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整合海洋物种分布数据以更好地服务于科学研究和保护工作。

Aligning marine species range data to better serve science and conservation.

作者信息

O'Hara Casey C, Afflerbach Jamie C, Scarborough Courtney, Kaschner Kristin, Halpern Benjamin S

机构信息

National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, CA, United States of America.

Department of Biometry and Environmental Systems Analysis, Albert-Ludwigs University, Tennenbacher Straße 4, Freiburg i. Br., Germany.

出版信息

PLoS One. 2017 May 3;12(5):e0175739. doi: 10.1371/journal.pone.0175739. eCollection 2017.

Abstract

Species distribution data provide the foundation for a wide range of ecological research studies and conservation management decisions. Two major efforts to provide marine species distributions at a global scale are the International Union for Conservation of Nature (IUCN), which provides expert-generated range maps that outline the complete extent of a species' distribution; and AquaMaps, which provides model-generated species distribution maps that predict areas occupied by the species. Together these databases represent 24,586 species (93.1% within AquaMaps, 16.4% within IUCN), with only 2,330 shared species. Differences in intent and methodology can result in very different predictions of species distributions, which bear important implications for scientists and decision makers who rely upon these datasets when conducting research or informing conservation policy and management actions. Comparing distributions for the small subset of species with maps in both datasets, we found that AquaMaps and IUCN range maps show strong agreement for many well-studied species, but our analysis highlights several key examples in which introduced errors drive differences in predicted species ranges. In particular, we find that IUCN maps greatly overpredict coral presence into unsuitably deep waters, and we show that some AquaMaps computer-generated default maps (only 5.7% of which have been reviewed by experts) can produce odd discontinuities at the extremes of a species' predicted range. We illustrate the scientific and management implications of these tradeoffs by repeating a global analysis of gaps in coverage of marine protected areas, and find significantly different results depending on how the two datasets are used. By highlighting tradeoffs between the two datasets, we hope to encourage increased collaboration between taxa experts and large scale species distribution modeling efforts to further improve these foundational datasets, helping to better inform science and policy recommendations around understanding, managing, and protecting marine biodiversity.

摘要

物种分布数据为广泛的生态研究和保护管理决策提供了基础。在全球范围内提供海洋物种分布的两项主要工作分别是:国际自然保护联盟(IUCN),它提供由专家生成的范围图,勾勒出一个物种分布的完整范围;以及AquaMaps,它提供由模型生成的物种分布图,预测物种占据的区域。这两个数据库总共涵盖了24,586个物种(AquaMaps涵盖93.1%,IUCN涵盖16.4%),只有2,330个物种是两个数据库共有的。意图和方法上的差异可能导致对物种分布的预测大不相同,这对在开展研究或为保护政策及管理行动提供信息时依赖这些数据集的科学家和决策者具有重要意义。通过比较两个数据集中都有的一小部分物种的分布图,我们发现AquaMaps和IUCN的范围图对于许多经过充分研究的物种显示出很强的一致性,但我们的分析突出了几个关键例子,其中引入的误差导致了预测物种范围的差异。特别是,我们发现IUCN的地图大大高估了珊瑚在不适合的深水中的存在,并且我们表明一些AquaMaps计算机生成的默认地图(其中只有5.7%经过专家审核)在物种预测范围的极端处可能会产生奇怪的不连续性。我们通过重复对海洋保护区覆盖范围差距的全球分析来说明这些权衡的科学和管理意义,并发现根据如何使用这两个数据集会得出显著不同的结果。通过强调这两个数据集之间的权衡,我们希望鼓励分类专家与大规模物种分布建模工作之间加强合作,以进一步改进这些基础数据集,从而更好地为围绕理解、管理和保护海洋生物多样性的科学和政策建议提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cde2/5414950/76e884e0c005/pone.0175739.g001.jpg

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