Modelling the influence of landscape connectivity on animal distribution: a functional grain approach

Authors


P. Galpern, Natural Resources Inst., Univ. of Manitoba, 70 Dysart Road, Winnipeg, MB R3T 2N2, Canada. E-mail: pgalpern@gmail.com

Abstract

Landscape change may reduce the connectivity of landscapes and impact the movement of animals. If movement processes have been influenced by landscape connectivity, we hypothesize that animals may distribute themselves in larger connected regions of the landscape in order to minimize the movement costs associated with obtaining required resources and avoiding predators. We adopt the term functional grain to describe a set of functionally connected regions. In this spatial pattern, each region describes a contiguous area of the landscape within which an animal may move freely below a threshold amount of movement cost. We used telemetry data from woodland caribou Rangifer tarandus caribou to test hypothetical functional grains where connectivity was determined by the spatial configuration of resource patches (patch only), by the resistance to movement presented by landscape features (resistance only), and by a combination of the two (patch + resistance). To identify these functional grains, we used a grains of connectivity approach, and introduced a novel lattice-based variant of this method to build the resistance only model. We developed a measure of fit that describes caribou distribution with respect to larger functionally connected regions in the grain, and used this to ask: 1) are seasonal caribou locations consistent with a random functional grain, implying that landscape connectivity has not shaped their distribution? 2) Given a functional grain model, are seasonal caribou locations distributed in larger functionally connected regions than random points, implying a response to the shape, size, and location of the connected regions. We found support for landscape connectivity influencing animal distribution using grains based on a landscape resistance model, and that support varied between behaviourally defined seasons. We also discuss how our novel lattice approach may be valuable for highly mobile mammals and other species where the identification of resource patches is a limitation.

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