Applying Network Analysis to the Conservation of Habitat Trees in Urban Environments: a Case Study from Brisbane, Australia

Abstract

In Australia more than 300 vertebrates, including 43 insectivorous bat species, depend on hollows in habitat trees for shelter with many species using a network of multiple trees as roosts. We used roost-switching data on white-striped freetail bats (Tadarida australis; Microchiroptera: Molossidae) to construct a network representation of day roosts in suburban Brisbane, Australia. Bats were caught from a communal roost tree with a roosting group of several hundred individuals and released with transmitters. Each roost used by the bats represented a node in the network, and the movements of bats between roosts formed the links between nodes. Despite differences in gender and reproductive stages, the bats exhibited the same behavior throughout three radiotelemetry periods and over 500 bat days of radio tracking: each roosted in separate roosts, switched roosts very infrequently, and associated with other bats only at the communal roost. This network resembled a scale-free network in which the distribution of the number of links from each roost followed a power law. Despite being spread over a large geographic area (> 200 km2), each roost was connected to others by less than three links. One roost (the hub or communal roost) defined the architecture of the network because it had the most links. That the network showed scale-free properties has profound implications for the management of the habitat trees of this roosting group. Scale-free networks provide high tolerance against stochastic events such as random roost removals but are susceptible to the selective removal of hub nodes. Network analysis is a useful tool for understanding the structural organization of habitat tree usage and allows the informed judgment of the relative importance of individual trees and hence the derivation of appropriate management decisions. Conservation planners and managers should emphasize the differential importance of habitat trees and think of them as being analogous to vital service centers in human societies.

Insectivorous Bats and Silviculture: Balancing Timber Production and Bat Conservation

“…Roost networks of northern long-eared bat, Myotis septentrionalis, in actively managed forests were scale-free and connected to a single central-node roost tree (Johnson et al 2012a). A similar pattern was observed for the open-space foraging white-striped free-tail bat, Tadarida australis, in south-east Queensland (Rhodes et al 2006). Given these patterns, we postulate that implementation of silvicultural systems, which promote retention of higher densities of dead and old living trees across forested ecosystems, should benefit bark-and cavity-roosting bats and facilitate 'natural patterns' in colony behaviours, social interactions, and the use of roost networks.…”

Four issues influencing the management of hollow-using bats of the Pilliga forests of inland New South Wales

“…Willis and Brigham (2004) suggest that this could be widespread among temperate zone bat species. A fission-fusion model has been proposed for the White-striped Freetailed Bat Tadarida australis in south-eastern Queensland (Rhodes and Wardell-Johnson 2006). They found that one hollow tree appeared to be a central hub through which many individuals moved en route to other localities, implying an important social role for such movements, including information transfer between individuals, such as the location of roost sites and foraging areas.…”

A Graph‐Theory Framework for Evaluating Landscape Connectivity and Conservation Planning

“…Recently, a network of bat-roosting trees was shown to have scale-free topology (Rhodes et al 2006). Nevertheless, a single landscape can have very different connectivity characteristics when examined from the perspective of different organisms (Bunn et al 2000).…”

“…Although graph theory has only recently been introduced to the field of landscape ecology (Urban & Keitt 2001;Jordan et al 2003;Rhodes et al 2006), there is a welldeveloped body of research from computer and social sciences that quantifies connectivity and flow in networks. Graph theory offers insight into regional and emergent network properties in an intuitive and visual way, provides a framework for cross-scale analysis, and allows spatially explicit representation of dynamics.…”

“…Although graph theory does not require knowledge of behavior, fecundity, or mortality parameters, these data can be incorporated and used to create an ecologically rich graph model. Empirical occupancy and movement data can also be used (but are not required) to build a graph that shows actual connectivity for a given species (e.g., Rhodes et al 2006). Alternatively, the graph can be built with connectivity estimates from a dispersal model, such as a spatially structured diffusion model (Ovaskainen 2004).…”