Abstract: Current protected habitat networks may be unsuitable to facilitate climate induced species range shifts. Designing permeable landscapes, through the creation or protection of habitat in the correct location, requires informed decision making. Computationally efficient metrics of landscape permeability enable conservationists to compare many thousands of alternative landscape configurations prior to assigning limited resources.
Metapopulation models are considered biologically realistic, but their computational inefficiency makes them impractical to use for a large number of landscapes. “Condatis” has been developed as an efficient metric to bridge this gap. However, it is based on an analogy of a resistor network rather than any biological process.
Here we propose an alternative metric, First Passage Time (FPT), which maintains the computational efficiency while portraying a more biologically meaningful process than Condatis. It is defined as the time taken for a random walker on a network of patches, starting at a source patch, to reach a target patch for the first time. Different statistical moments of FPT are calculated.
We compared the metrics’ ability to predict (using statistical models) mean invasion time (as calculated by metapopulation models) on a set of theoretical landscape configurations.
We found that while FPT statistics can be good predictors of invasion time and combinations of FPT statistics could improve predictions significantly, Condatis was generally the strongest single predictor. Adding FPT statistics allowed predictions to be up to 10% more accurate than using Condatis alone. Since FPT statistics are inexpensive to compute, they could be a useful way to improve our assessments of landscape’s suitability to sustain range expansion under climate change.
Our study highlights the application of First Passage Time as novel landscape summary metric, aiding practitioners to efficiently design landscapes robust to climate induced species range shifts.
