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A Field Evaluation of the Time-of-Detection Method to Estimate Population Size and Density for Aural Avian Point Counts

机译:现场时间评估方法的估计人口规模和密度的听觉禽点数。

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The time-of-detection method for aural avian point counts is a new method of estimating abundance, allowing for uncertain probability of detection. The method has been specifically designed to allow for variation in singing rates of birds. It involves dividing the time interval of the point count into several subintervals and recording the detection history of the subintervals when each bird sings. The method can be viewed as generating data equivalent to closed capture–recapture information. The method is different from the distance and multiple-observer methods in that it is not required that all the birds sing during the point count. As this method is new and there is some concern as to how well individual birds can be followed, we carried out a field test of the method using simulated known populations of singing birds, using a laptop computer to send signals to audio stations distributed around a point. The system mimics actual aural avian point counts, but also allows us to know the size and spatial distribution of the populations we are sampling. Fifty 8-min point counts (broken into four 2-min intervals) using eight species of birds were simulated. Singing rate of an individual bird of a species was simulated following a Markovian process (singing bouts followed by periods of silence), which we felt was more realistic than a truly random process. The main emphasis of our paper is to compare results from species singing at (high and low) homogenous rates per interval with those singing at (high and low) heterogeneous rates. Population size was estimated accurately for the species simulated, with a high homogeneous probability of singing. Populations of simulated species with lower but homogeneous singing probabilities were somewhat underestimated. Populations of species simulated with heterogeneous singing probabilities were substantially underestimated. Underestimation was caused by both the very low detection probabilities of all distant individuals and by individuals with low singing rates also having very low detection probabilities.
机译:用于听觉禽点计数的检测时间方法是一种估计丰度的新方法,可以实现不确定的检测概率。该方法经过专门设计,可以改变鸟类的歌唱速度。它涉及将点计数的时间间隔分为几个子间隔,并记录每只鸟唱歌时子间隔的检测历史。该方法可以看作是生成与封闭式捕获-再捕获信息等效的数据。该方法与距离和多观察者方法的不同之处在于,不需要所有的鸟都在点数期间唱歌。由于这种方法是新方法,并且对个体鸟类的追踪性能存在一定的关注,因此我们使用模拟的已知鸟类唱歌种群对该方法进行了现场测试,使用便携式计算机将信号发送到周围分布的音频站。点。该系统模拟了实际的鸟类鸟类点数,但也使我们能够知道所采样种群的大小和空间分布。使用八种鸟类模拟了五十个8分钟的点数(分为两个2分钟的间隔)。按照马尔可夫过程(先打一声然后停顿一段时间)模拟一个物种中单个鸟的歌唱率,我们认为这比真正随机的过程更为现实。我们论文的主要重点是比较以每个间隔(高和低)同质速率唱歌的物种与以(高和低)异质速率唱歌的物种的结果。准确估计了模拟物种的种群数量,并具有很高的同声歌唱概率。具有较低但均一的歌唱概率的模拟物种的种群被低估了。用异类歌唱概率模拟的物种种群被大大低估了。低估是由所有遥远的个体的极低检测概率和唱歌频率低的个体也具有极低的检测概率引起的。

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