Population density is the most basic ecological parameter for understanding population dynamics and biological conservation. Distance-based methods (or plotless methods) are considered as a more efficient but less robust approach than quadrat-based counting methods in estimating plant population density. The low robustness of distance-based methods mainly arises from the oversimplistic assumption of completely spatially random (CSR) distribution of a population in the conventional distance-based methods for estimating density of non-CSR populations in natural communities. In this study we derived two methods to improve on density estimation for plant populations of non-CSR distribution. The first method modified an existing composite estimator to correct for the long-recognized bias associated with that estimator. The second method was derived from the negative binomial distribution (NBD) that directly deals with aggregation in the distribution of a species. The performance of these estimators was tested and compared against various distance-based estimators by both simulation and empirical data of three large-scale stem-mapped forests. Results showed that the NBD point-to-tree distance estimator has the best and most consistent performance across populations with vastly different spatial distributions. This estimator offers a simple, efficient and robust method for estimating density for empirical populations of plant species.

中文翻译：

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基于距离的非随机分布种群密度估计方法

人口密度是了解人口动态和生物保护最基本的生态参数。在估计植物种群密度时，基于距离的方法（或无图方法）被认为是一种比基于样方的计数方法更有效但鲁棒性较差的方法。基于距离的方法的低稳健性主要源于在传统的基于距离的方法中估计自然群落中非 CSR 种群密度的种群完全空间随机 (CSR) 分布的过于简单化的假设。在这项研究中，我们导出了两种方法来改进非 CSR 分布的植物种群的密度估计。第一种方法修改了现有的复合估计量，以纠正与该估计量相关的长期公认的偏差。第二种方法源自负二项式分布 (NBD)，它直接处理物种分布中的聚集。通过三个大型茎映射森林的模拟和经验数据，对这些估计器的性能进行了测试并与各种基于距离的估计器进行了比较。结果表明，NBD 点到树距离估计器在空间分布差异很大的人群中具有最佳和最一致的性能。该估计器提供了一种简单、有效和稳健的方法来估计植物物种经验种群的密度。通过三个大型茎映射森林的模拟和经验数据，对这些估计器的性能进行了测试并与各种基于距离的估计器进行了比较。结果表明，NBD 点到树距离估计器在空间分布差异很大的人群中具有最佳和最一致的性能。该估计器提供了一种简单、有效和稳健的方法来估计植物物种经验种群的密度。通过三个大型茎映射森林的模拟和经验数据，对这些估计器的性能进行了测试并与各种基于距离的估计器进行了比较。结果表明，NBD 点到树距离估计器在空间分布差异很大的人群中具有最佳和最一致的性能。该估计器提供了一种简单、有效和稳健的方法来估计植物物种经验种群的密度。