Circuitscape in Julia: High Performance Connectivity Modelling to Support Conservation Decisions
Ranjan Anantharaman, Kimberly R. Hall, Viral B. Shah, Alan Edelman
Abstract
Connectivity across landscapes influences a wide range of conservation-relevant ecological processes, including species movements, gene flow, and the spread of wildfire, pests, and diseases. The computational demands of the next generation of connectivity models and the availability of increasingly fine-grained remote sensing data drive the need for faster software for connectivity modelling. To address this, we upgraded the widely-used Circuitscape connectivity package to the Julia programming language. The Julia package, Circuitscape.jl, can solve much larger problems up to an order of magnitude faster, with improved solvers and parallel computing features. We demonstrate scaling up to problems of 437 million grid cells, with speedups of up to 1800% over the previous version. These improvements increase the pace of interaction between scientists and key stakeholders, facilitating faster policy decisions.