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Draft:Systematic Conservation Planning

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Introduction

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Systematic conservation planning (SCP) is a structured approach for identifying and implementing priority areas for biodiversity conservation and restoration, while minimising trade-offs with other land and sea uses and sectors.[1][2] It is a form of spatial planning which seeks to ensure the cost-effective placement and application of conservation actions.[3] Over the last 30 years, SCP has become one of the most widely-used frameworks to inform conservation efforts globally, including the Great Barrier Reef Marine Park Zoning Plan, the establishment of new Marine Protected Areas (MPAs) in the Gulf of California, and recently by the United Nations Development Programme to map Essential Life Support Areas (ELSA).[4]

The origins of SCP can be traced back to Jamie Kirkpatrick's work using reserve selection algorithms in Tasmania in the 1980s.[5] Initially developed to establish protected areas in a systematic and evidence-based manner, the application of SCP has since broadened to prioritise conservation efforts in a variety of social and ecological contexts. Its applications now extend to informing land uses across multifunctional landscapes and seascapes outside of protected areas,[6] identifying climate refugia,[7][8] and considering multiple actions across different zones simultaneously.[9] Beyond its role in conservation spatial planning, SCP has also been used to support advocacy and influence decision and policymaking at local, national and global levels.[10]

The systematic conservation planning process

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SCP represents a stepwise, stakeholder-led approach to decision-making. It involves setting explicit goals and is underpinned by several core biological principles: complementarity, adequacy, comprehensiveness, irreplaceability, representativeness, threat and vulnerability[10]. By adhering to these principles, alongside ensuring stakeholder involvement at each stage, SCP aims to conserve biodiversity while balancing the needs of people and competing land and sea uses.

SCP was originally conceived as comprising of six steps[1], but has since expanded to 11 steps in response to the growing complexity of the social, ecological, and environmental contexts in which conservation plans are made[8]. These 11 steps can be divided into three main stages: framing, prioritisation, and implementation, with feedback and potential adaptive revision at any stage:

Table 1. 11 step framework of systematic conservation planning.
Stage Description
Framing 1. Scope and cost the planning process
2. Identify and involve stakeholders
3. Describe context for conservation areas
4. Identify conservation goals
Prioritisation 5. Collect data on conservation features
6. Collect data on socio-economic variables and threats
7. Set conservation objectives
8. Review current achievement of objectives
9. Select additional conservation areas
Implementation 10. Review current achievement of objectives
11.Select additional conservation areas

Framing

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The framing stage involves developing a shared vision for the planning process based on the conservation context[2]. This starts by scoping and costing the planning process, before identifying who to involve and how. At this stage it is important to gain an understanding of the social, economic and cultural context of the planning region. This shapes the constraints and opportunities for conservation that are available to the planning team. The final step of framing involves identifying conservation goals. This serves as an opportunity for stakeholders to build consensus and align conservation actions with the goals of implementing organisations and local peoples' values, wants and needs.

Prioritisation

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The prioritisation process varies based on the algorithm used, but generally involves: (i) dividing the region into planning units (or sites), (ii) defining and collecting spatially explicit data on conservation features (species, habitats, ecosystem types, etc) based on the conservation goals; (iii) determining the cost of including each planning unit (proxies are often used); (iv) calculating the amount of each feature in each of the planning units, and (v) using spatial prioritisation software to identify the best sets of planning units to meet conservation objectives, whilst minimising costs and maintaining connectivity.

The prioritisation stage generally relies on optimisation algorithms to identify areas where conservation objectives can be achieved at minimal cost. Commonly used tools include:

  • Marxan: A widely used software for spatial prioritisation, Marxan identifies near-optimal solutions for reserve design. It has evolved into a family of tools, including Marxan with Zones for multi-zone planning, Marxan with Probability for incorporating uncertainty, and Marxan with Connectivity for maintaining ecological linkages. The Marxan Planning Platform (MaPP) is a free, cloud-based resource for users to visualize, explore, and report on spatial data and conservation solutions. It allows users to store spatial data in cloud storage, enabling collaboration on projects.
  • Zonation: This algorithm prioritises areas by iteratively removing the least valuable planning units, retaining those that contribute most to achieving conservation objectives, such as species persistence, habitat connectivity, and ecosystem functioning. It produces a hierarchical ranking of the planning region that guides conservation planning.
  • prioritizR: An R-package, prioritizR generates optimal (rather than near-optimal) solutions for conservation planning. It allows for flexible, customisable prioritisation and integrates advanced features like multi-objective optimisation.[11]
  • C-Plan: Developed for conservation planning in Australia, C-Plan uses a decision-support framework to identify priority areas based on irreplaceability and vulnerability, ensuring efficient allocation of conservation resources.
  • CLUZ: a user-friendly QGIS plug-in for the design of conservation area and nature recovery networks.[12] It acts as a link to Marxan and Marxan with Zones software packages and can also be used with solutions identified within PrioritizR.

Implementation

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The implementation stage involves applying the chosen conservation actions to enable conservation objectives to be met. Key to ensuring the prioritisation stage is translated to on-the-ground action is the continued involvement of stakeholders in its development, and in ensuring the outputs of the prioritisation are delivered to end users in a user-friendly format .[13][14][15] Maintaining and monitoring these actions is vital to ensure long-term success of conservation plans. Results of monitoring should be used to inform adaptive management if required.

History

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In the 1980s and early 1990s, iterative algorithms were introduced to conservation biology to help prioritise areas for protection as nature reserves. A key development was Kirkpatrick's 1980 algorithm used in Tasmania, which applied an iterative method to select reserves that represented the regions plant diversity..[16] Unlike previous methods, this considered species rarity and complementarity, enabling more efficient prioritisation, especially for under-represented features. Similar algorithms were independently developed in Australia, South Africa, and the UK. These advancements ultimately led to the establishment of "systematic conservation planning," an approach introduced by Margules and Pressey in 2000[1]

In 2000, Margules and Pressey explicitly defined SCP by introducing quantitative methods, such as optimisation algorithms, to identify conservation priorities. They emphasised an integrated, methodical approach that accounts for ecological, social, and economic factors in conservation decision-making. Their work outlined six key steps for applying SCP, which recognised the complexities of the social, ecological and economic context within which conservation plans are made[8]. This approach helped establish SCP as a scientifically grounded, adaptable process for conservation planning at both local and landscape scales.

SCP has become widely applied in the conservation community. Since its formal conception in 2000, its application rapidly expanded as more countries and organisations recognised the need for a systematic, evidence-based approach to identifying priority areas for conservation[3].[17] Alongside the design of protected area networks, the SCP framework has been used to prioritise areas for nature recovery, maintain ecosystem services, and guide sustainable natural resource extraction. Moving forward, SCP will play a central role in informing conservation efforts outside of protected areas, helping to minimise impacts on other uses across multifunctional landscapes and seascapes.

Systematic conservation planning and global goals

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Global Biodiversity Framework

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The Kunming-Montreal Global Biodiversity Framework provides a global roadmap for biodiversity and ecosystems. Setting an ambitious vision for a world living in harmony with nature by 2025, 196 countries have committed to the delivery of its targets as Parties to the Convention on Biological Diversity (CBD). SCP has been noted as a key approach to achieving these targets[3]. In particular Target 2, to restore 30% of degraded ecosystems, and Target 3 to protect 30% of the planet in ecologically representative, well-connected and equitably governed networks of area-based conservation measures ("30 by 30"). SCP is also relevant to the delivery of Target 1, where spatial planning features prominently in the requirement to 'ensure that all areas are under participatory, integrated, and biodiversity inclusive spatial planning and/or effective management processes'. Achieving these targets will require biodiversity conservation to be balanced with other uses within multifunctional landscapes and seascapes. SCP has been used to help inform plans to meet the 30% target in countries that include England,[18] Gabon,[19] and Indonesia.[20]

Sustainable Development Goals

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The UNDP's "Mapping Nature for People and Planet" project used SCP to map Essential Life Support Areas (ELSAs), guiding countries in achieving multiple Sustainable Development Goals (SDGs). By applying integrated spatial planning, countries identify key areas for ecosystem protection, management, and restoration to meet policy targets related to biodiversity, climate, and human well-being. The process involves stakeholders in three phases: defining national goals, co-creating the ELSA map, and integrating results into policy.

IUCN WCPA Spatial Planning Task Force

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The IUCN WCPA Spatial Planning Task Force focuses on developing and promoting best practices in spatial planning for area-based conservation. The task force currently provides guidance on how to achieve the Kunming-Montreal Global Biodiversity Framework Targets while implementing participatory and biodiversity-inclusive spatial planning.

Notable examples

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SCP has played a key role globally in designing protected area networks and other conservation actions across both land and sea. Australia, the United States of America, and South Africa are key hubs for the approach.[21]

Great Barrier Reef Marine Park Zoning Plan

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The Great Barrier Reef Marine Park Zoning Plan is a landmark example of SCP applied to marine ecosystems. Implemented in 2004, the plan aimed to balance biodiversity protection with sustainable fisheries and tourism. It divided the reef into multiple zones, each with varying levels of human activity permitted, ranging from strict no-take areas to zones allowing recreational and commercial use.[22]

The planning process involved extensive stakeholder engagement, including scientists, policymakers, industry representatives, and the public. The result was a scientifically robust and socially inclusive plan that significantly improved the ecological health of the reef while supporting local livelihoods.[23]

This initiative is widely regarded as a global model for marine spatial planning and demonstrates how SCP can achieve both conservation and socioeconomic goals.

Channel Islands, California

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The Gulf of California has been the focus of several marine conservation planning exercises over the past 15 years, utilising SCP to address the region's biodiversity threats.[24] These exercises aimed to prioritise areas for conservation while balancing ecological protection with human activities such as fishing and tourism. The plans varied in scope, from national to sub-regional levels, and employed different methods, including expert-based assessments and conservation planning software.

Stakeholder participation played a crucial role, with input from scientists, conservation organisations, industry representatives, and local communities. Despite challenges, such as slow implementation due to conflicting interests and limited resources, these planning exercises contributed to improved coordination and better data for conservation efforts and influenced the establishment of new Marine Protected Areas (MPAs). However, uptake of recommendations has been gradual, demonstrating the need for political commitment to enable long-term success.

Systematic conservation planning in South Africa

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South Africa is recognised as a global leader in using SCP to guide conservation actions across spatial planning processes.[25] The country's use of SCP began in the 1990s with reserve-site selection algorithms and has evolved to inform large, donor-funded programs like the CAPE program, directing where investments are made.[26] In 2004, the South African National Biodiversity Institute (SANBI) was established and launched the Biodiversity Planning Forum. This forum serves to bring together those who create and use conservation plans, fostering a collaborative community of practice within the country.[27]

The community of practice has been instrumental in expanding the use of SCP, allowing planners to continually refine and improve conservation plans. It has also played a key role in engaging a broader range of stakeholders, ensuring that conservation planning reflects not only scientific values but also the values of local communities and other interested parties.[27]

References

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  1. ^ a b c Margules, C. R.; Pressey, R. L. (May 2000). "Systematic conservation planning". Nature. 405 (6783): 243–253. doi:10.1038/35012251. ISSN 0028-0836. PMID 10821285.
  2. ^ a b Rittenhouse, Chadwick (2017-10-30). "Conservation planning: informed decisions for a healthier planet". Landscape Ecology. 32 (11): 2219–2221. doi:10.1007/s10980-017-0577-9. ISSN 0921-2973.
  3. ^ a b c Giakoumi, Sylvaine; Richardson, Anthony J.; Doxa, Aggeliki; Moro, Stefano; Andrello, Marco; Hanson, Jeffrey O.; Hermoso, Virgilio; Mazor, Tessa; McGowan, Jennifer; Kujala, Heini; Law, Elizabeth; Álvarez-Romero, Jorge G.; Magris, Rafael A.; Gissi, Elena; Arafeh-Dalmau, Nur (April 2025). "Advances in systematic conservation planning to meet global biodiversity goals". Trends in Ecology & Evolution. 40 (4): 395–410. Bibcode:2025TEcoE..40..395G. doi:10.1016/j.tree.2024.12.002. PMID 39880725.
  4. ^ Mapping Essential Life Support Areas to Achieve the Sustainable Development Goals (Report). UNDP's Development Futures Series Briefs and Working Papers. United Nations Publications. 2024-04-21. doi:10.18356/30053307-75.
  5. ^ Pressey, R. L. (September 2002). "Classics in physical geography revisited". Progress in Physical Geography: Earth and Environment. 26 (3): 434–441. Bibcode:2002PrPG...26..434P. doi:10.1191/0309133302pp347xx. ISSN 0309-1333.
  6. ^ von Staden, Lize; Lötter, Mervyn C.; Holness, Stephen; Lombard, Amanda T. (April 2022). "An evaluation of the effectiveness of Critical Biodiversity Areas, identified through a systematic conservation planning process, to reduce biodiversity loss outside protected areas in South Africa". Land Use Policy. 115: 106044. Bibcode:2022LUPol.11506044V. doi:10.1016/j.landusepol.2022.106044. ISSN 0264-8377.
  7. ^ Reside, April E.; Butt, Nathalie; Adams, Vanessa M. (2017-09-27). "Adapting systematic conservation planning for climate change". Biodiversity and Conservation. 27 (1): 1–29. doi:10.1007/s10531-017-1442-5. ISSN 0960-3115.
  8. ^ a b c Frazão Santos, Catarina; Agardy, Tundi; Andrade, Francisco; Calado, Helena; Crowder, Larry B.; Ehler, Charles N.; García-Morales, Sara; Gissi, Elena; Halpern, Benjamin S.; Orbach, Michael K.; Pörtner, Hans-Otto; Rosa, Rui (2020-05-04). "Integrating climate change in ocean planning". Nature Sustainability. 3 (7): 505–516. Bibcode:2020NatSu...3..505F. doi:10.1038/s41893-020-0513-x. ISSN 2398-9629.
  9. ^ Watts, Matthew E.; Ball, Ian R.; Stewart, Romola S.; Klein, Carissa J.; Wilson, Kerrie; Steinback, Charles; Lourival, Reinaldo; Kircher, Lindsay; Possingham, Hugh P. (December 2009). "Marxan with Zones: Software for optimal conservation based land- and sea-use zoning". Environmental Modelling & Software. 24 (12): 1513–1521. Bibcode:2009EnvMS..24.1513W. doi:10.1016/j.envsoft.2009.06.005. ISSN 1364-8152.
  10. ^ a b Sinclair, Samuel P.; Milner-Gulland, E.J.; Smith, Robert J.; McIntosh, Emma J.; Possingham, Hugh P.; Vercammen, Ans; Knight, Andrew T. (2018-05-03). "The use, and usefulness, of spatial conservation prioritizations". Conservation Letters. 11 (6). Bibcode:2018ConL...11E2459S. doi:10.1111/conl.12459. ISSN 1755-263X.
  11. ^ Hanson, Jeffrey O.; Schuster, Richard; Strimas-Mackey, Matthew; Morrell, Nina; Edwards, Brandon P. M.; Arcese, Peter; Bennett, Joseph R.; Possingham, Hugh P. (2024-09-13). "Systematic conservation prioritization with the prioritizr R package". Conservation Biology. 39 (1). doi:10.1111/cobi.14376. ISSN 0888-8892. PMC 11780203. PMID 39268847.
  12. ^ Smith, Robert (2019-01-31). "The CLUZ plugin for QGIS: designing conservation area systems and other ecological networks". Research Ideas and Outcomes. 5. doi:10.3897/rio.5.e33510. ISSN 2367-7163.
  13. ^ Jumin, Robecca; Binson, Augustine; McGowan, Jennifer; Magupin, Sikula; Beger, Maria; Brown, Christopher J.; Possingham, Hugh P.; Klein, Carissa (2017-05-08). "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.
  14. ^ Game, Edward T.; Lipsett-Moore, Geoffrey; Hamilton, Richard; Peterson, Nate; Kereseka, Jimmy; Atu, William; Watts, Matthew; Possingham, Hugh (2010-09-14). "Informed opportunism for conservation planning in the Solomon Islands". Conservation Letters. 4 (1): 38–46. doi:10.1111/j.1755-263x.2010.00140.x. ISSN 1755-263X.
  15. ^ KNIGHT, ANDREW T.; COWLING, RICHARD M. (2007-05-10). "Embracing Opportunism in the Selection of Priority Conservation Areas". Conservation Biology. 21 (4): 1124–1126. Bibcode:2007ConBi..21.1124K. doi:10.1111/j.1523-1739.2007.00690.x. ISSN 0888-8892. PMID 17650262.
  16. ^ Kirkpatrick, J.B. (February 1983). "An iterative method for establishing priorities for the selection of nature reserves: An example from Tasmania". Biological Conservation. 25 (2): 127–134. Bibcode:1983BCons..25..127K. doi:10.1016/0006-3207(83)90056-3. ISSN 0006-3207.
  17. ^ Kukkala, Aija S.; Moilanen, Atte (2012-12-22). "Core concepts of spatial prioritisation in systematic conservation planning". Biological Reviews. 88 (2): 443–464. doi:10.1111/brv.12008. ISSN 1464-7931. PMC 3654170. PMID 23279291.
  18. ^ Smith, Robert; Cartwright, Samantha; Fairbairn, Andrew; Lewis, Deborah; Gibbon, Gwili; Stewart, Claire; Sykes, Rachel; Addison, Prue (2021-06-15). "Developing a Nature Recovery Network using systematic conservation planning". doi.org. doi:10.32942/osf.io/wqstj. Retrieved 2025-06-05.
  19. ^ Metcalfe, Kristian; White, Lee; Lee, Michelle E.; Fay, J. Michael; Abitsi, Gaspard; Parnell, Richard J.; Smith, Robert J.; Agamboue, Pierre Didier; Bayet, Jean Pierre; Mve Beh, Jean Hervé; Bongo, Serge; Boussamba, Francois; De Bruyne, Godefroy; Cardiec, Floriane; Chartrain, Emmanuel (February 2022). "Fulfilling global marine commitments; lessons learned from Gabon". Conservation Letters. 15 (3). Bibcode:2022ConL...15E2872M. doi:10.1111/conl.12872. ISSN 1755-263X.
  20. ^ Pusparini, Wulan; Cahyana, Andi; Grantham, Hedley S.; Maxwell, Sean; Soto-Navarro, Carolina; Macdonald, David W. (2023-01-16). "A bolder conservation future for Indonesia by prioritising biodiversity, carbon and unique ecosystems in Sulawesi". Scientific Reports. 13 (1): 842. Bibcode:2023NatSR..13..842P. doi:10.1038/s41598-022-21536-2. ISSN 2045-2322. PMC 9842766. PMID 36646696.
  21. ^ Sinclair, Samuel P.; Milner-Gulland, E.J.; Smith, Robert J.; McIntosh, Emma J.; Possingham, Hugh P.; Vercammen, Ans; Knight, Andrew T. (2018-05-03). "The use, and usefulness, of spatial conservation prioritizations". Conservation Letters. 11 (6). Bibcode:2018ConL...11E2459S. doi:10.1111/conl.12459. ISSN 1755-263X.
  22. ^ Kenchington, R. A.; Day, J. C. (2011-02-16). "Zoning, a fundamental cornerstone of effective Marine Spatial Planning: lessons learnt from the Great Barrier Reef, Australia". Journal of Coastal Conservation. 15 (2): 271–278. Bibcode:2011JCC....15..271K. doi:10.1007/s11852-011-0147-2. ISSN 1400-0350.
  23. ^ McIntosh, Emma J. (September 2019). "Barriers to the evaluation of systematic conservation plans: Insights from landmark Australian plans". Biological Conservation. 237: 70–80. Bibcode:2019BCons.237...70M. doi:10.1016/j.biocon.2019.06.029. ISSN 0006-3207.
  24. ^ Álvarez-Romero, Jorge G.; Pressey, Robert L.; Ban, Natalie C.; Torre-Cosío, Jorge; Aburto-Oropeza, Octavio (2013-03-11). "Marine conservation planning in practice: lessons learned from the Gulf of California". Aquatic Conservation: Marine and Freshwater Ecosystems. 23 (4): 483–505. Bibcode:2013ACMFE..23..483A. doi:10.1002/aqc.2334. ISSN 1052-7613.
  25. ^ Botts, Emily A.; Pence, Genevieve; Holness, Stephen; Sink, Kerry; Skowno, Andrew; Driver, Amanda; Harris, Linda R.; Desmet, Philip; Escott, Boyd; Lötter, Mervyn; Nel, Jeanne; Smith, Tammy; Daniels, Fahiema; Sinclair, Samuel; Stewart, Warrick (2019-06-04). "Practical actions for applied systematic conservation planning". Conservation Biology. 33 (6): 1235–1246. Bibcode:2019ConBi..33.1235B. doi:10.1111/cobi.13321. ISSN 0888-8892. PMID 30912598.
  26. ^ Cowling, R.M; Pressey, R.L; Rouget, M; Lombard, A.T (July 2003). "A conservation plan for a global biodiversity hotspot—the Cape Floristic Region, South Africa". Biological Conservation. 112 (1–2): 191–216. Bibcode:2003BCons.112..191C. doi:10.1016/s0006-3207(02)00425-1. ISSN 0006-3207.
  27. ^ a b Buschke, Falko T.; Botts, Emily A.; Sinclair, Samuel P. (2019-06-25). "Post-normal conservation science fills the space between research, policy, and implementation". Conservation Science and Practice. 1 (8). Bibcode:2019ConSP...1E..73B. doi:10.1111/csp2.73. ISSN 2578-4854.
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