{"title":"乌克兰草原鼠Spicilegus(啮齿类,鼠科)的生物气候生态位和分布模型","authors":"V. Tytar, I. I. Kozinenko, S. Mezhzherin","doi":"10.2478/vzoo-2019-0042","DOIUrl":null,"url":null,"abstract":"Abstract The Steppe mouse, Mus spicilegus, is endemic to Europe and found to be expanding its home range in recent years. In Ukraine there are indications a north- and eastwards expansion and/or reestablishment of M. spicilegus. We suggest that climatic conditions may be the primary factors that foster or limit the range expansion of M. spicilegus in Eastern Europe. Our objective was to complement the knowledge about the distribution of the species with an estimation of the potential distribution of the species in Ukraine using known occurrence sites (in Ukraine and neighbouring areas) and environmental variables in an ecological niche modelling algorithm. After accounting for sampling bias and spatial autocorrelation, we retained 73 occurrence records. The algorithm used in this paper, Maxent (Phillips et al., 2006), is a machine learning algorithm and only needs presence data, besides the environmental layers. Using this approach, we have highlighted the importance and significance of a number of bioclimatic variables, particularly those characterizing wintering conditions, under which higher mean temperatures enhance habitat suitability, whereas increased precipitation leads to an opposite effect. The broadly northwards shift of the home range of the species in Ukraine could generally be due to the increasing (since the 1980s) mean temperature of the winter season. We expect this expansion process will continue together with the changing climate and new records of locations of the species may be used for monitoring such change.","PeriodicalId":206426,"journal":{"name":"Vestnik Zoologii","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modelling the Bioclimatic Niche and Distribution of the Steppe Mouse, Mus Spicilegus (Rodentia, Muridae), in Ukraine\",\"authors\":\"V. Tytar, I. I. Kozinenko, S. Mezhzherin\",\"doi\":\"10.2478/vzoo-2019-0042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The Steppe mouse, Mus spicilegus, is endemic to Europe and found to be expanding its home range in recent years. In Ukraine there are indications a north- and eastwards expansion and/or reestablishment of M. spicilegus. We suggest that climatic conditions may be the primary factors that foster or limit the range expansion of M. spicilegus in Eastern Europe. Our objective was to complement the knowledge about the distribution of the species with an estimation of the potential distribution of the species in Ukraine using known occurrence sites (in Ukraine and neighbouring areas) and environmental variables in an ecological niche modelling algorithm. After accounting for sampling bias and spatial autocorrelation, we retained 73 occurrence records. The algorithm used in this paper, Maxent (Phillips et al., 2006), is a machine learning algorithm and only needs presence data, besides the environmental layers. Using this approach, we have highlighted the importance and significance of a number of bioclimatic variables, particularly those characterizing wintering conditions, under which higher mean temperatures enhance habitat suitability, whereas increased precipitation leads to an opposite effect. The broadly northwards shift of the home range of the species in Ukraine could generally be due to the increasing (since the 1980s) mean temperature of the winter season. We expect this expansion process will continue together with the changing climate and new records of locations of the species may be used for monitoring such change.\",\"PeriodicalId\":206426,\"journal\":{\"name\":\"Vestnik Zoologii\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Vestnik Zoologii\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/vzoo-2019-0042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vestnik Zoologii","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/vzoo-2019-0042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
草原鼠(Mus spicilegus)是欧洲特有的鼠类,近年来发现其活动范围正在扩大。在乌克兰有向北和向东扩张和/或重建的迹象。我们认为,气候条件可能是促进或限制spicilegus在东欧扩展范围的主要因素。我们的目标是利用已知的发生地点(在乌克兰和邻近地区)和生态位建模算法中的环境变量来估计乌克兰物种的潜在分布,以补充有关物种分布的知识。在考虑了抽样偏差和空间自相关后,我们保留了73条发生记录。本文使用的算法Maxent (Phillips et al., 2006)是一种机器学习算法,除了环境层之外,只需要在场数据。使用这种方法,我们强调了一些生物气候变量的重要性和意义,特别是那些表征冬季条件的变量,在这些变量下,较高的平均温度会增强栖息地的适宜性,而增加的降水会导致相反的效果。该物种在乌克兰的栖息地广泛向北移动,通常可能是由于冬季平均温度的增加(自20世纪80年代以来)。我们预计,随着气候的变化,这一扩展过程将继续下去,物种位置的新记录可用于监测这种变化。
Modelling the Bioclimatic Niche and Distribution of the Steppe Mouse, Mus Spicilegus (Rodentia, Muridae), in Ukraine
Abstract The Steppe mouse, Mus spicilegus, is endemic to Europe and found to be expanding its home range in recent years. In Ukraine there are indications a north- and eastwards expansion and/or reestablishment of M. spicilegus. We suggest that climatic conditions may be the primary factors that foster or limit the range expansion of M. spicilegus in Eastern Europe. Our objective was to complement the knowledge about the distribution of the species with an estimation of the potential distribution of the species in Ukraine using known occurrence sites (in Ukraine and neighbouring areas) and environmental variables in an ecological niche modelling algorithm. After accounting for sampling bias and spatial autocorrelation, we retained 73 occurrence records. The algorithm used in this paper, Maxent (Phillips et al., 2006), is a machine learning algorithm and only needs presence data, besides the environmental layers. Using this approach, we have highlighted the importance and significance of a number of bioclimatic variables, particularly those characterizing wintering conditions, under which higher mean temperatures enhance habitat suitability, whereas increased precipitation leads to an opposite effect. The broadly northwards shift of the home range of the species in Ukraine could generally be due to the increasing (since the 1980s) mean temperature of the winter season. We expect this expansion process will continue together with the changing climate and new records of locations of the species may be used for monitoring such change.