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Team: Francisco Contreras, Carlos Lechuga and Martin Merino Objectives:

Team: Francisco Contreras, Carlos Lechuga and Martin Merino Objectives: 1) reproduce our previous best classification of the coasts of Mexico in terms of LOICZ’s objectives 2) try it with the world coastline.

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Team: Francisco Contreras, Carlos Lechuga and Martin Merino Objectives:

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  1. Team: Francisco Contreras, Carlos Lechuga and Martin Merino Objectives: 1) reproduce our previous best classification of the coasts of Mexico in terms of LOICZ’s objectives 2) try it with the world coastline

  2. We chose three kind of proxies and the parameters that could work for each case: As runoff proxies: Precip, ann mean Runoff, annual mean * Basin Runoff Soil Carbonate C, As geomorphic proxies: CZ Bath/Elev, std dev of SS2 value Ocean Bath, mean SS2 value Land Elev, mean G30 value Land Elev, std dev of G30 values * Cell Landcover, % Water Basin Landcover, % Water As C, N, P, flux proxies: Soil Organic C, Cell Landcover, % Cropland * Cell Landcover, % Grassland Cell Landcover, % Urban and Built-up Population, 30' cell total Basin Landcover, % Cropland Basin Landcover, % Grassland Basin Landcover, % Urban and Built-up Basin Population

  3. Results: 1) We could get a typology that reproduces our previous classification target 2) However, variability was still present within our types, as most were represented by cells of two clusters

  4. Cluster: Cluster 0: low STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND Cluster 1: high STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN Cluster 2: medium CELL_PERCNT_CROPLAND, low RUNOFF_TOTAL_ANN Value Std Dev % Populated Value Std Dev % Populated Value Std Dev % Populated Archetype Point: 101008 -- -- 113252 -- -- 116848 -- -- Points Per Cluster: 131 -- -- 21 -- -- 53 -- -- STDDEV_G30VALUE: 173.042 49.4534 99.2 563.198 70.7314 100 72.3134 89.8572 100 RUNOFF_TOTAL_ANN: 140.087 216.295 96.2 1127.43 827.576 100 239.132 189.971 100 CELL_PERCNT_CROPLAND: 1.03247 1.69207 100 8.54583 7.65228 100 19.261 3.72895 100 Cluster: Cluster 3: low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND Cluster 4: medium STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND Cluster 5: medium RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND Value Std Dev % Populated Value Std Dev % Populated Value Std Dev % Populated Archetype Point: 117564 -- -- 99510 -- -- 103911 -- -- Points Per Cluster: 95 -- -- 56 -- -- 41 -- -- STDDEV_G30VALUE: 89.0325 62.6137 96.8 351.471 69.5229 100 84.172 86.4584 100 RUNOFF_TOTAL_ANN: 1032.86 284.369 97.9 471.527 441.103 98.2 2276.4 413.827 97.6 CELL_PERCNT_CROPLAND: 0.911829 1.61392 100 3.18674 3.58551 100 2.30703 4.62122 100 Cluster: Cluster 6: high CELL_PERCNT_CROPLAND, low RUNOFF_TOTAL_ANN Cluster 7: high RUNOFF_TOTAL_ANN Cluster 8: low CELL_PERCNT_CROPLAND, low RUNOFF_TOTAL_ANN Value Std Dev % Populated Value Std Dev % Populated Value Std Dev % Populated Archetype Point: 96680 -- -- 111101 -- -- 73646 -- -- Points Per Cluster: 22 -- -- 16 -- -- 73 -- -- STDDEV_G30VALUE: 55.8905 69.1968 100 35.4508 35.7994 81.2 45.8747 53.0853 100 RUNOFF_TOTAL_ANN: 299.591 421.04 100 4892.75 745.126 50 322.041 255.67 100 CELL_PERCNT_CROPLAND: 32.8416 6.64358 100 0.198038 0.4784 100 8.86829 2.60714 100 Cluster: Cluster 9: low STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND Value Std Dev % Populated Archetype Point: 97365 -- -- Points Per Cluster: 379 -- -- STDDEV_G30VALUE: 14.9067 21.7548 99.2 RUNOFF_TOTAL_ANN: 213.039 198.176 81.8 CELL_PERCNT_CROPLAND: 0.734166 1.15099 100 Entire Set Value Std Dev Min Max Archetype Point: -- -- -- -- Points Per Cluster: -- -- -- -- STDDEV_G30VALUE: 91.3612 126.454 0 672.35 RUNOFF_TOTAL_ANN: 502.286 736.475 0 5822 CELL_PERCNT_CROPLAND: 3.77287 7.14192 0 48.996

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