Comparing rates of springtail predation by web‐building spiders using Bayesian inference. Issue 15 (21st April 2014)

• Record Type: Journal Article
• Authors: Welch, Kelton D.; Schofield, Matthew R.; Chapman, Eric G.; Harwood, James D.
• Is Part Of: Molecular ecology. Volume 23:Issue 15(2014)
• Page Start: 3814
• Page End: 3825
• Publication Date: 2014-04-21
• Subjects: Molecular ecology -- Periodicals; Molecular population biology -- Periodicals; 576
• DOI: 10.1111/mec.12721
• Languages: English
• ISSNs: 0962-1083

Abstract

<abstract abstract-type="main" id="mec12721-abs-0001"> <title>Abstract</title> <p>A major goal of gut‐content analysis is to quantify predation rates by predators in the field, which could provide insights into the mechanisms behind ecosystem structure and function, as well as quantification of ecosystem services provided. However, percentage‐positive results from molecular assays are strongly influenced by factors other than predation rate, and thus can only be reliably used to quantify predation rates under very restrictive conditions. Here, we develop two statistical approaches, one using a parametric bootstrap and the other in terms of Bayesian inference, to build upon previous techniques that use DNA decay rates to rank predators by their rate of prey consumption, by allowing a statistical assessment of confidence in the inferred ranking. To demonstrate the utility of this technique in evaluating ecological data, we test web‐building spiders for predation on a primary prey item, springtails. Using these approaches we found that an orb‐weaving spider consumes springtail prey at a higher rate than a syntopic sheet‐weaving spider, despite occupying microhabitats where springtails are less frequently encountered. We suggest that spider‐web architecture (orb web vs. sheet web) is a primary determinant of prey‐consumption rates within this assemblage of predators, which demonstrates the potential influence of predator foraging behaviour on trophic web structure. We also discuss how additional assumptions can be incorporated into the same analysis to allow broader application of the technique beyond the specific example presented. We believe that such modelling techniques can greatly advance the field of molecular gut‐content analysis.</p> </abstract>