State‐space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape

Abstract

Abstract Habitat loss is a major cause of species loss and is expected to increase. Loss of habitat is often associated with fragmentation of remaining habitat. Whether species can persist in fragmented landscapes may depend on their movement behavior, which determines their capability to respond flexibility to changes in habitat structure and spatial distribution of patches. Movement is frequently generalized to describe a total area used, or segmented to highlight resource use, often overlooking finer‐scale individual behaviors. We applied hidden Markov models (HMM) to movement data from 26 eastern bettongs (Bettongia gaimardi) in fragmented landscapes. HMMs are able to identify distinct behavior states associated with different movement patterns and discover how these behaviors are associated with habitat features. Three distinct behavior states were identified and interpreted as denning, foraging, and fast‐traveling. The probability of occurrence of each state, and of transitions between them, was predicted by variation in tree‐canopy cover and understorey vegetation density. Denning was associated with woodland with low canopy cover but high vegetation density, foraging with high canopy cover but low vegetation density, and fast‐traveling with low canopy cover and low vegetation density. Bettongs did move outside woodland patches, often fast‐traveling through pasture and using smaller stands of trees as stepping stones between neighboring patches. Males were more likely to fast‐travel and venture outside woodlands patches, while females concentrated their movement within woodland patches. Synthesis and applications: Our work demonstrates the value of using animal movement to understand how animals respond to variation in habitat structure, including fragmentation. Analysis using HMMs was able to characterize distinct habitat types needed for foraging and denning, and identify landscape features that facilitate movement between patches. Future work should extend the use of individual movement analyses to guide management of fragmented habitat in ways that support persistence of species potentially threatened by habitat loss.

Keywords

• conservation
• fragmentation
• Hidden Markov Models
• management
• movement ecology
• restoration