ABSTRACT
Although species are central units for biological research, recent findings in genomics are raising awareness that what we call species can be ill-founded entities due to solely morphology-based, regional species descriptions. This particularly applies to groups characterized by intricate evolutionary processes such as hybridization, polyploidy, or asexuality. Here, challenges of current integrative taxonomy (genetics/genomics + morphology + ecology, etc.) become apparent: different favored species concepts, lack of universal characters/markers, missing appropriate analytical tools for intricate evolutionary processes, and highly subjective ranking and fusion of datasets. Now, integrative taxonomy combined with artificial intelligence under a unified species concept can enable automated feature learning and data integration, and thus reduce subjectivity in species delimitation. This approach will likely accelerate revising and unraveling eukaryotic biodiversity.
Subject(s)
Artificial Intelligence , Classification , Classification/methods , Biodiversity , GenomicsABSTRACT
Catastrophic flank collapses are recognized as important drivers of insular biodiversity dynamics, through the disruption of species ranges and subsequent allopatric divergence. However, little empirical data supports this conjecture, with their evolutionary consequences remaining poorly understood. Using genome-wide data within a population genomics and phylogenomics framework, we evaluate how mega-landslides have impacted evolutionary and demographic history within a species complex of weevils (Curculionidae) within the Canary Island of Tenerife. We reveal a complex genomic landscape, within which individuals of single ancestry were sampled in areas characterized by long-term geological stability, relative to the timing of flank collapses. In contrast, individuals of admixed ancestry were almost exclusively sampled within the boundaries of flank collapses. Estimated divergence times among ancestral populations aligned with the timings of mega-landslide events. Our results provide first evidence for a cyclical dynamic of range fragmentation and secondary contact across flank collapse landscapes, with support for a model where this dynamic is mediated by Quaternary climate oscillations. The context within which we reveal climate and topography to interact cyclically through time to shape the geographic structure of genetic variation, together with related recent work, highlights the importance of topoclimatic phenomena as an agent of diversification within insular invertebrates.
Subject(s)
Genetics, Population , Islands , Phylogeny , Animals , Weevils/genetics , Weevils/classification , BiodiversityABSTRACT
The relationship between species local abundance and their regional distribution (occupancy) is one of the most extensively recognized and investigated patterns in ecology. While exceptions exist, the generally held model is that locally abundant species also tend to be more widespread geographically. However, there is only a limited understanding of both the mechanisms driving this relationship, and their scale dependency. Here we use occupancy and abundance data for 123 species of spider from across the Canary Islands to understand how both dispersal ability and niche breadth might mediate variation among species for local abundance and occupancy. We test the predictions that (i) dispersal ability explains variation among species for both abundance and occupancy, and (ii) species with a higher degree of habitat specialization, reflecting more limited niche breadth, will have both higher occupancy and abundance. We find no evidence within habitat patches for an effect of dispersal ability on either local abundance or site occupancy, while across all patches species with higher dispersal ability tend to occupy more sites. Species largely restricted to laurel forests have higher abundance than species with broader niche breadth, but similar occupancy. The study revealed that dispersal ability and niche breadth were significant predictors of the abundance-occupancy relationship, highlighting the importance of both factors for understanding patterns of abundance and occupancy among spider species.
ABSTRACT
Understanding the relative contributions of ecological and evolutionary processes to the structuring of ecological communities is needed to improve our ability to predict how communities may respond to future changes in an increasingly human-modified world. Metabarcoding methods make it possible to gather population genetic data for all species within a community, unlocking a new axis of data to potentially unveil the origins and maintenance of biodiversity at local scales. Here, we present a new eco-evolutionary simulation model for investigating community assembly dynamics using metabarcoding data. The model makes joint predictions of species abundance, genetic variation, trait distributions and phylogenetic relationships under a wide range of parameter settings (e.g. high speciation/low dispersal or vice versa) and across a range of community states, from pristine and unmodified to heavily disturbed. We first demonstrate that parameters governing metacommunity and local community processes leave detectable signatures in simulated biodiversity data axes. Next, using a simulation-based machine learning approach we show that neutral and non-neutral models are distinguishable and that reasonable estimates of several model parameters within the local community can be obtained using only community-scale genetic data, while phylogenetic information is required to estimate those describing metacommunity dynamics. Finally, we apply the model to soil microarthropod metabarcoding data from the Troodos mountains of Cyprus, where we find that communities in widespread forest habitats are structured by neutral processes, while high-elevation and isolated habitats act as an abiotic filter generating non-neutral community structure. We implement our model within the ibiogen R package, a package dedicated to the investigation of island, and more generally community-scale, biodiversity using community-scale genetic data.
Subject(s)
Ecosystem , Models, Biological , Humans , Phylogeny , Biological Evolution , Biodiversity , Genetic Variation/geneticsABSTRACT
Since Darwin put forward his opposing hypotheses to explain the successful establishment of species in areas outside their native ranges, the preadaptation and competition-relatedness hypotheses, known as Darwin's naturalization conundrum, numerous studies have sought to understand the relative importance of each. Here, we take advantage of well-characterized beetle communities across laurel forests of the Canary Islands for a first evaluation of the relative support for Darwin's two hypotheses within arthropods. We generated a mitogenome backbone tree comprising nearly half of the beetle genera recorded within the Canary Islands for the phylogenetic placement of native and introduced species sampled in laurel forests, using cytochrome c oxidase I (COI) sequences. For comparative purposes, we also assembled and phylogenetically placed a data set of COI sequences for introduced beetle species that were not sampled within laurel forests. Our results suggest a stronger effect of species preadaptation over resource competition, while also revealing an underappreciated shortfall in arthropod biodiversity data-knowledge of species as being native or introduced. We name this the Humboldtean shortfall and suggest that similar studies using arthropods should incorporate DNA barcode sequencing to mitigate this problem.
Subject(s)
Arthropods , Coleoptera , Animals , Phylogeny , Coleoptera/genetics , Biodiversity , Forests , Introduced SpeciesABSTRACT
A recurring feature of oceanic archipelagos is the presence of adaptive radiations that generate endemic, species-rich clades that can offer outstanding insight into the links between ecology and evolution. Recent developments in evolutionary genomics have contributed towards solving long-standing questions at this interface. Using a comprehensive literature search, we identify studies spanning 19 oceanic archipelagos and 110 putative adaptive radiations, but find that most of these radiations have not yet been investigated from an evolutionary genomics perspective. Our review reveals different gaps in knowledge related to the lack of implementation of genomic approaches, as well as undersampled taxonomic and geographic areas. Filling those gaps with the required data will help to deepen our understanding of adaptation, speciation, and other evolutionary processes.
Subject(s)
Biological Evolution , Genetic Speciation , Phylogeny , Ecology , GenomicsABSTRACT
Current understanding of ecological and evolutionary processes underlying island biodiversity is heavily shaped by empirical data from plants and birds, although arthropods comprise the overwhelming majority of known animal species, and as such can provide key insights into processes governing biodiversity. Novel high throughput sequencing (HTS) approaches are now emerging as powerful tools to overcome limitations in the availability of arthropod biodiversity data, and hence provide insights into these processes. Here, we explored how these tools might be most effectively exploited for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first reviewed the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We considered how this could be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explored how these approaches could be implemented within the framework of an island Genomic Observatories Network (iGON) for the advancement of fundamental and applied understanding of island biodiversity. To this end, we identified seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonized efforts in HTS arthropod inventory could yield significant advances in island biodiversity research.
Subject(s)
Arthropods , Animals , Arthropods/genetics , Biodiversity , Genomics , Plants/genetics , DNA Barcoding, Taxonomic/methods , IslandsABSTRACT
Soils harbour a rich arthropod fauna, but many species are still not formally described (Linnaean shortfall) and the distribution of those already described is poorly understood (Wallacean shortfall). Metabarcoding holds much promise to fill this gap, however, nuclear copies of mitochondrial genes, and other artefacts lead to taxonomic inflation, which compromise the reliability of biodiversity inventories. Here, we explore the potential of a bioinformatic approach to jointly "denoise" and filter nonauthentic mitochondrial sequences from metabarcode reads to obtain reliable soil beetle inventories and address open questions in soil biodiversity research, such as the scale of dispersal constraints in different soil layers. We sampled cloud forest arthropod communities from 49 sites in the Anaga peninsula of Tenerife (Canary Islands). We performed whole organism community DNA (wocDNA) metabarcoding, and built a local reference database with COI barcode sequences of 310 species of Coleoptera for filtering reads and the identification of metabarcoded species. This resulted in reliable haplotype data after considerably reducing nuclear mitochondrial copies and other artefacts. Comparing our results with previous beetle inventories, we found: (i) new species records, potentially representing undescribed species; (ii) new distribution records, and (iii) validated phylogeographic structure when compared with traditional sequencing approaches. Analyses also revealed evidence for higher dispersal constraint within deeper soil beetle communities, compared to those closer to the surface. The combined power of barcoding and metabarcoding contribute to mitigate the important shortfalls associated with soil arthropod diversity data, and thus address unresolved questions for this vast biodiversity fraction.
Subject(s)
Arthropods , Coleoptera , Animals , Coleoptera/genetics , Reproducibility of Results , DNA Barcoding, Taxonomic/methods , Biodiversity , Forests , Arthropods/genetics , SoilABSTRACT
Disentangling the relative role of environmental filtering and spatial processes in driving metacommunity structure across mountainous regions remains challenging, as the way we quantify spatial connectivity in topographically and environmentally heterogeneous landscapes can influence our perception of which process predominates. More empirical data sets are required to account for taxon- and context-dependency, but relevant research in understudied areas is often compromised by the taxonomic impediment. Here we used haplotype-level community DNA metabarcoding, enabled by stringent filtering of amplicon sequence variants (ASVs), to characterize metacommunity structure of soil microarthropod assemblages across a mosaic of five forest habitats on the Troodos mountain range in Cyprus. We found similar ß diversity patterns at ASV and species (OTU, operational taxonomic unit) levels, which pointed to a primary role of habitat filtering resulting in the existence of largely distinct metacommunities linked to different forest types. Within-habitat turnover was correlated to topoclimatic heterogeneity, again emphasizing the role of environmental filtering. However, when integrating landscape matrix information for the highly fragmented Quercus alnifolia habitat, we also detected a major role of spatial isolation determined by patch connectivity, indicating that stochastic and niche-based processes synergistically govern community assembly. Alpha diversity patterns varied between ASV and OTU levels, with OTU richness decreasing with elevation and ASV richness following a longitudinal gradient, potentially reflecting a decline of genetic diversity eastwards due to historical pressures. Our study demonstrates the utility of haplotype-level community metabarcoding for characterizing metacommunity structure of complex assemblages and improving our understanding of biodiversity dynamics across mountainous landscapes worldwide.
Subject(s)
Moths , Soil , Animals , Forests , Ecosystem , BiodiversityABSTRACT
Metazoan metabarcoding is emerging as an essential strategy for inventorying biodiversity, with diverse projects currently generating massive quantities of community-level data. The potential for integrating across such data sets offers new opportunities to better understand biodiversity and how it might respond to global change. However, large-scale syntheses may be compromised if metabarcoding workflows differ from each other. There are ongoing efforts to improve standardization for the reporting of inventory data. However, harmonization at the stage of generating metabarcode data has yet to be addressed. A modular framework for harmonized data generation offers a pathway to navigate the complex structure of terrestrial metazoan biodiversity. Here, through our collective expertise as practitioners, method developers, and researchers leading metabarcoding initiatives to inventory terrestrial biodiversity, we seek to initiate a harmonized framework for metabarcode data generation, with a terrestrial arthropod module. We develop an initial set of submodules covering the 5 main steps of metabarcode data generation: (i) sample acquisition; (ii) sample processing; (iii) DNA extraction; (iv) polymerase chain reaction amplification, library preparation, and sequencing; and (v) DNA sequence and metadata deposition, providing a backbone for a terrestrial arthropod module. To achieve this, we (i) identified key points for harmonization, (ii) reviewed the current state of the art, and (iii) distilled existing knowledge within submodules, thus promoting best practice by providing guidelines and recommendations to reduce the universe of methodological options. We advocate the adoption and further development of the terrestrial arthropod module. We further encourage the development of modules for other biodiversity fractions as an essential step toward large-scale biodiversity synthesis through harmonization.
Subject(s)
Arthropods , Animals , Arthropods/genetics , Biodiversity , DNA Barcoding, Taxonomic , Longitudinal StudiesABSTRACT
Most of our understanding of island diversity comes from the study of aboveground systems, while the patterns and processes of diversification and community assembly for belowground biotas remain poorly understood. Here, we take advantage of a relatively young and dynamic oceanic island to advance our understanding of ecoevolutionary processes driving community assembly within soil mesofauna. Using whole organism community DNA (wocDNA) metabarcoding and the recently developed metaMATE pipeline, we have generated spatially explicit and reliable haplotype-level DNA sequence data for soil mesofaunal assemblages sampled across the four main habitats within the island of Tenerife. Community ecological and metaphylogeographic analyses have been performed at multiple levels of genetic similarity, from haplotypes to species and supraspecific groupings. Broadly consistent patterns of local-scale species richness across different insular habitats have been found, whereas local insular richness is lower than in continental settings. Our results reveal an important role for niche conservatism as a driver of insular community assembly of soil mesofauna, with only limited evidence for habitat shifts promoting diversification. Furthermore, support is found for a fundamental role of habitat in the assembly of soil mesofauna, where habitat specialism is mainly due to colonization and the establishment of preadapted species. Hierarchical patterns of distance decay at the community level and metaphylogeographical analyses support a pattern of geographic structuring over limited spatial scales, from the level of haplotypes through to species and lineages, as expected for taxa with strong dispersal limitations. Our results demonstrate the potential for wocDNA metabarcoding to advance our understanding of biodiversity.
Subject(s)
DNA Barcoding, Taxonomic , Soil , Biodiversity , DNA , Ecosystem , Haplotypes/geneticsABSTRACT
Dispersal ability is known to influence geographical structuring of genetic variation within species, with a direct relationship between low vagility and population genetic structure, which can potentially give rise to allopatric speciation. However, our general understanding of the relationship between dispersal ability, population differentiation and lineage diversification is limited. To address this issue, we sampled mitochondrial DNA variation within lineages of beetles and spiders across the Canary Islands to explore the relationships between dispersal ability, differentiation within lineages and diversification. We found positive relationships between population genetic structure and diversification for both beetles and spiders. Comparisons between dispersive and non-dispersive lineages revealed significant differences for both lineage differentiation and diversification. For both taxa, non-dispersive lineages had stronger population genetic structure. Genus-level endemic species richness and proxies for diversification rate within genera were higher in non-dispersive taxa for both beetles and spiders. Comparisons of average and maximum node divergences within genera suggest that species turnover may be higher in non-dispersive genera. Our results reveal a model where dispersal limitation may shape the diversity of lineages across evolutionary timescales by positively influencing intraspecific and species diversity, moderated by higher extinction rates compared to more dispersive lineages.
Subject(s)
Coleoptera , Spiders , Animals , Biological Evolution , Coleoptera/genetics , Genetic Speciation , Genetic Variation , Genetics, Population , Phylogeny , Spiders/geneticsABSTRACT
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 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.
Subject(s)
Computational Biology , DNA Barcoding, Taxonomic , Animals , Biodiversity , DNA/genetics , DNA Barcoding, Taxonomic/methods , EcologyABSTRACT
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, and 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.
Subject(s)
Arthropods , Biodiversity , Altitude , Animals , Ecosystem , HaplotypesABSTRACT
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.
Subject(s)
Biodiversity , Models, Biological , Biota , Genetic Variation , PhylogenyABSTRACT
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.
ABSTRACT
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.
Subject(s)
Biodiversity , Ecosystem , Animals , Insecta/genetics , Islands , Oceans and Seas , SpainABSTRACT
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 https://github.com/tjcreedy/metamate).
Subject(s)
Artifacts , DNA Barcoding, Taxonomic , DNA, Mitochondrial , Pseudogenes , Animals , DNA, Mitochondrial/genetics , Phylogeny , Reproducibility of Results , Sequence Analysis, DNAABSTRACT
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.