Spatial and Temporal Variations in Soil Organic Matter and Their Influencing Factors in the Songnen and Sanjiang Plains of China (1984–2021) DOI Creative Commons

Hongju Zhao,

Chong Luo,

Depiao Kong

et al.

Land, Journal Year: 2024, Volume and Issue: 13(9), P. 1447 - 1447

Published: Sept. 6, 2024

Soil organic matter (SOM) is essential for assessing land quality and enhancing soil fertility. Understanding SOM spatial temporal changes crucial sustainable management. This study investigates the variations influencing factors of content in Songnen Plain (SNP) Sanjiang (SJP) Heilongjiang Province, China, based on high-precision SOC data (RMSE = 4.84 g/kg−1, R2 0.75, RPIQ 2.43) from 1984 to 2021, with geostatistical analyses geodetector models. aims quantitatively reveal compare long-term characteristics their across these two plains. The results show that both plains has decreased over past 37 years. In SNP, average 48.61 g/kg 45.6 g/kg, representing a reduction 3.01 or 6.10% decrease; spatially northeast southwest, covering 63.1% area. SJP, declined 48.41 44.31 decrease 4.1 an 8.50% no pronounced pattern was observed, but declining area comprises 67.49%. Changing hotspots are concentrated southern SNP central northwestern showing clear heterogeneity counties. Geodetector model analysis indicates annual mean temperature as primary driver SNP; while elevation main combined explanatory power multiple surpasses individual ones. There positive correlation between policy protection positively influences These findings provide insights into differential SJP.

Language: Английский

Geo-spatial analysis of urbanization and environmental changes with deep neural networks: Insights from a three-decade study in Kerch peninsula DOI Creative Commons
Денис Кривогуз

Ecological Informatics, Journal Year: 2024, Volume and Issue: 80, P. 102513 - 102513

Published: Feb. 7, 2024

This study presents a comprehensive analysis of land use and cover (LULC) changes on the Kerch Peninsula over last thirty years, utilizing advanced satellite data spatial modeling techniques. The research used Landsat 5, 7 8 images to capture intricate dynamics LULC from 1990 2020. A quantitative approach was adopted, involving convolutional neural networks (CNN) for enhanced classification accuracy. methodology allowed detailed precise identification various classes, revealing significant trends transformations in region's landscape. incorporated this exploration both large-scale patterns localized changes, providing insights into drivers consequences dynamics. statistical revealed notable increase urbanized areas, coupled with decline natural ecosystems such as forests wetlands. These reflect impact sustained urban growth agricultural expansion, underscoring need informed management conservation strategies. findings contribute understanding urbanization processes their ecological implications, valuable guidance sustainable regional planning environmental protection.

Language: Английский

Citations

18
Variability analysis of soil organic carbon content across land use types and its digital mapping using machine learning and deep learning algorithms DOI
Mounir Oukhattar, Sébastien Gadal,

Yannick Robert

et al.

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(5)

Published: April 10, 2025

Language: Английский

Citations

0
Variation of Soil Organic Carbon Stocks with Land Use and Elevation Gradient on the Eastern Slopes of Mount Kenya DOI
Brian Rotich, Ádám Csorba, Caleb Melenya Ocansey

et al.

Published: Jan. 1, 2024

Understanding the influence of land use and elevation gradient on soil organic carbon stocks (SOCS) is essential for effective management, sustainable agricultural practices, mitigation climate change impacts. This research aimed to explore how types gradients SOCS eastern slopes Mount Kenya. Using a stratified systematic sampling approach, 68 samples were collected from 0–20 20–40 cm depths, representing forestland farmland, across six ranging 1000 2650 m above sea level (a.s.l.). Soil analysed bulk density (BD), pH, texture, concentration (SOC), total nitrogen (TN) using standard methods. The results showed that significantly higher (p<0.001) in forest compared farms. ranged 87.40 168.75 Mg ha−1 at 38.31 148.58 depths. On other hand, farmland depths range 21.86 50.38 17.27 49.84 ha−1, respectively. generally exhibited declining trend with increasing depth both types. Elevation-wise, mean aggregated 0–40 29.21 ± 5.6 lower (1000–1200 a.s.l) 141.75 17.4 upper (2350–2650 a.s.l). There was an increase (r² = 0.78). A significant positive correlation observed among studied parameters between SOCS, SOC TN. In contrast, negative existed BD, temperature outcomes this investigation provide foundational data monitoring Kenya ecosystem. It serves as basis future assessments management strategies promote health enhance measures.

Language: Английский

Citations

1
Changes in Soil Organic Matter Associated with Land Use of Arenosols from Southern Botswana DOI Creative Commons

Donald L. Kgathi,

M. B. M. Sekhwela,

Gonzalo Almendros

et al.

Agronomy, Journal Year: 2024, Volume and Issue: 14(8), P. 1869 - 1869

Published: Aug. 22, 2024

The effect of land use on sandy soils southern Botswana was carried out by comparing the composition and properties soil organic matter. Non-disturbed disturbed were sampled from savanna ecosystems (Central District Kweneng District). biodegradability matter evaluated incubation in laboratory. Humic fractions quantified humic acids analyzed visible infrared spectroscopy. results indicate that continued disturbance, whether due to grazing or subsistence farming, has resulted small yet significant changes concentration available nutrients soil. Nevertheless, substantial could be established C/N ratio, acid/fulvic acid structural characteristics acids. increased aromaticity (visible IR spectroscopies) following disturbance suggests biogeochemical activity and/or impact abiotic processes (such as periodic fires) selectively removing aliphatic constituents. overall low potential fertility, sustainable preservation which depends more features related quality than total amount matter, shows aromatization parallel its degree association with mineral fraction.

Language: Английский

Citations

0
Spatial and Temporal Variations in Soil Organic Matter and Their Influencing Factors in the Songnen and Sanjiang Plains of China (1984–2021) DOI Creative Commons

Hongju Zhao,

Chong Luo,

Depiao Kong

et al.

Land, Journal Year: 2024, Volume and Issue: 13(9), P. 1447 - 1447

Published: Sept. 6, 2024

Soil organic matter (SOM) is essential for assessing land quality and enhancing soil fertility. Understanding SOM spatial temporal changes crucial sustainable management. This study investigates the variations influencing factors of content in Songnen Plain (SNP) Sanjiang (SJP) Heilongjiang Province, China, based on high-precision SOC data (RMSE = 4.84 g/kg−1, R2 0.75, RPIQ 2.43) from 1984 to 2021, with geostatistical analyses geodetector models. aims quantitatively reveal compare long-term characteristics their across these two plains. The results show that both plains has decreased over past 37 years. In SNP, average 48.61 g/kg 45.6 g/kg, representing a reduction 3.01 or 6.10% decrease; spatially northeast southwest, covering 63.1% area. SJP, declined 48.41 44.31 decrease 4.1 an 8.50% no pronounced pattern was observed, but declining area comprises 67.49%. Changing hotspots are concentrated southern SNP central northwestern showing clear heterogeneity counties. Geodetector model analysis indicates annual mean temperature as primary driver SNP; while elevation main combined explanatory power multiple surpasses individual ones. There positive correlation between policy protection positively influences These findings provide insights into differential SJP.

Language: Английский

Citations

0