FdW84TkcrZ12 The case study was proposed by the LifeWatch CT Mediterranean in order to explore the susceptibility of EUNIS habitat to AS invasions. The case study was originally presented for freshwater and marine habitat (Boggero et al., 2014; Corriero et al, 2016). In the VRE alien species the case study, originally used to analyze freshwater and marine habitat, has been generalized to work with any biodiversity dataset available in the LW data portal. For a full comprehension of the rationale of the case study and the statistical approach used we strongly encourage the users to access the tutorial and to read carefully Boggero et al. (2014) and Corriero et al. (2016).  17URLhttps://www.lifewatchitaly.eu/en/alien-species-vre/enThe LifeWatch Italy national node has realised the Alien and Invasive Species Virtual Research Environment (Alien Species VRE) for supporting researchers to address basic and applied studies on ecosystem vulnerability to alien species arrival. The Alien Species VRE allows to: - access and download harmonised data on the national distribution of species of fauna and flora belonging to different habitats (marine, fresh and transitional waters, and terrestrial) published through the LifeWatch Italy Data Portal and distributed by the LifeWatch ERIC Metadata Catalogue; - upload their own datasets structured according to the LifeWatch Italy Data Schema in order to execute the service included in the VRE.alien speciesinvasive speciesEUNIS habitatWWNot availableFinalAuthorLifeWatch Italy2016MixedOpen accessNoNoCopyright © 2016 LifeWatch ItaliaExperimentMediumLowResearchersStudentsTrainingIntermediatePT15MNot availableNatural Sciences - Earth and related environmental scienceskHhx9jiEZn21The 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. This tutorial shows how to use the services included in the VRE. 21URLhttps://www.phytovre.lifewatchitaly.eu/enThe 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.phytoplanktontraitsdata analysisWW1.0FinalAuthorLifeWatch ItalyJuly 2018MixedOpen accessNoYesCopyright (c) 2018 LifeWatch ItalyExperimentMediumMediumResearchersStudentsTrainingBeginnerPT55M45SNot AvailableNatural Sciences - Earth and related environmental sciencesRcwrBMYavY26The olympic games of ecology for young people: the first national online ecology competition aimed at first and second grade secondary school students. 26URLhttps://training.lifewatchitaly.eu/education-and-schools-2/ecologicacup/itThe olympics of ecology for young people: the first national online ecology competition aimed at first and second grade secondary school children.gameItalianecologycompetition schoolWWNot availableFinalAuthorUniversity of Salento2007ActiveRestricted accessNoYesCopyright © Unisalento OESEMQuestionnaireHighMediumStudentsHigher educationIntermediateKnowledge-dependentNot availableNatural Sciences - Earth and related environmental sciencesxBFS53Iesg28ECOPOTENTIAL 4SCHOOLS Scientific Game You can test your skills in the field of Scientific Research with ECOPOTENTIAL4SCHOOLS, an online game addressed to students coming from all European Schools 28URLhttp://ecopotential4schools.lifewatchitaly.eu/enECOPOTENTIAL 4SCHOOLS Scientific Game: You can test your skills in the field of Scientific Research with ECOPOTENTIAL4SCHOOLS, an online game addressed to students coming from all European Schools.gamingScientific Gameschoolresearch competitionecopotentialeuropeanWWNot availableFinalAuthorUniversity of Salento2017ActiveRestricted accessNoYesCopyright © Unisalento European CommissionQuestionnaireMediumMediumStudentsHigher educationIntermediateKnowledge-dependentNot availableNatural Sciences - Earth and related environmental sciencesysWgLQvHIM30Playing with the game DISCOVERING CASTELPORZIANO you will deepen your understanding of the Presidential Estate of Castelporziano.  30URLhttps://training.lifewatchitaly.eu/education-and-schools-2/resources/?resource=/course/view.php?id=45enPlaying Discovery Castelporziano you will deepen your understanding of the Presidential Estate of Castelporziano.GameBiodiversityCastelporzianoWWFirstFinalAuthorLifeWatch Italy2020MixedRestricted accessNoYesCopyright © 2020 LifeWatch ItaliaQuestionnaireHighMediumStudentsSchoolBeginnerKnowledge-dependent Not AvailableNatural Sciences - Earth and related environmental sciencesSzXR8z8A4f35The game provides a guide to exploring the distinctive ecosystems of Castelporziano, focusing on the characteristic aspects of the dune ecosystems, describing the plants and animals that populate them, and then reaching the wooded ecosystem and pastures of the estate, and investigating the animal and plant diversity of these places. The game is suitable for children aged six to ten.  35URLhttps://training.lifewatchitaly.eu/education-and-schools-2/resources/?resource=/course/view.php?id=44enThe game provides a guide to exploring the distinctive ecosystems of Castelporziano, focusing on the characteristic aspects of the dune ecosystems, describing the plants and animals that populate them, and then reaching the wooded ecosystem and pastures of the estate, and investigating the animal and plant diversity of these places. The game is suitable for children aged six to ten.Scientific GameCastelporzianoWWNot availableFinalAuthorLifeWatch Italy2020ActiveCopyright © 2020 LifeWatch Italia NoYesCopyright © 2020 LifeWatch ItaliaQuestionnaireHighMediumStudentsSchoolBeginnerKnowledge-dependent Not AvailableUf7ZXlvIoz36Playing with Ecology in Castelporziano you you will explore the ecosystems and species that inhabit them, digging down into the factors that influence their distribution. With this game you will discover the biodiversity heritage of Castelporziano, and why it requires constant monitoring and conscientious conservation. This game is intended for students between 14 and 18 years of age.  36URLhttps://training.lifewatchitaly.eu/education-and-schools-2/resources/?resource=/course/view.php?id=42enPlaying with Ecology in Castelporziano you you will explore the ecosystems and species that inhabit them, digging down into the factors that influence their distribution. You will discover the biodiversity heritage of Castelporziano, and why it requires constant monitoring and conscientious conservation. This game is intended for students between 14 and 18 years of age. Scientific GameCastelporzianoWWNot availableFinalAuthorLifeWatch Italy2020ActiveRestricted accessNoYesCopyright © 2020 LifeWatch ItaliaQuestionnaireHighMediumStudentsSchoolBeginnerKnowledge-dependent Not AvailableNatural Sciences - Earth and related environmental sciencesOG30OCkYpG37Playing with Biodiversity in Castelporziano you will be able to test your knowledge of the management and conservation of resources at the Presidential Estate of Castelporziano and understand the legislative measures that exist at the European level for the protection of ecosystems. Thanks to this game, you will learn about the habitats and species of high naturalistic value that populate the estate, including some endangered species.  37URLhttps://training.lifewatchitaly.eu/education-and-schools-2/resources/?resource=/course/view.php?id=43enPlaying with Biodiversity in Castelporziano you will be able to test your knowledge of the management and conservation of resources at the Presidential Estate of Castelporziano and understand the legislative measures that exist at the European level for the protection of ecosystems. You will learn about the habitats and species of high naturalistic value that populate the estate, including some endangered species. (The resource is addressed at the students).Scientific GameCastelporzianoWWNot availableFinalAuthorLifeWatch Italy2020ActiveRestricted accessNoYesCopyright © 2020 LifeWatch ItaliaQuestionnaireHighMediumStudentsSchoolBeginnerKnowledge-dependent Not AvailableNatural Sciences - Earth and related environmental sciencesET6DKbr_cp41Phytoplankton plays an important role in aquatic ecosystems as it accounts for most of global primary production and affects the biogeochemical processes, trophic dynamics and biodiversity architecture.   LifeWatch Italy, one of the ERIC's national nodes, designed the Phytoplankton Virtual Research Environment (Phyto VRE) to support researches on phytoplankton guilds and their relative structure, organization and ecological function. The Phyto VRE services, in fact, enable researchers to analyse and process phytoplankton data at a level of resolution from individual cells to whole guilds. In particular, the Atlas of Phytoplankton and the Atlas of Shapes provide harmonised data on taxonomy and morphological and demographic traits.   This tutorial illustrates how to access, navigate and use these two services of the LifeWatch Italy Phyto VRE.  41URLhttps://training.lifewatchitaly.eu/en/services-tutorials-2/resources/?resource=/course/view.php?id=21enPhytoplankton plays an important role in aquatic ecosystems as it accounts for most of global primary production and affects the biogeochemical processes, trophic dynamics and biodiversity architecture. LifeWatch Italy, one of the ERIC's national nodes, designed the Phytoplankton Virtual Research Environment (Phyto VRE) to support researches on phytoplankton guilds and their relative structure, organization and ecological function. The Phyto VRE services, in fact, enable researchers to analyse and process phytoplankton data at a level of resolution from individual cells to whole guilds. In particular, the Atlas of Phytoplankton and the Atlas of Shapes provide harmonised data on taxonomy and morphological and demographic traits. This resource illustrates how to access, navigate and use these two services of the LifeWatch Italy Phyto VRE.phytoplanktonatlas of shapesatlas of phytoplanktonWWNot availableFinalAuthorLifeWatch Italy2021ExpositiveOpen accessNoYesCopyright © 2021 LifeWatch ItaliaNarrative textMediumMediumResearchersStudentsOtherIntermediateKnowledge-dependent Not AvailableNatural Sciences - Biological sciencesBvejgbUDd041The LifeWatch eCampus offers courses, short schools and lifelong learning products dedicated to universities, post-doc and early-career researchers. The biodiversity of all individuals in a given meta-community may be split into the diversity within and between local communities. From a conservational point of view several questions arise. What is the importance of the biodiversity of a single local community with respect to the entire metacommunity? Which local communities contribute more to the biodiversity of the meta-community? Is it possible to maintain the biodiversity of the meta-community preserving only the most diverse local communities or should we care more about the conservation of ecosystem peculiarities? This study-lab training briefly introduces the R software and then focuses on biodiversity partitioning, describing methodology and software for γ, α and β diversity profiling. It then discusses the theory behind mixed effects modeling and how this can be applied to investigate the variation of biodiversity measures. The training concludes with a practical unit that examines the use of the R implementation of mixed effects modeling routines with data from ecological surveys.  Knowledge of α-, β- and γ-biodiversity; biodiversity and entropy; linear models; mixed effects models; basics of the R software is preferable, but not mandatory. 41URLhttps://training.lifewatchitaly.eu/biodiversity-ecampus-2/resources/?resource=/course/view.php?id=6enThe biodiversity of all individuals in a given meta-community may be split into the diversity within and between local communities. From a conservational point of view several questions arise. What is the importance of the biodiversity of a single local community with respect to the entire metacommunity? Which local communities contribute more to the biodiversity of the meta-community? Is it possible to maintain the biodiversity of the meta-community preserving only the most diverse local communities or should we care more about the conservation of ecosystem peculiarities? This study-lab training briefly introduces the R software and then focuses on biodiversity partitioning, describing methodology and software for γ, α and β diversity profiling. It then discusses the theory behind mixed effects modeling and how this can be applied to investigate the variation of biodiversity measures. The training concludes with a practical unit that examines the use of the R implementation of mixed effects modeling routines with data from ecological surveys. Knowledge of α-, β- and γ-biodiversity; biodiversity and entropy; linear models; mixed effects models; basics of the R software is preferable, but not mandatory.Biodiversity analysisWWNot availableFinalAuthorLifeWatch ERIC2021MixedRestricted accessNoNoCopyright © 2021 LifeWatch ERICExerciseLowMediumResearchersStudentsTrainingAdvancedKnowledge-dependent Not AvailableNatural Sciences - Earth and related environmental sciencesnOk68qgKsP43The LifeWatch eCampus offers courses, short schools and lifelong learning products dedicated to universities, post-doc and early-career researchers. The Incidence Function Model describes presence/absence of a species in the patches of a highly fragmented landscape at discrete time intervals (years) as the result of colonization and extinction processes. The IFM ignores local dynamics since they are faster than metapopulation dynamics in producing changes in the size of local populations (Hanski, 1994). In the IFM, the process of occupancy of patch is described by a first-order Markov chain with two states, {O, i} (empty and occupied, respectively). The extinction probability of a population in a patch is constant in time and is assumed to decrease with increasing patch area, and the colonization probability is assumed to be a sigmoidal function increasing with connectivity. The IFM is the best known spatially explicit metapopulation model in literature. This model has been applied to conservation problems and to area-wide pest-management. Sound knowledge of Probability and Statistics and basic elements of any programming language is recommended. 43URLhttps://training.lifewatchitaly.eu/biodiversity-ecampus-2/resources/?resource=/course/view.php?id=8enThe LifeWatch eCampus offers courses, short schools and lifelong learning products dedicated to universities, post-doc and early-career researchers. The Incidence Function Model describes presence/absence of a species in the patches of a highly fragmented landscape at discrete time intervals (years) as the result of colonization and extinction processes. The IFM ignores local dynamics since they are faster than metapopulation dynamics in producing changes in the size of local populations (Hanski, 1994). In the IFM, the process of occupancy of patch is described by a first-order Markov chain with two states, {O, i} (empty and occupied, respectively). The extinction probability of a population in a patch is constant in time and is assumed to decrease with increasing patch area, and the colonization probability is assumed to be a sigmoidal function increasing with connectivity. The IFM is the best known spatially explicit metapopulation model in literature. This model has been applied to conservation problems and to area-wide pest-management. Sound knowledge of Probability and Statistics and basic elements of any programming language is recommended.Incidence Function ModelWWNot availableFinalAuthorLifeWatch ERIC2021MixedRestricted accessNoYesfree to useExerciseMediumMediumStudentsOtherBeginnerKnowledge-dependent Not AvailableNatural Sciences - Earth and related environmental sciences7RnqPz2XGX72The Citizen Science Toolkit is an open, online and interactive platform that aims to help anyone interested in learning and experimenting with citizen science to engage communities to tackle common concerns and deploy actions to make the world a better place to live. The Toolkit, available at https://citizensciencetoolkit.eu/, provides examples and resources from the CitieS-Health project and other participatory projects for identifying a common problem, designing a citizens-driven research study, and proactively collecting data to provide evidence that informs actions. 72URLhttps://citizensciencetoolkit.euenThe Citizen Science Toolkit is an open, online and interactive platform that aims to help anyone interested in learning and experimenting with citizen science to engage communities to tackle common concerns and deploy actions to make the world a better place to live.The Toolkit, available at https://citizensciencetoolkit.eu/, provides examples and resources from the CitieS-Health project and other participatory projects for identifying a common problem, designing a citizens-driven research study, and proactively collecting data to provide evidence that informs actions.openonlineinteractiveplatformbest practicesco-creationproject managementdata quality and standardsproject sustainabilityWWNot availableFinalAuthorRaul Toran and the CitieS-Health team2022ExpositiveOpen accessNoYesCopyright - Raul Toran and the CitieS-Health teamNarrative textLowMediumResearch communitiesStudentsPolicy MakersTrainingBeginnerKnowledge-dependentNot availableOther - Other