The hydrothermal changes in the active layers of permafrost soils during freeze–thaw processes are crucial for understanding the interactions between the surface and the atmosphere. The soil enthalpy of the active layer in permafrost regions is a comprehensive parameter incorporating soil temperature and moisture, reflecting the energy state of the soil. Changes in soil enthalpy during freeze–thaw processes have important impacts on soil hydrothermal coupling processes and the land–atmosphere energy exchange. In this paper, using the measured hydrothermal data of the continuous permafrost region at Tanggula and the relict permafrost region at Mahanshan on the Qinghai-Tibetan Plateau, we analyzed the characteristics of soil enthalpy changes during freeze–thaw processes and discuss the hydrothermal coupling effects of soil enthalpy and land–atmosphere energy changes occurring during the processes and the lag relationship between soil enthalpy and precipitation. The soil enthalpy changes at the two sites were different, mainly due to their difference in water content. There is a near-linear relationship between soil enthalpy and unfrozen water content, with correlation coefficients greater than 0.9 at all depths, reflecting the phase change and migration of soil moisture. Soil enthalpy and net radiation at the surface displayed similar patterns, reflecting the balance of the surface energy budget. There was a 1–2 months lag relationship between the soil enthalpy of the whole active layer and precipitation, and this relationship varied with the season and the underlying surface.
{"title":"The impacts of soil enthalpy change on land–atmosphere interactions of permafrost on the Qinghai-Tibet Plateau","authors":"Ren Li, Shenning Wang, Junjie Ma, Wenhao Liu, Tonghua Wu, Changwei Xie, Xiaodong Wu, Yongjian Ding, Lin Zhao, Guojie Hu, Jimin Yao, Xiaofan Zhu, Wu Wang, Yongliang Jiao, Yao Xiao, Jianzong Shi, Yongping Qiao","doi":"10.1016/j.geoderma.2025.117183","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117183","url":null,"abstract":"The hydrothermal changes in the active layers of permafrost soils during freeze–thaw processes are crucial for understanding the interactions between the surface and the atmosphere. The soil enthalpy of the active layer in permafrost regions is a comprehensive parameter incorporating soil temperature and moisture, reflecting the energy state of the soil. Changes in soil enthalpy during freeze–thaw processes have important impacts on soil hydrothermal coupling processes and the land–atmosphere energy exchange. In this paper, using the measured hydrothermal data of the continuous permafrost region at Tanggula and the relict permafrost region at Mahanshan on the Qinghai-Tibetan Plateau, we analyzed the characteristics of soil enthalpy changes during freeze–thaw processes and discuss the hydrothermal coupling effects of soil enthalpy and land–atmosphere energy changes occurring during the processes and the lag relationship between soil enthalpy and precipitation. The soil enthalpy changes at the two sites were different, mainly due to their difference in water content. There is a near-linear relationship between soil enthalpy and unfrozen water content, with correlation coefficients greater than 0.9 at all depths, reflecting the phase change and migration of soil moisture. Soil enthalpy and net radiation at the surface displayed similar patterns, reflecting the balance of the surface energy budget. There was a 1–2 months lag relationship between the soil enthalpy of the whole active layer and precipitation, and this relationship varied with the season and the underlying surface.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"74 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020250","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}
Peatlands are pivotal in global carbon sequestration initiatives. However, studies of winter ecological factors and their subsequent effects on soil carbon–nitrogen (C-N) coupling processes remain limited, particularly amidst altering snowpack conditions due to climate change. Here, an in situ field experiment focusing on snowpack manipulation (presence and absence) was conducted within a northern peatland, China. The N functional groups and availability, bacterial community’s structure, succession and metabolic function, and carbohydrate-active enzymes (CAZymes) were determined at 0–30 cm (topsoil) and 30–60 cm (subsoil) employing synchrotron radiation X-ray absorption near-edge structure (XANES) and metagenomic sequencing technologies. The findings revealed that snowpack absence augmented the number of freeze–thaw cycles by 9 times, causing the subsoil that initially did not experience freeze–thaw cycles to undergo 17 cycles. This amplification of freeze–thaw cycles significantly influenced soil N processes during the freeze–thaw period and subsequent seasons. Specifically, it resulted in a 40.2 % and 1.8 % increase in the metabolic potential of denitrification in the topsoil and subsoil, respectively. Concurrently, there was a reduction in inorganic N content by 4.1 % and 4.4 % in the topsoil and subsoil, respectively. Furthermore, the diminished N availability (ammonium and inorganic N) intensifying soil N limitation subsequently altered microbial assembly processes. This shift led to a significant increase in the abundance of CAZymes encoding the decomposition of lignin (19.2 % and 4.8 %), chitin (4.8 % and 1.4 %), and murein (9.0 % and 0.8 %) in the topsoil and subsoil. Additionally, the content of pyridine, primarily derived from the decomposition of lignin and microbial cell walls, increased by 2.2 % and 1.9 % at two studied depths under snowpack absence conditions. These results uncover a cascading relationship between snowpack conditions, N availability, and the decomposition of recalcitrant carbon in peatland soils, highlighting the need for further comprehensive studies in this domain.
{"title":"Freeze-thaw carry-over effect promotes decomposition of recalcitrant carbon in peatlands by nitrogen limitation","authors":"Jiawen Yan, Lianxi Sheng, Xiaofei Yu, Shanshan Ding, Yongen Min, Hongyan Shen, Yuanchun Zou","doi":"10.1016/j.geoderma.2025.117182","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117182","url":null,"abstract":"Peatlands are pivotal in global carbon sequestration initiatives. However, studies of winter ecological factors and their subsequent effects on soil carbon–nitrogen (C-N) coupling processes remain limited, particularly amidst altering snowpack conditions due to climate change. Here, an in situ field experiment focusing on snowpack manipulation (presence and absence) was conducted within a northern peatland, China. The N functional groups and availability, bacterial community’s structure, succession and metabolic function, and carbohydrate-active enzymes (CAZymes) were determined at 0–30 cm (topsoil) and 30–60 cm (subsoil) employing synchrotron radiation X-ray absorption near-edge structure (XANES) and metagenomic sequencing technologies. The findings revealed that snowpack absence augmented the number of freeze–thaw cycles by 9 times, causing the subsoil that initially did not experience freeze–thaw cycles to undergo 17 cycles. This amplification of freeze–thaw cycles significantly influenced soil N processes during the freeze–thaw period and subsequent seasons. Specifically, it resulted in a 40.2 % and 1.8 % increase in the metabolic potential of denitrification in the topsoil and subsoil, respectively. Concurrently, there was a reduction in inorganic N content by 4.1 % and 4.4 % in the topsoil and subsoil, respectively. Furthermore, the diminished N availability (ammonium and inorganic N) intensifying soil N limitation subsequently altered microbial assembly processes. This shift led to a significant increase in the abundance of CAZymes encoding the decomposition of lignin (19.2 % and 4.8 %), chitin (4.8 % and 1.4 %), and murein (9.0 % and 0.8 %) in the topsoil and subsoil. Additionally, the content of pyridine, primarily derived from the decomposition of lignin and microbial cell walls, increased by 2.2 % and 1.9 % at two studied depths under snowpack absence conditions. These results uncover a cascading relationship between snowpack conditions, N availability, and the decomposition of recalcitrant carbon in peatland soils, highlighting the need for further comprehensive studies in this domain.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"20 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020251","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 : 2025-01-21DOI: 10.1016/j.geoderma.2025.117181
Longnan Shi, Karen Daly, Sharon O’Rourke
Associating with mineral surfaces, mineral-associated organic carbon (MAOC) is able to persist against fast decomposition via chemical bonding or physical occlusion, considered as key to soil organic carbon (SOC) stabilisation. In this study, the feasibility and capability of using mid-infrared (MIR) spectral models to predict MAOC and optimising the estimation of theoretical MAOC saturation limits was tested. Based on measured MAOC from physical carbon fractionation, the spectral MAOC model (R<ce:sup loc="post">2</ce:sup> = 0.86, RMSE = 4.41 g C kg<ce:sup loc="post">−1</ce:sup>) predicted MAOC values from a large regional scale spectral library. Based on measured MAOC from physical carbon fractionation, the model with a medium RMSE (R<ce:sup loc="post">2</ce:sup> = 0.86, RMSE = 4.41 g C kg<ce:sup loc="post">−1</ce:sup>) among 41 randomizations was identified as the most generalized and was selected to predict MAOC values from a large regional-scale spectral library. As SOC increased, the rate of MAOC accumulation diminished, indicating the presence of a theoretical saturation limit. Hence, quantile regression at 95th was performed on the whole dataset based on the relationship between MAOC and silt + clay to estimate theoretical MAOC saturation limits. Using this approach, estimated theoretical MAOC saturation limits was 67.5 ± 2 g C kg<ce:sup loc="post">−1</ce:sup> with a 95 % confidence interval ranging from 64.0 to 71.4 g C kg<ce:sup loc="post">−1</ce:sup>. To advance this, a new data-driven approach combining quantile regression and MIR spectral library was proposed using a spectral neighbourhood framework, called ‘local quantile regression’, to improve the estimation of theoretical MAOC saturation limits in quantile regression. By defining neighbourhoods around each soil sample based on spectral dissimilarity, quantile regression was conducted within these neighbourhoods, and inverse distance weight averaging was applied to improve the robustness of the estimates. MAOC theoretical saturation limits estimated in local quantile regression varied from 44 g C kg<ce:sup loc="post">−1</ce:sup> to 82 g C kg<ce:sup loc="post">−1</ce:sup>. In contrast to the constant theoretical upper limit in global quantile regression, local quantile regression using MIR data captures chemical information, specifically, clay minerals related to carbon storage that offers potentially more realistic assessment of MAOC saturation. Moreover, based on correlation analysis and variable importance used in random forest model, soil mineralogy related properties, such as CEC and different cations, followed by land management related covariates, like available phosphorus and climatology, were identified as primary and secondary driving factors behind this variation of MAOC saturation limit. Hence, local quantile regression provided a conservative but more feasible MAOC sequestration target, overcoming limitations in global quantile regression and offering a better framework
与矿物表面相关的矿物伴生有机碳（MAOC）能够通过化学结合或物理阻断抵抗快速分解，被认为是土壤有机碳（SOC）稳定的关键。在本研究中，测试了使用中红外（MIR）光谱模型预测MAOC和优化理论MAOC饱和极限估计的可行性和能力。基于实测的物理碳分馏MAOC，光谱MAOC模型（R2 = 0.86, RMSE = 4.41 g C kg - 1）预测了区域尺度光谱库的MAOC值。基于物理碳分馏法测量的MAOC，在41个随机化模型中，RMSE为中等（R2 = 0.86, RMSE = 4.41 g C kg - 1）的模型被认为是最一般化的，并被选择用于预测大型区域尺度光谱库中的MAOC值。随着有机碳的增加，MAOC积累速率降低，表明存在理论饱和极限。因此，基于MAOC与粉土+粘土的关系，对整个数据集进行95分位数回归，估算MAOC的理论饱和极限。使用这种方法，估计理论mac饱和极限为67.5±2 g C kg - 1, 95%置信区间为64.0至71.4 g C kg - 1。为了推进这一点，提出了一种新的数据驱动方法，将分位数回归和MIR光谱库结合起来，使用称为“局部分位数回归”的光谱邻域框架，以改进分位数回归中理论mac饱和极限的估计。通过基于光谱不相似性定义每个土壤样本周围的邻域，在这些邻域内进行分位数回归，并应用逆距离加权平均来提高估计的稳健性。局部分位数回归估计的MAOC理论饱和极限从44 g C kg - 1到82 g C kg - 1不等。与全球分位数回归中恒定的理论上限相比，使用MIR数据的局部分位数回归捕获化学信息，特别是与碳储存相关的粘土矿物，这可能为MAOC饱和度提供更现实的评估。此外，基于相关分析和随机森林模型的变量重要性，确定了土壤矿物学相关属性（如CEC和不同阳离子）、土地管理相关协变量（如速效磷和气候）是MAOC饱和极限变化的主次驱动因素。因此，局部分位数回归提供了一个保守但更可行的MAOC固碳目标，克服了全局分位数回归的局限性，为区域尺度的碳固碳估算提供了更好的框架。基于局部分位数回归估计的MAOC饱和度，计算出MAOC固存潜力，在爱尔兰北半部草地矿质土壤中，MAOC在5-20 cm处共可固存530.4 Mt C，显示出巨大的碳固存潜力。
{"title":"Estimating mineral-associated organic carbon saturation and sequestration potential using MIR spectral based local quantile regression","authors":"Longnan Shi, Karen Daly, Sharon O’Rourke","doi":"10.1016/j.geoderma.2025.117181","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117181","url":null,"abstract":"Associating with mineral surfaces, mineral-associated organic carbon (MAOC) is able to persist against fast decomposition via chemical bonding or physical occlusion, considered as key to soil organic carbon (SOC) stabilisation. In this study, the feasibility and capability of using mid-infrared (MIR) spectral models to predict MAOC and optimising the estimation of theoretical MAOC saturation limits was tested. Based on measured MAOC from physical carbon fractionation, the spectral MAOC model (R<ce:sup loc=\"post\">2</ce:sup> = 0.86, RMSE = 4.41 g C kg<ce:sup loc=\"post\">−1</ce:sup>) predicted MAOC values from a large regional scale spectral library. Based on measured MAOC from physical carbon fractionation, the model with a medium RMSE (R<ce:sup loc=\"post\">2</ce:sup> = 0.86, RMSE = 4.41 g C kg<ce:sup loc=\"post\">−1</ce:sup>) among 41 randomizations was identified as the most generalized and was selected to predict MAOC values from a large regional-scale spectral library. As SOC increased, the rate of MAOC accumulation diminished, indicating the presence of a theoretical saturation limit. Hence, quantile regression at 95th was performed on the whole dataset based on the relationship between MAOC and silt + clay to estimate theoretical MAOC saturation limits. Using this approach, estimated theoretical MAOC saturation limits was 67.5 ± 2 g C kg<ce:sup loc=\"post\">−1</ce:sup> with a 95 % confidence interval ranging from 64.0 to 71.4 g C kg<ce:sup loc=\"post\">−1</ce:sup>. To advance this, a new data-driven approach combining quantile regression and MIR spectral library was proposed using a spectral neighbourhood framework, called ‘local quantile regression’, to improve the estimation of theoretical MAOC saturation limits in quantile regression. By defining neighbourhoods around each soil sample based on spectral dissimilarity, quantile regression was conducted within these neighbourhoods, and inverse distance weight averaging was applied to improve the robustness of the estimates. MAOC theoretical saturation limits estimated in local quantile regression varied from 44 g C kg<ce:sup loc=\"post\">−1</ce:sup> to 82 g C kg<ce:sup loc=\"post\">−1</ce:sup>. In contrast to the constant theoretical upper limit in global quantile regression, local quantile regression using MIR data captures chemical information, specifically, clay minerals related to carbon storage that offers potentially more realistic assessment of MAOC saturation. Moreover, based on correlation analysis and variable importance used in random forest model, soil mineralogy related properties, such as CEC and different cations, followed by land management related covariates, like available phosphorus and climatology, were identified as primary and secondary driving factors behind this variation of MAOC saturation limit. Hence, local quantile regression provided a conservative but more feasible MAOC sequestration target, overcoming limitations in global quantile regression and offering a better framework","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"19 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020007","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 : 2025-01-21DOI: 10.1016/j.geoderma.2025.117178
Piroska Kassai, Mihály Kocsis, Gábor Szatmári, András Makó, János Mészáros, Annamária Laborczi, Zoltán Magyar, Katalin Takács, László Pásztor, Brigitta Szabó
Large-scale maps of particle size fractions (i.e., sand, silt, and clay contents) were created for a case study based on the newly developed Profile-level Database of the Hungarian Large-Scale Soil Mapping (Hungarian acronym: NATASA). This database combines data from previous surveys, offering potential to improve soil mapping accuracy. The database includes information on soil taxonomy and basic soil chemical and physical properties. However, this database contains no direct information on sand, silt and clay content, only an indirect parameter, namely, the upper limit of soil plasticity. Particle size distribution is crucial for various applications, such as assessing soil degradation, hydrology and fertility. To overcome this limitation, we developed pedotransfer functions (PTFs) to compute the particle size distribution from the soil properties available in the NATASA dataset (1,372 soil profiles). The PTFs were trained and tested on the Hungarian Detailed Soil Hydrophysical Database (3,970 soil profiles) using the random forest method. For the prediction model, i) additive log-ratio transformed clay, silt and sand content were used as the dependent variables, and ii) the upper limit of soil plasticity, soil type, calcium carbonate content, organic matter content and pH were included as independent variables. The results indicate that the R2 values of the PTFs are 0.69 for clay, 0.58 for silt, and 0.74 for sand content. Since the NATASA database contains soil information from different depths, we splined the data into six standard depth layers (0–5, 5–15, 15–30, 30–60, 60–100 and 100–200 cm depths). The spatial modelling was performed by random forest kriging (RFK) using environmental auxiliary variables. The R2 values of the RFK models range from 0.19 to 0.67 for clay content, from 0.49 to 0.62 for silt content and from 0.69 to 0.74 for sand content. We compared the high-resolution (25 m) maps with the global SoilGrids (250 m resolution) and the national DOSoReMI.hu soil maps (100 m resolution). Our high-resolution maps offer more detailed information on clay, silt and sand content vertically and horizontally compared to global and national soil maps. This enhanced detail will facilitate future assessments of soil texture-related processes in the area.
{"title":"Large-scale mapping of soil particle size distribution using legacy data and machine learning-based pedotransfer functions","authors":"Piroska Kassai, Mihály Kocsis, Gábor Szatmári, András Makó, János Mészáros, Annamária Laborczi, Zoltán Magyar, Katalin Takács, László Pásztor, Brigitta Szabó","doi":"10.1016/j.geoderma.2025.117178","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117178","url":null,"abstract":"Large-scale maps of particle size fractions (i.e., sand, silt, and clay contents) were created for a case study based on the newly developed Profile-level Database of the Hungarian Large-Scale Soil Mapping (Hungarian acronym: NATASA). This database combines data from previous surveys, offering potential to improve soil mapping accuracy. The database includes information on soil taxonomy and basic soil chemical and physical properties. However, this database contains no direct information on sand, silt and clay content, only an indirect parameter, namely, the upper limit of soil plasticity. Particle size distribution is crucial for various applications, such as assessing soil degradation, hydrology and fertility. To overcome this limitation, we developed pedotransfer functions (PTFs) to compute the particle size distribution from the soil properties available in the NATASA dataset (1,372 soil profiles). The PTFs were trained and tested on the Hungarian Detailed Soil Hydrophysical Database (3,970 soil profiles) using the random forest method. For the prediction model, i) additive log-ratio transformed clay, silt and sand content were used as the dependent variables, and ii) the upper limit of soil plasticity, soil type, calcium carbonate content, organic matter content and pH were included as independent variables. The results indicate that the R<ce:sup loc=\"post\">2</ce:sup> values of the PTFs are 0.69 for clay, 0.58 for silt, and 0.74 for sand content. Since the NATASA database contains soil information from different depths, we splined the data into six standard depth layers (0–5, 5–15, 15–30, 30–60, 60–100 and 100–200 cm depths). The spatial modelling was performed by random forest kriging (RFK) using environmental auxiliary variables. The R<ce:sup loc=\"post\">2</ce:sup> values of the RFK models range from 0.19 to 0.67 for clay content, from 0.49 to 0.62 for silt content and from 0.69 to 0.74 for sand content. We compared the high-resolution (25 m) maps with the global SoilGrids (250 m resolution) and the national <ce:inter-ref xlink:href=\"http://DOSoReMI.hu\" xlink:type=\"simple\">DOSoReMI.hu</ce:inter-ref> soil maps (100 m resolution). Our high-resolution maps offer more detailed information on clay, silt and sand content vertically and horizontally compared to global and national soil maps. This enhanced detail will facilitate future assessments of soil texture-related processes in the area.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"22 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020008","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 : 2025-01-20DOI: 10.1016/j.geoderma.2025.117171
A. Sandhage-Hofmann, J. Lenzen, K. Frindte, A. Angombe, W. Amelung
Increasing global temperatures promote heterotrophic soil respiration (Rh) and subsequent carbon losses. In addition, greater variability in precipitation leads to more frequent rainfall following dry periods, resulting in a ’pulse’ of microbial activity and carbon release known as the Birch effect, especially in dry regions. But the effect of wildlife conservation and landuse intensification on Rh and Q10 in savanna systems is almost unknown. We hypothesized that i) the Rh pulse after rewetting (“Birch” effect) contributes notably to carbon losses in semi-arid regions, ii) conservation with increasing elephant numbers leads to higher Rh and lower Q10 values compared to rangeland and cropland, iii) modulated locally by habitat type (subcanopy, grass, bare patch), and iv) explained by microbial community composition. We sampled topsoils (0–10 cm) from different habitat types in high and low elephant density plots, croplands, and rangelands in savanna woodlands of the Zambezi region, Namibia. The samples were incubated at different temperatures (20-40° C) using a Respicond® apparatus. Microbial biomass and associated community composition were analyzed by DNA analysis. Immediately after rewetting, carbon losses were substantial and amounted to 200 g CO2-C day-1ha−1. High elephant densities had the highest Rh at 25° C (1.21 µg CO2 g-1h−1) relative to other land uses (mean 0.75 µg CO2 g-1h−1) and significantly higher qPCR copy numbers. Rh was similar under different habitat types. The mean Q10 value during the growing season was comparable under cultivation and high elephant density (∼2.3), exceeding fixed values of land surface models. Warming increased Rh from 0.6 µg CO2 g-1h−1 at 20° C by a mean factor of 2.6 at 40° C, with the highest increase at high elephant densities (factor 3.4). Generalized linear mixed models identified contents of nitrogen, silt, pH, and land use type as main predictor variables, explaining 57 % of Rh variability. We conclude that savanna soil’s vulnerability to climate warming is comparable between conservation and intensification but that carbon losses due to warming will be highest under wildlife conservation with high elephant densities.
全球气温升高促进了异养土壤呼吸（Rh）和随后的碳损失。此外，降水的更大变异性导致干旱期后降雨更频繁，导致微生物活动和碳释放的“脉冲”，即所谓的桦树效应，特别是在干旱地区。但野生动物保护和土地利用集约化对稀树草原系统Rh和Q10的影响几乎是未知的。我们假设i)再湿润后的Rh脉冲（“桦树”效应）对半干旱区的碳损失有显著贡献，ii)与牧场和农田相比，大象数量增加的保护导致更高的Rh和更低的Q10值，iii)由栖息地类型（亚冠、草地、光斑）局部调节，iv)由微生物群落组成解释。我们在纳米比亚赞比西地区稀树草原林地的不同生境类型、农田和放牧地取样了0-10 cm的表层土壤。样品使用Respicond®仪器在不同温度（20-40°C）下孵育。通过DNA分析分析微生物生物量和相关群落组成。在重新湿润后，碳损失非常大，达到200 g CO2-C day-1ha−1。相对于其他土地利用（平均0.75µg CO2 g-1h -1），高大象密度在25°C时的Rh最高（1.21µg CO2 g-1h -1）， qPCR拷贝数显著增加。不同生境类型下Rh值相近。生长季节的平均Q10值在种植和大象密度高的情况下相当（~ 2.3），超过陆地表面模型的固定值。升温使Rh从20°C时的0.6µg CO2 g-1h−1增加到40°C时的2.6倍，在大象密度高时增加最大（3.4倍）。广义线性混合模型将氮含量、淤泥、pH和土地利用类型确定为主要预测变量，解释了57%的Rh变异。我们得出结论，热带稀树草原土壤对气候变暖的脆弱性在保护和强化之间是相当的，但由于变暖导致的碳损失将在大象密度高的野生动物保护下最高。
{"title":"Effects of wildlife conservation and land use intensification on heterotrophic soil respiration and temperature sensitivity (Q10) in semiarid savannas","authors":"A. Sandhage-Hofmann, J. Lenzen, K. Frindte, A. Angombe, W. Amelung","doi":"10.1016/j.geoderma.2025.117171","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117171","url":null,"abstract":"Increasing global temperatures promote heterotrophic soil respiration (Rh) and subsequent carbon losses. In addition, greater variability in precipitation leads to more frequent rainfall following dry periods, resulting in a ’pulse’ of microbial activity and carbon release known as the Birch effect, especially in dry regions. But the effect of wildlife conservation and landuse intensification on Rh and Q10 in savanna systems is almost unknown. We hypothesized that i) the Rh pulse after rewetting (“Birch” effect) contributes notably to carbon losses in semi-arid regions, ii) conservation with increasing elephant numbers leads to higher Rh and lower Q10 values compared to rangeland and cropland, iii) modulated locally by habitat type (subcanopy, grass, bare patch), and iv) explained by microbial community composition. We sampled topsoils (0–10 cm) from different habitat types in high and low elephant density plots, croplands, and rangelands in savanna woodlands of the Zambezi region, Namibia. The samples were incubated at different temperatures (20-40° C) using a Respicond® apparatus. Microbial biomass and associated community composition were analyzed by DNA analysis. Immediately after rewetting, carbon losses were substantial and amounted to 200 g CO<ce:inf loc=\"post\">2</ce:inf>-C day<ce:sup loc=\"post\">-1</ce:sup>ha<ce:sup loc=\"post\">−1</ce:sup>. High elephant densities had the highest Rh at 25° C (1.21 µg CO<ce:inf loc=\"post\">2</ce:inf> g<ce:sup loc=\"post\">-1</ce:sup>h<ce:sup loc=\"post\">−1</ce:sup>) relative to other land uses (mean 0.75 µg CO<ce:inf loc=\"post\">2</ce:inf> g<ce:sup loc=\"post\">-1</ce:sup>h<ce:sup loc=\"post\">−1</ce:sup>) and significantly higher qPCR copy numbers. Rh was similar under different habitat types. The mean Q10 value during the growing season was comparable under cultivation and high elephant density (∼2.3), exceeding fixed values of land surface models. Warming increased Rh from 0.6 µg CO<ce:inf loc=\"post\">2</ce:inf> g<ce:sup loc=\"post\">-1</ce:sup>h<ce:sup loc=\"post\">−1</ce:sup> at 20° C by a mean factor of 2.6 at 40° C, with the highest increase at high elephant densities (factor 3.4). Generalized linear mixed models identified contents of nitrogen, silt, pH, and land use type as main predictor variables, explaining 57 % of Rh variability. We conclude that savanna soil’s vulnerability to climate warming is comparable between conservation and intensification but that carbon losses due to warming will be highest under wildlife conservation with high elephant densities.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"57 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020009","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}
Global change factors like atmospheric nitrogen (N) deposition and drought pose threats to forest ecosystem including soil microbial diversity. However, how arbuscular mycorrhizal (AM) fungi associated with tree respond to N deposition and drought remains largely unknown. Here root- and soil-inhabiting AM fungi were examined in a field experiment involving N addition and simulated drought (precipitation exclusion) in a Chinese fir (Cunninghamia lanceolata) plantation. The results showed that precipitation exclusion significantly reduced AM fungal intraradical colonization rate in summer, while N addition had no significant effect on AM fungal morphological traits of intraradical colonization rate, hyphal and spore densities. However, seasonal changes significantly affected AM fungal morphological traits, with higher values were observed in summer than in winter. Neither N addition nor drought significantly affected AM fungal diversity or community composition, but AM fungal communities exhibited pronounced seasonal differences. In winter, both root- and soil-associated AM fungal community composition significantly correlated with the ratio of microbial biomass carbon and phosphorus (MBC/MBP), while in summer AM fungal communities were primarily associated with MBP and DOC. These findings highlight the importance of accounting for interaction of N addition and drought, and seasonal response difference on AM fungi in subtropical forest ecosystems.
{"title":"Response of root- and soil-associated AM fungi to nitrogen addition and simulated drought in a Chinese fir plantation","authors":"Jiamian Shi, Xiaojie Li, Ge Song, Shengsheng Jin, Luhong Zhou, Maokui Lyu, Jinsheng Xie, Yalin Hu, Hang-Wei Hu, Ji-Zheng He, Yong Zheng","doi":"10.1016/j.geoderma.2025.117176","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117176","url":null,"abstract":"Global change factors like atmospheric nitrogen (N) deposition and drought pose threats to forest ecosystem including soil microbial diversity. However, how arbuscular mycorrhizal (AM) fungi associated with tree respond to N deposition and drought remains largely unknown. Here root- and soil-inhabiting AM fungi were examined in a field experiment involving N addition and simulated drought (precipitation exclusion) in a Chinese fir (<ce:italic>Cunninghamia lanceolata</ce:italic>) plantation. The results showed that precipitation exclusion significantly reduced AM fungal intraradical colonization rate in summer, while N addition had no significant effect on AM fungal morphological traits of intraradical colonization rate, hyphal and spore densities. However, seasonal changes significantly affected AM fungal morphological traits, with higher values were observed in summer than in winter. Neither N addition nor drought significantly affected AM fungal diversity or community composition, but AM fungal communities exhibited pronounced seasonal differences. In winter, both root- and soil-associated AM fungal community composition significantly correlated with the ratio of microbial biomass carbon and phosphorus (MBC/MBP), while in summer AM fungal communities were primarily associated with MBP and DOC. These findings highlight the importance of accounting for interaction of N addition and drought, and seasonal response difference on AM fungi in subtropical forest ecosystems.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"11 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020010","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}
Hydraulic properties of unsaturated soils are essential for understanding hydric functioning and solving flow and mass-transfer problems in the vadose zone. One of the best-known models for representing the experimental soil–water retention curve, which describes the matric potential (h) as a function of the water content (θ) of a soil horizon, is the van Genuchten (VG) model. It requires four parameters whose values vary by soil type: residual water content (θr), saturated water content (θs), the inverse of the air-entry pressure (α) and a shape parameter (n). The main objective of this study was to show the relevance of using near-infrared (NIR) spectroscopy to estimate the parameters of the VG model, based on the relation established between the soil water spectral index (SWSI) and θ (Soltani et al., 2019a). Based on this approach, the effective saturation of VG equals the effective SWSI. We applied the approach to 25 soil samples collected from topsoil and subsoil horizons in Brittany (western France), which exhibited high variability in texture and soil organic carbon content ranging from 0.07 % to 6.23 %. The results showed that i) the NIR-spectroscopy approach was relevant for estimating hydraulic parameters θs, α and n of the VG model and ii) the parameters obtained from a VG-like equation based on the relation between h and SWSI predicted values of θ of the soil–water retention curve that were similar to observed values, with a root-mean-square error of 0.031 and 0.045 cm3cm−3 for topsoil and subsoil horizons, respectively. The method was thus more accurate for topsoil horizons.
非饱和土的水力特性对于理解渗透带的水力功能和解决渗透带的流动和传质问题至关重要。van Genuchten （VG）模型是最著名的代表实验土壤-水保持曲线的模型之一，它将基质势(h)描述为土壤水平层含水量（θ）的函数。它需要四个参数，其值随土壤类型而变化：残余含水量（θr），饱和含水量（θs），空气进入压力的倒数（α）和形状参数(n)。本研究的主要目的是基于土壤水分光谱指数（SWSI）和θ之间建立的关系，证明使用近红外（NIR）光谱来估计VG模型参数的相关性（Soltani et al., 2019a）。基于该方法，VG的有效饱和度等于有效SWSI。我们将该方法应用于法国西部布列塔尼（Brittany）表层土壤和下层土壤的25个土壤样品，这些土壤样品的质地和土壤有机碳含量在0.07%至6.23%之间具有很高的变异性。结果表明：ⅰ)nir光谱法可用于估算VG模型的水力参数θs、α和n；ⅱ)基于h与SWSI预测的土壤保水曲线θ值的类VG方程得到的参数与观测值基本一致，表层和底土层的均方根误差分别为0.031和0.045 cm3cm−3。因此，这种方法对表层土壤的测量更为精确。
{"title":"Using near-infrared spectroscopy to estimate soil water retention curves with the van Genuchten model","authors":"Youssef Fouad, Inès Soltani, Christophe Cudennec, Didier Michot","doi":"10.1016/j.geoderma.2025.117175","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117175","url":null,"abstract":"Hydraulic properties of unsaturated soils are essential for understanding hydric functioning and solving flow and mass-transfer problems in the vadose zone. One of the best-known models for representing the experimental soil–water retention curve, which describes the matric potential (h) as a function of the water content (θ) of a soil horizon, is the van Genuchten (VG) model. It requires four parameters whose values vary by soil type: residual water content (θ<ce:inf loc=\"post\">r</ce:inf>), saturated water content (θ<ce:inf loc=\"post\">s</ce:inf>), the inverse of the air-entry pressure (α) and a shape parameter (n). The main objective of this study was to show the relevance of using near-infrared (NIR) spectroscopy to estimate the parameters of the VG model, based on the relation established between the soil water spectral index (SWSI) and θ (Soltani et al., 2019a). Based on this approach, the effective saturation of VG equals the effective SWSI. We applied the approach to 25 soil samples collected from topsoil and subsoil horizons in Brittany (western France), which exhibited high variability in texture and soil organic carbon content ranging from 0.07 % to 6.23 %. The results showed that i) the NIR-spectroscopy approach was relevant for estimating hydraulic parameters θ<ce:inf loc=\"post\">s</ce:inf>, α and n of the VG model and ii) the parameters obtained from a VG-like equation based on the relation between h and SWSI predicted values of θ of the soil–water retention curve that were similar to observed values, with a root-mean-square error of 0.031 and 0.045 cm<ce:sup loc=\"post\">3</ce:sup>cm<ce:sup loc=\"post\">−3</ce:sup> for topsoil and subsoil horizons, respectively. The method was thus more accurate for topsoil horizons.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"27 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020011","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}
The karst region is distinguished by pronounced and complex soil erosion, while the bedrock strata dip and root traits significantly influence the erosion slope, thereby altering the hydrodynamic characteristics and impacting Dc. Thus, it is imperative to comprehensively understand the influence mechanism of these factors on Dc in karst trough valley. The samples were collected from two types of natural grassland, Erigeron canadensis (EC; fibrous root system) and Neyraudia reynaudiana (NR; tap root system), as well as bare land (BL) without roots serving as the control. Subsequently, the samples underwent flow scouring in an indoor hydraulic flume at three rock dip angles (15°, 45°, and 65°) and three flow rates (60, 80, and 100 L·min−1) on dip/anti-dip slope. The results indicated that i) the soil organic matter (SOM), water-stable aggregates (WSA), root length density (RLD), root surface area density (RSAD), and root volume density (RVD) on the anti-dip slope were higher compared to those on the dip slope. Additionally, the EC demonstrated the highest abundance in karst trough valley. ii) The Dc of different rock dip angles both dip and anti-dip slopes followed the order of 45° > 65° > 15°. The Dc of two grassland and bare land can be ranked as follows: EC < NR < BL. iii) The Dc of the dip/anti-dip slope showed a significant negative correlation with WSA, root diameter (RD), RLD, RSAD, and RVD (P < 0.05). iv) The results of the multivariate analysis of variance showed that the root traits had the highest contribution rate to Dc, followed by rock dip angles, and bedrock strata dip was the lowest. The resistance of EC to Dc is better under different rock dip angles of the dip/anti-dip slope. Therefore, expanding the coverage of EC across both dip and anti-dip slopes will contribute to mitigating soil erosion and facilitating ecosystem restoration. The research findings enhance the comprehension of soil erosion mechanisms in karst trough valley and facilitate the formulation of effective ecological restoration strategies.
{"title":"Responses of soil detachment capacity to different rock dip angles in karst trough valley","authors":"Lisha Jiang, Fengling Gan, Xiaohong Tan, Hailong Shi, Youjin Yan, Qiuhao Liao, Junbing Pu","doi":"10.1016/j.geoderma.2025.117174","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117174","url":null,"abstract":"The karst region is distinguished by pronounced and complex soil erosion, while the bedrock strata dip and root traits significantly influence the erosion slope, thereby altering the hydrodynamic characteristics and impacting Dc. Thus, it is imperative to comprehensively understand the influence mechanism of these factors on Dc in karst trough valley. The samples were collected from two types of natural grassland, <ce:italic>Erigeron canadensis</ce:italic> (EC; fibrous root system) and <ce:italic>Neyraudia reynaudiana</ce:italic> (NR; tap root system), as well as bare land (BL) without roots serving as the control. Subsequently, the samples underwent flow scouring in an indoor hydraulic flume at three rock dip angles (15°, 45°, and 65°) and three flow rates (60, 80, and 100 L·min<ce:sup loc=\"post\">−1</ce:sup>) on dip/anti-dip slope. The results indicated that i) the soil organic matter (SOM), water-stable aggregates (WSA), root length density (RLD), root surface area density (RSAD), and root volume density (RVD) on the anti-dip slope were higher compared to those on the dip slope. Additionally, the EC demonstrated the highest abundance in karst trough valley. ii) The Dc of different rock dip angles both dip and anti-dip slopes followed the order of 45° > 65° > 15°. The Dc of two grassland and bare land can be ranked as follows: EC < NR < BL. iii) The Dc of the dip/anti-dip slope showed a significant negative correlation with WSA, root diameter (RD), RLD, RSAD, and RVD (<ce:italic>P</ce:italic> < 0.05). iv) The results of the multivariate analysis of variance showed that the root traits had the highest contribution rate to Dc, followed by rock dip angles, and bedrock strata dip was the lowest. The resistance of EC to Dc is better under different rock dip angles of the dip/anti-dip slope. Therefore, expanding the coverage of EC across both dip and anti-dip slopes will contribute to mitigating soil erosion and facilitating ecosystem restoration. The research findings enhance the comprehension of soil erosion mechanisms in karst trough valley and facilitate the formulation of effective ecological restoration strategies.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"74 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020012","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 : 2025-01-16DOI: 10.1016/j.geoderma.2025.117167
Yarong Sun, Senbao Lu, Yunming Chen
Soil carbon dioxide (CO2) release is a critical ecosystem process affecting regional and global carbon cycles. Currently, one of the key uncertainties in projecting carbon-climate feedback is the ongoing poor representation of the deep and nighttime soil CO2 release. Using CO2 probes at hourly intervals in the Robinia. pseudoacacia plantation in the loess hilly regions of China, this study explored the relationship of soil respiration between daytime and nighttime and the discrepancy in the influence of climate, vegetation, and soil properties on soil respiration at the 0–10, 10–50, and 50–100 cm soil depth. We estimated that the cumulative CO2 release at 0–100 cm soil depth reached 688.6 g·m−2·year−1, including a 29.1 % relative contribution from the 10–100 cm soil depths. This outcome showed the necessity for accurate quantification of deep soil CO2 release. We also revealed that the cumulative CO2 release was similar between daytime and nighttime throughout four seasons at the 0–100 cm soil depths. This result demonstrated that soil CO2 release can be predicted based on daytime measurements. Soil temperature < 0℃ was not identified as a primary driver, which only explained 1 %–4% of the variation in soil respiration. Meanwhile, the temperature sensitivity of soil respiration decreased by 1.3–1.8 times when soil temperatures were < 0°C compared to when soil temperatures were > 0°C. Thus, using the correlation model based on soil temperature to predict soil respiration might introduce slight inaccuracies in outcomes when soil temperatures are < 0°C. Soil respiration is intimately associated with soil temperature, soil organic carbon content, root biomass, and leaf carbon content; the cumulative contributions of climate, vegetation, and soil properties to soil respiration were 12 %–18 %, 18 %–30 %, and 41 %–50 % during daytime and 12 %–25 % 24 %–28 %, and 40 %–46 % during nighttime at soil depths of 0–10, 10–50, 50–100 cm. Additionally, Structural Equation Modelling implied that soil moisture and temperature directly affected soil respiration during the daytime, and air temperature and relative humidity acted as indirect factors during the nighttime. Clarifying the cumulative soil CO2 release relationship between the daytime and nighttime could help predict the soil C cycle with high precision within various climates in forest ecosystems.
{"title":"Variations and controlling factors of soil CO2 release at daytime and nighttime scales in the loess hilly regions of China","authors":"Yarong Sun, Senbao Lu, Yunming Chen","doi":"10.1016/j.geoderma.2025.117167","DOIUrl":"https://doi.org/10.1016/j.geoderma.2025.117167","url":null,"abstract":"Soil carbon dioxide (CO<ce:inf loc=\"post\">2</ce:inf>) release is a critical ecosystem process affecting regional and global carbon cycles. Currently, one of the key uncertainties in projecting carbon-climate feedback is the ongoing poor representation of the deep and nighttime soil CO<ce:inf loc=\"post\">2</ce:inf> release. Using CO<ce:inf loc=\"post\">2</ce:inf> probes at hourly intervals in the <ce:italic>Robinia. pseudoacacia</ce:italic> plantation in the loess hilly regions of China, this study explored the relationship of soil respiration between daytime and nighttime and the discrepancy in the influence of climate, vegetation, and soil properties on soil respiration at the 0–10, 10–50, and 50–100 cm soil depth. We estimated that the cumulative CO<ce:inf loc=\"post\">2</ce:inf> release at 0–100 cm soil depth reached 688.6 g·m<ce:sup loc=\"post\">−2</ce:sup>·year<ce:sup loc=\"post\">−1</ce:sup>, including a 29.1 % relative contribution from the 10–100 cm soil depths. This outcome showed the necessity for accurate quantification of deep soil CO<ce:inf loc=\"post\">2</ce:inf> release. We also revealed that the cumulative CO<ce:inf loc=\"post\">2</ce:inf> release was similar between daytime and nighttime throughout four seasons at the 0–100 cm soil depths. This result demonstrated that soil CO<ce:inf loc=\"post\">2</ce:inf> release can be predicted based on daytime measurements. Soil temperature < 0℃ was not identified as a primary driver, which only explained 1 %–4% of the variation in soil respiration. Meanwhile, the temperature sensitivity of soil respiration decreased by 1.3–1.8 times when soil temperatures were < 0°C compared to when soil temperatures were > 0°C. Thus, using the correlation model based on soil temperature to predict soil respiration might introduce slight inaccuracies in outcomes when soil temperatures are < 0°C. Soil respiration is intimately associated with soil temperature, soil organic carbon content, root biomass, and leaf carbon content; the cumulative contributions of climate, vegetation, and soil properties to soil respiration were 12 %–18 %, 18 %–30 %, and 41 %–50 % during daytime and 12 %–25 % 24 %–28 %, and 40 %–46 % during nighttime at soil depths of 0–10, 10–50, 50–100 cm. Additionally, Structural Equation Modelling implied that soil moisture and temperature directly affected soil respiration during the daytime, and air temperature and relative humidity acted as indirect factors during the nighttime. Clarifying the cumulative soil CO<ce:inf loc=\"post\">2</ce:inf> release relationship between the daytime and nighttime could help predict the soil C cycle with high precision within various climates in forest ecosystems.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"38 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020014","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 : 2025-01-16DOI: 10.1016/j.geoderma.2025.117168
Yongping Tong, Yunqiang Wang, Jingxiong Zhou, Meina He, Ting Wang, Yuting Xu, Xiangyu Guo, Mengya Sun, Zimin Li, Bin Shi
Regulating soil drought regime is essential for global ecology and climate security. Indeed, soil drought is largely dependent on rapid climate change, complex soil types, and interaction with vegetations, leading to its spatial and temporal heterogeneity. Previous studies paid less attention on temporal-frequently and spatial-deeply investigations, therefore causing information omission when studying soil drought. This study deployed Fiber Bragg Grating sensors in a 0–30 m profile to monitor deep soil drought with daily resolution under a Robinia pseudoacacia forest in the Chinese Loess Plateau. We aimed at deciphering the distribution, evolution, and determinants of soil drought in an extremely deep profile surpassing the region’s deepest root range. Our experiment identified three typical drought characteristic layers within the deep loess profile: 0–0.4 m (L1), 0.4–1.8 m (L2), and 1.8–30 m (L3). Soil desiccation indices in all three layers of L1, L2, and L3 were 3.56, 0.37, and −0.92, respectively. No drought was observed in L1, while L2 exhibited the most frequent drought changes, and L3 showed a stable and severe drought. These results reveal that both distribution and evolution of deep soil drought exhibited the significant stratified characteristics. For the drought in the entire profile, roots, soil organic carbon, and bulk density acted as the primary factors influenced its spatial distribution. The temporal dynamics of drought were more significantly influenced by temperature, wind speed, and relative humidity than by precipitation. Our analytical results also indicated that synergistic impacts existed when the aforementioned factors affected soil drought distribution and evolution. Considering heterogeneous characteristics and determinants in diverse layers, we suggest a ‘Soil Characteristic Layer Identification–Stratified Governance’ strategy during ecological recovery, to strike a water demand balance between vegetation restoration and soil drought regulation. Our findings therefore offer a reference for deep soil drought evaluation and regulation in loess regions worldwide.
调节土壤干旱对全球生态和气候安全至关重要。事实上，土壤干旱在很大程度上取决于快速的气候变化、复杂的土壤类型以及与植被的相互作用，导致其时空异质性。以往的研究缺乏对时间频次和空间深度的考察，造成了土壤干旱研究的信息遗漏。本研究在黄土高原刺槐林0 ~ 30 m剖面上部署光纤光栅传感器，对土壤深层干旱进行日分辨率监测。我们的目标是在超越该地区最深根系范围的极深剖面中破译土壤干旱的分布、演变和决定因素。在黄土深层剖面中确定了3个典型的干旱特征层：0-0.4 m （L1）、0.4-1.8 m （L2）和1.8-30 m （L3）。1、2、3层土壤干化指数分别为3.56、0.37、- 0.92。L1区未发生干旱，L2区干旱变化最频繁，L3区干旱稳定且严重。这些结果表明，深层土壤干旱的分布和演变都表现出明显的分层特征。在整个干旱剖面中，根系、土壤有机碳和容重是影响其空间分布的主要因素。干旱的时间动态受温度、风速和相对湿度的影响比对降水的影响更显著。分析结果还表明，上述因素对土壤干旱分布和演变的影响存在协同效应。考虑到不同层次的异质性特征和决定因素，我们建议在生态恢复过程中采取“土壤特征层识别-分层治理”策略，以实现植被恢复和土壤干旱调节之间的水分需求平衡。研究结果可为全球黄土深层土壤干旱评价与调控提供参考。
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