Changes between Version 10 and Version 11 of EwEugSpatialOptimizationProcedures


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Timestamp:
2010-11-24 00:10:10 (9 years ago)
Author:
shermanl
Comment:

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  • EwEugSpatialOptimizationProcedures

    v10 v11  
    88The most widely used approach for spatial planning with a conservation perspective is the Marxan approach and software, (http://www.uq.edu.au/marxan/) developed primarily by Hugh Possingham and colleagues at the Ecology Centre, University of Queensland. Marxan is a very flexible approach capable of incorporating large data sources and use categories, it is computationally efficient, and lends itself well to enabling stakeholder involvement in the site selection process. 
    99 
    10 We view the new importance layer sampling procedure as complimentary to the Marxan approach in that its strong side, through the underlying trophic modeling background is in evaluating ecological processes, including spatial connectivity; topics that are not well covered in Marxan analysis. In doing so, we, however, involve a rather complicated dynamic model, even if user-friendly, and this unavoidably has a cost. We therefore advocate that the two approaches, with their given advantages and limitations, be applied in conjunction using two sources to throw light at a problem from different angles, beats one, any time. We have in order to facilitate such comparative studies developed a two-way bridge between Marxan and EwE, enabling exchange of spatial information and of optimization results between the two approaches. We describe only briefly aspects of this below, as we have applied the bridge elsewhere for a formal comparison (Ferdaña et al., MS). 
     10We view the new importance layer sampling procedure as complimentary to the Marxan approach in that its strong side, through the underlying trophic modeling background is in evaluating ecological processes, including spatial connectivity; topics that are not well covered in Marxan analysis. In doing so, we, however, involve a rather complicated dynamic model, even if user-friendly, and this unavoidably has a cost. We therefore advocate that the two approaches, with their given advantages and limitations, be applied in conjunction - using two sources to throw light at a problem from different angles, beats one, any time. We have in order to facilitate such comparative studies developed a two-way bridge between Marxan and EwE, enabling exchange of spatial information and of optimization results between the two approaches. We describe only briefly aspects of this below, as we have applied the bridge elsewhere for a formal comparison (Ferdaña et al., MS). 
    1111 
    1212'''__Methodology__''' 
     
    5454[[Image(wiki:EwEugImages:03000021.png)]] 
    5555 
    56 We truncate the index in the extreme and unlikely case that [[Image(wiki:EwEugImages:03000022.png)]] would more than double from the base run. We only include higher trophic level groups (TL>3) in the calculation of the biomass diversity index should this, for models with only few functional groups, lead to less than 10 groups being included in the calculations, we, however, base the calculations on all living groups. As for the other ecological indicators we do not discount future index values. 
     56We truncate the index in the extreme and unlikely case that [[Image(wiki:EwEugImages:03000022.png)]] would more than double from the base run. We only include higher trophic level groups (TL>3) in the calculation of the biomass diversity index - should this, for models with only few functional groups, lead to less than 10 groups being included in the calculations, we, however, base the calculations on all living groups. As for the other ecological indicators we do not discount future index values. 
    5757 
    5858The final element in the objective function represents spatial connectivity, expressed through the boundary weight factor, [[Image(wiki:EwEugImages:03000023.png)]]