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SPATIAL AND TEMPORAL PATTERNS OF ELEPHANT MORTALITY IN NAROK COUNTY, KENYA

机译:肯尼亚纳罗克县大象死亡率的空间和时间模式

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This study aimed at determining the spatial temporal patterns of elephant mortality in Narok County using data from Kenya Wildlife Service (KWS) and World Wide Fund for Nature-Human-elephant Conflict (WWF-HEC) project compiled over the last 11 years. Field monitoring for one year was also carried out and any dead elephant was identified and details recorded to determine causes of mortality and distribution. Data were entered in an Excel spreadsheet and then converted into dBASE IV format and imported to ArcGIS to create a point shape file of elephant mortality and associated attribute data. Graphs and map were generated linking mortality with other aspects. Data obtained using qualitative research method was analysed using the Statistical Package for Social Sciences (SPSS). Frequencies obtained were calculated, and where appropriate, a chi-square test was used. A 0.05 level of significance was used to determine existing relationships between data categories. Results showed that most elephant mortality occurred outside the protected area (MMNR) and were due to trophy poaching (61.5%, n=13) which occurred during long rainy seasons and in dense bush lands. There was a significant difference in mortality cases during the short rain season (χ~2=4.500, df=1, p=0.034). Kernel density analysis depicted Olesentu and Sitoka in TM as hotspot area for elephant mortality due to trophy poaching. Elephant mortality due to conflicts occurred mostly on agricultural land with 10 (50%) cases. From the results, it was evident that elephant the distribution and pattern of elephant mortality is determined by several factors among them, Rainfall, vegetation cover, proximity to water source, roads and human settlement.
机译:该研究旨在确定奈良县大象死亡率的空间时间模式,使用来自肯尼亚野生动物服务(KWS)的数据和全球性质 - 人类大象冲突(WWF-HEC)项目在过去11年内编制的。还进行了一年的现场监测,并确定了任何死角,并记录了细节,以确定死亡率和分配的原因。数据在Excel电子表格中输入,然后转换为DBase IV格式,并导入ArcGIS以创建大象死亡率和相关属性数据的点形状文件。使用其他方面将死亡率与其他方面引起图形和地图。使用定性研究方法获得的数据使用统计包来分析社会科学(SPSS)。计算得出的频率,在适当的情况下,使用Chi-Square测试。使用0.05级的意义来确定数据类别之间的现有关系。结果表明,大多数大象死亡率发生在保护区外(MMNR)外,并且由于长雨季和茂密的灌木陆地发生奖杯偷猎(61.5%,n = 13)。在短雨季期间死亡案例有显着差异(χ〜2 = 4.500,df = 1,p = 0.034)。内核密度分析描绘了Olesentu和Sitoka在TM中作为热点区域因奖杯偷猎而导致的大象死亡率。由于冲突导致的大象死亡率主要发生在农业用地10(50%)案件。结果从结果中明显,大象的分布和模式的大象死亡率是由它们之间的几个因素决定,降雨,植被覆盖,水源,道路和人类沉降的近似。

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