Uncertainty analysis and robust areas of high and low modeled human impact on the global oceans: Human-Impact Areas
Uncertainty analysis and robust areas of high and low modeled human impact on the global oceans: Human-Impact Areas
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不确定性分析和人类对全球海洋影响高低模型的稳健区域：人类影响区域
DOI：
10.1111/cobi.13141
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发表时间：
2018
影响因子：
6.3
通讯作者：
Micheli, Fiorenza
中科院分区：
文献类型：
--
作者：
Stock, Andy;Crowder, Larry B.;Halpern, Benjamin S.;Micheli, Fiorenza
捕捞、污染、气候变化和其他来源对海洋生态系统造成的人为压力不断增加，是海洋保护领域的一个重大问题。因此，科学家们开发了空间模型来绘制人类对海洋生态系统的累积影响。然而，这些模型基于许多假设，并包含大量不完整和不准确的数据。我们没有使用单一模型，而是使用蒙特卡洛模拟来确定海洋的哪些部分在 7 个模拟的不确定性来源（因素：例如，缺少压力源数据和假设生态系统对压力的线性响应）下受到人为压力源的影响最大和最小。大多数地图一致认为，高影响区域位于东北大西洋、东地中海、加勒比海、西非北部大陆架、热带大西洋近海部分、马达加斯加以东的印度洋、东亚和东南亚部分地区、西北太平洋部分地区以及许多沿海水域。大片低影响地区位于南极洲附近、太平洋中部和大西洋南部。模拟人类影响的大范围空间分布的不确定性是由多种因素的总体影响造成的，而不是归因于单一的主要来源。尽管人类影响地图中存在确定的不确定性，但它们可以在广泛的空间尺度上并与其他环境和社会经济信息相结合，指出研究和管理的优先领域。
Increasing anthropogenic pressure on marine ecosystems from fishing, pollution, climate change, and other sources is a big concern in marine conservation. Scientists have thus developed spatial models to map cumulative human impacts on marine ecosystems. However, these models are based on many assumptions and incorporate data that suffer from substantial incompleteness and inaccuracies. Rather than using a single model, we used Monte Carlo simulations to identify which parts of the oceans are subject to the most and least impact from anthropogenic stressors under 7 simulated sources of uncertainty (factors: e.g., missing stressor data and assuming linear ecosystem responses to stress). Most maps agreed that high‐impact areas were located in the Northeast Atlantic, the eastern Mediterranean, the Caribbean, the continental shelf off northern West Africa, offshore parts of the tropical Atlantic, the Indian Ocean east of Madagascar, parts of East and Southeast Asia, parts of the northwestern Pacific, and many coastal waters. Large low‐impact areas were located off Antarctica, in the central Pacific, and in the southern Atlantic. Uncertainty in the broad‐scale spatial distribution of modeled human impact was caused by the aggregate effects of several factors, rather than being attributable to a single dominant source. In spite of the identified uncertainty in human‐impact maps, they can—at broad spatial scales and in combination with other environmental and socioeconomic information—point to priority areas for research and management.