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首页> 外文期刊>Ocean & coastal management >Predictive habitat models for managing marine areas: Spatial and temporal distribution of marine mammals within the Pelagos Sanctuary (Northwestern Mediterranean sea)
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Predictive habitat models for managing marine areas: Spatial and temporal distribution of marine mammals within the Pelagos Sanctuary (Northwestern Mediterranean sea)

机译：用于管理海洋区域的预测栖息地模型：Pelagos保护区（西北地中海）内海洋哺乳动物的时空分布

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摘要

Habitat use of seven different species of cetaceans inhabiting the Pelagos Sanctuary was studied using 18-year summer shipboard surveys data, in an area of approximately 25,000 km2. 2940 sightings were collected: 1996 striped dolphins, 626 fin whales, 120 Risso's dolphins, 114 sperm whales, 27 common bottlenose dolphins, 25 long-finned pilot whales, 23 Cuvier's beaked whales. Stepwise Logistic Regression Analysis was used to develop presence/absence predictive models. Statistics of depth and slope were used as covariates. Significant correlations were outlined (P < 0.05) supporting the hypothesis that physiographic factors may be employed as predictors of the species presence. The temporal variability of the species habitat use was also analyzed, confirming the reliability of the physiographic predictors. Temporal trends and variability in the species distribution were also assessed through a GLM analysis. The understanding offered by this long-term study is essential for managing the conservation status of these wide-ranging species.
机译：利用18年夏季船上调查数据，研究了居住在Pelagos保护区的7种不同种类的鲸类动物的栖息地，面积约为25,000 km2。目睹了2940个目击事件：1996年条纹海豚，626头鲸，120里索海豚，114抹香鲸，27只普通宽吻海豚，25头长鳍long鲸，23只居维叶喙鲸。逐步Logistic回归分析用于开发存在/不存在的预测模型。深度和斜率的统计用作协变量。概述了显着的相关性（P <0.05），支持以下假设：生理因素可以用作物种存在的预测因子。还分析了物种栖息地使用的时间变异性，证实了生理预测因子的可靠性。还通过GLM分析评估了物种分布的时间趋势和变异性。这项长期研究提供的理解对于管理这些广泛物种的保护状况至关重要。

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  • 来源
    《Ocean & coastal management》 |2012年第10期|p.63-74|共12页
  • 作者

    A. Azzellino; S. Panigada; C. Lanfredi; M. Zanardelli; S. Airoldi; G. Notarbartolo di Sciara;

  • 作者单位

    Politecnico di Milano, University of Technology, DIIAR Environmental Engineering Division, Piazza Leonardo da Vinci 32, 20133 Milano, Italy,Tethys Research Institute, Viale G.B. Cadio 2, 20121 Milano, Italy;

    Tethys Research Institute, Viale G.B. Cadio 2, 20121 Milano, Italy;

    Politecnico di Milano, University of Technology, DIIAR Environmental Engineering Division, Piazza Leonardo da Vinci 32, 20133 Milano, Italy,Tethys Research Institute, Viale G.B. Cadio 2, 20121 Milano, Italy;

    Tethys Research Institute, Viale G.B. Cadio 2, 20121 Milano, Italy;

    Tethys Research Institute, Viale G.B. Cadio 2, 20121 Milano, Italy;

    Tethys Research Institute, Viale G.B. Cadio 2, 20121 Milano, Italy;

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