首页 | 本学科首页   官方微博 | 高级检索  
     


Predicting invasion risk of 16 species of eucalypts using a risk assessment protocol developed for Brazil
Authors:  lvia R. Ziller,Michele de S   Dechoum,Rafael Dudeque Zenni
Affiliation:Sílvia R. Ziller,Michele de Sá Dechoum,Rafael Dudeque Zenni
Abstract:Risk analyses are predictive systems designed to detect the risk of invasion by non‐native species. Although eucalypts are often considered moderately invasive given the extent of cultivation on a global scale, some species are widely recognized as invasive for transforming and impacting natural areas in several countries. These problems may be due to propagule pressure derived from human interest in forest production and aesthetic values. Risk analyses were carried out for 16 eucalypt species cultivated in Brazil using a protocol adapted from an Australian model to Brazilian conditions. The species were: Corymbia citriodora, Corymbia maculata, Corymbia torelliana, Eucalyptus benthamii, Eucalyptus brassiana, Eucalyptus camaldulensis, Eucalyptus cloeziana, Eucalyptus dunnii, Eucalyptus globulus, Eucalyptus grandis, Eucalyptus pellita, Eucalyptus robusta, Eucalyptus saligna, Eucalyptus tereticornis, Eucalyptus urophylla and Eucalyptus viminalis. Results indicate high risk for seven species, moderate risk for eight species and low risk for one species. The only low risk species is E. dunnii, while the highest risk scores refer to C. torelliana, E. tereticornis and E. grandis. These results are consistent with the history of invasion of the species around the world and should be considered for plantations especially when investment capacity to prevent and permanently control spread is low or not associated with forest certification standards. Risk analysis is a valid tool for discriminating between species and making decisions on species to be introduced or cultivated. The results of this study show that there are many species that can be cultivated without incurring biological invasions.
Keywords:forestry  invasive non‐native species  management  prevention  tree invasion
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号