A simulation-based method to compare the pest suppression potential of predators: A case study with spiders

Abstract

A B S T R A C TAssessing and comparing the pest killing capacity of predators is a crucial but laborious task during the implementation of sustainable farming systems. Critical attributes of assessment include quantifying predator's attack rate (a) and handling time (T h ). The maximum attack rate (T/T h ) (i.e. the maximum number of prey that can be attacked by a predator during the time interval (T) considered) could be a more precise and interpretable indicator of the potential suppression of pests exerted by a predator; however, its calculation only provides a point estimator usually derived from incomplete datasets (e.g. unbalanced or low replicated experimental designs) that could lead to draw wrong conclusions. We introduce simaR (simulation of maximum attack rates using R), an R library that generates 95% confidence intervals around estimates of the maximum attack rate that can be easily and intuitively used to compare across species. We validated the simulation method and used the empirical results of a controlled laboratory experiment to compare the maximum attack rates of spiders across a range of Medfly prey densities and illustrate how to use simaR with non-replicated partial data. Applying our method we found a significant effect of temperature on the maximum attack rate of two different guilds of spiders, the orb-weaver A. cucurbitina and the ambusher S. globosum that was not relevant regarding their attack rate and handling time. Our method compares different predator species and/or experimental conditions in a simple and reproducible procedure through an accurate, easy-to-use, fast and statistically robust analysis, based on simulation and bootstrapping, that can be used to assess the pest suppression potential of predators by simulating their functional responses from low-effort laboratory trials.

Functional responses of three guilds of spiders: Comparing single‐ and multiprey approaches

“…overlapped with those obtained byBenhadi-Marín et al (2018).Regarding the multiple-prey experiments, our results clearly demonstrated that the presence of alternative prey can shift the predatory efficiency of a generalist predator on a target prey species. For the single-prey experiments, the most and the least efficient spider species against C. capitata were H. rufipes and S. globosum, respectively.…”

“…Finally, the maximum attack rate T/T h (i.e., the maximum number of prey that can be attacked by a predator during the time interval considered) was estimated for each spider species as 24/T h and its confidence intervals generated using the simaR library (Benhadi-Marín et al, 2018). In order to test the effect of additional prey species within the arenas, the multiple-prey functional response analysis was performed for each spider species as described for the single-prey functional responses considering C. capitata as target prey ignoring the other prey species, and then compared with the single-prey functional response assays through the confidence intervals.…”

Functional Response of Chrysoperla carnea (Neuroptera: Chrysopidae) Larvae on Saissetia oleae (Olivier) (Hemiptera: Coccidae): Implications for Biological Control

“…The confidence limits (95%) were determined to consider the differences between the attack rate (a) and the handling time (h) between the three developmental stages using the frair_boot function from the same package. We calculated the maximum attack rate (T/h) and its 95% confidence limits using the function Max_attackRates from the simaR package [32].…”

Functional Response of Harmonia axyridis to the Larvae of Spodoptera litura: The Combined Effect of Temperatures and Prey Instars

“…The ratio of 1/T h represents the maximum predation rate considering a predator that spends all its time handling (i.e., 24 h here). The CIs for maximum predation rate were obtained from a set of 20 simulated samples, and 50 datasets (i.e., 50 simulated replicates) were generated for this study by using "simaR" R software package (Benhadi-Marín et al, 2018). Again, significant differences in maximum predation rates among the temperatures were calculated by non-overlapping CIs.…”