4.6 Article

Uncertainty analysis and robust areas of high and low modeled human impact on the global oceans

期刊

CONSERVATION BIOLOGY
卷 32, 期 6, 页码 1368-1379

出版社

WILEY
DOI: 10.1111/cobi.13141

关键词

cumulative effects; mapping; marine; multiple stressors; sensitivity analysis; uncertainty

资金

  1. Goldman Graduate Fellowship from the Stanford Woods Institute for the Environment
  2. Gordon and Betty Moore Foundation
  3. Stanford Center for Ocean Solutions
  4. US NSF-CNH program [DEB-1212124, OCE-1736830]

向作者/读者索取更多资源

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.

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