A New Compendium of Soil Respiration Data for Africa

Epule, Terence Epule

doi:10.3390/challe6010088

Cited by 16 publications

(16 citation statements)

References 45 publications

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“…[] did not provide new field Rs records, they appended SOC values for some Rs records. Additionally, Epule [] provided field Rs records from Africa. The data of Song et al .…”

Section: Methodsmentioning

confidence: 99%

Model prediction of biome‐specific global soil respiration from 1960 to 2012

et al. 2017

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Biome-specific soil respiration (Rs) has important yet different roles in both the carbon cycle and climate change from regional to global scales. To date, no comparable studies related to global biome-specific Rs have been conducted applying comprehensive global Rs databases. The goal of this study was to develop artificial neural network (ANN) models capable of spatially estimating global Rs and to evaluate the effects of interannual climate variations on 10 major biomes. We used 1976 annual Rs field records extracted from global Rs literature to train and test the ANN models. We determined that the best ANN model for predicting biome-specific global annual Rs was the one that applied mean annual temperature (MAT), mean annual precipitation (MAP), and biome type as inputs (r 2 = 0.60). The ANN models reported an average global Rs of 93.3 ± 6.1 Pg C yr −1 from 1960 to 2012 and an increasing trend in average global annual Rs of 0.04 Pg C yr −1 . Estimated annual Rs increased with increases in MAT and MAP in cropland, boreal forest, grassland, shrubland, and wetland biomes. Additionally, estimated annual Rs decreased with increases in MAT and increased with increases in MAP in desert and tundra biomes, and only significantly decreased with increases in MAT (r 2 = 0.87) in the savannah biome. The developed biome-specific global Rs database for global land and soil carbon models will aid in understanding the mechanisms underlying variations in soil carbon dynamics and in quantifying uncertainty in the global soil carbon cycle.

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“…[] did not provide new field Rs records, they appended SOC values for some Rs records. Additionally, Epule [] provided field Rs records from Africa. The data of Song et al .…”

Section: Methodsmentioning

confidence: 99%

Model prediction of biome‐specific global soil respiration from 1960 to 2012

et al. 2017

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“…Based on the SRDB, Bond-Lamberty and Thomson (2010a, 2010b) developed boreal-, temperate-, and tropical-specific empirical models to estimate global R S and analyze how R S responds to global warming. Building on the updated R S data in the SRDB are a new compendium of R S data for Africa (Epule, 2015), as well as field R S records from China (Song et al, 2014). Using the updated data, Zhao et al (2017) estimated R S for 10 biomes across the globe using artificial neural network models.…”

Section: 1029/2018ef000937mentioning

confidence: 99%

“…For instance, Raich and Potter (1995) analyzed the heterogeneity of R S response to environmental factors within three biomes (moist biomes with no dramatic dry season, biomes with a distinct dry season, and wetlands) and created three biome-specific models to estimate R SG . Building on the updated R S data in the SRDB are a new compendium of R S data for Africa (Epule, 2015), as well as field R S records from China (Song et al, 2014). Fortunately, the number of site R S measurements has increased substantially over the past several decades, and a continuously updated annual timescale global R S database (SRDB) was developed (Bond-Lamberty & Thomsom, 2014).…”

Section: Introductionmentioning

confidence: 99%

Future Global Soil Respiration Rates Will Swell Despite Regional Decreases in Temperature Sensitivity Caused by Rising Temperature

2018

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Between 1960 and, the global soil respiration (R SG ) flux increased at a rate of 0.05 Pg C year À1 ; however, future increase is uncertain due to variations in projected temperature and regional heterogeneity. Regional differences in the sensitivity of soil respiration (R S ) to temperature may alter the overall increase in rates of R S because the R S rates of some regions may decelerate while others continue to rise. Using monthly global R S data, we modeled the relationship between R S and temperature for the globe and eight climate regions and estimated R SG between 1961and 2100 using historical and future (2015-2100) temperature data [Representative Concentration Pathways (RCP2.6 and RCP8.5)]. Importantly, our approach allowed for estimation of regional sensitivity, where respiration rates may peak or decline as temperature rises. Estimated historical R SG increase (0.05 Pg C year À1 ) was similar to the R SG increase of previous estimates. However, under the RCP8.5 scenario, which estimates approximately 3°C of warming globally, the forecasted acceleration of R SG increased to an average of 0.12 Pg C year À1 . Under RCP8.5, the temperature sensitivity of R S declined in the arid, winter-dry temperate, and tropic. These regional declines were offset by increased R S sensitivity and fluxes from the boreal and polar regions. In contrast, under RCP2.6 R SG decelerated slightly from current rates. If rising greenhouse gas emission remains unmitigated, future increases in R SG will be much faster than current and historical rates, thereby possibly enhancing future losses of soil carbon and contributing to positive feedback loops of climate change.

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“…A number of studies have synthesized the measurements of Rs at global and regional scales (Raich and Schlesinger, 1992;Raich and Potter, 1995;Raich et al, 2002;Bond-Lamberty and Thomson, 2010a;Chen et al, 2014;Epule, 2015). We added three currently available Rs databases (Bond-Lamberty and Thomson, 2014;Chen et al, 2014;Epule, 2015) together and found that the total number of Rs measurements by 2011 was 6147 globally, conducted at 1557 sites, with most of the measurements conducted in North America (but a few in Mexico), Western Europe, and East Asia (Fig.…”

Section: Spatial and Temporal Distribution Of Rs Measurementsmentioning

confidence: 99%

“…We added three currently available Rs databases (Bond-Lamberty and Thomson, 2014;Chen et al, 2014;Epule, 2015) together and found that the total number of Rs measurements by 2011 was 6147 globally, conducted at 1557 sites, with most of the measurements conducted in North America (but a few in Mexico), Western Europe, and East Asia (Fig. 2).…”

Section: Spatial and Temporal Distribution Of Rs Measurementsmentioning

confidence: 99%

Contribution of soil respiration to the global carbon equation

Shang

2016

Journal of Plant Physiology

160

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a b s t r a c tSoil respiration (Rs) is the second largest carbon flux next to GPP between the terrestrial ecosystem (the largest organic carbon pool) and the atmosphere at a global scale. Given their critical role in the global carbon cycle, Rs measurement and modeling issues have been well reviewed in previous studies. In this paper, we briefly review advances in soil organic carbon (SOC) decomposition processes and the factors affecting Rs. We examine the spatial and temporal distribution of Rs measurements available in the literature and found that most of the measurements were conducted in North America, Europe, and East Asia, with major gaps in Africa, East Europe, North Asia, Southeast Asia, and Australia, especially in dry ecosystems. We discuss the potential problems of measuring Rs on slope soils and propose using obliquely-cut soil collars to solve the existing problems. We synthesize previous estimates of global Rs flux and find that the estimates ranged from 50 PgC/yr to 98 PgC/yr and the error associated with each estimation was also high (4 PgC/yr to 33.2 PgC/yr). Using a newly integrated database of Rs measurements and the MODIS vegetation map, we estimate that the global annual Rs flux is 94.3 PgC/yr with an estimation error of 17.9 PgC/yr at a 95% confidence level. The uneven distribution of Rs measurements limits our ability to improve the accuracy of estimation. Based on the global estimation of Rs flux, we found that Rs is highly correlated with GPP and NPP at the biome level, highlighting the role of Rs in global carbon budgets.

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A New Compendium of Soil Respiration Data for Africa

Cited by 16 publications

References 45 publications

Model prediction of biome‐specific global soil respiration from 1960 to 2012

Model prediction of biome‐specific global soil respiration from 1960 to 2012

Future Global Soil Respiration Rates Will Swell Despite Regional Decreases in Temperature Sensitivity Caused by Rising Temperature

Contribution of soil respiration to the global carbon equation

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