<p>The dataset contains data on arthropods which was derived from DNA metabarcoding. The DNA metabarcoding was performed for samples from coloured canopy Malaise traps, caterpillar traps, branch sampling and blue and white pan traps. The traps were selected to capture predominantly flying insects, especially butterflies and hoverflies. They were placed as a defined set in four different habitat types: 'Forest (Beech and oak)', 'Centre of a short rotation coppice', 'Margin of a short rotation coppice' and 'Maize field'. There existed three replicates of each habitat type. The coloured canopy Malaise traps were equipped with blue, yellow and white cotton cloth panels (50 x 35 cm) and hung in a wooden frame four metres above ground. The caterpillar traps consisted of a dark-green plastic tarpaulin, which was stretched between trees and tapered towards the ground. At its lowest point, insects were collected with a capture bottle, which was attached to the tarpoulin with a fine gauze. The branch sampling was conducted by tabbing 100 tree branches and shaking ten trees at each site. In the corn fields, the shaking was replaced by another interval of tabbing. The blue and white pan traps were placed next to each other on a wooden table, one metre above ground. The pans were enlarged at the top with fine gauze to prevent from overfloating in the case of rain. All insects were captured and stored in 96.6% ethanol. The traps were operated in 15-day sampling intervals, each in June, July and August 2021. For DNA metabarcoding, the samples of each sampling interval and method were compiled. The DNA metabarcoding was performed following the method of Hausmann et al (2020): 'Toward a standardized quantitative and qualitative insect monitoring scheme. Ecology and Evolution, 10, 4009–4020'. Briefly, a lysis volume of 5-10 ml of the dried and homogenized composite samples was used for DNA extraction. The mitochondrial Cytochrome c Oxidase subunit I gene (COI) was amplified for species identification (see Leray et al. (2013): 'A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Frontiers in Zoology, 10, 34' and Morinière et al. (2016): 'Species Identification in Malaise Trap Samples by DNA Barcoding Based on NGS Technologies and a Scoring Matrix. PLOS ONE, 11, e0155497'. The resulting metabarcoding data contains the OTU sequences from the samples and their corresponding identities from the Barcode of Life database (BOLD, Ratnasingham and Hebert 2007), the database of the National Center for Biotechnology Information (NCBI) and the Ribosomal Database Project (RDP) classifier. For the two databases, the overlap between the OTU sequence and the database entry determined the determination depth (97-100%: species, 95-97%: genus; 90-95%. family, 85-90%: order, 80-85%: class, 75-80%: phylum, <75%: domain). Each taxonomic determination level of the RDP-classifier is additionally displayed with a bootstrap value. The table also provides data on the red list Germany and Bavaria for each entry.</p><p>The dataset is used in: Hoffmann, L. & Stoll, S. (2025) Catch effectiveness, complementarity and costs of five sampling techniques for flying insects across different land use types. Insect Conservation and Diversity, 1–12. Available from: https://doi.org/10.1111/icad.12839</p>
<p>The dataset comprises presence data of arthropods, but also on the groups 'Annelida', 'Bacillariophyta', 'Ascomycota', 'Basidiomycota', 'Bryozoa', 'Chordata', 'Cnidaria', 'Echinodermata', 'Glomeromycota', 'Haptophyta', 'Mollusca', 'Mucoromycota', 'Nematoda', 'Nemertea', 'Ochrophyta', 'Oomycota', 'Porifera', 'Pseudomonadota', 'Rhodophyta', 'Rotifera' and 'Tardigrada'. The arthropods were collected in four different life stages of short rotation coppices (harvested, young (2 years), mature (3 years) and old (4 years)) using 3 different trapping techniques: branch sampling (BS), coloured canopy Malaise traps (MT) and pitfall traps (PIT). In each life stage, three sets of traps were placed (3 sites per life stage) and activated for two weeks, each in May, June, July and August. Once in a month, a branch sampling was conducted. In the branch sampling, 16 trees within a radius of 20m around the canopy Malaise traps were randomly selected and shaken for 10 s. Arthropods fell on a plastic tarpaulin of 1x1 m that was emptied into a collection bottle where the arthropods were stored in 96.7% ethanol.</p><p>The samples were analysed using DNA metabarcoding. In DNA metabarcoding, the Cytochrome Oxidase I-Region was targeted using the primers fwhF2 (forward) and fwhR2n (reverse) from Vamos et al 2017 (https://doi.org/10.3897/mbmg.1.14625) The sequences found in the samples were matched with sequences in the BOLD database. The sequences displayed are already grouped like it is known from OTUs. For this grouping, all sequences with a similarity of 97% were compiled, which means that the grouped sequences finally comprise different genetic variants of the same taxa. For each hit in the database, a plausibility check was performed by comparing the distribution range of a species (calculated from GBIF coordinates) and the trapping locations. For each detection of a sequence in a sample, the number of reads is also given. A flagging system helps the user to estimate the degree of uncertainty arising from each species hit.</p><p>This data and the data in the datasets "https://doi.org/10.15468/9pzhm6" and "https://doi.org/10.15468/9pzhm6" belongs to one study.</p>
<p>The dataset comprises presence data on arthropods, but also on the groups 'Annelida', 'Ascomycota', 'Basidiomycota', 'Mollusca', 'Mucoromycota', 'Nematoda' and 'Proteobacteria'. For each detection of an Observational Taxonomic Unit (OTU), the number of reads is also given, as well as further information about the species assigned. The species information was derived from a comparison of the detected DNA sequences with the BOLD database and the database of the National Center for Biotechnology Information (NCBI). Further, the Ribosomal Database Project (RDP) classifier was used to identify species. A consensus taxonomy compiles the species information dervied from the different databases and ranks the results according to their validity by using labels from A to C (Information on A, B, and C given at the description of the variables). The DNA metabarcoding process is decribed in detail in Uhler et al (2021): Relationship of insect biomass and richness with land use along a climate gradient (https://www.nature.com/articles/s41467-021-26181-3#Sec10 ). Since the samples were devided into large and small subsamples to improve the metabarcoding results, the data is given for each of the subsamples separately. The samples that went through DNA metabarcoding were derived from a Malaise trap experiment, for which five different types of Malaise traps were placed on a meadow and a forest clearing site each in three regions of southwest Germany (Nationalpark Hunsrück-Hochwald, Rhine-Main-Observatory, Steigerwald). The sites in the Hunsrück and the Rhine-Main-Observatory are part of the Long-term Ecological Research Network Germany (LTER-D). </p>
<p>Biological invasions are a major challenge for natural systems in the Anthropocene, yet their underlying dynamics often remain insufficiently understood. This project establishes Johnstone’s Whistling Frog (Eleutherodactylus johnstonei) as a new alien amphibian model and reevaluates long-held assumptions about invasion processes and patterns. Native to a small Lesser Antillean island, E. johnstonei has achieved an unexpectedly broad exotic distribution. By integrating ecological, genetic, and microbiome perspectives, this work reveals that the species’ invasion success is driven less by intrinsic biological superiority and more by its compatibility with human-dominated environments.Field surveys conducted 25 years after the frog’s introduction to Colombia demonstrate that its distribution remains tightly associated with urban habitats and their characteristic environmental conditions. Comparative genetic analyses across E. johnstonei, its successful alien congener E. antillensis, and the island endemic E. portoricensis show consistently low genetic diversity in both native and exotic populations, indicating that genetic impoverishment does not preclude invasion success. Instead, species distribution models highlight human footprint as a key predictor of the frog’s wide exotic range. Furthermore, microbiome analyses reveal distinct microbial communities between native and introduced populations, suggesting that microbial restructuring accompanies range expansion and may reflect underlying adaptive or transfer processes.Together, these findings challenge conventional invasion theory by illustrating that islands can act as sources instead of sinks and that species with low genetic diversity can thrive across continents when human-mediated disturbances create favorable conditions. The study argues that conservation strategies should prioritize protecting native habitats over targeting adaptable alien species that succeed largely because of anthropogenic change. More broadly, it calls for a rethinking of "nativeness" in an era of rapid environmental transformation and underscores that the resilience of both macro- and micro-communities - rather than species origin - will shape biodiversity outcomes in the Anthropocene.</p>
<p>Examination of metabarcoding plant DNA traces from Malaise trap samples. A dataset of 79 samples from 21 sites in Germany was analyzed using the ITS2 barcode. This study is part of the project DINA (Diversity of insects in Nature Reserves) to study insect communities in 21 nature reserves in Germany.</p>
This data set contains occurrence data of the Western Tragopan (Tragopan melanocephalus) from a field survey in the Palas Valley, Pakistan. Numbers of calling individuals were counted during a standardized call count survey at 23 survey sites during the breeding season in April and May 2017 and 2018. Absence data at survey sites with no observations at a given day are also reported. Along with data from call count surveys we provide single point occurrences from transect walks in May and November 2019 (all sightings were counted, one occurrence refers to one individual).
<p>During 23 years, 3 institutions sampled fish in the Belgian part of the river Meuse with two distincts methodologies.</p> <p>Data were provided by the survey of fish passages in fish ladders at Tailfer (upstream Namur) and Lixhe (downstream Liège) over the 1989-2011 period (Matondo & Ovidio 2016). Fish were collected daily in a trap placed in the upper pool of the ladder when the migration peaks occurred, and twice a week outside the major migration period. All the fish species were identified and species abundances were estimated without taking into account the juveniles and the youngs-of-the-year. Annual fish abundances were expressed as monthly averages.</p> <p>Data from Hastière, Andenne and Visé were provided by electrofishing from a boat along the banks in 1994, 2007, 2008, 2009 and 2010. Abundances were expressed as number of individuals by 100m² of river sampled.</p>
Samples of Crustacea, Polychaeta and Sipuncula were collected in the Bering Sea and the Northwest Pacific Ocean during the BERING expedition (SO-249) on board of RV Sonne in 2016. Biological samples were collected using a dredge at depths ranging between 330–5070 m at 32 locations and were stored in 70% ethanol. Specimens were morphologically identified to the lowest taxonomic rank possible using a Leica M60 stereomicroscope. The presented data here comprises taxonomic information as well as annotated bathymetric and biogeographic metadata of a total of 78 samples (26 Crustacea, 47 Polychaeta, 4 Sipuncula and 1 Hirudinea). All data was prepared following Darwin Core Biodiversity standards for FAIR data sharing based on OBIS guidelines.
Collection data of terrestrial Mollusca from the 2019 VIETBIO inventory work in Cuc Phuong National Park, Vietnam.
<p>The B-BLOOMS2 dataset resulted from the monitoring of 4 Belgian reference lakes during the bloom seasons in 2007 and 2008. It is composed of 278 sample events for which 17 environmental parameters are available, as well as HPLC based pigment analysis, zooplankton counting, proportion of cyanobacterial populations (from genus to species), and MC-LR concentrations determined by ELISA. Molecular data acquired during this project are also available (http://hdl.handle.net/2268/213145). </p><p>These data were acquired with the financial support of BELSPO in the frame of the Science for a Sustainable Development programme funding the project B-BLOOMS2 (SD/TE/01). The final report is available at: http://www.bblooms.be/BBLOOMS2_FinalReport.pdf</p>
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