首页> 外文期刊>Ecological informatics: an international journal on ecoinformatics and computational ecology >Modelling potential habitats for Artemisia sieberi and Artemisia aucheri in Poshtkouh area, central Iran using the maximum entropy model and geostatistics
【24h】

Modelling potential habitats for Artemisia sieberi and Artemisia aucheri in Poshtkouh area, central Iran using the maximum entropy model and geostatistics

机译:使用最大熵模型和地统计学方法对伊朗中部Poshtkouh地区的蒿(Artemisia sieberi)和蒿(Artemisia aucheri)的潜在生境进行建模

获取原文
获取原文并翻译 | 示例
           

摘要

Predicting potential habitats of endemic species is a suitable method for biodiversity conservation and rehabilitation of rangeland ecosystems. The present study was conducted to estimate the geographic distribution of Artemisia sieberi (A. sieberi) and Artemisia aucheri (A. aucheri), find the most important environmental predictor variables and seek for similarities and differences in habitat preferences between the two species for Poshtkouh rangelands in Central Iran. Maps of environmental variables were created by means of geographic information system (GIS) and geostatistics. Then predictive distribution maps of both species were produced using the maximum entropy modeling technique (Maxent) and presence-only data. Model accuracy is evaluated by using the area under the curve (AUC). Lime1, gravel1, lime 2 and elevation most significantly affect habitat distribution of A. aucheri, while habitat distribution of A. sieberi is affected by elevation, lime1, am1, lime2, and om2. For both species, elevation has an influence on their potential distributions. However, A. aucheri depends more on elevation, and consequently climate in comparison to A. sieberi. Finally, it is revealed that the potential distribution of A. aucheri is limited mostly to mountainous landscapes while A. sieberi is present in wide ranges of environmental conditions.
机译:预测特有物种的潜在生境是保护生物多样性和恢复牧场生态系统的一种合适方法。进行本研究的目的是估计西蒿(A. sieberi)和青蒿(A. aucheri)的地理分布,找到最重要的环境预测变量,并寻找Poshtkouh牧场这两个物种之间的栖息地偏好的异同。在伊朗中部。环境变量图是通过地理信息系统(GIS)和地统计学创建的。然后,使用最大熵建模技术(Maxent)和仅存在数据生成两种物种的预测分布图。通过使用曲线下的面积(AUC)评估模型的准确性。石灰1,砾石1,石灰2和海拔高度对A. aucheri的栖息地分布影响最大,而西伯利亚i的栖息地分布受海拔,石灰1,am1,石灰2和om2影响。对于这两个物种,海拔高度都会影响它们的潜在分布。但是,与A. sieberi相比,A。aucheri更加依赖海拔,因此更加依赖气候。最后,揭示了A. aucheri的潜在分布主要限于山区景观,而A. sieberi存在于各种环境条件下。

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