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Identifying marine invasion hotspots using stacked species distribution models
Biological Invasions ( IF 2.8 ) Pub Date : 2020-08-29 , DOI: 10.1007/s10530-020-02332-3
Devin A. Lyons , J. Ben Lowen , Thomas W. Therriault , David Brickman , Lanli Guo , Andrea M. Moore , M. Angelica Peña , Zeliang Wang , Claudio DiBacco

Early detection and management of aquatic invasive species requires identification of those areas most at risk of invasion (i.e., hotspots). Here we identify present-day and future hotspots of invasion risk for marine invertebrates and algae in nearshore habitats of the northwest Atlantic and northeast Pacific using more than 12 years of monitoring data in conjunction with other occurrence data and stacked species distribution models. The stacked species distribution models predicted the general patterns of observed invasive species richness in both study areas (Atlantic: r2 = 0.52, Pacific: r2 = 0.42). In the northwest Atlantic, we identified hotspots through much of Massachusetts, New Hampshire and southern Maine, and in several bays in southwestern New Brunswick and Nova Scotia. In the northeast Pacific, much of the southern Salish Sea was identified as a hotspot, as were a few areas along the outer coast of Washington and Oregon. Projecting our species distribution modelling results to 2075 (climate scenario RCP 8.5), we found that existing hotspots are likely to expand slightly in the Atlantic, while in the Pacific existing hotspots are predicted to shift or expand, new hotspots are likely to appear, and areas with few invasive species attaining moderate invasive species richness. Our results suggest that climate change will have larger effects on the distributions of our focal invasive species on the Pacific coast compared to the Atlantic. Resultant hotspot maps provide an integrated perspective and guidance to managers tasked with prioritizing locations for monitoring and implementing policy related to marine invasive species, with projected hotspots making planning for future changes in invasion risk possible.



中文翻译:

使用堆叠物种分布模型识别海洋入侵热点

早期发现和管理水生入侵物种需要确定最容易受到入侵的区域(即热点)。在这里,我们使用12年以上的监测数据,结合其他事件数据和堆积物种分布模型,确定了西北大西洋和东北太平洋近岸生境中海洋无脊椎动物和藻类入侵风险的当前和未来热点。堆叠的物种分布模型预测了两个研究区域中观察到的入侵物种丰富度的一般模式(大西洋:r 2  = 0.52,太平洋:r 2 = 0.42)。在西北大西洋,我们确定了马萨诸塞州,新罕布什尔州和缅因州南部以及新不伦瑞克西南部和新斯科舍省多个海湾中的热点地区。在东北太平洋,南部的萨利什海大部分地区都被确定为热点,华盛顿和俄勒冈外沿岸的一些地区也被确定为热点。将我们的物种分布模型结果预测到2075年(气候情景RCP 8.5),我们发现大西洋现有的热点可能会略有扩展,而太平洋地区的现有热点预计会发生转移或扩展,新的热点可能会出现,并且入侵物种很少的地区获得适度的入侵物种丰富度。我们的结果表明,与大西洋相比,气候变化将对我们在太平洋沿岸的重点入侵物种的分布产生更大的影响。最终的热点地图为负责优先安排位置以监测和实施与海洋入侵物种有关的政策的管理人员提供了综合的观点和指导,而预计的热点使规划未来入侵风险的变化成为可能。

更新日期:2020-08-29
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