Replication Data for: Effect of temporal aggregation and phenology on LUE model variables and productivity in two deciduous forests.
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The integration of optical and flux data requires temporal aggregation of data. In this study, we explore the effect of temporal integration through an in-depth assessment exploring its impact and its ecological relevance. Optical remote sensing and eddy covariance flux data collected over four years from a Tropical Dry Forest (TDF) and a Deciduous Boreal Forest (DBF) were used in the analysis. Light use efficiency model variables (PAR, fAPARgreen, APARgreen, and LUE) were derived, temporally aggregated over the diurnal period at 1hr increasing intervals and compared to gross primary productivity, derived from flux measurements. Temporal aggregation analysis was performed at the seasonal scale as well as divided by phenological stage (greenup, maturity, and senescence). Seasonal aggregation analysis showed little effect on fAPARgreen de' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Eddy Covariance","LUE model","Phenology","Productivity"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The integration of optical and flux data requires temporal aggregation of data. In this study, we explore the effect of temporal integration through an in-depth assessment exploring its impact and its ecological relevance. Optical remote sensing and eddy covariance flux data collected over four years from a Tropical Dry Forest (TDF) and a Deciduous Boreal Forest (DBF) were used in the analysis. Light use efficiency model variables (PAR, fAPARgreen, APARgreen, and LUE) were derived, temporally aggregated over the diurnal period at 1hr increasing intervals and compared to gross primary productivity, derived from flux measurements. Temporal aggregation analysis was performed at the seasonal scale as well as divided by phenological stage (greenup, maturity, and senescence). Seasonal aggregation analysis showed little effect on fAPARgreen de' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The integration of optical and flux data requires temporal aggregation of data. In this study, we explore the effect of temporal integration through an in-depth assessment exploring its impact and its ecological relevance. Optical remote sensing and eddy covariance flux data collected over four years from a Tropical Dry Forest (TDF) and a Deciduous Boreal Forest (DBF) were used in the analysis. Light use efficiency model variables (PAR, fAPARgreen, APARgreen, and LUE) were derived, temporally aggregated over the diurnal period at 1hr increasing intervals and compared to gross primary productivity, derived from flux measurements. Temporal aggregation analysis was performed at the seasonal scale as well as divided by phenological stage (greenup, maturity, and senescence). Seasonal aggregation analysis showed little effect on fAPARgreen de
Eddy Covariance; LUE model; Phenology; Productivity