...
首页> 外文期刊>Ecological indicators >A probabilistic space-time prism to explore changes in white Stork habitat use in Iran
【24h】

A probabilistic space-time prism to explore changes in white Stork habitat use in Iran

机译:探索伊朗白鹳栖息地使用变化的概率时空棱镜

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Studying bird habitats, particularly, those of endangered birds, facilitates effective conservation efforts. The concept of a probabilistic space-time prism (PSTP), which has been introduced in GIScience circle in recent years, can be used to explore bird habitat selection behaviors. The theoretical methods behind the PSTP approach are based on the assumption that a bird's maximum habitat visit probability occurs along the axis of a prism; however, so far, this approach has not been used in a practical setting. In this paper, using movement data for the White Stork in Iran during the breeding and wintering seasons, the capability of a theoretical PSTP simulation method, named Truncated Brownian Bridge (TBB) was evaluated. To simulate the PSTPs, a Brownian motion variance was used. It was calculated, based on the collected movement data for the calibration of the dispersion parameters, so increasing the accuracy of the results. A comparison between the theoretical results and the movement data shows the method's ability to identify changes in the storks' habitat use was greater in the breeding season than during the wintering season. Also, no significant correlation was found between the predicted results and both the density of land use patches and the evenness of land use classes. (C) 2017 Elsevier Ltd. All rights reserved.
机译:研究鸟类栖息地,特别是濒危鸟类的栖息地,有助于有效的保护工作。近年来在GIS科学界引入的概率时空棱镜(PSTP)概念可用于探索鸟类栖息地的选择行为。 PSTP方法背后的理论方法是基于这样的假设,即鸟类的最大栖息地探访概率是沿着棱镜的轴发生的。但是,到目前为止,这种方法尚未在实际环境中使用。在本文中,利用繁殖和越冬季节伊朗白鹳的运动数据,评估了称为截断布朗桥(TBB)的理论PSTP模拟方法的能力。为了模拟PSTP,使用了布朗运动方差。基于收集的运动数据对色散参数进行校准进行计算,从而提高了结果的准确性。理论结果与运动数据之间的比较表明,在繁殖季节,该方法识别鹳栖息地使用变化的能力比冬季更高。同样,在预测结果与土地利用斑块的密度和土地利用类别的均匀性之间也没有发现显着相关性。 (C)2017 Elsevier Ltd.保留所有权利。

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