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Query: "keywords" (alien plants) .

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1.
Public preferences for the management of different invasive alien forest taxa
Anže Japelj, Jana Kus Veenvliet, Judita Malovrh, Andrej Verlič, Maarten De Groot, 2019, original scientific article

Abstract: Invasive alien species (IAS) require management to mitigate their impact on ecosystems. The success of management decisions often depends on whether they are socially acceptable and to what extent people are willing to be actively involved in an early warning and rapid response system (EWRR). We administered a nation-wide public poll to assess people%s knowledge on plant, insect and fungal IAS; their perception of IAS as an environmental problem; and their support for different IAS management measures. Most respondents (76%) knew the term IAS, and more than half (62%) provided a correct definition. Species with more media attention and those that are easily visible are more frequently identified correctly. Almost all respondents (97%) support an EWRR system; however, there is heterogeneity in terms of the types of actions people approve of. Non-lethal measures garner more support than lethal ones. Gender and previous knowledge also affect the level of agreement. The willingness-to-pay question largely confirmed this, as people were divided into four classes according to their preferences for either biological, mechanical or chemical measures to control IAS; completeness and location of removal; and having an EWRR established. Mechanical removal is the most preferred treatment in two of the four classes, and complete removal is preferred over partial removal in one of the four classes. Having an EWRR is consistently supported in all classes, and removal in urban areas is preferred over removal in forestland in only one class.
Keywords: Early warning and rapid response system, public attitudes, management measures, alien insects, alien plants, alien fungi
Published in DiRROS: 12.07.2019; Views: 2593; Downloads: 1419
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2.
Forewarned is forearmed : harmonized approaches for early detection of potentially invasive pests and pathogens in sentinel plantings
Carmen Morales-Rodríguez, Sten Anslan, Marie-Anne Auger-Rozenberg, Sylvie Augustin, Yuri Baranchikov, Amani Bellahirech, Daiva Burokiene, Dovile Čepukoit, Ejup Çota, Kateryna Davydenko, Maarten De Groot, 2019, original scientific article

Abstract: The number of invasive alien pest and pathogen species affecting ecosystem functioning, human health and economies has increased dramatically over the last decades. Discoveries of invasive pests and pathogens previously unknown to science or with unknown host associations yet damaging on novel hosts highlights the necessity of developing novel tools to predict their appearance in hitherto naïve environments. The use of sentinel plant systems is a promising tool to improve the detection of pests and pathogens before introduction and to provide valuable information for the development of preventative measures to minimize economic or environmental impacts. Though sentinel plantings have been established and studied during the last decade, there still remains a great need for guidance on which tools and protocols to put into practice in order to make assessments accurate and reliable. The sampling and diagnostic protocols chosen should enable as much information as possible about potential damaging agents and species identification. Consistency and comparison of results are based on the adoption of common procedures for sampling design and sample processing. In this paper, we suggest harmonized procedures that should be used in sentinel planting surveys for effective sampling and identification of potential pests and pathogens. We also review the benefits and limitations of various diagnostic methods for early detection in sentinel systems, and the feasibility of the results obtained supporting National Plant Protection Organizations in pest and commodity risk analysis.
Keywords: alien invasive pests, alien invasive pathogens, commodity risk analysis, early warning, sampling techniques, sentinel plants, pest risk analysis, prediction
Published in DiRROS: 01.07.2019; Views: 2289; Downloads: 1357
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