Broadening the ecology of fear: non-lethal effects arise from diverse responses to predation and parasitism
Daversa, David (2021), Broadening the ecology of fear: non-lethal effects arise from diverse responses to predation and parasitism, Dryad, Dataset, https://doi.org/10.5061/dryad.fxpnvx0qf
The ecology of fear demonstrates how prey responses to avoid predation cause non-lethal effects at all ecological scales. Parasites also elicit defensive responses in hosts with associated non-lethal effects, which raises the longstanding, yet unresolved question of how non-lethal effects of parasites compare with those of predators. We developed a framework for systematically answering this question for all types of predator and parasite systems. Our framework predicts that trait responses and their non-lethal effects should be strongest from predators and parasites that do not kill individuals to feed on them, but which nevertheless damage fitness. Analysing trait response data on amphibians, which have been well-studied for this area of research, showed that individuals generally responded more directly to short-term predation risks than to parasitism. Apart from studies using amphibians, there have been few direct comparisons of responses to predation and parasitism, and none have incorporated responses to micropredators, parasitoids, or parasitic castrators, or examined their long-term consequences. Addressing these and other data gaps highlighted by our general framework can advance the field toward understanding how non-lethal effects shape real food webs, which contain multiple predator and parasite species.
Data were compiled as part of a systematic review with the aims to (a) assess the breath of empirical studies to directly compare trait responses to predators and parasites, and (b) seek support for the predictions emerging from our general trait response framework.
We searched for literature using Google Scholar and Web of Science, using combinations of terms describing consumers (consumer, predat*, parasit*, anti-parasit*, anti-predat*, infect*, natural enemy), resources (host, prey, resource), traits (behavio*, activity, space use, refuge use, feeding, development), and effects (non-lethal, sub-lethal, risk, trait-mediated, trait response, indirect). initiated our search on 10 January 2017 and continued to monitor the literature until the time of manuscript submission. considered journal articles that met three criteria:
- measured traits associated with defense in an animal exposed to a predator cue. Cues included media (e.g. water) used by a predator , a consumed conspecific , a predator kept behind a barrier (e.g. mesh cage), or an unrestrained predator.
- measured the same trait response (in the same resource species and life stage, but not necessarily the same individuals) to 1) a parasite cue, such as media previously containing infected hosts or infective stages or direct exposure to parasite infective stages, or 2) in animals infected with parasites.
3. had a control, wherein defense traits were measured in individuals that were not exposed to either a parasite or predator cue.
We did not include studies of trade-offs between predation and parasitism that used infection (in the case of predator effects) or predation (in in the case of parasite effects) as response variables because different traits were measured between “predator” and “parasite” treatments, and therefore were not comparable.
We used the digitize package in R to extract data from figures. We recorded the number of replicates as ll as the mean and variance (SE or SD) of the response variables separately for controls, predator treatments, and parasite treatments. Studies often included a treatment containing both a predator and parasite cue (hereafter referred to as ‘combined’). We recorded these treatments as separate entries, with independent sample sizes, means, and variances. For studies that measured responses in multiple resource species and/or for multiple traits, we treated each species and trait as a different entry. When data were recorded across multiple days, we pooled data to calculate a single response mean and variance. We also pooled data from any additional treatments that varied factors such as consumer density or exposure frequency, and again calculated the response mean and variance for predator, parasite and, when applicable, combined treatments.