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Conservation planning is the science of choosing which actions to take where for the purpose of conserving biodiversity. Creating a system of protected areas is the most common form of systematic conservation planning. Hence, we will focus on the process of protected area selection in this chapter. Marxan is the most widely used software in the world for creating marine and terrestrial protected area systems. Because conservation planning is an important job skill for conservation and resource managers, you should understand the principles involved even if you don’t use this software in your job and even if you use software other than Marxan for systematic conservation planning. From this chapter, we would like you to.

Creating large conservation zones in remote areas, with less intense stakeholder overlap and limited environmental information, requires periodic review to ensure zonation mitigates primary threats and fill gaps in representation, while achieving conservation targets. Follow-up reviews can utilise improved methods and data, potentially identifying new planning options yielding a desirable balance between stakeholder interests. This research explored a marine zoning system in north-west Australia–a biodiverse area with poorly documented biota. Although remote, it is economically significant (i.e. petroleum extraction and fishing). Stakeholder engagement was used to source the best available biodiversity and socio-economic data and advanced spatial analyses produced 765 high resolution data layers, including 674 species distributions representing 119 families. Gap analysis revealed the current proposed zoning system as inadequate, with 98.2% of species below the Convention on Biological Diversity 10% representation targets. A systematic conservation planning algorithm Maxan provided zoning options to meet representation targets while balancing this with industry interests. Resulting scenarios revealed that conservation targets could be met with minimal impacts on petroleum and fishing industries, with estimated losses of 4.9% and 7.2% respectively. The approach addressed important knowledge gaps and provided a powerful and transparent method to reconcile industry interests with marine conservation.

This software note describes an extension to the conservation planning package Marxan in which multiple solutions can be evaluated instead of only relying on the measures of best solution and irreplaceability. For this extension we coupled Marxan with the statistical software R. The pool of possible conservation plans is transferred from Marxan into R - which returns an ordination plot, as well as a cluster dendrogram that can be used to evaluate similarity of solutions. Also, the most efficient solutions per group are flagged. We believe that identification of alternative planning options facilitates review and implementation of Marxan solutions as negotiating parties have multiple alternative starting points.

With marine biodiversity conservation the primary goal for reserve planning initiatives, a site's conservation potential is typically evaluated on the basis of the biological and physical features it contains. By comparison, socio-economic information is seldom a formal consideration of the reserve system design problem and generally limited to an assessment of threats, vulnerability or compatibility with surrounding uses. This is perhaps surprising given broad recognition that the success of reserve establishment is highly dependent on widespread stakeholder and community support. Using information on the spatial distribution and intensity of commercial rock lobster catch in South Australia, we demonstrate the capacity of mathematical reserve selection procedures to integrate socio-economic and biophysical information for marine reserve system design. Analyses of trade-offs highlight the opportunities to design representative, efficient and practical marine reserve systems that minimise potential loss to commercial users. We found that the objective of minimising the areal extent of the reserve system was barely compromised by incorporating economic design constraints. With a small increase in area (

Like many states and territories, South Australia has a legacy of marine reserves considered to be inadequate to meet current conservation objectives. In this paper we configured exploratory marine reserve systems, using the software MARXAN, to examine how efficiently South Australia's existing marine reserves contribute to quantitative biodiversity conservation targets. Our aim was to compare marine reserve systems that retain South Australia's existing marine reserves with reserve systems that are free to either ignore or incorporate them. We devised a new interpretation of irreplaceability to identify planning units selected more than could be expected from chance alone. This is measured by comparing the observed selection frequency for an individual planning unit with a predicted selection frequency distribution. Knowing which sites make a valuable contribution to efficient marine reserve system design allows us to determine how well South Australia's existing reserves contribute to reservation goals when representation targets are set at 5, 10, 15, 20, 30 and 50% of conservation features. Existing marine reserves that tail to contribute to efficient marine reserve systems constitute 'opportunity costs'. We found that despite spanning less than 4% of South Australian state waters, locking in the existing ad hoc marine reserves presented considerable opportunity costs. Even with representation targets set at 50%, more than halt of South Australia's existing marine reserves were selected randomly or less in efficient marine reserve systems. Hence, ad hoc marine reserve systems are likely to be inefficient and may compromise effective conservation of marine biodiversity.