Find research datasets worth reusing

Using convolutional neural networks to efficiently extract immense phenological data from community science images

Community science image libraries offer a massive, but largely untapped, source of observational data for phenological research. The iNaturalist platform offers a particularly rich archive, containing more than 49 million verifiable, georeferenced, open access images, encompassing seven continents and over 278,000 species. A critical limitation preventing scientists from taking full advantage of this rich data source is labor. Each image must be manually inspected and categorized by phenophase, which is both time-intensive and costly. Consequently, researchers may only be able to use a subset of the total number of images available in the database. While iNaturalist has the potential to yield enough data for high-resolution and spatially extensive studies, it requires more efficient tools for phenological data extraction. A promising solution is automation of the image annotation process using deep learning. Recent innovations in deep learning have made these open-source tools accessible to a general research audience. However, it is unknown whether deep learning tools can accurately and efficiently annotate phenophases in community science images. Here, we train a convolutional neural network (CNN) to annotate images of Alliaria petiolata into distinct phenophases from iNaturalist and compare the performance of the model with non-expert human annotators. We demonstrate that researchers can successfully employ deep learning techniques to extract phenological information from community science images. A CNN classified two-stage phenology (flowering and non-flowering) with 95.9% accuracy and classified four-stage phenology (vegetative, budding, flowering, and fruiting) with 86.4% accuracy. The overall accuracy of the CNN did not differ from humans (p = 0.383), although performance varied across phenophases. We found that a primary challenge of using deep learning for image annotation was not related to the model itself, but instead in the quality of the community science images. Up to 4% of A. petiolata images in iNaturalist were taken from an improper distance, were physically manipulated, or were digitally altered, which limited both human and machine annotators in accurately classifying phenology. Thus, we provide a list of photography guidelines that could be included in community science platforms to inform community scientists in the best practices for creating images that facilitate phenological analysis.

Experimental repatriation of snowshoe hares along a southern range boundary reveals historical community interactions

Climate change is altering interspecific interactions globally, yet community-level responses are difficult to predict due to both the direct and indirect effects of changing abiotic and biotic conditions. Snowshoe hares (Lepus americanus) are particularly vulnerable to decreasing snow cover and resultant camouflage mismatch. This species shares a suite of predators with alternative prey species including porcupines (Erethizon dorsatum) and ruffed grouse (Bonasa umbellus), and all three species historically exhibited synchronized population dynamics. Recently, the community has become partially disassembled, notably with the loss of snowshoe hares and associated enemy-mediated indirect interactions resulting from declining snow duration. Specifically, we hypothesized that the extirpation of hares in the early 1990s indirectly increased predation pressure on ruffed grouse and porcupines. To test our hypothesis, we experimentally translocated 96 snowshoe hares to a site within a regional ecotone between northern and southern forests where snowshoe hares were recently extirpated and monitored community members before, during and after translocation. Ruffed grouse were only loosely associated with the biotic interactions that linked porcupines and snowshoe hares, likely due to predation occurring from avian predators and strong negative direct effects of declining winter snow depths. In contrast, predation of neonate porcupines was virtually non-existent following repatriation, compared to periods without hares. This abrupt attenuation of predation did not increase overall survival due to increased non-predation mortality from cold, early spring weather. Porcupines directly benefitted from warming winters: decreased snow cover increased adult survival and warmer temperatures around parturition increased maternal condition and reduced non-predation causes of mortality for neonates. Our experimental manipulation suggests that enemy-mediated indirect interactions were likely important features of this community; however, climate change has disrupted these interactions, resulting in extirpation of a central prey species (snowshoe hare) and increased predation of an alternative prey species (porcupine). We show complex effects from climate change with some species directly and negatively affected, while others benefitted from direct effects of warming winters, but suffered negative effects from indirect interactions. Absent snowshoe hares and associated biotic interactions, continued persistence of this community module is unlikely, potentially resulting in altered no-analogue communities along trailing edge distributions.

Thermal tolerance in Drosophila: repercussions for distribution, community coexistence and responses to climate change

Here we combined controlled experiments and field surveys to determine if estimates of heat tolerance predict distributional ranges and phenology of different Drosophila species in southern South America. We contrasted thermal death time curves, which consider both magnitude and duration of the challenge to estimate heat tolerance, against the thermal range where populations are viable based on field surveys in an 8-yr longitudinal study. We observed a strong correspondence of the physiological limits, the thermal niche for population growth, and the geographic ranges across studied species, which suggests that the thermal biology of different species provides a common currency to understand how species will respond to warming temperatures both at a local level and throughout their distribution range. Our approach represents a novel analytical toolbox to anticipate how natural communities of ectothermic organisms will respond to global warming.

Semi‐quantitative metabarcoding reveals how climate shapes arthropod community assembly along elevation gradients on Hawaii Island

Spatial variation in climatic conditions along elevation gradients provides an important backdrop by which communities assemble and diversify. Lowland habitats tend to be connected through time, whereas highlands can be continuously or periodically isolated, conditions that have been hypothesized to promote high levels of species endemism. This tendency is expected to be accentuated among taxa that show niche conservatism within a given climatic envelope. While species distribution modeling approaches have allowed extensive exploration of niche conservatism among target taxa, a broad understanding of the phenomenon requires sampling of entire communities. Species-rich groups such as arthropods are ideal case studies for understanding ecological and biodiversity dynamics along elevational gradients given their important functional role in many ecosystems, but community-level studies have been limited due to their tremendous diversity. Here, we develop a novel semi-quantitative metabarcoding approach that combines specimen counts and size-sorting to characterize arthropod community-level diversity patterns along two elevational gradients across two volcanoes on the island of Hawai`i. We find that arthropod communities between the two transects become increasingly distinct compositionally at higher elevations. Resistance surface approaches suggest that climatic differences between sampling localities are an important driver in shaping beta-diversity patterns, though the relative importance of climate varies across taxonomic groups. Nevertheless, the climatic niche position of OTUs between transects was highly correlated, suggesting that climatic filters shape the colonization between adjacent volcanoes. Taken together, our results highlight climatic niche conservatism as an important factor shaping ecological assembly along elevational gradients and suggest topographic complexity as an important driver of diversification.

opencc-by-4.0Jan 2022View details →

Marginalized language communities questionnaire: Summary

This dataset contains the anonymized results of a questionnaire for members of marginalized language communities that aims to study their possibilities of access to recordings in their languages as well as connectivity and communication habits. A slightly different version has been designed for outsider researchers who are in contact with communities. The dataset contains the answers to the questionnaire (in English, Spanish, Russian) by December 27th 2021. The results are arranged in 31 columns, together with a brief summary for each below row 34. Note that row 26 (in grey) is discarded as invalid for our purposes and not included in the summary.

opencc-by-4.0Jan 2022View details →

Comparative analysis of surface sanitization protocols on the bacterial community structures in the hospital environment

In this study, we used 16S rRNA gene sequencing approaches to characterize the bacterial microbiota on different surfaces of the hospital environment. The longitudinal data was then subjected to comprehensive comparisons between different sanitation strategies (disinfectants, detergents and probiotics) to measure their potential effect on the microbial community structures in the hospital environment. This archive contains results and data of the 16S rRNA amplicon sequencing performed on 1019 environmental and 271 patient DNA samples collected over the time course of 40 weeks in a newly opened ward in the neurological station at the Charité Hospital (Berlin). The files include a study information and sample metadata sheets, BIOM-tables and information about the taxonomy results and diversity metrics.

opencc-by-4.0Feb 2022View details →

Viroplant Project - Microcosm studies on the effect of bacteriophages used as plant protection products on soil microbial communities

This file contains the description, data and DNA analyses on the effect of bacteriophages with a potential to be used as plant protecction products on the structure and function of soil microbial communities. The objective was to evaluate two different microcsom incubation systems with phages and microbial cells from soil, or soil itself and to analyses in a time dependent manner how the phages affect the natural soil microbiomes. The microbial communities were quantified with qPCR and their diversity analyzed with PCR amplified 16S rRNA gene sequences. Bioinformatic analyses were used to evaluate microbial community responses

Data from: Data-driven bioregionalization: A seascape-scale study of macrobenthic communities in the Eurasian Arctic

Aim: We conduct the first model-based assessment of the biogeographical subdivision of Eurasian Arctic seas to (1) delineate spatial distribution and boundaries of macrobenthic communities on a seascape level; (2) assess the significance of environmental drivers of macrobenthic community structures; (3) compare our modelling results to historical biogeographical classifications; and (4) couple the model to climate-change scenarios of environmental changes to project potential shifts in the distribution and composition of macrobenthic communities by 2100. Location: Eurasian Arctic seas, in particular Barents, Kara, and Laptev Seas Taxon: Macrobenthic fauna Methods: We employed the Region of Common Profile (RCP) approach to assess the regionalization patterns of Eurasian Arctic seafloor communities. Results: Four RCPs were identified based on the spatial distribution patterns of 169 macrobenthic species and a set of environmental factors, such as sediment composition, sea-ice concentration, depth of the euphotic zone, particulate organic carbon concentration at the ocean surface, as well as near-bottom water temperature and salinity. The identified regions are in strong agreement with previous classifications of macrobenthic communities. The projections are driven by climate-change scenario "Representative Concentration Pathway 6.0" suggested a general eastward shift of the RCPs over the 21st century, correlated to retreating sea-ice and increasing sea-bottom temperature. Main conclusions: The RCP approach allowed us to identify seascape-scale distribution patterns of macrobenthic communities in Eurasian Arctic seas by simultaneously considering biotic and environmental data within one modelling step. This technique can represent biota and ecoregions in a probabilistic form together with assessment of uncertainties of the predictions, and assess the significance of a broad selection of environmental drivers. This first quantitative assessment of potential climate-driven changes in macrobenthic biodiversity will promote their inclusion in conservation measures.

Genome-wide sequence data show no evidence of hybridization and introgression among pollinator wasps associated with a community of Panamanian strangler figs

The specificity of pollinator host choice influences opportunities for reproductive isolation in their host plants. Similarly, host plants can influence opportunities for reproductive isolation in their pollinators. For example, in the fig and fig wasp mutualism, offspring of fig pollinator wasps mate inside the inflorescence that the mothers pollinate. Although often host specific, multiple fig pollinator species are sometimes associated with the same fig species, potentially enabling hybridization between wasp species. Here we study the 19 pollinator species (Pegoscapus spp.) associated with an entire community of 16 Panamanian strangler fig species (Ficus subgenus Urostigma, section Americanae) to determine whether the previously documented history of pollinator host switching and current host sharing predicts genetic admixture among the pollinator species, as has been observed in their host figs. Specifically, we use genome-wide ultraconserved element (UCE) loci to estimate phylogenetic relationships and test for hybridization and introgression among the pollinator species. In all cases, we recover well-delimited pollinator species that contain high interspecific divergence. Even among pairs of pollinator species that currently reproduce within syconia of shared host fig species, we found no evidence of hybridization or introgression. This is in contrast to their host figs, where hybridization and introgression have been detected within this community, and more generally, within figs worldwide. Consistent with general patterns recovered among other obligate pollination mutualisms (e.g., yucca moths and yuccas), our results suggest that while hybridization and introgression are processes operating within the host plants, these processes are relatively unimportant within their associated insect pollinators.

Temperature and nutrient availability alter consequences of phenological shifts in predatory-prey communities

While there is mounting evidence indicating that the relative timing of predator and prey phenologies shapes the outcome of trophic interactions, we still lack a comprehensive understanding of how important the environmental context (e.g. abiotic conditions) is for shaping this relationship. Environmental conditions not only frequently drive shifts in phenologies, but they can also affect the very same processes that mediate the effects of phenological shifts on species interactions. Thus, identifying how environmental conditions shape the effects of phenological shifts is key to predict community dynamics across a heterogenous landscape and how they will change with ongoing climate change in the future. Here I tested how environmental conditions shape effects of phenological shifts by experimentally manipulating temperature, nutrient availability, and relative phenologies in two predator-prey freshwater systems (mole salamander- bronze frog vs dragonfly larvae-leopard frog). This allowed me to (1) isolate the effect of phenological shifts and different environmental conditions, (2) determine how they interact, and (3) how consistent these patterns are across different species and environments. I found that delaying prey arrival dramatically increased predation rates, but these effects were contingent on environmental conditions and predator system. While both nutrient addition and warming significantly enhanced the effect of arrival time, their effect was qualitatively different: Nutrient addition enhanced the positive effect of early arrival while warming enhanced the negative effect of arriving late. Predator responses varied qualitatively across predator-prey systems. Only in the system with strong gape-limitation were predators (salamanders) significantly affected by prey arrival time and this effect varied with environmental context. Correlations between predator and prey demographic rates suggest that this was driven by shifts in initial predator-prey size ratios and a positive feedback between size-specific predation rates and predator growth rates. These results highlight the importance of accounting for temporal and spatial correlation of local environmental conditions and gape-limitation in predator-prey systems when predicting the effects of phenological shifts and climate change on predator-prey systems.

Simple attributes predict the value of plants as hosts to fungal and arthropod communities

Fungal and arthropod consumers constitute the vast majority of global terrestrial biodiversity. Yet, the link from richness and composition of producer (plant) communities to the richness of consumer communities is poorly understood. Fungal and arthropod species richness could be a simple function of producer species richness at a site. Alternatively, it could be a complex function of chemical and structural properties of the producer species making up communities. We used databases on plant-fungus and plant-arthropod trophic links to derive the richness of consumer biota per associated plant species (coined link score). We assessed how well link scores could be predicted by simple attributes of plant species. Next, we used a multi-taxon inventory of 130 sites, representing all major habitat types in a country (Denmark), to investigate whether link scores summed over plant species in communities (coined link sum) could outperform simple plant species richness as predictor of fungal and arthropod richness at the sites. We found plant species' link scores for both fungi and arthropods to be positively related to plant size, regional occupancy, nativeness and ectomycorrhizal status. Link-based indices generally improved the prediction of richness of fungal and arthropod communities. For fungal communities, both observed link sum (from databases) and predicted link sum (from plant attributes) had high predictive power, while plant richness alone had none. For arthropod communities, predictive performance varied between functional groups. For both fungi and arthropods, richness predictions were further improved by considering abiotic habitat conditions. Our results underline the importance of plants as niche space for the megadiverse groups of arthropods and fungi. The plant-attribute approach holds promise for predicting local and regional consumer richness in areas of the world lacking detailed plant-consumer databases.

Imprints of latitude, host taxon and decay stage on fungus-associated arthropod communities

Interactions among fungi and insects involve hundreds of thousands of species. While insect communities on plants have formed some of the classic model systems in ecology, fungus-based communities and the forces structuring them remain poorly studied by comparison. We characterize the arthropod communities associated with fruiting bodies of eight mycorrhizal basidiomycete fungus species from three different orders along a 1200-km latitudinal gradient in northern Europe. We hypothesized that—matching the pattern seen for most insect taxa on plants—we would observe a general decrease of fungal-associated species with latitude. Against this backdrop, we expected local communities to be structured by host identity and phylogeny, with more closely related fungal species sharing more similar communities of associated organisms. As a more unique dimension added by the ephemeral nature of fungal fruiting bodies, we expected further imprints generated by successional change, with younger fruiting bodies harboring communities different from older ones. Using DNA metabarcoding to identify arthropod communities from fungal fruiting bodies, we find that latitude leaves a clear imprint on fungus-associated arthropod community composition, with host phylogeny and decay stage of fruiting bodies leaving lesser but still-detectable effects. The main latitudinal imprint is on a high arthropod species turnover, with no detectable pattern in overall species richness. Overall, these findings paint a new picture of the drivers of fungus-associated arthropod communities, suggesting that latitude will not affect how many arthropod species inhabits a fruiting body, but rather what species occur in it and at what relative abundances (as measured by sequence read counts). These patterns upset simplistic predictions regarding latitudinal gradients in species richness and in the strength of biotic interactions.

opencc-by-4.0Feb 2022View details →

Dataset for Anomaly Detection in a Production Wireless Mesh Community Network

CSV dataset generated gathering data from a production wireless mesh community network. Data is gathered every 5 minutes during the interval 2021-04-13 00:00:00 to 2021-04-16 00:00:00. During the interval 2021-04-14 02:00:00 2021-04-14 17:50:00 (both included) there is the failure of a gateway in the mesh (nodeid 24).  Live mesh network monitoring link: <a href="http://dsg.ac.upc.edu/qmpsu">http://dsg.ac.upc.edu/qmpsu</a> The dataset consists of single gzip compressed CSV file. The first line of the file is a header describing the features. The first column is a GMT timestamp of the sample in the format as "2021-03-16 00:00:00".  The rest of the columns provide the comma-separated values of the features collected from each node in the corresponding capture. A suffix with the nodeid is added to each feature. For instance, the feature having the number of processes of node with nodeid 24 is named as "processes-24". In total, 63 different nodes showed up during the samples, each being assigned a different nodeid. Features are of two types: (i) absolute values, for instance, the CPU 1-minute load average, and (ii) counters that are monotonically increased, for instance the number of transmitted packets. We have converted counter-type kernel variables to rates, by dividing the difference between two consecutive samples, over the difference of the corresponding timestamps in seconds, as shown in the following pseudo-code:   feature.rate are columns computed from feature as     feature.rate <- (feature[2:n]-feature[1:(n-1)])/(epoch[2:n]-epoch[1:(n-1)])     feature.rate <- feature.rate[feature.rate >= 0] # discard samples where the counter is restarted    where n is the number of samples features - processes     number of processes - loadavg.m1     1 minute load average - softirq.rate     servicing softirqs - iowait.rate     waiting for I/O to complete - intr.rate       - system.rate     processes executing in kernel mode - idle.rate     twiddling thumbs - user.rate     normal processes executing in user mode - irq.rate     servicing interrupts - ctxt.rate     total number of context switches across all CPUs - nice.rate     niced processes executing in user mode - nr_slab_unreclaimable     The part of the Slab that can't be reclaimed under memory pressure - nr_anon_pages     anonymous memory pages - swap_cache     Memory that once was swapped out, is swapped back in but still also is in the swapfile - page_tables     Memory used to map between virtual and physical memory addresses - swap       - eth.txe.rate     tx errors over all ethernet interfaces - eth.rxe.rate     rx errors over all ethernet interfaces - eth.txb.rate     tx bytes over all ethernet interfaces - eth.rxb.rate     rx bytes over all ethernet interfaces - eth.txp.rate     tx packets over all ethernet interfaces - eth.rxp.rate     rx packets over all ethernet interfaces - wifi.txe.rate     tx errors over all wireless interfaces - wifi.rxe.rate     rx errors over all wireless interfaces - wifi.txb.rate     tx bytes over all wireless interfaces - wifi.rxb.rate     rx bytes over all wireless interfaces - wifi.txp.rate     tx packets over all wireless interfaces - wifi.rxp.rate     rx packets over all wireless interfaces - txb.rate        tx bytes over all ethernet and wifi interfaces - txp.rate        tx packets over all ethernet and wifi interfaces - rxb.rate        rx bytes over all ethernet and wifi interfaces - rxp.rate        rx packets over all ethernet and wifi interfaces - sum.xb.rate    tx+rx bytes over all ethernet and wifi interfaces - sum.xp.rate    tx+rx packets over all ethernet and wifi interfaces - diff.xb.rate      tx-rx bytes over all ethernet and wifi interfaces - diff.xp.rate      tx-rx packets over all ethernet and wifi interfaces

Data from: Metabarcoding of soil environmental DNA replicates plant community variation but not specificity

<blockquote> While metabarcoding of plant DNA from their environment is an exciting method that can supplement inventorying of live plant species, the accuracy and specificity has yet to be fully assessed over complex continuous landscapes. In this work, we evaluate plant community profiles produced via metabarcoding of soil by comparing them to a morphological survey. We assessed plant communities by metabarcoding of soil DNA in 130 sites along ecological gradients (nutrients, succession, moisture) in Denmark using chloroplast trnL region (10-143 bp) primer set and compared the resulting communities to communities produced with a longer nuclear ITS2 region (~216 bp) and a morphological survey. We found that the community variation observed within the morphological survey was well represented by molecular surveys, with significant correlation with both community composition and richness using both primer sets. While the majority of the ITS2 sequences could be assigned to species (over 80%), we had less success with the trnL sequences (70%), which was only possible after restricting the reference database to local species. We conclude that the community profiles produced by metabarcoding can be highly effective in performing large-scale macroecological studies. However, the discovery rates and taxonomic assignments produced via metabarcoding remained inferior to morphological surveys, but manual curation of databases improves the specificity of assignments made by the trnL primers, and improves the accuracy of the assignments made with the ITS2 primers. Finally, we suggest that a greater percentage of named diversity would be recovered by increasing soil sampling with the use of additional universal primer sets. </blockquote>

opencc-by-4.0Mar 2022View details →

Local communities' perceptions of wild edible plant and mushroom change: A systematic review

These datasets are the basis of publication "Local communities’ perceptions of wild edible plant and mushroom change: A systematic review", DOI: https://doi.org/10.1016/j.gfs.2021.100601 File GFS_paperIDs.csv lists the articles that are included in the systematic review with their identification numbers. File GFS_data_papers.csv contains data related to the articles reporting on changes of wild edible plants. File GFS_data_plants.csv contains data related to the plant species that are affected by the changes. File GFS_variable_desriptions.txt informs about the variables in files GFS_data_papers.csv and GFS_data_plants.csv.

opencc-by-4.0Mar 2022View details →

Food web rewiring drives long-term compositional differences and late-disturbance interactions at the community level

Abstract Ecological communities are constantly exposed to multiple natural and anthropogenic disturbances. Multivariate composition (if recovered) has been found to need significantly more time to be regained after pulsed disturbance compared to univariate diversity metrics and functional endpoints. However, the mechanisms driving the different recovery times of communities to single and multiple disturbances remain unexplored. Here, we apply for the first time quantitative ecological network analyses to try to elucidate the mechanisms driving long-term community composition dissimilarity and late-stage disturbance interactions at the community level. For this, we evaluate the effects of two pesticides, nutrients enrichment and their interactions in outdoor mesocosms containing a complex freshwater community. We found changes in interactions strength to be strongly related to compositional changes and identified post-disturbance interaction strength rewiring to be responsible for most of the observed compositional changes. Additionally, we found pesticides interactions to be significant in the long term only when both interactions strength and food web architecture are reshaped by the disturbances. We suggest that quantitative network analysis has the potential to unveil ecological processes that prevent long-term community recovery. Significance Statement Multiple anthropogenic disturbances affect the structure and functioning of communities. Recent evidence highlighted that, after pulse disturbance, the functioning a community performs may be recovered fast due to functional redundancy, whereas community multivariate composition needs longer time. Yet, the mechanisms that drive the different community recovery times have not been quantified empirically. We use quantitative food web analysis to assess the influence of species interactions on community recovery. We found species interactions strength to be the main mechanism driving differences between structural and functional recovery. Additionally, we show that interactions between multiple disturbances appear in the long term only when both species interaction strength and food web architecture change significantly. Please see the "readme" sheet in the datafile for a description of the file structure and treatments abreviations.

opencc-zeroMar 2022View details →

SSP: An R package to estimate sampling effort in studies of ecological communities

SSP (simulation-based sampling protocol) is an R package that uses simulations of ecological data and dissimilarity-based multivariate standard error (MultSE) as an estimator of precision to evaluate the adequacy of different sampling efforts for studies that will test hypothesis using permutational multivariate analysis of variance. The procedure consists in simulating several extensive data matrixes that mimic some of the relevant ecological features of the community of interest using a pilot data set. For each simulated data, several sampling efforts are repeatedly executed and MultSE calculated. The mean value, 0.025 and 0.975 quantiles of MultSE for each sampling effort across all simulated data are then estimated and standardized regarding the lowest sampling effort. The optimal sampling effort is identified as that in which the increase in sampling effort does not improve the highest MultSE beyond a threshold value (e.g. 2.5 %). The performance of SSP was validated using real data. In all three cases, the simulated data mimicked the real data and allowed to evaluate the relationship MultSE – n beyond the sampling size of the pilot studies. SSP can be used to estimate sample size in a wide variety of situations, ranging from simple (e.g. single site) to more complex (e.g. several sites for different habitats) experimental designs. The latter constitutes an important advantage in the context of multi-scale studies in ecology. An online version of SSP is available for users without an R background.

opencc-by-4.0Mar 2022View details →

Data for manuscript: Ecological lags govern the pace and outcome of plant community responses to 21st century climate change

These data were used in the analyses reported in Block et al. "Ecological lags govern the pace and outcome of plant community responses to 21st century climate change".

opencc-zeroMar 2022View details →

Oral bacteria from a community-based generation study RHINESSA in Bergen, Norway

The oral cavity is the main gateway for oral bacteria and their components to enter the lungs. Disruption of the oral microbiota due to internal or external factors has been associated with respiratory diseases. This dataset is used to explore the association between oral bacteria, lung function, and lung inflammation in a generally healthy community-based generation study RHINESSA in Bergen, Norway. Study-specific metadata can be found in respective research articles linked to this dataset.