The location- and scale- specific correlation between temperature and soil carbon sequestration across the globe

Huang, Jingyi; Minasny, Budiman; McBratney, Alex B.; Padarian, José

doi:10.1016/j.scitotenv.2017.09.136

Cited by 37 publications

(11 citation statements)

References 52 publications

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“…In our study, SOCD was correlated negatively with temperature. This result is consistent with the global changes and some studies at regional scales between 52°N and 40°S [18, 60]. In our study, a 1°C increase in temperature resulted in a 0.36% decrease of SOCD, which is similar to the 3.3% decrease of SOCD at the global level.…”

Section: Discussionsupporting

confidence: 93%

The spatio-temporal patterns of the topsoil organic carbon density and its influencing factors based on different estimation models in the grassland of Qinghai-Tibet Plateau

et al. 2019

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The grassland soils of the Qinghai-Tibet Plateau (QTP) store a large amount of organic carbon because of the cold, humid climate, and topsoil organic carbon is quite sensitive to global climate changes. However, the spatio-temporal dynamics and factors that influence the soil organic carbon (SOC) on the QTP’s grassland are not understood well. Moreover, there are few comparative analyses of different approaches to estimate the QTP’ SOC. In this study, we estimated the storage and patterns of SOC density (SOCD) using several methods, including MODIS (moderate-resolution imaging spectroradiometer) retrieval, field data and previous empirical models (Models1-4, and soil organic matter (SOM)). And their relations with aboveground biomass, soil moisture, temperature, elevation, and soil conductivity were further explored. The results showed that SOC showed a similar variation trend in the different models, in which it decreased with increasing bulk density (BD) in the topsoil at 30 cm. For meadow and steppe grasslands, Models 1, 2, and 4 showed similar estimated values of SOCD, while Model3 had a lower value than them. SOC storage in the BD 3 and SOM methods had abnormal values, while the MODIS-NDVI, BD 1, 2, and 4 methods had similar SOC stock values for meadow and steppe grassland. Moreover, meadow grassland had a higher SOC storage than did steppe grassland, with means values of 397.9×1010 kg and 242.2×1010 kg, respectively. SOCD’s spatial distribution using MODIS-NDVI method differed clearly from the empirical models, with a significant tendency for spatial variation that increased from the northwestern to southeastern regions on the QTP. Therefore, based on the values estimated and spatial variation features, the MODIS-NDVI method may be a more feasible and valid model to estimate SOC. Moreover, the mean annual SOCD values during 2000–2015 showed an increasing trend, with a higher mean value in meadow and a lower mean value in steppe. Further, SOCD was correlated significantly and positively with aboveground biomass and soil moisture, and negatively correlated with elevation and soil conductivity. Increasing temperature had negative effects on SOCD, which was consistent with the global trend. These results indicated that topsoil moisture plays a key role in SOCD spatial patterns. Our results provide valuable support for the long-term estimation of SOCD in future research on the QTP.

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Section: Discussionsupporting

confidence: 93%

The spatio-temporal patterns of the topsoil organic carbon density and its influencing factors based on different estimation models in the grassland of Qinghai-Tibet Plateau

et al. 2019

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“…SOC distribution is determined by multiple factors [ 27 ], the importance of which vary mainly with bioclimatic conditions. It is therefore hard to delineate general functions that explain the world SOC distribution using only geographical positions, although a general inverse correlation was found with average annual air temperature on a regional scale between 52° N and 40° S and a direct correlation beyond this region [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Validating the regional estimates of changes in soil organic carbon by using the data from paired-sites: the case study of Mediterranean arable lands

Schillaci

Saia

Lipani

et al. 2021

Carbon Balance Manage

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Background Legacy data are unique occasions for estimating soil organic carbon (SOC) concentration changes and spatial variability, but their use showed limitations due to the sampling schemes adopted and improvements may be needed in the analysis methodologies. When SOC changes is estimated with legacy data, the use of soil samples collected in different plots (i.e., non-paired data) may lead to biased results. In the present work, N = 302 georeferenced soil samples were selected from a regional (Sicily, south of Italy) soil database. An operational sampling approach was developed to spot SOC concentration changes from 1994 to 2017 in the same plots at the 0–30 cm soil depth and tested. Results The measurements were conducted after computing the minimum number of samples needed to have a reliable estimate of SOC variation after 23 years. By applying an effect size based methodology, 30 out of 302 sites were resampled in 2017 to achieve a power of 80%, and an α = 0.05. A Wilcoxon test applied to the variation of SOC from 1994 to 2017 suggested that there was not a statistical difference in SOC concentration after 23 years (Z = − 0.556; 2-tailed asymptotic significance = 0.578). In particular, only 40% of resampled sites showed a higher SOC concentration than in 2017. Conclusions This finding contrasts with a previous SOC concentration increase that was found in 2008 (75.8% increase when estimated as differences of 2 models built with non-paired data), when compared to 1994 observed data (Z = − 9.119; 2-tailed asymptotic significance < 0.001). This suggests that the use of legacy data to estimate SOC concentration dynamics requires soil resampling in the same locations to overcome the stochastic model errors. Further experiment is needed to identify the percentage of the sites to resample in order to align two legacy datasets in the same area.

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“…SOC distribution is determined by multiple factors (Lacoste et al, 2014), the importance of which vary mainly with bioclimatic conditions. It is therefore hard to delineate general functions that explain the world SOC distribution using only geographical position, although a general inverse correlation was found with average annual air temperature on a regional scale between 52° N and 40° S and a direct correlation beyond this region (Huang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Determination of minimum number of samples allowing to detect long term soil organic carbon changes in Mediterranean arable lands using paired-sites

Schillaci

Saia

Lipani

et al. 2021

Preprint

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Background Legacy data are unique occasions for estimating soil organic carbon (SOC) concentration changes and spatial variability, but their use can pose limitations due to the sampling schemes adopted and improvements may be needed in the analysis methodologies. When SOC changes is estimated with legacy data, the use of soil samples collected in different plots (i.e., non-aligned data) may lead to biased results. In the present work, N=302 georeferenced soil samples were selected from a regional (Sicily, south of Italy) soil database. An operational sampling approach was developed to spot SOC concentration changes from 1994 to 2017 in the same plots at the 0-30 cm soil depth and tested. Results The measurements were conducted after computing the minimum number of samples needed to have a reliable estimate of SOC variation after 23 years. By applying an effect size based methodology, 30 out of 302 sites were resampled in 2017 to achieve a power of 80%, and an a=0.05. A Wilcoxon test applied to the variation of SOC from 1994 to 2017 suggested that there was not a statistical difference in SOC concentration after 23 years (Z = -0.556; 2-tailed asymptotic significance = 0.578). In particular, only 40% of resampled sites showed a higher SOC concentration than in 2017. Conclusions This finding contrasts with a previous SOC concentration increase that was found in 2008 (75.8% increase when estimated as differences of 2 models built with non-aligned data), when compared to 1994 observed data (Z = -9.119; 2-tailed asymptotic significance < 0.001). Such a result implies that the use of legacy data to estimate SOC concentration dynamics requires soil resampling in the same locations to overcome the stochastic model errors. Further experiment is needed to identify the percentage of the sites to resample in order to align two legacy datasets in the same area.

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The location- and scale- specific correlation between temperature and soil carbon sequestration across the globe

Cited by 37 publications

References 52 publications

The spatio-temporal patterns of the topsoil organic carbon density and its influencing factors based on different estimation models in the grassland of Qinghai-Tibet Plateau

The spatio-temporal patterns of the topsoil organic carbon density and its influencing factors based on different estimation models in the grassland of Qinghai-Tibet Plateau

Validating the regional estimates of changes in soil organic carbon by using the data from paired-sites: the case study of Mediterranean arable lands

Determination of minimum number of samples allowing to detect long term soil organic carbon changes in Mediterranean arable lands using paired-sites

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