Scripts for Assessing potential landscape service trade-offs driven by urbanization in Switzerland

Description

Scripts ordered by their main purpose within sequential folders in this ReadMe marked with

Within the folders the capital letters refer to the parallel or sequential use of the scripts; scripts here in ReadMe are marked with

00_Function Scripts Functions.r Script containing several functions for analyzing statistical models: cohen.kappa, meva.table, D2, max-Tss, plot-TSS

Service_functions.R Script containing functions for calculating all services and returning sums (and median for bd and rec) as well as rasters

01_Data Preparation A_AS_raster_preparation.R Preparation of the land use rasters for the years 1985, 1997, and 2009 based on the original Arealstatistik (AS/ASCH); Assigning our categories and assining new values to all "construction sites" for calibrating the models For model projection starting point (2009) and for service calculations (all ASCH years) the "other" categories were assigned to the land use categories based on dominant neighbor, so that there were no empty cells Creation of water & mountainous area raster that stayed stable throughout the projections Creation of MFH raster (2009), to have as base for all new projection years, as this category never becames any other

B_Factors_preparation.R Preparation of the factor rasters that were used to calculate service values per cell (see Table 2): LWfactor, Transportation, Vol, Rivers, Lakes, slope, TWW, Hazard_risk

B_Predictors_preparation.R Preparation of the raster of the predictors used for calibrating (ASCH years) and projecting (stable) the transition models that do not depend on the land use categories: Temperature (ASCH years), solar radiation (stable), Public transportation access (stable), Elevation (stable), Workers density (ASCH years), Population change (ASCH transitions)

B_Regions_preparation.R Preparation of bioregions as raster to be used to mask asxxxx later to calculated services and land use area just for one region

C_Pred_proj.R Projecting the dynamic predictors into the future for projecting the land use transitions with the model: Linear extrapolations for workers densities and population; more detailed extrapolation of temperature (based on data for all stations that matched between the temp table we used for the calibration period and the projections from CS2M, and then making a spatial interpolation for all years based on the interpolation of temperature for all years per station)

02_Model calibration A_Bioreg_pred_corr.R Calculating correlation between the predictors for each bioregion and land use category, Output are those with too high correlation so that one predictor can be removed from transitions were both predictors occur

A_trans_numbers_bioreg.R Calculate transition numbers for each bioregion to decide which transitions to primarily consider

B_Bioreg_ext_eval.R Calculating TSS based on the external evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 85-97, evaluation data: 97-09)

B_Bioreg_int_eval.R Calculating TSS based on the internal evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 70%, evaluation data: 30%)

C_Bioreg_TSS_analysis.R Extracting TSS numbers from internal and external evaluation, calculating mean and median for each transition for each region for each evaluation method and saving as csv per region to be able to select only the transitions with high enough model performance

D_Bioreg_Models_for_prediction.R Calibration of the models that were then used to project land use transitions into the future; calibrated separately for each bioregion

E_Residuals_trans_models.R Calculation of Moran's I statistics to analyze the residuals of the land use transition models

03_Projections A_Bioreg_Projections_run.R Master script for: Extrapolaitng into the future with the regional models and then assembling for each time step to calculate new AS predictors; Several Outputs: txt file to test for NAs in Predictors, txt file with random seed number for sampling, txt file with times for calculation steps (check progress of script while running), csv sheet with projected transition frequencies, tif-rasters for every region and time step, pdf with raster plot for every region and time step

04_Service calculation A_Bioreg_as_services.R Calculate services per bioregion for years 1985, 1997, 2009

A_Service_calculation_bioregions.R Extracting service numbers(sums) per bioregions for all projection runs and storing them in a list of matrixes to be available for further plotting; can be run for swiss wide projections or regional ones

05_Analysis A_Bioreg_ASCH_development.R Extracting the occurrence of each category per region for all runs (first part), then for ASCH years, and then plotting them nicely; only works for regional projections

A_Bioreg_Predictors_importanceD2.R Calculating D2 for each transition and each considered predictor from bivariate models to get value of importance

B_Bioreg_Pred_imp_analysis.R Using calculated D2 to sort Predictors according to their importance for each transition

A_Bioreg_Spatial_results_analysis.R Plotting randomly sampled runs for ASCH and services to analyses their spatial development

A_Bioreg_Transition_numbers_check_v1.R Analyzing the frequency for all transitions for all regions and producing the point plots for each transition separately

A_Bioreg_Transition_numbers_check_v2.R Analyzing percentage and numbers of all transitions but plotting them per region and originating ASCH category

B_Transition_Analysis.R Further Analysis of transition numbers

A_Service_analysis.R Plotting of the service development for bioregions in several ways for analyzing