Ecological data in Darwin Core: the case of earthworm surveys.
Ontology highlight
ABSTRACT: Background
This sampling-event dataset provides primary data about species diversity, age structure, abundance (in terms of biomass and density) and seasonal activity of earthworms (Lumbricidae). The study was carried out in old-growth broad-leaved and young forests of two protected areas ("Kaluzhskiye Zaseki" Nature Reserve and Ugra National Park) of Kaluga Oblast (Russia).New information
The published dataset provides new data about earthworm communities in European Russia. We propose a new schema according to Darwin Core for the standardisation of the soil invertebrates survey data.
SUBMITTER: Shashkov M
PROVIDER: S-EPMC8674212 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:We describe an implementation of the Darwin Core Archive (DwC-A) standard that allows for the exchange of biodiversity information contained within the Scratchpads virtual research environment with external collaborators. Using this single archive file Scratchpad users can expose taxonomies, specimen records, species descriptions and a range of other data to a variety of third-party aggregators and tools (currently Encyclopedia of Life, eMonocot Portal, CartoDB, and the Common Data Model) for secondary use. This paper describes our technical approach to dynamically building and validating Darwin Core Archives for the 600+ Scratchpad user communities, which can be used to serve the diverse data needs of all of our content partners.
| S-EPMC3964728 | biostudies-literature
Project description:Darwin Core, the data standard used for sharing modern biodiversity and paleodiversity occurrence records, has previously lacked proper mechanisms for reporting what is known about the estimated age range of specimens from deep time. This has led to data providers putting these data in fields where they cannot easily be found by users, which impedes the reuse and improvement of these data by other researchers. Here we describe the development of the Chronometric Age Extension to Darwin Core, a ratified, community-developed extension that enables the reporting of ages of specimens from deeper time and the evidence supporting these estimates. The extension standardizes reporting about the methods or assays used to determine an age and other critical information like uncertainty. It gives data providers flexibility about the level of detail reported, focusing on the minimum information needed for reuse while still allowing for significant detail if providers have it. Providing a standardized format for reporting these data will make them easier to find and search and enable researchers to pinpoint specimens of interest for data improvement or accumulate more data for broad temporal studies. The Chronometric Age Extension was also the first community-managed vocabulary to undergo the new Biodiversity Informatics Standards (TDWG) review and ratification process, thus providing a blueprint for future Darwin Core extension development.
| S-EPMC9477364 | biostudies-literature
Project description:The present work is part of a process to create a Catalogue of the Freshwater Fishes of Colombia and consisted in the depuration and updating of the taxonomic and geographic components of the checklist of the freshwater fishes of Colombia. An exhaustive revision of the 1435 species recorded in 2008 was necessary to: 1. Add new species described since 2009 and species originally described from Colombia but inadvertently omitted in 2008; 2. Add new records of already described species; 3. Delete species whose presence in Colombia was not supported by voucher specimens in ichthyological collections; and 4. Revise the geographic distribution of the species listed in 2008. This process resulted in the following numbers: 1. Total number of freshwater fish species in Colombia: 1494; 2. Number of species recorded by hydrographic region - Amazon: 706, Orinoco: 663, Caribbean: 223, Magdalena-Cauca: 220, Pacific: 130; and 3. Number of endemic species: 374 (76% from the trans-Andean region). Updating the current checklist is a fundamental requirement to ensure its incorporation in the decision-making process with regard to the conservation of Colombian aquatic species and ecosystems, which are facing transformation processes as a result of activities such as mining, construction of hydroelectric plants, expansion of the agricultural frontier and subsequent deforestation, industrial and domestic pollution, development of waterways, introduction of exotic species, and climate change.
| S-EPMC5674168 | biostudies-literature
Project description:The earthworm gut virome influences the structure and function of the gut microbiome, which in turn influences worm health and ecological functions. However, despite its ecological and soil quality implications, it remains elusive how earthworm intestinal phages respond to different environmental stress, such as soil pollution. Here we used metagenomics and metatranscriptomics to investigate interactions between the worm intestinal phages and their bacteria under different benzo[a]pyrene (BaP) concentrations. Low-level BaP (0.1 mg kg-1) stress stimulated microbial metabolism (1.74-fold to control), and enhanced the antiphage defense system (n = 75) against infection (8 phage-host pairs). Low-level BaP exposure resulted in the highest proportion of lysogenic phages (88%), and prophages expressed auxiliary metabolic genes (AMGs) associated with nutrient transformation (e.g., amino acid metabolism). In contrast, high-level BaP exposure (200 mg kg-1) disrupted microbial metabolism and suppressed the antiphage systems (n = 29), leading to the increase in phage-bacterium association (37 phage-host pairs) and conversion of lysogenic to lytic phages (lysogenic ratio declined to 43%). Despite fluctuating phage-bacterium interactions, phage-encoded AMGs related to microbial antioxidant and pollutant degradation were enriched, apparently to alleviate pollution stress. Overall, these findings expand our knowledge of complex phage-bacterium interactions in pollution-stressed worm guts, and deepen our understanding of the ecological and evolutionary roles of phages.
| S-EPMC10284932 | biostudies-literature
Project description:Many ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or lab is limited. However, an increasing number of works uses digital imagery, which opens opportunities to automatise counting tasks. In this study, we use machine learning to automate counting objects of interest without the need to label individual objects. By leveraging already existing image-level annotations, this approach can also give value to historical data that were collected and annotated over longer time series (typical for many ecological studies), without the aim of deep learning applications. We demonstrate deep learning regression on two fundamentally different counting tasks: (i) daily growth rings from microscopic images of fish otolith (i.e., hearing stone) and (ii) hauled out seals from highly variable aerial imagery. In the otolith images, our deep learning-based regressor yields an RMSE of 3.40 day-rings and an [Formula: see text] of 0.92. Initial performance in the seal images is lower (RMSE of 23.46 seals and [Formula: see text] of 0.72), which can be attributed to a lack of images with a high number of seals in the initial training set, compared to the test set. We then show how to improve performance substantially (RMSE of 19.03 seals and [Formula: see text] of 0.77) by carefully selecting and relabelling just 100 additional training images based on initial model prediction discrepancy. The regression-based approach used here returns accurate counts ([Formula: see text] of 0.92 and 0.77 for the rings and seals, respectively), directly usable in ecological research.
| S-EPMC8636638 | biostudies-literature
Project description:Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.
| S-EPMC8140120 | biostudies-literature
Project description:While the formalization of chronobiology as a scientific discipline occurred in the mid-20th century, the exploration of rhythmic phenomena has a longer history, notably exemplified by De Mairan's observations of Mimosa pudica in darkness in 1729. In this historical narrative, Charles Darwin is known for his investigations into the "sleep movements" of plants. Nevertheless, the complete scope of Darwin's exploration of biological rhythms remains incompletely understood. Through a detailed examination of Darwin's writings, meticulous observations, experiments, and conceptualizations, we unveil a depth of engagement that surpasses his widely acknowledged work on plants, revealing a more extensive interest in and insight into biological rhythms than traditionally recognized.
| S-EPMC11348560 | biostudies-literature
Project description:In many real-world networks, the ability to withstand targeted or global attacks; extinctions; or shocks is vital to the survival of the network itself, and of dependent structures such as economies (for financial networks) or even the planet (for ecosystems). Previous attempts to characterise robustness include nestedness of mutualistic networks or exploration of degree distribution. In this work we present a new approach for characterising the stability and robustness of networks with all-positive interactions by studying the distribution of the k-shell of the underlying network. We find that high occupancy of nodes in the inner and outer k-shells and low occupancy in the middle shells of financial and ecological networks (yielding a "U-shape" in a histogram of k-shell occupancy) provide resilience against both local targeted and global attacks. Investigation of this highly-populated core gives insights into the nature of a network (such as sharp transitions in the core composition of the stock market from a mix of industries to domination by one or two in the mid-1990s) and allow predictions of future network stability, e.g., by monitoring populations of "core" species in an ecosystem or noting when stocks in the core-dominant sector begin to move in lock-step, presaging a dramatic move in the market. Moreover, this "U-shape" recalls core-periphery structure, seen in a wide range of networks including opinion and internet networks, suggesting that the "U-shaped" occupancy histogram and its implications for network health may indeed be universal.
| S-EPMC7042264 | biostudies-literature
Project description:Motivation: Monitoring, assessment and prediction of environmental risks that chemicals pose demand rapid and accurate diagnostic assays. A variety of toxicological effects have been associated with explosive compounds TNT and RDX. One important goal of microarray experiments is to discover novel biomarkers for toxicity evaluation. We have developed an earthworm microarray containing 15,208 unique oligo probes. Our objective was to identify biomarker genes that can separate earthworm samples into three groups: control, TNT-treated, and RDX-treated. Results: We developed a discriminant analysis and cluster (DAC) pipeline to analyze a 248-array dataset. First, a total of 869 significantly changed genes in response to TNT or RDX exposure were inferred by class comparison statistical algorithms. Then, nine decision tree-based algorithms were applied to generate classification rules and a set of 286 classifier genes. These classifier genes were ranked by their overall weight of significance, and were used to build support vector machines (SVMs). An SVM containing all 286 classifier genes had the highest classification accuracy (91.5%). An unsupervised clustering method was used to cluster the worm samples and results show that the use of the top 100 classifier genes can assign the largest number of worm samples into the three reference clusters obtained by using all the 14,188 filtered genes, suggesting that these top-ranked genes may be potential candidates for biomarkers. This study demonstrates that the DAC pipeline can be used to identify a small set of biomarker genes from high dimensional datasets and generate a reliable SVM classification model for multiple classes.
2010-10-08 | GSE18495 | GEO