Evidence map›Paper›PMID 42710508›Full record

ReviewEcology2026

Knowledge gaps and areas for synthesis in experimental studies of context-dependent predation risk.

Nicole E Peckham, Scott D Peacor, Michael J Sheriff, Justine A Smith, Nathan J Dorn, Michael J Cherry, Tanya L Rogers, David L Kimbro

Abstract readReview
In one paragraph

Review in Ecology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Nicole E PeckhamDepartment of Marine and Environmental Science, Northeastern University, Nahant, Massachusetts, USA.ORCID https://orcid.org/0000-0003-4942-4018
Scott D PeacorDepartment of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA.ORCID https://orcid.org/0000-0002-5334-7775
Michael J SheriffBiology Department, University of Massachusetts Dartmouth, North Dartmouth, Massachusetts, USA.
Justine A SmithDepartment of Wildlife, Fish, and Conservation Biology, University of California-Davis, Davis, California, USA.ORCID https://orcid.org/0000-0001-8753-4061
Nathan J DornDepartment of Biological Sciences and Institute of Environment, Florida International University, Miami, Florida, USA.
Michael J CherryCaesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, Texas, USA.ORCID https://orcid.org/0000-0002-5771-0893
Tanya L RogersSouthwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Santa Cruz, California, USA.ORCID https://orcid.org/0000-0003-1253-9903
David L KimbroDepartment of Marine and Environmental Science, Northeastern University, Nahant, Massachusetts, USA.ORCID https://orcid.org/0000-0003-4711-3531

Funding

NSF DEB-1145808NSF OCE-1736943
6 · The paper itself

Abstract

A growing number of experimental studies address whether the anti-predator trait responses of prey are associated with costs to prey fitness (non-consumptive effects) or to the fitness of other species (trait-mediated indirect effects). Because ecologists remain keen to determine when these risk effects matter, there is a need to know how much of this literature has also evaluated the context-dependence of risk effects. Such knowledge would identify both understudied research directions and richly investigated areas whose synthesis could advance general understanding of predation risk effects. As a guide for ecologists, we reviewed publications from 1990 to 2021 that experimentally manipulated both predation risk (presence/absence of risk) and another aspect of biotic or abiotic condition (context). We classified each experiment according to a common scheme: the manipulated context was assigned to a Focus (predator, prey, resource, or environment) and Category (community, population, or individual for biotic contexts; temperature, water, habitat, or anthropogenic disturbance for abiotic contexts). A finer categorization of Specific Context (e.g., predator identity, resource abundance) was assigned within each Focus and Category. We also identified the System (marine, freshwater, terrestrial) and Venue (laboratory or field) of each experiment. We classified 433 manipulations (339 publications) falling within 49 different Specific Contexts. Many experiments (63%) manipulated aspects of the predator and/or prey Foci, independently and factorially. Additionally, several Specific Contexts have many published papers and could be suitable for synthesis, including predator and prey identity, predator diversity, prey and resource abundance, habitat structure, and temperature. Meanwhile, manipulations of resources of the prey are relatively lacking. Because most experiments (51%) featured freshwater systems, more marine and terrestrial experiments are needed. Regardless, an imbalance between laboratory (69%) and field (31%) experiments highlights the need for more field investigations. We discuss potential contributors to biases in the literature and consider how understudied contexts should be prioritized. Consequently, our review undergirds future work on the context-dependency of predation risk effects. As many biotic and abiotic contexts are impacted by anthropogenic activities, optimizing the integration of experimental approaches with other research efforts is crucial to furthering the development and application of predation risk theory.

Indexed as

Food ChainPredatory BehaviorAnimalsEcosystemcontext‐dependenceecology of fearliterature reviewnonconsumptive effectsnon‐lethaltrait‐mediated indirect effectstrait response

Identifiers

PMID42710508
PMCPMC13553125

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.