Washington Cooperative Fish and Wildlife Research Unit, School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, 98195, USA.
U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Avenue, Building C, Fort Collins, Colorado, 80526, USA.
Ecol Appl. 2021 Oct;31(7):e02410. doi: 10.1002/eap.2410. Epub 2021 Aug 24.
Estimates of species abundance are critical to understand population processes and to assess and select management actions. However, capturing and marking individuals for abundance estimation, while providing robust information, can be economically and logistically prohibitive, particularly for species with cryptic behavior. Camera traps can be used to collect data at temporal and spatial scales necessary for estimating abundance, but the use of camera traps comes with limitations when target species are not uniquely identifiable (i.e., "unmarked"). Abundance estimation is particularly useful in the management of invasive species, with herpetofauna being recognized as some of the most pervasive and detrimental invasive vertebrate species. However, the use of camera traps for these taxa presents additional challenges with relevancy across multiple taxa. It is often necessary to use lures to attract animals in order to obtain sufficient observations, yet lure attraction can influence species' landscape use and potentially induce bias in abundance estimators. We investigated these challenges and assessed the feasibility of obtaining reliable abundance estimates using camera-trapping data on a population of invasive brown treesnakes (Boiga irregularis) in Guam. Data were collected using camera traps in an enclosed area where snakes were subject to high-intensity capture-recapture effort, resulting in presumed abundance of 116 snakes (density = 23/ha). We then applied spatial count, random encounter and staying time, space to event, and instantaneous sampling estimators to photo-capture data to estimate abundance and compared estimates to our presumed abundance. We found that all estimators for unmarked populations performed poorly, with inaccurate or imprecise abundance estimates that limit their usefulness for management in this system. We further investigated the sensitivity of these estimators to the use of lures (i.e., violating the assumption that animal behavior is unchanged by sampling) and camera density in a simulation study. Increasing the effective distances of a lure (i.e., lure attraction) and camera density both resulted in biased abundance estimates. Each estimator rarely recovered truth or suffered from convergence issues. Our results indicate that, when limited to unmarked estimators and the use of lures, camera traps alone are unlikely to produce abundance estimates with utility for brown treesnake management.
物种丰度的估计对于理解种群过程以及评估和选择管理措施至关重要。然而，捕捉和标记个体进行丰度估计虽然提供了可靠的信息，但在经济和物流上可能是不可行的，特别是对于行为隐蔽的物种。相机陷阱可用于收集估计丰度所需的时间和空间尺度的数据，但当目标物种无法唯一识别（即“未标记”）时，使用相机陷阱会受到限制。丰度估计在入侵物种的管理中特别有用，爬行动物被认为是最普遍和最具破坏性的入侵脊椎动物之一。然而，对于这些分类群，使用相机陷阱存在与多个分类群相关的额外挑战。为了获得足够的观察结果，通常需要使用诱饵来吸引动物，但诱饵的吸引力会影响动物的景观利用，并可能导致丰度估计器产生偏差。我们研究了这些挑战，并评估了在关岛入侵的棕色树蛇（Boiga irregularis）种群中使用相机陷阱数据获得可靠丰度估计的可行性。在一个蛇类受到高强度捕获-再捕获努力的封闭区域中使用相机陷阱收集数据，导致蛇类的丰度估计为 116 条（密度=23/公顷）。然后，我们将空间计数、随机遭遇和停留时间、空间到事件和瞬时采样估计器应用于照片捕获数据，以估计丰度，并将估计值与我们的假设丰度进行比较。我们发现，所有用于未标记种群的估计器表现不佳，其丰度估计不准确或不精确，限制了它们在该系统管理中的实用性。我们进一步在模拟研究中调查了这些估计器对诱饵使用（即，违反了动物行为不受采样影响的假设）和相机密度的敏感性。增加诱饵的有效距离（即诱饵吸引力）和相机密度都会导致丰度估计出现偏差。每个估计器很少能够恢复真实值或存在收敛问题。我们的结果表明，当仅限于未标记的估计器和诱饵的使用时，相机陷阱本身不太可能产生对棕色树蛇管理有用的丰度估计。
