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. By leveraging the vocabulary of Avida, researchers can gain deeper insights into the evolutionary processes and dynamics of digital organisms. In addition, OntoAvida allows researchers to make inference based on certain rules and constraints, facilitate the reproducibility of in silico evolution experiments and trace the provenance of the data stored in avidaDB-an RDF database containing the genomes, transcriptomes, and phenotypes of more than a million digital organisms. OntoAvida is part of the Open Biological and Biomedical Ontologies (OBO Foundry) and is available at http://www.obofoundry.org/ontology/ontoavida.html .

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. I show here that plasticity pervades not only natural but also artificial systems that mimic the developmental process of biological organisms, such as self-replicating and evolving computer programs-digital organisms. Specifically, the environment can modify the sequence of instructions executed from a digital organism's genome (i.e. its transcriptome), which results in changes in its phenotype (i.e. the ability of the digital organism to perform Boolean logic operations). This genetic-based pathway for plasticity comes at a fitness cost to an organism's viability and generation time: the longer the transcriptome (higher fitness cost), the more chances for the environment to modify the genetic execution flow control, and the higher the likelihood for the genome to encode novel phenotypes. By studying to what extent a digital organism's phenotype is influenced by both its genome and the environment, I make a parallelism between natural and artificial evolving systems on how natural selection might slide trait regulation anywhere along a continuum from total environmental control to total genomic control, which harbours lessons not only for designing evolvable artificial systems, but also for synthetic biology.

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. We compared plant-fungi interactions between mutualistic and antagonist networks, and searched for a diamond-like module defined by a mycoheterotrophic and an autotrophic plant interacting with the same pair of fungi to investigate whether pairs of fungi simultaneously linked to plant species from each interaction type were overrepresented throughout the network. Mycoheterotrophic plants as a group interacted with a subset of the fungi detected in autotrophs but are indirectly linked to all autotrophic plants, and fungi with a high overlap in autotrophic partners tended to interact with a similar set of mycoheterotrophs. Moreover, pairs of fungi sharing the same mycoheterotrophic and autotrophic plant species are overrepresented in the network. We hypothesise that the maintenance of antagonistic interactions is maximised by targeting well linked mutualistic fungi, thereby minimising the risk of carbon supply shortages.

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. Here we quantify the probability for two partners to interact wherever they co-occur (i.e., partner fidelity) by analyzing the most extensive database on species interaction networks worldwide. We found that mutualistic species show more fidelity in their interactions than antagonistic ones when there is asymmetric specialization (i.e., when specialist species interact with generalist partners). Moreover, resources (e.g., plants in plant-pollinator mutualisms or hosts in host-parasite interactions) show a higher partner fidelity in mutualistic interactions than in antagonistic interactions, which can be explained neither by sampling effort nor by phylogenetic constraints developed during their evolutionary histories. In spite of the general belief that mutualistic interactions among free-living species are labile, asymmetric specialization is very much conserved across large geographic areas.

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. Our results across 57 Neotropical communities show that cultural heritage is as important as plants for preserving indigenous knowledge both locally and regionally. Indeed, knowledge networks collapse as fast when plant species are driven extinct as when cultural diffusion, either within or among communities, is lost. But it is the joint loss of plant species and knowledge that erodes these networks at a much higher rate. Our findings pave the road toward integrative policies that recognize more explicitly the inseparable links between cultural and biological heritage.

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. Yet, we still lack experimental evidence of the role of coevolution in driving changes in the structure of such species interaction networks. Filling this gap is important because network structure influences community persistence through indirect effects. Here, we quantified experimentally to what extent coevolutionary dynamics lead to contrasting patterns in the architecture of bacteria-phage infection networks. Specifically, we look at the tendency of these networks to be organized in a nested pattern by which the more specialist phages tend to infect only a proper subset of those bacteria infected by the most generalist phages. We found that interactions between coevolving bacteria and phages become less nested over time under fluctuating dynamics, and more nested under arms race dynamics. Moreover, when coevolution results in high average infectivity, phages and bacteria differ more from each other over time under arms race dynamics than under fluctuating dynamics. The tradeoff between the fitness benefits of evolving resistance/infectivity traits and the costs of maintaining them might explain these differences in network structure. Our study shows that the interaction pattern between bacteria and phages at the community level depends on the way coevolution unfolds.

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. Thus, to what degree plant interactions affect biodiversity and ecological networks across trophic levels is poorly understood. We manipulated plant communities driven by foundation species facilitation and sampled plant-pollinator networks at fine spatial scale in a field experiment in Sierra Nevada, Spain. We found that plant-plant facilitation shaped pollinator diversity and structured pollination networks. Nonadditive effects of plant interactions on pollinator diversity and interaction diversity were synergistic in one foundation species networks while they were additive in another foundation species. Nonadditive effects of plant interactions were due to rewiring of pollination interactions. In addition, plant facilitation had negative effects on the structure of pollination networks likely due to increase in plant competition for pollination. Our results empirically demonstrate how different network types are coupled, revealing pervasive consequences of interaction chains in diverse communities.

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. We propose integrating ecological and evolutionary processes in hierarchical networks to explore interdependencies in biological systems. We connect gene networks underlying predator-prey trait distributions to food webs. Our approach addresses longstanding questions about how complex traits and intraspecific trait variation affect the interdependencies among biological levels and the stability of meta-ecosystems.

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.e. self-replicating computer programs that mutate, evolve and coevolve within a user-defined computational environment. Here, we quantify the role of the non-adaptive origins of host resistance traits in determining the evolution of ecological interactions among host and parasite digital organisms. We find that host resistance traits arising spontaneously as exaptations increase the complexity of antagonistic host-parasite networks. Specifically, they lead to higher host phenotypic diversification, a larger number of ecological interactions and higher heterogeneity in interaction strengths. Given the potential of network architecture to affect network dynamics, such exaptations may increase the persistence of entire communities. Our in silico approach, therefore, may complement current theoretical advances aimed at disentangling the ecological and evolutionary mechanisms shaping species interaction networks.This article is part of the themed issue 'Process and pattern in innovations from cells to societies'.

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. To test this hypothesis, we sampled 33 populations of P. veris consisting of forest and grassland patches and used clustering techniques and network analyses to identify sets of populations that are more connected to each other than to other sets of populations and estimated the timing of divergence. Our results showed that spatial genetic variation had a significantly modular structure and consisted of four well-defined modules that almost perfectly coincided with habitat features. Genetic divergence was estimated to have occurred about 114 generations ago, coinciding with historic major changes in the landscape. Overall, these results illustrate how populations adapting to different environments become structured genetically within landscapes on small spatial scales.

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. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

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 Bialowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact. This likelihood is estimated extending recent developments on the study of structural stability in ecological communities. We find that the observed species turnover strongly varies the likelihood of community persistence between summer and winter. Importantly, we demonstrate that the observed seasonal interaction changes minimize the variation in the likelihood of persistence associated with species turnover across the year. We find that these community dynamics can be explained as the coupling of individual species to their environment by minimizing both the variation in persistence conditions and the interaction changes between seasons. Our results provide a homeostatic explanation for seasonal species interactions and suggest that monitoring the association of interactions changes with the level of variation in community dynamics can provide a good indicator of the response of species to environmental pressures.

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. We build the spatial networks of seed dispersal events between trees and seed-plots within the studied population-local network-and the spatial network that includes all dispersal events-regional network. Such networks are structured in well-defined modules, i.e. groups of tightly connected mother trees and seed-plots. Neither geographical distance, nor microhabitat type explained this modular structure, but when long-distance dispersal events are incorporated in the network it shows a relative increase in overall modularity. Independent field observations suggested the co-occurrence of two complementary groups, short- and long-distance dispersers, mostly contributing to the local and regional seed rain, respectively. The main long-distance disperser at our site, Turdus viscivorus, preferentially visits the most productive trees, thus shaping the seed rain at the landscape scale and affecting the local modular organization. We end by discussing how DNA barcoding could serve to better quantify the role of functional diversity.

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). We then used a resampling procedure to simulate the additive effects of genetic variation on overall food-web complexity. We found that trait variation among host-plant genotypes was associated with resistance to insect herbivores, which indirectly affected interactions between herbivores and their insect parasitoids. Direct and indirect genetic effects resulted in distinct compositions of trophic interactions associated with each host-plant genotype. Moreover, our simulations suggest that food-web complexity would increase by 20% over the range of genetic variation in the experimental population of host plants. Taken together, our results indicate that intraspecific genetic variation can play a key role in structuring ecological networks, which may in turn affect network persistence.

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. By combining network analysis with immunogenetics, we show that host species infected by similar parasites harbour similar alleles with similar frequencies. We further show, using a Bayesian approach, that the probability of mutual occurrence of a functional allele and a parasite in a given host individual is nonrandom and depends on other host-parasite interactions, driving co-evolution within subgroups of parasite species and functional alleles. Therefore, indirect effects among hosts and parasites can shape host MHC diversity, scaling it from the population to the community level.

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. Nest predators were identified by video-recording nests and surveyed from 2004 to 2011. As landscapes urbanized, bird-plant networks were more nested, less compartmentalized and dominated by strong interactions between a few species (i.e. low evenness). Evenness of interaction strengths promoted avian nest survival, and evenness explained demography better than urbanization, level of invasion, numbers of predators or other qualitative network metrics. Highly uneven networks had approximately half the nesting success as the most even networks. Thus, nest survival reflected how urbanization altered species interactions, particularly with respect to how nest placement affected search efficiency of predators. The demographic effects of urbanization were not direct, but were filtered through bird-plant networks. This study illustrates how network structure can influence demography at the community level and further, that knowledge of species interactions and a network approach may be requisite to understanding demographic responses to environmental change.

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. 2. We used data on a network of small mammals and their ectoparasites surveyed over 6 years to test hypotheses exploring (i) the temporal variability in direct and indirect influences species exert on each other in a community, and (ii) the differences in temporal variability of direct/indirect influences between temporally persistent (TP) and temporally intermittent species. 3. We modelled the temporal variation in (i) direct reciprocal influence between hosts and parasites (hosts providing resources to parasites and parasites exploiting the resources of hosts), using an asymmetry index, and (ii) indirect influence among species within a community (e.g. facilitation of parasite infestation by other parasites), using betweenness centrality. We also correlated asymmetry and centrality to examine the relationship between them. 4. Network dynamics was determined by TP species but even those species had strong among-species heterogeneity in the temporal variation of the direct/indirect effects they exerted. In addition, there was a significant positive linear correlation between asymmetry and centrality. 5. We conclude that the temporal dynamics of host-parasite interactions is driven by TP hosts. However, even within this group of persistent species, some exhibit large temporal variation, such that the functional roles they play (e.g. in promoting parasite transmission) change over time. In addition, parasites having a large negative impact on hosts are also those facilitating the spread of other parasites through the entire host community. Our results provide new insights into community dynamics and can be applied in the management of antagonistic networks aimed at preventing disease outbreaks.

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., digital organisms) that experience the same major ecological interactions as biological organisms (e.g., competition, predation, parasitism, and mutualism). Despite being computational, these programs evolve quickly in an open-ended way, and starting from only one or two ancestral organisms, the formation of ecological networks can be observed in real-time by tracking interactions between the constantly evolving organism phenotypes. These phenotypes may be defined by combinations of logical computations (hereafter tasks) that digital organisms perform and by expressed behaviors that have evolved. The types and outcomes of interactions between phenotypes are determined by task overlap for logic-defined phenotypes and by responses to encounters in the case of behavioral phenotypes. Biologists use these evolving networks to study active and fundamental topics within evolutionary ecology (e.g., the extent to which the architecture of multispecies networks shape coevolutionary outcomes, and the processes involved).

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. To what degree this is the case has been difficult to evaluate, partly because of the lack of both spatially extended genetic data and an appropriate framework to map and analyse such data. Here, we extend recent work on the analysis of networks of spatial genetic variation to address the robustness of these networks in the face of perturbations. We illustrate the potential of this framework using the case study of an amphibian metapopulation. Our results show that while the disappearance of some spatial sites barely changes the modular structure of the genetic network, other sites have a much stronger effect. Interestingly, these consequences can not be anticipated using topological, static measures. Mapping these networks of spatial genetic variation will allow identifying significant evolutionary units and how they vanish, merge and reorganise following perturbations.

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. In the 24 networks that were modular, closely related hosts co-occurred in the same module more often than expected by chance; in contrast, this was rarely the case for parasites. The within- and among-module connectivity of the same host or parasite species varied geographically. However, among-module but not within-module connectivity of host and parasites was somewhat phylogenetically constrained. These findings suggest that the establishment of host-parasite networks results from the interplay between phylogenetic influences acting mostly on hosts and local factors acting on parasites, to create an asymmetrically constrained pattern of geographic variation in modular structure. Modularity in host-parasite networks seems to result from the shared evolutionary history of hosts and by trait convergence among unrelated parasites. This suggests profound differences between hosts and parasites in the establishment and functioning of bipartite antagonistic networks.