Graph theory in ecological network analysis: A systematic review for connectivity assessment

Abstract

Graph theory (GT) has become an indispensable tool for exploring environmental interconnections and elucidating ecological relationships. The integration of GT with Ecological network analysis (ENA) has been increasingly recognised for its potential to enhance our understanding of ecological systems. However, the application of GT in ENA faces several limitations that warrant closer examination. This paper aims to investigate these challenges through a systematic review, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review encompasses 329 selected articles published from January 2014 to December 2021, highlighting GT's uptake in ENA but also pinpointing significant challenges. The review reveals that while GT offers flexibility in analysing different ecological networks (ENs), challenges exist related to understanding landscape dynamics, the accuracy of measurement scale, species-specific data, and reliability. Specially, the use of nodes and links presents definitional and measurement complexities, compounded by an overwhelming variety of indicators that may dilute analytical precision. The paper advocates for the development of frameworks to conceptualise ideal and sustainable ENs and to establish indicators for assessing network efficacy. Future research must tackle these methodological hurdles, with a special focus on refining measurement scale, species-specific data, spatio-temporal considerations, and node and link assessment for different species, while ensuring reliability. Additionally, the potential of GT to mitigate the impact of ecological threats is underscored as a critical area for future applications. Addressing these challenges is imperative for advancing GT's contribution to ENA and fostering more effective environmental conservation strategies.