# Unveiling the Hidden Feast: A Model to Translate Molecular Detection Into Predation Rate—Application Example on Biological Control by Generalist Predators in Agricultural Fields

## TL;DR

This paper introduces a new model to estimate how often predators eat prey using molecular data, which helps improve understanding of biological control in agriculture.

## Contribution

The novel model integrates field and lab data to estimate predation rates and introduces a new biocontrol indicator.

## Key findings

- The model estimates predation rates for 25 carabid beetle species and 5 prey types in agricultural fields.
- A new community-scale biocontrol indicator is introduced based on predation rate estimates.
- The model's performance is evaluated and compared to existing predation models.

## Abstract

Few processes are as decisive as predation in shaping the structure and dynamics of ecological communities. For most predator species, however, the number of prey items killed by a predator in a day (predation rate) remains impossible to assess because direct observations are scarce or impossible to acquire. For such species, molecular gut content analyses are routinely used to test for the presence of a prey in the predator's gut. Specifically, our model uses a novel mechanistic representation of predation and digestion to integrate field data on prey detection and laboratory data on prey molecular signal decay in the predator's gut. Model fit provides an estimate of the slope and intercept of the digestion curve (molecular signal decay) and an estimate of the predation rate. In a case study targeting 25 carabid beetle species and 5 types of prey in agricultural fields (winter wheat), we use our model to estimate predation rates for each predator–prey pair. Based on predation rate estimates, we introduce a new biocontrol indicator at community scale and explore its potential for advanced agroecological research. We discuss the performance of our model on the basis of the scant information available in the literature and detail its conditions of application to highlight its advantages over existing predation models.