A Graph-Theory Approach to Landscape Connectivity

How does network analysis improve the understanding of landscape dynamics?

Cátia Matos

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Photo by Red Zeppelin on Unsplash

Conservation efforts have relied on ecological modelling for a long time now.

To consider an effective conservation action future implications need be to predicted under habitat fragmentation scenarios.

Network analysis is a valuable analytic tool in ecology because it combines habitat patch dynamics, distribution and habitat suitability within a landscape-scale analysis.

Here, graph theory can be used in connectivity analysis to locate high-quality patches in the landscape networks and improve the knowledge of species movements in patchy environments such as suburban areas.

This article aims to present a case study on how to use network analysis while prioritizing landscape areas for a threatened amphibian species.

Contents:I. Landscape connectivity and animal movements1.1 Amphibian migration movements1.2 Importance of identifying High-quality habitat (HQH)II. Connectivity modelling using graph theoryIII. Mitigation implications and conclusions

I. Landscape connectivity and animal movements

Landscape connectivity modelling includes both the structural elements and the functional traits of the landscape. This is because we need to imply the future scenarios when animal presence and movements are at risk from human actions.

Structural connectivity corresponds to the physical structure of a landscape. For example, topography, location of linear infrastructures like roads or railways. Functional connectivity is linked to the behavioural traits of wildlife while moving across the structural elements of the landscape. This includes distances of migration or dispersal, avoidance behaviour, specific responses from animal to types of habitats.

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Cátia Matos

Movement Ecology Ph.D / Lecturer in Spatial Ecology / Publishing about research, data and life.