Toward global integration of biodiversity big data: a harmonized metabarcode data generation module for terrestrial arthropods

Three steps towards comparability and standardization among molecular methods for characterizing insect communities

Molecular methods are currently some of the best-suited technologies for implementation in insect monitoring. However, the field is developing rapidly and lacks agreement on methodology or community standards. To apply DNA-based methods in large-scale monitoring, and to gain insight across commensurate data, we need easy-to-implement standards that improve data comparability. Here, we provide three recommendations for how to improve and harmonize efforts in biodiversity assessment and monitoring via metabarcoding: (i) we should adopt the use of synthetic spike-ins, which will act as positive controls and internal standards; (ii) we should consider using several markers through a multiplex polymerase chain reaction (PCR) approach; and (iii) we should commit to the publication and transparency of all protocol-associated metadata in a standardized fashion. For (i), we provide a ready-to-use recipe for synthetic cytochrome c oxidase spike-ins, which enable between-sample comparisons. For (ii), we propose two gene regions for the implementation of multiplex PCR approaches, thereby achieving a more comprehensive community description. For (iii), we offer guidelines for transparent and unified reporting of field, wet-laboratory and dry-laboratory procedures, as a key to making comparisons between studies. Together, we feel that these three advances will result in joint quality and calibration standards rather than the current laboratory-specific proof of concepts. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Global contribution of invertebrates to forest litter decomposition

Forest litter decomposition is an essential component of global carbon and nutrient turnover. Invertebrates play important roles in litter decomposition, but the regional pattern of their effects is poorly understood. We examined 476 case studies across 93 sites and performed a meta-analysis to estimate regional effects of invertebrates on forest litter decomposition. We then assessed how invertebrate diversity, climate and soil pH drive regional variations in invertebrate-mediated decomposition. We found that (1) invertebrate contributions to litter decomposition are 1.4 times higher in tropical and subtropical forests than in forests elsewhere, with an overall contribution of 31% to global forest litter decomposition; and (2) termite diversity, together with warm, humid and acidic environments in the tropics and subtropics are positively associated with forest litter decomposition by invertebrates. Our results demonstrate the significant difference in invertebrate effects on mediating forest litter decomposition among regions. We demonstrate, also, the significance of termites in driving litter mass loss in the tropics and subtropics. These results are particularly pertinent in the tropics and subtropics where climate change and human disturbance threaten invertebrate biodiversity and the ecosystem services it provides.

Plant-derived environmental DNA complements diversity estimates from traditional arthropod monitoring methods but outperforms them detecting plant-arthropod interactions

Our limited knowledge about the ecological drivers of global arthropod decline highlights the urgent need for more effective biodiversity monitoring approaches. Monitoring of arthropods is commonly performed using passive trapping devices, which reliably recover diverse communities, but provide little ecological information on the sampled taxa. Especially the manifold interactions of arthropods with plants are barely understood. A promising strategy to overcome this shortfall is environmental DNA (eDNA) metabarcoding from plant material on which arthropods leave DNA traces through direct or indirect interactions. However, the accuracy of this approach has not been sufficiently tested. In four experiments, we exhaustively test the comparative performance of plant-derived eDNA from surface washes of plants and homogenized plant material against traditional monitoring approaches. We show that the recovered communities of plant-derived eDNA and traditional approaches only partly overlap, with eDNA recovering various additional taxa. This suggests eDNA as a useful complementary tool to traditional monitoring. Despite the differences in recovered taxa, estimates of community α- and β-diversity between both approaches are well correlated, highlighting the utility of eDNA as a broad scale tool for community monitoring. Last, eDNA outperforms traditional approaches in the recovery of plant-specific arthropod communities. Unlike traditional monitoring, eDNA revealed fine-scale community differentiation between individual plants and even within plant compartments. Especially specialized herbivores are better recovered with eDNA. Our results highlight the value of plant-derived eDNA analysis for large-scale biodiversity assessments that include information about community-level interactions.

Towards a Canary Islands barcode database for soil biodiversity: revealing cryptic and unrecorded mite species diversity within insular soils

Soil arthropod diversity contributes to a high proportion of the total biodiversity on Earth. However, most soil arthropods are still undescribed, hindering our understanding of soil functioning and global biodiversity estimations. Inventorying soil arthropods using conventional taxonomical approaches is particularly difficult and costly due to the great species richness, abundance and local-scale heterogeneity of mesofauna communities and the poor taxonomic background knowledge of most lineages. To alleviate this situation, we have designed and implemented a molecular barcoding framework adapted to soil fauna. This pipeline includes different steps, starting with a morphology-based selection of specimens which are imaged. Then, DNA is extracted non-destructively. Both images and voucher specimens are used to assign a taxonomic identification, based on morphology that is further checked for consistency with molecular information. Using this procedure, we studied 239 specimens of mites from the Canary Islands including representatives of Mesostigmata, Sarcoptiformes and Trombidiformes, of which we recovered barcode sequences for 168 specimens that were morphologically identified to 49 species, with nine specimens that could only be identified at the genus or family levels. Multiple species delimitation analyses were run to compare molecular delimitations with morphological identifications, including ASAP, mlPTP, BINs and 3% and 8% genetic distance thresholds. Additionally, a species-level search was carried out at the Biodiversity Databank of the Canary Islands (BIOTA) to evaluate the number of species in our dataset that were not previously recorded in the archipelago. In parallel, a sequence-level search of our sequences was performed against BOLD Systems. Our results reveal that multiple morphologically identified species correspond to different molecular lineages, which points to significant levels of unknown cryptic diversity within the archipelago. In addition, we evidenced that multiple species in our dataset constituted new records for the Canary Islands fauna and that the information for these lineages within online genetic repositories is very incomplete. Our study represents the first systematic effort to catalogue the soil arthropod mesofauna of the Canary Islands and establishes the basis for the Canary Islands Soil Biodiversity barcode database. This resource will constitute a step forward in the knowledge of these arthropods in a region of special interest.

Inferring the ecological and evolutionary determinants of community genetic diversity

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.

Collective and harmonized high throughput barcoding of insular arthropod biodiversity: Toward a Genomic Observatories Network for islands

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.

Dynamics of species-rich predator-prey networks and seasonal alternations of core species

In nature, entangled webs of predator-prey interactions constitute the backbones of ecosystems. Uncovering the network architecture of such trophic interactions has been recognized as the essential step for exploring species with great impacts on ecosystem-level phenomena and functions. However, it has remained a major challenge to reveal how species-rich networks of predator-prey interactions are continually reshaped through time in the wild. Here, we show that dynamics of species-rich predator-prey interactions can be characterized by remarkable network structural changes and alternations of species with greatest impacts on community processes. On the basis of high-throughput detection of prey DNA from 1,556 spider individuals collected in a grassland ecosystem, we reconstructed dynamics of interaction networks involving, in total, 50 spider species and 974 prey species and strains through 8 months. The networks were compartmentalized into modules (groups) of closely interacting predators and prey in each month. Those modules differed in detritus/grazing food chain properties, forming complex fission-fusion dynamics of belowground and aboveground energy channels across the seasons. The substantial shifts of network structure entailed alternations of spider species located at the core positions within the entangled webs of interactions. These results indicate that knowledge of dynamically shifting food webs is crucial for understanding temporally varying roles of 'core species' in ecosystem processes.

Arthropods are kin: Operationalizing Indigenous data sovereignty to respectfully utilize genomic data from Indigenous lands

Indigenous peoples have cultivated biodiverse agroecosystems since time immemorial. The rise of metagenomics and high-throughput sequencing technologies in biodiversity studies has rapidly expanded the scale of data collection from these lands. A respectful approach to the data life cycle grounded in the sovereignty of indigenous communities is imperative to not perpetuate harm. In this paper, we operationalize an indigenous data sovereignty (IDS) framework to outline realistic considerations for genomic data that span data collection, governance, and communication. As a case study for this framework, we use arthropod genomic data collected from diversified and simplified farm sites close to and far from natural habitats within a historic Kānaka 'Ōiwi (Indigenous Hawaiian) agroecosystem. Diversified sites had the highest Operational Taxonomic Unit (OTU) richness for native and introduced arthropods. There may be a significant spillover effect between forest and farm sites, as farm sites near a natural habitat had higher OTU richness than those farther away. We also provide evidence that management factors such as the number of Polynesian crops cultivated may drive arthropod community composition. Through this case study, we emphasize the context-dependent opportunities and challenges for operationalizing IDS by utilizing participatory research methods, expanding novel data management tools through the Local Contexts Hub, and developing and nurturing community partnerships-all while highlighting the potential of agroecosystems for arthropod conservation. Overall, the workflow and the example presented here can help researchers take tangible steps to achieve IDS, which often seems elusive with the expanding use of genomic data.

Future of DNA-based insect monitoring

Insects are crucial for ecosystem health but climate change and pesticide use are driving massive insect decline. To mitigate this loss, we need new and effective monitoring techniques. Over the past decade there has been a shift to DNA-based techniques. We describe key emerging techniques for sample collection. We suggest that the selection of tools should be broadened, and that DNA-based insect monitoring data need to be integrated more rapidly into policymaking. We argue that there are four key areas for advancement, including the generation of more complete DNA barcode databases to interpret molecular data, standardisation of molecular methods, scaling up of monitoring efforts, and integrating molecular tools with other technologies that allow continuous, passive monitoring based on images and/or laser imaging, detection, and ranging (LIDAR).