Yield increases mediated by pollination and carbon payments can offset restoration costs in coffee landscapes

This dataset and code can be used to reproduce results from the article with the same title

The scripts to generate the farm-level scenarios and the regional-level scenarios are as following:

• farm-level = optimization_scenarios.R
• regional-level = optimization_scenarios_rl.R

The properties boundaries and APP limits for the municipalities considered in this study can be obtained from the adress:

• https://www.car.gov.br/publico/imoveis/index.

The list of municipalities is located at the file "list_mun.csv" within the tables folder.

The raster with land-use and land-cover classes is classified as follows:

• class 0: all other uses;
• class 1: natural vegetation;
• class 2: coffee;

The estimated yield per property is at the yield_estimation.csv file. Each property (n=507) is identified with an unique ID. The dataframe contains:

• the predicted yield in coffee bags/ha (predictec_coffee_bags);
• yield in USD/ha (yield_USD_future); the difference in yield bewteen the future scenarios and the baseline scenario (diff_USD);
• the net present value of the difference between the future scenarios and the baseline (npv_yield_USD_future)

The script "merging_scen_land_use.R" was used to combine the restoration scenarios generated by the optimization model with the baseline land-use and land-cover;