I am a conservation scientist. I’m interested in solving the challenges that prevent us from creating strategic plans to effectively conserve biodiversity. My research focuses on incorporating novel datasets into conservation planning exercises (e.g. establishing new protected areas), applying optimisation algorithms to find optimal solutions to conservation problems, and identifying cost-effective surrogate data that can inform conservation decisions when high quality expensive data are not available (e.g. genetic data). I also develop decision support tools to help others apply my findings to their own work (e.g. prioritizr, raptr, oppr R packages). In my doctoral thesis, entitled “Conserving evolutionary processes”, I operationalized ecological and evolutionary processes to develop plans for protected area systems that maximize the long-term persistence of biodiversity (watch the recording of my exit seminar below). At the University of Carleton, I am currently working to optimise the allocation of resources for establishing new protected areas and survey programmes from a shared budget. I hope to provide guidelines that conservation practitioners can use when deciding which places to survey to maximize biodiversity persistence.
Hanson JO, Veríssimo A, Velo‐Antón G, Marques A, Camacho‐Sanchez M, Martínez‐Solano Í, Gonçalves H, Sequeira F, Possingham HP & Carvalho SB (2020) Evaluating surrogates of genetic diversity for conservation planning. Conservation Biology, In press: DOI:10.1111/cobi.13602.
Hanson JO, Marques A, Veríssimo A, Camacho‐Sanchez M, Velo‐Antón G, Martínez‐Solano Í & Carvalho SB (2020) Conservation planning for adaptive and neutral evolutionary processes. Journal of Applied Ecology, In press: DOI:10.1111/1365-2664.13718.
Camacho‐Sanchez M, Velo‐Antón G, Hanson JO, Veríssimo A, Martínez‐Solano Í, Marques A, Moritz C, Carvalho SB (2020) Comparative assessment of range‐wide patterns of genetic diversity and structure with SNPs and microsatellites: A case study with Iberian amphibians. Ecology & Evolution, In press: DOI:10.1002/ece3.6670.
Ambrose L, Hanson JO, Riginos C, Xu W, Fordyce S, Cooper RD & Beebe NW (2019) Population genetics of Anopheles koliensis through Papua New Guinea: New cryptic species and landscape topography effects on genetic connectivity. Ecology & Evolution, 9: 13375–13388.
- Hanson JO, Rhodes JR, Possingham HP & Fuller RA (2018) raptr: Representative and adequate prioritization toolkit in R. Methods in Ecology & Evolution, 9: 320–330.
Hanson JO, Rhodes JR, Riginos C & Fuller RA (2017) Environmental and geographic variables are effective surrogates for genetic variation in conservation planning. Proceedings of the National Academy of Sciences of the United States of America, 114: 12755–12760.
Mather AT, Hanson JO, Pope LC & Riginos C (2017) Comparative phylogeography of two co-distributed but ecologically distinct rainbowfishes of far-northern Australia. Journal of Biogeography, 45: 127–141.
Dhanjal-Adams KL, Hanson JO, Murray NJ, Phinn SR, Wingate VR, Mustin K, Lee JR, Allan JR, Cappadonna JL, Studds CE, Clemens RS, Roelfsema CM & Fuller RA (2016) The distribution and protection of intertidal habitats in Australia. Emu, 116: 208–214
Dudaniec RY, Worthington Wilmer J, Hanson JO, Warren M, Bell S & Rhodes JR (2016) Dealing with uncertainty in landscape genetic resistance models: a case of three co-occurring marsupials. Molecular Ecology, 25: 470-486.
Hanson J. O., Salisbury SW, Campbell HA, Dwyer RG, Jardine TD & Franklin CE (2015) Feeding across the food web: The interaction between diet, movement and body size in estuarine crocodiles (Crocodylus porosus). Austral Ecology, 40: 275-286.
Bunton JD, Ernst AT, Hanson JO, Beyer HL, Hammill E, Runge CA, Venter O, Possingham HP & Rhodes JR (2015) Integrated planning of linear infrastructure and conservation offsets. In Weber, T., McPhee, M. J. & Andersson R. S. (eds) MODSIM 2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2015, pp. 1427-1433.
Rabeb D, Othman DS, Essilfie AT, Hansbro PM, Hanson JO, McEwan AG & Kappler U (2015) Maturation of molybdoenzymes and its influence on the pathogenesis of non-typeable Haemophilus influenzae. Frontiers in Microbiology, 6: 01219.
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 it by watching my talk at User! 2018 below.
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.
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.
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.
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.
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.
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.
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.
I have tutored in the following workshops.
- “Spatial Conservation Prioritization: Concepts, Methods and Applications” coordinated by Silvia Carvalho, Virgilio Hermoso, and Jeffrey Hanson at CIBIO/InBIO, Universidade do Porto, Vairão, Portugal.
- “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.
- “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.
- “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.
- “Introducing R” coordinated by Simon Blomberg at The University of Queensland, 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.
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).
I completed my Bachelor of Science at The University of Queensland with a major in Ecology.