Binary space partitioning generates hierarchical and rectilinear neutral landscape models suitable for human-dominated landscapes

Abstract

AbstractContextNeutral landscape models are useful and popular tools for exploring effects of spatial patterns on ecological processes. Most neutral landscape models mimic natural landscape patterns that often consist of curved, complex, and sometimes fractal shapes. However, human-dominated landscapes often have a spatial rectilinear pattern that is highly aligned and dominated by straight lines and right angles.ObjectivesAs existing rectilinear neutral landscape models lack controls over either the size, position, orientation, and shape of the rectilinear patches, or do not recognise the hierarchical structure of patch formation in human-dominated landscapes, our objective was to create a neutral landscape model capable of meeting these requirements.MethodsWe present binary space partitioning as a method that generates hierarchical and rectilinear neutral landscape models. In doing so we explain how to control the size, position, orientation, and shape of the rectilinear patches, as well as generate a tree that records the hierarchical patch structure.ResultsBinary space partitioning succeeds in providing a simple, repeatable, process to generate a range of neutral landscape models for human-dominated landscapes. A large variety of landscape patterns can be efficiently produced from only a very small number of parameters.ConclusionsBinary space partitioning based neutral landscape models would be useful in representing many human-dominated landscapes. Their implementation is straightforward and should be easily understood, used, and developed by landscape ecologists.