Calculating the uncertainty associated to the forecast of species dispersals: Stochastic Flow Connectivity

• Main Author: Alessandro Ferrarini
• Format: Article
• Language: English
• Published: International Academy of Ecology and Environmental Sciences 2016-03-01
• Series: Computational Ecology and Software
• Subjects: biotic flows; dynamical GIS;flow connectivity;gene flow;landscape connectivity; species dispersal; sensitivity analysis; uncertainty
• Online Access: http://www.iaees.org/publications/journals/ces/articles/2016-6(1)/uncertainty-associated-to-the-forecast-of-species-dispersals.pdf
• ISSN: 2220-721X; 2220-721X

To date, corridors for species dispersals have been thought as deterministic outputs emerging from some kind of model. Uncertainty about the individuation of biotic corridors has never been considered. Flow connectivity (FC) is a methodology first introduced in 2013 to forecast biotic flows over real landscapes, alternative to both circuit theory and least-cost modelling. Its name is due to the fact that it resembles in some way the motion characteristic of fluids over a surface. FC predicts species dispersal by minimizing at each time step the potential energy due to fictional gravity force over a frictional 3D landscape built upon the real landscape. In this work, FC is further developed to find a solution to the problem of calculating the uncertainty associated to the forecast of species dispersals. The output of this method is an ''uncertainty polygon'' (e.g., 5% or 10% uncertainty) around the predicted biotic flow. The importance of this new variant of FC is clear: when planning greenways for biodiversity, uncertainty about biotic flows prediction must be taken into account and the planned corridors must encompass the ''uncertainty polygon'' as well, otherwise they are at serious risk to underestimate the necessary space required by animal species to flow over landscape.