Evidence map›Paper›PMID 25234371›Full record

ArticleOecologia2014

Diagnosing predation risk effects on demography: can measuring physiology provide the means?

Liana Y Zanette, Michael Clinchy, Justin P Suraci

Abstract read
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In one paragraph

Article in Oecologia, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.6field-weighted citation impact, top 4% of its field
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

16 citing papers in PubMed, 53 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Liana Y ZanetteDepartment of Biology, University of Western Ontario, 1151 Richmond Street, London, ON, N6A 5B7, Canada, lzanette@uwo.ca.
Michael Clinchy
Justin P Suraci
University of Victoria · CAWestern University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predators kill prey thereby affecting prey survival and, in the traditional top-down view of predator limitation, that is their sole effect. Bottom-up food limitation alters the physiological condition of individuals affecting both fecundity and survival. Predators of course also scare prey inducing anti-predator defences that may carry physiological costs powerful enough to reduce prey fecundity and survival. Here, we consider whether measuring physiology can be used as a tool to unambiguously diagnose predation risk effects. We begin by providing a review of recent papers reporting physiological effects of predation risk. We then present a conceptual framework describing the pathways by which predators and food can affect prey populations and give an overview of predation risk effects on demography in various taxa. Because scared prey typically eat less the principal challenge we see will be to identify measures that permit us to avoid mistaking predator-induced reductions in food intake for absolute food shortage. To construct an effective diagnostic toolkit we advocate collecting multiple physiological measures and utilizing multivariate statistical procedures. We recommend conducting two-factor predation risk × food manipulations to identify those physiological effects least likely to be mistaken for responses to bottom-up food limitation. We suggest there is a critical need to develop a diagnostic tool that can be used when it is infeasible to experimentally test for predation risk effects on demography, as may often be the case in wildlife conservation, since failing to consider predation risk effects may cause the total impact of predators to be dramatically underestimated.

Indexed as

Food ChainAnimalsInvertebratesPopulation DynamicsPredatory BehaviorRiskVertebrates

Identifiers

PMID25234371
OpenAlexW2093006908

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.