# Effects of Landscape Compositional Heterogeneity and Spatial Autocorrelation on Environmental Niche and Dispersal in Simulated Organisms

## TL;DR

This study explores how landscape structure affects the evolution of environmental niche and dispersal traits in simulated organisms.

## Contribution

The study integrates local adaptation, environmental tolerance, and dispersal in a spatially explicit model to examine their joint evolution.

## Key findings

- Compositional heterogeneity had the strongest influence on trait evolution.
- Spatial autocorrelation acted as a mediator in trait selection.
- Dispersal frequency and distance responded differently to landscape structure.

## Abstract

Local adaptation, environmental tolerance, and dispersal mutually influence the evolution of one another and each are in turn influenced by landscape spatial structure. While each of the three have been investigated frequently in isolation in relation to spatial structure, the three have rarely been considered together. In this study, we explored how the magnitude of landscape environmental heterogeneity (compositional heterogeneity), and environmental spatial autocorrelation jointly affect the evolution of environmental niche optima, tolerance, dispersal frequency, and dispersal distance using a spatially explicit individual based model simulating organisms living, reproducing, and dispersing within grid‐based fractal landscapes. Compositional heterogeneity tended to have the strongest influence over patterns while spatial autocorrelation typically played a mediating role. We found that niche adaptation and dispersal patterns were driven by a balance between pressure to avoid risk imposed by spatial heterogeneity and pressure to hedge against risk imposed by temporal environmental fluctuations. Dispersal frequency and dispersal distance were affected differently by spatial structure, underscoring the importance of considering the two independently.

This study examines how local adaptation, environmental tolerance, and dispersal evolve in response to landscape spatial structure, specifically focusing on environmental heterogeneity and spatial autocorrelation. Using a spatially explicit individual‐based model, we found that compositional heterogeneity had the strongest influence, while spatial autocorrelation played a mediating role in selection on traits. Niche adaptation and dispersal patterns were shaped by the balance between avoiding spatial risks and hedging against temporal fluctuations, with dispersal frequency and distance affected differently by the landscape structure.