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原文連結
論文資訊
- 類型：已發表論文
- 日期：2012
摘要
The world's oceans are undergoing profound changes as a result of human activities. However, the consequences of escalating human impacts on 海洋 mammal 生物多樣性 remain poorly understood. The International Union for the Conservation of Nature (IUCN) identifies 25% of 海洋 mammals as at risk of extinction, but the conservation status of nearly 40% of 海洋 mammals remains unknown due to insufficient data. Predictive models of extinction risk are crucial to informing present and future conservation needs, yet such models have not been developed for 海洋 mammals. In this paper, we: (i) used powerful machine-learning and spatial-modeling approaches to understand the intrinsic and extrinsic drivers of 海洋 mammal extinction risk; (ii) used this 資訊 to predict risk across all 海洋 mammals, including IUCN "Data D
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