Predicting phenotypic expression from genomic and environmental information is arguably the greatest challenge in today’s biology. Being able to survey genomic content, e.g., as single-nucleotide polymorphism data, within a diverse population and predict the phenotypes of external traits, represents...
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Soil microorganisms play fundamental roles in cycling of soil carbon, nitrogen, and other nutrients, yet we have a poor understanding of how soil microbiomes are shaped by their nutritional and physical environment. In this study, we investigated the successional dynamics of a soil microbiome during...
Category
The direct and diffused components of downward shortwave radiation (SW), and photosynthetically active radiation (PAR) at the Earth surface play an essential role in biochemical (e.g. photosynthesis) and physical (e.g. energy balance) processes that control weather and climate conditions, and...
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Publication
Soil respiration (Rs), the flow of CO2 from the soil surface to the atmosphere, is one of the largest carbon fluxes in the terrestrial biosphere. The spatial variability of Rs is both large and poorly understood, limiting our ability to robustly scale it in space. One factor in Rs spatial...
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The high temporal variability of the soil-to-atmosphere CO2 flux (soil respiration, RS) has been studied at hourly to multiannual timescales, but remains less well understood than RS spatial variability. How RS fluxes vary and are auto-correlated at various time lags has practical implications for...
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Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category