Characterising landscape connectivity using a dispersal guild approach

Authors and Affiliations: 

Alex Mark Lechner (1), Daniel Sprod (2), Oberon Carter (3), Edward C. Lefroy (4)

(1) School of Environmental and Geographical Sciences, University of Nottingham Malaysia Campus, 43500 Semenyih, Malaysia
(2) Tasmanian Land Conservancy, Tasmania (Australia)
(3) Natural and Cultural Heritage Division, Department of Primary Industries, Parks, Water and Environment, Hobart, Tasmania (Australia)
(4) Centre for Environment, University of Tasmania, Hobart Tasmania (Australia)

Corresponding author: 
Alex Lechner

Connectivity is increasingly seen as a requirement for effective conservation in fragmented landscapes, but the question remains: ‘connectivity for which species?’ We developed a method for modelling connectivity for multiple species by extending the guild concept to include species with similar dispersal and habitat characteristics. This approach allows for the application of a rapid, expert-based connectivity model where species are grouped on similar fine-scale dispersal behaviour (such as between scattered trees) and habitat characteristics. These connectivity modelling parameters describe fine-scale connectivity using two thresholds: the interpatch-crossing distance and gap-crossing distance (Lechner et al 2015). The gap-crossing distance is the maximum distance a species will cross between fine-scale connectivity elements (such as scattered trees) and/or habitat patches. Individual species are allocated to a dispersal guild using an unsupervised cluster analysis and then expert opinion. Connectivity is modelled for each of the dispersal guilds with Graphab (Foltête et al 2012) to calculate graph-metrics and least-cost paths between patches and Linkage Mapper (with Circuitscape) (McRae et al 2008; McRae and Kavanagh 2011) to characterise least-cost corridors and individual movement probabilities for each of the dispersal guilds.

We demonstrate the application of this method to conservation planning by modelling connectivity for 12 mammal species of conservation concern in the Tasmanian Northern Midlands, Australia. Six groupings were identified from the original 12 with the cluster analysis. Five dispersal guilds from the original six groupings were agreed to by the expert panel. The expert panel labelled the guilds according to the ecological characteristics that united group members. Three guilds were made up of smaller mammals with shorter interpatch-crossing and gap-crossing dispersal distances and smaller habitat requirements and two separate single-species dispersal guilds were made up of medium-sized carnivores with long, but distinct dispersal distances. The connectivity analysis of the five dispersal guilds showed large differences in the effects of fragmentation. For the two medium-sized carnivores the landscape essentially appeared connected. While from the perspective of the three dispersal guilds of smaller mammals, the landscape appeared highly fragmented.

Decision makers need tools that are sufficiently flexible and dynamic to assess connectivity without being too complex, difficult to use or time-consuming. The method outlined is an intermediate between single species or multiple single species connectivity models and general habitat-based. The outputs provide guidance on where effort invested in connectivity is likely to be effective for different combinations of species, and where restoration is likely to be of little value. The method is developed for conservation planners who have limited data and resources, but yields broadly applicable and biologically defensible outputs. The outputs provide a useful basis from which to prioritise conservation investment for connectivity and further research.


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Lechner AM, Doerr V, Harris RMB, et al (2015) A framework for incorporating fine-scale dispersal behaviour into biodiversity conservation planning. Landsc Urban Plan 141:11–23. doi: 10.1016/j.landurbplan.2015.04.008

Lechner AM, Sprod D, Carter O, Lefroy EC (2016) Characterising landscape connectivity for conservation planning using a dispersal guild approach. Landsc Ecol 32:99–113. doi: 10.1007/s10980-016-0431-5

McRae BH, Dickson BG, Keitt TH, Shah VB (2008) Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89:2712–2724. doi: 10.1890/07-1861.1

McRae BH, Kavanagh DM (2011) Linkage Mapper Connectivity Analysis Software. doi: 10.1016/S0022-3913(12)00047-9

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