Integrating drivers influencing the detection of plant pests carried in the international cut flower trade

F J Areal, Julia M. Touza, A MacLeod, K Dehnen-Schmutz, C Perrings, M G Palmieri, N J Spence

Research output: Contribution to journalArticlepeer-review


This paper analyses the cut flower market as an example of an invasion pathway along which species of non-indigenous plant pests can travel to reach new areas. The paper examines the probability of pest detection by assessing information on pest detection and detection effort associated with the import of cut flowers. We test the link between the probability of plant pest arrivals, as a precursor to potential invasion, and volume of traded flowers using count data regression models. The analysis is applied to the UK import of specific genera of cut flowers from Kenya between 1996 and 2004. There is a link between pest detection and the Genus of cut flower imported. Hence, pest detection efforts should focus on identifying and targeting those imported plants with a high risk of carrying pest species. For most of the plants studied, efforts allocated to inspection have a significant influence on the probability of pest detection. However, by better targeting inspection efforts, it is shown that plant inspection effort could be reduced without increasing the risk of pest entry. Similarly, for most of the plants analysed, an increase in volume traded will not necessarily lead to an increase in the number of pests entering the UK. For some species, such as Carthamus and Veronica, the volume of flowers traded has a significant and positive impact on the likelihood of pest detection. We conclude that analysis at the rank of plant Genus is important both to understand the effectiveness of plant pest detection efforts and consequently to manage the risk of introduction of non-indigenous species.
Original languageEnglish
Pages (from-to)300-307
Number of pages8
JournalJournal of Environmental Management
Issue number4
Publication statusPublished - Dec 2008


  • Commerce
  • Great Britain
  • International Trade
  • Kenya
  • Regression Analysis
  • Plant pest species
  • Risk Assessment
  • Risk Management
  • Phytosanitary inspection
  • Cut flowers

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