Gupta Manan, Joshi Amitabh, Vidya T N C
Evolutionary and Organismal Biology Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bengaluru, India.
PLoS One. 2017 Mar 17;12(3):e0173609. doi: 10.1371/journal.pone.0173609. eCollection 2017.
Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species.
标记重捕估计器通常用于种群数量估计,对于大多数独居且家域大小为低到中等的物种,通常能得出无偏估计。然而,这些方法假定个体间的捕获是独立的,而这一假设在呈现裂变-融合动态的群居物种(如亚洲象)中显然被违背。在亚洲象的具体案例中,人们对种群数量估计的准确性提出了质疑。更重要的是,一般社会组织对标记重捕方法使用所带来的潜在问题尚未得到系统解决。我们开发了一个基于个体的模拟框架,以系统地研究社会组织类型以及其他因素(如陷阱密度和布局、采样空间尺度以及种群密度)对通过POPAN、稳健设计以及具有检测异质性的稳健设计所估计的种群数量偏差的潜在影响。在本研究中,我们使用与亚洲象种群相关的生物学、人口统计学和生态学参数进行模拟,但该模拟框架可轻松扩展以解决与其他群居物种相关的问题。我们从模拟中收集捕获历史数据,并使用这些数据来检验种群数量估计中的偏差。在大多数分析中,社会组织显著影响偏差,但效应大小各不相同,这取决于其他因素。当陷阱布局均匀且采样力度较低时,社会组织往往会引入较大偏差。POPAN明显优于我们测试的两种稳健设计模型,如果在研究区域随机布置陷阱,并且种群密度和陷阱密度不太低时,它产生的偏差接近零。对于POPAN给出或多或少无偏种群数量估计的这些参数组合,社会组织对偏差没有重大影响。因此,通过使用具有特定参数组合的POPAN,可以消除社会组织对种群估计偏差的影响,从而在群居物种中获得种群数量估计。