Seebens Hanno, Schwartz Nicole, Schupp Peter J, Blasius Bernd
Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, 26111 Oldenburg, Germany; Department of Botany and Biodiversity Research, University of Vienna, 1030 Vienna, Austria; Senckenberg Biodiversity and Climate Research Centre, 60325 Frankfurt, Germany
Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, 26111 Oldenburg, Germany;
Proc Natl Acad Sci U S A. 2016 May 17;113(20):5646-51. doi: 10.1073/pnas.1524427113. Epub 2016 Apr 18.
The human-mediated translocation of species poses a distinct threat to nature, human health, and economy. Although existing models calculate the invasion probability of any species, frameworks for species-specific forecasts are still missing. Here, we developed a model approach using global ship movements and environmental conditions to simulate the successive global spread of marine alien species that allows predicting the identity of those species likely to arrive next in a given habitat. In a first step, we simulated the historical stepping-stone spreading dynamics of 40 marine alien species and compared predicted and observed alien species ranges. With an accuracy of 77%, the model correctly predicted the presence/absence of an alien species in an ecoregion. Spreading dynamics followed a common pattern with an initial invasion of most suitable habitats worldwide and a subsequent spread into neighboring habitats. In a second step, we used the reported distribution of 97 marine algal species with a known invasion history, and six species causing harmful algal blooms, to determine the ecoregions most likely to be invaded next under climate warming. Cluster analysis revealed that species can be classified according to three characteristic spreading profiles: emerging species, high-risk species, and widespread species. For the North Sea, the model predictions could be confirmed because two of the predicted high-risk species have recently invaded the North Sea. This study highlights that even simple models considering only shipping intensities and habitat matches are able to correctly predict the identity of the next invading marine species.
人类介导的物种迁移对自然、人类健康和经济构成了独特的威胁。尽管现有模型可以计算任何物种的入侵概率,但针对特定物种预测的框架仍然缺失。在此,我们开发了一种模型方法,利用全球船舶运输和环境条件来模拟海洋外来物种在全球范围内的连续扩散,从而能够预测下一个可能进入特定栖息地的物种身份。第一步,我们模拟了40种海洋外来物种的历史踏脚石式扩散动态,并比较了预测的和观察到的外来物种分布范围。该模型以77%的准确率正确预测了生态区域中外来物种的存在/不存在情况。扩散动态遵循一种常见模式,即首先入侵全球最适宜的栖息地,随后扩散到邻近栖息地。第二步,我们利用97种有已知入侵历史的海洋藻类物种以及6种导致有害藻华的物种的报告分布情况,来确定在气候变暖情况下最有可能接下来被入侵的生态区域。聚类分析表明,物种可根据三种特征性扩散模式进行分类:新兴物种、高风险物种和广泛分布物种。对于北海而言,模型预测得到了证实,因为预测出的两种高风险物种最近已入侵北海。这项研究强调,即使是仅考虑航运强度和栖息地匹配情况的简单模型,也能够正确预测下一个入侵的海洋物种身份。