Maritime Use Conflict ===================== Aim of the module ------------------- The MUC module allows to assess and map maritime use conflicts. Conflicts (MUC) are defined as the constraints creating disadvantages to maritime activities located in a given sea area. The method applied is in line with COEXIST Project methodology (Gramolini et al., 2010), already applied within the Adriatic-Ionian Sea (Barbanti et al., 2015; Depellegrin et al., 2017). .. figure:: images/muc_conceptual_schema.png :alt: MUC conceptual schema :align: center :name: muc-conceptual-schema Conceptual schema of the Maritime Use Conflict module .. _muc-module-inputs: Module inputs ------------- Input layers ++++++++++++ .. figure:: images/muc_input_layers.png :alt: MUC imput layer :align: center :name: muc-input-layers Web map representing the geospatial distribution of human activities. COEXISTS rules and human traits +++++++++++++++++++++++++++++++ MUC methodology is implemented according to Barbanti et al. 2015. The following operational steps allow to define the potential conflict score for pariwise combination: 1. human uses classification and assignment of numerical values to five traits (mobility, spatial, vertical and temporal scale, location) (ses :numref:`muc-factors`; 2. assignment of the three rules to calculate default level of conflict for pairwise combinations 3. expert-based adjustments to define the validate version of the potential conflict score matrix (see :numref:`muc-potential-score-matrix`) According to original COEXIST methodology, the rules for automatically calculate the default level of conflict are: - Rule 1: if vertical domain of activity 1 is different from vertical domain of activity 2 and no one of them interests the whole water column then conflict score is equal to 0; - Rule 2: If both activities are “mobile” then conflict score is equal to the minimum of temporal domain plus the minimum of spatial domain - Rule 3: if Rule1 and Rule2 cannot be applied then the conflict score is equal to the maximum value of temporal domain plus the maximum value of spatial domain. .. table:: Potential conflict traits for classifing human uses. :widths: auto :name: muc-factors +---+-------------------------+-------------------------+--------------+ | | Human traits | Value | Value | +===+=========================+=========================+==============+ | 1 | Vertical scale | - Pelagic | - Value = 1 | | | | - Benthic | - Value = 2 | | | | - whole water column | - Value = 3 | +---+-------------------------+-------------------------+--------------+ | 2 | Spatial scale | - Small | - Value = 1 | | | | - Medium | - Value = 2 | | | | - Large | - Value = 3 | +---+-------------------------+-------------------------+--------------+ | 3 | Temporal scale | - Small | - Value = 1 | | | | - Medium | - Value = 2 | | | | - Large | - Value = 3 | +---+-------------------------+-------------------------+--------------+ | 4 | Mobility | - Mobile | - Value = 1 | | | | - Fixed | - Value = 2 | +---+-------------------------+-------------------------+--------------+ | 5 | Location | - Land | - Value = 1 | | | | - Sea | - Value = 2 | +---+-------------------------+-------------------------+--------------+ .. figure:: images/muc_potential_score_matrix.png :alt: MUC potential score matrix :align: center :name: muc-potential-score-matrix Example of potential conflict score matrix. Module outputs -------------- The MUC module produces the following main outputs: - geospatial distribution of conflict score (MUCSCORE) (see :numref:`muc-output-map`). A 2-D GeoTIFF raster file representing the overall conflict score in each raster grid cell. Coordinate reference system (CRS) and resolution are defined by the Case Study configuration. - MUC score for each U-U combination (HEATUSEMUC) (see :numref:`muc-output-matrix`). A table/matrix representing the contribution (in percentage) of the single pairwise combinations to the total MUC score (for the whole area of analysis). .. figure:: images/muc_output_map.png :alt: Geospatial distribution of MUC scores :align: center :name: muc-output-map Example of geospatial distribution of MUC scores for the Adriatic sea. .. figure:: images/muc_output_matrix.png :alt: MUC :align: center :name: muc-output-matrix Example of MUC supporting MSP ------------------ According to Pinarbasi et al. (2017), the MSP process can be subdivided into seven steps (see :numref:`muc-msp-steps`). MUC module has been designed to directly support three steps: Gather data and define current condition, Identify issues, constraints, and future condition and Evaluate alternative management actions. .. |logo_check| image:: ../../images/check_circle.png :scale: 75% .. table:: Major steps of the MSP conceptual mtehod :widths: auto :name: muc-msp-steps +--------+--------------------------------------------------------+--------------+ | Stages | Definition | MUC module | +========+========================================================+==============+ | 1 | Define goals and objectives | | +--------+--------------------------------------------------------+--------------+ | 2 | **Gather data and define current conditions** | |logo_check| | +--------+--------------------------------------------------------+--------------+ | 3 | **Identify issues, constraints, and future condition** | |logo_check| | +--------+--------------------------------------------------------+--------------+ | 4 | Develop alternative management actions | | +--------+--------------------------------------------------------+--------------+ | 5 | **Evaluate alternative management actions** | |logo_check| | +--------+--------------------------------------------------------+--------------+ | 6 | Monitor and evaluate management actions | | +--------+--------------------------------------------------------+--------------+ | 7 | Refine goals, objectives and management actions | | +--------+--------------------------------------------------------+--------------+ Main examples of use of MUC module in supporting the MSP process are: * identify and spatialize current/potential human uses and assesses their interaction in terms of conflicts (business as usual scenario); * support MSP process testing hypotheses of reallocation of maritime uses; * iterate the analysis over different time periods through integration of new conflict scores and geospatial datasets on sea uses; * perform scenario analysis to test planning options References ---------- Depellegrin, Daniel, Stefano Menegon, Giulio Farella, Michol Ghezzo, Elena Gissi, Alessandro Sarretta, Chiara Venier, and Andrea Barbanti. 2017. “Multi-Objective Spatial Tools to Inform Maritime Spatial Planning in the Adriatic Sea.” Science of The Total Environment 609 (December): 1627–39. https://doi.org/10.1016/j.scitotenv.2017.07.264. Menegon, Stefano, Daniel Depellegrin, Giulio Farella, Alessandro Sarretta, Chiara Venier, and Andrea Barbanti. 2018. “Addressing Cumulative Effects, Maritime Conflicts and Ecosystem Services Threats through MSP-Oriented Geospatial Webtools.” Ocean & Coastal Management 163 (September): 417–36. https://doi.org/10.1016/j.ocecoaman.2018.07.009. Menegon, Stefano, Alessandro Sarretta, Daniel Depellegrin, Giulio Farella, Chiara Venier, and Andrea Barbanti. 2018. “Tools4MSP: An Open Source Software Package to Support Maritime Spatial Planning.” PeerJ Computer Science 4 (October): e165. https://doi.org/10.7717/peerj-cs.165. Pınarbaşı, Kemal, Ibon Galparsoro, Ángel Borja, Vanessa Stelzenmüller, Charles N. Ehler, and Antje Gimpel. 2017. “Decision Support Tools in Marine Spatial Planning: Present Applications, Gaps and Future Perspectives.” Marine Policy 83 (September): 83–91. https://doi.org/10.1016/j.marpol.2017.05.031.