United States Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, Maryland 20708, USA.
Ecol Appl. 2012 Jul;22(5):1665-74. doi: 10.1890/11-2129.1.
False positive errors are a significant component of many ecological data sets, which in combination with false negative errors, can lead to severe biases in conclusions about ecological systems. We present results of a field experiment where observers recorded observations for known combinations of electronically broadcast calling anurans under conditions mimicking field surveys to determine species occurrence. Our objectives were to characterize false positive error probabilities for auditory methods based on a large number of observers, to determine if targeted instruction could be used to reduce false positive error rates, and to establish useful predictors of among-observer and among-species differences in error rates. We recruited 31 observers, ranging in abilities from novice to expert, who recorded detections for 12 species during 180 calling trials (66,960 total observations). All observers made multiple false positive errors, and on average 8.1% of recorded detections in the experiment were false positive errors. Additional instruction had only minor effects on error rates. After instruction, false positive error probabilities decreased by 16% for treatment individuals compared to controls with broad confidence interval overlap of 0 (95% CI:--46 to 30%). This coincided with an increase in false negative errors due to the treatment (26%;--3 to 61%). Differences among observers in false positive and in false negative error rates were best predicted by scores from an online test and a self-assessment of observer ability completed prior to the field experiment. In contrast, years of experience conducting call surveys was a weak predictor of error rates. False positive errors were also more common for species that were played more frequently but were not related to the dominant spectral frequency of the call. Our results corroborate other work that demonstrates false positives are a significant component of species occurrence data collected by auditory methods. Instructing observers to only report detections they are completely certain are correct is not sufficient to eliminate errors. As a result, analytical methods that account for false positive errors will be needed, and independent testing of observer ability is a useful predictor for among-observer variation in observation error rates.
假阳性错误是许多生态数据集的一个重要组成部分,这些错误与假阴性错误结合在一起,可能导致对生态系统的结论产生严重偏差。我们介绍了一项野外实验的结果,在该实验中,观察者在模拟野外调查的条件下,记录已知组合的电子广播蛙类叫声的观测结果,以确定物种的出现。我们的目标是描述基于大量观察者的听觉方法的假阳性错误概率,确定是否可以使用有针对性的指导来降低假阳性错误率,并确定观察者之间和物种之间错误率差异的有用预测因子。我们招募了 31 名观察者,他们的能力从新手到专家不等,在 180 次叫声试验中记录了 12 个物种的检测结果(总共 66960 个观测结果)。所有观察者都犯了多次假阳性错误,实验中记录的检测结果中有 8.1%是假阳性错误。额外的指导对错误率只有很小的影响。在指导之后,与对照组相比,处理个体的假阳性错误概率降低了 16%,置信区间重叠为 0(95%CI:-46 至 30%)。这与由于处理而导致的假阴性错误增加(26%;-3 至 61%)相对应。观察者在假阳性和假阴性错误率方面的差异最好由在线测试和实验前完成的观察者能力自我评估的分数来预测。相比之下,进行叫声调查的年数是错误率的一个较弱预测因子。假阳性错误在播放频率较高的物种中更为常见,但与叫声的主要光谱频率无关。我们的结果证实了其他研究表明,假阳性是通过听觉方法收集的物种出现数据的一个重要组成部分。指导观察者仅报告他们完全确定的检测结果是不足以消除错误的。因此,需要分析方法来解释假阳性错误,而观察者能力的独立测试是观察者之间观察错误率差异的有用预测因子。