期刊
OECOLOGIA
卷 150, 期 2, 页码 282-290出版社
SPRINGER
DOI: 10.1007/s00442-006-0520-2
关键词
benthic invertebrates; energetic equivalence; size spectra; stable isotope analysis; trophic structure
类别
Abundance-body size relationships are widely observed macroecological patterns in complete food webs and in taxonomically or functionally defined subsets of those webs. Observed abundance-body size relationships have frequently been compared with predictions based on the energetic equivalence hypothesis and, more recently, with predictions based on energy availability to different body size classes. Here, we consider the ways in which working with taxonomically or functionally defined subsets of food webs affected the relationship between the predicted and observed scaling of biomass and body mass in sediment dwelling benthic invertebrate communities at three sites in the North Sea. At each site, the energy available to body size classes in the whole community (community defined as all animals of 0.03125-32.0 g shell-free wet weight) and in three subsets was predicted from estimates of trophic level based on nitrogen stable isotope analysis. The observed and predicted scalings of biomass and body size were not significantly different for the whole community, and reflected an increase in energy availability with body size. However, the results for subsets showed that energy availability could increase or decrease with body size, and that individuals in the subsets were likely to be competing with individuals outside the subsets for energy. We conclude that the study of abundance-body mass relationships in functionally or taxonomically defined subsets of food webs is unlikely to provide an adequate test of the energetic equivalence hypothesis or other relationships between energy availability and scaling. To consistently and reliably interpret the results of these tests, it is necessary to know about energy availability as a function of body size both within and outside the subset considered.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据