...
首页> 外文期刊>Management of Biological Invasions >A framework for aquatic invasive species surveillance site selection and prioritization in the US waters of the Laurentian Great Lakes
【24h】

A framework for aquatic invasive species surveillance site selection and prioritization in the US waters of the Laurentian Great Lakes

机译:水生侵入物种监视场地选择和优先级的劳伦特湖大湖水域框架

获取原文
   

获取外文期刊封面封底 >>

       

摘要

Risk-based prioritization for early detection monitoring is of utmost importance to prevent and mitigate invasive species impacts and is especially needed for large ecosystems where management resources are not sufficient to survey all locations susceptible to invasion. In this paper we describe a spatially-explicit and quantitative approach for identifying the highest risk sites for aquatic invasive species (AIS) introduction into the United States’ waters of the Laurentian Great Lakes, a vast inland sea with a surface area of 246,049 square km and a shoreline length of 16,431 km. We compiled data from geospatial metrics available across all of the US waters of the Great Lakes as surrogates for propagule pressure from the dominant AIS pathways. Surrogates were weighted based on the observed or expected contribution of each pathway to past (historic) and predicted future invasions. Weighted surrogate data were combined to generate “invasion risk” scores for plants, invertebrates, fish, and all taxa combined at 3,487 management units (9 km × 9 km). The number of sites with invasion risk scores 0 is: for plants (490), for invertebrates (220), for fish (436), and for all taxa (403). The rank order of sites with the highest risk scores varies by taxa, but in general the top thirty highest risk sites are the same across all groups. For all taxonomic groups, we show that the “top 30” sites account for at least 50% of predicted propagule pressure to the basin from all pathways. Many of the highest risk sites are located in western Lake Erie, southern Lake Michigan, and the St. Clair-Detroit River System. This framework provides a starting point for objective surveillance planning and implementation that can be adaptively improved.
机译:早期检测监测的风险优先级至关重要,最重要的是预防和减轻侵入性物种的影响,并且特别需要对管理资源不足以调查易受入侵的所有地点的大型生态系统。在本文中,我们描述了一种空间显式和定量的方法,用于识别水生侵入性物种(AIS)的最高风险部位(AIS)介绍劳伦特岛大湖泊的水域,这是一个巨大的内陆海域,占地面积246,049平方公里和海岸线长度为16,431公里。我们从大湖泊所有美国水域提供的地理空间指标中汇编了数据作为来自主导AIS途径的传播压力的替代品。基于每种途径到过去(历史)的观察到或预期贡献以及预测未来入侵的替代品。加权替代数据被组合以产生植物,无脊椎动物,鱼类的“入侵风险”分数,并在3,487个管理单位(9公里×9公里)。入侵风险评分的网站数量> 0是:用于植物(490),用于无脊椎动物(220),用于鱼(436),以及所有分类群(403)。风险评分最高的站点的排名顺序因分类群而异,但一般来说,所有群体中最高的最高风险网站都是相同的。对于所有分类组,我们表明“前30名”网站占所有途径的预测传播压力的至少50%。许多最高风险位点位于西湖Erie,Michigan南部和圣克莱特罗特河系统。该框架为客观监视规划和实现提供了可以自适应地改进的起点。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号