Detection Probability of Red Wood Ants in Friedenweiler, Germany 2015

Estimation of population sizes and species ranges is central to population and conservation biology. It is widely appreciated that imperfect detection of mobile animals must be accounted for when estimating population size from presence-absence data. Sessile organisms also are imperfectly detected, but correction for detection probability in estimating their population sizes is rare. We illustrate challenges of detection probability and population estimation of sessile organisms using censuses of red wood ant (Formica rufa-group) nests as a case study. These ants, widespread in the northern hemisphere, can make large (up to 2m tall), highly visible nests. Using data from a two-day mapping campaign by eight individuals of 147 ant nests spread across sixteen 3600-m2 plots in the Black Forest region of southwest Germany, we developed a Bayesian model for quantifying detection probability of sessile organisms. Detection probabilities by individual observers of red wood ant nests ranged from 0.31 – 0.56, and depended on experience of the observers, size and density of nests, and habitat characteristics. Robust estimation of population density of sessile organisms—even highly apparent ones such as red wood ant nests—requires unbiased estimation of detection probability, just as it does when estimating population density of rare or cryptic species.种群规模与物种分布范围的估算，是种群生物学与保护生物学的核心研究内容。学界普遍认为，基于存在-缺失数据估算种群规模时，必须考量移动动物的不完全检测问题。固着生物同样存在不完全检测的情况，但在估算其种群规模时，针对检测概率进行校正的研究却相对罕见。我们以红木蚁（Formica rufa-group）巢穴的普查作为案例研究，阐释了固着生物的检测概率与种群估算所面临的挑战。这类蚂蚁广泛分布于北半球，可构筑高度可达2米、辨识度极高的巢穴。我们依托德国西南部黑森林区域内16块面积为3600平方米的样地中分布的147个蚁巢数据，由8名观测者开展了为期两天的测绘工作，并据此构建了用于量化固着生物检测概率的贝叶斯模型。单个观测者对红木蚁巢穴的检测概率介于0.31至0.56之间，且受观测者经验、蚁巢大小与密度以及生境特征的影响。即便是红木蚁巢穴这类辨识度极高的固着生物，要对其种群密度进行可靠估算，同样需要对检测概率进行无偏估计——这与估算稀有或隐秘物种的种群密度时的要求完全一致。