...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>BMC Ecology >Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa
【24h】

Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa

机译：数据贫乏国家的空间保护优先级：使用多个分类群的定量敏感性分析

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Spatial conservation prioritisation (SCP) is a set of computational tools designed to support the efficient spatial allocation of priority areas for conservation actions, but it is subject to many sources of uncertainty which should be accounted for during the prioritisation process. We quantified the sensitivity of an SCP application (using software Zonation) to possible sources of uncertainty in data-poor situations, including the use of different surrogate options; correction for sampling bias; how to integrate connectivity; the choice of species distribution modelling (SDM) algorithm; how cells are removed from the landscape; and two methods of assigning weights to species (red-list status or prediction uncertainty). Further, we evaluated the effectiveness of the Egyptian protected areas for conservation, and spatially allocated the top priority sites for further on-the-ground evaluation as potential areas for protected areas expansion. Focal taxon (butterflies, reptiles, and mammals), sampling bias, connectivity and the choice of SDM algorithm were the most sensitive parameters; collectively these reflect data quality issues. In contrast, cell removal rule and species weights contributed much less to overall variability. Using currently available species data, we found the current effectiveness of Egypt’s protected areas for conserving fauna was low. For SCP to be useful, there is a lower limit on data quality, requiring data-poor countries to improve sampling strategies and data quality to obtain unbiased data for as many taxa as possible. Since our sensitivity analysis may not generalise, conservation planners should use sensitivity analyses more routinely, particularly relying on more than one combination of SDM algorithm and surrogate group, consider correction for sampling bias, and compare the spatial patterns of predicted priority sites using a variety of settings. The sensitivity of SCP to connectivity parameters means that the responses of each species to habitat loss are important knowledge gaps.
机译：空间保护优先级排序（SCP）是一组旨在支持保护行动的优先级区域的有效空间分配的一组计算工具，但它受到许多不确定性的来源，应在优先级过程中占核算。我们量化了SCP应用程序（使用软件区划）对数据不可确定的情况的可能源的敏感性，包括使用不同的替代方案;取样偏差的纠正;如何整合连接;物种分布建模（SDM）算法的选择;细胞如何从景观中移除;分配给物种的权重（红色列表状态或预测不确定性）的两种方法。此外，我们评估了埃及保护区的保护区的有效性，并在空间地分配了最优先级地点，以进一步在地面评估中作为保护区扩张的潜在领域。焦点分类（蝴蝶，爬行动物和哺乳动物），采样偏置，连接和SDM算法的选择是最敏感的参数;集体这些反映了数据质量问题。相比之下，细胞去除规则和物种重量对整体变异性贡献得多。使用目前可用的物种数据，我们发现埃及保护区保护区的当前有效性低。对于SCP有用，数据质量有较低的限制，需要数据较差国家来改善采样策略和数据质量，以获得尽可能多的分类群的无偏见数据。由于我们的敏感性分析可能没有概括，因此保护规划者应更常规地使用敏感性分析，特别是依赖于SDM算法和代理组的多种组合，考虑采样偏置的校正，并使用各种比较预测优先级站点的空间模式设置。 SCP对连接参数的敏感性意味着每个物种对栖息地损失的响应是重要的知识差距。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号