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Marxan

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Developer

National Environmental Research Program Environmental Decisions Hub and the former Australian Research Council Centre of Excellence for Environmental Decisions; based at the University of Queensland

Latest documentation

2020

Designed for use in

Worldwide

Ongoing

Yes

Assessment purpose

Management effectiveness, Prioritisation, Values

Assessment criteria

Socio-cultural, Significance, Physical and chemical, Management and planning, Flora, Fauna, Economic

Method type

Desktop

Timescale

Medium-long term – The time required for Marxan to provide 100 good solutions ranges from minutes to days. It is usually the advanced features of Marxan (such as separation distance and minimum clump size) that can slow the analysis down significantly, especially with large numbers of planning units (Game and Grantham 2008).

Scale

Landscape/Catchment, Region, Site/habitat

Wetland system

Estuarine, Lacustrine, Marine, Other, Palustrine, Riverine

Description and method logic

Method purpose

Marxan is a suite of tools designed to help decision makers find good solutions to conservation planning problems. This includes free software that can be used to solve several types of planning problems and extensive documentation and examples describing a framework for approaching conservation planning (Marxan 2020).

Summary

Marxan provides decision support to a range of conservation planning problems, including:
  • the design of new reserve systems
  • reporting on the performance of existing reserve systems
  • developing multiple-use zoning plans for natural resource management (Marxan 2020).

These features provide users with decision support to achieve an efficient allocation of resources across a range of different uses, including:
  • Identify areas that efficiently meet targets for a range of biodiversity features for minimal cost
  • Use the principle of complementarity to select planning units which complement the conservation area network (the whole is more than the sum of its parts)
  • Meet spatial requirements such as compactness of a reserve system
  • Include data on ecological processes, threats, and condition
  • Identify trade-offs between conservation and socio-economic objectives
  • Generate a number of very good (near-optimal) solutions (Marxan 2020).

Marxan software has contributed to several major conservation projects including the rezoning of the Great Barrier Reef Marine Park (Bell et al 2009 and references within).

Method logic

Marxan uses the well-accepted 'minimum-set' approach to identify spatial conservation priorities,
'minimum-set' and 'maximal coverage'. The objective of the minimum-set strategy is to achieve the conservation objectives while minimizing the resources expended or negative impacts on stakeholders.

Marxan provides many near-optimal solutions to a minimum-set problem, which are designed to be used as decision support and considered within a broader decision-making process involving a range of stakeholders (Watts et al 2017 and references within).

There are four main steps to running Marxan:
  • Setting up the input files
  • Setting the scenario parameters
  • Running Marxan
  • Interpreting the results (Game and Grantham 2008).

Users should refer to the Marxan User Manual (Game and Grantham 2008) and the Marxan Good Practices Handbook (Ardron et al 2010). There are several freely-available user interfaces that can assist in running Marxan, for example C-plan, CLUZ (Conservation Land Use Zoning) and PANDA (Protected areas Network Design Application) (Game and Grantham 2008).

Criteria groupings of the method

Spatial data: planning units and conservation features. Planning unit data will always need to be defined and the selection of conservation criteria will be dependent on the type of reserve being implemented.

Data required

Four input files are required (without them Marxan will not run):
  • Input parameter (sets values for all the main parameters that control the way Marxan works)
  • Conservation feature (information about each of the conservation features being considered)
  • Planning unit (information about the planning units including cost and condition)
  • Planning unit versus conservation feature (the distribution of conservation features in each of the planning units) (Game and Granthan 2008).

Optional files include:
  • Boundary length (the length or ‘effective length’ of shared boundaries between planning units)
  • Block definition (can be used to set a series of default variable values for groups of conservation features) (Game and Grantham 2008).

Resources required

Expertise required

Marxan requires experience with conservation planning and GIS software.

Materials required

The Marxan software, Microsoft operating system, GIS software and access to spatial datasets.

Method outputs

Outputs

In addition to advising which planning units make up an efficient reserve system, Marxan can also provide other outputs, such as:
  • Run (the repeat runs the output pertains to)
  • Value (the overall objective function value for the solution from that run, which is how Marxan chooses the ‘best’ solution out of you repeat runs)
  • Cost (total cost of the reserve system)
  • Planning Units (PUs) (number of planning units contained in the solution for that run)
  • Boundary (total boundary length of the reserve system)
  • Missing (the number of conservation features that did not achieve their targets in the final solution for that run)
  • Shortfall (the amount by which the targets for conservation features have not been met in the solution for that run)
  • Penalty (the penalty that was added to the objective function because the reserve system failed to meet the representation targets for all features) (Game and Grantham 2008).

Marxan can save up to eight different output files:
  • Solutions for each run
  • Best solution from all runs
  • Missing values for each run
  • Summary information
  • Scenario details
  • Summed solution
  • Screen log file
  • Snapshot files (Game and Grantham 2008).

Uses

  • Input to other planning processes and interfaces.
  • Marine and terrestrial applications.
  • Economic-spatial planning.
  • Conservation planning.
  • Land use planning.
  • Reserve design planning.
  • Resilience and disaster planning.
  • Spatial resource planning.

Criteria by category

    Physical and chemical

    • Planning unit dimensions
    • Planning unit location

    Economic

    • Economic constraints

    Socio-cultural

    • Socio-cultural constraints

    Management and planning

    • Planning unit cost
    • Planning unit location
    • Planning unit status (condition)

    Significance

    • Significant ecosystems
    • Significant features
    • Significant species

    Flora

    • Conservation status
    • Distribution
    • Importance

    Fauna

    • Conservation value
    • Distribution
    • Importance

Review

Recommended user

Marxan is useful to spatial planners for conservation and reserve design purposes. This technique may be useful for government agencies, natural resource managers and others.

Strengths

  • Compatible with other software suites.
  • Quantitative technique.
  • Outputs verified by sensitivity analysis.
  • Data can be displayed visually for ease of interpretation.
  • Overcomes the ‘minimum set problem’ of reserve planning.
  • Facilitates transparency and repeatability in planning.

Limitations

  • Not intended to act as a stand-alone reserve design solution, depends on the stakeholder engagement, best practice ecological principles, scientifically defensible conservation goals and targets, and quality spatial datasets.
  • Requires considerable experimentation in order to produce defensible results.

Case studies

Links


References

  1. Sinclair, SP, Milner‐Gulland, EJ, Smith, RJ, McIntosh, EJ, Possingham, HP, Vercammen, A & Knight, AT (2018), 'The use, and usefulness, of spatial conservation prioritizations', Conservation Letters. [online], vol. 11, no. 6, p. e12459. Available at: https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/conl.12459.
  2. Carwardine, J, Klein, CJ, Wilson, KA, Pressey, RL & Possingham, HP (2009), 'Hitting the target and missing the point: target-based conservation planning in context', Conservation Letters. [online], vol. 2, no. 12009, pp. 4-11. Available at: https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/j.1755-263X.2008.00042.x.
  3. Watts, ME, Stewart, RR, Martin, TG, Klein, CJ, Carwardine, J & Possingham, HP (2017), 'Systematic Conservation Planning with Marxan', in Learning Landscape Ecology: A Practical Guide to Concepts and Techniques. [online], Springer-Verlag, New York, pp. 211-228. Available at: https://www.researchgate.net/publication/315854586_Systematic_Conservation_Planning_with_Marxan.
  4. Kirkpatrick, S, Gelatt, CD & Vecchi, MP (1983), 'Optimization by Simulated Annealing', Science. [online], vol. 220, no. 4598, pp. 671-680. Available at: https://www.researchgate.net/publication/6026283_Optimization_by_Simulated_Annealing.
  5. Margules, CR & Pressey, RL (2000), 'Systematic conservation planning', Nature. [online], vol. 405, pp. 243-253. Available at: https://www.nature.com/articles/35012251.
  6. Possingham, HP, Willson, KA, Andelman, SJ & Vynne, CH (2006), 'Protected Areas: Goals, Limitations, and Design', in Principles of Conservation Biology. [online], Sinauer Associates, Inc., Sunderland. Available at: https://www.researchgate.net/publication/37629187_Protected_areas_Goals_limitations_and_design.
  7. SANBI & UNEP-WCMC (2016), Mapping biodiversity priorities: A practical, science-based approach to national biodiversity assessment and prioritisation to inform strategy and action planning. [online], UNEP-WCMC, Cambridge, UK. Available at: https://marxansolutions.org/wp-content/uploads/2020/04/mapping-biodiversity-priorities-web.pdf.
  8. Game, ET & Grantham, HS (2008), Marxan User Manual: For Marxan Version 1.8.10.. [online], University of Queensland, St. Lucia, Queensland, Australia, and Pacific Marine Analysis and Research Association, Vancouver, British Columbia, Canada. Available at: https://pacmara.org/wp-content/uploads/2010/01/marxan-manual-1.8.10.pdf.
  9. Ardron, JA, Possingham, HP & Klein, CJ (2010), Marxan Good Practices Handbook, Version 2. [online], p. 165, Pacific Marine Analysis and Research Association, Victoria, BC, Canada. Available at: https://pdfs.semanticscholar.org/5dbd/d08f56f26e9d40fccf3d3333d17ab07cd128.pdf?_ga=2.105893255.568620288.1596591733-735466665.1596591733.
  10. Watts, ME, Ball, IR, Stewart, RR, Klein, CJ, Wilson, K, Steinback, C, Lourival, R, Kircher, L & Possingham, HP (2009), Marxan with Zones: software for optimal conservation based land- and sea-use zoning, Environmental Modelling & Software doi:10.1016/j.envsoft.2009.06.005. [online] Available at: https://www.sciencedirect.com/science/article/pii/S1364815209001418.
  11. Ball, I & Possingham, H (2000), Marxan (v1.8.2), Marine Reserve Design using Spatially Explicit Annealing, A Manual Prepared for The Great Barrier Reef Marine Park Authority. [online], p. 70, University of Queensland, St. Lucia, Queensland, Australia. Available at: http://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf.

Last updated: 16 September 2020

This page should be cited as:

Department of Environment and Science, Queensland (2020) Marxan, WetlandInfo website, accessed 13 May 2021. Available at: https://wetlandinfo.des.qld.gov.au/wetlands/resources/tools/assessment-search-tool/marxan/

Queensland Government
WetlandInfo   —   Department of Environment and Science