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BackgroundBroad-scale monitoring of arthropods is often carried out with passive traps (e.g. Malaise traps) that can collect thousands of specimens per sample. The identification of individual specimens requires time and taxonomic expertise, limiting the geographical and temporal scale of research and monitoring studies. DNA metabarcoding of bulk-sample homogenates is faster and has been found to be efficient and reliable, but is destructive and prevents a posteriori validation of species occurrences and/or relative abundances. Non-destructive DNA metabarcoding from the collection medium has been applied in a limited number of studies, but further tests of efficiency are required in a broader range of circumstances to assess the consistency of the method.MethodsWe quantified the detection rate of arthropod species when applying non-destructive DNA metabarcoding with a short (127-bp) fragment of mitochondrial COI on two types of passive traps and collection media: 1) water with monopropylene glycol (H2O–MPG) used in window-flight traps (WFT, 53 in total); 2) ethanol with monopropylene glycol (EtOH–MPG) used in Malaise traps (MT, 27 in total). We then compared our results with those obtained for the same samples using morphological identification (for WFTs) or destructive metabarcoding of bulk homogenate (for MTs). This comparison was applied as part of a larger study of arthropod species richness in silver fir (Abies alba) stands across a range of climate-induced tree dieback levels and forest management strategies.ResultsOf the 53 H2O-MPG samples from WFTs, 16 produced no metabarcoding results, while the remaining 37 samples yielded 77 arthropod MOTUs in total. None of those MOTUs were shared species with the 389 morphological taxa (343 of which were Coleoptera) obtained from the same traps. Metabarcoding of 26 EtOH–MPG samples from MTs detected more arthropod MOTUs (233) and insect orders (11) than destructive metabarcoding of homogenate (146 MOTUs, 8 orders). Arachnida and Collembola were more diverse in EtOH-MPG samples, but Hymenoptera, Coleoptera and Lepidoptera were less represented than in homogenate. Overall, MOTU richness per trap similar for EtOH–MPG (21.81 MOTUs) than for homogenate (32.4 MOTUs). Arthropod communities from EtOH–MPG and homogenate metabarcoding were relatively distinct, with 162 MOTUs (53%) unique to the collection medium and only 71 MOTUs (23%) present in both treatments. Finally, collection medium did not reveal any significant changes in arthropod richness along a disturbance gradient in silver fir forests. We conclude that DNA metabarcoding of collection medium can be used to complement homogenate metabarcoding in inventories to favour the detection of soft-bodied arthropods like spiders.

Mountain forests are increasingly affected by changes in rainfall and pest outbreaks, and the way forests are managed can have direct consequences for the streams flowing through forests. Aquatic macroinvertebrate communities are great bioindicators and changes to their ecosystem likely translates to changes in their overall composition and abundance. The Bavarian Forest National Park (SE Germany) is dominated by the Norway spruce (Picea abies) which, weakened by storms and other stressors, is susceptible to infestation by the European spruce bark beetle (Ips typographus). The result is large scale forest dieback in some areas, and forest management practices that lead to a predominance of three different forest types (hereafter habitats): Intact forest that is healthy and not impacted by Ips typographus; Disturbed forest that was impacted by Ips typographus, left to regenerate naturally, and from which deadwood was not removed; and Salvaged forest that was heavily impacted by Ips typographus with the same consequences, but from which deadwood was removed, creating a treeless forest meadow. Intact forest that is healthy and not impacted by Ips typographus; Disturbed forest that was impacted by Ips typographus, left to regenerate naturally, and from which deadwood was not removed; and Salvaged forest that was heavily impacted by Ips typographus with the same consequences, but from which deadwood was removed, creating a treeless forest meadow. To analyze the impacts these different forest management strategies have on the aquatic insect communities, 30 samples from 11 different streams were taken using kick-sampling. Operational taxonomic units (OTUs) were identified by bulk metabarcoding of dried, ground samples. A mock community was used to verify the setup and a DNA spike-in with three foreign OTUs was added to each sample to measure the biases introduced by PCR amplification and sequencing. Biases varied across samples, but spike-in OTUs produced a pattern indicating predictable biases which could lead to quantifiable metabarcoding results in the future. In total, 260 macroinvertebrate OTUs were identified. In comparison, a morphological study by Bojková et al. (2018) in the same region with twice the number of sampling sites collected 194 taxa in the same month as our samples. This underlines the potential for metabarcoding in evaluating species richness. Species richness was high across all habitats. A significant difference between the forest conditions was detected: The number of detected Diptera OTUs was lowest in disturbed habitats (55) and highest in salvaged areas (73). A permutational multivariate analysis of variance (PERMANOVA) indicated that habitat (i.e., intact, disturbed, salvaged) had an effect on the observed OTU distribution (9.2%), but that the stream catchment had a much larger effect (39.3%) regardless of the habitat. Our findings indicate that forest management can affect stream macroinvertebrate communities, and that this was most pronounced for the Diptera, a group for which DNA metabarcoding is particularly well suited because of their small size and high diversity.

Among the many concerns for biodiversity in the Anthropocene, recent reports of flying insect loss are particularly alarming, given their importance as pollinators and as a food source for many predators. Few insect monitoring programs cover large spatial scales required to provide more generalizable estimates of insect responses to global change drivers.We ask how climate and surrounding habitat affect flying insect biomass and day of peak biomass using data from the first year of a new standardized distributed monitoring network at 84 locations across Germany comprising spatial gradient of land-cover types from protected to urban areas.Flying insect biomass increased linearly with monthly temperature across Germany. However, the effect of temperature on flying insect biomass flipped to negative in the hot months of June and July when local temperatures most exceeded long-term averages.Land-cover explained little variation in insect biomass, but biomass was lowest in forested sites. Grasslands, pastures and orchards harbored the highest insect biomass. The date of peak biomass was primarily driven by surrounding land-cover type, with grasslands especially having earlier insect biomass phenologies.Standardized, large-scale monitoring is pivotal to uncover underlying processes of insect decline and to develop climate-adapted strategies to promote insect diversity. In a temperate climate region, we find that the benefits of temperature on flying insect biomass diminish in a German summer at locations where temperatures most exceeded long-term averages. These results highlighting the importance of local adaptation in climate change-driven impacts on insect communities.

De novo OTU picking from large metabarcoding read datasets is at the same time a current and a complex task, and several methods coexist to perform it. We present here the outcome of a collective project developed within Working Group on « Data Analysis and Storage » in DNAqua.net. Our aim has been to organize a thorough comparison of OTU composition according to some selected methods called by the wrappers, in a diversity of situations. This has been done by disposing of a set of different datasets, and a set of different methods, applying each method on each dataset, and comparing the results. We have deliberately chosen to work with cleaned datasets only, and not to include cleaning in the process. We have worked with a set of about 60 different datasets, some environmental, some as mock communities, produced by six teams, in different countries (D, F, I, T, UK), each with specific markers for different organisms. All datasets have been cleaned beforehand by the team proposing it. We have installed four different tools for building OTUs by unsupervised clustering : Swarm (Mahé et al. 2015), Vsearch (Rognes et al. 2016) with the same receipe for all datasets, usearch (Edgar 2010) with a unique command, the same for all datasets, and yapotu, which computes pairwise Smith-Waterman distances between all reads of a given dataset, and then clusters them with graph based techniques. Yapotu approach is expected to be the most accurate one, as there are no heuristics in the calculations. We have harmonized common input/output format for the four methods, to make comparisons. Here is a summary of the indicators selected for comparing results. We have first computed basic indicators per sample and method, like the number of OTU, the number of singletons, the number of OTUs with ten reads or more (after dereplication), and the fraction of reads that have been allocated to an OTU. The four methods displayed a great variety of counts, with highest number of OTUs and singletons for Swarm, then slighltly equivalent figures (but a smaller number of singletons) for yapotu, and significantly smaller counts for Vsearch and Usearch. However, the counts for the number of OTUs with 10 reads or more are much more convergent between the four methods. We have then compared rank-size curves, which have been computed for all pairs (sample by method). Here again, yapotu and swarm results are very similar, whereas Vsearch and Usearch sometimes are close to the former pattern, sometimes very different (I attach a figure?) We then have computed 10 different diversity indices, like OTU richness, Shannon, Chao, eveness. Here again, results provided by Swarm and Yapotu are very similar, with very strong correlations between indices over all samples by method, whereas the correlations with Vsearch and Usearch is very poor. Finally, we have computed all contingency tables (in a sparse format) between all pairs of methods (hence, 6 pairs) for all samples, which accurately describe whether OTUs composition are similar or dissimilar between methods. We have observed that swarm OTUs are systematically nested within yapotu OTUs, and most often, there is a one to one correspondence between a Swarm and a Yapotu OTU. As a conclusion, we show that - Swarm and yapotu yield very similar results including for fine details, the only diffrence being a larger number of singletons provided by Swarm ; - This shows that Swarm OTUs are very close to OTUs built by single linkage Clustering on Smith-Waterman pairwise distances, and consolidates these approaches. - Very often, both Vsearch and Usearch diverge from those convergent results, but not always, and it is not easy to understand when and why. Some further investigations are needed therefore. All datasets will be publicly available for further benchmarking of a wider set of methods and datasets.

1. Among the many concerns for biodiversity in the Anthropocene, recent reports of flying insect loss are particularly alarming, given their importance as pollinators, pest control agents, and as a food source. Few insect monitoring programmes cover the large spatial scales required to provide more generalizable estimates of insect responses to global change drivers. 2. We ask how climate and surrounding habitat affect flying insect biomass using data from the first year of a new monitoring network at 84 locations across Germany comprising a spatial gradient of land cover types from protected to urban and crop areas. 3. Flying insect biomass increased linearly with temperature across Germany. However, the effect of temperature on flying insect biomass flipped to negative in the hot months of June and July when local temperatures most exceeded long-term averages. 4. Land cover explained little variation in insect biomass, but biomass was lowest in forests. Grasslands, pastures, and orchards harboured the highest insect biomass. The date of peak biomass was primarily driven by surrounding land cover, with grasslands especially having earlier insect biomass phenologies. 5. Standardised, large-scale monitoring provides key insights into the underlying processes of insect decline and is pivotal for the development of climate-adapted strategies to promote insect diversity. In a temperate climate region, we find that the positive effects of temperature on flying insect biomass diminish in a German summer at locations where temperatures most exceeded long-term averages. Our results highlight the importance of local adaptation in climate change-driven impacts on insect communities.

Invasive species pose a major threat to forest biodiversity, particularly on islands, such as the Galapagos. Here, invasive plants are threatening the remnants of the unique cloud forest and its iconic Darwin's finches. We posit that food web disturbances caused by invasive Rubus niveus (blackberry), but also the management measures used to control it, could contribute to the rapid decline of the insectivourous warbler finch (Certhidae olivacea). We compared changes in long-term management, short-term management and unmanaged areas. We measured C:N ratios, δ15N-nitrogen and δ13C-carbon signatures in bird blood and arthropods, as indicators of resource use change, in addition to mass abundance and diversity of arthropods. We reconstructed the bird's diets using isotope mixing models. The results revealed that finches in (Rubus-invaded) unmanaged areas foraged on abundant yet low quality arthropods and had shorter tarsi. Is this the first evidence of hidden hunger in degraded terrestrial ecosystems in Galapagos?

Metabarcoding increases the taxonomic resolution and geographic scale at which researchers can assess the impacts of climate change on insect communities in forests