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，必须考虑移动类群动物的检测不完全问题。固着生物（sessile organisms）同样存在检测不完全的情况，但在估算其种群规模时对检测概率进行校正的研究却较为少见。本研究以红褐林蚁（Formica rufa-类群）蚁巢普查为案例，阐释固着生物检测概率与种群估算面临的挑战。这类蚂蚁广泛分布于北半球，可构筑高度可达2米、辨识度极高的蚁巢。本研究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147个蚁巢的2天普查绘图数据，开发了用于量化固着生物检测概率的贝叶斯模型（Bayesian model）。单名调查人员对红褐林蚁蚁巢的检测概率介于0.31至0.56之间，且受调查人员经验、蚁巢大小与密度以及生境特征的影响。即便对于红褐林蚁蚁巢这类辨识度极高的固着生物，要稳健估算其种群密度，也需对检测概率进行无偏估计，这与稀有或隐蔽物种的种群密度估算要求一致。