Browsing by Author "Shiklomanov, Alexey N."

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    A community convention for ecological forecasting: output files and metadata v1.0
    Dietze, Michael C.; Thomas, R. Quinn; Peters, Jody; Boettiger, Carl; Koren, Gerbrand; Shiklomanov, Alexey N.; Ashander, Jaime (Wiley, 2023-11-23)
    This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe the convention conceptually in terms of global attributes, forecast dimensions, forecasted variables, and ancillary indicator variables. We then illustrate the application of this convention to the two file formats that are currently preferred by the EFI, netCDF (network common data form), and comma-separated values (CSV), but note that the convention is extensible to future formats. For metadata, EFI's convention identifies a subset of conventional metadata variables that are required (e.g., temporal resolution and output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity, which aims to facilitate cross-forecast synthesis. The initial application of this convention expands upon the Ecological Metadata Language (EML), a commonly used metadata standard in ecology. To facilitate community adoption, we also provide a Github repository containing a metadata validator tool and several vignettes in R and Python on how to both write and read in the EFI standard. Lastly, we provide guidance on forecast archiving, making an important distinction between short-term dissemination and long-term forecast archiving, while also touching on the archiving of code and workflows. Overall, the EFI convention is a living document that can continue to evolve over time through an open community process.
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    Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle
    Jian, Jinshi; Bailey, Vanessa; Dorheim, Kalyn; Konings, Alexandra G.; Hao, Dalei; Shiklomanov, Alexey N.; Snyder, Abigail; Steele, Meredith; Teramoto, Munemasa; Vargas, Rodrigo; Bond-Lamberty, Ben (Springer Nature, 2022-04-01)
    The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, RS), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and RS are irreconcilable. When we estimate GPP based on RS measurements and some assumptions about RS:GPP ratios, we found the resulted global GPP values (bootstrap mean 149+29−23 Pg C yr−1) are significantly higher than most GPP estimates reported in the literature (113+18−18 Pg C yr−1). Similarly, historical GPP estimates imply a soil respiration flux (RsGPP, bootstrap mean of 68+10−8 Pg C yr−1) statistically inconsistent with most published RS values (87+9−8 Pg C yr−1), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global RS:GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.