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. 2020 Dec;26(12):7268-7283.
doi: 10.1111/gcb.15353. Epub 2020 Oct 7.

COSORE: A community database for continuous soil respiration and other soil-atmosphere greenhouse gas flux data

Ben Bond-Lamberty  1 Danielle S Christianson  2 Avni Malhotra  3 Stephanie C Pennington  1 Debjani Sihi  4 Amir AghaKouchak  5 Hassan Anjileli  5 M Altaf Arain  6 Juan J Armesto  7   8 Samaneh Ashraf  9 Mioko Ataka  10 Dennis Baldocchi  11 Thomas Andrew Black  12 Nina Buchmann  13 Mariah S Carbone  14 Shih-Chieh Chang  15 Patrick Crill  16 Peter S Curtis  17 Eric A Davidson  18 Ankur R Desai  19 John E Drake  20 Tarek S El-Madany  21 Michael Gavazzi  22 Carolyn-Monika Görres  23 Christopher M Gough  24 Michael Goulden  25 Jillian Gregg  26 Omar Gutiérrez Del Arroyo  11 Jin-Sheng He  27 Takashi Hirano  28 Anya Hopple  29   30 Holly Hughes  31 Järvi Järveoja  32 Rachhpal Jassal  12 Jinshi Jian  1 Haiming Kan  33 Jason Kaye  34 Yuji Kominami  35 Naishen Liang  36 David Lipson  37 Catriona A Macdonald  38 Kadmiel Maseyk  39 Kayla Mathes  40 Marguerite Mauritz  41 Melanie A Mayes  4 Steve McNulty  22 Guofang Miao  42 Mirco Migliavacca  21 Scott Miller  43 Chelcy F Miniat  44 Jennifer G Nietz  17 Mats B Nilsson  32 Asko Noormets  45 Hamidreza Norouzi  46 Christine S O'Connell  11   47 Bruce Osborne  48 Cecilio Oyonarte  49 Zhuo Pang  33 Matthias Peichl  32 Elise Pendall  38 Jorge F Perez-Quezada  50   51 Claire L Phillips  52 Richard P Phillips  53 James W Raich  54 Alexandre A Renchon  38 Nadine K Ruehr  55 Enrique P Sánchez-Cañete  56 Matthew Saunders  57 Kathleen E Savage  58 Marion Schrumpf  21 Russell L Scott  59 Ulli Seibt  60 Whendee L Silver  11 Wu Sun  61 Daphne Szutu  11 Kentaro Takagi  62 Masahiro Takagi  63 Munemasa Teramoto  36 Mark G Tjoelker  38 Susan Trumbore  21 Masahito Ueyama  64 Rodrigo Vargas  65 Ruth K Varner  66 Joseph Verfaillie  11 Christoph Vogel  67 Jinsong Wang  68 Greg Winston  69 Tana E Wood  70 Juying Wu  33 Thomas Wutzler  21 Jiye Zeng  36 Tianshan Zha  71 Quan Zhang  72 Junliang Zou  33
Affiliations

COSORE: A community database for continuous soil respiration and other soil-atmosphere greenhouse gas flux data

Ben Bond-Lamberty et al. Glob Chang Biol. 2020 Dec.

Abstract

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Keywords: carbon dioxide; greenhouse gases; methane; open data; open science; soil respiration.

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Figures

FIGURE 1
FIGURE 1
Summary of COSORE structure (multiple datasets, each with six tables; Tables 2, 3, 4, 5) and primary accessor R functions, as described in the text (see Section 2.1 in text). For example, R users can join specific tables across all datasets using the csr_table() function, and can access individual datasets with csr_dataset(). Non‐R users access flat‐file versions of the same data, with essentially the same structure as the R internal structure shown here
FIGURE 2
FIGURE 2
Geographic distribution of COSORE datasets (N = 89), with point sizes corresponding to the number of records in each dataset. Map tiles show USGS land cover and national elevation data and are by Stamen Design, under CC BY 3.0; data by OpenStreetMap, under ODbL; figure rendered using R’s ggmap (Kahle & Wickham, 2013)
FIGURE 3
FIGURE 3
Distribution of COSORE datasets (black markers) in global climate space (WorldClim 2, Fick & Hijmans, 2017) of mean annual temperature (MAT) versus mean annual precipitation (MAP). Background colours indicate the number of half‐degree grid cells with each particular MAT–MAP combination. Inset plot shows the same points in Whittaker biome space (Ricklefs, 2008)
FIGURE 4
FIGURE 4
Flux observations, by IGBP (defined in Table 1), over time. Each square represents 5,000 observations, with categories of <5,000 observations rounded up so that they occupy a single square
FIGURE 5
FIGURE 5
Temporal density of COSORE datasets, by latitude of the observational site
FIGURE 6
FIGURE 6
Number of observations by day of year, for northern and southern hemisphere and by gas (CO2 or CH4), in the current COSORE datasets; the database currently has no CH4 data from the Southern hemisphere (bottom left)
FIGURE 7
FIGURE 7
Temporal resolution (time interval between successive measurements, minutes; note logarithmic scale of x‐axis) of COSORE data
FIGURE 8
FIGURE 8
Distribution of CO2 fluxes in COSORE datasets, by IGBP classification (cf. Table 1). For visual clarity this figure excludes fluxes <−1 and >10 µmol m−2 s−1 (210,752 observations, 2.6% of the data). Number of datasets (sites) making up data is given in parentheses after IGBP abbreviations in each panel
FIGURE 9
FIGURE 9
Distribution of CH4 fluxes in COSORE datasets, by IGBP classification (cf. Table 1). For visual clarity this figure excludes some extreme values (18,719 observations or 4.5% of the data). Number of datasets (sites) making up data is given in parentheses after IGBP abbreviations in each panel. Positive values are emissions to the atmosphere, and negative values uptake by the soil

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