Data from: Predicting the continuum between corridors and barriers to animal movements using Step Selection Functions and Randomized Shortest Paths

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.