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  • 1
    In: Research Ideas and Outcomes, Pensoft Publishers, Vol. 3 ( 2017-05-02)
    Abstract: Imagine a future where dynamically, from year to year, we can track the progression of alien species (AS), identify emerging problem species, assess their current and future risk and timely inform policy in a seamless data-driven workflow. One that is built on open science and open data infrastructures. By using international biodiversity standards and facilities, we would ensure interoperability, repeatability and sustainability. This would make the process adaptable to future requirements in an evolving AS policy landscape both locally and internationally. In recent years, Belgium has developed decision support tools to inform invasive alien species (IAS) policy, including information systems, early warning initiatives and risk assessment protocols. However, the current workflows from biodiversity observations to IAS science and policy are slow, not easily repeatable, and their scope is often taxonomically, spatially and temporally limited. This is mainly caused by the diversity of actors involved and the closed, fragmented nature of the sources of these biodiversity data, which leads to considerable knowledge gaps for IAS research and policy. We will leverage expertise and knowledge from nine former and current BELSPO projects and initiatives: Alien Alert, Invaxen, Diars, INPLANBEL, Alien Impact, Ensis, CORDEX.be, Speedy and the Belgian Biodiversity Platform. The project will be built on two components: 1) The establishment of a data mobilization framework for AS data from diverse data sources and 2) the development of data-driven procedures for risk evaluation based on risk modelling, risk mapping and risk assessment. We will use facilities from the Global Biodiversity Information Facility (GBIF), standards from the Biodiversity Information Standards organization (TDWG) and expertise from Lifewatch to create and facilitate a systematic workflow. Alien species data will be gathered from a large set of regional, national and international initiatives, including citizen science with a wide taxonomic scope from marine, terrestrial and freshwater environments. Observation data will be funnelled in repeatable ways to GBIF. In parallel, a Belgian checklist of AS will be established, benefiting from various taxonomic and project-based checklists foreseen for GBIF publication. The combination of the observation data and the checklist will feed indicators for the identification of emerging species; their level of invasion in Belgium; changes in their invasion status and the identification of areas and species of concern that could be impacted upon by bioinvasions. Data-driven risk evaluation of identified emerging species will be supported by niche and climate modelling and consequent risk mapping using critical climatic variables for the current and projected future climate periods at high resolution. The resulting risk maps will complement risk assessments performed with the recently developed Harmonia+ protocol to assess risks posed by emergent species to biodiversity and human, plant, and animal health. The use of open data will ensure that interested stakeholders in Belgium and abroad can make use of the information we generate. The open science ensures everyone is free to adopt and adapt the workflow for different scenarios and regions. The checklist will be used at national level, but will also serve as the Belgian reference for international databases (IUCN - GRIIS, EASIN) and impact assessments (IPBES, SEBI). The workflow will be showcased through GEO BON, the Invasivesnet network and the COST Actions Alien Challenge and ParrotNet. The observations and outcomes of risk evaluations will be used to provide science-based support for the implementation of IAS policies at the regional, federal and EU levels. The publication of Belgian data and checklists on IAS is particularly timely in light of the currently ongoing EU IAS Regulation and its implementation in Belgium. By proving that automated workflows can provide rapid and repeatable production of information, we will open up this technology for other conservation assessments.
    Type of Medium: Online Resource
    ISSN: 2367-7163
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2017
    detail.hit.zdb_id: 2833254-4
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  • 2
    In: Proceedings of TDWG, Pensoft Publishers, Vol. 1 ( 2017-09-01), p. e20749-
    Type of Medium: Online Resource
    ISSN: 2535-0897
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2017
    detail.hit.zdb_id: 3028709-1
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  • 3
    In: Citizen Science: Theory and Practice, Ubiquity Press, Ltd., Vol. 4, No. 1 ( 2019-12-02)
    Type of Medium: Online Resource
    ISSN: 2057-4991
    Language: English
    Publisher: Ubiquity Press, Ltd.
    Publication Date: 2019
    detail.hit.zdb_id: 2932178-5
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  • 4
    In: Database, Oxford University Press (OUP), Vol. 2020 ( 2020-01-01)
    Abstract: Species checklists are a crucial source of information for research and policy. Unfortunately, many traditional species checklists vary wildly in their content, format, availability and maintenance. The fact that these are not open, findable, accessible, interoperable and reusable (FAIR) severely hampers fast and efficient information flow to policy and decision-making that are required to tackle the current biodiversity crisis. Here, we propose a reproducible, semi-automated workflow to transform traditional checklist data into a FAIR and open species registry. We showcase our workflow by applying it to the publication of the Manual of Alien Plants, a species checklist specifically developed for the Tracking Invasive Alien Species (TrIAS) project. Our approach combines source data management, reproducible data transformation to Darwin Core using R, version control, data documentation and publication to the Global Biodiversity Information Facility (GBIF). This checklist publication workflow is openly available for data holders and applicable to species registries varying in thematic, taxonomic or geographical scope and could serve as an important tool to open up research and strengthen environmental decision-making.
    Type of Medium: Online Resource
    ISSN: 1758-0463
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2496706-3
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  • 5
    Online Resource
    Online Resource
    Pensoft Publishers ; 2018
    In:  Biodiversity Information Science and Standards Vol. 2 ( 2018-03-15), p. e24749-
    In: Biodiversity Information Science and Standards, Pensoft Publishers, Vol. 2 ( 2018-03-15), p. e24749-
    Abstract: Reducing the damage caused by invasive species requires a community approach informed by rapidly mobilized data. Even if local stakeholders work together, invasive species do not respect borders, and national, continental and global policies are required. Yet, in general, data on invasive species are slow to be mobilized, often of insufficient quality for their intended application and distributed among many stakeholders and their organizations, including scientists, land managers, and citizen scientists. The Belgian situation is typical. We struggle with the fragmentation of data sources and restrictions to data mobility. Nevertheless, there is a common view that the issue of invasive alien species needs to be addressed. In 2017 we launched the Tracking Invasive Alien Species (TrIAS) project, which envisages a future where alien species data are rapidly mobilized, the spread of exotic species is regularly monitored, and potential impacts and risks are rapidly evaluated in support of policy decisions (Vanderhoeven et al. 2017). TrIAS is building a seamless, data-driven workflow, from raw data to policy support documentation. TrIAS brings together 21 different stakeholder organizations that covering all organisms in the terrestrial, freshwater and marine environments. These organizations also include those involved in citizen science, research and wildlife management. TrIAS is an Open Science project and all the software, data and documentation are being shared openly (Groom et al. 2018). This means that the workflow can be reused as a whole or in part, either after the project or in different countries. We hope to prove that rapid data workflows are not only an indispensable tool in the control of invasive species, but also for integrating and motivating the citizens and organizations involved.
    Type of Medium: Online Resource
    ISSN: 2535-0897
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2018
    detail.hit.zdb_id: 3028709-1
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  • 6
    Online Resource
    Online Resource
    Frontiers Media SA ; 2024
    In:  Frontiers in Ecology and Evolution Vol. 12 ( 2024-2-9)
    In: Frontiers in Ecology and Evolution, Frontiers Media SA, Vol. 12 ( 2024-2-9)
    Abstract: Species distribution models (SDMs) are often used to produce risk maps to guide conservation management and decision-making with regard to invasive alien species (IAS). However, gathering and harmonizing the required species occurrence and other spatial data, as well as identifying and coding a robust modeling framework for reproducible SDMs, requires expertise in both ecological data science and statistics. Methods We developed WiSDM, a semi-automated workflow to democratize the creation of open, reproducible, transparent, invasive alien species risk maps. To facilitate the production of IAS risk maps using WiSDM, we harmonized and openly published climate and land cover data to a 1 km 2 resolution with coverage for Europe. Our workflow mitigates spatial sampling bias, identifies highly correlated predictors, creates ensemble models to predict risk, and quantifies spatial autocorrelation. In addition, we present a novel application for assessing the transferability of the model by quantifying and visualizing the confidence of its predictions. All modeling steps, parameters, evaluation statistics, and other outputs are also automatically generated and are saved in a R markdown notebook file. Results Our workflow requires minimal input from the user to generate reproducible maps at 1 km 2 resolution for standard Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emission representative concentration pathway (RCP) scenarios. The confidence associated with the predicted risk for each 1km 2 pixel is also mapped, enabling the intuitive visualization and understanding of how the confidence of the model varies across space and RCP scenarios. Discussion Our workflow can readily be applied by end users with a basic knowledge of R, does not require expertise in species distribution modeling, and only requires an understanding of the ecological theory underlying species distributions. The risk maps generated by our repeatable workflow can be used to support IAS risk assessment and surveillance.
    Type of Medium: Online Resource
    ISSN: 2296-701X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2024
    detail.hit.zdb_id: 2745634-1
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  • 7
    In: Biological Invasions, Springer Science and Business Media LLC, Vol. 19, No. 9 ( 2017-9), p. 2507-2517
    Type of Medium: Online Resource
    ISSN: 1387-3547 , 1573-1464
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2014991-8
    SSG: 12
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  • 8
    In: Biodiversity Information Science and Standards, Pensoft Publishers, Vol. 4 ( 2020-10-01)
    Abstract: To support invasive alien species risk assessments, the Tracking Invasive Alien Species (TrIAS) project has developed an automated, open, workflow incorporating state-of-the-art species distribution modelling practices to create risk maps using the open source language R. It is based on Global Biodiversity Information Facility (GBIF) data and openly published environmental data layers characterizing climate and land cover. Our workflow requires only a species name and generates an ensemble of machine-learning algorithms (Random Forest, Boosted Regression Trees, K-Nearest Neighbors and AdaBoost) stacked together as a meta-model to produce the final risk map at 1 km 2 resolution (Fig. 1). Risk maps are generated automatically for standard Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emission scenarios and are accompanied by maps illustrating the confidence of each individual prediction across space, thus enabling the intuitive visualization and understanding of how the confidence of the model varies across space and scenario (Fig. 2). The effects of sampling bias are accounted for by providing options to: use the sampling effort of the higher taxon the modelled species belongs to (e.g., vascular plants), and to thin species occurrences. use the sampling effort of the higher taxon the modelled species belongs to (e.g., vascular plants), and to thin species occurrences. The risk maps generated by our workflow are defensible and repeatable and provide forecasts of alien species distributions under further climate change scenarios. They can be used to support risk assessments and guide surveillance efforts on alien species in Europe. The detailied modeling framework and code are available on GitHub: https://github.com/trias-project.
    Type of Medium: Online Resource
    ISSN: 2535-0897
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2020
    detail.hit.zdb_id: 3028709-1
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