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Habitat suitability model for black rhinoceros in Augrabies Falls National Park, South Africa

机译:南非奥克拉比斯瀑布国家公园的黑犀栖息地适应性模型

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To assist with identifying land for reintroduction, a habitat suitability model (HSM) for black rhinoceros (Diceros bicornis) was developed in the arid Augrabies Falls National Park, South Africa, from records of sightings, feeding trails and dung middens. Logistic regression and Bayesian Information Criterion were employed to construct and select the best HSM from >35 eco-geographical variables. The modelled and the observed distributions of black rhinos did not differ (P = 0.323) and k-fold cross-validation confirmed the model's ability to predict the distribution of independent data. The HSM consisted of five variables: availability and equitability of three preferred foods, distance to roads, habitat heterogeneity, slope and shade. The variables 'distance to water' and 'rockiness' were also included in the confidence set of models. Only 50% of the study area had a habitat suitability exceeding 11%, but featured 89% of rhino locations. Of 10 vegetation communities, two with high volumes of favourite foods were preferred. Feeding areas with a high density of preferred food plants were also highly preferred. The riverine vegetation community was not preferred, because its abundant browse was not of the preferred species. The apparent avoidance of roads warrants more research and the attention of park managers.
机译:为了帮助确定要重新引入的土地,根据目击记录,觅食路线和粪便中毒的记录,在南非干旱的奥格拉比斯瀑布国家公园中开发了黑犀牛(Diceros bicornis)的栖息地适应性模型(HSM)。采用Logistic回归和贝叶斯信息准则从> 35个生态地理变量中构建和选择最佳的HSM。黑犀牛的建模分布和观察到的分布没有差异(P = 0.323),k倍交叉验证证实了该模型能够预测独立数据的分布。 HSM由五个变量组成:三种首选食物的可获得性和公平性,与道路的距离,栖息地的异质性,坡度和阴影。模型的置信度集合中还包括变量“距水的距离”和“岩石的”。研究区域中只有50%的栖息地适宜性超过11%,但有89%的犀牛栖息地。在10个植被群落中,有2个具有大量喜欢的食物是首选。具有高度密度的优选食用植物的饲养区域也是高度优选的。河流植被群落不是首选,因为其丰富的浏览并不是首选的物种。明显避开道路需要更多的研究和公园管理者的注意。

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