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Predicting the tangible and intangible costs of co-occurring with wildlife

机译:预测与野生动物共同发生的切实和无形成本

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Perceived intangible costs of co-occurring with wildlife are one of the strongest drivers of attitudes towards wild species, yet they have been little studied. Thus, determining the factors that influence the perception of such costs is essential to devise conservation strategies in landscapes where human-wildlife interactions are high. The main aim of this paper was to compare the effect of socio-demographic, exposure and attitudinal factors on the perceived cost probability of two species with associated tangible and intangible costs (i.e. crop-damage and fear respectively). Data were collected through semi-structured interviews and analyzed through logistic regressions under Bayesian approach. Model assessment and comparison was conducted using leave-one-out cross-validation (LOO) and their expected log pointwise predictive density (elpd). Although for both species, the exposure model was favored over the socio-demographic and attitudinal models, their perceived cost probability exhibited opposite responses. In the case of the crop-damaging species, the exposure model had considerably better predictive performance than the other two models. However, in the case of the feared species, the predictive performance of the exposure model was not better than the predictive performance of the other models. These results suggest: first, that the drivers of the perceived cost probability of co-occurring with wildlife are cost-specific; and second, that the perceived cost probability of the feared species has a lower predictability than the perceived cost probability of the crop-damaging species, given the set of candidate models. Considering that fear is an important perceived intangible cost of co-occurring with wildlife, more research is needed on its drivers, as well as on strategies to minimize it.
机译:感知与野生动物共同发生的无形成本是对野生物种的最强大的驱动因素之一,但它们已经很少研究过。因此,确定影响这种成本感知的因素对于设计人野生动物相互作用高的景观中的保护策略是必不可少的。本文的主要目的是比较社会人口统计,暴露和态度因素对两个物种的感知成本概率的影响,具有相关的有形和无形成本(即分别的作物损坏和恐惧)。通过半结构化访谈收集数据,并通过贝叶斯方法下的逻辑回归分析。使用休假交叉验证(LOO)和其预期的日志预测密度(ELPD)进行模型评估和比较。虽然对于这两种物种,曝光模型对社会人口统计和态度模型受到青睐,但它们的感知成本概率表现出相反的反应。在作物损坏物种的情况下,曝光模型比其他两种模型更好地预测性能。然而,在令人担忧的物种的情况下,曝光模型的预测性能并不优于其他模型的预测性能。这些结果表明:首先,与野生动物共同发生的感知成本概率的驱动力是特定的;其次,鉴于候选模型一组候选模型,令人担忧的物种的感知成本概率比作物损坏物种的感知成本概率较低。考虑到恐惧是与野生动物共同发生的重要感知无形成本,在其司机上需要更多的研究,以及最小化它的策略。

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