物种相对多度指数在红外相机数据分析中的应用及局限

多度是衡量物种种群数量的参数之一, 多度的动态及其影响因素是种群生态学研究的经典问题。物种相对多度指数(relative abundance index, RAI)作为一种简单、便利的指标, 广泛应用于动物本底清查中。但RAI易受物种自身特征、探测率和环境因素的影响, 需要结合其他物种数量分析方法, 以验证其与种群大小的相关性。随着红外相机技术在野生动物调查中的广泛应用, 用红外相机数据估计动物种群数量的研究越来越多。目前, 基于红外相机数据计算RAI的方法有多种, 不同计算方法和应用范围存在差异, 亟需对现有方法和应用进行梳理。本文综述了根据红外相机数据计算物种相对多度的4种主要方法: (1)拍摄一张有效照片所需要的天数; (2)基于单位调查强度的物种拍摄率; (3)每个位点每天的物种拍摄率; (4)某一物种的照片数占所有物种的比例。总结了我国野生动物监测调查中采用红外相机方法计算RAI的应用现状。国内的研究主要采用第2种和第4种计算方法, 其中约72.5%的研究论文应用第2种计算方法, 而第4种方法一般适用于群落中的物种组成比较。我们建议根据红外相机数据计算RAI时尽量使用第2种计算方法, 这有助于研究或管理人员对不同研究中的物种RAI进行比较分析。

Limitations of relative abundance indices calculated from camera-trapping data

Abundance is an important parameter used to estimate the population size of various wildlife species. With the growing application of camera-traps (movement or heat activated) to monitoring wildlife, the relative abundance index (RAI) has become one of the most popular indicators of population abundance for inventories and assessment. Despite a simple and convenient indicator of population size, RAI obtained from camera-trapping data can be greatly affected by many factors such as species traits, detection rates and environmental factors. Therefore, we need verify the correlation between RAI and population density prior to its general application. So far, several types of RAIs have been developed based on camera-trapping data, and it is critical to compare these RAI indices and their applications. In this paper, we summarized the methods calculating RAI with camera-trapping data and reviewed their applications in wildlife monitoring and inventories in China. Four main types of RAIs were identified including (1) the number of days when one animal is photographed, (2) the number of photographs of focal species per 100 trap days, (3) the number of photographs of focal species per trap day, and (4) the proportion of photos from the focal species compared to all photos of all animals. Among them, the second RAI type is the most widely used (72.5%) in wildlife monitoring and inventories in China, and the fourth RAI type is used to compare species components in communities. Consequently, we recommend the second RAI type for estimating population abundance in particular when camera-trapping data are used for broad-scale comparisons over different spatial and temporal scales.