J. Carvalho, L. Martins, J. P. Silva, J. Santos, R. Torres, C. Fonseca
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This method was developed in three distinct phases: i) setting the objectives, ii) analysing pairs of factors through the application of a comparison matrix and iii) its synthesis with the weight assignment that followed a predetermined numeric range according to the ecological requirements of the study species. The variables used in the red deer habitat suitability model included the hydrographic network, asphalted roads, relief aspects and land use. From October 2010 to March 2011, a total of 129 observations along line transects were recorded and used to validate the final model. By using the AUC method it was obtained a success rate of 72%. Our results suggest that this method would be applied on a larger scale being suitable to predict red deer expansion. 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引用次数: 6
摘要
监测种群趋势对野生动物管理至关重要。事实上,在任何保护计划中,确定与栖息地使用和选择有关的环境条件是一项关键任务。本研究的目的是预测马鹿(Cervus elaphus Linnaeus, 1758)在葡萄牙最大的野生种群之一伦巴达国家狩猎区(Lombada National Hunting Area, LNHA)的殖民。在过去的几十年里,马鹿的密度和范围的急剧增加证明了对这一种群进行仔细监测的必要性。该方法采用层次分析法(AHP)和基于矩阵代数的GIS加权空间分析相结合的多准则模型。该方法分为三个不同的阶段:i)设定目标;ii)通过应用比较矩阵分析因子对;iii)根据研究物种的生态要求,按照预定的数字范围分配权重。马鹿生境适宜性模型中使用的变量包括水文网络、沥青路面、地形和土地利用。从2010年10月到2011年3月,共记录了129个沿线样带的观测数据,并用于验证最终模型。采用AUC法,成功率为72%。结果表明,该方法适用于马鹿种群扩张的大规模预测。据我们所知,这是第一次在葡萄牙使用这种方法来评估赤鹿与栖息地的关系。
Habitat suitability model for red deer (Cervus elaphus Linnaeus, 1758): spatial multi-criteria analysis with GIS application
Monitoring population trends is essential in wildlife management. In fact, to identify those environmental conditions linked to habitat use and selection is a key task in any conservation plan. Our aim in this work was predict red deer (Cervus elaphus Linnaeus, 1758) colonization in the Lombada National Hunting Area (LNHA), one of the largest wild populations in Portugal. The sharply increase in density and range of red deer over the last decades justify the careful monitoring of this population. A multi-criteria model using the Analytical Hierarchic Process (AHP) and GIS weighted spatial analysis with matrix algebra techniques were applied in this approach. This method was developed in three distinct phases: i) setting the objectives, ii) analysing pairs of factors through the application of a comparison matrix and iii) its synthesis with the weight assignment that followed a predetermined numeric range according to the ecological requirements of the study species. The variables used in the red deer habitat suitability model included the hydrographic network, asphalted roads, relief aspects and land use. From October 2010 to March 2011, a total of 129 observations along line transects were recorded and used to validate the final model. By using the AUC method it was obtained a success rate of 72%. Our results suggest that this method would be applied on a larger scale being suitable to predict red deer expansion. To our knowledge, this is the first study performed in Portugal using this methodological approach to assess the red deer-habitat relationships.