Biological Invasions (2021) 23, 2435-2449

Sima Sohrabi, Jan Pergl, Petr Pysek, Llewellyn C. Foxcroft and Javid Gherekhloo (2021)
Quantifying the potential impact of alien plants of Iran using the Generic Impact Scoring System (GISS) and Environmental Impact Classification for Alien Taxa (EICAT)
Biological Invasions 23 (8), 2435-2449
Abstract: Assessing the impacts of alien plant species is scientifically important and critical for supporting invasion-related policies. Generic Impact Scoring System (GISS) and Environmental Impact Classification for Alien Taxa (EICAT) are standardized schemes to evaluate, compare, and eventually predict the magnitudes of the variety of impacts invasive species can have. Here, we apply these two systems to classify alien plants of Iran according to the magnitude of their environmental and socioeconomic impacts. A review of published literature and online resources was undertaken to collate information on the reported environmental and socioeconomics impacts of 27 alien plants in Iran. The resulting data ranked species by their total sum of impact scores and by their highest scores. According to total impact scores from GISS Eichhornia crassipes, Ailanthus altissima, Imperata cylindrica, Amsinckia menziesii, and Paulownia sp. had the highest impacts. About 60% of alien plants assessed had higher environmental impacts than socioeconomic impacts, 18% had higher scores for socioeconomic impacts, and 22% scored the same in both categories. According to EICAT, Ulex europaeus, Ambrosia psilostachya, E. crassipes, A. altissima, and A. menziesii were the five species with major impacts; other 16 species (59%) were classified as with moderate impacts, five with minor and two of minimal concern. Seven species had similar rankings by both GISS and EICAT. The deficit of scientific literature to quantify impacts on complex ecosystem services in Iran or emphasis on the reversibility of impacts in the EICAT protocol could explain differences in ranking of species by the two schemes. GISS and EICAT could be used to link impact magnitudes and type (environmental or socioeconomic) to biological traits to understand and forecast species with different types of impact.
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Link to article at publishers website
Database assignments for author(s): Jan Pergl, Petr Pysek

Research topic(s) for pests/diseases/weeds:
damage/losses/economics

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Pest and/or beneficial records:

Beneficial	Pest/Disease/Weed	Crop/Product	Country	Quarant.
	Pontederia crassipes (weed)		Iran
	Imperata cylindrica (weed)		Iran
	Ailanthus altissima (weed)		Iran
	Amsinckia menziesii (weed)		Iran