This HydroShare resource contains the complete R code, intermediate outputs, and analysis products used in the study entitled “A vegetation-based modeling framework for estimating ecosystem respiration across land uses.”
The workflow consists of two primary R scripts and one supplementary R script.

1. The first script (01_Data_Preparation_and_RecoBase_Fitting.R) prepares input datasets, merges satellite and flux observations, and derives the baseline ecosystem respiration component (Reco_Base).
2. The second script (02_RecoNew_Fitting_and_Main_Analyses.R) performs model parameter optimization, ecosystem respiration simulation, model evaluation, bias analysis, time-series diagnostics, parameter distribution analysis, and seasonal supplementary analyses.
3. The third script (03_Supplementary_Analyses) conducts supplementary analyses such as Air temperature and T_opt sensitivity analysis and 80:20 split evaluation.

The generated outputs are organized into numbered directories corresponding to major analytical steps:
01_Site_Map: Locations of all study sites.
02_Fitting_and_Simulation: Optimized model parameters and simulated Reco datasets.
03_Model_Comparison_Scatter: Scatter plot comparisons between observed and modeled Reco.
04_Bias_Analysis: Quantitative bias metrics by land-use category.
05_Bias_Barplots: Visualization of model bias statistics.
06_TimeSeries_Comparison: Site-level time-series comparisons and diagnostic plots.
07_Parameter_Error_Analysis: Parameter summaries and error analyses.
08_Parameter_PDF_Density: Probability density distributions of fitted parameters.
09_Seasonal_Supplementary_Figures: Seasonal governing-factor analyses and soil moisture-temperature coupling figures.
10_Supplementary Analysis: Air temperature and T_opt sensitivity analysis, and 80:20 split evaluation

All original eddy covariance observations used in this study were obtained from the AmeriFlux networks. Satellite-derived vegetation products, including MODIS-based datasets, were acquired from available NASA data repositories.
This resource is intended to support transparency, reproducibility, and future methodological development related to ecosystem respiration modeling and carbon-cycle research.