Volumetric Soil Water Content Research Articles

Species difference of transpiration in three urban coniferous forests in a semiarid region of China

Tree transpiration and associated evaporative cooling play a critical role in water cycles and combating ‘Urban Heat Islands’ effects. However, species differences in transpiration magnitude, seasonality, and biophysical regulation in dryland urban regions are not well understood. We measured the sap flow of three widely planted coniferous species, Pinus tabulaeformis, Pinus sylvestris, and Picea meyeri, for urban greening, and concurrent soil moisture and meteorological variables in three pure urban forest plantations during three successive growing seasons (May to September during 2017–2019) under a semiarid urban environment in northern China. Stand-level transpiration (Ec) differed significantly among the three species (p < 0.001), where the mean daily Ec of P. tabulaeformis, P. sylvestris, and P. meyeri plantations were 0.78 ± 0.02 mm d–1, 0.68 ± 0.01 mm d–1, and 0.20 ± 0.01 mm d–1, respectively. Additionally, distinct differences in the seasonality of Ec were observed among tree species. Except for 2017, the Ec of P. tabulaeformis and P. sylvestris maintained at low levels in May and June and increased significantly with precipitation in July and August (p < 0.05) when soil volumetric water content (VWC) increased, but the Ec of P. meyeri remained relatively stable throughout the growing season. Responses of Ec in P. tabulaeformis and P. sylvestris plantations to meteorological factors can be changed by soil water availability. Under relatively higher water availability, the Ec of P. tabulaeformis and P. sylvestris were primarily controlled by vapor pressure deficit (VPD) and solar radiation (Rs). Under soil water stress, the Ec of P. tabulaeformis and P. sylvestris were more affected by VWC than P. meyeri. Biologically, P. tabulaeformis had a higher stomatal sensitivity to VPD than P. sylvestris and P. meyeri. At the beginning of growing seasons, the high water use in P. tabulaeformis and P. sylvestris plantations could lead to soil water depletion. Therefore, the species-specific biophysical regulations of tree water use should be carefully considered for urban forest management to achieve ecosystem services by balancing the tradeoff between water consumption and its cooling effects (through evapotranspiration) in semiarid cities.

不同时间尺度下华北落叶松人工林冠层蒸腾与环境因子的关系

PDF HTML阅读 XML下载 导出引用 引用提醒 不同时间尺度下华北落叶松人工林冠层蒸腾与环境因子的关系 DOI: 10.5846/stxb202107151903 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 内蒙古自治区关键技术攻关计划项目(2021GG0033);内蒙古自治区林业和草原局科研能力提升项目;内蒙古自治区自然科学基金项目(2021MS03101) Relationship between canopy transpiration of larch plantation and environmental factors at different time scales Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在半干旱区连续2年监测华北落叶松(Larix principis-rupprechtii)的树干液流、气象因子和土壤体积含水量,分析不同时间尺度下人工林冠层蒸腾与环境因子的关系。结果表明:不同时间尺度下,华北落叶松人工林冠层蒸腾的季节变化均呈单峰曲线,即先增大后减小的趋势;2016年、2017年日蒸腾量分别为1.58 mm/d和1.71 mm/d,生长季蒸腾总量分别为241.30 mm和260.97 mm。在日尺度下,气温、太阳辐射强度和饱和水汽压差是影响华北落叶松人工林冠层蒸腾主要环境因子;月尺度下,气温、风速、降水和土壤水分是冠层蒸腾的主要影响因子;冠层蒸腾与降水、大气相对湿度的相关关系由日尺度下的负相关到月尺度的正相关,相关性增强。总体来看,随时间尺度由小到大,气温、风速、大气相对湿度、降水、土壤水分对冠层蒸腾的影响作用增大,而太阳辐射强度、饱和水汽压差的作用减弱;在未来增温增雨趋势下,研究区生长季将延长,华北落叶松人工林冠层蒸腾量可能会加大。 Abstract:Canopy transpiration is a major part of forestland water balance and a fundamental datum in understanding the planted forest ecophysiology in dry regions. Quantitatively analyzing variation of canopy transpiration induced by the environmental factors is beneficial for a better estimation forestland water balance and prediction the plantation ecophysiology. But the response mechanism of canopy transpiration to environmental factors may be different in different time scales, so it needs to be further understood. This study was conducted in a 42-year-old Larix principis-Rupprechtii plantation (a density of 1933 trees/hm2) at the middle position of a north facing slope in the Inner Mongolian Daqingshan National Nature Reserve, a semi-arid region of China. Firstly, the sap flow velocity in ten healthy and dominant Larix principis-Rupprechtii trees, soil volumetric water content and meteorological factors including air temperature, precipitation, solar radiation intensity, air relative humidity and wind speed, were observed during two growing seasons (May 1 to September 30) in 2016 and 2017 which precipitation was 435.00 mm and 348.80 mm, respectively. Then, sap flow velocity values which was measured by the thermal diffusion method, were upscaled to the forest canopy level. Finally, the relationship between canopy transpiration and the environmental factors at different time scales was analyzed. The results showed that the seasonal changes of canopy transpiration showed a single peak curve under the different time scales, that was, the trend of increase first and then decrease. In 2016 and 2017, the average value of daily canopy-level transpiration was 1.58 mm/d and 1.71 mm/d, respectively, and the total transpiration in the growing season was 241.30 mm and 260.97 mm, respectively. On the daily scale, air temperature, solar radiation intensity and saturated vapor pressure deficit markedly affected canopy transpiration. At the monthly scale, air temperature, wind speed, precipitation and soil volumetric water content were the main influencing factors of canopy transpiration. The correlation between transpiration and precipitation and air relative humidity increased from negative correlation on the daily scale to positive correlation on the monthly scale. In general, with time scale from small to large, the effects of air temperature, wind speed, air relative humidity, precipitation and soil water content on canopy transpiration increase, while the effects of solar radiation intensity and saturated vapor pressure deficit decrease. With the trend of increasing temperature and rainfall in the future, the growing season of Larix principis-Rupprechtii in the study area will be prolonged, and the canopy transpiration may increase. 参考文献 相似文献 引证文献

Optimal Time Domain Reflectometry Penetrometer Design for Soil Water Content and Electrical Conductivity Profiling

Abstract Taiwan has a subtropics monsoon climate and frequently counters typhoons and rainfall, resulting in shallow landslides and landform changes. The significant quantities of soil yields affect the infrastructure safety and environment nearby. Among the influences of factors of safety of the soil slopes, the soil water content (WC) is crucial, and WC and electrical conductivity (EC) profilings of the soil slope assist early warning during a rainfall event. Thus, this study adapted time domain reflectometry (TDR) with the current bipolar type penetrometer to simultaneously measure the volumetric WC (VWC) and the EC in a case study at reservoir watersheds. TDR committed continuous monitoring but with apparent bias because of the insufficient sensing volume of the bipolar type penetrometer. Based on the field experience, this study applied numerical analysis to improve the TDR penetrometer into the dipole type by examining the electrical field, the electrical energy density, and the strain with external stress. After considering all the factors to obtain the optimal design, verifications were accomplished in a sandbox to retrieve measurement performance and the relationship between the soil VWC and the EC in different wetting and drying rates. Results denoted the adequate procedures for TDR on-site monitoring and corresponding calibration of soil VWC and EC for slope stability analysis.

Analysis of soil water potential characteristics of wheat croplands and apple orchards in an agroforestry ecosystem based on the van Genuchten model

Due to intense droughts and water shortages, soil water deficit limits agricultural production in arid and semiarid areas, such as China’s Loess Plateau region. Yet the effects of different cover crops on soil water in these areas have received insufficient attention. This study was conducted in the Weibei rainfed highland to investigate soil water potential dynamics in an agroforestry ecosystem comprising winter wheat (<i>Triticum aestivum</i> L.) and apple (<i>Malus domestica</i>) trees over the apple growth period (March to September of 2020). Soil water characteristic curves (SWCCs) of cropland topsoil (0 to 40 cm), orchard topsoil (0 to 40 cm), dark loessial subsoil (40 to 80 cm), and loess parent material (80 to 150 cm) were determined using the centrifuge method and water vapor equilibrium method. The van Genuchten model was used to fit SWCCs and then convert volumetric soil water content monitored in field plots to soil water potential. A quantitative analysis was conducted to evaluate soil water stress in wheat croplands and apple orchards. The model performed well in fitting SWCCs for all tested soils, yielding a robust accuracy (<i>R</i>² &gt; 0.96). Compared to apple trees, wheat was more threatened by drought. From mid-March to early July, the 0 to 100 cm soil layers of croplands all exhibited high water stress with matric suction pF &gt; 3.98, and unavailable water occurred in the 0 to 20 cm and 0 to 80 cm soil layers in late March to late April and mid-May to mid-July, respectively. Drought threat in apple orchards increased with an increase in tree age. In young orchards (&lt;10 y), high water stress was found only in surface soil layers (0 to 20 cm) in mid-March to late April and late May to early July, which spread to a depth of 70 cm in early June to early July. In mature orchards (10 to 20 y), high water stress was similarly observed in the surface soil layers in mid-March to early May and late May to early July, which extended to the 80 cm depth in late May to early July. In old orchards (&gt;20 y), high water stress initially emerged in the surface soil layers in early April to mid-April and then reached the 70 cm depth in late May to mid-July, whereas unavailable water occurred in the 0 to 60 cm soil layers in mid-June to mid-July. The results indicated that soil water stress zones with low water potential were formed intermittently at different soil depths of apple orchards depending on tree age and growth stage. However, compared to wheat croplands, apple orchards were less influenced by drought stress, so that converting croplands to orchards could alleviate drought threats in the Weibei area.

Comparing Water Use Characteristics of Bromus inermis and Medicago sativa Revegetating Degraded Land in Agro-Pasture Ecotone in North China

Revegetation with herbaceous plants has been effective in neutralizing land degradation; however, there is limited understanding about the water use characteristics and influences on soil water dynamics of revegetated species for ecological restoration. Hence, the stable isotopic composition of xylem water, soil water and groundwater was measured to investigate the water uptake patterns of Bromus inermis and Medicago sativa in the semi-arid agro-pasture ecotone in North China. Based on hierarchical clustering analysis of soil volumetric water content (SWC), soil was classified into four layers (0–5 cm, 5–10 cm, 10–20 cm and 20–30 cm) as different water sources. The main sources for Bromus inermis were from 20–30 cm (27.0%) and groundwater (24.2%) in May, to 0–5 cm (33.9%) and 5–10 cm (26.8%) in June, became groundwater (54.7%) in July, and then to 10–20 cm and 20–30 cm in August (23.2% and 20.6%) and September (35.1% and 32.1%). Medicago sativa were from groundwater (52.9%) and 20–30 cm (32.4%) in May, to 0–5 cm in June (61.0%), July (39.9%), August (47.6%), and then to 5–10 cm (77.8%) in September. Regression analysis showed a negative relationship between SWC and contribution of water uptake (CWU) (CWU = −2.284 × SWC + 60.833), when the difference in water isotopes was small among soil layers. Finally, the two grassland types showed distinct soil water dynamics shaped by species-specific water use strategies and associated soil pore properties. These results indicate that water use characteristics are species specific and a species combination with less water competition is recommended for sustainable revegetation of degraded land.

A Stacked Machine Learning Algorithm for Multi-Step Ahead Prediction of Soil Moisture

A trustworthy assessment of soil moisture content plays a significant role in irrigation planning and in controlling various natural disasters such as floods, landslides, and droughts. Various machine learning models (MLMs) have been used to increase the accuracy of soil moisture content prediction. The present investigation aims to apply MLMs with novel structures for the estimation of daily volumetric soil water content, based on the stacking of the multilayer perceptron (MLP), random forest (RF), and support vector regression (SVR). Two groups of input variables were considered: the first (Model A) consisted of various meteorological variables (i.e., daily precipitation, air temperature, humidity, and wind speed), and the second (Model B) included only daily precipitation. The stacked model (SM) had the best performance (R2 = 0.962) in the prediction of daily volumetric soil water content for both categories of input variables when compared with the MLP (R2 = 0.957), RF (R2 = 0.956) and SVR (R2 = 0.951) models. Overall, the SM, which, in general, allows the weaknesses of the individual basic algorithms to be overcome while still maintaining a limited number of parameters and short calculation times, can lead to more accurate predictions of soil water content than those provided by more commonly employed MLMs.

Seasonal and Soil Use Dependent Variability of Physical and Hydraulic Properties: An Assessment under Minimum Tillage and No-Tillage in a Long-Term Experiment in Southern Italy

Defining the optimal sampling time across the growing season is crucial to standardize sampling protocols for soil physical status monitoring and to achieve comparable results under different experimental conditions and on different sites. In this study, the seasonal variability of soil physical and hydraulic properties under two conservative soil management strategies, minimum tillage and no-tillage, was evaluated in a long-term field experiment. On two sampling dates, autumn 2021 and summer 2022, soil bulk density (BD) and volumetric soil water content at the time of the experiments (θi) were measured in each experimental unit and Beerkan infiltration experiments were performed. The soil water retention curve and the hydraulic conductivity function were then estimated using the Beerkan estimation of soil transfer parameters (BEST) methodology. In this way, the saturated hydraulic conductivity (Ks) and a set of capacitive indicators—plant available water capacity (PAWC), soil macroporosity (PMAC), air capacity (AC) and relative field capacity (RFC)—were obtained. Results underlined the role of soil moisture conditions as a main factor affecting variability in soil physical properties. Different soil moisture under autumn and summer samplings significantly affected BD (1.0093 and 1.1905 g cm−3, respectively, in autumn and summer) and Ks (0.0431 and 0.0492 mm s−1). Relationships observed between BEST-derived variables, such as PMAC (or AC) and RFC, and measured variables, such as BD, showed consistent results, with increases in PMAC to BD decreases. However, a comparison of capacity-based indicators obtained by BEST with those obtained from measured soil water retention curves, in a previous year but under comparable soil conditions, highlighted some discrepancies. This finding drives the focus towards the need to use more robust datasets deriving from experimental measurements or from coupling information obtained from measured and estimated data. Finally, this study provided further evidence that, in the long-term field experiment investigated, the two soil management systems allowed keeping the values of key soil physical quality indicators, such as bulk density and saturated hydraulic conductivity, within the optimal or near- optimal reference ranges.

Continuous Automatic Estimation of Volumetric Water Content Profile During Infiltration Using Sparse Multi-Offset GPR Data

Ground-penetrating radar (GPR) is a non-destructive and non-invasive geophysical survey method that has been used to characterize soil volumetric water content (VWC) dynamics. An array antenna GPR system was used to collect nearly seamless, time-lapse multi-offset GPR data during an in-situ infiltration test on sand dunes with limited traces. Because the data volume was significant, an approach was utilized to automatically determine electromagnetic wave velocities from sparse common midpoint (CMP) data using standard velocity analysis, such as semblance analysis. The objective of this study was to develop a methodology that allows one to automatically perform velocity analysis by interpolating sparse CMP data obtained with the array GPR system. The proposed method determined the optimal normal moveout velocity values and the removal range of the F-K zone pass filter that minimized errors between the original and interpolated CMP data using leave-one-out cross-validation (LOOCV). After interpolating the sparse CMP data with the F-K zone pass filter, semblance analysis was used to determine the time-lapse velocity structure of the soil profile during water infiltration. The velocity data were converted to VWC data based on the Topp equation, which relates the soil VWC to the soil dielectric constant. The proposed method was tested using CMP data obtained via numerical simulation and experiments. The VWC profile from the proposed approach matched well with the independently observed VWC profiles obtained from an invasive probe-type soil moisture sensor.

Physiological Responses and Identification of Drought- Responsive miRNAs in Oil Palm Seedlings under Drought Stress ConditionsResilient Forests

Global climatic change poses a considerable risk to Malaysia’s booming oil palm industry as theinflorescence initiation and differentiation in oil palms are affected by drought stress. As a result, theproportion of female flowers significantly decreases, leading to reduced fruit bunch productivity. Hence, itis crucial for plantation companies to understand the physiological response of different oil palm genotypesto drought stress in ensuring that suitable genotypes are selected for stable yield production. Therefore, thisstudy aimed to understand the physiological and biochemical responses of oil palm seedlings under droughtstress conditions and to identify drought-responsive miRNAs in different oil palm progenies. Drought stresstreatment was imposed on 3-month-old seedlings consisting of two oil palm genotypes, Deli dura x pisifera(BC21) and URT-Calabar (EB8), by withholding irrigation for 20 days. Physiological measurements suchas fluorescence parameter (Fv/Fm) and stomatal conductance (gs) were then carried out weekly. Biochemicalassays were also performed to measure the chlorophyll content and proline concentration. Finally, advancedmolecular techniques were conducted to identify drought-responsive miRNA from drought stress samples.Based on the results, the decreased soil volumetric water content (vwc) resulted in a reduced plant growthrate with low biomass in drought stress BC21T (37%) and EB8T (31%). In addition, the increased prolinecontent in both genotypes by 3.9-fold for BC21T and 1.8-fold for EB8T confirmed the stress condition intreated seedlings. Furthermore, significant differences in gs and Fv/Fm were recorded earlier in BC21 (6days, 14 days) compared to EB8 (14 days, 20 days). The earlier gs reduction indicated that BC21 was moresensitive to drought stress than EB8. Meanwhile, bioinformatics analysis of small RNA sequencing readsidentified 151 conserved miRNAs in both genotypes, with 58 out of 77 identified as novel miRNAs weredifferentially expressed. Apart from that, nine miRNAs were identified as responsive to drought treatmentin both genotypes and played an essential role in various biological processes. Overall, this study providesvaluable insights into exploring oil palm physiological responses to drought and miRNA expressionpatterns, which may facilitate future research on developing drought tolerant markers.

Functional physiological phenotyping and transcriptome analysis provide new insight into strawberry growth and water consumption.

Global warming is expected to increase agricultural water scarcity; thus, optimized irrigation schedules are important and timely for sustainable crop production. Deficit irrigation, which balances crop growth and water consumption, has been proposed, but the critical threshold is not easily quantified. Here, we conducted experiments on strawberry plants subjecting progressive drought following various water recovery treatments on the high-throughput physiological phenotyping system "Plantarray". The critical soil water contents (θcri), below which the plant transpiration significantly decreased, were calculated from the inflection point of the transpiration rate (Tr) - volumetric soil water content (VWC) curve fitted by a piecewise function. The physiological traits of water relations were compared between the well-watered plants (CK), plants subjecting the treatment of rewatering at the point of θcri following progressive drought (WR_θcri), and the plants subjecting the treatment of rewatering at severe drought following progressive drought (WR_SD). The results showed that midday Tr, daily transpiration (E), and biomass gain of the plants under WR_θcri treatment were equivalent to CK during the whole course of the experiment, but those under WR_SD treatment were significantly lower than CK during the water stress phase that could not recover even after rehydration. To explore the gene regulatory mechanisms, transcriptome analysis of the samples collected 12h before, 12h post and 36h post water recovery in the three treatments was conducted. GO and KEGG enrichment analyses for the differentially expressed genes indicated that genes involved in mineral absorption and flavonoid biosynthesis were among the most striking transcriptionally reversible genes under the WR_θcri treatment. Functional physiological phenotyping and transcriptome data provide new insight into a potential, quantitative, and balanceable water-saving strategy for strawberry irrigation and other agricultural crops.

Microbial metabolic responses and CO2 emissions differentiated by soil water content variation in subarctic tundra soils.

Recent rapid air temperature increases across the northern-latitude tundra have prolonged permafrost thawing and snow melting periods, resulting in increased soil temperature (Ts) and volumetric soil water content (SWC). Under prolonged soil warming at 8°C, Alaskan tundra soils were incubated in a microcosm system and examined for the SWC differential influence on the microbial decomposition activity of large molecular weight (MW) humic substances (HS). When one microcosm soil (AKC1-1) was incubated at a constant SWC of 41% for 90 days (T = 90) and then SWC was gradually decreased from 41% to 29% for another T = 90, the initial HS was partly depolymerized. In contrast, in AKC1-2 incubated at a gradually decreasing SWC from the initial 32% to 10% for T = 90 and then increasing to 27% for another T = 90, HS depolymerization was undetected. Overall, the microbial communities in AKC1-1 could maintain metabolic activity at sufficient and constant SWC during the initial T = 90 incubation. In contrast, AKC1-2 microbes may have been damaged by drought stress during the drying SWC regimen, possibly resulting in the loss of HS decomposition activity, which did not recover even after re-wetting to an optimal SWC range (20-40%). After T = 90, the CO2 production in both treatments was attributed to the increased decomposition of small-MW organic compounds (including aerobic HS-degradative products) within an optimal SWC range. We expect this study to provide new insights into the early effects of warming- and topography-induced SWC variations on the microbial contribution to CO2 emissions via HS decomposition in northern-latitude tundra soil.

A newly integrated ground temperature dataset of permafrost along the China–Russia crude oil pipeline route in Northeast China

Abstract. The thermal state of permafrost in the present and future is fundamental to ecosystem evolution, hydrological processes, carbon release and infrastructure integrity in cold regions. In 2011, we initiated a permafrost monitoring network along the China–Russia crude oil pipeline (CRCOP) route at the eastern flank of the northern Da Xing'anling Mountains in Northeast China. We compiled an integrated dataset of the ground thermal state along the CRCOP route consisting of meteorological data near the southern limit of latitudinal permafrost, ground temperature (GT) data in 20 boreholes with depths of 10.0–60.6 m, soil volumetric liquid water contents (VWCs) and 2D electrical resistivity tomography (ERT) data at different sites. Results demonstrate a permafrost warming during 2011–2020 in the vicinity of the southern limit of latitudinal permafrost, as manifested by rising GTs at almost all depths in response to climate warming. Local thermal disturbances triggered by the construction and operation of CRCOPs have resulted in significant permafrost warming and subsequent thawing on the right-of-way (ROW) of the pipelines. This permafrost thaw will persist, but it can be alleviated by adopting mitigative measures, such as an insulation layer and thermosyphons. The in situ observational dataset is of great value for assessing the variability of permafrost under the linear disturbances of the CRCOPs and related environmental effects, for understanding hydro–thermal–mechanical interactions between the buried pipelines and permafrost foundation soils, and for evaluating the operational and structural integrity of the pipeline systems in the future. The dataset is available at the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.272357; Li, 2022).

In situ Soil Moisture Sensors in Undisturbed Soils.

Soil moisture directly affects operational hydrology, food security, ecosystem services, and the climate system. However, the adoption of soil moisture data has been slow due to inconsistent data collection, poor standardization, and typically short record duration. Soil moisture, or quantitatively volumetric soil water content (SWC), is measured using buried, in situ sensors that infer SWC from an electromagnetic response. This signal can vary considerably with local site conditions such as clay content and mineralogy, soil salinity or bulk electrical conductivity, and soil temperature; each of these can have varying impacts depending on the sensor technology. Furthermore, poor soil contact and sensor degradation can affect the quality of these readings over time. Unlike more traditional environmental sensors, there are no accepted standards, maintenance practices, or quality controls for SWC data. As such, SWC is a challenging measurement for many environmental monitoring networks to implement. Here, we attempt to establish a community-based standard of practice for in situ SWC sensors so that future research and applications have consistent guidance on site selection, sensor installation, data interpretation, and long-term maintenance of monitoring stations. The videography focuses on a multi-agency consensus of best-practices and recommendations for the installation of in situ SWC sensors. This paper presents an overview of this protocol along with the various steps essential for high-quality and long-term SWC data collection. This protocol will be of use to scientists and engineers hoping to deploy a single station or an entire network.

Short‐term effects of organic matter and compaction manipulations on soil temperature, moisture, and soil respiration for 2 years in the Oregon Cascades

AbstractUnderstanding the factors controlling nutrient dynamics can help guide forest management plans to promote their long‐term productivity. We used experimental treatments with three levels of biomass removals and two levels of compaction to monitor the impacts to soil biophysical characteristics in an intensively managed forest. Soil temperature, moisture, and respiration observations began 6 mo after treatment installation completion and continued for 2 yr. Compaction had few consistent significant effects on measured variables, and there were negligible differences in volumetric soil water content between whole tree (WT) and bole only (BO) harvesting. Compared with BO, the 10‐cm average and maximum growing season temperatures in WT significantly increased by 1.2 and 2.5 °C, respectively. The effects of WT removals resulted in whole profile (10–100 cm) increases in the average and maximum growing season soil temperatures. The WT removals resulted in an increase of 1.4 times more soil growing degree days (SGDD) at 10 cm and 1.6 times more at 100 cm compared with BO. Despite favorable temperature and moisture conditions, differences in soil respiration could not be explained by biomass or compaction treatments. The uncut reference forest was consistently cooler and drier, but respired more CO2 throughout both years of observation compared with treated areas. The large physical disturbance of forest harvesting on the site likely masked any incremental treatment differences by homogenizing the microbial response in the ensuing 2‐yr study period. Future research should continue to investigate whether these soil biophysical changes influence site productivity or more sensitive indices of soil C dynamics.

Investigating the Spatial Structure of Soil Hydraulic Properties in a Long-Term Field Experiment Using the BEST Methodology

Understanding the spatial structure of soil properties at field scale and introducing this information into appropriate data analysis methods can help in detecting the effects of different soil management practices and in supporting precision agriculture applications. The objectives of this study were: (i) assessing the spatial structure of soil physical and hydraulic properties in a long-term field experiment; (ii) defining a set of spatial indicators for gaining an integrated view of the studied system. In seventy-two georeferenced locations, soil bulk density (BD), initial volumetric soil water content (θi) and cumulative infiltration curve as function of the time (I(t)) were measured. The soil water retention curve (θ(h)) and the hydraulic conductivity function (K(h)) were then estimated using the Beerkan Estimation of Soil Transfer parameters (BEST) methodology. The volumetric soil water contents at soil matrix (h = −10 cm), field capacity (h = −100 cm) and wilting point (h = −15,300 cm) were considered. In addition, a set of capacitive indicators—plant available water capacity (PAWCe), soil macroporosity (PMACe), air capacity (ACe) and relative field capacity (RFCe)—were computed. The data were first analyzed for overall spatial dependence and then processed through variography for structural analysis and subsequent spatial interpolation. Cross-correlation analysis allowed for assessing the spatial relationships between selected physical and hydraulic properties. On average, optimal soil physical quality conditions were recorded; only PMACe values were indicative of non-optimal conditions, whereas mean values of all the other indicators (BD, Ks, PAWCe, ACe, RFCe) fell within optimal ranges. The exponential model was found to be the best function to describe the spatial variability of all the considered variables, except ACe. A good spatial dependence was found for most of the investigated variables and only BD, ACe and Ks showed a moderate autocorrelation. Ks was confirmed to be characterized by a relatively high spatial variability, and thus, to require a more intensive spatial sampling. An inverse spatial cross-correlation was observed between BD and Ks up to a distance of 10 m; significant cross-correlations were also recorded between Ks and PMACe and ACe. This result seems to suggest the possibility to use these soil physical quality indicators as covariates in predictive multivariate approaches.

Effects of soil drought and nitrogen deposition on BVOC emissions and their O3 and SOA formation for Pinus thunbergii

Soil drought and nitrogen (N) deposition can influence the biogenic volatile organic compound (BVOC) emissions and thereby their ozone (O3) and secondary organic aerosol (SOA) formation. This study addressed their single and combined effects on BVOC emissions of Pinus thunbergii by laboratory simulation experiments. The results showed that light drought (LD, 50% soil volumetric water content (VWC)) stimulated isoprene, monoterpene, sesquiterpene, and total BVOC emissions, while moderate drought (MD, 30% and 40% VWC) and severe drought (SD, 10% and 20% VWC) inhibited their emissions (except for sesquiterpene in 20% VWC). N deposition decreased other VOC emissions and increased isoprene and sesquiterpene emissions. Total BVOCs and monoterpene were stimulated in low N deposition (LN, 2 g N/(m2·yr)) and inhibited in moderate (MN, 5 g N/(m2·yr)) and high N deposition (HN, 10 g N/(m2·yr)). Under combined treatment of soil drought and N deposition, total BVOC, monoterpene, and other VOC emissions were inhibited, sesquiterpene had no significant change, and isoprene emission was inhibited in MD combined treatment but promoted in SD. The O3 formation potential (OFP) and SOA formation potential (SOAP) from the changed BVOC emissions were calculated, OFP and SOAP of BVOC emissions and their compositions varied significantly among the treatments. Our study provided theoretical basis for assessing the impact of climate change and atmospheric pollution on BVOC emissions and their contribution to the formation of secondary atmospheric pollution.

Soil nutrient release and microbial changes after burning of masticated fuels

AbstractSoil temperature extremes are not uncommon when woody fuels are ignited in prescribed burns or wildfires. Whether this leads to substantial loss of soil organic matter or microbial life is unclear. We created a soil heat gradient by burning four levels of masticated woody fuels (0, 34, 101, and 169 Mg ha−1) to determine if heat thresholds produce abrupt changes in soil C, N, microbial biomass, or fungal hyphae. Twenty‐four burns were conducted with masticated fuels overlaying a clay loam soil equilibrated at either 4 or 25% volumetric soil water content. Maximum temperatures ranged from 40 to 450 °C depending on fuel load and soil moisture content, with heat duration (&gt;60 °C) as great as 22 h. Moist soil quenched temperatures two‐ to threefold compared with dry soil at comparable fuel loads. A slight, gradual decline in total C and N was found with increasing temperature and heat duration, reaching a maximum loss of 14–18% of the total at the highest heat load. Available NH4 increased linearly starting at 150–175 °C and reached a maximum 15‐fold increase relative to unburned soil by 450 °C. Nitrification (30 d post‐fire) was low regardless of treatment and was essentially eliminated at the highest temperatures. Microbial biomass declined curvilinearly with increased heating, approaching 65% loss compared with unburned soil, and was most rapid in moist soil once temperatures exceeded 60–70 °C. Ultimately, we found no evidence of abrupt heat thresholds for these common soil properties. Instead, property changes followed a slightly declining trajectory (soil C, N, NO3, fungal hyphae) or a steady incremental increase (NH4) or decrease (microbial biomass).

Topographic Wetness Index as a Proxy for Soil Moisture in a Hillslope Catena: Flow Algorithms and Map Generalization

Topographic wetness index (TWI) is used as a proxy for soil moisture, but how well it performs across varying timescales and methods of calculation is not well understood. To assess the effectiveness of TWI, we examined spatial correlations between in situ soil volumetric water content (VWC) and TWI values over 5 years in soils at 42 locations in an agroforestry catena in Fayetteville, Arkansas, USA. We calculated TWI 546 ways using different flow algorithms and digital elevation model (DEM) preparations. We found that most TWI algorithms performed poorly on DEMs that were not first filtered or resampled, but DEM filtration and resampling (collectively called generalization) greatly improved the TWI performance. Seasonal variation of soil moisture influenced TWI performance which was best when conditions were not saturated and not dry. Pearson correlation coefficients between TWI and grand mean VWC for the 5-year measurement period ranged from 0.18 to 0.64 on generalized DEMs and 0.15 to 0.59 for on DEMs that were not generalized. These results aid management of crop fields with variable moisture characteristics.

Parameterizing the AquaCrop model for potato growth modeling in a semi-arid region

The AquaCrop model was used to model potato growth in a hot semi-arid environment under diverse irrigation managements including water saving irrigation treatments in two growing seasons of 2012 and 2013. The potato cultivars were Agria and Ramos in 2012, and Agria and Sante in 2013. The irrigation treatments were full irrigation and different static and dynamic deficit irrigation managements. The model was calibrated with the data of the cultivar Agria under full irrigation and static deficit irrigation in 2013. Validation was performed using the data from the other potato cultivars and growing seasons, by keeping the conservative crop parameters adjusted in calibration and changing those non-conservative parameters referring to the crop development. Analysis showed that biomass simulation was highly affected by the normalized water productivity (WP*). Unlike the previous studies on modeling with AquaCrop that assumed only one WP* for the whole growing period, we found that it is required to calibrate one WP* for the first half of the growing season until flowering, and then recalibrated WP* for the late growing season. One single WP* assumed for the whole growing season could not simulate the declining potato growth at the late growing season satisfactory, when potatoes were subject to water stress and high air temperature (heat stress). The simulations of the calibrated model showed that the model could simulate total soil water content, volumetric soil water content, and tuber dry yield satisfactory. In addition, the model showed excellent performance in simulation of the total actual evapotranspiration and end-season water productivity. The AquaCrop model was good in simulating the in-season biomass, though it showed fair simulation of biomass in the late growing season. Overall, the performance of the AquaCrop model was reasonable and satisfactory, and the model is a reliable analytical tool for irrigation water management and proper decision making in potato production under variable water resources in the hot semi-arid areas. • AquaCrop has been used for modeling potato growth in a hot and semi-arid region. • AquaCrop had satisfactory performance in simulating soil water content and tuber dry yield. • AquaCrop had excellent performance in simulating end-season actual evapotranspiration and water productivity. • Two WP* values were assumed to differentiate the effects of water and heat stresses on different growing periods. • The calibrated WP* was assigned 13 and 10 g m −2 during the early and late growing season, respectively.

A new combined penetrometer-dielectric-low frequency acoustic-electrical conductivity sensor for measuring the soil physical characteristics

Development of simple and economical sensors to measure the soil physical properties is of great importance in precision agriculture. Building on a previous study with a fusion of penetrometer, dielectric and high-frequency acoustic sensors, the present work was aimed to develop a combined penetrometer-dielectric-microphone-apparent electrical conductivity (ECa) sensor to present a cost-effective instrument for measuring the soil physical properties. The multi-sensor probe consists of a cone connected to a load cell, an integrated dielectric-ECa sensor and a microphone inside the cone to record the passive sound produced at the soil-cone interface. To evaluate the multi-sensor probe, soils with different textural compositions (clay content from 142 to 537 g kg-1) were remoulded at three levels of water content and three levels of bulk density. The probe was tested in vertical penetration tests using a hydraulic loading frame. The results of acoustic signal processing using principal component analysis showed satisfactory differentiation between coarse and fine-grained texture classes. The output of the dielectric sensor was related to soil volumetric water content with R2 = 0.81 with some texture dependency. With fusion of penetrometer, dielectric and microphone sensors, R2 increased to 0.9 with RMSE= 0.031 m3 m-3. The soil relative density was predicted from data fusion of penetrometer, dielectric and microphone sensors with a regression model with R2 = 0.86 and RMSE= 3.11%. The ECa sensor showed rational responses to the concentration of NaCl solution as well as decreased the RMSE of soil water content and relative density prediction when fused with the other sensors. The multi-sensor probe developed is an economical instrument for simultaneously measuring the soil physical properties. Field evaluations are needed to further evaluate the sensor in wider range of soil texture and soil characteristics as well as in on-the-go measurement to be applied in precision agriculture.