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首页> 外文期刊>The Journal of Applied Ecology >A novel method for quantifying habitat selection and predicting habitat use
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A novel method for quantifying habitat selection and predicting habitat use

机译:一个新颖的方法量化栖息地选择和预测栖息地的使用

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1. The study of habitat selection and habitat use are crucial for understanding the biological requirements of animals and the strategies they use to fulfil their needs. A variety of statistical techniques are available to quantify habitat selection, most of them based on the comparison of habitat attributes in sites used by the animals and in unused, but available, sites. Because of the difficulties in defining what is available from an animal's perspective for many species, statistical approaches such as first-passage time (FPT) analysis have been developed, which explore habitat-use intensities through the areas used by animals. 2. In this study, we expand on that approach by using FPT-derived data within the framework of mixed-effects Cox proportional hazards models (CPH models) to quantify habitat selection. By modelling FPTs, CPH models evaluate which habitat attributes best explain the 'risk' or 'hazard' of the animal leaving an area of a given radius. For quantitative interpretations, the coefficients of the CPH model can be used to calculate hazard ratios that estimate relative habitat preferences: the lower the hazard ratio (i.e. the lower the risk of leaving), the higher the preference. Accounting for individual variability in habitat use by means of a random-effect term added to CPH models provides inferences that more appropriately reflect the typical hierarchical structure of telemetric data on animal space use. 3. Synthesis and applications. In addition to providing inferences about habitat selection based on the estimated parameters, survival functions of fixed-effects CPH models can be used to construct spatial predictions, for instance maps of population-level space use. Such predictions can be particularly useful for applied purposes, for example as a basis for species conservation plans and reserve selection. The method is illustrated using two data sets from marine mammal species: ringed seals Phoca hispida and white whales Delphinapterus leucas, but it is broadly applicable to habitat selection and prediction studies of other highly mobile animals in marine or terrestrial systems.
机译:1. 理解的关键是生物吗动物和策略的要求使用它来满足他们的需求。统计技术可用于量化栖息地的选择,其中大部分是基于在网站使用的栖息地的属性进行比较动物和未使用的,但可用的网站。因为困难的定义是什么可以从动物的角度来看物种、统计方法等首次通过时间(把)分析开发,探索栖息地利用强度通过动物使用的区域。研究中,我们扩展这种方法通过使用FPT-derived数据的框架内mixed-effects Cox比例风险模型(CPH模型)量化栖息地选择。造型把,CPH模型评估它的栖息地属性最好解释的“风险”或“风险”动物留下的一个给定的半径。系数的定量解释CPH模型可以用来计算风险比率估计相对的栖息地偏好:风险比(即越低低的风险离开),越高偏好。栖息地的使用的随机效应添加到CPH模型提供了更多的推论恰当地反映了典型的层次遥测数据结构在动物空间使用。3.提供推断栖息地选择基于估计参数,生存可以使用的功能固定后果CPH模型例如,构建空间预测地图的群体空间使用。预测可以特别有用应用目的,例如为基础物种保护计划和储备的选择。该方法使用两个数据集从海洋哺乳动物物种:斑海豹Phocahispida和白鲸Delphinapterus莱夫卡斯岛,但它是广泛适用于栖息地选择和其他高度流动的预测研究动物在海洋或陆地系统。

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