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Circuitscape - A Case Study on Scientific Computing
In this talk I would talk about some of the challenges faced in typical scientific computing applications and how to address them, taking Circuitscape as a case study. it would walk the audience briefly through what is possible through modern scientific computing platforms built on Python and Julia.
Circuitscape is an open-source program, which borrows algorithms from electronic circuit theory to predict patterns of movement, gene flow, and genetic differentiation among plant and animal populations in heterogeneous landscapes. It is used by academics, policy makers, and governments around the world in conservation planning.
Created by Brad McRae and Viral B. Shah, it equates life forms to electrons, the landscape as a grid of resistances and the movement of life forms across a landscape as current flowing through a circuit. Interestingly, this has been able to model reality much better than many other approaches. Circuitscape has been used to model raster landscapes containing as many as 20 million cells, covering vast geographies over thousands of square kilometres, resulting in jobs that run over days to compute wildlife corridors.
This talk is about Circuitscape and its application. I will cite the example of Circuitscape usage: “Connectivity of Tiger (Panthera tigris) Populations in the Human-Influenced Forest Mosaic of Central India” during the talk, and how this concept can be applied across other domains.
I am one of the co-creators of the Julia programming language and Circuitscape.