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

3. 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

5. 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

9. 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 ValueStd Dev% PopulatedValueStd Dev% PopulatedValueStd Dev% Populated Archetype Point:101008----113252----116848---- Points Per Cluster:131----21----53---- STDDEV_G30VALUE:173.04249.453499.2563.19870.731410072.313489.8572100 RUNOFF_TOTAL_ANN:140.087216.29596.21127.43827.576100239.132189.971100 CELL_PERCNT_CROPLAND:1.032471.692071008.545837.6522810019.2613.72895100 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 ValueStd Dev% PopulatedValueStd Dev% PopulatedValueStd Dev% Populated Archetype Point:117564----99510----103911---- Points Per Cluster:95----56----41---- STDDEV_G30VALUE:89.032562.613796.8351.47169.522910084.17286.4584100 RUNOFF_TOTAL_ANN:1032.86284.36997.9471.527441.10398.22276.4413.82797.6 CELL_PERCNT_CROPLAND:0.9118291.613921003.186743.585511002.307034.62122100 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 ValueStd Dev% PopulatedValueStd Dev% PopulatedValueStd Dev% Populated Archetype Point:96680----111101----73646---- Points Per Cluster:22----16----73---- STDDEV_G30VALUE:55.890569.196810035.450835.799481.245.874753.0853100 RUNOFF_TOTAL_ANN:299.591421.041004892.75745.12650322.041255.67100 CELL_PERCNT_CROPLAND:32.84166.643581000.1980380.47841008.868292.60714100 Cluster:Cluster 9: low STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND ValueStd Dev% Populated Archetype Point:97365---- Points Per Cluster:379---- STDDEV_G30VALUE:14.906721.754899.2 RUNOFF_TOTAL_ANN:213.039198.17681.8 CELL_PERCNT_CROPLAND:0.7341661.15099100 Entire Set ValueStd DevMinMax Archetype Point:-------- Points Per Cluster:-------- STDDEV_G30VALUE:91.3612126.4540672.35 RUNOFF_TOTAL_ANN:502.286736.47505822 CELL_PERCNT_CROPLAND:3.772877.14192048.996