Sequential Experimental Design for Predator-Prey Functional Response Experiments

TL;DR

This paper introduces a novel sequential experimental design method for predator-prey functional response studies, reducing data collection costs and time while improving inference quality through sequential Monte Carlo techniques.

Contribution

It develops the first sequential design approach tailored for predator-prey experiments, enhancing efficiency and flexibility in ecological data collection.

Findings

Sequential design outperforms static design in simulations.

Method reduces number of experiments needed.

Code implementation is publicly available.

Abstract

Understanding functional response within a predator-prey dynamic is a cornerstone for many quantitative ecological studies. Over the past 60 years, the methodology for modelling functional response has gradually transitioned from the classic mechanistic models to more statistically oriented models. To obtain inferences on these statistical models, a substantial number of experiments need to be conducted. The obvious disadvantages of collecting this volume of data include cost, time and the sacrificing of animals. Therefore, optimally designed experiments are useful as they may reduce the total number of experimental runs required to attain the same statistical results. In this paper, we develop the first sequential experimental design method for predator-prey functional response experiments. To make inferences on the parameters in each of the statistical models we consider, we use sequential Monte Carlo, which is computationally efficient and facilitates convenient estimation of important utility functions. It provides coverage of experimental goals including parameter estimation, model discrimination as well as a combination of these. The results of our simulation study illustrate that for predator-prey functional response experiments sequential design outperforms static design for our experimental goals. R code for implementing the methodology is available via https://github.com/haydenmoffat/sequential_design_for_predator_prey_experiments.