Chemolithoautotroph distributions across the subsurface of a convergent margin.

Subducting oceanic crusts release fluids rich in biologically relevant compounds into the overriding plate, fueling subsurface chemolithoautotrophic ecosystems. To understand the impact of subsurface geochemistry on microbial communities, we collected fluid and sediments from 14 natural springs across a ~200 km transect across the Costa Rican convergent margin and performed shotgun metagenomics. The resulting 404 metagenome-assembled genomes (MAGs) cluster into geologically distinct regions based on MAG abundance patterns: outer forearc-only (25% of total relative abundance), forearc/arc-only (38% of total relative abundance), and delocalized (37% of total relative abundance) clusters. In the outer forearc, Thermodesulfovibrionia, Candidatus Bipolaricaulia, and Firmicutes have hydrogenotrophic sulfate reduction and Wood-Ljungdahl (WL) carbon fixation pathways. In the forearc/arc, Anaerolineae, Ca. Bipolaricaulia, and Thermodesulfovibrionia have sulfur oxidation, nitrogen cycling, microaerophilic respiration, and WL, while Aquificae have aerobic sulfur oxidation and reverse tricarboxylic acid carbon fixation pathway. Transformation-based canonical correspondence analysis shows that MAG distribution corresponds to concentrations of aluminum, iron, nickel, dissolved inorganic carbon, and phosphate. While delocalized MAGs appear surface-derived, the subsurface chemolithoautotrophic, metabolic, and taxonomic landscape varies by the availability of minerals/metals and volcanically derived inorganic carbon. However, the WL pathway persists across all samples, suggesting that this versatile, energy-efficient carbon fixation pathway helps shape convergent margin subsurface ecosystems.

A continental-scale survey of Wolbachia infections in blue butterflies reveals evidence of interspecific transfer and invasion dynamics.

Infections by maternally inherited bacterial endosymbionts, especially Wolbachia, are common in insects and other invertebrates but infection dynamics across species ranges are largely under studied. Specifically, we lack a broad understanding of the origin of Wolbachia infections in novel hosts, and the historical and geographical dynamics of infections that are critical for identifying the factors governing their spread. We used Genotype-by-Sequencing data from previous population genomics studies for range-wide surveys of Wolbachia presence and genetic diversity in North American butterflies of the genus Lycaeides. As few as one sequence read identified by assembly to a Wolbachia reference genome provided high accuracy in detecting infections in host butterflies as determined by confirmatory PCR tests, and maximum accuracy was achieved with a threshold of only 5 sequence reads per host individual. Using this threshold, we detected Wolbachia in all but 2 of the 107 sampling localities spanning the continent, with infection frequencies within populations ranging from 0% to 100% of individuals, but with most localities having high infection frequencies (mean = 91% infection rate). Three major lineages of Wolbachia were identified as separate strains that appear to represent 3 separate invasions of Lycaeides butterflies by Wolbachia. Overall, we found extensive evidence for acquisition of Wolbachia through interspecific transfer between host lineages. Strain wLycC was confined to a single butterfly taxon, hybrid lineages derived from it, and closely adjacent populations in other taxa. While the other 2 strains were detected throughout the rest of the continent, strain wLycB almost always co-occurred with wLycA. Our demographic modeling suggests wLycB is a recent invasion. Within strain wLycA, the 2 most frequent haplotypes are confined almost exclusively to separate butterfly taxa with haplotype A1 observed largely in Lycaeides melissa and haplotype A2 observed most often in Lycaeides idas localities, consistent with either cladogenic mode of infection acquisition from a common ancestor or by hybridization and accompanying mutation. More than 1 major Wolbachia strain was observed in 15 localities. These results demonstrate the utility of using resequencing data from hosts to quantify Wolbachia genetic variation and infection frequency and provide evidence of multiple colonizations of novel hosts through hybridization between butterfly lineages and complex dynamics between Wolbachia strains.

Additive genetic effects in interacting species jointly determine the outcome of caterpillar herbivory.

Plant-insect interactions are common and important in basic and applied biology. Trait and genetic variation can affect the outcome and evolution of these interactions, but the relative contributions of plant and insect genetic variation and how these interact remain unclear and are rarely subject to assessment in the same experimental context. Here, we address this knowledge gap using a recent host-range expansion onto alfalfa by the Melissa blue butterfly. Common garden rearing experiments and genomic data show that caterpillar performance depends on plant and insect genetic variation, with insect genetics contributing to performance earlier in development and plant genetics later. Our models of performance based on caterpillar genetics retained predictive power when applied to a second common garden. Much of the plant genetic effect could be explained by heritable variation in plant phytochemicals, especially saponins, peptides, and phosphatidyl cholines, providing a possible mechanistic understanding of variation in the species interaction. We find evidence of polygenic, mostly additive effects within and between species, with consistent effects of plant genotype on growth and development across multiple butterfly species. Our results inform theories of plant-insect coevolution and the evolution of diet breadth in herbivorous insects and other host-specific parasites.

Insects and recent climate change.

Insects have diversified through more than 450 million y of Earth's changeable climate, yet rapidly shifting patterns of temperature and precipitation now pose novel challenges as they combine with decades of other anthropogenic stressors including the conversion and degradation of land. Here, we consider how insects are responding to recent climate change while summarizing the literature on long-term monitoring of insect populations in the context of climatic fluctuations. Results to date suggest that climate change impacts on insects have the potential to be considerable, even when compared with changes in land use. The importance of climate is illustrated with a case study from the butterflies of Northern California, where we find that population declines have been severe in high-elevation areas removed from the most immediate effects of habitat loss. These results shed light on the complexity of montane-adapted insects responding to changing abiotic conditions. We also consider methodological issues that would improve syntheses of results across long-term insect datasets and highlight directions for future empirical work.

Nest substrate, more than ant activity, drives fungal pathogen community dissimilarity in seed-dispersing ant nests.

Myrmecochory is a widespread mutualism in which plants benefit from seed dispersal services by ants. Ants might also be providing seeds with an additional byproduct benefit via reduced plant pathogen loads in the ant nest environment through their antimicrobial glandular secretions. We investigate this byproduct benefit by identifying fungal communities in ant nests and surrounding environments and quantifying fungal community change (1) through time, (2) between different nest substrates, and (3) as a function of average ant activity levels within nests (based on observed ant activity at nest entrances throughout the summer). We split fungal communities by functional guild to determine seed-dispersing ant-induced changes in the overall fungal community, the animal pathogen fungal community, the plant pathogen fungal community, and the myrmecochore pathogen fungal community. Nest substrate (soil or log) explained much of the variation in fungal community dissimilarity, while substrate occupation (ant nest or control sample) and time had no influence on fungal community composition. Average ant activity had no effect on the community turnover in fungal communities except for the myrmecochore pathogenic fungal community. In this community, higher ant activity throughout the summer resulted in more fluctuation in the pathogenic community in the ant nest. Our results are not consistent with a byproduct benefit framework in myrmecochory, but suggest that nest substrate drives dissimilarity in fungal communities. The influence of nest substrate on fungal communities has important implications for seeds taken into ant nests, as well as ant nest location choice by queens and during nest relocation.

Bacterial communities of the Salvia lyrata rhizosphere explained by spatial structure and sampling grain.

Advancements in molecular technology have reduced the constraints that the grain of observation, or the spatial resolution and volume of the sampling unit, has on the characterization of plant-associated microbiomes. With discrete ecological sampling and massive parallel sequencing, we can more precisely portray microbiome community assembly and microbial recruitment to host tissue over space and time. Here, we differentiate rarefied community richness and relative abundance in bacterial microbiomes of Salvia lyrata dependent on three spatial depths, which are discrete physical distances from the soil surface within the rhizosphere microhabitat as a proxy for the root system zones. To assess the impact of sampling grain on rarefied community richness and relative abundance, we evaluated the variation of these metrics between samples pooled prior to DNA extraction and samples pooled after sequencing. A distance-based redundancy analysis with the quantitative Jaccard distance revealed that rhizosphere microbiomes vary in richness between rhizosphere soil depths. At all orders of diversity, rarefied microbial richness was consistently lowest at the deepest samples taken (approximately 4 cm from soil surface) in comparison with other rhizosphere soil depths. We additionally show that finer grain sampling (i.e., three samples of equal volume pooled after sequencing) recovers greater microbial richness when using 16S rRNA gene sequencing to describe microbial communities found within the rhizosphere system. In summary, to further elucidate the extent host-specific microbiomes assemble within the rhizosphere, the grain at which bacterial communities are sampled should reflect and encompass fine-scale heterogeneity of the system.

Microbial Communities across Global Marine Basins Show Important Compositional Similarities by Depth.

The environmental surveys following the 2010 Deepwater Horizon (DWH) spill identified a variety of hydrocarbon-degrading microorganisms, and laboratory studies with field-collected water samples then demonstrated faster-than-expected hydrocarbon biodegradation rates at 5°C. Knowledge about microbial community composition, diversity, and functional metabolic capabilities aids in understanding and predicting petroleum biodegradation by microbial communities in situ and is therefore an important component of the petroleum spill response decision-making process. This study investigates the taxonomic composition of microbial communities in six different global basins where petroleum and gas activities occur. Shallow-water communities were strikingly similar across basins, while deep-water communities tended to show subclusters by basin, with communities from the epipelagic, mesopelagic, and bathypelagic zones sometimes appearing within the same cluster. Microbial taxa that were enriched in the water column in the Gulf of Mexico following the DWH spill were found across marine basins. Several hydrocarbon-degrading genera (e.g., Actinobacteria, Pseudomonas, and Rhodobacteriacea) were common across all basins. Other genera such as Pseudoalteromonas and Oleibacter were highly enriched in specific basins.IMPORTANCE Marine microbial communities are a vital component of global carbon cycling, and numerous studies have shown that populations of petroleum-degrading bacteria are ubiquitous in the oceans. Few studies have attempted to distinguish all of the taxa that might contribute to petroleum biodegradation (including, e.g., heterotrophic and nondesignated microbes that respond positively to petroleum and microbes that grow on petroleum as the sole carbon source). This study quantifies the subpopulations of microorganisms that are expected to be involved in petroleum hydrocarbon biodegradation, which is important information during the decision-making process in the event of a petroleum spill accident.

Microbiome Variation Across Two Hemlock Species With Hemlock Woolly Adelgid Infestation.

The hemlock woolly adelgid (Adelges tsugae, HWA), an invasive insect, is devastating native hemlock populations in eastern North America, and management outcomes have so far had limited success. While many plant microbiomes influence and even support plant immune responses to insect herbivory, relatively little is known about the hemlock microbiome and its interactions with pathogens or herbivores such as HWA. Using 16S rRNA and ITS gene amplicon sequencing, we characterized the needle, branch, root, and rhizosphere microbiome of two hemlock species, Tsuga canadensis and T. sieboldii, that displayed low and high levels of HWA populations. We found that both archaeal/bacterial and fungal needle communities, as well as the archaeal/bacterial branch and root communities, varied in composition in both hemlock species relative to HWA population levels. While host species and plant-associated habitats explained a greater proportion of the variance in the microbiome than did HWA population level, high HWA populations were associated with enrichment of 100 likely fungal pathogen sequence variants across the four plant-associated habitats (e.g., needle, branch, root, rhizosphere) compared to trees with lower HWA populations. This work contributes to a growing body of literature linking plant pathogens and pests with the changes in the associated plant microbiome and host health. Furthermore, this work demonstrates the need to further investigate plant microbiome effects across multiple plant tissues to understand their influences on host health.

Caterpillars on a phytochemical landscape: The case of alfalfa and the Melissa blue butterfly.

Modern metabolomic approaches that generate more comprehensive phytochemical profiles than were previously available are providing new opportunities for understanding plant-animal interactions. Specifically, we can characterize the phytochemical landscape by asking how a larger number of individual compounds affect herbivores and how compounds covary among plants. Here we use the recent colonization of alfalfa (Medicago sativa) by the Melissa blue butterfly (Lycaeides melissa) to investigate the effects of indivdiual compounds and suites of covarying phytochemicals on caterpillar performance. We find that survival, development time, and adult weight are all associated with variation in nutrition and toxicity, including biomolecules associated with plant cell function as well as putative anti-herbivore action. The plant-insect interface is complex, with clusters of covarying compounds in many cases encompassing divergent effects on different aspects of caterpillar performance. Individual compounds with the strongest associations are largely specialized metabolites, including alkaloids, phenolic glycosides, and saponins. The saponins are represented in our data by more than 25 individual compounds with beneficial and detrimental effects on L. melissa caterpillars, which highlights the value of metabolomic data as opposed to approaches that rely on total concentrations within broad defensive classes.

Recent hybrids recapitulate ancient hybrid outcomes.

Genomic outcomes of hybridization depend on selection and recombination in hybrids. Whether these processes have similar effects on hybrid genome composition in contemporary hybrid zones versus ancient hybrid lineages is unknown. Here we show that patterns of introgression in a contemporary hybrid zone in Lycaeides butterflies predict patterns of ancestry in geographically adjacent, older hybrid populations. We find a particularly striking lack of ancestry from one of the hybridizing taxa, Lycaeides melissa, on the Z chromosome in both the old and contemporary hybrids. The same pattern of reduced L. melissa ancestry on the Z chromosome is seen in two other ancient hybrid lineages. More generally, we find that patterns of ancestry in old or ancient hybrids are remarkably predictable from contemporary hybrids, which suggests selection and recombination affect hybrid genomes in a similar way across disparate time scales and during distinct stages of speciation and species breakdown.

Codependency between plant and arbuscular mycorrhizal fungal communities: what is the evidence?

That arbuscular mycorrhizal (AM) fungi covary with plant communities is clear, and many papers report nonrandom associations between symbiotic partners. However, these studies do not test the causal relationship, or 'codependency', whereby the composition of one guild affects the composition of the other. Here we outline underlying requirements for codependency, compare important drivers for both plant and AM fungal communities, and assess how host preference - a pre-requisite for codependency - changes across spatiotemporal scales and taxonomic resolution for both plants and AM fungi. We find few examples in the literature designed to test for codependency and those that do have been conducted within plots or mesocosms. Also, while plants and AM fungi respond similarly to coarse environmental filters, most variation remains unexplained, with host identity explaining less than 30% of the variation in AM fungal communities. These results combined question the likelihood of predictable co-occurrence, and therefore evolution of codependency, between plant and AM fungal taxa across locations. We argue that codependency is most likely to occur in homogeneous environments where specific plant - AM fungal pairings have functional consequences for the symbiosis. We end by outlining critical aspects to consider moving forward.

Distinguishing nutrient-dependent plant driven bacterial colonization patterns in alfalfa.

To understand factors that influence the assembly of microbial communities, we inoculated Medicago sativa with a series of nested bacterial synthetic communities and grew plants in distinct nitrogen concentrations. Two isolates in our eight-member synthetic community, Williamsia sp. R60 and Pantoea sp. R4, consistently dominate community structure across nitrogen regimes. While Pantoea sp. R4 consistently colonizes plants to a higher degree compared to the other six organisms across each community and each nutrient level, Williamsia sp. R60 exhibits nutrient specific colonization differences. Williamsia sp. R60 is more abundant in plants grown at higher nitrogen concentrations, but exhibits the opposite trend when no plant is present, indicating plant-driven influence over colonization. Our research discovered unique, repeatable colonization phenotypes for individual microbes during plant microbiome assembly, and identified alterations caused by the host plant, microbes, and available nutrients.

Vertical differentiation in tropical forest butterflies: a novel mechanism generating insect diversity?

Many tropical fruit-feeding nymphalid butterflies are associated with either the forest canopy or the understorey; however, the exceptions offer insights into the origins of tropical diversity. As it occurs in both habitats of tropical forests in Ecuador and Peru, Archaeoprepona demophon is one such exception. We compared patterns of occurrence of A. demophon in the canopy and understorey and population genomic variation for evidence of ecological and genetic differentiation between habitats. We found that butterfly occurrences in the canopy were largely uncorrelated with occurrences in the understorey at both localities, indicating independent demographic patterns in the two habitats. We also documented modest, significant genome-level differentiation at both localities. Genetic differentiation between habitat types (separated by approx. 20 m in elevation) was comparable to levels of differentiation between sampling locations (approx. 1500 km). We conclude that canopy and understorey populations of A. demophon represent incipient independent evolutionary units. These findings support the hypothesis that divergence between canopy and understorey-associated populations might be a mechanism generating insect diversity in the tropics.

Extreme heterogeneity of population response to climatic variation and the limits of prediction.

Certain general facets of biotic response to climate change, such as shifts in phenology and geographic distribution, are well characterized; however, it is not clear whether the observed similarity of responses across taxa will extend to variation in other population-level processes. We examined population response to climatic variation using long-term incidence data (collected over 42 years) encompassing 149 butterfly species and considerable habitat diversity (10 sites along an elevational gradient from sea level to over 2,700 m in California). Population responses were characterized by extreme heterogeneity that was not attributable to differences in species composition among sites. These results indicate that habitat heterogeneity might be a buffer against climate change and highlight important questions about mechanisms maintaining interpopulation differences in responses to weather. Despite overall heterogeneity of response, population dynamics were accurately predicted by our model for many species at each site. However, the overall correlation between observed and predicted incidence in a cross validation analysis was moderate (Pearson's r = 0.23, SE 0.01), and 97% of observed data fell within the predicted 95% credible intervals. Prediction was most successful for more abundant species as well as for sites with lower annual turnover. Population-level heterogeneity in response to climate variation and the limits of our predictive power highlight the challenges for a future of increasing climatic variability.

Reef fish functional traits evolve fastest at trophic extremes.

Trophic ecology is thought to exert a profound influence on biodiversity, but the specifics of the process are rarely examined at large spatial and evolutionary scales. We investigate how trophic position and diet breadth influence functional trait evolution in one of the most species-rich and complex vertebrate assemblages, coral reef fishes, within a large-scale phylogenetic framework. We show that, in contrast with established theory, functional traits evolve fastest in trophic specialists with narrow diet breadths at both very low and high trophic positions. Top trophic level specialists exhibit the most functional diversity, while omnivorous taxa with intermediate trophic positions and wide diet breadth have the least functional diversity. Our results reveal the importance of trophic position in shaping evolutionary dynamics while simultaneously highlighting the incredible trophic and functional diversity present in coral reef fish assemblages.

The predictability of genomic changes underlying a recent host shift in Melissa blue butterflies.

Despite accumulating evidence that evolution can be predictable, studies quantifying the predictability of evolution remain rare. Here, we measured the predictability of genome-wide evolutionary changes associated with a recent host shift in the Melissa blue butterfly (Lycaeides melissa). We asked whether and to what extent genome-wide patterns of evolutionary change in nature could be predicted (i) by comparisons among instances of repeated evolution and (ii) from SNP × performance associations in a laboratory experiment. We delineated the genetic loci (SNPs) most strongly associated with host use in two L. melissa lineages that colonized alfalfa. Whereas most SNPs were strongly associated with host use in none or one of these lineages, we detected a an approximately twofold excess of SNPs associated with host use in both lineages. Similarly, we found that host-associated SNPs in nature could also be partially predicted from SNP × performance (survival and weight) associations in a laboratory rearing experiment. But the extent of overlap, and thus degree of predictability, was somewhat reduced. Although we were able to predict (to a modest extent) the SNPs most strongly associated with host use in nature (in terms of parallelism and from the experiment), we had little to no ability to predict the direction of evolutionary change during the colonization of alfalfa. Our results show that different aspects of evolution associated with recent adaptation can be more or less predictable and highlight how stochastic and deterministic processes interact to drive patterns of genome-wide evolutionary change.

A hierarchical Bayesian model to incorporate uncertainty into methods for diversity partitioning.

Recently there have been major theoretical advances in the quantification and partitioning of diversity within and among communities, regions, and ecosystems. However, applying those advances to real data remains a challenge. Ecologists often end up describing their samples rather than estimating the diversity components of an underlying study system, and existing approaches do not easily provide statistical frameworks for testing ecological questions. Here we offer one avenue to do all of the above using a hierarchical Bayesian approach. We estimate posterior distributions of the underlying "true" relative abundances of each species within each unit sampled. These posterior estimates of relative abundance can then be used with existing formulae to estimate and partition diversity. The result is a posterior distribution of diversity metrics describing our knowledge (or beliefs) about the study system. This approach intuitively leads to statistical inferences addressing biologically motivated hypotheses via Bayesian model comparison. Using simulations, we demonstrate that our approach does as well or better at approximating the "true" diversity of a community relative to naïve or ad-hoc bias-corrected estimates. Moreover, model comparison correctly distinguishes between alternative hypotheses about the distribution of diversity within and among samples. Finally, we use an empirical ecological dataset to illustrate how the approach can be used to address questions about the makeup and diversities of assemblages at local and regional scales.

Species-free species distribution models describe macroecological properties of protected area networks.

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.

Pairwise beta diversity resolves an underappreciated source of confusion in calculating species turnover.

Beta diversity is an important metric in ecology quantifying differentiation or disparity in composition among communities, ecosystems, or phenotypes. To compare systems with different sizes (N, number of units within a system), beta diversity is often converted to related indices such as turnover or local/regional differentiation. Here we use simulations to demonstrate that these naive measures of dissimilarity depend on sample size and design. We show that when N is the number of sampled units (e.g., quadrats) rather than the "true" number of communities in the system (if such exists), these differentiation measures are biased estimators. We propose using average pairwise dissimilarity as an intuitive solution. That is, instead of attempting to estimate an N-community measure, we advocate estimating the expected dissimilarity between any random pair of communities (or sampling units)-especially when the "true" N is unknown or undefined. Fortunately, measures of pairwise dissimilarity or overlap have been used in ecology for decades, and their properties are well known. Using the same simulations, we show that average pairwise metrics give consistent and unbiased estimates regardless of the number of survey units sampled. We advocate pairwise dissimilarity as a general standardization to ensure commensurability of different study systems.