Empirical assessment of the relation between ecological connectivity and land complexity based on information-theoretic metrics

Abstract

Habitat fragmentation and connectivity loss pose significant threats to biodiversity at both local and landscape levels. Strategies to increase ecological connectivity and preserve strong connectivity are important for dealing with the potential threat of habitat degradation. Various metrics have been used to measure (i.e., quantify) landscape composition and configuration in landscape ecology. However, their relationship with ecological connectivity must be understood to interpret landscape patterns comprehensively. In the present study, correlations between ecological connectivity and land complexity are examined based on information-theory metrics. Two primary questions are explored: (1) to what extent are landscape mosaic measures of entropy correlated with ecological connectivity, with landscape gradient-based measures, and with each other? (2) are landscape gradient-based entropy measures correlated with ecological connectivity more than discrete entropy measures? Results show that all information theoretic metrics are statistically significant (p < 0.05) for modelling ecological connectivity. Among categorically-based indices, the relationship between ECI and joint entropy was the most significant, while a generalized additive model indicated that Boltzmann entropy could predict the ecological connectivity index, explaining ∼60% of the variance. Therefore, configurational entropy can be used for improving ecological connectivity models.