期刊论文详细信息
Brazilian Journal of Biology
Use of ecological niche models to predict the distribution of invasive species: a scientometric analysis
Fg. Barbosa2  F. Schneck2  As. Melo1 
[1] ,Universidade Federal do Rio Grande do Sul Instituto de Biociências Porto Alegre RS ,Brazil
关键词: biodiversity;    biological invasions;    scientific production;    trends;    biodiversidade;    invasões biológicas;    produção científica;    tendências;   
DOI  :  10.1590/S1519-69842012000500007
来源: SciELO
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【 摘 要 】

We conducted a scientometric analysis to determine the main trends and gaps of studies on the use of ecological niche models (ENMs) to predict the distribution of invasive species. We used the database of the Thomson Institute for Scientific Information (ISI). We found 190 papers published between 1991 and 2010 in 82 journals. The number of papers was low in the 1990s, but began to increase after 2003. One-third of the papers were published by researchers from the United States of America, and consequently, the USA was also the most studied region. The majority of studies were carried out in terrestrial environments, while only a few investigated aquatic systems, probably because important aquatic predictor variables are scarce or unavailable for most regions in the world. Species-occurrence records were mainly composed of presence-only records, and almost 70% of the studies were carried out with plants and insects. Twenty-three different distribution modelling methods were used. The Genetic Algorithm for Rule-set Production (GARP) was used most often. Our scientometric analysis showed a growing interest in the use of ENMs to predict the distribution of invasive species, especially in the last decade, which is probably related to the increase in species introductions worldwide. Among some important gaps that need to be filled, the relatively small number of studies conducted in developing countries and in aquatic environments deserves careful attention.

【 授权许可】

CC BY   
 All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License

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