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High-throughput sequencing (HTS) is increasingly being used for the characterization and monitoring of biodiversity. If applied in a structured way, across broad geographical scales, it offers the potential for a much deeper understanding of global biodiversity through the integration of massive quantities of molecular inventory data generated independently at local, regional and global scales. The universality, reliability and efficiency of HTS data can potentially facilitate the seamless linking of data among species assemblages from different sites, at different hierarchical levels of diversity, for any taxonomic group and regardless of prior taxonomic knowledge. However, collective international efforts are required to optimally exploit the potential of site-based HTS data for global integration and synthesis, efforts that at present are limited to the microbial domain. To contribute to the development of an analogous strategy for the nonmicrobial terrestrial domain, an international symposium entitled "Next Generation Biodiversity Monitoring" was held in November 2019 in Nicosia (Cyprus). The symposium brought together evolutionary geneticists, ecologists and biodiversity scientists involved in diverse regional and global initiatives using HTS as a core tool for biodiversity assessment. In this review, we summarize the consensus that emerged from the 3-day symposium. We converged on the opinion that an effective terrestrial Genomic Observatories network for global biodiversity integration and synthesis should be spatially led and strategically united under the umbrella of the metabarcoding approach. Subsequently, we outline an HTS-based strategy to collectively build an integrative framework for site-based biodiversity data generation.

Monitoring biodiversity is essential to protect, preserve and restore ecosystems, particularly in the context of current challenges such as climate change, habitat destruction and globalization (Baird & Hajibabaei, 2012). Biomonitoring is needed for developing biotic indices for assessing ecological status, measuring impacts of anthropogenic activities in natural ecosystems, evaluating biodiversity loss, surveying nonindigenous species, conservation, and identifying cryptic species (Balvanera et al., 2006; Fišer et al., 2018). Thus, spatially and temporally structured biomonitoring activities provide a powerful tool for the implementation of regional, national and international regulations, directives and policies for nature conservation. However substantial impediments exist including access to remote locations, limited specialist taxonomic knowledge, cost, slow pace of human-driven data analyses, and typically low sensitivity for detection of rare and elusive species (Zinger et al., 2020). These drawbacks are often translated into expensive monitoring activities with limited spatial, temporal and taxonomic coverage. In this context, new approaches for biomonitoring are being explored, among which advanced DNA-based technologies are emerging (Kissling et al., 2018). The field of biodiversity monitoring through the analysis of the pool of DNA isolated from environmental samples, referred to as environmental DNA or eDNA (Pawlowski et al., 2020; Taberlet et al., 2012), is rapidly growing. This growth is being driven through improved approaches for sampling, data generation and analyses, and with recent advances on how eDNA should be interpreted for biodiversity assessments (Bohmann et al., 2014). The success of eDNA-based biomonitoring is reflected in exponential growth of publications within this area and increasing submissions to Molecular Ecology Resources in particular (Figure 1). Molecular Ecology Resources aims to publish high quality eDNA studies that serve as

Dispersal limitation has been recurrently suggested to shape both macroecological patterns and microevolutionary processes within invertebrates. However, because of potential interactions among biological, environmental, temporal, and spatial variables, causal links among flight-related traits, diversification and spatial patterns of community assembly remain elusive. Integrating genetic variation within species across whole insect assemblages, within a simplified spatial and environmental framework, can be used to reduce the impact of these potentially confounding variables. Here, we used standardized sampling and mitochondrial DNA sequencing for a whole-community characterization of the beetle fauna inhabiting a singular forested habitat (laurel forest) within an oceanic archipelago setting (Canary Islands). The spatial structure of species assemblages together with species-level genetic diversity was compared at the archipelago and island scales for 104 winged and 110 wingless beetle lineages. We found that wingless beetle lineages have: (i) smaller range sizes at the archipelago scale, (ii) lower representation in younger island communities, (iii) stronger population genetic structure, and (iv) greater spatial structuring of species assemblages between and within islands. Our results reveal that dispersal limitation is a fundamental trait driving diversity patterns at multiple hierarchical levels by promoting spatial diversification and affecting the spatial configuration of entire assemblages at both island and archipelago scales.

Oceanic island archipelagos provide excellent models to understand evolutionary processes. Colonization events and gene flow can interact with selection to shape genetic variation at different spatial scales. Landscape-scale variation in biotic and abiotic factors may drive fine-scale selection within islands, while long-term evolutionary processes may drive divergence between distantly related populations. Here, we examine patterns of population history and selection between recently diverged populations of the Berthelot's pipit (Anthus berthelotii), a passerine endemic to three North Atlantic archipelagos. First, we use demographic trees and f3 statistics to show that genome-wide divergence across the species range is largely shaped by colonization and bottlenecks, with evidence of very weak gene flow between populations. Then, using a genome scan approach, we identify signatures of divergent selection within archipelagos at single nucleotide polymorphisms (SNPs) in genes potentially associated with craniofacial development and DNA repair. We did not detect within-archipelago selection at the same SNPs as were detected previously at broader spatial scales between archipelagos, but did identify signatures of selection at loci associated with similar biological functions. These findings suggest that similar ecological factors may repeatedly drive selection between recently separated populations, as well as at broad spatial scales across varied landscapes.

Aim: To (a) evaluate if colonization of newly emerged high-elevation habitats occurred from neighbouring highlands (allopatric divergence and niche conservatism) or from within the same mountain (peripatric or parapatric divergence and niche shift), and (b) test for the effect of past landscape configurations in geographically structuring biodiversity (a West-East structure spanning the central part of the Transmexican Volcanic Belt).Location: Transmexican Volcanic Belt, Mexico. Taxa: Coleoptera and Araneae. Methods: Coleoptera and Araneae communities were collected in a comparative sampling framework. Seven sky-islands were sampled within two high-elevation habitats separated by altitude. Samples were individually sequenced for a region of the mtDNA COI gene to delimit Operational Taxonomic Units (OTUs) and haplotypes within them. Richness was estimated at the community level, as well as genetic diversity within and among mountains and habitats. The West East structure was tested with a null model and an analysis of variance with permutations. Results: Few OTUs were shared between the Abies forests and alpine grasslands. High beta diversity was found across mountains. Beta diversity between the West – East grouping is higher than expected by chance. Main conclusions: Our results indicate that colonization from other mountains followed by allopatric divergence dominates as a source of OTU formation, and that despite some probable connectivity during glacial periods existed, ancient communities and genetic structures persist.

Metabarcoding of Metazoa using mitochondrial genes may be confounded by both the accumulation of PCR and sequencing artefacts and the co-amplification of nuclear mitochondrial pseudogenes (NUMTs). The application of read abundance thresholds and denoising methods is efficient in reducing noise accompanying authentic mitochondrial amplicon sequence variants (ASVs). However, these procedures do not fully account for the complex nature of concomitant sequences and the highly variable DNA contribution of specimens in a metabarcoding sample. We propose, as a complement to denoising, the metabarcoding Multidimensional Abundance Threshold Evaluation (metaMATE) framework, a novel approach that allows comprehensive examination of multiple dimensions of abundance filtering and the evaluation of the prevalence of unwanted concomitant sequences in denoised metabarcoding datasets. metaMATE requires a denoised set of ASVs as input, and designates a subset of ASVs as being either authentic (mitochondrial DNA haplotypes) or nonauthentic ASVs (NUMTs and erroneous sequences) by comparison to external reference data and by analysing nucleotide substitution patterns. metaMATE (i) facilitates the application of read abundance filtering strategies, which are structured with regard to sequence library and phylogeny and applied for a range of increasing abundance threshold values, and (ii) evaluates their performance by quantifying the prevalence of nonauthentic ASVs and the collateral effects on the removal of authentic ASVs. The output from metaMATE facilitates decision-making about required filtering stringency and can be used to improve the reliability of intraspecific genetic information derived from metabarcode data. The framework is implemented in the metaMATE software (available at ).

The most remarkable feature of our planet is the diversity of its life forms, ranging from viruses and nanobacteria to blue whales and giant sequoias to satanic leaf‐tailed geckos and leafy seadragons (look them up!). Life is found in essentially all environments on earth, and the number of species living on our planet is many times greater than we could have imagined a century ago. A well‐regarded estimate pegs the number of eukaryotic species on earth at 8.7 million (±1.3 million), of which fewer than 15% are currently described (Mora et al., 2011). The diversity of prokaryotes is less clear (and highly controversial), but an analysis of 1.6 billion 16S ribosomal RNA sequences estimated that 0.8–1.6 million prokaryotic operational taxonomic units exist globally (Louca et al., 2019). While we do not know how many species are currently extant, or have existed in the past, we do know that this biodiversity is valuable, providing food, fibre and medicine, furnishing ecosystem services such as water and air purification, nutrient cycling, pollination and carbon uptake, and contributing to technological innovations ranging from biotechnology to robotics to material science. Moreover, biodiversity underlies the cultural identity of human populations and is important to human health and well‐being. Geographically, species richness increases from the Polar Regions to the tropics in terrestrial and surface marine ecosystems. Thus, some countries, especially those in tropical and subtropical regions, are endowed with much greater biodiversity than others. Unfortunately, benefits arising from the access and utilization of this biodiversity have been unequally shared, with (paradoxically) biodiversity‐poor countries often accruing the lion's share of economic gains. There can be imbalances within countries as well, wherein some segments of the population obtain greater economic benefits from biodiversity and associated traditional knowledge than indigenous peoples. The “Nagoya

The genus Baezia Alonso-Zarazaga & García, 1999 is endemic to the Canary Islands, where four species were known to date. Based on morphological evidence, three new species of Baezia are described in this study: Baezia aranfaybo García & López, sp. nov. from El Hierro island, and Baezia madai García & Oromí sp. nov. and Baezia tizziri García & Andújar, sp. nov. from La Palma island. Notes on their biology, habitat, and distribution are presented. The number of taxa in this endemic Canarian genus increases to seven eyeless species. One species has been reported from the soil (endogean environment), with the other six associated with caves and the mesovoid shallow substratum (hypogean or subterranean environment). Frequent association with the presence of roots suggests that species of Baezia may inhabit the continuum represented by the endogean and hypogean environments. Identification key to the seven species are provided.

High‐throughput sequencing (HTS) is increasingly being used for the characterization and monitoring of biodiversity. If applied in a structured way, across broad geographical scales, it offers the potential for a much deeper understanding of global biodiversity through the integration of massive quantities of molecular inventory data generated independently at local, regional and global scales. The universality, reliability and efficiency of HTS data can potentially facilitate the seamless linking of data among species assemblages from different sites, at different hierarchical levels of diversity, for any taxonomic group and regardless of prior taxonomic knowledge. However, collective international efforts are required to optimally exploit the potential of site‐based HTS data for global integration and synthesis, efforts that at present are limited to the microbial domain. To contribute to the development of an analogous strategy for the nonmicrobial terrestrial domain, an international symposium entitled “Next Generation Biodiversity Monitoring” was held in November 2019 in Nicosia (Cyprus). The symposium brought together evolutionary geneticists, ecologists and biodiversity scientists involved in diverse regional and global initiatives using HTS as a core tool for biodiversity assessment. In this review, we summarize the consensus that emerged from the 3‐day symposium. We converged on the opinion that an effective terrestrial Genomic Observatories network for global biodiversity integration and synthesis should be spatially led and strategically united under the umbrella of the metabarcoding approach. Subsequently, we outline an HTS‐based strategy to collectively build an integrative framework for site‐based biodiversity data generation.

Montane cloud forests are areas of high endemism, and are one of the more vulnerable terrestrial ecosystems to climate change. Thus, understanding how they both contribute to the generation of biodiversity, and will respond to ongoing climate change, are important and related challenges. The widely accepted model for montane cloud forest dynamics involves upslope forcing of their range limits with global climate warming. However, limited climate data provides some support for an alternative model, where range limits are forced downslope with climate warming. Testing between these two models is challenging, due to the inherent limitations of climate and pollen records. We overcome this with an alternative source of historical information, testing between competing model predictions using genomic data and demographic analyses for a species of beetle tightly associated to an oceanic island cloud forest. Results unequivocally support the alternative model: populations that were isolated at higher elevation peaks during the Last Glacial Maximum are now in contact and hybridizing at lower elevations. Our results suggest that genomic data are a rich source of information to further understand how montane cloud forest biodiversity originates, and how it is likely to be impacted by ongoing climate change.

Metabarcoding of DNA extracted from community samples of whole organisms (whole organism community DNA, wocDNA) is increasingly being applied to terrestrial, marine and freshwater metazoan communities to provide rapid, accurate and high resolution data for novel molecular ecology research. The growth of this field has been accompanied by considerable development that builds on microbial metabarcoding methods to develop appropriate and efficient sampling and laboratory protocols for whole organism metazoan communities. However, considerably less attention has focused on ensuring bioinformatic methods are adapted and applied comprehensively in wocDNA metabarcoding. In this study we examined over 600 papers and identified 111 studies that performed COI metabarcoding of wocDNA. We then systematically reviewed the bioinformatic methods employed by these papers to identify the state-of-the-art. Our results show that the increasing use of wocDNA COI metabarcoding for metazoan diversity is characterised by a clear absence of bioinformatic harmonisation, and the temporal trends show little change in this situation. The reviewed literature showed (i) high heterogeneity across pipelines, tasks and tools used, (ii) limited or no adaptation of bioinformatic procedures to the nature of the COI fragment, and (iii) a worrying underreporting of tasks, software and parameters. Based upon these findings we propose a set of recommendations that we think the wocDNA metabarcoding community should consider to ensure that bioinformatic methods are appropriate, comprehensive and comparable. We believe that adhering to these recommendations will improve the long-term integrative potential of wocDNA COI metabarcoding for biodiversity science.

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 Eco-evolutionary 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 multi-dimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine 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.

Neutral theory proposes that dispersal stochasticity is one of the main drivers of local diversity. Haplotypes-level genetic variation can now be efficiently sampled from across whole communities, thus making it possible to test neutral predictions from the genetic to species-level diversity, and higher. However, empirical data is still limited, with the few studies to date coming from temperate latitudes. Here, we focus on a tropical mountain within the Transmexican Volcanic Belt to evaluate spatially fine-scale patterns of arthropod community assembly to understand the role of dispersal limitation and landscape features as drivers of diversity. We sampled whole-communities of arthropods for eight orders at a spatial scale ranging from 50 m to 19 km, using whole community metabarcoding. We explored multiple hierarchical levels, from individual haplotypes to lineages at 0.5, 1.5, 3, 5, 7.5% similarity thresholds, to evaluate patterns of richness, turnover, and distance decay of similarity with isolation-by-distance and isolation-by resistance (costs to dispersal given by landscape features) approaches. Our results showed that distance and altitude influence distance decay of similarity at all hierarchical levels. This holds for arthropod groups of contrasting dispersal abilities, but with different strength depending on the spatial scale. Our results support a model where local-scale differentiation mediated by dispersal constraints, combined with long-term persistence of lineages, is an important driver of diversity within tropical sky islands.

BPEC is an R package for Bayesian phylogeographic and ecological clustering which allows geographical, environmental and phenotypic measurements to be combined with deoxyribonucleic acid (DNA) sequences in order to reveal geographic structuring of DNA sequence clusters consistent with migration events. DNA sequences are modelled using a collapsed version of a simplified coalescent model projected onto haplotype trees, which subsequently give rise to constrained clusterings as migrations occur. Within each cluster, a multivariate Gaussian distribution of the covariates (geographical, environmental, phenotypic) is used. Inference follows tailored reversible jump Markov chain Monte Carlo sampling so that the number of clusters (i.e., migrations) does not need to be pre-specified. A number of output plots and visualizations are provided which reflect the posterior distribution of the parameters of interest. BPEC also includes functions that create output files which can be loaded into Google Earth. The package commands are illustrated through an example dataset of the polytypic Near Eastern brown frog Rana macrocnemis analyzed using BPEC.

In Focus: Scalercio, S., Cini, A., Menchetti, M., Vodă, R., Bonelli, S., Bordoni, A., … Dapporto, L. (2020). How long is 3 km for a butterfly? Ecological constraints and functional traits explain high mitochondrial genetic diversity between Sicily and the Italian Peninsula. Journal of Animal Ecology. https://doi.org/10.1111/1365‐2656.13196. Biotic and abiotic factors can shape geographical patterns of genetic variation within species, but few studies have addressed how this might generate common patterns at the level of communities of species. Scalercio et al. (2020) have combined mtDNA sequence data and life‐history traits, to reveal a repeated pattern of genetic structure between Sicilian and southern Italian butterfly populations, which are separated by only 3 km of ocean. They reveal how intrinsic species traits and extrinsic environmental constraints explain this pattern, demonstrating an important role for wind. Moreover, the inclusion of almost 8,000 georeferenced sequences reveals that, in spite of also being present in southern Italy, almost half of Sicilian butterfly species are more closely related to populations from other parts of Europe, Asia or North Africa. We provide further discussion on the biogeographic barrier they identify, and the potential of community‐level DNA barcoding to identify processes that structure genetic variation across communities.

Background There is an increasing demand for databases including species trait information for biodiversity and community ecology studies. The existence of trait databases is useful for comparative studies within taxa or geographical regions, but there is low availability of databases for certain organisms. Here we present an open access functional trait database for spiders from Macaronesia and the Iberian Peninsula, recording several morphological and ecological traits related to the species life histories, microhabitat and trophic preferences. New information We present a database that includes 12 biological traits for 506 spider species present in natural forests of the Iberian Peninsula (Spain) and three Macaronesian archipelagoes (Azores, Madeira and Canary Islands). The functional trait database consists of two sections: individual-level data for six morphological traits (total body size, prosoma length, prosoma width, prosoma height, tibia I length and fang length), based on direct measurements of 2844 specimens of all spider species; and species-level aggregate data for 12 traits (same 6 morphological traits as in the previous section plus dispersal ability, vertical stratification, circadian activity, foraging strategy, trophic specialization and colonization status), based on either the average of the direct measurements or bibliographic searches. This functional trait database will serve as a data standard for currently ongoing analyses that require trait and functional diversity statistics.

Soil arthropod communities are highly diverse and critical for ecosystem functioning. However, our knowledge of spatial structure and the underlying processes of community assembly are scarce, hampered by limited empirical data on species diversity and turnover. We implement a high‐throughput sequencing approach to generate comparative data for thousands of arthropods at three hierarchical levels: genetic, species and supra‐specific lineages. A joint analysis of the spatial arrangement across these levels can reveal the predominant processes driving the variation in biological assemblages at the local scale. This multihierarchical approach was performed using haplotype‐level COI metabarcoding of entire communities of mites, springtails and beetles from three Iberian mountain regions. Tens of thousands of specimens were extracted from deep and superficial soil layers and produced comparative phylogeographic data for >1,000 codistributed species and nearly 3,000 haplotypes. Local assemblage composition differed greatly between grasslands and forests and, within each habitat, showed strong spatial structure and high endemicity. Distance decay was high at all levels, even at the scale of a few kilometres or less. The local distance decay patterns were self‐similar for the haplotypes and higher hierarchical entities, and this fractal structure was similar in all regions, suggesting that uniform processes of limited dispersal determine local‐scale community assembly. Our results from whole‐community metabarcoding provide insight into how dispersal limitations constrain mesofauna community structure within local spatial settings over evolutionary timescales. If generalized across wider areas, the high turnover and endemicity in the soil locally may indicate extremely high richness globally, challenging our current estimations of total arthropod diversity on Earth.

Phylogenetic relatedness is a key diversity measure for the analysis and understanding of how species and communities evolve across time and space. Understanding the nonrandom loss of species with respect to phylogeny is also essential for better-informed conservation decisions. However, several factors are known to influence phylogenetic reconstruction and, ultimately, phylogenetic diversity metrics. In this study, we empirically tested how some of these factors (topological constraint, taxon sampling, genetic markers and calibration) affect phylogenetic resolution and uncertainty. We built a densely sampled, species-level phylogenetic tree for spiders, combining Sanger sequencing of species from local communities of two biogeographical regions (Iberian Peninsula and Macaronesia) with a taxon-rich backbone matrix of Genbank sequences and a topological constraint derived from recent phylogenomic studies. The resulting tree constitutes the most complete spider phylogeny to date, both in terms of terminals and background information, and may serve as a standard reference for the analysis of phylogenetic diversity patterns at the community level. We then used this tree to investigate how partial data affect phylogenetic reconstruction, phylogenetic diversity estimates and their rankings, and, ultimately, the ecological processes inferred for each community. We found that the incorporation of a single slowly evolving marker (28S) to the DNA barcode sequences from local communities, had the highest impact on tree topology, closely followed by the use of a backbone matrix. The increase in missing data resulting from combining partial sequences from local communities only had a moderate impact on the resulting trees, similar to the difference observed when using topological constraints. Our study further revealed substantial differences in both the phylogenetic structure and diversity rankings of the analyzed communities estimated from the different phylogenetic treatments

High-throughput DNA methods hold great promise for phylogenetic analysis of lineages that are difficult to study with conventional molecular and morphological approaches. The mites (Acari), and in particular the highly diverse soil-dwelling lineages, are among the least known branches of the metazoan Tree-of-Life. We extracted numerous minute mites from soils in an area of mixed forest and grassland in southern Iberia. Selected specimens representing the full morphological diversity were shotgun sequenced in bulk, followed by genome assembly of short reads from the mixture, which produced >100 mitochondrial genomes representing diverse acarine lineages. Phylogenetic analyses in combination with taxonomically limited mitogenomes available publicly resulted in plausible trees defining basal relationships of the Acari. Several critical nodes were supported by ancestral-state reconstructions of mitochondrial gene rearrangements. Molecular calibration placed the minimum age for the common ancestor of the superorder Acariformes, which includes most soil-dwelling mites, to the Cambrian–Ordovician (likely within 455–552 Ma), whereas the origin of the superorder Parasitiformes was placed later in the Carboniferous-Permian. Most family-level taxa within the Acariformes were dated to the Jurassic and Triassic. The ancient origin of Acariformes and the early diversification of major extant lineages linked to the soil are consistent with a pioneering role for mites in building the earliest terrestrial ecosystems.

Recent biological analyses suggest that reductions in dispersal ability have beenkey drivers of diversification across numerous lineages. We synthesise emergingdata to highlight similarities regarding the causes and consequences of dispersalreduction across taxa and ecosystems, as well as the diverse genomic mechanismsunderpinning these shifts. Natural selection has acted on standing genetic variationwithin taxa to drive often rapid–and in some cases parallel–losses of dispersal,and ultimately speciation. Such shifts can thus represent an important nexus be-tween adaptive and neutral diversification processes, with substantial evolutionaryconsequences. Recognition of the links between these concepts that are emergingfrom differentfields, taxa and ecosystems is transforming our understanding of thefascinating role of dispersal reduction in the formation of biodiversity.

Geographic isolation substantially contributes to species endemism on oceanic islands when speciation involves the colonisation of a new island. However, less is understood about the drivers of speciation within islands. What is lacking is a general understanding of the geographic scale of gene flow limitation within islands, and thus the spatial scale and drivers of geographical speciation within insular contexts. Using a community of beetle species, we show that when dispersal ability and climate tolerance are restricted, microclimatic variation over distances of only a few kilometres can maintain strong geographic isolation extending back several millions of years. Further to this, we demonstrate congruent diversification with gene flow across species, mediated by Quaternary climate oscillations that have facilitated a dynamic of isolation and secondary contact. The unprecedented scale of parallel species responses to a common environmental driver for evolutionary change has profound consequences for understanding past and future species responses to climate variation.

Weevils (Coleoptera: Curculionoidea) represent one of the most diverse groups of organisms on Earth; interactions with their host plants have been recognized to play a central role in their remarkable diversity, yet the exact mechanisms and factors still remain poorly understood. Using phylogenetic comparative analyses, here we investigate the evolution of host use and its possible role in diversification processes of Rhinusa and Gymnetron, two closely related groups of weevils that feed and develop inside plant tissues of hosts within the families Scrophulariaceae and Plantaginaceae. We found strong evidence for phylogenetic conservatism of host use at the plant family level, most likely due to substantial differences in the chemical composition of hosts, reducing the probability of shifts between host families. In contrast, the use of different plant organs represents a more labile ecological trait and ecological niche expansion that allows a finer partitioning of resources. Rhinusa and Gymnetron weevils initially specialized on plants within Scrophulariaceae and then shifted to the closely related Plantaginaceae; likewise, a gall inducing behavior evolved from non-galler weevils, possibly in response to resource competition, as galls facilitate larval development by providing enhanced nutrition and a favorable microhabitat. Results from trait-dependent diversification analyses suggest that both use of hosts within Plantaginaceae and parasitism on fruits and seed capsules are associated with enhanced diversification of Rhinusa and Gymnetron via low extinction rates. Our study provides quantitative evidence and insights on the ecological factors that can promote diversification in phytophagous insects that feed and develop inside plant tissues.

Geographic isolation substantially contributes to species endemism on oceanic islands when speciation involves the colonisation of a new island. However, less is understood about the drivers of speciation within islands. What is lacking is a general understanding of the geographic scale of gene flow limitation within islands, and thus the geographic scale and drivers of geographical speciation within insular contexts. Using a community of beetle species, we show that when dispersal ability and climate tolerance are restricted, microclimatic variation over distances of only a few kilometres can maintain strong geographic isolation and drive incipient speciation. Further to this, we demonstrate congruent diversification with gene flow across species, mediated by Quaternary climate oscillations that have facilitated a dynamic of isolation and secondary contact. The unprecedented scale of parallel species responses to a common environmental driver for evolutionary change has profound consequences for understanding past and future species responses to climate variation.

Introgression, the transmission of genetic material of one taxon into another through hybridization, can have various evolutionary outcomes. Previous studies have detected signs of introgression between western populations of the Mexican endemic and threatened spiny-tailed iguana, Ctenosaura pectinata. However, the extent of this phenomenon along the geographic distribution of the species is unknown. Here, we use multilocus data together with detailed geographic sampling to (1) define genotypic clusters within C. pectinata; (2) evaluate geographic concordance between maternally and biparentally inherited markers; (3) examine levels of introgression between genotypic clusters, and (4) suggest taxonomic modifications in light of this information. Applying clustering methods to genotypes of 341 individuals from 49 localities of C. pectinata and the closely related C. acanthura, we inferred the existence of five genotypic clusters. Contact zones between genotypic clusters with signatures of interbreeding were detected, showing different levels of geographic discordance with mtDNA lineages. In northern localities, mtDNA and microsatellites exhibit concordant distributions, supporting the resurrection of C. brachylopha. Similar concordance is observed along the distribution of C. acanthura, confirming its unique taxonomic identity. Genetic and geographic concordance is also observed for populations within southwestern Mexico, where the recognition of a new species awaits in depth taxonomic revision. In contrast, in western localities a striking pattern of discordance was detected where up to six mtDNA lineages co-occur with only two genotypic clusters. Given that the type specimen originated from this area, we suggest that individuals from western Mexico keep the name C. pectinata. Our results have profound implications for conservation, management, and forensics of Mexican iguanas.

The study of biodiversity started as a single unified field that spanned both ecology and evolution and both macro and micro phenomena. But over the 20th century, major trends drove ecology and evolution apart and pushed an emphasis towards the micro perspective in both disciplines. Macroecology and macroevolution re-emerged as self-consciously distinct fields in the 1970s and 1980s, but they remain largely separated from each other. Here, we argue that despite the challenges, it is worth working to combine macroecology and macroevolution. We present 25 fundamental questions about biodiversity that are answerable only with a mixture of the views and tools of both macroecology and macroevolution.

[Aim]: Understanding the drivers of speciation within islands is key to explain the high levels of invertebrate diversification and endemism often observed within islands. Here, we propose an insular topoclimate model for Quaternary diversification (ITQD), and test the general prediction that, within a radially eroded conical island, glacial climate conditions facilitate the divergence of populations within species across valleys. [Location]: Gran Canaria, Canary Islands. [Taxon]: The Laparocerus tessellatus beetle species complex (Coleoptera, Curculionidae). [Methods]: We characterize individual-level genomic relationships using single nucleotide polymorphisms produced by double-digest restriction site associated DNA sequencing (ddRAD-seq). A range of parameter values were explored in order to filter our data. We assess individual relatedness, species boundaries, demographic history and spatial patterns of connectivity. [Results]: The total number of ddRAD-seq loci per sample ranges from 4,576 to 512, with 11.12% and 4.84% of missing data respectively, depending on the filtering parameter combination. We consistently infer four genetically distinct ancestral populations and two presumed cases of admixture, one of which is largely restricted to high altitudes. Bayes factor delimitation support the hypothesis of four species, which is consistent with the four inferred ancestral gene pools. Landscape resistance analyses identified genomic relatedness among individuals in two out of the four inferred species to be best explained by annual precipitation during the last glacial maximum rather than geographic distance. [Main conclusions]: Our data reveal a complex speciation history involving population isolation and admixture, with broad support for the ITQD model here proposed. We suggest that further studies are needed to test the generality of our model, and enrich our understanding of the evolutionary process in island invertebrates. Our results demonstrate the power