Statistical precision of diet diversity from scat and pellet analysis
This data was imported from Scopus:
Journal: Ecological Informatics
Knowledge of trophic interactions is of vital importance for understanding ecological community dynamics. While techniques such as direct observation of prey consumption and stomach content analysis are suitable for some species; for wide ranging carnivores, especially those of conservation concern, analysis of matter in faecal scats or regurgitated pellets is still common practice. This study investigates sample sizes needed to predict changes in the diversity of the diet of three carnivore species (grey seals, Mexican wolves and long horned owls). Using a bootstrapping process, estimations of precision of diet diversity (i.e. the number and evenness of prey species, as measured using Simpson's index) were made with increasing sample sizes (numbers of scats/pellets sampled). Precision of diversity of diet was much greater for grey seals than for owls or wolves, largely because the number of prey items (remains of individuals of the same or different species) in a scat was much higher. When these results are used to test hypotheses to determine difference in diet diversity, the results show that changes in seal diet diversity between different areas of the North Sea could be elucidated with analysis of as few as three scats from each region. However, demonstrating differences in diet diversity between different, but related, owl species from the same area would not be possible even if the contents of >>500 pellets were analysed. This study provides tools and guidelines for sample size requirements in scat or pellet analysis for future studies, as well as indicating that in some cases - for example in grey seals - scat samples may be an efficient method of investigating changes in diet diversity, and hence niche breath, which may alter with prey availability as caused by anthropogenic pressures such as climate change and fishing. © 2011 Elsevier B.V.
This data was imported from Web of Science (Lite):
Authors: Williams, R.L., Goodenough, A.E. and Stafford, R.
Journal: ECOLOGICAL INFORMATICS