This service aims at creating a stack of coregistered multi-spectral raster images. It groups four multi-seasons images and stack them to obtain a unique image at native resolution (30 meters) by using the Landsat 5 sensor. It represents the Step 3 of the Ailanthus 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.

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.

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.

A service that aims at verifying the species names (performing the taxonomy check) by using the input file SIA.csv. It represents the Step 1 of the Crustaceans Workflow within the Internal Joint Initiative.

This service aims at enabling the dataset uploading from the user. It represents the Step 1b of the Biotope vulnerability Workflow within the Internal Joint Initiative.

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.

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.

This service intersects the map(s) (geographical spatial polygons) from GBIF occurrence(s) with the locations of a list of taxa detected from eDNA metabarcoding and which were not included in the NIS checklist to verify if such eDNA detection(s) is/are likely to be new NIS detected in that location from eDNA sequences. It represents the Step 5 of the Metabarcoding Workflow within the Internal Joint Initiative.

It is a Support Vector Machine, pixel-based, classifier trained for a multi-class problem. It represents the Step 4 of the Ailanthus Workflow within the Internal Joint Initiative.