Geoderma Regional, Год журнала: 2023, Номер 36, С. e00745 - e00745
Опубликована: Дек. 19, 2023
Язык: Английский
Geoderma Regional, Год журнала: 2023, Номер 36, С. e00745 - e00745
Опубликована: Дек. 19, 2023
Язык: Английский
Remote Sensing of Environment, Год журнала: 2023, Номер 300, С. 113911 - 113911
Опубликована: Ноя. 16, 2023
Язык: Английский
Процитировано
30Ecological Indicators, Год журнала: 2023, Номер 155, С. 110988 - 110988
Опубликована: Сен. 26, 2023
Soil organic carbon (SOC) is an important pool in the global cycle, playing a vital role moderating atmospheric CO2 concentrations. largest terrestrial ecosystems and, as basic unit of soil structure, aggregates are key to protecting pools. However, influence aggregate particle size, SOC distribution, and contribution different sizes still unclear, particularly under land use types. In this study, samples were collected from five types (slope farmland (SF), forest (FL), grassland (GL), shrubland (SL), terraced field (TF)) typical small watershed Loess Plateau, China. We analyzed composition, stability after dry wet sieving, content aggregates, effects on distribution SOC. The results showed that, surface (0 ∼ 20 cm) water-stable relatively stable, FL, mean weight diameter (MWD) value was 2.16 mm. Deep (40 60 non-water stable more GL optimal, MWD 3.94 total nitrogen (TN) significantly correlated with indicators (p < 0.01). (0.25 2 mm) highest lowest microaggregates (<0.25 use. carbon/nitrogen (C/N) ratio higher SF (the C/N 23.17) 31.04) than other uses 0.01) 20–40 cm layer. soil, contributed>50% TF. deep all made rate at 57%. These findings indicate that sequestration study area can be improved by combination appropriate management ecological construction increase strengthen fixation protection SOC, reduce emissions soil.
Язык: Английский
Процитировано
22Geoderma Regional, Год журнала: 2024, Номер 36, С. e00770 - e00770
Опубликована: Янв. 26, 2024
Язык: Английский
Процитировано
5Land, Год журнала: 2024, Номер 13(7), С. 915 - 915
Опубликована: Июнь 23, 2024
Synthesizing bare soil pictures in regions with complex vegetation is challenging, which hinders the accuracy of predicting organic carbon (SOC) specific areas. An SOC prediction model was developed this study by integrating convolutional neural network and long short-term memory (CNN-LSTM) algorithms, taking into consideration soil-forming factors such as climate, vegetation, topography Hainan. Compared common algorithmic models (random forest, CNN, LSTM), based on CNN-LSTM algorithm achieved high (R2 = 0.69, RMSE 6.06 g kg−1, RPIQ 1.96). The predicted that content ranged from 5.49 to 36.68 Hainan central southern parts region values surrounding areas low values, roughly distributed follows: mountainous flat Among four models, outperformed LSTM, random forest terms R2 11.3%, 23.2%, 53.3%, respectively. demonstrates its applicability shows great potential where obtaining sample data challenging influenced multiple interacting factors. Furthermore, it significant for advancing broader field digital mapping.
Язык: Английский
Процитировано
4Applied Sciences, Год журнала: 2025, Номер 15(3), С. 1006 - 1006
Опубликована: Янв. 21, 2025
Land use patterns significantly influence the quantity and composition of litter in soil humus layers, thereby affecting dynamics organic carbon. However, differences labile carbon fractions sequestration index under different land patterns, as well their impact on storage layers mollisols—without migration loss erosion—remain unclear. Labile is classified into such dissolved carbon, easily oxidized particulate microbial biomass which are identified through chemical extraction methods. This study investigates long-term dynamics, pools, KOS, CPMI mollisols across five treatments: SC (continuous soybean cultivation), MC maize MSR (maize–soybean rotation), GB (grass belt), FB (forest belt). It also selects three depths (0–20 cm, 20–40 40–60 cm) over an 11-year period for analysis. The results indicate that (EOC, POC, DOC, MBC), decrease with depth, while KOS increases. Non-tillage treatments enhance SOC accumulation exhibiting highest content, surpassing GB, MC, SC, by 22.88%, 52.35%, 60.64%, 80.12%, respectively. can fractions, aligning observed trends treatment optimal. Additionally, these increase CPMI, improving stability. To minimize loss, should encourage conversion farmland to grassland forest, recommended optimal strategy protection sustainable development soils long term. approach significant understanding cycle, rationally planning strategies, providing a reference enhancing quality ecosystem sinks.
Язык: Английский
Процитировано
0Agriculture, Год журнала: 2025, Номер 15(3), С. 339 - 339
Опубликована: Фев. 4, 2025
The accurate prediction of soil organic matter (SOM) content is important for sustainable agriculture and effective management. This task particularly challenging due to the variability in factors influencing SOM distribution across different cultivated land types, as well site-specific responses remote sensing data environmental covariates, especially black region northeastern China, where exhibits significant spatial variability. study evaluated variations on importance imagery covariates zones. A total 180 samples (0–20 cm) were collected from Youyi County, Heilongjiang Province, multi-year synthetic bare images 2014 2022 (focusing April May) acquired using Google Earth Engine. Combining three types such drainage, climate topography, area was categorized into dry field paddy field. Then, model constructed random forest regression method accuracy strategies by 10-fold cross-validation. findings indicated that, (1) overall analysis, combining drainage variables May could attain highest accuracy, ranked follows: (RS) > (CLI) (DN) Topography (TP). (2) Zonal analysis conducted with a high degree precision, evidenced an R2 0.72 impressively low RMSE 0.73%. time window monitoring More specifically, optimal frames dryland identified May, while those fields concentrated May. (3) In addition, diverse observed vary types. regions characterized intricate fields, contributions assumed heightened importance. Conversely, featuring flat terrain, roles played more substantial role outcomes. These underscore selecting appropriate inputs improving accuracy.
Язык: Английский
Процитировано
0Applied Soil Ecology, Год журнала: 2025, Номер 209, С. 106036 - 106036
Опубликована: Март 23, 2025
Язык: Английский
Процитировано
0CATENA, Год журнала: 2024, Номер 249, С. 108633 - 108633
Опубликована: Дек. 5, 2024
Язык: Английский
Процитировано
2Sustainability, Год журнала: 2024, Номер 16(13), С. 5403 - 5403
Опубликована: Июнь 25, 2024
It is important to ensure the ratio of stable and labile soil organic carbon (SOC) compounds in as this influences ecosystem functions sustainability management. The aim investigation was determine changes SOC quality improvement Arenosol after conversion arable land natural agricultural use. use types included pine afforestation (PA), uncultivated abandoned (UAL), unfertilised fertilised cropland (CLunf, CLf), grassland (GRunf, GRf). To assess lability (OC) compounds, levels mobile humic substances (MHSs), acids (MHAs), fulvic (MFAs), active C pool (POXC), water-soluble (WEOC) were determined. found that faster OC accumulation occurs PA than CLf, somewhat slower uses (GRf UAL). As amount increased, more MHS formed. A significant increase their quantity (+92.2%) CRf UAL (+51.5–52.7%). application mineral fertilisers promoted formation MHSs CLf GRf. PA, GRunf, GRf soils had suitable conditions for MHA (MHA/MFA > 1.3), whereas CLunf contained MFAs. POXC insensitive land-use Arenosol. After conversion, amounts significantly (p < 0.05) higher ecosystems (UAL PA) fertiliser perennial grasses CL. WEOC increased most UAL, (7.4–71.1%). sequence decrease GRf, CLunf, GRunf. decreasing order management index (CMI) different (PA GRunf Clunf) confirms occurred values (CLI) variation (CLunf show uses, matter (OM) forms are relatively less formed, which stabilises soil. CMI showed soils.
Язык: Английский
Процитировано
0IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Год журнала: 2024, Номер unknown, С. 1585 - 1589
Опубликована: Июль 7, 2024
Язык: Английский
Процитировано
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