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  • An R package to get downloads from the EurOBIS database. In 2019, development started for the eurobis R package, to serve as an easy to use interface to download EurOBIS data in R. Currently, the main functions and documentation are being developed and are working, but need some further testing and user feedback before it can be officially released.

  • 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 stack of coregistered multi-spectral raster images. It groups two seasons images (summer and autumn) and stack them to obtain a unique image at native resolution (2 meters) by using the Worldview-2 sensor. It represents the Step 5 of the Ailanthus Workflow within the Internal Joint Initiative.

  • 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.

  • A service that aims at verifying the coordinates (latitude and longitude in column 3 and 4 of file “Pop_trop_SIA.csv”) match with the location (“country” and “location” in column 1 and 2 of file “Pop_troph_SIA.csv”) using the “SIAShapefile.shp”. This is very important because these geographic coordinates will be used in other services to extract and retrieve environmental data on the location of the species observation/occurrence. So scientists need to ensure these coordinates are correct. It represents the Step 3.2 of the Crustaceans Workflow within the Internal Joint Initiative.

  • Background Monitoring hard-bottom marine biodiversity can be challenging as it often involves non-standardised sampling methods that limit scalability and inter-comparison across different monitoring approaches. Therefore, it is essential to implement standardised techniques when assessing the status of and changes in marine communities, in order to give the correct information to support management policy and decisions, and to ensure the most appropriate level of protection for the biodiversity in each ecosystem. Biomonitoring methods need to comply with a number of criteria including the implementation of broadly accepted standards and protocols and the collection of FAIR data (Findable, Accessible, Interoperable, and Reusable). Introduction Artificial substrates represent a promising tool for monitoring community assemblages of hard-bottom habitats with a standardised methodology. The European ARMS project is a long-term observatory network in which about 20 institutions distributed across 14 European countries, including Greenland and Antarctica, collaborate. The network consists of Autonomous Reef Monitoring Structures (ARMS) which are deployed in the proximity of marine stations and Long-term Ecological Research sites. ARMS units are passive monitoring systems made of stacked settlement plates that are placed on the sea floor. The three-dimensional structure of the settlement units mimics the complexity of marine substrates and attracts sessile and motile benthic organisms. After a certain period of time these structures are brought up, and visual, photographic, and genetic (DNA metabarcoding) assessments are made of the lifeforms that have colonised them. These data are used to systematically assess the status of, and changes in, the hard-bottom communities of near-coast ecosystems. Aims ARMS data are quality controlled and open access, and they are permanently stored (Marine Data Archive) along with their metadata (IMIS, catalogue of VLIZ) ensuring data fairness. Data from ARMS observatories provide a promising early-warning system for marine biological invasions by: i) identifying newly arrived Non-Indigenous Species (NIS) at each ARMS site; ii) tracking the migration of already known NIS in European continental waters; iii) monitoring the composition of hard-bottom communities over longer periods; and iv) identifying the Essential Biodiversity Variables (EBVs) for hard-bottom fauna, including NIS. The ARMS validation case was conceived to achieve these objectives: a data-analysis workflow was developed to process raw genetic data from ARMS; end-users can select ARMS samples from the ever-growing number available in collection; and raw DNA sequences are analysed using a bioinformatic pipeline (P.E.M.A.) embedded in the workflow for taxonomic identification. In the data-analysis workflow, the correct identification of taxa in each specific location is made with reference to WoRMS and WRiMS, webservices that are used to check respectively the identity of the organisms and whether they are introduced.

  • Background Ailanthus altissima is one of the worst invasive plants in Europe. It reproduces both by seeds and asexually through root sprouting. The winged seeds can be dispersed by wind, water and machinery, while its robust root system can generate numerous suckers and cloned plants. In this way, Ailanthus altissima typically occurs in very dense clumps, but can also occasionally grow as widely spaced or single stems. This highly invasive plant can colonise a wide range of anthropogenic and natural sites, from stony and sterile soils to rich alluvial bottoms. Due to its vigour, rapid growth, tolerance, adaptability and lack of natural enemies, it spreads spontaneously, out-competing other plants and inhibiting their growth Introduction Over the last few decades, Ailanthus altissima has quickly spread in the Alta Murgia National Park (Southern Italy) which is mostly characterized by dry grassland and pseudo-steppe, wide-open spaces with low vegetation, which are very vulnerable to invasion. Ailanthus altissima causes serious direct and indirect damages to ecosystems, replacing and altering communities that have great conservation value, producing severe ecological, environmental and economic effects, and causing natural habitat loss and degradation. The spread of Ailanthus altissima is likely to increase in the future, unless robust action is taken at all levels to control its expansion. In a recent working document of the European Commission, it was found that the cost of controlling and eliminating invasive species in Europe amounts to €12 billion per year. Two relevant questions then arise: i) whether it is possible or not to fully eradicate or, at least, to reduce the impact of an invasive species and ii) how to achieve this at a minimum cost, in terms of both environmental damage and economic resources. A Life Program funded the Life Alta Murgia project (LIFE12BIO/IT/000213) had, as its main objective, the eradication of this invasive exotic tree species from the Alta Murgia National Park. That project provided both the expert knowledge and valuable in-field data for the Ailanthus validation case study, which was conceived and developed within the Internal Joint Initiative of LifeWatch ERIC. Aims At the start of the on-going eradication program a single map of A. altissima was available, dating back to 2012. Due to the lack of data, predicting the extent of invasion and its impacts was extremely difficult, making it impossible to assess the efficacy of control measures. Static models based on statistics cannot predict spatial–temporal dynamics (e.g. where and when A. altissima may repopulate an area), whereas mechanistic models incorporating the growth and spread of a plant would require precise parametrisation, which was extremely difficult with the scarce information available. To overcome these limitations, a relatively simple mechanistic model has been developed, a diffusion model, which is validated against the current spatial distribution of the plant estimated by satellite images. This model accounts for the effect of eradication programs by using a reaction term to estimate the uncertainty of the prediction. This model provides an automatic tool to estimate a-priori the effectiveness of a planned control action under temporal and budget constraints. This robust tool can be easily applied to other geographical areas and, potentially, to different species.

  • Background Freshwater ecosystems have been profoundly affected by habitat loss, degradation, and overexploitation, leaving them now especially vulnerable to biological invasions. Whether non-indigenous species are the key drivers or mere complementary factors of biodiversity loss is still debated among the scientific community, however biological invasions together with other anthropogenic stressors are determining population declines and homogenisation of biodiversity in freshwater ecosystems worldwide. For example, it has been demonstrated that river basins with greater numbers of non-indigenous species have higher extinction rates of native fish species. Consequently, the application of effective biomonitoring approaches to support protection actions of managers, stakeholders and policy-makers is nowadays essential. Introduction Conventional methods of monitoring freshwater fish diversity are based on direct observation of organisms and are therefore costly, labour and resource intensive, require taxonomic expertise, and can be invasive. Obtaining information about species and communities by retrieving DNA from environmental samples has the ability to overcome some of these difficulties. The molecular investigation of environmental samples is known as environmental DNA (eDNA). Environmental DNA can be isolated from water, soil, air or faeces as organisms shed their genetic material in the surroundings through metabolic waste, damaged tissues, sloughed skin cells and decomposition. The analysis of eDNA consists of extracting the genetic material and subjecting it to a Polymerase Chain Reaction (PCR) which amplifies the target DNA. The use of high-throughput sequencing (HTS) allows the simultaneous identification of many species within a certain taxonomic group. This community-wide approach is known as eDNA metabarcoding and involves the use of broad-range primers during PCR that amplify a set of species. In recent years, the cost of this technology has drastically decreased, making it very attractive in conservation management and scientific research. A number of studies have demonstrated that eDNA metabarcoding is more sensitive than conventional biomonitoring methods for freshwater fish as it can detect rare or low-abundance taxa. As a result, eDNA metabarcoding can be used as an early-warning tool to detect new NIS at the initial stages of colonisation, when they are not yet abundant in the ecosystem. Aims This validation case regards eDNA metabarcoding fish sequences collected from the Douro Basin in Portugal. DNA sequences are processed through a bioinformatic pipeline wrapped in the first part of the analytical workflow which conducts a quality check and assigns the DNA sequences to produce a list of taxa. The analytical workflow developed can process DNA sequences of different kinds, depending on the genetic markers used for the analysis and so this workflow can be applied to different taxonomic groups and ecosystems. The taxa identified might include indigenous organisms as well as newly identified taxa within a certain geographical region. For that reason, the national checklists of introduced and invasive species (GRISS) from GBIF are consulted to check if the organisms detected are recognised as NIS or if previously unrecorded NIS have been detected through eDNA metabarcoding analysis.

  • This service aims to create a dataset of environmental predictors linked to SIA’s coordinates by exploiting oceanographic and bioclimatic raster layers. It extracts Enviromental Data and represents the Step 4 of the Crustaceans Workflow within the Internal Joint Initiative.

  • The service aims at harvesting species occurrences from GBIF based on a keyword for the geographic region (two letter country code) and a time interval, both entered by the user. It represents the Step 1a of the Biotope vulnerability Workflow within the Internal Joint Initiative.