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MARXAN is a family of software designed to aid systematic reserve design on conservation planning. With the use of stochastic optimisation routines (Simulated Annealing) Marxan generates spatial reserve systems that achieve particular biodiversity representation goals with reasonable optimality. Over the years, Marxan has grown from its standard two zone application to consider more complex challenges like incorporating connectivity, probabilities and multiple zones. Along the way, Marxan’s user community has also built plug-ins and interfaces to assist with planning projects.

Computationally, Marxan provides solutions to a conservation version of the 0-1 knapsack problem, where the objects of interest are potential reserve sites with given biological attributes. The simulated annealing algorithm attempts to minimise the total cost of the reserve system, while achieving a set of conservation goals (typically that a certain percentage of each geographical/biological feature is represented by the reserve system).

History

Marxan is a portmanteau acronym, fusing MARine, and SPEXAN, itself an acronym for SPatially EXplicit ANnealing. It was a product of Ian R. Ball's PhD thesis, while he was a student at the University of Adelaide in 2000, and was supervised and funded by Professor Hugh Possingham, the state of Queensland's (Australia) current Chief Scientist who holds a Federation Fellowship at the University of Queensland. It was an extension of the existing SPEXAN program.

In 2018, the vision of “Democratizing Marxan” began. Through the Biodiversity and Protected Areas Management programme (BIOPAMA), funded by the European Union, the Joint Research Centre worked closely with The Nature Conservancy to prototype a web-based Marxan platform that improves accessibility to non-experts and supports our common vision of providing accessible tools for evidence-based conservation planning. This led to a partnership with Microsoft in 2020, which aims to scale Marxan’s infrastructure for global accessibility and empowering users with the tools and data they need to make smarter decisions for the planet. In late 2020 and early 2021 Microsoft's Azure Quantum team made several open source contributions to Marxan resulting in increased performance when running on multi-core machines and cloud environments. The resulting version 4 of Marxan is now available from marxansolutions.org.

Applications

Example Marxan outputs - selection frequency (the summed solution of each planning unit across all runs in a Marxan analysis). Figure 7 from McGowan et al. 2013,[1] a comparison of Marxan results prioritizing conservation of seabird habitat alone (scenario 1) and with the inclusion of human activities (scenario 2), shown by the cell selection frequency for 10, 30, and 50% conservation targets.

MARXAN is the most widely used systematic reserve planning software in the world,[2] and has been used to create the marine reserve network on the Great Barrier Reef, in Queensland, Australia, the largest marine protected area in the world.[3] It has been used for many other marine and terrestrial reserve planning applications.[4]

Beyond protected area network design, MARXAN has been applied to hundreds of conservation planning challenges, from designing optimal poaching patrols for game reserves and identifying where to conserve essential ecosystem services, to helping with transboundary ocean planning and understanding where transnational collaborations might best be prioritized to achieve conservation goals. While it would be almost impossible to list all of MARXAN's applications, here are a few examples beyond protected area network design. For software specific examples, see the Software section.

  • Restoration activities in the Atlantic Forest, Brazil,[10] in the Yucatan Peninsula in the Mexican Caribbean,[11] in the Murray–Darling Basin in South Australia,[12] and southwestern Alberta, Canada[13]
  • Provision of ecosystem services in Central Coast ecoregion of California, United States,[14] Telemark in southern Norway,[15] and Vermont, United States[16]
  • Understanding trade-offs between competing objectives in the Andes of Bolivia,[17] and Central Kalimantan, Indonesia[18]
  • Identifying management priorities in the Danube River Basin, Europe,[19] and South Africa's grassland biome[20]
  • Law enforcement activities in the Greater Virunga Landscape, in central Africa,[21] and the Patos Lagoon estuary along the Brazilian coast[22]

MARXAN has been used extensively by The Nature Conservancy, and is a major part of the systematic planning tools being used in the Global Marine Initiative. The World Wildlife Fund used MARXAN to define a Global set of Marine Protected Areas, the Roadmap to Recovery, which they used to petition the UN about the creation of open ocean marine reserve networks.

The software has also been used in terrestrial applications, such as:

Software

Marxan

Marxan is the most widely used decision-support software for conservation planning globally, and has been used to build marine and terrestrial conservation systems covering approximately 5% of the Earth’s surface. Marxan supports the design of cost-efficient networks that meet conservation targets for biodiversity.

Marxan with Zones

Marxan with Zones has the same functionality as Marxan but extends on the range of problems the software can solve and allows for the incorporation of multiple costs and zones into a systematic planning framework. Applications could be zoning for marine protected areas with various protection levels or landscapes that balance agriculture, biodiversity protection, and sustainable forestry zones. Marxan with Zones assigns each planning unit in a study region to a particular zone in order to meet a number of ecological, social and economic objectives at a minimum total cost.[25] Some example locations where it has been used to inform decisions includes Raja Ampat, Indonesia,[26] Tun Mustapha Park in Sabah, Malaysia,[27] Central Kalimantan, Indonesia,[18] and Indonesian Borneo.[28]

Marxan with Connectivity

Marxan with Connectivity is an extension of the Marxan software family that allows for more sophisticated connectivity considerations in spatial planning. For example, sites may be connected through processes such as larval dispersal, animal migrations, and genetic flows which are desirable objectives in conservation plans. Marxan with Connectivity has been applied in freshwater, marine, terrestrial and land-sea systems to conserve sites that may be spatially distanced but ecologically connected. Some examples include planning for threatened loggerhead sea turtles (Caretta caretta) in the Mediterranean,[29] and accounting for river connectivity in the Guadiana River basin in the southwestern Iberian Peninsula.[30] It has been recently operationalized through ‘Marxan Connect’ - a new open source, open access Graphical User Interface (GUI) tool designed to assist conservation planners with the appropriate use of data on ecological connectivity in protected area network planning.[31]

Marxan with Probability

Marxan with Probability (MarProb) is Marxan with an additional objective function term that incorporates the probability of a site being destroyed at some point in the future. This function helps plan for persistence in protected area networks (see Game et al. 2008[32]). Some examples where it has been used includes planning for Iberian herptile conservation while accounting for uncertainty in their predicted distributions due to climate change,[33] and accounting for the inherent uncertainty associated with coral reef habitat maps in conservation planning, in the Kubulau District fisheries management area, Fiji.[34]

Companion Tools

Zonae Cogito

Zonae Cogito is a freely available software package that help manage and visualise Marxan projects.[35] The interface streamlines and simplifies the development and evaluation of alternative planning scenarios, allows direct editing to input files, calibrates parameters, and helps users easily access important output files for evaluation.

CLUZ

CLUZ (Conservation Land-Use Zoning software) is a QGIS plug-in that allows users to design protected area networks and other conservation landscapes and seascapes.[36] It can be used for on-screen planning and also acts as a link for the Marxan conservation planning software. It was developed by Bob Smith and funded by the UK Government’s Darwin Initiative.[37]

Marxan toolboxes

Helpful tools developed by Trevor Wiens from Apropos Information Systems are available for both ArcGIS and QGIS users.[38]

Prioritizr

Systematic Conservation Prioritization in R – The prioritizr R package[39] 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.

References

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  2. ^ Ball, I. R., Possingham, H. P., & Watts, M. E. (2009). Marxan and relatives: Software for spatial conservation prioritization. In A. Moilanen, K. A. Wilson, & H. P. Possingham (Eds.), Spatial conservation prioritisation: Quantitative methods and computational tools (pp. 185–210). Oxford University Press.
  3. ^ "Fish Boats Barred From One-Third of Great Barrier Reef". International Daily Newswire. Environment News Service. 2004. Retrieved 28 May 2006.
  4. ^ "Ecology Centre MARXAN Homepage".
  5. ^ Airame S. 2005. Channel Islands National Marine Sanctuary: advancing the science and policy of marine protected areas. In: A Scholz and D Wright (Eds). Place matters: geospatial tools for marine science, conservation, and management in the Pacific Northwest. Corvallis, OR: Oregon State University Press.
  6. ^ Chatwin A, Huggins A, Kramer P, Wear S, Zenny N, Jeo R (2005). "The greater Caribbean marine ecoregional assessment. Chapter IV. 1. Part IV: conservation initiatives in the Caribbean. Caribbean marine biodiversity: the known and the unknown.". In Miloslavich P, Klein E (eds.). Census of Marine Life Caribbean. Lancaster: DEStech Publications Inc. pp. 293–8. Archived from the original on 2006-05-23.
  7. ^ "Selection Frequencies of Cells in the Australian South-East Marine Region". Neptune - the National Oceans Office Data Directory. Archived from the original on 22 December 2004.
  8. ^ "Using Computer Software To Design Marine Reserve Networks: Planners Discuss Their Use Of Marxan". MPA News. Archived from the original on 3 March 2016.
  9. ^ Helsinki Commission. (2010). "Towards an ecologically coherent network of well-managed Marine Protected Areas–Implementation report on the status and ecological coherence of the HELCOM BSPA network" (PDF). Baltic Sea Environment Proceedings B. 124A: 147. Archived from the original (PDF) on 2011-07-17.
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  19. ^ Domisch S, Kakouei K, Martínez-López J, Bagstad KJ, Magrach A, Balbi S, et al. (March 2019). "Social equity shapes zone-selection: Balancing aquatic biodiversity conservation and ecosystem services delivery in the transboundary Danube River Basin". The Science of the Total Environment. 656: 797–807. Bibcode:2019ScTEn.656..797D. doi:10.1016/j.scitotenv.2018.11.348. PMID 30530149.
  20. ^ Egoh BN, Reyers B, Rouget M, Richardson DM (June 2011). "Identifying priority areas for ecosystem service management in South African grasslands". Journal of Environmental Management. 92 (6): 1642–50. doi:10.1016/j.jenvman.2011.01.019. hdl:2263/15971. PMID 21334134.
  21. ^ Plumptre AJ, Fuller RA, Rwetsiba A, Wanyama F, Kujirakwinja D, Driciru M, et al. (2014). "Efficiently targeting resources to deter illegal activities in protected areas". Journal of Applied Ecology. 51 (3): 714–725. doi:10.1111/1365-2664.12227. ISSN 1365-2664.
  22. ^ Duarte de Paula Costa M, Mills M, Richardson AJ, Fuller RA, Muelbert JH, Possingham HP (September 2018). "Efficiently enforcing artisanal fisheries to protect estuarine biodiversity" (PDF). Ecological Applications. 28 (6): 1450–1458. doi:10.1002/eap.1744. PMID 29944185.
  23. ^ Ceballos G, Ehrlich PR, Soberón J, Salazar I, Fay JP (July 2005). "Global mammal conservation: what must we manage?". Science. 309 (5734): 603–7. Bibcode:2005Sci...309..603C. doi:10.1126/science.1114015. PMID 16040704. S2CID 44377512.
  24. ^ "Great Sand Hills Environmental Study". The Government of Saskatchewan. Archived from the original on 2008-07-29.
  25. ^ Watts ME, Ball IR, Stewart RS, Klein CJ, Wilson K, Steinback C, et al. (2009-12-01). "Marxan with Zones: Software for optimal conservation based land- and sea-use zoning". Environmental Modelling & Software. 24 (12): 1513–1521. doi:10.1016/j.envsoft.2009.06.005. ISSN 1364-8152.
  26. ^ Grantham HS, Agostini VN, Wilson J, Magubhai S, Hidayat N, Muljadi A, et al. (2013-03-01). "A comparison of zoning analyses to inform the planning of a marine protected area network in Raja Ampat, Indonesia". Marine Policy. 38: 184–194. doi:10.1016/j.marpol.2012.05.035. ISSN 0308-597X.
  27. ^ Jumin R, Binson A, McGowan J, Magupin S, Beger M, Brown CJ, Possingham HP, Klein C (October 2018). "From Marxan to management: ocean zoning with stakeholders for Tun Mustapha Park in Sabah, Malaysia". Oryx. 52 (4): 775–786. doi:10.1017/S0030605316001514. ISSN 0030-6053.
  28. ^ Venter O, Possingham HP, Hovani L, Dewi S, Griscom B, Paoli G, Wells P, Wilson KA (2013). "Using systematic conservation planning to minimize REDD+ conflict with agriculture and logging in the tropics". Conservation Letters. 6 (2): 116–124. doi:10.1111/j.1755-263X.2012.00287.x.
  29. ^ Mazor T, Beger M, McGowan J, Possingham HP, Kark S (2016). "The value of migration information for conservation prioritization of sea turtles in the Mediterranean" (PDF). Global Ecology and Biogeography. 25 (5): 540–552. doi:10.1111/geb.12434. ISSN 1466-8238.
  30. ^ Hermoso V, Linke S, Prenda J, Possingham HP (2011). "Addressing longitudinal connectivity in the systematic conservation planning of fresh waters". Freshwater Biology. 56 (1): 57–70. doi:10.1111/j.1365-2427.2009.02390.x. hdl:10272/4384. ISSN 1365-2427.
  31. ^ Daigle RM, Metaxas A, Balbar AC, McGowan J, Treml EA, Kuempel CD, Possingham HP, Beger M (2020). "Operationalizing ecological connectivity in spatial conservation planning with Marxan Connect". Methods in Ecology and Evolution. 11 (4): 570–579. doi:10.1111/2041-210X.13349. ISSN 2041-210X.
  32. ^ Game ET, Watts ME, Wooldridge S, Possingham HP (April 2008). "Planning for persistence in marine reserves: a question of catastrophic importance" (PDF). Ecological Applications. 18 (3): 670–80. doi:10.1890/07-1027.1. PMID 18488626.
  33. ^ Carvalho SB, Brito JC, Crespo EG, Watts ME, Possingham HP (2011-07-01). "Conservation planning under climate change: Toward accounting for uncertainty in predicted species distributions to increase confidence in conservation investments in space and time". Biological Conservation. 144 (7): 2020–2030. doi:10.1016/j.biocon.2011.04.024. ISSN 0006-3207.
  34. ^ Tulloch VJ, Possingham HP, Jupiter SD, Roelfsema C, Tulloch AI, Klein CJ (2013-06-01). "Incorporating uncertainty associated with habitat data in marine reserve design" (PDF). Biological Conservation. 162: 41–51. doi:10.1016/j.biocon.2013.03.003. ISSN 0006-3207.
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  36. ^ Smith R (2019-01-31). "The CLUZ plugin for QGIS: designing conservation area systems and other ecological networks". Research Ideas and Outcomes. 5: e33510. doi:10.3897/rio.5.e33510. ISSN 2367-7163.
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  38. ^ "Open Source Desktop GIS". qgis.org.
  39. ^ "prioritizr R package". GitHub. 11 May 2021.
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