ESM ESM

This is the description of the dataset used in my manuscript titled: "Fluctuations in Ecosystem Services in Response to Land Conversion and Climate Extremes as an Index of Ecosystem Degradation and Restoration: A Comparison of the Lake Chad and Aral Sea Basins." The annual worldwide land cover datasets at a 300-meter resolution for the years 2000, 2010, and 2020 were sourced directly from the European Space Agency's Climate Change Initiative (CCI) project. The climatic indices (precipitation and temperature) data were acquired from the Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) and the ERA5 dataset, a detailed reanalysis dataset from the European Center for Medium-Range Weather Forecasts (ECMWF). The heights were obtained from the Universal Multi-resolution Terrain Height Data (UMTED2010) at 250 m spatial resolution. Data on soil qualities, such as the percentage of sand, clay, silt, and organic carbon matter, as well as the depth of the soil's roots, were obtained at a 250-meter spatial resolution from the International Soil Reference and Information Center (www.isric-world-soil). All datasets were obtained via JavaScript coding on the Google Earth Engine platform. We estimated eWBR using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model version 3.13.0 based on the Budyko curve (Yang et al., 2019). The InVEST model also estimated the total amount of carbon stored (CS) and carbon sequestrated(C.Seq) (Piyathilake et al., 2022), by combining the carbon pool density assigned to each LULC  This is the description of the dataset used in my manuscript titled: "Fluctuations in Ecosystem Services in Response to Land Conversion and Climate Extremes as an Index of Ecosystem Degradation and Restoration: A Comparison of the Lake Chad and Aral Sea Basins." The annual worldwide land cover datasets at a 300-meter resolution for the years 2000, 2010, and 2020 were sourced directly from the European Space Agency's Climate Change Initiative (CCI) project. The climatic indices (precipitation and temperature) data were acquired from the Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) and the ERA5 dataset, a detailed reanalysis dataset from the European Center for Medium-Range Weather Forecasts (ECMWF). The heights were obtained from the Universal Multi-resolution Terrain Height Data (UMTED2010) at 250 m spatial resolution. Data on soil qualities, such as the percentage of sand, clay, silt, and organic carbon matter, as well as the depth of the soil's roots, were obtained at a 250-meter spatial resolution from the International Soil Reference and Information Center (www.isric-world-soil). All datasets were obtained via JavaScript coding on the Google Earth Engine platform. We estimated eWBR using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model version 3.13.0 based on the Budyko curve (Yang et al., 2019). The InVEST model also estimated the total amount of carbon stored (CS) and carbon sequestrated(C.Seq) (Piyathilake et al., 2022), by combining the carbon pool density assigned to each LULC