Efficient abstracting of dive profiles using a broken-stick model
Efficient abstracting of dive profiles using a broken-stick model
复制标题
使用断棍模型有效提取潜水剖面
DOI：
10.1111/2041-210x.12328
复制
发表时间：
2015
影响因子：
6.6
通讯作者：
Photopoulou T
中科院分区：
文献类型：
--
作者：
Photopoulou T
对于潜水动物，动物携带的传感器用于收集时间深度信息，以研究行为、测距模式和觅食生态。通常，需要压缩该信息以进行存储或传输。广泛使用的设备称为电导率-温度-深度卫星中继数据记录器（CTD-SRDL），在潜水过程中以高分辨率采样时间和深度，然后使用断棒模型（BSM）抽象时间-深度轨迹。这种近似方法可以使用具有少量、固定数量的顶点或断点的分段线性形状，有效地概括潜水的曲线形状。我们提出了使用 BSM 抽象潜水的过程，并通过测量与其生成的剖面相关的不确定性来量化其性能。我们开发了一种方法来获取抽象潜水剖面的置信区和拟合优度指数（潜水区指数，DZI）。我们通过使用象海豹潜水的案例研究来验证我们的结果（Miroungaspp.）。我们使用广义加性模型 (GAM) 来确定 DZI 是否可以用作绝对拟合测量的代理，并研究 DZI 和潜水形状之间的关系。我们发现，对于 CTD-SRDL 产生的潜水，详细和抽象剖面之间差异的残差平方和 (RSS) 与 DZI 和最大残差 (R4) 之间存在很强的相关性（解释了 69% 的偏差）。天珠本身解释了较低的偏差百分比，这对于具有不同断点数量的抽象潜水是可变的。我们还发现了不同潜水形状的 DZI 存在系统差异的证据（解释了 65% 的偏差）。尽管 BSM 在抽象时间深度潜水剖面时信息损失的比例很高，但剩下的信息足以通过反转抽象过程来推断抽象剖面的拟合优度。我们的结果表明，DZI 和 R4 可以一起用作 RSS 的代理，并且我们提出了获取 BSM 抽象配置文件的这些指标的方法。
For diving animals, animal‐borne sensors are used to collect time–depth information for studying behaviour, ranging patterns and foraging ecology. Often, this information needs to be compressed for storage or transmission. Widely used devices called conductivity‐temperature‐depth satellite relay data loggers (CTD‐SRDLs) sample time and depth at high resolution during a dive and then abstract the time–depth trajectory using a broken‐stick model (BSM). This approximation method can summarize efficiently the curvilinear shape of a dive, using a piecewise linear shape with a small, fixed number of vertices, or break points.We present the process of abstracting dives using the BSM and quantify its performance, by measuring the uncertainty associated with the profiles it produces. We develop a method for obtaining a confidence zone and an index for the goodness‐of‐fit (dive zone index, DZI) for abstracted dive profiles. We validate our results with a case study using dives from elephant seals (Miroungaspp.). We use generalized additive models (GAMs) to determine whether the DZI can be used as a proxy for an absolute measure of fit and investigate the relationship between the DZI and the dive shape.We found a strong correlation between the residual sum of squares (RSS) for the difference between the detailed and abstracted profiles, and the DZI and maximum residual (R4), for dives resulting from CTD‐SRDLs (69% deviance explained). On its own, the DZI explained a lower percentage of deviance which was variable for abstracted dives with different numbers of break points. We also found evidence for systematic differences in the DZI for different dive shapes (65% deviance explained).Although the proportional loss of information in the abstraction of time–depth dive profiles by BSM is high, what remains is sufficient to infer goodness‐of‐fit of the abstracted profile by reversing the abstraction process. Our results suggest that together the DZI and R4 can be used as a proxy for the RSS, and we present the method for obtaining these metrics for BSM‐abstracted profiles.