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管理者、建模师以及衡量物种分布模型不确定性对海洋区划决策的影响。

Managers, modelers, and measuring the impact of species distribution model uncertainty on marine zoning decisions.

机构信息

NOAA National Centers for Coastal Ocean Science, Biogeography Branch, Silver Spring, Maryland, United States of America.

NOAA National Marine Fisheries Service, Habitat Conservation Division, Saipan, CNMI.

出版信息

PLoS One. 2018 Oct 10;13(10):e0204569. doi: 10.1371/journal.pone.0204569. eCollection 2018.

Abstract

Marine managers routinely use spatial data to make decisions about their marine environment. Uncertainty associated with this spatial data can have profound impacts on these management decisions and their projected outcomes. Recent advances in modeling techniques, including species distribution models (SDMs), make it easier to generate continuous maps showing the uncertainty associated with spatial predictions and maps. However, SDM predictions and maps can be complex and nuanced. This complexity makes their use challenging for non-technical managers, preventing them from having the best available information to make decisions. To help bridge these communication and information gaps, we developed maps to illustrate how SDMs and associated uncertainty can be translated into readily usable products for managers. We also explicitly described the potential impacts of uncertainty on marine zoning decisions. This approach was applied to a case study in Saipan Lagoon, Commonwealth of the Northern Mariana Islands (CNMI). Managers in Saipan are interested in minimizing the potential impacts of personal watercraft (e.g., jet skis) on staghorn Acropora (i.e., Acropora aspera, A. formosa, and A. pulchra), which is an important coral assemblage in the lagoon. We used a recently completed SDM for staghorn Acropora to develop maps showing the sensitivity of zoning options to three different prediction and three different uncertainty thresholds (nine combinations total). Our analysis showed that the amount of area and geographic location of predicted staghorn Acropora presence changed based on these nine combinations. These dramatically different spatial patterns would have significant zoning implications when considering where to exclude and/or allow jet skis operations inside the lagoon. They also show that different uncertainty thresholds may lead managers to markedly different conclusions and courses of action. Defining acceptable levels of uncertainty upfront is critical for ensuring that managers can make more informed decisions, meet their marine resource goals and generate favorable outcomes for their stakeholders.

摘要

海洋管理者通常会使用空间数据来做出有关海洋环境的决策。与这些空间数据相关的不确定性会对这些管理决策及其预期结果产生深远的影响。最近在建模技术方面的进展,包括物种分布模型(SDM),使得更容易生成连续的地图,显示与空间预测和地图相关的不确定性。然而,SDM 预测和地图可能很复杂和微妙。这种复杂性使得非技术管理者难以使用它们,无法获得做出决策的最佳可用信息。为了帮助弥合这些沟通和信息差距,我们开发了地图,以说明如何将 SDM 及其相关不确定性转化为易于管理者使用的产品。我们还明确描述了不确定性对海洋分区决策的潜在影响。这种方法应用于北马里亚纳群岛塞班环礁的案例研究。塞班的管理者有兴趣将个人水上摩托艇(例如水上摩托艇)对鹿角珊瑚(即 Acropora aspera、A. formosa 和 A. pulchra)的潜在影响降到最低,鹿角珊瑚是环礁中一个重要的珊瑚组合。我们使用最近完成的鹿角珊瑚 SDM 来开发地图,展示分区选项对三种不同预测和三种不同不确定性阈值(共九种组合)的敏感性。我们的分析表明,根据这九种组合,预测鹿角珊瑚存在的面积和地理位置发生了变化。当考虑在环礁内何处禁止和/或允许水上摩托艇操作时,这些截然不同的空间模式会对分区产生重大影响。它们还表明,不同的不确定性阈值可能导致管理者得出截然不同的结论和行动方案。事先定义可接受的不确定性水平对于确保管理者能够做出更明智的决策、实现其海洋资源目标并为其利益相关者带来有利结果至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95b9/6179233/7ab8ef797b4b/pone.0204569.g001.jpg

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