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LifeWatch ERIC Service Centre

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  • To address the today’s ecological challenges, it is necessary to use data coming from different disciplines and providers. Discovery and integration of data, especially from the ecological domain, is highly labour-intensive and often ambiguous in semantic terms. To improve the location, interpretation and integration of data based on its inherent meaning vocabularies can help in harmonizing and enriching descriptions of data, providing a formal mechanism for the definition of terms and their relationships. To satisfy these emerging needs LifeWatch ERIC developed a Semantic Resources Catalogue (EcoPortal) focused on the Biodiversity and Ecosystem Research. This effort will help to support the community in the management and integration/alignment of their semantics and subsequently also of their data. The main goal of the EcoPortal initiative is to provide a unique platform for vocabularies in the ecological and domain for different kinds of stakeholders.

  • TITAN comprises a well-grounded stack of Big Data technologies including Apache Kafka for inter-component communication, Apache Avro for data serialisation and Apache Spark for data analytics. Furthermore, DRAMA framework is the underlying workflow orchestrator engine used by TITAN.

  • The LifeWatch Italy national node has realised the Phytoplankton Virtual Research Environment (Phyto VRE) for supporting researchers to address basic and applied studies on phytoplankton ecology at a level of resolution going from individual cells to whole assemblages. The Phyto VRE enables researchers to: - produce harmonised data on taxonomy and morphological traits by using the Atlas of Phytoplankton, Atlas of Shapes and Phytoplankton Traits Thesaurus; - access, download, and select LifeWatch Italy datasets (published through the LifeWatch Italy Data Portal and distributed by the LifeWatch ERIC Metadata Catalogue) or upload their own datasets structured according to the Phyto template based on the LifeWatch Italy Data Schema in order to execute the services included in the VRE; - faciliatate the computation of morphological and demographic traits (such as hidden dimension, biovolume, surface area, surface-volume ratio, cell carbon content, etc.) and investigate their distribution patterns at different levels of data aggregation (i.e. spatial, temporal, taxonomic) by means of services which automate a set of operations written in the R language.

  • The size class distribution web service allows to visualize the distribution of phytoplankton in different size classes selected on the basis of logarithmic values of biovolume or carbon content. The service works on datasets structured according to the Phytoplankton Data Template that can be selected by the GUI or uploaded by the researchers. The input file is in CSV format with some mandatory fields (density, biovolume or cell carbon content). Before selecting or uploading the input file, users have to specify some parameters (e.g., the trait to be used for the ranked distribution, the logarithm base, the spatial and temporal levels for the clusterization of data). The web service provides as output a zip file containing a summary table in csv format and one or more bar plots according to the selected clusters.

  • The size density relationships web service calculates and describes the relationships between size (total biovolume and total carbon content) and density for any given combination of spatial, temporal and taxonomic level of observations. The service works on datasets structured according to the Phytoplankton Data Template that can be selected by the GUI or uploaded by the researchers. The input file is in CSV format with some mandatory fields (density, biovolume or cell carbon content). Before selecting or uploading the input file, users have to specify some parameters (e.g., the trait to be used for the size distribution, the taxonomic level for the size distribution and the spatial and temporal levels for the clusterization of data). The web service provides as output a zip file containing two summary tables in csv format and a scatter plot.

  • Background Biological invasions are acknowledged to be significant environmental and economic threats, yet the identification of key ecological traits determining invasiveness of species has remained elusive. One unappreciated source of variation concerns dietary flexibility of non-native species and their ability to shift trophic position within invaded food webs. Trophic plasticity may greatly influence invasion success as it facilitates colonisation, adaptation, and successful establishment of non-native species into new territories. In addition, having a flexible diet gives the introduced species a better chance to become invasive and, as a consequence, to have a strong impact on food webs, determining secondary disruptions such as trophic cascades and changes in energy fluxes. The deleterious effects can affect multiple trophic levels. Introduction Crustaceans are considered the most successful taxonomic group of aquatic invaders worldwide. Their ability to colonise and easily adapt to new ecosystems can be ascribed to a number of ecological features including their omnivorous feeding behaviour. This validation case study focuses on two invasive crustaceans widely distributed in marine and freshwater European waters: the Atlantic blue crab Callinectes sapidus and the Louisiana crayfish or red swamp crayfish Procambarus clarkii. Callinectes sapidus and Procambarus clarkii are opportunistic omnivores that feed on a variety of food sources from detritus to plants and invertebrates. For this reason, they represent a good model to investigate the variation of trophic niches in invaded food webs and their ecological impact on native communities. The ecological consequences of the invasion and establishment of these invasive crustaceans can vary from modification of carbon cycles in benthic food webs to regulation of prey/predator abundance through bottom-up and top-down interactions. Understanding how the trophic ecology of these invasive crustaceans shapes benthic food webs in invaded ecosystems is crucial for an accurate assessment of their impact. The analysis of stable isotopes can provide important clues on the trophic effects of invasive species within non-native ecosystems by evaluating changes in their trophic position and characteristics of their trophic niche. Aims This validation case uses a collection of stable isotopes (δ13C and δ15N) of C. sapidus and P. clarkii and their potential prey in invaded food webs to quantify changes in the trophic position of the invaders and to assess post-invasion shifts in their dietary habits. This case study additionally evaluates the main environmental drivers involved in trophic niche adaptations and whether such bioclimatic predictors influence broad-scale patterns of variation in the trophic position of the invader.

  • This service aims at creating a vector from the coordinates in the “Pop_troph_SIA.csv” file and convert it into a shapefile. It represents the Step 3.1 of the Crustaceans Workflow within the Internal Joint Initiative.

  • This service represents the Step 2 of the Metabarcoding Workflow within the Internal Joint Initiative. It aims at converting the CSV into rdata. It takes as input the Species_occ.csv file (output of the Step 1 Metabarcoding Runner), verifies the checklists available for each country and retrieves the first one. It produces two rdata files, that will be the inputs for the Step 3 GBIF NIS Verifier of the Metabarcoding workflow.

  • This service aims at checking which taxa detected and identified from eDNA metabarcoding sequences are listed as NIS and which taxa are not (i.e. native or unrecorded NIS). This service uses available GBIF (Global Biodiversity Information Facility) records of NIS for each Country provided by the Invasive Species Specialist Group (ISSG). it checks if a species is present in the checklist and if this is the case, the species is flagged as being invasive for that country by adding 1 (yes) or 0 (no) to the column isInChecklist of the data frame, and the checklist key or a note to the ref_checklistKey column, for the corresponding cases. It represents the Step 3 of the Metabarcoding Workflow within the Internal Joint Initiative.

  • This service extracts from GBIF (Global Biodiversity Information Facility) taxa occurrence records that were not classified as NIS in Step 3 (GBIF NIS Verifier) of the Metabarcoding workflow. This step aims to verify if eDNA detections were identified outside the known distribution range using GBIF occurrences records. Additionally, for such eDNA detections, this step produces a geographical spatial polygon based on occurrence records available in GBIF. It represents the Step 4 of the Metabarcoding Workflow within the Internal Joint Initiative.