Jeffrey Hanson

Conservation Scientist
I help people make better conservation decisions

About me

   
  • I am a conservation scientist, currently living in Palmerston North, New Zealand. I work remotely as a postdoctoral researcher in the Bennett Lab at Carleton University, Ottawa. I’m interested in helping people make better conservation decisions. My research focuses on applying optimization algorithms to solve problems in conservation (e.g., allocating funds for 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), and identifying cost-effective surrogate data to inform conservation decisions when high quality data are not available (e.g., using environmental data as a proxy for genetic data). I also develop decision support tools to help others apply my findings in their own work (e.g., prioritizr, raptr, oppr, surveyvoi and wdpar R packages). Please reach out if you’d like to chat about my research or have any questions about the decision support tools I’ve helped develop.

  • Publications

       
  • Journal articles

    2024

    2023

    2022

    2021

    2020

    2019

    2018

    2017

    2016

    2015

  • Non-peer reviewed articles

    2020

    2015

  • Projects

  • prioritizr R package
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    The prioritizr R package uses integer linear programming (ILP) techniques to provide a flexible interface for building and solving conservation planning problems. It supports a broad range of objectives, constraints, and penalties that can be used to custom-tailor conservation planning problems to the specific needs of a conservation planning exercise. Once built, conservation planning problems can be solved using a variety of commercial and open-source exact algorithm solvers. In contrast to the algorithms conventionally used to solve conservation problems, such as heuristics or simulated annealing, the exact algorithms used here are guaranteed to find optimal solutions. Furthermore, conservation problems can be constructed to optimize the spatial allocation of different management actions or zones, meaning that conservation practitioners can identify solutions that benefit multiple stakeholders. Finally, this package has the functionality to read input data formatted for the Marxan conservation planning program, and find much cheaper solutions in a much shorter period of time than Marxan. Download the official version from CRAN, or the developmental version from GitHub. You can learn more about the prioritizr R package by watching my talk at User! 2018 (first video below), or how optimization techniques can be used to inform conservation decision making (second video below).

  • oppr R package
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    The oppr R package is decision support tool for prioritizing conservation projects. Prioritizations can be developed by maximizing expected feature richness, expected phylogenetic diversity, the number of features that meet persistence targets, or identifying a set of projects that meet persistence targets for minimal cost. Constraints (e.g. lock in specific actions) and feature weights can also be specified to further customize prioritizations. After defining a project prioritization problem, solutions can be obtained using exact algorithms, heuristic algorithms, or random processes. In particular, it is recommended to install the Gurobi optimizer because it can identify optimal solutions very quickly. Finally, methods are provided for comparing different prioritizations and evaluating their benefits. You can learn more about it by reading our paper published in Methods in Ecology and Evolution. Download the official version from CRAN, or the developmental version from GitHub.

  • wdpar R package
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    The wdpar R package provides an interface to the World Database on Protected Areas (WDPA) and functions for cleaning the data following best practices. Download the official version from CRAN, or the developmental version from GitHub.

  • surveyvoi R package
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    The surveyvoi R package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management – wherein some sites have previously been surveyed and other sites have not – this package provides functionality to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and by maximizing value of information. After generating plans for surveys, they can also be evaluated using value of information analysis. Download the official version from CRAN, or the developmental version from GitHub.

  • raptr R package
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    The raptr R package can be used to generate plans for protected areas (prioritizations) using spatially explicit targets for biodiversity patterns and processes. To obtain solutions in a feasible amount of time, this package uses the commercial ‘Gurobi’ software package. Download the official version from CRAN, or the developmental version from GitHub.

  • Experiences

         
  • Postdoctoral researcher at Department of Biology, Carleton University, Ottawa, Canada
    Ottawa, Canada

    I am currently working to optimise the allocation of resources for establishing new conservation areas and survey programmes from a shared budget. Conservation practitioners are often faced with the difficult decision of acting with limited data, or collecting more data to create more effective conservation plans. Acting with limited data means that more resources are available for directly conserving biodiversity – since no resources are spent collecting more data – but could also mean that these resources are poorly allocated. On the other hand, collecting more data could result in more effective conservation plans but also means that fewer resources are available for actually conserving biodiversity. I hope to provide guidelines that conservation practitioners can use when deciding which places to survey so they can use remaining funds to establish protected areas in the places that will maximize biodiversity persistence.

         
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  • Postdoctoral researcher at CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto, Vairão, Portugal
    Vairão, Portugal

    I worked on the Next Generation Conservation project in the BIODESERTS group at CIBIO/InBIO. I assessed how well existing protected areas in Portugal and Spain are representing the evolutionary processes for three endemic amphibian species (Hyla molleri, Pelobates cultripes, and Rana iberica) and identified priorities for addressing shortfalls. I also evaluated potential surrogates for representing genetic diversity in plans for protected area systems when genetic data are not available.

         
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  • Casual Professional Staff at The University of Queensland
    Brisbane, Australia

    I developed software for the Field Ecology course (BIOL2015). During the course students would visit Fraser Island and collect data using applications on smart phones. I wrote a data formatting tool to streamline the process of harvesting and validating data collected using the smart phones. This program also prepared the data for statistical analysis. Additionally, I wrote a data visualization tool to help students explore trends in the data that they collected. I have contributed to the further development of these tools on-and-off over the last few years.

         
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  • Research Assistant in the Fuller Lab at The University of Queensland
    Brisbane, Australia

    I was primarily responsible for producing tidal flat maps for the East-Australasian Flyway. To achieve this, I compiled databases of LANDSAT satellite images and processed spatial data. Additionally, I helped compile a global database of protected areas using data from the World Database on Protected Areas and additional sources. This work contributed to the publication by Dhanjal-Adams et al. 2016.

         
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  • Research Assistant in the Rhodes Lab at The University of Queensland
    Brisbane, Australia

    My primary role was data preparation and analysis. I assisted with preparing genetic and spatial data for landscape genetics analysis. I generated connectivity models for Sugar Gliders, Squirrel Gliders, and the Yellow Footed Antechinus using landscape and genetic data. Additionally, I developed a decision support tool to help understand the impacts of development on the connectivity of these species in South East Queensland, Australia. This work contributed to the publication by Dudaneic et al. 2016.

         
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  • Workshops

    I have tutored in the following workshops.

    • 2019
      • Spatial Conservation Prioritization: Concepts, Methods and Applications” coordinated by Silvia Carvalho, Virgilio Hermoso, and Jeffrey Hanson at CIBIO/InBIO, Universidade do Porto, Vairão, Portugal.
    • 2017
      • Use of Machine Learning in Conservation, Moving beyond just Maxent and SDMs” coordinated by Falk Huettmann at the 28th International Congress of Conservation Biology, Cartagena, Colombia.
    • 2015
      • “Geospatial Analysis in R” coordinated by Hawthorne Beyer, Rebbecca Runting and Jutta Beher at the Student Conference of Conservation Science, Australia.
      • “Smoothing the Marxan Flow with R” coordinated by Matthew Watts at the Student Conference of Conservation Science, Australia.
    • 2013
      • “Introduction to Geospatial Analysis” coordinated by Hawthorne Beyer at The University of Queensland, Australia.
      • “Introduction to Spatial Data Analysis in R” workshop coordinated by Hawthorne Beyer at The University of Queensland, Australia.
    • 2011
      • “Introducing R” coordinated by Simon Blomberg at The University of Queensland, Australia.
         
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    Education

       
  • PhD
    Brisbane, Australia

    I completed my PhD at the School of Biological Sciences, The University of Queensland. During this time, I developed new methods for explicitly incorporating evolutionary processes into conservation planning, examined potential surrogates for guiding reserve selection when genetic data are not available, and examined how well the global protected area system may be representing the habitats that promote adaptation in nearly 20 thousand vertebrate species. My supervisors were Richard Fuller and Jonathan Rhodes.

  • Bachelor of Science (1st Class Hons) at The University of Queensland
    Brisbane, Australia

    My honors thesis was titled “Using stable isotopes to assess the relationship between body-size, habitat use and diet in estuarine crocodiles (Crocodylus porosus)”. This work contributed to the publication by Hanson et al. (2015).

  • Bachelor of Science at The University of Queensland
    Brisbane, Australia

    I completed my Bachelor of Science at The University of Queensland with a major in Ecology.

  • Information

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