Reading List for 2013 SDM Workshop - Marxan Case Studies

Game, E. T., M. E. Watts, S. Wooldridge, and H. P. Possingham. 2008. Planning for persistence in marine reserves: a question of catastrophic importance. Ecological Applications 18:670–680.

  • Location: Great Barrier Reef
  • Marxan Version:1.8.2
  • Planning units: Reef
  • Cost: Area, lost fishing revenue
  • Conservation targets: Reef bioregions
  • Conservation goals: 20% of each bioregion
  • Themes: Consideration of catastrophic events (esp. climate change related) as part of the reserve design process

Langford, W. T., A. Gordon, and L. Bastin. 2009. When do conservation planning methods deliver? Quantifying the consequences of uncertainty. Ecological Informatics 4:123–135.
  • Location: Victoria, Australia
  • Marxan Version: ?
  • Planning units: 16 ha square
  • Cost: Equal
  • Conservation targets: 7 species
  • Conservation goals: Varied representation for each species
  • Themes: Quantifying the effects of uncertainty on reserve selection results. Implications are a “need for standard practice to include evaluating the effects of multiple real-world complications on the behavior of any conservation planning method. Includes Zonation.

Watts, M. E., I. R. Ball, R. S. Stewart, C. J. Klein, K. Wilson, C. Steinback, R. Lourival, L. Kircher, and H. P. Possingham. 2009. Marxan with Zones: software for optimal conservation based land- and sea-use zoning. Environmental Modelling & Software 24:1513–1521

  • Location: Multiple
  • Marxan Version: Marxan with Zones
  • Planning units:
  • Cost:
  • Conservation targets:
  • Conservation goals:
  • Themes: Introducing Marxan with Zones.

Underwood, J. G., C. D’agrosa, and L. R. Gerber. 2010. Identifying conservation areas on the basis of alternative distribution data sets. Conservation Biology 24:162–170
  • Location: Arizona
  • Marxan Version: 2.0.2
  • Planning units: 25 km² square
  • Cost: Equal
  • Conservation targets: 71 mammal species
  • Conservation goals: Representation of each species at least once, 10% of occurrences of each
  • Themes: Impact of different distribution data sets on reserve selection.

Huber, P. R., S. E. Greco, and J. H. Thorne. 2010. Spatial scale effects on conservation network design: trade-offs and omissions in regional versus local scale planning. Landscape Ecology 25:683–695.

  • Location: Central Valley, California
  • Marxan Version: 1.8.2
  • Planning units: 13.3 ha hex
  • Cost: Area
  • Conservation targets: 8 species habitat suitability
  • Conservation goals: 30% of potential habitat for each species
  • Themes: Scale of analysis has important effects on resulting reserve network.

Klein, C. J., C. Steinback, M. Watts, A. J. Scholz, and H. P. Possingham. 2009. Spatial marine zoning for fisheries and conservation. Frontiers in Ecology and the Environment 8:349–353.

  • Location: California coast
  • Marxan Version: Marxan with Zones
  • Planning units: ~0.5 km² square
  • Cost: Sum of value for all fisheries not allowed to fish in a zone
  • Conservation targets: Habitats, regions, depth zones
  • Conservation goals: 10-30% of each conservation feature
  • Themes: Comparison of MWZ to Marxan. MWZ performs better in that impacts to fishing are reduced and loss is spread across fisheries.

Guerrero, A. M., A. T. Knight, H. S. Grantham, R. M. Cowling, and K. A. Wilson. 2010. Predicting willingness-to-sell and its utility for assessing conservation opportunity for expanding protected area networks. Conservation Letters 3:332–339
  • Location: Eastern Cape Province, South Africa
  • Marxan Version: ?
  • Planning units: Parcels
  • Cost: Purchase cost, willingness-to-sell
  • Conservation targets: 19 vegetation types
  • Conservation goals: 10%, 30%
  • Themes: Included a willingness-to-sell component in the model.

Lagabrielle, E., A. Botta, W. Daré, D. David, S. Aubert, and C. Fabricius. 2010. Modelling with stakeholders to integrate biodiversity into land-use planning – Lessons learned in Réunion Island (Western Indian Ocean). Environmental Modelling & Software 25:1413–1427.

  • Location: Réunion Island
  • Marxan Version: 1.8.2
  • Planning units: 4 ha squares
  • Cost: Implementation, invasive plants control, restoration, conversion pressure
  • Conservation targets: Habitats, processes, species
  • Conservation goals: 30% (pre-human colonization)
  • Themes: Participatory development of land use simulation models should be promoted.

Esselman, P. C., and J. D. Allan. 2011. Application of species distribution models and conservation planning software to the design of a reserve network for the riverine fishes of northeastern Mesoamerica. Freshwater Biology 56:71–88.

  • Location: Yucatan
  • Marxan Version: ?
  • Planning units: Local catchments
  • Cost: Risk of environmental degradation
  • Conservation targets: Fish species ranges
  • Conservation goals: 15% of the range of each species
  • Themes: Integrating Maxent and Marxan.

Stralberg, D., D. R. Cameron, M. D. Reynolds, C. M. Hickey, K. Klausmeyer, S. M. Busby, L. E. Stenzel, W. D. Shuford, and G. W. Page. 2011. Identifying habitat conservation priorities and gaps for migratory shorebirds and waterfowl in California. Biodiversity and Conservation 20:19–40.
  • Location: California
  • Marxan Version: ?
  • Planning units: 1,000 ha hex
  • Cost: Housing density
  • Conservation targets: Shorebirds and waterfowl populations
  • Conservation goals: 50%, 75% total mean count of each species in each ecoregion or basin
  • Themes: Linked estimated bird density models to Marxan.

Lourival, R., M. Drechsler, M. E. Watts, E. T. Game, and H. P. Possingham. 2011. Planning for reserve adequacy in dynamic landscapes; maximizing future representation of vegetation communities under flood disturbance in the Pantanal wetland. Diversity and Distributions 17:297–310.
  • Location: Pantanal wetlands, South America
  • Marxan Version: ?
  • Planning units: 10,000 ha square
  • Cost: ?
  • Conservation targets: 5 plant communities
  • Conservation goals: 20%
  • Themes: Using Marxan for planning in dynamic landscapes.

Januchowski-Hartley, S. R., P. Visconti, and R. L. Pressey. 2011. A systematic approach for prioritizing multiple management actions for invasive species. Biological Invasions 13:1241–1253.
  • Location: Queensland, Australia
  • Marxan Version: ?
  • Planning units: Wetlands, stream reaches
  • Cost: Management cost (most appropriate for planning unit)
  • Conservation targets: Reduction of infestation
  • Conservation goals: Specified level
  • Themes: First use of Marxan to address the spatial allocation of management actions and funds for invasive species management at a local scale. Used Maxent to model invasive species distribution.

Schneider, R. R., G. Hauer, D. Farr, W. L. Adamowicz, and S. Boutin. 2011. Achieving conservation when opportunity costs are high: optimizing reserve design in Alberta’s oil sands region. PLoS ONE 6:e23254.

  • Location: Alberta, Canada
  • Marxan Version: ?
  • Planning units: Townships (~9,500 ha)
  • Cost: Net present value of resources, linear features (intactness)
  • Conservation targets: Subregions, forest types, riparian corridors
  • Conservation goals: 15-40%, increments of 5%, all or none
  • Themes: Incorporation of economic costs into planning process.

Chan, K. M. A., L. Hoshizaki, and B. Klinkenberg. 2011. Ecosystem services in conservation planning: targeted benefits vs. co-benefits or costs? PLoS ONE 6:e24378.
  • Location: British Columbia, Canada
  • Marxan Version: 2.0.2
  • Planning units: 500 ha hex
  • Cost: Timber production
  • Conservation targets: ecosystem services (biodiversity, angling, carbon storage)
  • Conservation goals: 50%
  • Themes: Inclusion of ecosystem services in systematic conservation planning.

Game, E. T., G. Lipsett-Moore, E. Saxon, N. Peterson, and S. Sheppard. 2011. Incorporating climate change adaptation into national conservation assessments. Global Change Biology 17:3150–3160.
  • Ecosystem: Papua New Guinea
  • Marxan Version: ?
  • Planning units: 5,000 ha hex
  • Cost: Human population
  • Conservation targets: Vegetation types by ecoregion, restricted range endemic species (reptiles, amphibians, mammals), land systems (slope, substrate, elevation)
  • Conservation goals: 10% (more for rare or endangered types), 50% of species distribution, 10% of land system types
  • Themes: Incorporating climate change adaption into conservation assessments using geophysical variables.

Segan, D. B., E. T. Game, M. E. Watts, R. R. Stewart, and H. P. Possingham. 2011. An interoperable decision support tool for conservation planning. Environmental Modelling & Software 26:1434–1441.
  • Ecosystem: n/a
  • Marxan Version: Zonae Cogito
  • Planning units: n/a
  • Cost: n/a
  • Conservation targets: n/a
  • Conservation goals: n/a
  • Themes: ZC combines Marxan with MapWindow GIS interface, other features

Carvalho, S. B., J. C. Brito, R. L. Pressey, E. Crespo, and H. P. Possingham. 2010. Simulating the effects of using different types of species distribution data in reserve selection. Biological Conservation 143:426–438.
  • Ecosystem: Iberian Peninsula
  • Marxan Version: 1.8.10
  • Planning units: 100 km² square
  • Cost: Equal, random
  • Conservation targets: 66 amphibian and reptile species
  • Conservation goals: 10% of occurrences, 5%, 1%, variable (conservation status, biological status, range).
  • Themes: Using different species distribution data as inputs in Marxan. Results are sensitive to choice, which should be made by evaluating the scenario circumstances.

Hermoso, V., and M. J. Kennard. 2012. Uncertainty in coarse conservation assessments hinders the efficient achievement of conservation goals. Biological Conservation 147:52–59.
  • Ecosystem: Daly River basin, Australia
  • Marxan Version: ?
  • Planning units: Sub-catchments
  • Cost: Equal
  • Conservation targets: Fish species
  • Conservation goals: 6% of planning units
  • Themes: Effect of grain size of species distribution data vs. size of planning units on conservation planning outputs.

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