Marxan and relatives: Software for spatial conservation prioritization

By I. Ball, Hugh P. Possingham, Matthew E. Watts. 2009

943 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/80f78b0ce4565d68ca1fdc4c05eef30081b0f6a1

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Citations in the corpus

The Diversity of Life in African Freshwaters: Under Water, Under Threat: An Analysis of the Status and Distribution of Freshwater Species throughout Mainland Africa (2011, background): “(2008) modifi ed the boundary quality indicator in ZONATION to deal with longitudinal connectivity, while a number of studies have applied MARXAN (Ball et al. 2009) to plan conservation along river networks by only considering the boundaries between connected sub-catchments (Klein et al.”
Remote Sensing of Coral Reefs for Monitoring and Management: A Review (2016, methodology): “This kind of information is essential for management; maps of resources and the location of critical habitats and biotopes are the baseline for a management plan, especially when using spatial analysis tools such as Marxan [37] (see Section 4).”
Core concepts of spatial prioritisation in systematic conservation planning (2012, background): “Irreplaceability has several slightly different operational definitions and it is sometimes confounded by selection frequency or alternative solutions produced by stochastic optimisation (Ball et al., 2009).”
Conservation priorities for freshwater biodiversity: the key biodiversity area approach refined and tested for continental Africa (2012, methodology): “MARXAN prioritised between 1287 and 1343 catchments, covering between 17.14% and 21.46% of the total land area (Fig.”
Informed opportunism for conservation planning in the Solomon Islands (2011, methodology): “Although housing the underlying data and building the Marxan databases currently relies upon The Nature Conservancy staff, successful execution of the process described in Table 1 depends upon capacity using Zonae Cogito being transferred to the Environment Officer of the Lauru Land Conference of Tr”
Synthesis of pattern and process in biodiversity conservation assessment: a flexible whole‐landscape modelling framework (2010, methodology): “…have been developed to help solve this problem, employing various forms of exact optimization techniques, optimization heuristics such as genetic algorithms or simulating annealing (e.g. Ball et al., 2009), and stepwise forward-selection or backward-removal approaches (e.g. Moilanen et al., 2005).”
Difficult decisions: Strategies for conservation prioritization when taxonomic, phylogenetic and functional diversity are not spatially congruent (2018, background): “…long history in conservation (Kirkpatrick, 1983; Margules and Pressey, 2000; Pressey et al., 1993) and modern prioritization schemes rely on the principle that optimal selection requires knowledge about multiple sites and priorities (Ball et al., 2009; Carvalho et al., 2017; Moilanen et al., 2005).”
Application of species distribution models and conservation planning software to the design of a reserve network for the riverine fishes of northeastern Mesoamerica (2011, methodology): “…(e.g. catchments) that most efficiently meets predefined targets for protection of one or numerous conservation features, while also meeting the general criteria of reserve design (e.g. comprehensiveness, efficiency, complementarity, etc.; Possingham, Ball & Andelman, 2000; Ball et al., 2009).”