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Using crisp and fuzzy modelling to identify favourability hotspots useful to perform gap analysis

机译:使用清晰和模糊的模型来确定有利于进行差距分析的热点

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In this study, we propose the use of a favourability function to perform Gap Analysis. To exemplify this, we modelled the distribution of terrestrial mammal species in Andalusia (South of Spain) on the basis of their presence/absence on a grid of 10 km x 10 km UTM cells (n = 961). Using logistic regression and 30 variables related with the environment, space and human influence, we obtained probabilities of occurrence for each species in each cell. We computed a crisp favourability index considering the areas as favourable or unfavourable for a species if the probability of occurrence was higher or lower than the species prevalence, respectively. We also used a favourability function and fuzzy logic to level all species to the same threshold of favourability, which allowed to compare and to combine species distributions. Adding up the fuzzy favourability values for each species in each cell we obtained a fuzzy favourability index that we compared with species richness (sum of species in each cell) and with the crisp favourability index. We performed Gap Analysis by overlapping these results with the current reserve network of Andalusia. Gaps were grouped in fewer and bigger zones after applying the favourability indices. Considerations and recommendations for the use of the favourability function to select areas of conservation interest are discussed.
机译:在这项研究中,我们建议使用偏好功能执行差距分析。为了举例说明这一点,我们基于在10 km x 10 km UTM细胞(n = 961)的网格上是否存在安达卢西亚(西班牙南部)的陆生哺乳动物物种进行了建模。使用逻辑回归和与环境,空间和人类影响有关的30个变量,我们获得了每个细胞中每个物种的发生概率。如果出现概率分别高于或低于物种流行率,我们考虑区域对物种的有利或不利而计算出清晰的有利指数。我们还使用了可喜度函数和模糊逻辑,将所有物种的可喜度阈值均等化,从而可以比较和组合物种分布。将每个单元格中每种物种的模糊有利度值相加,我们获得了模糊有利度指数,并将其与物种丰富度(每个单元格中物种的总和)和脆性有利度指数进行了比较。我们通过将这些结果与安达卢西亚当前的储备网络重叠来进行差距分析。应用好感度指数后,差距被分为越来越少的区域。讨论了使用优惠性功能来选择具有保护意义的领域的考虑和建议。

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