Literature review dataset on predation-risk effects
Cite this dataset
Peacor, Scott et al. (2022). Literature review dataset on predation-risk effects [Dataset]. Dryad. https://doi.org/10.5061/dryad.ffbg79cxt
A well-accepted narrative in ecology is that prey modify traits to reduce predation risk, and the trait modification has costs large enough to cause ensuing demographic, trophic and ecosystem consequences, with implications for conservation, management, and agriculture. But ecology has a long history of emphasizing that quantifying the importance of an ecological process ultimately requires evidence linking a process to unmanipulated field patterns. We suspected that such process-linked-to pattern (PLP) studies were poorly represented in the predation risk literature, which conflicts with the confidence often given to the importance of risk effects. We reviewed 29 years of the ecological literature which revealed that there are well over 4000 articles on risk effects. Of those, 349 studies examined risk effects on prey fitness measures or abundance (i.e., non-consumptive effects) of which only 26 were PLP studies, while 275 studies examined effects on other interacting species (i.e., trait mediated indirect effects) of which only 35 were PLP studies. PLP studies were narrowly focused taxonomically and included only 3 that examined risk effects on unmanipulated patterns of prey abundance. Before asserting that risk effects drive ecological community dynamics, more attention must be given to examining whether risk-effect processes influence unmanipulated field patterns across diverse ecosystems.
Our search was composed of three sub-searches encompassing 1990-2018 (29 years). In the first sub-search, we scoured the literature using prominent risk-effect terms in Web of Science (All Databases; Supporting Information S2) which yielded 4013 publications. One author made a first pass through the papers by reading the titles, and abstracts if necessary, to eliminate papers that clearly did not meet the criteria; many were not ecological or were using the search terms to describe different processes (as in Box 2 in Peacor et al. 2020). From the reduced list, pairs of authors reviewed each paper independently according to the decision rules, and thereafter met to reconcile their scores. Disagreements were passed along and considered by a third member of the team. Finally, the lead author, SDP, reviewed all results with special attention to any that had disagreements or flagged concerns. In this final scoring, difficult papers were discussed among everybody that had reviewed the paper. For approximately 20 papers, when there was a clear question on methodology that we could not discern in the paper, we sought input from the authors of the reviewed paper for clarification. In the end, each paper in the reduced list was examined by 3-4 authors with closer examination given to papers that made it further along the decision tree.
For figure 2, the date represented in panel A concern #NCE (nonconsumptive effects), TMIEs (Trait-mediated indirect effects), either (TMIE or NCEs), and total Ecology papers, identified for each year. The three year average calculation provided. Data normalized by dividing by the total provided. Please see methods of article for further information.
In Figure 2, the data represented in panels B-D is the number of PLP studies identified that examined fitness components. This is given for NCE and TMIE studies. Please see text for description of the categories. E.g. "PLP - Fitness component" is explained there.
In Figure 3, data concern the number of PLP studies that had different fitness components as a response measured, for NCE and TMIE studies.
In Figure 4, data concern number of total studies ("All") and PLP studies that had a given taxa as the prey species, for NCE and TMIE studies. The figure presents % of total, and those percents also provided.
A data tab contains a list of studies that were identified as PLP studies, and whether the prey was Invertabrate or vertabrate, the prey taxa, whether the study looked at a fitness measure, population growth rate or abundance, and the fitness correlate measured if there was one. (Same information provided in supplementary material S4)
National Science Foundation, Award: OCE-1736943
National Science Foundation, Award: DEB-1145808
Stuart W. Stedman Chair for 4 White-tailed Deer Research