Theories, Vectors, and Computer Models: Marine Invasion Science in the Anthropocene
Theories, Vectors, and Computer Models: Marine Invasion Science in the Anthropocene
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理论、向量和计算机模型:人类世的海洋入侵科学
DOI:
10.1007/978-3-030-20389-4_10
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发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Llanos SD
中科院分区:
文献类型:
--
作者:
Laeseke PL;Schiller J;Letschert J;Llanos SD
Marine invasions are well-recognized as a worldwide threat to biodiversity and cause for tremendous economic damage. Fundamental aspects in invasion ecology are not yet fully understood, as there is neither a clear definition of invasive species nor their characteristics. Likewise, regulations to tackle marine invasions are fragmentary and either restricted to specific regions or certain aspects of the invasion process. Nonetheless, marine anthropogenic vectors (eg, vessel fouling, ballast water, aquaculture, marine static structures, floating debris, and human-mediated climate change) are well described. The most important distribution vector for marine nonindigenous species is the shipping sector, composed by vessel fouling and ballast water discharge. Ship traffic is a constantly growing sector, as not only ship sizes are increasing, but also remote environments such as the polar regions are becoming accessible for commercial use. To mitigate invasions, it is necessary to evaluate species’ capability to invade a certain habitat, as well as the risk of a region of becoming invaded. On an ecological level, this may be achieved by Ecological Niche Modelling based on environmental data. In combination with quantitative vector data, sophisticated species distribution models may be developed. Especially the ever-increasing amount of available data allows for comprehensive modelling approaches to predict marine invasions and provide valuable information for policy makers. For this article, we reviewed available literature to provide brief insights into the backgrounds and regulations of major marine vectors, as well as species distribution modelling. Finally, we present some state-of-the-art modelling approaches based on ecological and vector data, beneficial for realistic risk assessments.
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影响因子:
4.6
作者:
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发表时间:
2005
期刊:
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作者:
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DOI:
--
发表时间:
1987
期刊:
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作者:
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