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Identifying emerging invasive species is a priority to implement early preventive and control actions. In terms of the number of invasive tree species, forestry represents the second largest pathway of introduction, with an invasive debt likely existing for alien conifers in Europe. In the early 1900s, a network of arboreta was established in southern Belgium to assess the wood production potential of prospective conifer and broadleaved species. Here, we use eight arboreta as natural experiments to identify alien conifers presenting invasive behavior. Through systematic sampling, we quantified the natural regeneration of alien conifers and recorded local environmental variables. For each species, regeneration density, dispersal distances, and age structure were analyzed. Generalized mixed effects models were fitted to test the effect of planted area and tree-stand type on regeneration. The environmental space occupied by regenerating alien conifers was evaluated using principal component analysis. Out of 31 planted alien species, 15 (48%) were identified in natural regeneration, of which eight (26%) exhibited important regeneration density and dispersal distances. The most invasive species were Tsuga heterophylla and Abies grandis, confirming earlier field observations. Both large planted areas and areas planted with alien conifer species increased the density of regeneration. Species that had the highest regeneration density tolerated a wide range of environmental conditions, including shaded understory, which could lead to the invasion of mature, undisturbed forests. This study showed that 17% of the studied alien conifers are potentially invasive because they show important regeneration, long-distance dispersal, and, of importance, have already produced offspring that have matured and are capable of creating new satellite populations. In conclusion, our results provide a guideline for future planting operations, recommending extreme caution when planting these species in the temperate forests of Western Europe.

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.