MaxEnt analysis of Ochotona rufescens, Oumm Qatafa
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For pika, we collected the coordinates of 35 find spots of recent and sub-recent <em>O. rufescens</em> (Čermák et al. 2006; Khaki-Saneh 2014), a set of rasters representing current (1979 - 2013) climate based on standard 19 bioclim variables at 10-min resolution (Anthropocene, v1.2b: https://chelsa-climate.org/). These data were used to construct a Maximum Entropy model for the current distribution of the Afghan pika using the ‘maxnet’ package (Phillips 2021) in R (version 4.0.2). Other libraries used include ‘terra’ (Hijman 2021) and ‘modEvA’ (Barbosa et al. 2013). The model provided a list of variables that parsimoniously predict suitable environments for the Afghan pika, and also a projection of the probability of finding suitable habitats, as defined by the bioclimatic variables, in geographical space under present-day conditions. The values of the selected model bioclimatic variables at the present find spots were compared with the same values for Oumm Qatafa to examine its present climatic suitability as a habitat for pikas. Barbosa, A.M., Real, R., Munoz, A.R. & Brown, J.A. (2013). New measures for assessing model equilibrium and prediction mismatch in species distribution models. Diversity and Distributions, 19(10), 1333-1338. https://onlinelibrary.wiley.com/doi/full/10.1111/ddi.12100. Čermák, S., Obuch, S., Benda, P. (2006). Notes on the genus <em>Ochotona</em> in the Middle East (Lagomorpha: Ochotonidae). <em>Lynx</em> (Praha) 37, 51–66. Hijmans, R.J. (2021). terra: Spatial Data Analysis. R package version 1.5-8. https://rspatial.org/terra/ Khaki Sahneh, S., Nouri, Z., Alizadeh Shabani, A., Dehdar Dargahi, M. (2014). A review on habitats selection by Afghan Pika (<em>Ochotona rufescens</em>), case study: the Lashgardar protected area in Hamadan Province. <em>Journal on New Biological Reports</em> 3(3), 186–199. Phillips, S. (2021). maxnet: Fitting 'Maxent' Species Distribution Models with 'glmnet'. R package version 0.1.4. https://CRAN.R-project.org/package=maxnet.
本研究采集了近期及亚近期红耳鼠兔（Ochotona rufescens）的35个发现点位坐标（Čermák等，2006；Khaki-Saneh，2014），并采用源自CHELSA气候数据库Anthropocene v1.2b版本的1979-2013年当前气候栅格数据，该数据集包含19个标准生物气候变量，分辨率为10角分（https://chelsa-climate.org/）。 基于上述数据，本研究在R语言（版本4.0.2）中借助maxnet包（Phillips，2021）构建了阿富汗鼠兔当前分布的最大熵模型（Maximum Entropy model），所用其他R包包括terra（Hijmans，2021）与modEvA（Barbosa等，2013）。 该模型筛选出可简约预测阿富汗鼠兔适宜生境环境的变量，并基于当前生物气候变量，在地理空间中投影得到了适宜生境的分布概率。本研究将当前发现点位处筛选出的生物气候变量取值与乌姆卡塔法（Oumm Qatafa）的对应变量取值进行对比，以评估该区域作为鼠兔生境的当前气候适宜性。 参考文献： 1. Barbosa, A.M., Real, R., Muñoz, A.R. & Brown, J.A. (2013). 物种分布模型的模型均衡性与预测偏差评估新指标. 《多样性与分布》, 19(10), 1333-1338. https://onlinelibrary.wiley.com/doi/full/10.1111/ddi.12100. 2. Čermák, S., Obuch, S., Benda, P. (2006). 中东地区鼠兔属笔记（兔形目：鼠兔科）. 《Lynx (布拉格版)》37, 51–66. 3. Hijmans, R.J. (2021). terra：空间数据分析. R包版本1.5-8. https://rspatial.org/terra/ 4. Khaki Sahneh, S., Nouri, Z., Alizadeh Shabani, A., Dehdar Dargahi, M. (2014). 阿富汗鼠兔（Ochotona rufescens）生境选择研究综述——以哈马丹省拉什加尔达尔保护区为例. 《新生物学报告杂志》3(3), 186–199. 5. Phillips, S. (2021). maxnet：基于glmnet拟合最大熵物种分布模型. R包版本0.1.4. https://CRAN.R-project.org/package=maxnet.
