Predicting Abundances of Invasive Ragweed Across Europe Using a “Top-down” Approach

Skjøth, C. ORCID: https://orcid.org/0000-0001-5992-9568, Sun, Y., Karrer, G., Sikoparija, B., Smith, Matt ORCID: https://orcid.org/0000-0002-4170-2960, Schaffner, U. and Müller-Schärer, H. (2019) Predicting Abundances of Invasive Ragweed Across Europe Using a “Top-down” Approach. Science of the Total Environment, 686. pp. 212-222. ISSN Print: 0048-9697 Online: 1879-1026

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Abstract

Common ragweed (Ambrosia artemisiifolia L.) is a widely distributed and harmful invasive plant that is an important source of highly allergenic pollen grains and prominent crop weed. As a result, ragweed causes huge costs to both human health and agriculture in affected areas. Efficient mitigation requires accurate mapping of ragweed densities that, until now, has not been achieved accurately for the whole of Europe. Here we provide two inventories of common ragweed abundances with grid resolutions of 1 km and 10 km. These “top-down” inventories integrate pollen data from 349 stations in Europe with habitat and landscape management information, derived from land cover data and expert knowledge. This allows us to cover areas where surface observations are missing. Model results were validated using “bottom–up” data of common ragweed in Austria and Serbia. Results show high agreement between the two analytical methods. The inventory shows that areas with the lowest ragweed abundances are found in Northern and Southern European countries and the highest abundances are in parts of Russia, parts of Ukraine and the Pannonian Plain. Smaller hotspots are found in Northern Italy, the Rhône Valley in France and in Turkey. The top-down approach is based on a new approach that allows for cross continental studies and is applicable to other anemophilous species. Due to its simplicity, it can be used to investigate such species that are difficult and costly to identify at larger scales using traditional vegetation surveys or remote sensing. The final inventory is open source and available as a georeferenced tif file, allowing for multiple usages, reducing costs for health services and agriculture through well-targeted management interventions.

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