# Evolution of foraging behaviour induces variable complexity-stability relationships in mutualist-exploiter-predator communities

## TL;DR

This paper explores how foraging behavior evolution affects the stability of complex ecological networks with mutualistic and antagonistic interactions.

## Contribution

The study introduces an adaptive network model to show how foraging adaptations influence complexity-stability relationships in ecological communities.

## Key findings

- Adaptive foraging of top predators can stabilize mutualism but also cause chaotic dynamics under certain conditions.
- Complexity-stability relationships can show multiple patterns, including double-peaked forms under high adaptation and competition.
- Model predictions align with observed patterns in both freshwater and marine ecological communities.

## Abstract

Early ecological theory predicts that complex ecological networks are unstable and are unlikely to persist, despite many empirical studies of such complexity in nature. This inconsistency has fascinated ecologists for decades. To resolve the complexity-stability debate, coupling population dynamics and trait dynamics is considered to be an important way to understand the long-term stability of ecological community assemblages. However, we still do not know how eco-evolutionary feedbacks affect the relationship between complexity and stability in ecologically realistic networks with both antagonistic and mutualistic interactions. Here, we explored an adaptive network model to evaluate how the evolution of foraging preference to determine the relationship between network complexity (i.e., connectance) and stability (i.e., community persistence at steady state) in mutualist-exploiter-predator communities (MEST). Our theoretical results showed: (i) adaptive foraging of the top predator contributes to the stability of mutualism and intermediate intensity of foraging adaptations can lead to chaotic dynamics in a four-species MEST community; (ii) the complexity-stability relationship may show positive monotonic, negative monotonic, peaked and double-peaked patterns in general MEST communities, while the double-peaked pattern is only obtained when both the adaptation intensity and interspecific competition are high. Furthermore, model predictions may be consistent with both the negative monotonic pattern revealed in freshwater communities and the peaked pattern revealed in marine communities. Finally, we infer that foraging adaptations of the top predator may alter positive or/and negative feedback loops (trait-mediated indirect effects) to affect the stability of general MEST communities. Our adaptive network framework may provide an effective way to address the complexity-stability debate in real ecosystems.

In our recent work, we investigated the intricate relationship between network complexity and stability within diverse communities that exhibit both mutualistic and antagonistic interactions. Traditional ecological theories often suggest that complex networks are inherently unstable, yet nature is full of such complexity. To bridge this gap, we developed an adaptive network model that considers both mutualist-exploiter-predator dynamics and the evolution of foraging preferences. Our findings reveal that adaptive foraging strategies can significantly enhance the stability of mutualistic interactions while also introducing potential chaos under certain conditions. We identified various complexity-stability relationship patterns, indicating that both the intensity of foraging adaptations and interspecific competition play critical roles. This insight could help explain the observed variability in stability across different ecological communities. Ultimately, our adaptive network framework offers valuable insights that may help resolve ongoing debates about the stability of complex ecological networks, benefiting both scientific communities and conservation efforts aimed at preserving biodiversity.