Highlights What are the main findings? Identified the sensitive wavelength band for precise severity monitoring at each disease stage. Developed a classification model to assess disease severity across different stages. What are the implications of the main findings? The identified sensitive wavelength bands provide a basis for non-destructive and precise remote sensing monitoring of disease severity. The stage-specific classification model enables accurate assessment of walnut leaf necrosis severity and supports disease monitoring and management.Highlights What are the main findings? Identified the sensitive wavelength band for precise severity monitoring at each disease stage. Developed a classification model to assess disease severity across different stages. What are the implications of the main findings? The identified sensitive wavelength bands provide a basis for non-destructive and precise remote sensing monitoring of disease severity. The stage-specific classification model enables accurate assessment of walnut leaf necrosis severity and supports disease monitoring and management.Abstract Walnut leaf necrosis causes leaf desiccation and premature abscission, substantially reducing photosynthetic efficiency, impairing fruit development, and ultimately leading to yield loss and quality deterioration. In severe cases, it accelerates branch senescence or even whole-tree mortality, resulting in considerable economic damage to the walnut industry. Rapid and accurate monitoring of this disease is therefore essential for sustainable production. This study aimed to characterize the different stages of walnut leaf necrosis using spectral analysis and develop classification models for stage-specific identification. Leaf samples representing healthy leaves and the early, middle, and late stages of necrosis were analyzed for spectral responses. Sensitive bands were identified using the variable importance in projection (VIP), successive projections algorithm (SPA), and the combined VIP-SPA method, and corresponding vegetation indices were constructed. The selected features were incorporated into classification models based on random forest (RF), extreme gradient boosting (XGBoost), and convolutional neural networks (CNNs). Results revealed that the red-edge (640-700 nm) and near-infrared (720-1000 nm) regions were identified as key diagnostic spectral ranges. Among the vegetation indices evaluated, the Simple Ratio Index (SRI) calculated from reflectance at 705.7 nm and 707.1 nm, the Normalized Difference Index (NDI) using the same band pair, and the Difference Index (DI) derived from 417.1 nm and 638.7 nm emerged as the most sensitive indicators of disease severity. Classification accuracies for different necrosis stages reached 0.9583, 0.9583, and 0.9333, respectively. These findings demonstrate that the identified spectral bands and vegetation indices provide robust tools for monitoring the progression of walnut leaf necrosis.

Tracking the sap flux of woody plants in savannas is essential for understanding their response to climate change and human management. Solar-induced fluorescence (SIF) has potential to predict transpiration yet its applicability for estimating savanna sap flux is unclear. Using three years of tower-based far-red SIF observations and ground-based sap flow monitoring in a temperate savanna of Otindag Sandy Land, China, we investigated the relationship between far-red SIF and sap flux density and developed linear and random forest models for estimating. The results show a variable correlation between SIF and sap flux density for Ulmus pumila var. sabulosa (J.H. Xin) G.H. Zhu & D.H. Bian (U. pumila.) at an hourly scale. The strongest correlations were during the mid- growth period July and August when considering the time lag between SIF and sap flux (0-0.5 h). Photosynthetically active radiation was the primary factor driving the SIF and sap flux density relationship. Soil moisture, vapor pressure deficit, and air temperature also influenced this relationship on daily and monthly scales. Compared to SIF-based linear regression models, the SIF-based random forest model performed better in tracking the seasonal sap flux density. The results suggest the feasibility of accurately monitoring vegetation sap flux using SIF, woody fractional vegetation cover, and environmental factors in a temperate savanna. This method could also be used in modeling land surface processes in savanna-type ecosystems.

Quantifying photosystem II (PSII) open reaction centers (qL) and their relationship with electron transport rate (ETR) is crucial for understanding photosynthetic dynamics across spatial scales. However, accurate estimation of these photosynthetic variables remains challenging due to observational constraints and complex environment-ecosystem feedbacks under dynamic conditions. A novel approach to mechanically quantify the qL and linear electron transport rates (JPSII) from PSII to photosystem I (PSI) using solar-induced chlorophyll fluorescence (SIF) at leaf and canopy scales was established, termed the SIF-qL redox model. The simulation was validated at two evergreen forest sites (ZGT and DEJU) using continuous pulse-amplitude modulated (PAM) chlorophyll fluorescence and flux measurements. At the leaf-scale, the model demonstrated high accuracy in predicting qL for needleleaf vegetation in ZGT (R2 = 0.82, RMSE = 0.09), but performed poorly in DEJU (R2 = 0.45). The model accurately simulated JPSII dynamics at both sites at the leaf level (R2 = 0.92-0.97). When scaled to canopy level, the model maintained reliable predictive capability for JPSII (R2 = 0.62-0.71). The simulations captured distinct qL dynamics: at ZGT, qL declined with increasing PAR, particularly at lower temperatures, while DEJU showed minimal temperature-dependent variation. The observed JPSII- qL relationships revealed that Ribulose-1,5-bisphosphate (RUBP) generation limitations on JPSII were dominant at both sites. This study developed a SIF-qL redox model to mechanistically connect chlorophyll fluorescence with photosynthetic dynamics, while validating the cross-scale applicability of leaf-level parameters in canopy-scale simulations. Future refinements should address species- and environment-specific adaptations to enhance the universal applicability of the ecosystem photosynthesis process.

Growing evidence has revealed δD offsets in soil-plant water systems, contradicting the long-held hypothesis of isotopic non-fractionation during plant water absorption. We aimed to determine whether δD offsets exist for plants in walnut (Juglans regia L.) -alfalfa (Medicago sativa L.) intercropping system and to explore the effects of intercropping and plant species on δD offsets. We conducted an analysis of the isotopic signatures of soil and plant water, calculated δD offsets utilizing the soil water excess (SW-excess) equation across varying seasons from 2021 to 2023 in walnut-alfalfa intercropping, monocropping walnut, and monocropping alfalfa systems. The findings revealed that all plant systems exhibited δD offsets with distinct seasonal variations. Specifically, walnuts and alfalfa displayed noteworthy positive δD offsets during dry-1 season (1.43 and 2.98‰) and substantial negative δD offsets during the rainy season (-8.80 and -12.25‰). Additionally, walnut exhibited negative δD offsets (-7.53‰) in dry-2 season, while alfalfa showed no δD offsets. The δD offset patterns in intercropped and monocropped plants remained consistent across different seasons, with no significant disparities between them. Correlation analyses indicated that walnut δD offsets were negatively associated with air humidity and soil moisture content, yet positively correlated with saturated vapor pressure difference; whereas, alfalfa δD offsets were notably negatively correlated with air temperature and relative humidity. Our findings suggest that δD offset may be a prevalent phenomenon, unaffected by intercropping patterns but significantly influenced by plant species. Compared to walnuts, alfalfa displayed higher sensitivity to climatic factors, resulting in a more pronounced offset magnitude.

Walnut (Juglans regia L.) is an important oilseed crop, and salt stress threatens the growth of walnut tree. In this study, NO3− or NH4+ was applied at three concentrations (4, 32, and 100 mM) to investigate the effect of NO3−-N and NH4+-N on walnut seedlings under 100 mM NaCl stress. Results showed that moderate (32 mM) NO3−-N application alleviated the effect of salt stress. Moreover, plants treated with 32 mM NO3−-N showed no significant morphological difference from those subjected to the nonstress treatment. The treatment of 32 mM NO3−-N application enhanced plant growth, increased antioxidant enzyme activities (superoxide dismutase and catalase), and restricted Na⁺ and Cl⁻ uptake and transport. Additionally, it might induce beneficial shifts in the rhizosphere microbiome. Low-concentration (4 mM) NO3⁻ or NH4⁺ treatment individually induced the minor alleviation of salt stress. By contrast, 100 mM NO3⁻ and all tested concentrations of NH₄⁺ further inhibited biomass and root growth, thereby exacerbating salt injury. Notably, 100 mM NH₄⁺ caused severe defoliation and seedling mortality. Furthermore, in contrast to its NO3− counterpart, 32 mM NH4⁺ shifted the root microbiome and impaired microbial diversity, likely contributing to increased salt sensitivity. This study demonstrates that moderate NO3⁻ application can effectively mitigate salt stress during walnut growth, offering a potential strategy for fertilizing walnut plantations under saline conditions.

Accurately evaluating the water status of walnuts in different growth stages is fundamental to implementing deficit irrigation strategies and improving the yield of walnuts. The crop water stress index (CWSI) based on the canopy temperature is one of the most commonly used tools for current research on plant water monitoring. However, the suitability and effectiveness of using the CWSI as an indicator of the walnut water status under field conditions are still unclear. This paper focuses on walnut orchards in Northwest China using synchronous monitoring of the canopy temperature, meteorological parameters, and water physiological parameters of walnut trees under both full irrigation and deficit irrigation treatments. The aim is to test the effectiveness of the simplified crop water stress index (CWSIs) and the theoretical crop water stress index (CWSIt) in tracking the diurnal and daily variations of the water conditions in walnut orchards. The CWSIs can reflect the diurnal and daily changes in the water status of walnut orchards. It was found that the CWSIs at 12:00 local time had the best performance in tracking the daily changes in the water status. Compared to the daily averaged CWSI calculated using the measured transpiration (CWSITr_day), the correlation coefficient, index of agreement, and root mean squared error between the CWSIs and CWSITr_day were 0.82, 0.94, and 0.11, respectively. However, due to the calculation errors of the aerodynamic resistance in walnut trees, the CWSIt was unable to track the diurnal variations in the water status in walnut orchards and the degree of water stress was underestimated. In addition, the variations in minimum canopy resistance in the various growth stages of walnut orchards may also affect the accuracy of the CWSIt in terms of indicating the seasonal changes in the water status. The CWSIs provides a non-destructive, quickly and effective method for monitoring the water status of walnuts. However, the results of this study suggest that the effects of aerodynamic resistance parameterization and variations in minimum canopy resistance in the various growth stages of walnut orchards in the CWSIt calculation should be noted.

Land use change affects the balance of organic carbon（C） reserves and the global C cycle.Microbial residues are essential constituents of stable soil organic C（SOC）. However, it remains unclear how microbial residue changes over time following afforestation. In this study, 16-, 23-, 52-, and 62-year-old Mongolian pine stands and 16-year-old cropland were studied in the Horqin Sandy Land,China. We analyzed changes in SOC, amino sugar content, and microbial parameters to assess how microbial communities influence soil C transformation and preservation. The results showed that SOC storage increased with stand age in the early stage of afforestation but remained unchanged at about 1.27-1.29 kg/m2 after 52 a. Moreover, there were consistent increases in amino sugars and microbial residues with increasing stand age. As stand age increased from 16 to 62 a, soil pH decreased from 6.84 to 5.71, and the concentration of total amino sugars increased from 178.53 to 509.99 mg/kg. A significant negative correlation between soil pH and the concentration of specific and total amino sugars was observed, indicating that the effects of soil acidification promote amino sugar stabilization during afforestation. In contrast to the Mongolian pine plantation of the same age, the cropland accumulated more SOC and microbial residues because of fertilizer application. Across Mongolian pine plantation with different ages, there was no significant change in calculated contribution of bacterial or fungal residues to SOC, suggesting that fungi were consistently the dominant contributors to SOC with increasing time. Our results indicate that afforestation in the Horqin Sandy Land promotes efficient microbial growth and residue accumulation in SOC stocks and has a consistent positive impact on SOC persistence.

Accurate tracking Savanna woody plants hydraulics is the key step to understand its response to climate change and human management. Great inaccuracy existed in estimating vegetation hydraulics of Savanna ecosystem. Solar-induced fluorescence (SIF) has shown the potential to predict vegetation transpiration but the possibility of using it in vegetation hydraulics estimation of Savanna is not clear. Based on three years tower observed far-red SIF and ground sap flow monitoring in a temperate savanna of Otindag sandy land, China, we explore the relationship between far-red SIF and sap flux density and build up a SIF based random forest model for sap flux density estimation. Our results showed that SIF was linear related to sap flux density for elm (Ulmus pumila var. sabulosa) tree markedly at daily (R2=0.62-0.68, p < 0.001) vs. hourly scale (R2=0.47-0.56, p < 0.001). The predominant correlations of SIF-sap flux density were observed during the U. pumila.'s medium growth period (July & August). Photosynthetic active radiation (PAR) is the major driver for SIF and sap flux density relationship. Soil moisture, vapor pressure deficit (VPD) and air temperature influence the SIF-sap flux density relationship on the daily and monthly scale. By employing machine learning algorithm, with SIF, woody fractional vegetation coverage (FVC) and environmental factors (PAR, air temperature and VPD) as predictors, SIF based model proposed a great performance in tracking seasonal U. pumila.'s sap flux density (R2=0.71; RMSE=0.003). Our results confirmed the possibility of accurately monitoring vegetation hydraulics by SIF, woody FVC and environmental factors in temperate Savanna. This method could be also used in land surface process modelling of Savanna type sparse vegetation ecosystem.

The lower limit temperature in the crop water stress index (CWSI) model refers to the canopy temperature (Tc) or the canopy-air temperature differences (dT) under well-watered conditions, which has significant impacts on the accuracy of the model in quantifying plant water status. At present, the direct estimation of lower limit temperature based on data-driven method has been successfully used in crops, but its applicability has not been tes-ted in forest ecosystems. We collected continuously and synchronously Tc and meteorological data in a Quercus variabilis plantation at the southern foot of Taihang Mountain to evaluate the feasibility of multiple linear regression model and BP neural network model for estimating the lower limit temperature and the accuracy of the CWSI indicating water status of the plantation. The results showed that, in the forest ecosystem without irrigation conditions, the lower limit temperature could be obtained by setting soil moisture as saturation in the multiple linear regression mo-del and the BP neural network model with soil water content, wind speed, net radiation, vapor pressure deficit and air temperature as input parameters. Combining the lower limit temperature and the upper limit temperature determined by the theoretical equation to normalize the measured Tc and dT could realize the non-destructive, rapid, and automatic diagnosis of the water status of Q. variabilis plantation. Among them, the CWSI obtained by combining the lower limit temperature determined by the dT under well-watered condition calculated by the BP neural network model and the upper limit temperature was the most suitable for accurate monitoring water status of the plantation. The coefficient of determination, root mean square error, and index of agreement between the calculated CWSI and measured CWSI were 0.81, 0.08, and 0.90, respectively. This study could provide a reference method for efficient and accurate monitoring of forest ecosystem water status.

Many studies have been conducted on organic carbon changes under different land use patterns, but studies and data concerning changes in the molecular composition of soil organic matter (SOM) during land use conversion are scarce. In this work, we studied the chemical composition of SOM on two Robinia pseudoacacia L. plantations and their adjacent croplands in the Loess Plateau using biomarker and nuclear magnetic resonance (NMR) techniques. Experimental data on the molecular composition of SOM showed that the soil microbial biomass carbon content initially decreased and then returned to the original level gradually after afforestation, while the SOM content and stocks increased over time. At the initial stage of afforestation, the content of total solvent extracts did not change significantly but changed slowly over time in the plantations without artificial disturbance. With an increase in restoration time, the concentrations of both the microbial- and plant-derived solvent extracts increased. Moreover, the concentrations of plant-derived solvent extracts were consistently lower than those of microbial-derived solvent extracts. Afforestation also significantly increased the lignin-derived phenol content in the surface soil layer (0–10 cm). However, no obvious change was observed in the lignin-derived phenols of the two adjacent croplands. These results indicate that the accumulation of aboveground litter and underground roots has the strongest effects on the lignin-derived phenol content. In contrast to cropland, the two plantations exhibited a high degree of degradation of lignin-derived phenols in the surface soil, but this remained almost unchanged over time. Moreover, in contrast to 20 years after the establishment of the R. pseudoacacia plantation, the low alkyl/O-alkyl carbon ratio of the 8-year R. pseudoacacia plantation indicated that more easily degradable components accumulated during the initial stage of afforestation. Therefore, the proportion of the unstable carbon pool was relatively high and the SOM content may decline in the early stage of afforestation. These results provide evidence illustrating the detailed changes in the chemical composition of SOM during the ecological restoration process.

Soil thermal conductivity (λ) is an important physical parameter in agricultural, meteorological, and geophysical processes. Few datasets are available for investigating the response of the λ in soils containing different salts. In this study, we compared the effects of different salt types and contents on the λ of quartz sand and determined the changes in λ of various salt-affected soils before and after salt leaching. Quartz sand and different types of salt with different contents were mixed, and various salt-affected soils were collected. The λ of different samples with a series of known water contents was determined by using a portable thermal property tester. The salts did not influence the λ of the sand in the dry state or at relatively high moisture contents. At intermediate moisture contents, the λ was lower by 0.11 W m−1 K−1, 0.07 W m−1 K−1, and 0.05 W m−1 K−1 for the sand with chloride, sulfate, and bicarbonate, respectively, than that of soil without the salts. The salinity insignificantly influenced the λ of the sand with 3–9 g kg−1 salts when the salt content in the sand was greater than 3 g kg−1 for most salt types. The effects of salt type on the decrease in λ followed the order of chloride > sulfate > bicarbonate. The λ of quartz sand with added CaCl2 and KCl decreased the greatest, followed by soil with NaCl and MgCl2. After washing away salts, λ increased significantly by 13.1

Solar-induced chlorophyll fluorescence (SIF) is a rapidly developed remote sensing technology and has been used to estimate leaf-level net CO2 assimilation by a mechanistic light reaction (MLR-SIF) equation. However, the application of this model would be limited by the challenging measurement and estimation of input parameters (e.g., fraction of open PSII reaction centres, qL). We modified the MLR-SIF model by replacing qL by the easily obtained parameters (non-photochemical quenching [NPQ]) to facilitate its application. We employed synchronous measurements of gas exchanges, ChlF parameters and SIF for Leymus chinensis, Populus tomentosa Carrières and Ulmus pumila var. sabulosa under the soil–water deficit and rehydration process to test the robustness of the modified MLR-SIF model. Our results demonstrated that for L. chinensis the net photosynthesis rate dynamics under severe drought stress and saturated water condition were effectively captured by the modified MLR-SIF model (R2 = 0.75–0.92, RMSE = 1.11–3.56). For P. tomentosa Carrières and U. pumila var. sabulosa, the net photosynthesis rates were predicted by the modified MLR-SIF model with good accuracy (R2 = 0.86, RMSE = 9.44; R2 = 0.88, RMSE = 4.16) across the water deficit and rehydration condition. However, the electron transport rate estimated by the modified MLR-SIF model uncoupled with the photosynthetic capacity (r2 = −0.13) and lowered the net photosynthesis rate simulation precision (R2 = 0.35, RMSE = 3.41) for L. chinensis under mild drought stress and saturated light intensities. The electron transport rate estimated by the modified MLR-SIF model downregulated the photosynthetic capacity for P. tomentosa Carrières (r2 = 0.32) and U. pumila var. sabulosa (r2 = 0.22) under mild drought stress. The shift of the Rubisco and RUBP limited state cross-points, the dynamic photosynthesis parameters across the plant species and the alternative electron sinks under soil–water deficit and rehydration process influenced the simulation precision of the modified MLR-SIF model. Our modified MLR-SIF model provided a basis for understanding and inferring the photosynthetic rate by SIF and NPQ under drought stress.

The soil thermal conductivity (λ) and matric suction of soil water (h, the negative of matric potential) relationship has been widely used in land surface models for estimating soil temperature and heat flux following the McCumber and Pielke (1981, MP81) λ-h model. However, few datasets are available for evaluating the accuracy and feasibility of the MP81 λ-h model under various soil and moisture conditions. In this study, we developed a new λ-h model and compared its performance with that of the MP81 model using measurements on 18 soils with a wide range of textures, water contents and bulk densities. The heat pulse technique was used to measure λ, and the suction table, micro-tensiometers, pressure plate device, and the dew point potentiometer were applied to obtain soil water retention curves at the appropriate suction ranges. In the range of pF (the common logarithm of h in cm)≤3, the λ-h relationships were highly nonlinear and varied strongly with soil texture and bulk density. In the dry range (i.e., pF > 3), there existed a universal λ-h relationship for all soil textures and bulk densities, and an exponential function was established to describe the relationship. Independent evaluations using λ-h data on five intact soil samples showed that the new model produced accurate λ data from pF values with root mean square errors (RMSE) with the range of 0.03–0.18W m−1 K−1. While, large errors (RMSEs within 0.17–0.36W m−1 K−1) were observed with λ estimates from the MP81 model.

Over the past several decades, a vegetation restoration project has been conducted in the southeastern Loess Plateau of China by converting cropland into forest plantations to combat soil erosion. However, the effects of land use change on soil fertility are poorly documented. Here, we assessed soil chemical properties in areas of the southeastern Loess Plateau following afforestation of cropland with Robinia pseudoacacia plantations that had been established for 16 years and 49 years, a 49-year-old naturally restored forest, and adjacent cropland. We found that the effect of afforestation on soil organic carbon and total nitrogen mainly occurred at shallow depths. Soil organic carbon and total nitrogen concentrations in the topsoil of both 49-year-old forests were significantly higher than those in cropland. However, the highest total phosphorus concentrations were observed in the topsoil of cropland due to the application of fertilizer. The nitrogen-fixing effect of leguminous Robinia pseudoacacia was not obvious through comparisons of soil total nitrogen within 49-year-old naturally restored and planted forests. Our results indicate that both natural restoration and planting can increase soil organic carbon stocks, but that the increase after 16 years is slight. In this experiment, we found that soil organic carbon concentrations were negatively correlated with soil pH for all four land use patterns, and that the strength of the correlation increased with time since restoration. In contrast to cropland and naturally restored forest, plantations of both ages showed soil acidification across their entire profiles. This may be due to the root exudate and rhizosphere environment created by R. pseudoacacia. These results provide important insights about the impacts of ecological restoration on soil chemical properties in the Loess Plateau and elsewhere.

通过测定两种土壤和一种玻璃珠的两相热导率随气压的变化,分析变压条件下气体分子碰撞平均自由程和多孔介质孔隙结构间的关系.研究计算了表征土壤平均孔隙结构的孔隙特征长度(d),同时依据静态几何学方法计算获取了颗粒平均间距(D).结果表明,基于热传输方法获取的d值是从气体分子碰撞传热的动态观点获取的孔隙结构表征,标识着土壤颗粒间的热分离特征,是表征土壤孔隙结构的有效指标.由于土壤的d和D值相差3个数量级,但在玻璃珠上无量级差异,这说明d值可能只能表征土壤团聚体间的平均孔隙结构,不能反映团聚体内部及黏土颗粒内部的微细孔隙结构.

The soil water retention curve represents the relationship between soil water content (theta) and matric potential (psi). The van Genuchten (vG) model is commonly used to characterize the shape of a theta(psi) curve. Based on the similarities between theta(psi) curves and soil thermal conductivity (lambda) versus theta curves, Lu and Dong proposed a unified conceptual lambda(theta) model (LD model) for estimating lambda(theta) curves from theta(psi) curves. Their work makes it possible to relate the shapes of lambda(theta) curves to theta(psi) curves. In this study, we present an empirical approach to estimate the vG model parameter m from the LD model shape parameter p based on a model calibration with theta(psi) and lambda(theta) datasets obtained from 10 soils. The saturated water content theta s and the vG model parameter alpha are estimated from selected soil properties (i.e., bulk density, particle density, particle size distribution and organic carbon content), and the residual water content theta r is estimated from the LD model parameter theta f. For model evaluation, the theta(psi) curves of six soils were estimated from measured lambda(theta) values and selected soil properties, and were compared to direct theta(psi) measurements. The proposed method performed well with root mean square errors of estimated theta values ranging from 0.015 to 0.052 cm3 cm-3 and bias ranging from -0.009 to 0.040 cm3 cm-3. We conclude that the proposed method accurately estimates theta(psi) curves from lambda(theta) curves and selected soil properties.

Soil thermal conductivity (λ) is affected by the energy status of water and is closely related to soil matric potential (h). In this study, a soil water retention curve and a soil thermal conductivity curve were linked via the critical point that separated the adsorption water and capillary water regimes. Based on existing water retention curve and a thermal conductivity curve models, we derived a new implicit mathematical formulation of the λ-h relationship. The λ-h relationship was valid for the entire water content range at room temperature. The new model parameter values for adsorption, capillarity and soil thermal conduction were optimized, and a linear relationship between critical water content and maximum adsorption capacity was established by fitting the SWRC and STCC models to measurements from eight soils. Laboratory evaluations using λ and h measurements on a loam soil and a clay loam soil showed that the new model well described observed values with coefficients of determination greater than 0.97. The implicit model can quantify λ-h behaviors for various soil textures over the entire water content range.

Knowledge on the components of apparent soil thermal conductivity (λ) across various water contents (θ) and temperatures is important to accurately understand soil heat transfer mechanisms. In this study, soil thermal conductivity was measured for sandy loam and silty clay soils at various temperatures and air pressures using a transient method. Four components of λ, namely, heat conduction, latent heat transfer by water vapor diffusion, sensible heat transfer by liquid water, and sensible heat transfer by water vapor diffusion were quantified. Results showed that in uniform soils, the magnitudes of sensible heat transfers by liquid water and water vapor were negligible during these transient measurements. The contribution of latent heat transfer through vapor diffusion to total heat transfer increased as temperature increased, and the peak value occurred at an intermediate water content. The water content at which the maximum vapor diffusion occurred varied with soil texture. In addition to the four calculated components, a significant residual contribution to λ caused by an unidentified vapor transfer mechanism was observed between 3.5°C and 81°C. For example, calculations indicated that approximately 66% of the sandy loam λ at θ=0.11 m3 m−3 was caused by an unidentified vapor transfer mechanism at 81°C. This extra contribution by vapor transfer could be explained either as enhanced vapor diffusion or by an advection mechanism. Further investigation is needed to clarify whether enhanced diffusion or advection is occurring in unsaturated soils.

Soil thermal conductivity is an important parameter for estimating soil heat flux and soil thermal regime. Knowledge on the components of apparent soil thermal conductivity (lambda) across various water contents (theta) and temperatures is important to accurately understand soil heat transfer mechanisms. In this study, soil thermal conductivity was measured for sandy loam and silty clay soils at various temperatures and air pressures using a transient method. Four components of lambda, namely, heat conduction, latent heat transfer by water vapor diffusion, sensible heat transfer by liquid water, and sensible heat transfer by water vapor diffusion were quantified. Results showed that in uniform soils, the magnitudes of sensible heat transfers by liquid water and water vapor were negligible during these transient measurements. The contribution of latent heat transfer through vapor diffusion to total heat transfer increased as temperature increased, and the peak value occurred at an intermediate water content. The water content at which the maximum vapor diffusion occurred varied with soil texture. In addition to the four calculated components, a significant residual contribution to lambda caused by an unidentified vapor transfer mechanism was observed between 3.5 degrees C and 81 degrees C. For example, calculations indicated that approximately 66% of the sandy loam lambda at theta=0.11 m(3) m(-3) was caused by an unidentified vapor transfer mechanism at 81 degrees C. This extra contribution by vapor transfer could be explained either as enhanced vapor diffusion or by an advection mechanism. Further investigation is needed to clarify whether enhanced diffusion or advection is occurring in unsaturated soils.

土地利用变化影响土壤团聚性及有机碳分布,进而改变土壤碳循环过程.对太行山南部50年刺槐人工林(R50)、17年刺槐人工林(R17)、自然恢复林(NR)和农田(CL)等不同土地利用方式下的表层土壤(0-20 cm)进行了系统研究,利用湿筛法对土壤团聚体进行分级,并计算土壤结构稳定性参数(平均重量直径MWD,团聚体比例AR)及不同粒径团聚体有机碳贡献率,进而分析弃耕后土壤团聚体分布及团聚体有机碳含量变化.结果 表明,土地利用方式对土壤团聚体粒径分布及团聚体有机碳含量有显著影响,自然恢复林与刺槐林的大团聚体(＞0.25 mm)含量都高于农田,且自然恢复林的大团聚体增加更显著.MWD的计算结果表明:自然恢复林＞刺槐人工林＞农田,说明该区域的自然恢复方式更容易促进大团聚体的形成,并显著改良土壤结构及增强土壤团聚体稳定性.弃耕后,不同土地利用方式0-10 cm土层各粒径团聚体有机碳含量均高于农田,且团聚体有机碳含量与团聚体稳定性呈正相关.这些结果说明,研究区域的自然植被恢复和人工造林都可以显著提高土壤的固碳能力,且储存的有机碳主要存于大团聚体中,而农田的有机碳大都存于粘粒+粉粒团聚体中.自然植被恢复和人工造林均提高了土壤结构稳定性,是改善团粒结构、提高土壤质量的有效方式.