Particulate organic carbon exports from the terrestrial biosphere controlled by erosion

Luo, Xiaoying; Bai, Xiaoyong; Tan, Qiu; Chen, Ran; Chen, Huan; Xi, Huipeng; Chen, Fei; Wu, Luhua; Li, Chao‐Jun; Zhang, Sirui; Zhong, Xin; Tian, Shuang

doi:10.1016/j.catena.2021.105815

Cited by 20 publications

(5 citation statements)

References 61 publications

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“…Research on the factors influencing CLP has mainly focused on individual natural factors such as sunshine (Gopinath et al, 2022), precipitation (Huang et al, 2017), temperature (Pan & Dong, 2018), the thickness of black soil (Gu et al, 2018), organic matter content (Lal, 2020), organic carbon (Luo et al, 2022), carbon fluxes (Ichii et al, 2005), fertilizer (Sinha et al, 2022), salinization degree (Sui et al, 2018), Differential Vegetation Index (DVI) (Franch et al, 2019), landform (Rahmanipour et al, 2014), slope (Montealegre et al, 2022), loss of biodiversity (Cowles et al, 2016), degree of mechanization (Zhu et al, 2019), and irrigation potential (Ozdogan, 2011). However, different combinations of meteorological, climate change, land degradation, and seasonal variations could have a significant combined impact on productivity (Raich et al, 1991).…”

Section: Introductionmentioning

confidence: 99%

Spatial–temporal pattern of cultivated land productivity based on net primary productivity and analysis of influencing factors in the Songhua River basin

et al. 2022

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Inefficient utilization puts the productivity of cultivated land in a low development state. The key challenge for the efficient utilization of cultivated land is to clarify how various factors affect the spatial differentiation pattern of cultivated land productivity (CLP), to improve food production. However, evaluating the impact of the intensity and direction of CLP on a large-scale is a difficulty and there is a gap in knowledge. In this study, we used net primary productivity (NPP) to calculate the productivity of cultivated land and reveal its spatial differentiation. Also, this study examined the spatio-temporal heterogeneity of CLP and determined the effect intensity and the direction of effect of various factors on productivity, using the Songhua River basin (SRB) in China as a research case. We used genetic algorithms to modify and improve a neural network model of factor dimensionality reduction, combined with path analysis, cluster analysis, and regression analysis, to identify the main factors impacting CLP, synergies between these factors, and effect intensity and direction. The results showed that: (1) the area of cultivated land in SRB decreased, but the NPP of cultivated land area increased, during 2000-2020; (2) spatially, NPP was relatively low in the middle of the basin and gradually increased towards the periphery; (3) The main positive factors were the normalized difference vegetation index (NDVI), slope, precipitation, evapotranspiration, and total nitrogen, while the main negative factors were temperature, ratio vegetation index, and total phosphorus. Individual principal factors and the synergy between these factors gave CLP different temporal and spatial heterogeneity. Collaborative management of the threshold range of various influencing factors would improve the CLP. This novel information on

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Section: Introductionmentioning

confidence: 99%

Spatial–temporal pattern of cultivated land productivity based on net primary productivity and analysis of influencing factors in the Songhua River basin

et al. 2022

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“…At the same time, the root function, distribution and population difference of vegetation all affect the rate of rock weathering carbon sink to varying degrees. In addition, the combination of terrestrial rock weathering carbon sinks and particulate organic carbon transport from land to ocean through rivers affects the redistribution of global organic carbon (Luo et al., 2022), which will help us better evidence that carbonate rock weathering has a carbon sink effect. This research needs to be discussed in detail, not just a partial correlation analysis.…”

Section: Discussionmentioning

confidence: 99%

High‐Resolution Data Sets for Global Carbonate and Silicate Rock Weathering Carbon Sinks and Their Change Trends

et al. 2022

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The Carbonate rock weathering Carbon Sink (CCS) and Silicate rock weathering Carbon Sink (SCS) play a significant role in the carbon cycle and global climate change. However, the spatial‐temporal patterns and trends of the CCS and SCS from 1950 to 2099 have not been systematically quantified. Thus, Supported by long‐term hydrometeorological data under the RCP8.5, we use the accepted Suchet and Hartmann models to determine the following. First, we found except for the difference in their weathering rates, the SCS covers 37.2 million km2 more area than the CCS. The CCS Flux (CCSF) and SCS Flux (SCSF) are 5.36 and 1.22 t/km2/yr, respectively. Similarly, the Full CCS (FCCS, 0.3 Pg/yr) is more than the Full SCS (FSCS, 0.08 Pg/yr). Furthermore, the CCS (7.01 kg/km2) and SCS (3.95 kg/km2) are in a state of overall increase. In addition, the mid‐to‐high latitudes of the northern hemisphere are aggravated by warming (0.03°C) and humidity (0.65 mm), while the decrease in runoff in the mid‐latitudes of the southern hemisphere reduces karstification. Specifically, by 2099, the CCSF in the mid‐latitudes of the southern hemisphere will decrease by 5.72%. Instead, the CCSF in the northern hemisphere and lower latitudes of the southern hemisphere will exhibit a gentle upward slope. Particularly, the peak regions of the global FCCS (65.63 Tg/yr) and FSCS (33.01 Tg/yr) are the tropical zone. In conclusion, this study contributes a high‐resolution and long‐time series CS datasets for the CCS and SCS. We provide data and a theory for solving terrestrial carbon sink loss.

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“…The global physical erosion rate is strongly affected by land‐use change, and construction on land may have a restrictive effect on physical erosion. Land‐use change is the dominant factor determining sediment yields and soil loss rates (Erskine et al, 2002; Luo et al, 2022). At present, high‐resolution Land‐Use Harmonization product data (LUH2) have been widely used.…”

Section: Methodsmentioning

confidence: 99%

High‐resolution mapping of the global silicate weathering carbon sink and its long‐term changes

Bai

Tan

et al. 2022

Global Change Biology

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Climatic and non‐climatic factors affect the chemical weathering of silicate rocks, which in turn affects the CO2 concentration in the atmosphere on a long‐term scale. However, the coupling effects of these factors prevent us from clearly understanding of the global weathering carbon sink of silicate rocks. Here, using the improved first‐order model with correlated factors and non‐parametric methods, we produced spatiotemporal data sets (0.25° × 0.25°) of the global silicate weathering carbon‐sink flux (SCSFα) under different scenarios (SSPs) in present (1950–2014) and future (2015–2100) periods based on the Global River Chemistry Database and CMIP6 data sets. Then, we analyzed and identified the key regions in space where climatic and non‐climatic factors affect the SCSFα. We found that the total SCSFα was 155.80 ± 90 Tg C yr−1 in present period, which was expected to increase by 18.90 ± 11 Tg C yr−1 (12.13%) by the end of this century. Although the SCSFα in more than half of the world was showing an upward trend, about 43% of the regions were still showing a clear downward trend, especially under the SSP2‐4.5 scenario. Among the main factors related to this, the relative contribution rate of runoff to the global SCSFα was close to 1/3 (32.11%), and the main control regions of runoff and precipitation factors in space accounted for about 49% of the area. There was a significant negative partial correlation between leaf area index and silicate weathering carbon sink flux due to the difference between the vegetation types. We have emphasized quantitative analysis the sensitivity of SCSFα to critical factors on a spatial grid scale, which is valuable for understanding the role of silicate chemical weathering in the global carbon cycle.

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Particulate organic carbon exports from the terrestrial biosphere controlled by erosion

Cited by 20 publications

References 61 publications

Spatial–temporal pattern of cultivated land productivity based on net primary productivity and analysis of influencing factors in the Songhua River basin

Spatial–temporal pattern of cultivated land productivity based on net primary productivity and analysis of influencing factors in the Songhua River basin

High‐Resolution Data Sets for Global Carbonate and Silicate Rock Weathering Carbon Sinks and Their Change Trends

High‐resolution mapping of the global silicate weathering carbon sink and its long‐term changes

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