DOI: 10.5061/dryad.4v13r
title: Data from: Predicting the continuum between corridors and barriers to animal movements using Step Selection Functions and Randomized Shortest Paths

description: 1. The loss, fragmentation and degradation of habitat everywhere on Earth
 prompts increasing attention to identifying landscape features that
 support animal movement (corridors) or impedes it (barriers). Most
 algorithms used to predict corridors assume that animals move through
 preferred habitat either optimally (e.g. least cost path) or as random
 walkers (e.g. current models), but neither extreme is realistic. 2. We
 propose that corridors and barriers are two sides of the same coin and
 that animals experience landscapes as spatiotemporally dynamic
 corridor-barrier continua connecting (separating) functional areas where
 individuals fulfil specific ecological processes. Based on this conceptual
 framework, we propose a novel methodological approach that uses
 high-resolution individual-based movement data to predict corridor-barrier
 continua with increased realism. 3. Our approach consists of two
 innovations. First, we use step selection functions (SSF) to predict
 friction maps quantifying corridor-barrier continua for tactical steps
 between consecutive locations. Secondly, we introduce to movement ecology
 the randomized shortest path algorithm (RSP) which operates on friction
 maps to predict the corridor-barrier continuum for strategic movements
 between functional areas. By modulating the parameter Ѳ, which controls
 the trade-off between exploration and optimal exploitation of the
 environment, RSP bridges the gap between algorithms assuming optimal
 movements (when Ѳ approaches infinity, RSP is equivalent to LCP) or random
 walk (when Ѳ → 0, RSP → current models). 4. Using this approach, we
 identify migration corridors for GPS-monitored wild reindeer (Rangifer t.
 tarandus) in Norway. We demonstrate that reindeer movement is best
 predicted by an intermediate value of Ѳ, indicative of a movement
 trade-off between optimization and exploration. Model calibration allows
 identification of a corridor-barrier continuum that closely fits empirical
 data and demonstrates that RSP outperforms models that assume either
 optimality or random walk. 5. The proposed approach models the multiscale
 cognitive maps by which animals likely navigate real landscapes and
 generalizes the most common algorithms for identifying corridors. Because
 suboptimal, but non-random, movement strategies are likely widespread, our
 approach has the potential to predict more realistic corridor-barrier
 continua for a wide range of species.
description: dataframeData to replicate analyses in Panzacchi et al 2015, JAEenv_raster_brickraster data needed to make mapsshapefilesshapefiles of the study area needed to perform the analysesData.zipKernelUtilizationDistributionKernel Utilization distribution of winter and calving locationsBBMM_Aust_March_MayBBMM_Aust_March_May.tif is a georeferenced raster that can be visualized in QGIS. It illustrates the results of the Brownian Bridge Movement Model built on wild reindeer locations during the period march-May (i.e. spring migration)