# Dining in danger: Resolving adaptive fish behavior increases realism of modeled ecosystem dynamics

## TL;DR

This paper shows how modeling realistic fish behavior improves predictions of ecosystem dynamics and stability.

## Contribution

The study introduces a mechanistic model of adaptive fish behavior that enhances ecosystem modeling realism and stability.

## Key findings

- Adaptive fish behavior stabilizes food web dynamics in ecosystem models.
- Including optimal behavior leads to more realistic responses to environmental changes.
- Behavioral trade-offs significantly influence trophic control and food web structure.

## Abstract

Animals occupying higher trophic levels can have disproportionately large influence on ecosystem structure and functioning, owning to intricate behavioral responses to their environment, but the effects of behavioral adaptations on aquatic ecosystem dynamics are underrepresented, especially in model studies. Here, we explore how adaptive behavior of fish can affect the dynamics of aquatics ecosystems. We frame fish behavior in the context of the central trade‐off between feeding and predation, calculating the optimal level of feeding determined by ambient food availability and predation risk. To explore whole‐ecosystem consequences of fish behavior, we embed our behavioral model within the Water Ecosystems Tool (WET), a contemporary end‐to‐end aquatic ecosystem model. The principle of optimality provides a robust and mechanistic framework for representing animal behavior that is relevant for complex models, and can provide a stabilizing effect on model dynamics. The model predicts an emergent functional response similar to Holling type III, but with richer dynamics and a more rigorous theoretical foundation. We show how adaptive fish behavior works to stabilize food web dynamics compared to a control model with no optimal behavior, and how changing the strength of the underlying trade‐off has profound effects on trophic control and food web structure. Furthermore, we demonstrate how including fish behavior allows for an overall more realistic response of the model system to environmental perturbation in the form of nutrient enhancement. We discuss the structuring effects of behavioral adaptations in real ecosystems, and how approaches like this one may benefit aquatic ecological modeling. Our study further highlights how a mechanistic approach based on concepts from theoretical ecology can be successfully implemented in complex operational models resulting in improved dynamics and descriptive power.

We investigated how the trade‐off between predator avoidance and feeding in fish can influence the function and structure of a modeled lake ecosystem. The results showcase how more realistic behavior in ecosystem models can have many benefits, including more realistic model responses to perturbation and increased model stability.