当前位置: X-MOL 学术Biodivers. Conserv. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Reliability of multinomial N-mixture models for estimating abundance of small terrestrial vertebrates
Biodiversity and Conservation ( IF 3.0 ) Pub Date : 2020-06-30 , DOI: 10.1007/s10531-020-02006-5
Andrea Costa , Antonio Romano , Sebastiano Salvidio

Information on population abundance is important to correctly plan conservation and management of animal populations. In general, capture-mark-recapture (CMR) is considered the most robust technique to estimate population abundance, but it is costly in terms of time and effort. Recently, binomial N-mixture models, based on counts of unmarked individuals, have been widely employed to estimate abundance. These models have limits and their reliability has been criticized. In the majority of cases, multinomial N-mixture models based on multiple observer protocols, that are hierarchical extensions of simple CMR, are applied in estimating abundance of animals with large body size, conspicuous behavior or high detection probabilities. We applied and evaluated the reliability of a multinomial N-mixture modelling approach with multiple observer data to a small and cryptic terrestrial salamander, found in different habitats where populations possess different level of detectability. Estimates obtained with multinomial N-mixture models were compared to estimates obtained with classical methods, such as removal sampling, and their reliability has also been evaluated by simulations scenarios. Our results show that multinomial N-mixture models, applied within a multiple observer framework, give reliable and robust estimates of population abundance even when detection and density are relatively low. Therefore, multinomial N-mixture models appear efficient and cost-effective when planning and identifying management actions and conservation programs of small terrestrial animals such as amphibians and reptiles.



中文翻译:

多项式N混合模型用于估计小陆生脊椎动物数量的可靠性

有关种群数量的信息对于正确规划动物种群的保护和管理非常重要。通常,捕获标记捕获(CMR)被认为是估计种群数量的最可靠的技术,但是在时间和精力上花费很大。最近,基于无标记个体计数的二项式N混合模型已被广泛用于估计丰度。这些模型有局限性,其可靠性受到批评。在大多数情况下,基于多个观察者协议的多项式N混合物模型是简单CMR的分层扩展,可用于估算具有大体型,明显行为或高检测概率的动物的数量。我们将具有多个观察者数据的多项式N混合建模方法的可靠性应用到了小型隐密的陆地sal中,并对其进行了评估,该,在人口具有不同可检测水平的不同栖息地中发现。将使用多项式N混合物模型获得的估计值与通过经典方法(例如去除采样)获得的估计值进行比较,并且还通过模拟方案评估了它们的可靠性。我们的结果表明,即使在检测率和密度相对较低的情况下,在多个观测器框架内应用的多项式N混合模型也可以给出可靠且可靠的总体数量估算。因此,

更新日期:2020-06-30
down
wechat
bug