Department of Fisheries and Wildlife, Hermiston Agricultural Research and Extension Center, Oregon State University, Hermiston, OR 97838, USA.
J Insect Sci. 2010;10:25. doi: 10.1673/031.010.2501.
Significant progress has been made in developing subsampling techniques to process large samples of aquatic invertebrates. However, limited information is available regarding subsampling techniques for terrestrial invertebrate samples. Therefore a novel subsampling procedure was evaluated for processing samples of terrestrial invertebrates collected using two common field techniques: pitfall and pan traps. A three-phase sorting protocol was developed for estimating abundance and taxa richness of invertebrates. First, large invertebrates and plant material were removed from the sample using a sieve with a 4 mm mesh size. Second, the sample was poured into a specially designed, gridded sampling tray, and 16 cells, comprising 25% of the sampling tray, were randomly subsampled and processed. Third, the remainder of the sample was scanned for 4-7 min to record rare taxa missed in the second phase. To compare estimated abundance and taxa richness with the true values of these variables for the samples, the remainder of each sample was processed completely. The results were analyzed relative to three sample size categories: samples with less than 250 invertebrates (low abundance samples), samples with 250-500 invertebrates (moderate abundance samples), and samples with more than 500 invertebrates (high abundance samples). The number of invertebrates estimated after subsampling eight or more cells was highly precise for all sizes and types of samples. High accuracy for moderate and high abundance samples was achieved after even as few as six subsamples. However, estimates of the number of invertebrates for low abundance samples were less reliable. The subsampling technique also adequately estimated taxa richness; on average, subsampling detected 89% of taxa found in samples. Thus, the subsampling technique provided accurate data on both the abundance and taxa richness of terrestrial invertebrate samples. Importantly, subsampling greatly decreased the time required to process samples, cutting the time per sample by up to 80%. Based on these data, this subsampling technique is recommended to minimize the time and cost of processing moderate to large samples without compromising the integrity of the data and to maximize the information extracted from large terrestrial invertebrate samples. For samples with a relatively low number of invertebrates, complete counting is preferred.
在开发用于处理大量水生无脊椎动物样本的抽样技术方面已经取得了重大进展。然而,关于用于处理陆地无脊椎动物样本的抽样技术的信息有限。因此,评估了一种新的抽样程序,用于处理使用两种常见野外技术收集的陆地无脊椎动物样本:陷阱和潘陷阱。开发了一个三阶段分类协议来估计无脊椎动物的丰度和分类 richness。首先,使用 4 毫米网眼尺寸的筛子从样品中去除大型无脊椎动物和植物材料。其次,将样品倒入专门设计的带网格的采样托盘,随机抽取并处理 16 个单元格,占采样托盘的 25%。第三,扫描剩余的样品 4-7 分钟,以记录第二阶段错过的稀有分类。为了将估计的丰度和分类 richness 与这些变量的真实值进行比较,对每个样品的其余部分进行了完全处理。结果相对于三个样本大小类别进行了分析:少于 250 个无脊椎动物的样本(低丰度样本)、250-500 个无脊椎动物的样本(中等丰度样本)和超过 500 个无脊椎动物的样本(高丰度样本)。对于所有大小和类型的样本,抽取 8 个或更多单元格后的无脊椎动物数量估计非常准确。即使仅抽取 6 个样本,也可以实现对中等和高丰度样本的高精度估计。然而,对于低丰度样本的无脊椎动物数量的估计不太可靠。抽样技术还充分估计了分类 richness;平均而言,抽样检测到样本中发现的 89%的分类。因此,抽样技术提供了陆地无脊椎动物样本丰度和分类 richness 的准确数据。重要的是,抽样大大减少了处理样本所需的时间,每个样本的时间减少了 80%。基于这些数据,建议使用这种抽样技术来最小化处理中等至大型样本的时间和成本,同时不影响数据的完整性,并最大限度地从大型陆地无脊椎动物样本中提取信息。对于无脊椎动物数量相对较少的样本,首选完整计数。