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首页> 外文期刊>Ecological indicators >Evaluating organic carbon fractions, temperature sensitivity and artificial neural network modeling of CO_2 efflux in soils: Impact of land use change in subtropical India (Meghalaya)
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Evaluating organic carbon fractions, temperature sensitivity and artificial neural network modeling of CO_2 efflux in soils: Impact of land use change in subtropical India (Meghalaya)

机译：评估土壤中有机碳含量，温度敏感性和人工神经网络模型，研究CO_2的外流：亚热带印度（梅加拉亚邦）土地利用变化的影响

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摘要

The present study investigates the changes in land use pattern from fallow land (control) to fruit orchards on soil organic carbon (SOC) dynamics especially, organic carbon stocks, fractions, and CO2efflux. The SOC fractions such as total organic carbon (TOC), particulate organic carbon (POC), readily oxidizable carbon (ROC), non-labile carbon (CNL), microbial biomass carbon (MBC), carbon management index (CMI) and their sensitivity to land use change were the focus of this study. The organic carbon fractions showed increasing trend (19.4–46%) under fruit orchards compared to control. Furthermore, the orchard withP. persicarecorded the highest mean SOC stocks (59.4 Mg ha−1) and TOC (3.03 g 100 g−1) while orchard withC. reticulatashowed the highest ROC (6.11 g kg−1) and MBC (401 mg kg−1). Fruit orchards were characterized by high Cmic:CTOC(microbial quotient; qMIC) and POC: TOC ratios, indicating an increase in substrate availability. Furthermore, the CMI was highest underC. reticulata(226.4) followed byP. guajava(173.3), whereasP. communisshowed relatively lower value (160.5). While, upper soil layer (0–15 cm) exhibited higher organic carbon stock and fractions viz., 35.1 % and 58.3%, respectively compared to the subsurface soil (15–75 cm) in all orchards. The labile SOC fractions (POC, ROC, and MBC) showed a positively significant correlation with TOC and CO2efflux indicating that these labile fractions are the sensitive indicators of soil quality changes and improvements. Soil CO2efflux exhibited a pronounced variation corresponding to land use change with values ranging from 22.80 µg C g−1 h−1(fallow land) to 27.39 µg C g−1 h−1(P. guajava). With temperature increment from 25 to 35 °C, the soil CO2efflux increased from 55% (P. persica) to 88% (fallow) with an average increase of 72%. However, the microbial metabolic quotient (qCO2), also called as specific respiratory activity (SRA), was relatively lower (40.9 µg CO2 mg MBC−1) in orchards compared to fallow land (50.4 µg CO2 mg MBC−1). A multi-layered Artificial Neural Network model (ANN) was also developed, and the experimental CO2efflux values obtained from different land uses are in good agreement with the predicted CO2efflux. We conclude that, labile SOC fractions are highly sensitive to land use change and could be effectively used as the sensitive indicators along with CMI for land use change under mid-altitude subtropical ecosystems. In addition, fruit orchards could store more carbon thus could be a potential option to mitigate global warming.
机译：本研究调查了休耕地（控制地）到果园的土地利用方式在土壤有机碳（SOC）动力学方面的变化，特别是在有机碳储量，馏分和CO2排放量方面。 SOC分数，例如总有机碳（TOC），颗粒有机碳（POC），易氧化碳（ROC），非活性碳（CNL），微生物生物量碳（MBC），碳管理指数（CMI）及其敏感性土地利用变化是本研究的重点。与对照相比，果园中的有机碳分数显示出增加趋势（19.4–46％）。此外，果园有P。波斯菊的平均SOC储量最高（59.4 Mg ha-1）和TOC（3.03 g 100 g-1），而果园含C。网纹的ROC（6.11 g kg-1）和MBC（401 mg kg-1）最高。果园的特征在于高的Cmic：CTOC（微生物商； qMIC）和POC：TOC比，表明底物利用率增加。此外，CMI在C下最高。网纹（226.4），接着是P。 guajava（173.3），而P。社区显示相对较低的值（160.5）。而在所有果园中，上层土壤层（0–15 cm）显示出较高的有机碳储量和分数，分别为表层土壤（15–75 cm）的35.1％和58.3％。不稳定的SOC组分（POC，ROC和MBC）与TOC和CO2外排量呈显着正相关，表明这些不稳定的组分是土壤质量变化和改善的敏感指标。土壤CO2流出量表现出与土地利用变化相对应的显着变化，其变化范围为22.80μggCg-1 h-1（休耕地）至27.39μggCg-1 h-1（P。guajava）。随着温度从25°C升高到35°C，土壤CO2排放量从55％（P. persica）增加到88％（fallow），平均增加72％。然而，果园的微生物代谢商（qCO2）也被称为比呼吸活动（SRA）相对较低（40.9μg/ gCO2·mg·MBC-1），相对于休耕地（50.4μg/ gCO2·mg·MBC-1）。还开发了一个多层人工神经网络模型（ANN），并且从不同土地利用获得的实验CO2外排量值与预测的CO2外排量非常吻合。我们得出的结论是，不稳定的SOC组分对土地利用变化高度敏感，可以与CMI一起有效用作中海拔亚热带生态系统土地利用变化的敏感指标。此外，果园可以储存更多的碳，因此可能是缓解全球变暖的潜在选择。

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