexplored avenues for research at their overlap. Ultimately, we suggest, including movement empowers ecologists to pose new questions expanding our understanding of host-pathogen dynamics, and improving our predictive capacity for wildlife and even human diseases.

ecology↗
bioRxiv2018

Growth tradeoffs produce complex microbial communities without direct interactions

The relationship between the dynamics of a community and its constituent pairwise interactions is a fundamental problem in ecology. Higher-order ecological effects beyond pairwise interactions may be key to complex ecosystems, but mechanisms to produce these effects remain poorly understood. Here we show that higher-order effects can arise from variation in multiple microbial growth traits, such as lag times and growth rates, on a single limiting resource with no other interactions. These effects produce a range of ecological phenomena: an unlimited number of strains can exhibit multi stability and neutral coexistence, potentially with a single keystone strain; strains that coexist in pairs do not coexist all together; and the champion of all pairwise competitions may not dominate in a mixed community. Since variation in multiple growth traits is ubiquitous in microbial populations due to pleiotropy and non-genetic variation, our results indicate these higher-order effects may also be widespread, especially in laboratory ecology and evolution experiments.

ecology↗
bioRxiv2018

Predicting provenance of forensic soil samples: soil DNA predicts habitat and environmental properties

Environmental DNA is increasingly applied in ecological studies, including forensic ecology where eDNA from soil can be used to pair samples or reveal sample provenance. We collected soil eDNA samples as part of a large national biodiversity research project across 130 sites in Denmark. We investigated the potential for soil eDNA in predicting provenance in terms of environmental conditions, habitat characteristics and geographic regions. We used linear regression for predicting environmental gradients of light, moisture, soil pH and nutrients (represented by Ellenberg Indicator Values, EIVs) and quadratic discriminant analysis (QDA) to predict habitat class and geographic region. We found high predictive power for environmental gradients (R2 > 0.73). The discriminatory power of QDA in predicting habitat characteristics varied from high accuracy in predicting certain forest types, less accurate prediction of heathland and poor accuracy for geographic region. We demonstrate the application of provenance prediction in forensic science by evaluating and discussing two mock crime scenes. Here, we supplement with plant species lists from annotated sequences. Where predictions of environmental gradients and habitat classes give an overall accurate description of a crime scene, care should be taken when interpreting annotated sequences, e.g. due to erroneous assignments in GenBank. The outlined approach clearly demonstrates that basic ecological information that can be extracted from soil eDNA, contributing to the range of potential applications of eDNA in forensic ecology.

ecology↗
bioRxiv2018

When do shifts in trait dynamics precede population declines?

Predicting population responses to environmental change is an on-going challenge in ecology. Studies investigating the links between fitness-related phenotypic traits and demography have shown that trait dynamic responses to environmental change can sometimes precede population dynamic responses, and thus, can be used as an early warning signal. However, it is still unknown under which ecological and evolutionary circumstances, shifts in fitness-related traits can precede population responses to environmental perturbation. Here, we take a trait-based demographic approach and investigate both trait and population dynamics in a density-regulated population in response to a gradual change in the environment. We explore the ecological and evolutionary constraints under which shifts in a fitness-related trait precedes a decline in population size. We show both analytically and with experimental data that under medium-to-slow rate of environmental change, shifts in trait value can precede population decline. We further show the positive influence of environmental predictability, average reproductive rate, plasticity, and genetic variation on shifts in trait dynamics preceding potential population declines. These results still hold under non-constant genetic variation and environmental stochasticity. Our study highlights ecological and evolutionary circumstances under which a fitness-related trait can be used as an early warning signal of an impending population decline.

ecology↗
bioRxiv2018

Managing river fish biodiversity generates substantial economic benefits in four European countries

Ecosystems and biodiversity produce benefits to society, but many of them are hard to quantify. For example, it is unclear whether European societies gain benefits from experiencing rivers that host high native biodiversity. Without such knowledge, monetary investments into ecologically oriented river management plans are difficult to justify. The objective of this study was to reveal how the public in four European countries values ecological characteristics of domestic rivers and the outcomes of hypothetical river basin management plans designed to improve river ecosystems, particularly fish biodiversity. We conducted a choice experiment among the populations in Norway, Sweden, Germany and France. We found similar preference structures in all countries with high marginal willingness-to-pay for improvements of abiotic river attributes (increased accessiblity of the river banks, improved bathing water quality, decreased river fragmentation). Citizens also benefited from certain fish species occurring in a river with native salmonid species being more valued than nonnatives, particularly in Norway, and from the degree of a rivers native biodiversity. Welfare measures calculated for selected river basin management plans (policy scenarios) revealed societal benefits that were primarily derived from ecological river management whereas a scenario focusing on hydroelectricity production generated the lowest utility. We conclude that ecological river management may produce high nonmarket economic benefits in all study countries, particularly through the management of abiotic river attributes and the restoration of declining or extinct fish species. Our results help to inform decisions on restoration efforts by showcasing the benefits that these measures have for the public.

ecology↗
bioRxiv2015

Machine Learning Biogeographic Processes from Biotic Patterns: A New Trait-Dependent Dispersal and Diversification Model with Model-Choice By Simulation-Trained Discriminant Analysis

Current statistical biogeographical analysis methods are limited in the ways ecology can be related to the processes of diversification and geographical range evolution, requiring conflation of geography and ecology, and/or assuming ecologies that are uniform across all lineages and invariant in time. This precludes the possibility of studying a broad class of macro-evolutionary biogeographical theories that relate geographical and species histories through iineage-specific ecological and evolutionary dynamics, such as taxon cycle theory. Here we present a new model that generates phylogenies under a complex of superpositioned geographical range evolution, trait evolution, and diversification processes that can communicate with each other. This means that, under our model, the diversification and transition of the states of a lineage through geographical space is separate from, yet is conditional on, the state of the lineage in trait space (or vice versa). We present a likelihood-free method of inference under our model using discriminant analysis of principal components of summary statistics calculated on phylogenies, with the discriminant functions trained on data generated by simulations under our model. This approach of model classification is shown to be efficient, robust, and performant over a broad range of parameter space defined by the relative rates of dispersal, trait evolution, and diversification processes. We apply our method to a case study of the taxon cycle, i.e. testing for habitat and trophic-level constraints in the dispersal regimes of the Wallacean avifaunal radiation.

Evolutionary Biology↗
bioRxiv2015

Whole-genome sequencing uncovers cryptic and hybrid species among Atlantic and Pacific cod-fish

Speciation often involves the splitting of a lineage and the adaptation of daughter lineages to different environments. It may also involve the merging of divergent lineages, thus creating a stable homoploid hybrid species1 that constructs a new ecological niche by transgressing2 the ecology of the parental types. Hybrid speciation may also contribute to enigmatic and cryptic biodiversity in the sea.3,4 The enigmatic walleye pollock, which is not a pollock at all but an Atlantic cod that invaded the Pacific 3.8 Mya,5 differs considerably from its presumed closest relatives, the Pacific and Atlantic cod. Among the Atlantic cod, shallow-water coastal and deep-water migratory frontal ecotypes are associated with highly divergent genomic islands;6,7 however, intermediates remain an enigma.8 Here, we performed whole-genome sequencing of over 200 individuals using up to 33 million SNPs based on genotype likelihoods9 and showed that the evolutionary status of walleye pollock is a hybrid species: it is a hybrid between Arctic cod and Atlantic cod that transgresses the ecology of its parents. For the first time, we provide decisive evidence that the Atlantic cod coastal and frontal ecotypes are separate species that hybridized, leading to a true-breeding hybrid species that differs ecologically from its parents. We refute monophyly and dichotomous branching of these taxa, and stress the importance of looking beyond branching trees at admixture and hybridity. Our study demonstrates the power of whole-genome sequencing and population genomics in providing deep insights into fundamental processes of speciation. Our study was a starting point for further work aimed at examining the criteria of hybrid speciation,10 selection, sterility and structural chromosomal variation11 among cod-fish, which are among the most important fish stocks in the world. The hybrid nature of both the walleye pollock and Atlantic cod raises the question concerning the extent to which very profitable fisheries12,13 depend on hybrid vigour. Our results have implications for management of marine resources in times of rapid climate change.14,15

Preprint↗
bioRxiv2016

Genome-culture coevolution promotes rapid divergence in the killer whale

The interaction between ecology, culture and genome evolution remains poorly understood. Analysing population genomic data from killer whale ecotypes, which we estimate have globally radiated within less than 250,000 years, we show that genetic structuring including the segregation of potentially functional alleles is associated with socially inherited ecological niche. Reconstruction of ancestral demographic history revealed bottlenecks during founder events, likely promoting ecological divergence and genetic drift resulting in a wide range of genome-wide differentiation between pairs of allopatric and sympatric ecotypes. Functional enrichment analyses provided evidence for regional genomic divergence associated with habitat, dietary preferences and postzygotic reproductive isolation. Our findings are consistent with expansion of small founder groups into novel niches by an initial plastic behavioural response, perpetuated by social learning imposing an altered natural selection regime. The study constitutes an important step toward an understanding of the complex interaction between demographic history, culture, ecological adaptation and evolution at the genomic level.

Genomics↗
bioRxiv2016

Evolutionary stability of microbial communities with antibiotic degrading species

A major puzzle in ecology is how antibiotic resistant, sensitive and producer species coexist in close proximity. Recently, we showed that antibiotic degrading species dramatically alter community dynamics: replacing intrinsic resistance with resistance through degradation generates stable communities resilient to spatial mixing, large species abundance perturbations, changes in interaction strengths, and differences in species growth rates. In addition to ecological stability, it is interesting to consider evolutionary stability of these communities to the appearance of cheater species that either cease production or degradation of antibiotics. Our investigation of evolutionary stability of cyclical 3-species communities revealed that these communities are robust to cheaters that stop degrading antibiotics. Our simulations also showed that cheaters that stop producing antibiotics do not take over the community, yet they can transiently invade and cause community collapse. In the analytical approximation we initially investigated, production cheaters with a small fitness advantage can invade the community simply because the benefit of inhibiting competitors is shared among all cells. Here, we consider evolutionary stability to cheaters in our complete model, where spatial mixing is introduced only after a short range colonization step. In this regime, an antibiotic producer cell directly benefits from killing nearby competitor species as it has a greater chance of colonizing the newly voided spaces created by the action of its antibiotic. Simulating response to cheater invasions for the cyclical three species community and for random 4-species ecologically stable topologies, we find that these communities can be fully resilient to both degradation and production cheaters. The strength of selection against cheaters varies with the area of the zone of inhibition around producers and is maximized for weak inhibition, where there is less overlap between the killing zones of neighboring cells. These results may aid the construction of complex synthetic communities that are both ecological and evolutionary stable.

Evolutionary Biology↗
bioRxiv2016

MMinte: An application for predicting metabolic interactions among the microbial species in a community

Background.The explosive growth of microbiome research has yielded great quantities of data. These data provide us with many answers, but raise just as many questions. 16S rDNA--the backbone of microbiome analyses--allows us to assess -diversity, {beta}-diversity, and microbe-microbe associations, which characterize the overall properties of an ecosystem. However, we are still unable to use 16S rDNA data to directly assess the microbe-microbe and microbe-environment interactions that determine that system's broader ecology. Thus, properties such as competition, cooperation, and nutrient conditions remain insufficiently analyzed. Here, we apply predictive community metabolic models of microbes identified with 16S rDNA data to probe the ecology of microbial communities.\n\nResults.We developed a methodology for the large-scale assessment of microbial metabolic interactions (MMinte)from 16S rDNA data. MMinte assesses the relative growth rates of interacting pairs of organisms within a community metabolic network and whether that interaction has a positive or negative effect. Moreover, MMinte's simulations take into account the nutritional environment, which play a strong role in determining the metabolism of individual microbes. We present two case studies that demonstrate this software's utility. In the first, we show how diet influences the nature of the microbe-microbe interactions. In the second, we use MMinte's modular feature set to better understand how the growth of Desulfovibrio piger is affected by, and affects the growth of, other members in a simplified gut community under metabolic conditions suggested to be determinant for their dynamics.\n\nConclusion.By applying metabolic models to commonly available sequence data, MMinte grants the user insight into the metabolic relationships between microbes, highlighting important features that may relate to ecological stability, susceptibility, and cross-feeding. These relationships are at the foundation of a wide range of ecological questions that impact our ability to understand problems such as microbially-derived toxicity in colon cancer.

Bioinformatics↗
bioRxiv2016

A functional analysis of the contribution of climatic niche divergence to adaptive radiation

Elucidating how ecological and evolutionary mechanisms interact to produce and maintain biodiversity is a fundamental problem in evolutionary ecology. We investigate this issue by focusing on how physiological evolution affects performance and species coexistence along the thermal niche axis in replicated radiations of Anolis lizards, groups best known for resource partitioning based on morphological divergence. We find repeated divergence in thermal physiology within these radiations, and that this divergence significantly affects performance within natural thermal environments. Morphologically similar species that co-occur invariably differ in their thermal physiology, providing evidence that physiological divergence facilitates species co-existence within anole communities. Despite repeated divergence in traits of demonstrable ecological importance, phylogenetic comparative analyses indicate that physiological traits have evolved more slowly than key morphological traits related to the structural niche. Phylogenetic analyses also reveal that physiological divergence is correlated with divergence in broad-scale habitat climatic features commonly used to estimate thermal niche evolution, but that the latter incompletely predicts variation in the former. We provide comprehensive evidence for repeated adaptive evolution of physiological divergence within Anolis adaptive radiations, including the complementary roles of physiological and morphological divergence in promoting community-level diversity. We recommend greater integration of performance-based traits into analyses of climatic niche evolution, as they facilitate a more complete understanding of the phenotypic and ecological consequences of climatic divergence.

Evolutionary Biology↗
bioRxiv2017

Worldwide Population Structure Of Escherichia coli Reveals Two Major Subspecies

Recombination is one of the most important mechanisms of prokaryotic species evolution but its exact roles are still in debate. Here we try to infer genome-wide recombination events within a species uti-lizing a dataset of 104 complete genomes of Escherichia coli from diverse origins, among which 45 from world-wide animal-hosts are in-house sequenced using SMRT (single-molecular real time) technology.Two major clades are identified based on evidences of ecological and physiological characteristics, as well as distinct genomic features implying scarce inter-clade genetic exchange. By comparing the synteny of identical fragments genome-widely searched for each genome pair, we achieve a fine-scale map of re-combination within the population. The recombination is rather extensive within clade, which is able to break linkages between genes but does not interrupt core genome framework and primary metabolic port-folios possibly due to natural selection for physiological compatibility and ecological fitness. Meanwhile,the recombination between clades declines drastically as the phylogenetic distance increases, generally 10-fold reduced than those of the intra-clade, which establishes genetic barrier between clades. These empirical data of recombination suggest its critical role in the early stage of speciation, where recombina-tion rate differs according to phylogentic distance. The extensive intra-clade recombination coheres sister strains into a quasi-sexual group and optimizes genes or alleles to streamline physiological activities,whereas shapely declined inter-clade recombination split the population into clades adaptive to divergent ecological niches.\n\nSignificance StatementRoles of recombination in species evolution have been debated for decades due to difficulties in inferring recombination events during the early stage of speciation, especially when recombination is always complicated by frequent gene transfer events of bacterial genomes. Based on 104 high-quality complete E. coli genomes, we infer gene-centric dynamics of recombination in the formation of two E. coli clades or subpopulations, and recombination is found to be rather intensive in a within-clade fashion, which forces them to be quasi-sexual. The recombination events can be mapped among individual genomes in the context of genes and their variations; decreased between-clade and increased intra-claderecombination engender a genetic barrier that further encourages clade-specific secondary metabolic portfolios for better environmental adaptation. Recombination is thus a major force that accelerates bacterial evolution to fit ecological diversity.

microbiology↗
bioRxiv2017

Niche Partitioning In Sympatric Populations Of Aquatic Stenotrophomonas Uncovered By Evolutionary Species Delimitation

The genus Stenotrophomonas (Gammaproteobacteria) has a broad environmental distribution. S. maltophilia is its best known species because it is a globally emerging, multidrug-resistant (MDR), opportunistic pathogen. Members of this species are known to display high genetic, ecological and phenotypic diversity, forming the so-called S. maltophilia complex (Smc). Heterogeneous resistance and virulence phenotypes have been reported for environmental Smc isolates of diverse ecological origin. We hypothesized that this heterogeneity could be in part due to the potential lumping of several cryptic species in the Smc. Here we used state-of-the-art phylogenetic and population genetics methods to test this hypothesis based on the multilocus dataset available for the genus at pubmlst.org. It was extended with sequences from complete and draft genome sequences to assemble a comprehensive set of reference sequences. This framework was used to analyze 108 environmental isolates obtained in this study from the sediment and water column of four rivers and streams in Central Mexico, affected by contrasting levels of anthropogenic pollution. The aim of the study was to identify species in this collection, defined as genetically cohesive sequence clusters, and to determine the extent of their genetic, ecological and phenotypic differentiation. The multispecies coalescent, coupled with Bayes factor analysis was used to delimit species borders, together with population genetic structure analyses, recombination and gene flow estimates between sequence clusters.\n\nThese analyses consistently revealed that the Smc contains at least 5 significantly differentiated lineages: S. maltophilia and Smc1 to Smc4. Only S. maltophilia was found to be intrinsically MDR, all its members expressing metallo-{beta}-lactamases (MBLs). The other Smc lineages were not MDR and did not express MBLs. We also obtained isolates related to S. acidaminiphila, S. humi and S. terrae. They were significantly more susceptible to antibiotics than S. maltophilia. We demonstrate that the sympatric lineages recovered display significantly differentiated habitat preferences, antibiotic resistance profiles and beta-lactamase expression phenotypes, as shown by diverse multivariate analyses and robust univariate statistical tests. We discuss our data in light of current models of bacterial speciation, which fit these data well, stressing the implications of species delimitation in ecological, evolutionary and clinical research.

microbiology↗
bioRxiv2017

Scientific Theories and Artificial Intelligence

The grand ambition of theorists studying ecology and evolution is to discover the logical and mathematical rules driving the worlds biodiversity at every level from genetic diversity within species to differences between populations, communities, and ecosystems. This ambition has been difficult to realize in great part because of the complexity of biodiversity. Theoretical work has led to a complex web of theories, each having non-obvious consequences for other theories. Case in point, the recent realization that genetic diversity involves a great deal of temporal and spatial stochasticity forces theoretical population genetics to consider abiotic and biotic factors generally reserved to ecosystem ecology. This interconnectedness may require theoretical scientists to adopt new techniques adapted to reason about large sets of theories. Mathematicians have solved this problem by using formal languages based on logic to manage theorems. However, theories in ecology and evolution are not mathematical theorems, they involve uncertainty. Recent work in Artificial Intelligence in bridging logic and probability theory offers the opportunity to build rich knowledge bases that combine logics ability to represent complex mathematical ideas with probability theorys ability to model uncertainty. We describe these hybrid languages and explore how they could be used to build a unified knowledge base of theories for ecology and evolution.\n\ncase study you explore using the Salix tritrophic system.

scientific communication and education↗