Geoderma最新文献

{"title":"Decadal warming-induced changes in abiotic factors and multitrophic diversity drive soil multifunctionality in an alpine meadow","authors":"Tianyang Zhou ,&nbsp;Luming Ding ,&nbsp;Xiaoyue Yin ,&nbsp;Subinuer Wubuli ,&nbsp;Jingying Feng ,&nbsp;Changting Wang ,&nbsp;Pengfei Wu ,&nbsp;Allan Degen","doi":"10.1016/j.geoderma.2024.117035","DOIUrl":"10.1016/j.geoderma.2024.117035","url":null,"abstract":"<div><div>Climate warming can be detrimental to biodiversity and ecosystem multifunctionality. Numerous studies have examined the effect of warming on ecosystem multifunctionality; however, little is known about how long-term warming affects ecosystem multifunctionality and its seasonal dynamics. Here, we determined the effects of long-term (10 years) <em>in-situ</em> soil warming on multitrophic diversity (plants, soil bacteria, soil fungi, arthropods, and nematodes) and soil multifunctionality in an alpine meadow. The effects of warming on multitrophic diversity were inconsistent, showing a positive effect on soil microbial diversity, including bacterial diversity and fungal diversity, in the upper layer (0–10 cm), a negative effect on plant diversity, and no effect on soil fauna diversity in either the upper (0–10 cm) or lower soil layers (10–20 cm). Warming had a minor effect on soil multifunctionality, and reduced seasonal differences in soil multifunctionality in upper soil layers, but expanded the differences in the lower soil layers. Based on structural equation models, both abiotic factors (soil water content and soil pH) and biotic factors (microbial diversity and fauna diversity) jointly influenced soil multifunctionality, with abiotic factors having a greater effect than biotic factors. The findings provide insights in the important effects of long-term warming on seasonal dynamics of soil multifunctionality, and the crucial role of multitrophic diversity for maintaining the sustainable development of the alpine ecosystem under climate warming.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117035"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the compression properties of Gravel-bearing forest soil in northeast China’s seasonally frozen regions under Freeze-thaw cycles and varying gravel content","authors":"Yuan Zhou ,&nbsp;Shufa Sun ,&nbsp;Yue Xu ,&nbsp;Dong Ding ,&nbsp;Zongxu Li ,&nbsp;Zian Ding ,&nbsp;Can Xu","doi":"10.1016/j.geoderma.2024.117050","DOIUrl":"10.1016/j.geoderma.2024.117050","url":null,"abstract":"<div><div>Due to climate change, human activities and natural disturbances in high-latitude permafrost and seasonally frozen areas are gradually increasing, attracting more attention from scholars. However, research primarily focuses on soil biology and chemistry in these regions, with limited exploration of their mechanical properties, especially compression properties. This study aims to evaluate the effects of gravel content and freeze–thaw (F-T) cycles on the compression properties of coarse-grained layered forest soil from northeast China’s seasonally frozen regions, with the goal of predicting the soil’s compressive changes under heavy mechanical loads. Specifically, using uniaxial confined compression tests (UCCT) on 252 disturbed soil samples (including two soil layers: AB and B_hs; six gravel contents; and seven F-T cycles), three characteristic compression coefficients—precompression stress (σ_pc), compression index (C_c), and swelling index (C_s)—were measured. Additionally, scanning electron microscopy (SEM) was used to analyze the mesostructure evolution of coarse-grained gravel-bearing soil. Volume changes of samples were measured after 15F-T cycles with varying gravel contents. Results indicate non-linear effects of gravel content and F-T cycles on σ_pc. Gravel content below 50% positively influences σ_pc, while content above 50% increases soil pore content, decreasing σ_pc. C_c and C_s exhibit an approximately negative correlation with gravel content and initially increase followed by a decrease with more F-T cycles. Moreover, the σ_pc and C_c of the AB layer are higher than those in the B_hs layer, likely due to differences in clay and organic carbon contents. Notably, the observed trends differ from previous studies on other soil types such as farmland and paddy fields. This study fills a gap in understanding the compression characteristics of layered gravel-bearing forest soil in seasonally frozen regions, providing valuable insights for evaluating soil compression in both seasonally frozen and permafrost regions, and understanding mechanical vehicle-soil interactions. It also lays the theoretical groundwork and provides data support for constructing compression models of layered gravel-bearing forest soil.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117050"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global patterns and influencing factors of Mn accumulation in litter at different decomposition stages—A synthesis","authors":"Yaoyi Zhang,&nbsp;Fuzhong Wu,&nbsp;Kai Yue,&nbsp;Xiangyin Ni,&nbsp;Ji Yuan,&nbsp;Xinyu Wei,&nbsp;Xinying Zhang","doi":"10.1016/j.geoderma.2024.117048","DOIUrl":"10.1016/j.geoderma.2024.117048","url":null,"abstract":"<div><div>Manganese (Mn) is an essential cofactor for lignin-degrading enzymes and crucial for nutrient cycling and ecosystem functions. During litter decomposition, Mn may accumulate to fulfill the microbial demand for degrading recalcitrant substances such as lignin, which is reflected in the relative increase in Mn in decomposing litter compared with its initial amount. However, a global-scale quantification of the patterns and factors influencing Mn behavior at different decomposition stages has not been conducted. Thus, we systematically synthesized 1,466 observations from 53 publications to assess the global patterns and influencing factors of Mn accumulation in litter across various stages of decomposition. Our findings are as follows: (1) Mn primarily accumulated during litter decomposition on a global scale, despite some variability among stages. Notably, Mn accumulation was lower in the early decomposition stage (&lt;40 % mass loss) than in the intermediate and late stages. (2) Litter quality and soil properties were the primary factors influencing Mn accumulation in litter throughout most of the decomposition process, and climatic conditions were significantly correlated with Mn accumulation only in the intermediate stage (40–60 % mass loss). (3) During the early stage of decomposition (20–40 % mass loss), Mn accumulation in litter was significantly influenced by ecosystem and vegetation types, with higher accumulation observed in wetland litter than in upland litter and in tree litter than in shrub litter. Our study quantitatively synthesizes the global patterns and influencing factors of Mn accumulation in litter across different decomposition stages, thus enhancing our understanding of global Mn cycling and litter decomposition processes across different ecosystems and vegetation types. Furthermore, these findings highlight the necessity to incorporate Mn dynamics into global models of litter decomposition dynamics.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117048"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Earthworms regulate soil microbial and plant residues through decomposition","authors":"Jiahui Liao ,&nbsp;Juanping Ni ,&nbsp;Xiaoming Zou ,&nbsp;Han Y.H. Chen ,&nbsp;Manuel Delgado-Baquerizo ,&nbsp;Yuanyuan Li ,&nbsp;Tingting Ren ,&nbsp;Ke Shi ,&nbsp;Honghua Ruan","doi":"10.1016/j.geoderma.2024.117040","DOIUrl":"10.1016/j.geoderma.2024.117040","url":null,"abstract":"<div><div>Earthworms are keystone regulators of carbon exchange between terrestrial ecosystems and the atmosphere. However, exactly how earthworms regulate the composition of microbial and plant-derived carbon in soil organic matter remains poorly understood. Here we conducted a microcosm experiment with two species of endogeic earthworms (<em>Drawida gisti</em> and <em>Metaphire guillelmi</em>) to investigate their effects on cellular and extracellular-microbial residues versus fast and slow-decaying plant materials. We found that both species of earthworms reduced microbial residues (amino sugars or the protein content of extracellular polymeric substances (EPS)) and facilitated the decomposition of microbial residues rather than their formation. Neither earthworm species affected slow-decaying plant residues (lignin phenols). However, their effects on the fast-decaying fraction of plant residues (particulate organic matter (POM)) depended on the earthworm species. Principal component analysis (PCA) revealed that earthworms mediated two gradients between microbial and plant residues. The first gradient was between the nitrogenous fraction of microbial residues (e.g., amino sugars and EPS-protein) versus slow-decaying plant lignin, while the second gradient was between the fast-decaying POM versus EPS-polysaccharide. Our results suggest that earthworms play vital roles in mediating plant and microbial residue fractions in soil through their multifaceted mechanisms in regulating the chemical composition of organic carbon, and in understanding biological control of the global soil carbon cycle.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117040"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing soil fungal diversity under different sampling schemes in conjunction with remote sensing technologies in a subtropical forest","authors":"Wanwan Yu ,&nbsp;Hua Xing ,&nbsp;Chunchun Wang ,&nbsp;Xinyue Cui ,&nbsp;Xian Wu ,&nbsp;Yu Liu","doi":"10.1016/j.geoderma.2024.117058","DOIUrl":"10.1016/j.geoderma.2024.117058","url":null,"abstract":"<div><div>Fungi, serving as real-time bioindicators to environmental changes and stressors, are crucial for effective forest conservation and management practices under ongoing global change. However, the large-scale assessment of soil fungi still encounters challenges in striking a balance between the extensive sampling costs and the limited accuracy of minimal sampling. In this study, we analyzed 1,606 soil samples collected from 625 quadrats (20 m × 20 m) within a 25-ha subtropical forest dynamic plot in East China. Our primary objective was to explore the impact of different sampling schemes, in conjunction with remote sensing (RS) technologies, on the interpolation of soil fungal diversity using Ordinary Kriging (OK) and Co-kriging (CoK) models. Our findings suggested that a sampling scheme including points at 0 m (the base points) and 8 m within each quadrat, totaling to 26 points/ha, would be a sufficient scheme. This scheme with OK model yielded comparable results to those of more intensive schemes (at 0, 2, 5 and 8 m), but required the fewest sampling points. Upon incorporating each RS variable separately into the CoK models, including two vegetation indices (normalized difference vegetation index and transformed chlorophyll absorption ratio index 2), three terrain attributes (Elevation, Aspect and Slope), and the synthesis of these RS variables, the accuracy of the predicted results was further improved for each sampling scheme. By leveraging high-precision soil DNA sequencing in conjunction with cost-effective RS technologies, this study proposes a rapid and affordable approach for monitoring soil fungal diversity on a large scale. This will facilitate data collection for understanding responses of forest soil fungi to ongoing global change.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117058"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of thermal conductivity of frozen soils from basic soil properties using ensemble learning methods","authors":"Xinye Song ,&nbsp;Sai K. Vanapalli ,&nbsp;Junping Ren","doi":"10.1016/j.geoderma.2024.117053","DOIUrl":"10.1016/j.geoderma.2024.117053","url":null,"abstract":"<div><div>Thermal conductivity is one of the important properties required for understanding the frozen soils behavior. There are several models available in the literature for the prediction of thermal conductivity of frozen soils based on the proportions of unfrozen water, ice, gas, and soil particles. In this study, two ensemble learning methods-based models; namely, the Random Forest (RF) model and the Least Squares Boosting (LSB) model, are extended to estimate the thermal conductivity of frozen soils. These models utilize basic soil properties as input parameters that include water content, dry density, temperature, and fractions of gravel, sand, silt, and clay, can be measured easily, or determined. Additionally, seven widely used thermal conductivity models, referred to as the traditional models for frozen soils, were evaluated. Both the RF and LSB models, as well as the traditional models, were assessed using data of 823 tests derived from 43 soils with different textures that were gathered from the literature. The results highlight that the traditional models have their strengths and limitations in terms of their use for different types of soils. In contrast, the proposed ensemble learning methods-based models provide higher prediction accuracy compared to the traditional models and can be applied to all soil types and temperature ranges. Furthermore, estimation from the ensemble learning methods-based models can be used to provide probability of multi-dimensional analysis of frozen soils.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117053"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil aggregate stability index independent from pre-stress aggregate size distribution: A test from soils affected by the water level fluctuation in the Three Gorges Reservoir, China","authors":"Gratien Nsabimana ,&nbsp;Yuhai Bao ,&nbsp;Xiubin He ,&nbsp;Jean de Dieu Nambajimana","doi":"10.1016/j.geoderma.2024.117055","DOIUrl":"10.1016/j.geoderma.2024.117055","url":null,"abstract":"<div><div>Soil aggregate stability measurement is essential to determine soil health status under various conditions. The Mean Weight Diameter (MWD) is the most applied index to express aggregate stability particularly for wet and dry sieving. However, the MWD could generally present results affected by pre-stress aggregate size distribution when remained aggregates after stress are considered for calculation. Therefore, the objective of the present study was to eliminate the similarities between the MWD results and pre-stress aggregate size distribution, which largely affects treatments differentiation. Samples from 145-160 m (lower), 160–169 m (middle), and 169–175 m (upper) elevations differently affected by the Water Level Fluctuation in Three Gorges Reservoir (TGR) and control (&gt;175 m) were exposed to wet shaking stress. Aggregates remained at each sieve opening, aggregates disintegrated/passed through the sieve opening, and small macroaggregates and microaggregates accumulated were recorded. These aggregates were used to determine and compare two indexes (1) using remained aggregates (MWD) and (2) using disintegrated/accumulated aggregates (MWD<em>_d/a</em>) based on the differences among treatments. The results for both pre-stress aggregates and remained aggregates after stress were showed consistent significant differences (p &lt; 0.05) between upper and control elevations. This gives indication that aggregates remained after stress strongly depend on pre-stress aggregate size distribution. As the MWD was calculated from remained aggregates, the identified difference between upper and control elevations for this index could also confirm its dependence to pre-stress aggregates distribution. Contrary, disintegrated and accumulated aggregates showed non-significant differences between upper and control elevations. This non-significant and significant differences between upper and control elevations for disintegrated and pre-stress aggregates suggest a non-dependence condition. Similarly, the upper and control elevations showed no significant differences in MWD<em>_d/a</em>. This substantially informs that this index is independent from pre-stress aggregates distribution because it was entirely calculated from disintegrated aggregates. Higher aggregate stability was indicated by high MWD, with values ranging from 1.41 to 6.24 mm. On the other hand, higher stability was expressed by lower values of the MWD<em>_d/a</em>, with the values varying between 3.87 and 0.5 mm. Overall, the present study evidenced the major advantage of considering the disintegrated/accumulated than remained aggregates in calculating unbiased MWD index for aggregate stability.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117055"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-supervised learning of Vision Transformers for digital soil mapping using visual data","authors":"Paul Tresson ,&nbsp;Maxime Dumont ,&nbsp;Marc Jaeger ,&nbsp;Frédéric Borne ,&nbsp;Stéphane Boivin ,&nbsp;Loïc Marie-Louise ,&nbsp;Jérémie François ,&nbsp;Hassan Boukcim ,&nbsp;Hervé Goëau","doi":"10.1016/j.geoderma.2024.117056","DOIUrl":"10.1016/j.geoderma.2024.117056","url":null,"abstract":"<div><div>In arid environments, prospecting cultivable land is challenging due to harsh climatic conditions and vast, hard-to-access areas. However, the soil is often bare, with little vegetation cover, making it easy to observe from above. Hence, remote sensing can drastically reduce costs to explore these areas. For the past few years, deep learning has extended remote sensing analysis, first with Convolutional Neural Networks (CNNs), then with Vision Transformers (ViTs). The main drawback of deep learning methods is their reliance on large calibration datasets, as data collection is a cumbersome and costly task, particularly in drylands. However, recent studies demonstrate that ViTs can be trained in a self-supervised manner to take advantage of large amounts of unlabelled data to pre-train models. These backbone models can then be finetuned to learn a supervised regression model with few labelled data.</div><div>In our study, we trained ViTs in a self-supervised way with a 9500 km² satellite image of dry-lands in Saudi Arabia with a spatial resolution of 1.5 m per pixel. The resulting models were used to extract features describing the bare soil and predict soil attributes (pH H₂O, pH KCl, Si composition). Using only RGB data, we can accurately predict these soil properties and achieve, for instance, an RMSE of 0.40 ± 0.03 when predicting alkaline soil pH. We also assess the effectiveness of adding additional covariates, such as elevation. The pretrained models can as well be used as visual features extractors. These features can be used to automatically generate a clustered map of an area or as input of random forests models, providing a versatile way to generate maps with limited labelled data and input variables.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117056"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linking land value to indicators of soil quality and land use pressure","authors":"John J. Drewry ,&nbsp;Stephen J. McNeill ,&nbsp;Richard W. McDowell ,&nbsp;Richard Law ,&nbsp;Bryan A. Stevenson","doi":"10.1016/j.geoderma.2024.117054","DOIUrl":"10.1016/j.geoderma.2024.117054","url":null,"abstract":"<div><div>Soil quality is used to assess the soil’s ability to maintain ecological and environmental quality as well as agricultural productivity. A unique indicator associated with land use pressure is agricultural land value. Because land value is assessed at a property scale and regularly updated, we considered land value to be a good proxy for agricultural intensification. We therefore tested whether a relationship exists between land value per hectare, point-scale soil quality, other land pressure indicators (stock numbers, dominant land use), and catchment characteristics, as this has not been tested previously. We used soil quality from a national soil quality monitoring dataset, and land pressure indicators across 192 catchments (31% of land area) in New Zealand. We tested an array of models with the random forest model exhibiting the best goodness-of-fit metrics. The most important explanatory variable in predicting land valuation per hectare in the random forest model was catchment elevation (mean decrease in the mean square error; 0.92), followed by catchment potential evapotranspiration (0.78). Similarly, the fraction of dairy (0.28) and arable (0.27) land use had a relatively important effect, as did soil pH (0.32), the C:N ratio (0.31), and carbon concentration (0.30). We conclude that that land value per hectare has a well-defined relationship with land use and some soil quality measures, though expressing soil quality data at a catchment scale presented some challenges. Although the relationship was complicated, this study indicates that further work to determine if land value could act as an integrating proxy for land intensification is warranted.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117054"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In situ soil moisture and thermal properties estimated using a dual-probe heat-pulse","authors":"Jie Liu ,&nbsp;Bin Shi ,&nbsp;Meng-Ya Sun ,&nbsp;Jun-Cheng Yao ,&nbsp;Ke Fang","doi":"10.1016/j.geoderma.2024.117064","DOIUrl":"10.1016/j.geoderma.2024.117064","url":null,"abstract":"<div><div><em>In situ</em> monitoring of the temporal and spatial distribution of soil moisture and thermal properties are important for studying the water and energy transport in the vadose zone. The single-probe heat-pulse method based on fiber Bragg grating technology (SPHP-FBG) has become a research focus in field monitoring because of its capability to realize quasi-distributed and real-time monitoring. However, the SPHP-FBG method can only obtain thermal conductivity. This study developed a dual-probe heat-pulse method based on FBG (DPHP-FBG). The DPHP-FBG method can measure thermal conductivity (<em>λ</em>), volumetric heat capacity (<em>C_v</em>), and thermal diffusivity (<em>k</em>). Consequently, volumetric soil water content (<em>θ</em>) can be estimated from its linear relationship with <em>C_v</em>. The accuracy of the DPHP-FBG method in the estimation of <em>C_v</em>, <em>λ</em>, and <em>θ</em> was tested under different heating duration and various soil moisture conditions. In addition, Monte Carlo simulation was performed to investigate the impact of FBG measurement errors on accuracy. Finally, a field test was conducted to verify the effectiveness of the developed DPHP-FBG system. The results show that the DPHP-FBG method allows accurate soil moisture and thermal properties estimation without soil-specific calibration. The mean errors of the <em>C_v</em> and <em>θ</em> decrease with the extended heating duration. When the heating lasts 20 s, the measured <em>C_v</em> and <em>θ</em> have mean errors of 0.02 MJ m⁻³ K⁻¹ and 0.01 m³/m³, respectively, for various moisture conditions. In the field test, the spatio-temporal distribution of soil moisture and thermal properties can be obtained in real time. Thereby, the proposed DPHP-FBG monitoring system is potential to conduct <em>in situ</em> coupled heat and soil moisture measurements at a large scale.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"450 ","pages":"Article 117064"},"PeriodicalIF":5.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}