Global biodiversity is in crisis. Faced with incomplete information, limited resources, and a myriad of demands from stakeholders, conservation practitioners need to identify priority areas for conservation. To help resolve this, systematic conservation planning provides a framework that combines biodiversity, economic, and land use data with optimization algorithms to generate conservation plans. Although systematic conservation planning has traditionally relied on ranking, heuristic, and meta-heuristic algorithms, exact algorithm solvers (such as Gurobi) are becoming increasingly common.
In this webinar, Dr. Jeffrey Hanson, Postdoctoral Scientist, Carleton University, will start with an introduction to systematic conservation planning, explain some of the key concepts and mathematical problems formulations for generating conservation plans, and highlight case studies from the literature. Dr. Richard Schuster, Director of Social Planning and Innovation, Nature Conservancy of Canada, will then compare exact algorithm solvers with conventional software for conservation planning, and talk about some real-world examples where exact algorithms solvers — such as Gurobi — have been used to help guide conservation decisions. By using exact algorithm solvers, conservation practitioners can quickly identify cost-effective conservation plans to inform decision making.
Dr. Jeffrey Hanson
Postdoctoral Scientist, Carleton University, Canada
Dr. Jeffrey Hanson is a postdoctoral scientist at Carleton University, Canada. His research focuses on solving the challenges that prevent us from creating plans to conserve biodiversity. His work includes applying optimization algorithms to solve problems in conservation (e.g., allocating funds for species’ recovery projects or identifying priority areas for protection), leveraging novel datasets to better inform conservation decision making (e.g., using genetic data to prioritize conservation efforts), identifying cost-effective surrogate data when high quality data are not available (e.g., using environmental data as a proxy for genetic data), and comparing different planning methodologies to inform best practice (e.g., comparing different approaches to account for connectivity). To make his research accessible, he contributes to the development of open source data processing and decision support tools (e.g., prioritizr, raptr, oppr, wdpar R packages). For more information, see his website: http://jeffrey-hanson.com.
Dr. Richard Schuster
Director of Spatial Planning and Innovation, Nature Conservancy of Canada
Adjunct Professor, Carleton University
Dr. Richard Schuster completed his PhD at the University of British Columbia focusing on systematic conservation planning in human dominated landscapes. Richard is the director of spatial planning and innovation at the Nature Conservancy of Canada (NCC), the largest not for profit land conservation organization in Canada. He is responsible for the development and implementation of NCC’s conservation planning framework, strategic conservation planning research efforts and new conservation technology initiatives. Richard has over 15 years of experience working on systematic conservation planning and spatial modelling for conservation purposes. For more information, see his website: https://richard-schuster.com/.
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