avidaR: an R library to perform complex queries on an ontology-based database of digital organisms.

Digital evolution is a branch of artificial life in which self-replicating computer programs-digital organisms-mutate and evolve within a user-defined computational environment. In spite of its value in biology, we still lack an up-to-date and comprehensive database on digital organisms resulting from evolution experiments. Therefore, we have developed an ontology-based semantic database-avidaDB-and an R package-avidaR-that provides users of the R programming language with an easy-to-use tool for performing complex queries without specific knowledge of SPARQL or RDF.

Ontology for the Avida digital evolution platform.

The Ontology for Avida (OntoAvida) aims to develop an integrated vocabulary for the description of Avida, the most widely used computational approach for performing experimental evolution using digital organisms-self-replicating computer programs that evolve within a user-defined computational environment. The lack of a clearly defined vocabulary makes some biologists feel reluctant to embrace the field of digital evolution. This integrated framework empowers biologists by equipping them with the necessary tools to explore and analyze the field of digital evolution more effectively.

The phenotypic plasticity of an evolving digital organism.

Climate change will fundamentally reshape life on Earth in the coming decades. Therefore, understanding the extent to which species will cope with rising temperatures is of paramount importance. Phenotypic plasticity is the ability of an organism to change the morphological and functional traits encoded by its genome in response to the environment.

Mycoheterotrophic plants preferentially target arbuscular mycorrhizal fungi that are highly connected to autotrophic plants.

How mycoheterotrophic plants that obtain carbon and soil nutrients from fungi are integrated in the usually mutualistic arbuscular mycorrhizal networks is unknown. Here, we compare autotrophic and mycoheterotrophic plant associations with arbuscular mycorrhizal fungi and use network analysis to investigate interaction preferences in the tripartite network. We sequenced root tips from autotrophic and mycoheterotrophic plants to assemble the combined tripartite network between autotrophic plants, mycorrhizal fungi and mycoheterotrophic plants.

Partner Fidelity and Asymmetric Specialization in Ecological Networks.

AbstractSpecies are embedded in complex networks of interdependencies that may change across geographic locations. Yet most approaches to investigate the architecture of this entangled web of life have considered exclusively local communities. To quantify to what extent species interactions change at a biogeographic scale, we need to shed light on how among-community variation affects the occurrence of species interactions.

Indigenous knowledge networks in the face of global change.

Indigenous communities rely extensively on plants for food, shelter, and medicine. It is still unknown, however, to what degree their survival is jeopardized by the loss of either plant species or knowledge about their services. To fill this gap, here we introduce indigenous knowledge networks describing the wisdom of indigenous people on plant species and the services they provide.

Coevolutionary dynamics shape the structure of bacteria-phage infection networks.

Coevolution-reciprocal evolutionary change among interacting species driven by natural selection-is thought to be an important force in shaping biodiversity. This ongoing process takes place within tangled networks of species interactions. In microbial communities, evolutionary change between hosts and parasites occurs at the same time scale as ecological change.

Plant interactions shape pollination networks via nonadditive effects.

Plants grow in communities where they interact with other plants and with other living organisms such as pollinators. On the one hand, studies of plant-plant interactions rarely consider how plants interact with other trophic levels such as pollinators. On the other, studies of plant-animal interactions rarely deal with interactions within trophic levels such as plant-plant competition and facilitation.

Deciphering the Interdependence between Ecological and Evolutionary Networks.

Biological systems consist of elements that interact within and across hierarchical levels. For example, interactions among genes determine traits of individuals, competitive and cooperative interactions among individuals influence population dynamics, and interactions among species affect the dynamics of communities and ecosystem processes. Such systems can be represented as hierarchical networks, but can have complex dynamics when interdependencies among levels of the hierarchy occur.

Non-adaptive origins of evolutionary innovations increase network complexity in interacting digital organisms.

The origin of evolutionary innovations is a central problem in evolutionary biology. To what extent such innovations have adaptive or non-adaptive origins is hard to assess in real organisms. This limitation, however, can be overcome using digital organisms, i.

Analysis of spatial genetic variation reveals genetic divergence among populations of Primula veris associated to contrasting habitats.

Genetic divergence by environment is a process whereby selection causes the formation of gene flow barriers between populations adapting to contrasting environments and is often considered to be the onset of speciation. Nevertheless, the extent to which genetic differentiation by environment on small spatial scales can be detected by means of neutral markers is still subject to debate. Previous research on the perennial herb Primula veris has shown that plants from grassland and forest habitats showed pronounced differences in phenology and flower morphology, suggesting limited gene flow between habitats.

The genotype-phenotype map of an evolving digital organism.

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution.

Seasonal species interactions minimize the impact of species turnover on the likelihood of community persistence.

Many of the observed species interactions embedded in ecological communities are not permanent, but are characterized by temporal changes that are observed along with abiotic and biotic variations. While work has been done describing and quantifying these changes, little is known about their consequences for species coexistence. Here, we investigate the extent to which changes of species composition impact the likelihood of persistence of the predator-prey community in the highly seasonal Białowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact.

How does the functional diversity of frugivorous birds shape the spatial pattern of seed dispersal? A case study in a relict plant species.

Genetic markers used in combination with network analysis can characterize the fine spatial pattern of seed dispersal and assess the differential contribution of dispersers. As a case study, we focus on the seed dispersal service provided by a small guild of frugivorous birds to the common yew, Taxus baccata L., in southern Spain.

Genetic specificity of a plant-insect food web: Implications for linking genetic variation to network complexity.

Theory predicts that intraspecific genetic variation can increase the complexity of an ecological network. To date, however, we are lacking empirical knowledge of the extent to which genetic variation determines the assembly of ecological networks, as well as how the gain or loss of genetic variation will affect network structure. To address this knowledge gap, we used a common garden experiment to quantify the extent to which heritable trait variation in a host plant determines the assembly of its associated insect food web (network of trophic interactions).

Host-parasite network structure is associated with community-level immunogenetic diversity.

Genes of the major histocompatibility complex (MHC) encode proteins that recognize foreign antigens and are thus crucial for immune response. In a population of a single host species, parasite-mediated selection drives MHC allelic diversity. However, in a community-wide context, species interactions may modulate selection regimes because the prevalence of a given parasite in a given host may depend on its prevalence in other hosts.

Community-level demographic consequences of urbanization: an ecological network approach.

Ecological networks are known to influence ecosystem attributes, but we poorly understand how interspecific network structure affect population demography of multiple species, particularly for vertebrates. Establishing the link between network structure and demography is at the crux of being able to use networks to understand population dynamics and to inform conservation. We addressed the critical but unanswered question, does network structure explain demographic consequences of urbanization? We studied 141 ecological networks representing interactions between plants and nesting birds in forests across an urbanization gradient in Ohio, USA, from 2001 to 2011.

Temporal dynamics of direct reciprocal and indirect effects in a host-parasite network.

1. Temporal variation in the direct and indirect influence that hosts and parasites exert on each other is still poorly understood. However, variation in species' influence due to species and interactions turnover can have important consequences for host community dynamics and/or for parasite transmission dynamics, and eventually for the risk of zoonotic diseases.

Evolving digital ecological networks.

"It is hard to realize that the living world as we know it is just one among many possibilities" [1]. Evolving digital ecological networks are webs of interacting, self-replicating, and evolving computer programs (i.e.

Assessing the robustness of networks of spatial genetic variation.

Habitat transformation is one of the leading drivers of biodiversity loss. The ecological effects of this transformation have mainly been addressed at the demographic level, for example, finding extinction thresholds. However, interpopulation genetic variability and the subsequent potential for adaptation can be eroded before effects are noticed on species abundances.

Phylogenetic signal in module composition and species connectivity in compartmentalized host-parasite networks.

Abstract Across different taxa, networks of mutualistic or antagonistic interactions show consistent architecture. Most networks are modular, with modules being distinct species subsets connected mainly with each other and having few connections to other modules. We investigate the phylogenetic relatedness of species within modules and whether a phylogenetic signal is detectable in the within- and among-module connectivity of species using 27 mammal-flea networks from the Palaearctic.

Evolution of a modular software network.

"Evolution behaves like a tinkerer" (François Jacob, Science, 1977). Software systems provide a singular opportunity to understand biological processes using concepts from network theory. The Debian GNU/Linux operating system allows us to explore the evolution of a complex network in a unique way.

Nestedness versus modularity in ecological networks: two sides of the same coin?

1. Understanding the structure of ecological networks is a crucial task for interpreting community and ecosystem responses to global change. 2.

Networks of spatial genetic variation across species.

Spatial patterns of genetic variation provide information central to many ecological, evolutionary, and conservation questions. This spatial variability has traditionally been analyzed through summary statistics between pairs of populations, therefore missing the simultaneous influence of all populations. More recently, a network approach has been advocated to overcome these limitations.

Compartments in a marine food web associated with phylogeny, body mass, and habitat structure.

A long-standing question in community ecology is whether food webs are organized in compartments, where species within the same compartment interact frequently among themselves, but show fewer interactions with species from other compartments. Finding evidence for this community organization is important since compartmentalization may strongly affect food web robustness to perturbation. However, few studies have found unequivocal evidence of compartments, and none has quantified the suite of mechanisms generating such a structure.