Jaksić F M, Medel R G
Departamento de Ecología, Universidad Católica de Chile, Casilla, 114-D, Santiago, Chile.
Oecologia. 1990 Jan;82(1):87-92. doi: 10.1007/BF00318537.
Presently, no standard protocol for objective guild recognition is consistently used by ecologists. Apart from intuitive designations of guild membership, four statistically-based protocols are currently available: those of Colwell (1977); Holmes (1979); Lawlor (1980); and Adams (1985). The first is based on nearest-neighbor variance in overlap, the second on multivariate statistics, the third on clustering techniques, and the fourth on psychometric analysis. We propose a fifth approach, first developed by Strauss (1982) for purposes other than guild recognition. We advocate the use of bootstrap procedures to resample any given empirical matrix of consumers by resources, within constraints set by either of four different randomization algorithms. Subsequently, pseudovalues of similarity in resource use between the consumers are computed and their frequency distribution is displayed in a histogram. The overlap pseudovalue that exceeds percentile 95 may be considered statistically significant and chosen as the cutoff point that identifies significant species clusters (guilds) in the original (empirical) similarity matrix. We exemplify use of this approach with the food-niche matrix obtained for a predatory assemblage in California, and discuss its implications for the general analysis of guild structure.
目前，生态学家们并未始终如一地采用标准的客观类群识别方案。除了凭直觉指定类群成员外，目前有四种基于统计的方案：科尔韦尔（1977年）的方案；霍姆斯（1979年）的方案；劳勒（1980年）的方案；以及亚当斯（1985年）的方案。第一种基于重叠的最近邻方差，第二种基于多元统计，第三种基于聚类技术，第四种基于心理测量分析。我们提出了第五种方法，该方法最初由施特劳斯（1982年）开发，用于类群识别以外的目的。我们主张使用自助程序，在四种不同随机化算法之一设定的约束条件下，对任何给定的消费者与资源的经验矩阵进行重采样。随后，计算消费者之间资源利用相似性的伪值，并将其频率分布显示在直方图中。超过第95百分位数的重叠伪值可被视为具有统计学意义，并被选作识别原始（经验）相似性矩阵中显著物种聚类（类群）的截止点。我们用为加利福尼亚一个捕食性组合获得的食物生态位矩阵举例说明了这种方法的使用，并讨论了其对类群结构一般分析的意义。
