CEFE, CNRS, Montpellier, France.
PLoS One. 2011 Jan 26;6(1):e14592. doi: 10.1371/journal.pone.0014592.
Although habitat use reflects a dynamic process, most studies assess habitat use statically as if an animal's successively recorded locations reflected a point rather than a movement process. By relying on the activity time between successive locations instead of the local density of individual locations, movement-based methods can substantially improve the biological relevance of utilization distribution (UD) estimates (i.e. the relative frequencies with which an animal uses the various areas of its home range, HR). One such method rests on Brownian bridges (BBs). Its theoretical foundation (purely and constantly diffusive movements) is paradoxically inconsistent with both HR settlement and habitat selection. An alternative involves movement-based kernel density estimation (MKDE) through location interpolation, which may be applied to various movement behaviours but lacks a sound theoretical basis.
METHODOLOGY/PRINCIPAL FINDINGS: I introduce the concept of a biased random (advective-diffusive) bridge (BRB) and show that the MKDE method is a practical means to estimate UDs based on simplified (isotropically diffusive) BRBs. The equation governing BRBs is constrained by the maximum delay between successive relocations warranting constant within-bridge advection (allowed to vary between bridges) but remains otherwise similar to the BB equation. Despite its theoretical inconsistencies, the BB method can therefore be applied to animals that regularly reorientate within their HRs and adapt their movements to the habitats crossed, provided that they were relocated with a high enough frequency.
CONCLUSIONS/SIGNIFICANCE: Biased random walks can approximate various movement types at short times from a given relocation. Their simplified form constitutes an effective trade-off between too simple, unrealistic movement models, such as Brownian motion, and more sophisticated and realistic ones, such as biased correlated random walks (BCRWs), which are too complex to yield functional bridges. Relying on simplified BRBs proves to be the most reliable and easily usable way to estimate UDs from serially correlated relocations and raw activity information.
尽管栖息地利用反映了一个动态过程，但大多数研究都是静态地评估栖息地利用情况，就好像动物连续记录的位置反映的是一个点，而不是一个移动过程。通过依赖于连续位置之间的活动时间，而不是个体位置的局部密度，基于运动的方法可以大大提高利用分布（UD）估计的生物学相关性（即动物使用其家域内各个区域的相对频率）。其中一种方法基于布朗桥（BB）。它的理论基础（纯粹且持续扩散的运动）与 HR 定居和栖息地选择都不一致，这具有矛盾性。另一种方法涉及基于位置插值的基于运动的核密度估计（MKDE），它可以应用于各种运动行为，但缺乏合理的理论基础。
方法/主要发现：我引入了有偏随机（平流扩散）桥（BRB）的概念，并表明 MKDE 方法是一种基于简化（各向同性扩散）BRB 来估计 UD 的实用方法。BRB 的控制方程受到连续重新定位之间最大延迟的限制，该延迟保证了恒定的桥内平流（允许在不同的桥之间变化），但在其他方面与 BB 方程相似。尽管存在理论上的不一致，但只要动物在家域内经常重新定向并适应所穿越的栖息地，就可以将 BB 方法应用于它们，前提是它们以足够高的频率被重新定位。
结论/意义：有偏随机漫步可以在给定重新定位的短时间内近似各种移动类型。它们的简化形式构成了过于简单、不现实的运动模型（如布朗运动）和更复杂、更现实的模型（如有偏相关随机漫步（BCRW））之间的有效折衷，后者过于复杂，无法产生功能桥。从连续相关的重新定位和原始活动信息中估计 UD，依赖简化的 BRB 被证明是最可靠和易于使用的方法。
