Assessing uncertainty in sighting records: an example of the Barbary lion

Assessing uncertainty in sighting records: an example of the Barbary lion
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DOI:
10.7717/peerj.1224
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发表时间:
2015-09-01
期刊:
影响因子:
2.7
通讯作者:
Roberts, David L.
Roberts, David L.
中科院分区:
生物学3区
文献类型:
--
作者:
Lee, Tamsin E.;Black, Simon A.;Roberts, David L.

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随着物种变得稀少并濒临灭绝,所谓的目击事件可能会引起争议,特别是当稀缺的管理资源受到威胁时。我们考虑的概率,每个单独的目击一系列是有效的。获得这些概率需要一个严格的框架,以确保它们尽可能准确地代表。我们使用了一个过程,该过程已被证明可以提供一组专家的准确估计,以获得32次巴巴里狮目击事件的验证概率。我们考虑的情况下,专家被简单地问到是否目击是有效的,以及要求他们评分的目击的基础上,可验证性,观察者的能力,和可验证性。我们发现,要求专家提供这三个方面的分数,导致每个目击被认为是更个别的,这意味着这种新的提问方法提供了非常不同的估计概率,目击是有效的,这极大地影响了灭绝模型的结果。我们考虑线性意见池和对数意见池来联合收割机组合这三个分数,并且还联合收割机组合对每个目击的意见。我们发现这两种方法产生了类似的结果,允许用户专注于每种方法的选定功能,例如满足边缘化属性或外部贝叶斯。
As species become rare and approach extinction, purported sightings can be controversial, especially when scarce management resources are at stake. We consider the probability that each individual sighting of a series is valid. Obtaining these probabilities requires a strict framework to ensure that they are as accurately representative as possible. We used a process, which has proven to provide accurate estimates from a group of experts, to obtain probabilities for the validation of 32 sightings of the Barbary lion. We consider the scenario where experts are simply asked whether a sighting was valid, as well as asking them to score the sighting based on distinguishablity, observer competence, and verifiability. We find that asking experts to provide scores for these three aspects resulted in each sighting being considered more individually, meaning that this new questioning method provides very different estimated probabilities that a sighting is valid, which greatly affects the outcome from an extinction model. We consider linear opinion pooling and logarithm opinion pooling to combine the three scores, and also to combine opinions on each sighting. We find the two methods produce similar outcomes, allowing the user to focus on chosen features of each method, such as satisfying the marginalisation property or being externally Bayesian.