Data on in situ estimations of annual CH4 fluxes in forest soils worldwide
; Gyenge, Javier Enrique ; Juliarena, María Paula ; Fernandez, Maria Elena Otros responsables
Fecha
Publicador:
Consejo Nacional de Investigaciones Científicas y Técnicas
Fecha de depósito:
16/12/2024
Fecha de creación:
01/12/2019
Clasificación temática
Palabras clave
Resumen
The database contains in situ measurements of soil CH₄ fluxes in forests worldwide. This database was built using peer-reviewed papers as sources and was collected following standardized bibliographic search protocols. The database was constructed during the development of a PICT project and was part of the work conducted under a postdoctoral fellowship associated with this project. The goal of building this database was to obtain global data on methane fluxes in soils of different types of forests. In this way, we explored the environmental and anthropogenic factors that explain the variation in methane fluxes. The main interest was to identify the key factors that promote methane consumption in soils, as this is one of the greenhouse gases with the greatest relative impact on global warming. The data were used for a publication in the journal Global Change Biology.
Información Técnica
This database was compiled from two sources of peer-reviewed papers: (a) existing datasets previously compiled and published by Castaldi, Ermice, & Strumia (2006), Dutaur & Verchot (2007), Feng et al. (2020), and Ni & Groffman (2018), and (b) Scopus® (Elsevier B.V.). To expand our dataset, we searched peer-reviewed papers in Scopus using the terms: “methane” OR “CH₄” AND “soil*” AND “forest*.” Based on both sources, we identified approximately 600 potential studies published up to December 2019. From these potential studies, we selected those that met the following criteria: (a) studies with measurements of soil CH₄ fluxes using the static chamber method and gas chromatography technique; (b) studies reporting annual average soil CH₄ flux values based on at least two measurements obtained during both dry and wet seasons; and (c) studies that represent field conditions without experimental treatments (i.e., control or unmanaged plots). We excluded two studies from the 1980s because they did not explicitly include geographic location. A total of 478 observational units were collected from various forests worldwide, based on 191 peer-reviewed papers. Additionally, each observational unit was characterized with measurements of climatic, soil, and anthropogenic drivers, sourced from several references detailed in the Metadata tab of the archive.
Métodos
As studies varied in temporal frequency of the field measure-ments and presented different units (μg m−2hr −1 , g m−2day −1 , and kg ha−1year−1), we included the average values obtained from the data measured within the same year (annual average of CH4flux) and reported in tables or in the main text of the original studies, which were all standardized to kg ha−1year−1. When it was not avail-able, data were extracted from figures using Data Thief III (https:// datat hief.org/) and, then, annual average was calculated as the mean value of all measurements performed in 1 year and also standard-ized to kg ha −1year−1. When soil CH4 flux was available for more than 1 year at the same observational unit we used the mean value of reported measurements. Thus, our measurements represent the average rate of soil CH4 flux at annual scale, which is appropriate to our objective since that illustrates on average whether a site tends to be soil CH4 sink or source as well as the magnitude of these net fluxes. We checked if the tem-poral resolution would have influenced the soil CH4 flux adding the number of measurements used to estimate annual average as a fixed predictor in our statistical models. Additionally, for each observation, we extracted from the original article ancillary data such as latitude, longitude, time interval of experimental period (and standardized to months), age of plantation, time of recent wildfire, biome classification (boreal, temperate, tropical, subtropical and savannah–sparse–woodland forests), forest type (natural or plantation) and landscape position (upland or floodplain). Details about additional variables such as climate, biome, soil texture, etc., are clarified in the original article associated with this data source.
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