Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117662
Limin Bai , Chao Song , Mengfan Li , Lei Yang , Xin Wang , Qiqian Wu , Jianxiao Zhu
Mixed-species litter modifies decomposition rates through complex interplays driven by species composition and functional traits of litter. However, there remains no consensus on how ecosystem type, climate, species traits, and decomposition stage jointly influence the direction and magnitude of litter mixing effects. We conducted a global meta-analysis of 1,258 effect sizes from 91 field studies (1989–2024) to assess how ecosystem type, climate, and species traits influence mixed-species litter decomposition rates across different stages of decomposition. Decomposition rates of mixed-species litter were 4.4 % significantly higher than those of the mono-species litter. Synergistic effects were most pronounced in temperate and forest ecosystems. These effects were generally observed after 180 days, and peaked between 360 and 720 days, but they declined as decomposition progressed, often shifting to additive or antagonistic effects as recalcitrant compounds accumulated. The relationship between species diversity and mixing effects was not linear, depending on specific species combinations and proportions. Phylogenetic distance and litter quality divergence between species significantly affect the mixing effect of decomposition. The mixing effects of litter decomposition are highly context-dependent and temporally dynamic. Our results provide empirical support for a dynamic, stage-dependent theory of litter mixing effects, emphasizing that their strength and direction hinge on critical decomposition phases and trait-mediated interactions. Recognizing these temporal dynamics is essential for predicting biodiversity impacts on ecosystem carbon and nutrient cycling.
{"title":"Global patterns and drivers of decomposition of mixed-species litter","authors":"Limin Bai , Chao Song , Mengfan Li , Lei Yang , Xin Wang , Qiqian Wu , Jianxiao Zhu","doi":"10.1016/j.geoderma.2025.117662","DOIUrl":"10.1016/j.geoderma.2025.117662","url":null,"abstract":"<div><div>Mixed-species litter modifies decomposition rates through complex interplays driven by species composition and functional traits of litter. However, there remains no consensus on how ecosystem type, climate, species traits, and decomposition stage jointly influence the direction and magnitude of litter mixing effects. We conducted a global meta-analysis of 1,258 effect sizes from 91 field studies (1989–2024) to assess how ecosystem type, climate, and species traits influence mixed-species litter decomposition rates across different stages of decomposition. Decomposition rates of mixed-species litter were 4.4 % significantly higher than those of the mono-species litter. Synergistic effects were most pronounced in temperate and forest ecosystems. These effects were generally observed after 180 days, and peaked between 360 and 720 days, but they declined as decomposition progressed, often shifting to additive or antagonistic effects as recalcitrant compounds accumulated. The relationship between species diversity and mixing effects was not linear, depending on specific species combinations and proportions. Phylogenetic distance and litter quality divergence between species significantly affect the mixing effect of decomposition. The mixing effects of litter decomposition are highly context-dependent and temporally dynamic. Our results provide empirical support for a dynamic, stage-dependent theory of litter mixing effects, emphasizing that their strength and direction hinge on critical decomposition phases and trait-mediated interactions. Recognizing these temporal dynamics is essential for predicting biodiversity impacts on ecosystem carbon and nutrient cycling.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117662"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117657
Marleen A.E. Vos , Wim de Vries , Jorad de Vries , Marcel R. Hoosbeek , José A. Medina Vega , Richard Sikkema , Frank Sterck
Increasing demands for timber and biomass production from European forests have raised concerns about the sustainability of harvesting practices, since forest nutrient stocks have decreased due to enhanced leaching of base cations driven by soil acidification from elevated nitrogen (N) and sulfur (S) deposition. We quantified the impact of three harvest intensities—high-thinning (also known as crown thinning; ∼20 % basal area removal), shelterwood (∼80 %), and clearcut (100 %)—, two harvest methods (stem-only and whole-tree harvest), and soil preparation (shallow mulching and no mulching) on post-harvest nutrient leaching in beech, Douglas fir, and Scots pine stands in the Netherlands, compared to unharvested control plots. Leaching was quantified by combining monthly dissolved nutrient measurements over a full year with a mechanistic model simulating monthly water fluxes.
Leaching of macronutrients in unharvested control plots was generally higher in Douglas fir than in Scots pine and beech. Clearcutting, and to a lesser extent shelterwood harvesting, strongly increased dissolved nutrient concentrations, especially nitrate (NO3), indicating rapid mobilization of large N stocks and, to a lesser extent, S stocks. These increases were associated with accelerated soil acidification, induced by losses of base cations (calcium [Ca], magnesium [Mg] and potassium [K]) and acid cations (aluminum [Al], iron [Fe] and manganese [Mn]). Thinning, harvest method, and shallow mulching had minimal or negligible effects on post-harvest leaching, underscoring the potential of low-intensity harvests for sustainable forest use with low nutrient losses. Our study shows that high harvest intensity strongly accelerates nutrient leaching within one year after harvest, but the long-term impacts over a rotation period remain to be explored.
{"title":"Harvest intensity, rather than harvest method or soil preparation, affects post-harvest nutrient leaching in acidic sandy forest soils","authors":"Marleen A.E. Vos , Wim de Vries , Jorad de Vries , Marcel R. Hoosbeek , José A. Medina Vega , Richard Sikkema , Frank Sterck","doi":"10.1016/j.geoderma.2025.117657","DOIUrl":"10.1016/j.geoderma.2025.117657","url":null,"abstract":"<div><div>Increasing demands for timber and biomass production from European forests have raised concerns about the sustainability of harvesting practices, since forest nutrient stocks have decreased due to enhanced leaching of base cations driven by soil acidification from elevated nitrogen (N) and sulfur (S) deposition. We quantified the impact of three harvest intensities—high-thinning (also known as crown thinning; ∼20 % basal area removal), shelterwood (∼80 %), and clearcut (100 %)—, two harvest methods (stem-only and whole-tree harvest), and soil preparation (shallow mulching and no mulching) on post-harvest nutrient leaching in beech, Douglas fir, and Scots pine stands in the Netherlands, compared to unharvested control plots. Leaching was quantified by combining monthly dissolved nutrient measurements over a full year with a mechanistic model simulating monthly water fluxes.</div><div>Leaching of macronutrients in unharvested control plots was generally higher in Douglas fir than in Scots pine and beech. Clearcutting, and to a lesser extent shelterwood harvesting, strongly increased dissolved nutrient concentrations, especially nitrate (NO<sub>3</sub>), indicating rapid mobilization of large N stocks and, to a lesser extent, S stocks. These increases were associated with accelerated soil acidification, induced by losses of base cations (calcium [Ca], magnesium [Mg] and potassium [K]) and acid cations (aluminum [Al], iron [Fe] and manganese [Mn]). Thinning, harvest method, and shallow mulching had minimal or negligible effects on post-harvest leaching, underscoring the potential of low-intensity harvests for sustainable forest use with low nutrient losses. Our study shows that high harvest intensity strongly accelerates nutrient leaching within one year after harvest, but the long-term impacts over a rotation period remain to be explored.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117657"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117659
Nannan Wang , Kexin Li , Xinhao Zhu , Yunjiang Zuo , Jianzhao Liu , Ziyu Guo , Ying Sun , Yuedong Guo , Changchun Song , Fenghui Yuan , Xiaofeng Xu
The relationship between soil multifunctionality and microbial diversity is well established, and using genomic data to link microbial diversity with soil functions is increasingly recognized as a reliable approach, despite challenges such as horizontal gene transfer, functional redundancy, and transcriptional uncertainty. Here, we investigated how microbial taxonomic and functional diversities derived from metagenomic data explain soil multifunctionality across soil profiles. We conducted analyses across four seasons and two contrasting hydrological habitats: wetland and cropland. We found that microbial functional diversity captured soil functions more effectively than taxonomic diversity, and its explanatory power depended on scale, strongest at broader classification levels (phylum/module) and higher data hierarchies (cosmopolitan). Microbial functional diversity explained 95 % and 79 % of individual soil functions in wetland and cropland, respectively, and showed a closer association with overall soil multifunctionality. The relationship remained consistent across spatial (0–100 cm soil profiles), temporal (four seasons), and hydrological (wetland and cropland) gradients, demonstrating greater stability than taxonomic diversity. By linking microbial diversity to soil functions across space and time, our findings show that genome-derived microbial functional diversity provides a robust and reliable framework for explaining soil functions, reinforcing the potential of genome-based microbial modeling.
{"title":"Scale dependence of genome-derived microbial functional diversity informing soil functions","authors":"Nannan Wang , Kexin Li , Xinhao Zhu , Yunjiang Zuo , Jianzhao Liu , Ziyu Guo , Ying Sun , Yuedong Guo , Changchun Song , Fenghui Yuan , Xiaofeng Xu","doi":"10.1016/j.geoderma.2025.117659","DOIUrl":"10.1016/j.geoderma.2025.117659","url":null,"abstract":"<div><div>The relationship between soil multifunctionality and microbial diversity is well established, and using genomic data to link microbial diversity with soil functions is increasingly recognized as a reliable approach, despite challenges such as horizontal gene transfer, functional redundancy, and transcriptional uncertainty. Here, we investigated how microbial taxonomic and functional diversities derived from metagenomic data explain soil multifunctionality across soil profiles. We conducted analyses across four seasons and two contrasting hydrological habitats: wetland and cropland. We found that microbial functional diversity captured soil functions more effectively than taxonomic diversity, and its explanatory power depended on scale, strongest at broader classification levels (phylum/module) and higher data hierarchies (cosmopolitan). Microbial functional diversity explained 95 % and 79 % of individual soil functions in wetland and cropland, respectively, and showed a closer association with overall soil multifunctionality. The relationship remained consistent across spatial (0–100 cm soil profiles), temporal (four seasons), and hydrological (wetland and cropland) gradients, demonstrating greater stability than taxonomic diversity. By linking microbial diversity to soil functions across space and time, our findings show that genome-derived microbial functional diversity provides a robust and reliable framework for explaining soil functions, reinforcing the potential of genome-based microbial modeling.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117659"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117650
Qingwen Zhang , Dehua Mao , Weidong Man , Fuping Li , Yongbin Zhang , Fenghua Wu , Caiyao Kou , Rui Yang , Jiannan He , Xuan Yin , Mingyue Liu
Coastal wetlands play a vital role in carbon sequestration and climate change mitigation. However, the invasion of Spartina alterniflora (S.alterniflora) poses a significant threat to these ecosystems. In this study, we collected 114 soil samples from S.alterniflora-invaded coastal wetlands and acquired monthly remote sensing images throughout the sampling year. Time-series variables covering the entire growth stages of S.alterniflora were extracted from these images. The iterative Boruta algorithm was employed to identify sensitive variables, and machine learning algorithms (Random Forest, Boosted Regression Trees, and eXtreme Gradient Boosting) were used to predict soil organic carbon (SOC) content. A space-for-time substitution approach was then applied to assess the impact of S.alterniflora invasion age on SOC dynamics. The results show that the correlation between SOC content and remote sensing variables varied significantly across months, with June-derived variables exhibiting the highest average correlation. Independent validation further indicated that all machine learning models achieved R2 values above 0.6, with the random forest model performing best (R2 = 0.663, nRMSE = 0.157, RPD = 1.713). NDWI was identified as the most important predictor based on variable importance and SHAP analysis, followed by the vertical–vertical (VV) polarization and shortwave infrared (SWIR) band reflectance. Furthermore, spatial evidence revealed that SOC content increased with invasion age, peaking at a saturation point after 19 years. A slight decline was observed after 22 years, due to the greater distance from the coastline, which may have limited the exchange of water, salt, and nutrients. These findings provide spatially explicit insights into the long-term effects of biological invasion on soil carbon dynamics and establish a scientific basis for the sustainable management of coastal wetlands under invasion pressure.
{"title":"Spartina alterniflora invasion-induced soil organic carbon content changes: An assessment by time-series remote sensing and machine learning","authors":"Qingwen Zhang , Dehua Mao , Weidong Man , Fuping Li , Yongbin Zhang , Fenghua Wu , Caiyao Kou , Rui Yang , Jiannan He , Xuan Yin , Mingyue Liu","doi":"10.1016/j.geoderma.2025.117650","DOIUrl":"10.1016/j.geoderma.2025.117650","url":null,"abstract":"<div><div>Coastal wetlands play a vital role in carbon sequestration and climate change mitigation. However, the invasion of <em>Spartina alterniflora</em> (<em>S.alterniflora</em>) poses a significant threat to these ecosystems. In this study, we collected 114 soil samples from <em>S.alterniflora</em>-invaded coastal wetlands and acquired monthly remote sensing images throughout the sampling year. Time-series variables covering the entire growth stages of <em>S.alterniflora</em> were extracted from these images. The iterative Boruta algorithm was employed to identify sensitive variables, and machine learning algorithms (Random Forest, Boosted Regression Trees, and eXtreme Gradient Boosting) were used to predict soil organic carbon (SOC) content. A space-for-time substitution approach was then applied to assess the impact of <em>S.alterniflora</em> invasion age on SOC dynamics. The results show that the correlation between SOC content and remote sensing variables varied significantly across months, with June-derived variables exhibiting the highest average correlation. Independent validation further indicated that all machine learning models achieved R<sup>2</sup> values above 0.6, with the random forest model performing best (R<sup>2</sup> = 0.663, nRMSE = 0.157, RPD = 1.713). NDWI was identified as the most important predictor based on variable importance and SHAP analysis, followed by the vertical–vertical (VV) polarization and shortwave infrared (SWIR) band reflectance. Furthermore, spatial evidence revealed that SOC content increased with invasion age, peaking at a saturation point after 19 years. A slight decline was observed after 22 years, due to the greater distance from the coastline, which may have limited the exchange of water, salt, and nutrients. These findings provide spatially explicit insights into the long-term effects of biological invasion on soil carbon dynamics and establish a scientific basis for the sustainable management of coastal wetlands under invasion pressure.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117650"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117671
Mingchang Wang , Xingnan Liu , Yilin Bao , Jialin Cai , Liheng Liang , Yiting Fan , Hongchao Fan
Remote sensing (RS) technology enables the rapid and accurate acquisition of soil organic matter (SOM) content, which is crucial for ensuring food security and promoting precision agriculture. Multispectral imagery is widely used for large-scale SOM mapping, but its limited spectral resolution substantially constrains estimation accuracy. While proximal hyperspectral data provide detailed spectral information, their point-based observations limit scalability across large regions. To overcome these limitations, a cross-modal modeling framework integrating proximal hyperspectral and satellite spectral data was proposed. Hyperspectral reconstruction technology was applied to enhance satellite spectral resolution and to extend proximal hyperspectral observations into spatially continuous imagery, achieving a balance between spectral accuracy and spatial continuity. To address SOM spatial heterogeneity, a spatial similarity-based random forest (SS-RF) local modeling strategy was introduced. Furthermore, the study systematically evaluated the impact of different soil particle size levels on spectral reflectance and SOM estimation accuracy. This study was conducted in a typical black soil region located in Northeast China. A multimodal dataset was constructed for SOM modeling, including in-situ and laboratory hyperspectral data with multiple particle size treatments, as well as satellite imagery from Zhuhai-1 and Sentinel-2A. The results indicated that the proposed cross-modal fusion and SS-RF framework demonstrated superior SOM estimation performance. The reconstructed hyperspectral imagery effectively integrated proximal and satellite spectral data, thereby preserving spectral integrity and enhancing their correlation with SOM. Among these, the reconstructed imagery based on finer particle sizes (100 mesh, ≤0.15 mm) exhibited the best performance (R2 = 0.874, LCCC = 0.756, RMSE = 2.871 g·kg−1, and RPIQ = 2.159), while the reconstruction using 50 mesh particles (≤0.35 mm) also achieved comparatively good accuracy (R2 = 0.864). In contrast, the model constructed using field in-situ hyperspectral reconstructed imagery produced the lowest accuracy (R2 = 0.730). The estimation accuracy based on the reconstructed imagery was significantly higher than that achieved using Sentinel-2A (R2 = 0.712) and Zhuhai-1 (R2 = 0.759). Compared to traditional global models, the proposed SS-RF local strategy improved accuracy, increasing R2 by 7.64 %. This synergistic optimization approach, which combines spectral reconstruction, local modeling, and particle size standardization provides new insights and technical support for high-precision SOM estimation at the regional scale.
{"title":"Cross-modal integration framework for soil organic matter estimation using proximal and satellite spectral data: Modeling optimization with particle size effects and spatial similarity","authors":"Mingchang Wang , Xingnan Liu , Yilin Bao , Jialin Cai , Liheng Liang , Yiting Fan , Hongchao Fan","doi":"10.1016/j.geoderma.2025.117671","DOIUrl":"10.1016/j.geoderma.2025.117671","url":null,"abstract":"<div><div>Remote sensing (RS) technology enables the rapid and accurate acquisition of soil organic matter (SOM) content, which is crucial for ensuring food security and promoting precision agriculture. Multispectral imagery is widely used for large-scale SOM mapping, but its limited spectral resolution substantially constrains estimation accuracy. While proximal hyperspectral data provide detailed spectral information, their point-based observations limit scalability across large regions. To overcome these limitations, a cross-modal modeling framework integrating proximal hyperspectral and satellite spectral data was proposed. Hyperspectral reconstruction technology was applied to enhance satellite spectral resolution and to extend proximal hyperspectral observations into spatially continuous imagery, achieving a balance between spectral accuracy and spatial continuity. To address SOM spatial heterogeneity, a spatial similarity-based random forest (SS-RF) local modeling strategy was introduced. Furthermore, the study systematically evaluated the impact of different soil particle size levels on spectral reflectance and SOM estimation accuracy. This study was conducted in a typical black soil region located in Northeast China. A multimodal dataset was constructed for SOM modeling, including in-situ and laboratory hyperspectral data with multiple particle size treatments, as well as satellite imagery from Zhuhai-1 and Sentinel-2A. The results indicated that the proposed cross-modal fusion and SS-RF framework demonstrated superior SOM estimation performance. The reconstructed hyperspectral imagery effectively integrated proximal and satellite spectral data, thereby preserving spectral integrity and enhancing their correlation with SOM. Among these, the reconstructed imagery based on finer particle sizes (100 mesh, ≤0.15 mm) exhibited the best performance (R<sup>2</sup> = 0.874, LCCC = 0.756, RMSE = 2.871 g·kg<sup>−1</sup>, and RPIQ = 2.159), while the reconstruction using 50 mesh particles (≤0.35 mm) also achieved comparatively good accuracy (R<sup>2</sup> = 0.864). In contrast, the model constructed using field in-situ hyperspectral reconstructed imagery produced the lowest accuracy (R<sup>2</sup> = 0.730). The estimation accuracy based on the reconstructed imagery was significantly higher than that achieved using Sentinel-2A (R<sup>2</sup> = 0.712) and Zhuhai-1 (R<sup>2</sup> = 0.759). Compared to traditional global models, the proposed SS-RF local strategy improved accuracy, increasing R<sup>2</sup> by 7.64 %. This synergistic optimization approach, which combines spectral reconstruction, local modeling, and particle size standardization provides new insights and technical support for high-precision SOM estimation at the regional scale.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117671"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117660
Manisha Dolui , Teneille Nel , Laura M. Phillips , Abbygail R. McMurtry , Kimber Moreland , Malak Tfaily , Karis McFarlane , Joseph A. Mason , Erika Marin-Spiotta , Marie-Anne de Graaff , Teamrat Ghezzehei , Asmeret Asefaw Berhe
Paleosols form when soils are buried through deposition by aeolian, colluvial, alluvial or other processes. Burial of former topsoil isolates soil organic matter (SOM) from surface conditions, allowing carbon to accumulate and potentially remain stable for millennia. In this study, SOM composition, distribution, and persistence were analyzed in the Brady Soil of Nebraska, USA to compare SOM spatial variability in modern and buried soils, as well as the impact of erosional exposure on SOM stability. The Brady Soil, formed as a surface soil during the Pleistocene-Holocene transition and now a paleosol buried up to 6 m deep (or more) by loess deposition during the Holocene, was sampled along burial (up to 5.8 m depth) and erosional (up to 1.8 m depth) transects to compare SOM dynamics in different geomorphic settings. Fourier Transform Infrared Spectroscopy (FTIR) and Fourier Transform ion cyclotron resonance mass spectrometry (FTICR-MS) were used to analyze SOM composition, while C isotope analyses identified SOM sources and radiocarbon values were used to estimate turnover rates. Results confirmed a vegetation shift from C3 to C4 plants after Brady Soil formation, reflecting warming climatic conditions. Increasing SOM age and decreasing C and N values with depth indicated slowing of decomposition rate in buried soils. Higher pH in the Brady Soil suggested greater base cation content, supporting SOM stabilization through organo-mineral associations and aggregate formation. However, exposure of the Brady Soil due to surface erosion caused faster SOM turnover. This result suggested susceptibility of buried SOM to losses via decomposition upon erosional exposure, possibly accelerated by priming in response to modern SOM inputs. These findings highlight the potential loss of carbon stocks in buried soils under future climate change, as shifts in soil physicochemical properties may destabilize long-preserved SOM.
{"title":"Composition and persistence of soil organic matter along eroding and depositional transects in buried vs. modern soil layers: A case of the Brady paleosol at Wauneta, Nebraska","authors":"Manisha Dolui , Teneille Nel , Laura M. Phillips , Abbygail R. McMurtry , Kimber Moreland , Malak Tfaily , Karis McFarlane , Joseph A. Mason , Erika Marin-Spiotta , Marie-Anne de Graaff , Teamrat Ghezzehei , Asmeret Asefaw Berhe","doi":"10.1016/j.geoderma.2025.117660","DOIUrl":"10.1016/j.geoderma.2025.117660","url":null,"abstract":"<div><div>Paleosols form when soils are buried through deposition by aeolian, colluvial, alluvial or other processes. Burial of former topsoil isolates soil organic matter (SOM) from surface conditions, allowing carbon to accumulate and potentially remain stable for millennia. In this study, SOM composition, distribution, and persistence were analyzed in the Brady Soil of Nebraska, USA to compare SOM spatial variability in modern and buried soils, as well as the impact of erosional exposure on SOM stability. The Brady Soil, formed as a surface soil during the Pleistocene-Holocene transition and now a paleosol buried up to 6 m deep (or more) by loess deposition during the Holocene, was sampled along burial (up to 5.8 m depth) and erosional (up to 1.8 m depth) transects to compare SOM dynamics in different geomorphic settings. Fourier Transform Infrared Spectroscopy (FTIR) and Fourier Transform ion cyclotron resonance mass spectrometry (FTICR-MS) were used to analyze SOM composition, while <span><math><msup><mrow><mi>δ</mi></mrow><mrow><mn>13</mn></mrow></msup></math></span>C isotope analyses identified SOM sources and radiocarbon values were used to estimate turnover rates. Results confirmed a vegetation shift from C3 to C4 plants after Brady Soil formation, reflecting warming climatic conditions. Increasing SOM age and decreasing <span><math><msup><mrow><mi>δ</mi></mrow><mrow><mn>13</mn></mrow></msup></math></span>C and <span><math><msup><mrow><mi>δ</mi></mrow><mrow><mn>15</mn></mrow></msup></math></span>N values with depth indicated slowing of decomposition rate in buried soils. Higher pH in the Brady Soil suggested greater base cation content, supporting SOM stabilization through organo-mineral associations and aggregate formation. However, exposure of the Brady Soil due to surface erosion caused faster SOM turnover. This result suggested susceptibility of buried SOM to losses via decomposition upon erosional exposure, possibly accelerated by priming in response to modern SOM inputs. These findings highlight the potential loss of carbon stocks in buried soils under future climate change, as shifts in soil physicochemical properties may destabilize long-preserved SOM.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117660"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117666
Liji Wu , Shengen Liu , Haonan Wang , Manuel Delgado-Baquerizo , Ying Wu , Xiaoming Lu , Bing Wang , Guiyao Zhou , Peter Dietrich , Yongfei Bai , Dima Chen
Theory and observation suggest that single-dimensional plant attributes and diversity may play a key role in explaining variation in soil biodiversity, but the empirical evidence in this area is still lacking considering multiple functional groups in soil biota. In this study, we explore the associations between plant taxonomic, phylogenetic, and functional diversity and soil biodiversity of multiple functional groups, as well as ecosystem functions in both monoculture and natural grasslands. We identified multidimensional plant attributes that could be categorized into three dimensions related to plant productivity, nutrient levels in leaves and roots, and phylogenetic relationships. We found that multidimensional plant attributes and soil properties commonly explained the biomass, richness and composition of soil biota across multitrophic levels, but this varied with the types of communities and their functional groups in both monoculture and natural grasslands. For example, plant functional traits or phylogeny explained more variation in soil fungi than in soil bacteria. Additionally, some links between multidimensional plant attributes and soil biota and soil functions were similar in both monoculture and natural grasslands, but there were weak effects of soil bacteria in the natural grassland and consistent strong effects of soil fungi in both monoculture and natural grasslands. This study provides experimental evidence supporting the effect of plant taxonomic, phylogenetic, and functional traits on shaping soil biodiversity and functions, which are crucial for understanding how plant-soil interactions may be impacted by ongoing global environmental changes.
{"title":"Multisource grassland evidence for plant functional traits in predicting soil biota biodiversity and functions","authors":"Liji Wu , Shengen Liu , Haonan Wang , Manuel Delgado-Baquerizo , Ying Wu , Xiaoming Lu , Bing Wang , Guiyao Zhou , Peter Dietrich , Yongfei Bai , Dima Chen","doi":"10.1016/j.geoderma.2025.117666","DOIUrl":"10.1016/j.geoderma.2025.117666","url":null,"abstract":"<div><div>Theory and observation suggest that single-dimensional plant attributes and diversity may play a key role in explaining variation in soil biodiversity, but the empirical evidence in this area is still lacking considering multiple functional groups in soil biota. In this study, we explore the associations between plant taxonomic, phylogenetic, and functional diversity and soil biodiversity of multiple functional groups, as well as ecosystem functions in both monoculture and natural grasslands. We identified multidimensional plant attributes that could be categorized into three dimensions related to plant productivity, nutrient levels in leaves and roots, and phylogenetic relationships. We found that multidimensional plant attributes and soil properties commonly explained the biomass, richness and composition of soil biota across multitrophic levels, but this varied with the types of communities and their functional groups in both monoculture and natural grasslands. For example, plant functional traits or phylogeny explained more variation in soil fungi than in soil bacteria. Additionally, some links between multidimensional plant attributes and soil biota and soil functions were similar in both monoculture and natural grasslands, but there were weak effects of soil bacteria in the natural grassland and consistent strong effects of soil fungi in both monoculture and natural grasslands. This study provides experimental evidence supporting the effect of plant taxonomic, phylogenetic, and functional traits on shaping soil biodiversity and functions, which are crucial for understanding how plant-soil interactions may be impacted by ongoing global environmental changes.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117666"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117663
Nicolas Bonfanti , Jerome Poulenard , Pascal Salze , Jerome Foret , Lucie Liger , Cindy Arnoldi , Tim Goodall , Robert Griffiths , Jeremy Puissant , Jean-Christophe Clement
Snow acts as an insulating layer on soils, preserving microbial function and promoting soil organic matter (SOM) mineralization over winter. Climate change is expected to increase the frequency of winter drought in temperate mountain ecosystems leading to snow-free winter, exposing soils to freezing and drying conditions that can disrupt microbial activity and key biogeochemical processes. However, the consequences of extreme snow drought event on microbial communities and associated C and N dynamics remain poorly understood, particularly from a functional and compositional perspective. This study aimed to investigate the ecological consequences of an extreme snow drought in subalpine grasslands by experimentally excluding all winter snowfall. By isolating the effects of a snow-free winter, without the confounding influences of warming or vegetation change, we were able to trace its impacts on ecosystem functioning from winter through the subsequent spring and summer. We observed a sharp spike in N2O emissions (+700 %) and a significant drop in CO2 fluxes (−70 %) during the snow-free winter, measured through discrete greenhouse gas flux sampling throughout the year, including winter. These changes coincided with immediate soil freezing and were linked to shifts in microbial community composition and function, assessed at three key periods—winter, spring, and peak growing season—using a combination of DNA-based community profiling, biomass quantification, and enzymatic assays. Functional markers showed widespread declines in microbial activity, including respiration, decomposition, and ammonification, along with a compositional shift toward anaerobic taxa and increased denitrification. These functional disruptions were further reflected in SOM mineralization dynamics, characterized via infrared spectroscopy and labile carbon fractions, and in reduced nitrogen cycling, measured through NH4+, NO3− content, and resin bag analyses. Although an extended growing season and compensatory microbial responses partially offset winter impacts, full functional recovery was not achieved by the end of the growing season. These findings highlight how snow-free winters, though extreme, can profoundly disrupt soil functioning, leaving lasting carry-over effects that last into subsequent seasons.
{"title":"Snow drought alters soil microbial communities and greenhouse gas fluxes in a subalpine grassland","authors":"Nicolas Bonfanti , Jerome Poulenard , Pascal Salze , Jerome Foret , Lucie Liger , Cindy Arnoldi , Tim Goodall , Robert Griffiths , Jeremy Puissant , Jean-Christophe Clement","doi":"10.1016/j.geoderma.2025.117663","DOIUrl":"10.1016/j.geoderma.2025.117663","url":null,"abstract":"<div><div>Snow acts as an insulating layer on soils, preserving microbial function and promoting soil organic matter (SOM) mineralization over winter. Climate change is expected to increase the frequency of winter drought in temperate mountain ecosystems leading to snow-free winter, exposing soils to freezing and drying conditions that can disrupt microbial activity and key biogeochemical processes. However, the consequences of extreme snow drought event on microbial communities and associated C and N dynamics remain poorly understood, particularly from a functional and compositional perspective. This study aimed to investigate the ecological consequences of an extreme snow drought in subalpine grasslands by experimentally excluding all winter snowfall. By isolating the effects of a snow-free winter, without the confounding influences of warming or vegetation change, we were able to trace its impacts on ecosystem functioning from winter through the subsequent spring and summer. We observed a sharp spike in N<sub>2</sub>O emissions (+700 %) and a significant drop in CO<sub>2</sub> fluxes (−70 %) during the snow-free winter, measured through discrete greenhouse gas flux sampling throughout the year, including winter. These changes coincided with immediate soil freezing and were linked to shifts in microbial community composition and function, assessed at three key periods—winter, spring, and peak growing season—using a combination of DNA-based community profiling, biomass quantification, and enzymatic assays. Functional markers showed widespread declines in microbial activity, including respiration, decomposition, and ammonification, along with a compositional shift toward anaerobic taxa and increased denitrification. These functional disruptions were further reflected in SOM mineralization dynamics, characterized via infrared spectroscopy and labile carbon fractions, and in reduced nitrogen cycling, measured through NH<sub>4</sub><sup>+</sup>, NO<sub>3</sub><sup>−</sup> content, and resin bag analyses. Although an extended growing season and compensatory microbial responses partially offset winter impacts, full functional recovery was not achieved by the end of the growing season. These findings highlight how snow-free winters, though extreme, can profoundly disrupt soil functioning, leaving lasting carry-over effects that last into subsequent seasons.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117663"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117632
Eduardo Velázquez , Luis Lassaletta , Carmen Galea , Antonio Vallejo , Juliana Hurtado , Josette Garnier , Klaus Butterbach-Bahl , Carmen González-Murua , Teresa Fuertes-Mendizábal , José María Estavillo , Mohammad Zaman , Alberto Sanz-Cobena
The ability of riparian forests to reduce nutrient flows from crops to streams is well known. However, their role as sources and sinks of greenhouse gases (GHGs) has been less studied, particularly in Mediterranean environments. We assessed the changes in daily soil N2O and CH4 fluxes between 2021 and 2023 in a riparian zone located in Central Spain. We also evaluated if cumulative fluxes of such GHGs depended on soil NO3−, NH4+ and DOC contents, and water-filled pore space (WFPS). Their dependence to different vegetation types and distances to the riverbank, as well as on the existence of wet periods, which include occasional floods, was also analysed. Daily N2O and CH4 fluxes were both low. Those of N2O were positive whereas those of CH4 were mostly negative, but positive fluxes of this GHG were nevertheless observed in late autumn 2021 and in spring 2022. Cumulative fluxes were mainly driven by soil NH4+ contents in the case of N2O and by WFPS in the case of CH4, and influenced by the distance from the riverbank in both cases. The relationships between cumulative fluxes of N2O and its major drivers were positively and significantly influenced by the wet periods. Our results indicate that our riparian zone acted as a net source of N2O and a net sink of CH4, but it became a net source of CH4 in cold and wet periods, where anoxic conditions in which methanogenesis occurs are favoured. Soil N2O emissions mainly originate as a by-product of nitrification but also from incomplete denitrification after heavy rainfall events in warm months. Thus, we advocate for preventive strategies to reduce nitrogen flows from cropping systems to reduce soil N2O emissions in Mediterranean riparian zones.
{"title":"Mediterranean riparian zones as hotspots of greenhouse gases: effects of vegetation, distance to the riverbank and wet periods","authors":"Eduardo Velázquez , Luis Lassaletta , Carmen Galea , Antonio Vallejo , Juliana Hurtado , Josette Garnier , Klaus Butterbach-Bahl , Carmen González-Murua , Teresa Fuertes-Mendizábal , José María Estavillo , Mohammad Zaman , Alberto Sanz-Cobena","doi":"10.1016/j.geoderma.2025.117632","DOIUrl":"10.1016/j.geoderma.2025.117632","url":null,"abstract":"<div><div>The ability of riparian forests to reduce nutrient flows from crops to streams is well known. However, their role as sources and sinks of greenhouse gases (GHGs) has been less studied, particularly in Mediterranean environments. We assessed the changes in daily soil N<sub>2</sub>O and CH<sub>4</sub> fluxes between 2021 and 2023 in a riparian zone located in Central Spain. We also evaluated if cumulative fluxes of such GHGs depended on soil NO<sub>3</sub><sup>−</sup>, NH<sub>4</sub><sup>+</sup> and DOC contents, and water-filled pore space (WFPS). Their dependence to different vegetation types and distances to the riverbank, as well as on the existence of wet periods, which include occasional floods, was also analysed. Daily N<sub>2</sub>O and CH<sub>4</sub> fluxes were both low. Those of N<sub>2</sub>O were positive whereas those of CH<sub>4</sub> were mostly negative, but positive fluxes of this GHG were nevertheless observed in late autumn 2021 and in spring 2022. Cumulative fluxes were mainly driven by soil NH<sub>4</sub><sup>+</sup> contents in the case of N<sub>2</sub>O and by WFPS in the case of CH<sub>4</sub>, and influenced by the distance from the riverbank in both cases. The relationships between cumulative fluxes of N<sub>2</sub>O and its major drivers were positively and significantly influenced by the wet periods. Our results indicate that our riparian zone acted as a net source of N<sub>2</sub>O and a net sink of CH<sub>4</sub>, but it became a net source of CH<sub>4</sub> in cold and wet periods, where anoxic conditions in which methanogenesis occurs are favoured. Soil N<sub>2</sub>O emissions mainly originate as a by-product of nitrification but also from incomplete denitrification after heavy rainfall events in warm months. Thus, we advocate for preventive strategies to reduce nitrogen flows from cropping systems to reduce soil N<sub>2</sub>O emissions in Mediterranean riparian zones.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117632"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.geoderma.2025.117664
Feng Gao , Yajuan Xing , Liming Yin , Guancheng Liu , Chao Liang , Xiaochun Wang , Shijie Han , Lijian Xu , Qinggui Wang
The priming effect induced by labile carbon inputs can influence soil organic carbon (SOC) decomposition, which can be regulated by nitrogen (N) availability. However, how long-term N addition affects the priming effect is still unclear. Here, we address this issue by combining results from an experiment and a data synthesis. For the experiment, soils were collected from a 12-year in-situ N addition in a boreal forest, and 13C-labeled glucose, glycine or oxalic acid were added as a rate of 2.5% of SOC. Further, we conducted a global data synthesis with 188 observations from 50 studies from forests to compare priming in response to transient incubation addition versus continuous field N addition. The positive priming effect caused by glycine was highest among the three C types especially in the control treatment, i.e., a significant interaction between N addition and C type. These variations could be attributed to differences in microbial substrate metabolic pathways. N addition significantly suppressed the priming effect, consistent with trends observed in the global data synthesis. However, the extent of N inhibition from field studies was marginally lower than that from incubation studies, suggesting that the N inhibition on priming may be to some extent overestimated. Overall, our results emphasize that the inhibition of long-term N addition on priming may depend on labile C type. More studies with soils from long-term N addition in the field are urgently needed for accurately assessing SOC decomposition via the priming effect in the context of chronic N deposition in boreal forests.
{"title":"Decreases in priming effect vary with labile carbon type under long-term nitrogen addition in a boreal forest","authors":"Feng Gao , Yajuan Xing , Liming Yin , Guancheng Liu , Chao Liang , Xiaochun Wang , Shijie Han , Lijian Xu , Qinggui Wang","doi":"10.1016/j.geoderma.2025.117664","DOIUrl":"10.1016/j.geoderma.2025.117664","url":null,"abstract":"<div><div>The priming effect induced by labile carbon inputs can influence soil organic carbon (SOC) decomposition, which can be regulated by nitrogen (N) availability. However, how long-term N addition affects the priming effect is still unclear. Here, we address this issue by combining results from an experiment and a data synthesis. For the experiment, soils were collected from a 12-year <em>in-situ</em> N addition in a boreal forest, and <sup>13</sup>C-labeled glucose, glycine or oxalic acid were added as a rate of 2.5% of SOC. Further, we conducted a global data synthesis with 188 observations from 50 studies from forests to compare priming in response to transient incubation addition <em>versus</em> continuous field N addition. The positive priming effect caused by glycine was highest among the three C types especially in the control treatment, <em>i.e.</em>, a significant interaction between N addition and C type. These variations could be attributed to differences in microbial substrate metabolic pathways. N addition significantly suppressed the priming effect, consistent with trends observed in the global data synthesis. However, the extent of N inhibition from field studies was marginally lower than that from incubation studies, suggesting that the N inhibition on priming may be to some extent overestimated. Overall, our results emphasize that the inhibition of long-term N addition on priming may depend on labile C type. More studies with soils from long-term N addition in the field are urgently needed for accurately assessing SOC decomposition via the priming effect in the context of chronic N deposition in boreal forests.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"465 ","pages":"Article 117664"},"PeriodicalIF":6.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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