Detecting the ecological footprint of selection.

The structure of communities is influenced by many ecological and evolutionary processes, but the way these manifest in classic biodiversity patterns often remains unclear. Here we aim to distinguish the ecological footprint of selection-through competition or environmental filtering-from that of neutral processes that are invariant to species identity. We build on existing Massive Eco-evolutionary Synthesis Simulations (MESS), which uses information from three biodiversity axes-species abundances, genetic diversity, and trait variation-to distinguish between mechanistic processes. To correctly detect and characterise competition, we add a new and more realistic form of competition that explicitly compares the traits of each pair of individuals. Our results are qualitatively different to those of previous work in which competition is based on the distance of each individual's trait to the community mean. We find that our new form of competition is easier to identify in empirical data compared to the alternatives. This is especially true when trait data are available and used in the inference procedure. Our findings hint that signatures in empirical data previously attributed to neutrality may in fact be the result of pairwise-acting selective forces. We conclude that gathering more different types of data, together with more advanced mechanistic models and inference as done here, could be the key to unravelling the mechanisms of community assembly and question the relative roles of neutral and selective processes.

Global determinants of insect mitochondrial genetic diversity.

Understanding global patterns of genetic diversity is essential for describing, monitoring, and preserving life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrates, which comprise only a small fraction of Earth's biodiversity. Here, we construct a global map of predicted insect mitochondrial genetic diversity from cytochrome c oxidase subunit 1 sequences, derived from open data. We calculate the mitochondrial genetic diversity mean and genetic diversity evenness of insect assemblages across the globe, identify their environmental correlates, and make predictions of mitochondrial genetic diversity levels in unsampled areas based on environmental data. Using a large single-locus genetic dataset of over 2 million globally distributed and georeferenced mtDNA sequences, we find that mitochondrial genetic diversity evenness follows a quadratic latitudinal gradient peaking in the subtropics. Both mitochondrial genetic diversity mean and evenness positively correlate with seasonally hot temperatures, as well as climate stability since the last glacial maximum. Our models explain 27.9% and 24.0% of the observed variation in mitochondrial genetic diversity mean and evenness in insects, respectively, making an important step towards understanding global biodiversity patterns in the most diverse animal taxon.

Multiple paths toward repeated phenotypic evolution in the spiny-leg adaptive radiation (Tetragnatha; Hawai'i).

The repeated evolution of phenotypes provides clear evidence for the role of natural selection in driving evolutionary change. However, the evolutionary origin of repeated phenotypes can be difficult to disentangle as it can arise from a combination of factors such as gene flow, shared ancestral polymorphisms or mutation. Here, we investigate the presence of these evolutionary processes in the Hawaiian spiny-leg Tetragnatha adaptive radiation, which includes four microhabitat-specialists or ecomorphs, with different body pigmentation and size (Green, Large Brown, Maroon, and Small Brown). We investigated the evolutionary history of this radiation using 76 newly generated low-coverage, whole-genome resequenced samples, along with phylogenetic and population genomic tools. Considering the Green ecomorph as the ancestral state, our results suggest that the Green ecomorph likely re-evolved once, the Large Brown and Maroon ecomorphs evolved twice and the Small Brown evolved three times. We found that the evolution of the Maroon and Small Brown ecomorphs likely involved ancestral hybridization events, while the Green and Large Brown ecomorphs likely evolved through novel mutations, despite a high rate of incomplete lineage sorting in the dataset. Our findings demonstrate that the repeated evolution of ecomorphs in the Hawaiian spiny-leg Tetragnatha is influenced by multiple evolutionary processes.

A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities.

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce massive ecoevolutionary synthesis simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: (i) species richness and abundances, (ii) population genetic diversities, and (iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multidimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.

The Easter Egg Weevil (Pachyrhynchus) genome reveals syntenic patterns in Coleoptera across 200 million years of evolution.

Patterns of genomic architecture across insects remain largely undocumented or decoupled from a broader phylogenetic context. For instance, it is unknown whether translocation rates differ between insect orders. We address broad scale patterns of genome architecture across Insecta by examining synteny in a phylogenetic framework from open-source insect genomes. To accomplish this, we add a chromosome level genome to a crucial lineage, Coleoptera. Our assembly of the Pachyrhynchus sulphureomaculatus genome is the first chromosome scale genome for the hyperdiverse Phytophaga lineage and currently the largest insect genome assembled to this scale. The genome is significantly larger than those of other weevils, and this increase in size is caused by repetitive elements. Our results also indicate that, among beetles, there are instances of long-lasting (>200 Ma) localization of genes to a particular chromosome with few translocation events. While some chromosomes have a paucity of translocations, intra-chromosomal synteny was almost absent, with gene order thoroughly shuffled along a chromosome. This large amount of reshuffling within chromosomes with few inter-chromosomal events contrasts with patterns seen in mammals in which the chromosomes tend to exchange larger blocks of material more readily. To place our findings in an evolutionary context, we compared syntenic patterns across Insecta in a phylogenetic framework. For the first time, we find that synteny decays at an exponential rate relative to phylogenetic distance. Additionally, there are significant differences in decay rates between insect orders, this pattern was not driven by Lepidoptera alone which has a substantially different rate.

High-throughput sequencing for community analysis: the promise of DNA barcoding to uncover diversity, relatedness, abundances and interactions in spider communities.

Large-scale studies on community ecology are highly desirable but often difficult to accomplish due to the considerable investment of time, labor and, money required to characterize richness, abundance, relatedness, and interactions. Nonetheless, such large-scale perspectives are necessary for understanding the composition, dynamics, and resilience of biological communities. Small invertebrates play a central role in ecosystems, occupying critical positions in the food web and performing a broad variety of ecological functions. However, it has been particularly difficult to adequately characterize communities of these animals because of their exceptionally high diversity and abundance. Spiders in particular fulfill key roles as both predator and prey in terrestrial food webs and are hence an important focus of ecological studies. In recent years, large-scale community analyses have benefitted tremendously from advances in DNA barcoding technology. High-throughput sequencing (HTS), particularly DNA metabarcoding, enables community-wide analyses of diversity and interactions at unprecedented scales and at a fraction of the cost that was previously possible. Here, we review the current state of the application of these technologies to the analysis of spider communities. We discuss amplicon-based DNA barcoding and metabarcoding for the analysis of community diversity and molecular gut content analysis for assessing predator-prey relationships. We also highlight applications of the third generation sequencing technology for long read and portable DNA barcoding. We then address the development of theoretical frameworks for community-level studies, and finally highlight critical gaps and future directions for DNA analysis of spider communities.

Nonequilibrium evolution of volatility in origination and extinction explains fat-tailed fluctuations in Phanerozoic biodiversity.

Fluctuations in biodiversity, large and small, pervade the fossil record, yet we do not understand the processes generating them. Here, we extend theory from nonequilibrium statistical physics to describe the fat-tailed form of fluctuations in Phanerozoic marine invertebrate richness. Using this theory, known as superstatistics, we show that heterogeneous rates of origination and extinction between clades and conserved rates within clades account for this fat-tailed form. We identify orders and families as the taxonomic levels at which clades experience interclade heterogeneity and within-clade homogeneity of rates, indicating that families are subsystems in local statistical equilibrium, while the entire system is not. The separation of timescales between within-clade background rates and the origin of major innovations producing new orders and families allows within-clade dynamics to reach equilibrium, while between-clade dynamics do not. The distribution of different dynamics across clades is consistent with niche conservatism and pulsed exploration of adaptive landscapes.

Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding.

Amplicon based metabarcoding promises rapid and cost-efficient analyses of species composition. However, it is disputed whether abundance estimates can be derived from metabarcoding due to taxon specific PCR amplification biases. PCR-free approaches have been suggested to mitigate this problem, but come with considerable increases in workload and cost. Here, we analyze multilocus datasets of diverse arthropod communities, to evaluate whether amplification bias can be countered by (1) targeting loci with highly degenerate primers or conserved priming sites, (2) increasing PCR template concentration, (3) reducing PCR cycle number or (4) avoiding locus specific amplification by directly sequencing genomic DNA. Amplification bias is reduced considerably by degenerate primers or targeting amplicons with conserved priming sites. Surprisingly, a reduction of PCR cycles did not have a strong effect on amplification bias. The association of taxon abundance and read count was actually less predictable with fewer cycles. Even a complete exclusion of locus specific amplification did not exclude bias. Copy number variation of the target loci may be another explanation for read abundance differences between taxa, which would affect amplicon based and PCR free methods alike. As read abundance biases are taxon specific and predictable, the application of correction factors allows abundance estimates.

Reinterpreting maximum entropy in ecology: a null hypothesis constrained by ecological mechanism.

Simplified mechanistic models in ecology have been criticised for the fact that a good fit to data does not imply the mechanism is true: pattern does not equal process. In parallel, the maximum entropy principle (MaxEnt) has been applied in ecology to make predictions constrained by just a handful of state variables, like total abundance or species richness. But an outstanding question remains: what principle tells us which state variables to constrain? Here we attempt to solve both problems simultaneously, by translating a given set of mechanisms into the state variables to be used in MaxEnt, and then using this MaxEnt theory as a null model against which to compare mechanistic predictions. In particular, we identify the sufficient statistics needed to parametrise a given mechanistic model from data and use them as MaxEnt constraints. Our approach isolates exactly what mechanism is telling us over and above the state variables alone.

Sunflower (Helianthus annuus) pollination in California's Central Valley is limited by native bee nest site location.

The delivery of ecosystem services by mobile organisms depends on the distribution of those organisms, which is, in turn, affected by resources at local and landscape scales. Pollinator-dependent crops rely on mobile animals like bees for crop production, and the spatial relationship between floral resources and nest location for these central-place foragers influences the delivery of pollination services. Current models that map pollination coverage in agricultural regions utilize landscape-level estimates of floral availability and nesting incidence inferred from expert opinion, rather than direct assessments. Foraging distance is often derived from proxies of bee body size, rather than direct measurements of foraging that account for behavioral responses to floral resource type and distribution. The lack of direct measurements of nesting incidence and foraging distances may lead to inaccurate mapping of pollination services. We examined the role of local-scale floral resource presence from hedgerow plantings on nest incidence of ground-nesting bees in field margins and within monoculture, conventionally managed sunflower fields in California's Central Valley. We tracked bee movement into fields using fluorescent powder. We then used these data to simulate the distribution of pollination services within a crop field. Contrary to expert opinion, we found that ground-nesting native bees nested both in fields and edges, though nesting rates declined with distance into field. Further, we detected no effect of field-margin floral enhancements on nesting. We found evidence of an exponential decay rate of bee movement into fields, indicating that foraging predominantly occurred in less than 1% of medium-sized bees' predicted typical foraging range. Although we found native bees nesting within agricultural fields, their restricted foraging movements likely centralize pollination near nest sites. Our data thus predict a heterogeneous distribution of pollination services within sunflower fields, with edges receiving higher coverage than field centers. To generate more accurate maps of services, we advocate directly measuring the autecology of ecosystem service providers, which vary by crop system, pollinator species, and region. Improving estimates of the factors affecting pollinator populations can increase the accuracy of pollination service maps and help clarify the influence of farming practices on wild bees occurring in agricultural landscapes.

Integrating macroecological metrics and community taxonomic structure.

We extend macroecological theory based on the maximum entropy principle from species level to higher taxonomic categories, thereby predicting distributions of species richness across genera or families and the dependence of abundance and metabolic rate distributions on taxonomic tree structure. Predictions agree with qualitative trends reported in studies on hyper-dominance in tropical tree species, mammalian body size distributions and patterns of rarity in worldwide plant communities. Predicted distributions of species richness over genera or families for birds, arthropods, plants and microorganisms are in excellent agreement with data. Data from an intertidal invertebrate community, but not from a dispersal-limited forest, are in excellent agreement with a predicted new relationship between body size and abundance. Successful predictions of the original species level theory are unmodified in the extended theory. By integrating macroecology and taxonomic tree structure, maximum entropy may point the way towards a unified framework for understanding phylogenetic community structure.

Taxon categories and the universal species-area relationship (a comment on Sizling et al., "between geometry and biology:the problem of universality of the species-area relationship").

A theory of macroecology based on the maximum information entropy (MaxEnt) inference procedure predicts that the log-log slope of the species-area relationship (SAR) at any spatial scale is a specified function of the ratio of abundance, N(A), to species richness, S(A), at that scale. The theory thus predicts, in generally good agreement with observation, that all SARs collapse onto a specified universal curve when local slope, z(A), is plotted against N(A)/S(A). A recent publication, however, argues that if it is assumed that patterns in macroecology are independent of the taxonomic choices that define assemblages of species, then this principle of "taxon invariance" precludes the MaxEnt-predicted universality of the SAR. By distinguishing two dimensions of the notion of taxon invariance, we show that while the MaxEnt-based theory predicts universality regardless of the taxonomic choices that define an assemblage of species, the biological characteristics of assemblages should under MaxEnt, and do in reality, influence the realism of the predictions.

Intensive agriculture erodes ß-diversity at large scales.

Biodiversity is declining from unprecedented land conversions that replace diverse, low-intensity agriculture with vast expanses under homogeneous, intensive production. Despite documented losses of species richness, consequences for ß-diversity, changes in community composition between sites, are largely unknown, especially in the tropics. Using a 10-year data set on Costa Rican birds, we find that low-intensity agriculture sustained ß-diversity across large scales on a par with forest. In high-intensity agriculture, low local (α) diversity inflated ß-diversity as a statistical artefact. Therefore, at small spatial scales, intensive agriculture appeared to retain ß-diversity. Unlike in forest or low-intensity systems, however, high-intensity agriculture also homogenised vegetation structure over large distances, thereby decoupling the fundamental ecological pattern of bird communities changing with geographical distance. This ~40% decline in species turnover indicates a significant decline in ß-diversity at large spatial scales. These findings point the way towards multi-functional agricultural systems that maintain agricultural productivity while simultaneously conserving biodiversity.

Relative contributions of neutral and niche-based processes to the structure of a desert grassland grasshopper community.

Whether neutral or deterministic factors structure biotic communities remains an open question in community ecology. We studied the spatial structure of a desert grassland grasshopper community and tested predictions for species sorting based on niche differentiation (deterministic) and dispersal limitation (neutral). We contrasted the change in species relative abundance and community similarity along an elevation gradient (i.e., environmental gradient) against community change across a relatively homogeneous distance gradient. We found a significant decrease in pairwise community similarity along both elevation and distance gradients, indicating that dispersal limitation plays a role in structuring local grasshopper communities. However, the distance decay of similarity was significantly stronger across the elevational gradient, indicating that niche-based processes are important as well. To further investigate mechanisms underlying niche differentiation, we experimentally quantified the dietary preferences of two common species, Psoloessa texana and Psoloessa delicatula, for the grasses Bouteloua eriopoda and Bouteloua gracilis, which are the dominant plants (~75% of total cover) in our study area. Cover of the preferred host plant explained some of the variation in relative abundances of the two focal species, although much variance in local Psoloessa distribution remained unexplained. Our results, the first to examine these hypotheses in arid ecosystems, indicate that the composition of local communities can be influenced by both probabilistic processes and mechanisms based in the natural histories of organisms.