Research Dataset Catalog and ShareScore Ratings | ScienceDex

zenodo44/100

Sampling metadata for the publication: "Deep-sea sponge derived environmental DNA analysis reveals demersal fish biodiversity of a remote Arctic ecosystem "

Meta data of sampling location, time and depth of eDNA samples used in the study: "Deep-sea sponge derived environmental DNA analysis reveals demersal fish biodiversity of a remote Arctic ecosystem". As well as taxonomic identification of sponges, their microbial abundance and growth form.

opencc-by-4.0Nov 2022View details →

zenodo40/100

A Gridded Microclimate Dataset from a Sub-Arctic Biodiversity Hotspot in Finland

The dataset comprises 63 spatially continuous microclimate surfaces for the Kilpisjärvi region in northwestern Finland. The study region is a biodiversity hotspot for arctic-alpine flora and fauna and one of the most extensively investigated regions in Northern Europe. The data were gathered through a collaborative network of microclimate loggers, encompassing 430 measurement locations that comprehensively cover the 300 km2 landscape under study. We employed predominantly well-performing Random Forest models to project microclimate variables across the study area at a 3-metre spatial resolution.

opencc-by-4.0Mar 2024View details →

dryad36/100

Data from: Proteomic fingerprinting enables quantitative biodiversity assessments of species and ontogenetic stages in Calanus congeners (Copepoda, Crustacea) from the Arctic Ocean

Species identification is pivotal in biodiversity assessments, and proteomic fingerprinting by MALDI-TOF mass spectrometry has already been shown to reliably identify calanoid copepods to species level. However, MALDI-TOF data may contain more information beyond mere species identification. In this study, we investigated different ontogenetic stages (copepodids C1-C6 females) of three co-occurring Calanus species from the Arctic Fram Strait, which cannot be identified to species level based on morphological characters alone. Differentiation of the three species based on mass spectrometry data was without any error. In addition, a clear stage-specific signal was detected in all species, supported by clustering approaches as well as machine learning using Random Forest. More complex mass spectra in later ontogenetic stages as well as relative intensities of certain mass peaks were found as the main drivers of stage distinction in these species. Through a dilution series, we were able to show that this did not result from the higher amount of biomass that was used in tissue processing of the larger stages. Finally, the data were tested in a simulation for application in a real biodiversity assessment by using Random Forest for stage classification of specimens absent from the training data. This resulted in a successful stage-identification rate of almost 90%, making proteomic fingerprinting a promising tool to investigate polewards shifts of Atlantic Calanus species and, in general, to assess stage compositions in biodiversity assessments of Calanoida, which can be notoriously difficult using conventional identification methods.

opencc-zeroSep 2022View details →

zenodo36/100

Arctic Biodiversity: Arctic Algae

Biogeography and other attributes for Arctic organisms, various sources.algal distribution records for the Arctic, various sources