<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Skjøth, Carsten Ambelas</dc:creator>
  <dc:creator>Sun, Yan</dc:creator>
  <dc:creator>Karrer, Gerhard</dc:creator>
  <dc:creator>Sikoparija, Branko</dc:creator>
  <dc:creator>Smith, Matt</dc:creator>
  <dc:creator>Schaffner, Urs</dc:creator>
  <dc:creator>Müller-Schärer, Heinz</dc:creator>
  <dc:date>2019-10-10</dc:date>
  <dc:description xmlns:ns0="xml" ns0:lang="en">Common ragweed (Ambrosia artemisiifolia L.) is a widely distributed and harmful  invasive plant that is an important source of highly allergenic pollen grains and a  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.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>https://folia.unifr.ch/global/documents/308074</dc:identifier>
  <dc:identifier>https://folia.unifr.ch/documents/308074/files/mue_pai.pdf</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.1016/j.scitotenv.2019.05.215</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>License undefined</dc:rights>
  <dc:source>Science of The Total Environment. - 2019, vol. 686, p. 212–222</dc:source>
  <dc:subject>info:eu-repo/classification/udc/57</dc:subject>
  <dc:title xmlns:ns1="xml" ns1:lang="en">Predicting abundances of invasive ragweed across Europe using a “top-down” approach</dc:title>
  <dc:type>http://purl.org/coar/resource_type/c_6501</dc:type>
</oai_dc:dc>
