Daily Soil Temperature Research Articles

Effects of High Tunnel Soil Solarization on Sclerotinia sclerotiorum in the Temperate Climate of Central Kentucky.

Diseases caused by Sclerotinia spp. can affect a wide range of plants, including vegetables, with yield losses ranging from 10 to 50%. Sclerotinia diseases can be especially problematic in high tunnels where high-value vegetable crops are planted in early spring to extend the growing season, achieve earlier harvest, and bring higher profits. Fungicide applications and crop rotations are limited due to product application restrictions and constraints on time, crop resistance, and profitability. Soil solarization is a cultural management method that uses transparent polyethylene to raise soil temperatures via solar irradiation to kill pathogens, pests, and weeds. A two-year study was conducted in a Kentucky high tunnel to determine the maximum temperature potential of solarization at various soil depths at different durations during different seasons and to identify temperatures at which S. sclerotiorum sclerotia lose viability. The experiment included solarization treatments of 2, 4, and 6 weeks and a non-solarized control implemented in spring, summer, and fall. Sclerotia and temperature data loggers were buried at 5.1, 10.2, and 15.2 cm soil depths. The number of hours at which soil temperatures reached ≥ 40 °C was greatest in summer in both years, followed by fall, and then spring. The highest average daily maximum soil temperature reached was 48.9°C, which occurred during the summer 6-week solarization in Year 1. The viability of buried sclerotia was overall lower in solarized treatments compared to non-solarized treatments in both years. In general, the 2-week solarization treatment had significantly higher percent sclerotial germination than the 4-week and 6-week treatments, which were not significantly different from one another. The viability of sclerotia was progressively higher with burial depth. In both years, sclerotia germination was significantly lower in summer compared to spring and fall.

Utilization of the Google Earth Engine for the evaluation of daily soil temperature derived from Global Land Data Assimilation System in two different depths over a semiarid region

AbstractThe Google Earth Engine (GEE) was used to investigate the performance of the Global Land Data Assimilation System (GLDAS) soil temperature (ST) data against observed ST from 13 synoptic stations over a semiarid region in Iran. Three‐hourly ST data were collected and analyzed in two depths (0–10 cm; 40–100 cm) and 5 years. In each depth, GLDAS‐Noah ST data were evaluated for daily minimum, maximum, and average ST (i.e., Tmin, Tmax, and Tavg). Based on the correlation coefficient, Kling–Gupta Efficiency, and Nash–Sutcliffe Efficiency the overall performance of the GLDAS‐Noah is 0.96, 0.66, and 0.79 for Tmin; 0.97, 0.84, and 0.89 for Tavg; and 0.95, 0.89, and 0.89 for Tmax, respectively in the first layer. Likewise, 0.97, 0.85, and 0.86 for Tmin; 0.97, 0.77, and 0.80 for Tavg; and 0.97, 0.69, and 0.69 for Tmax are obtained in the second layer. However, there is a significant negative bias which tends to underestimate ST in the two investigated layers, given by an average bias over all the stations analyzed of −24%, −12%, and −5% for Tmin, Tavg, and Tmax in the first layer, and average bias of −8%, −13%, and −17% for Tmin, Tavg, and Tmax in the second layer. This study reveals that GLDAS‐Noah‐derived ST can be used in arid regions where little or no observation data is available. Moreover, GEE performed as an advanced geospatial processing tool in regional scale analysis of ST in different layers.

Soil freeze/thaw dynamics strongly influences runoff regime in a Tibetan permafrost watershed: Insights from a process-based model

The Tibetan Plateau (TP) is a region rich in extensive frozen ground and the source of many major Asian rivers. However, how soil freeze/thaw (F/T) dynamics influence runoff production at the catchment scale in the TP is poorly understood. This study employs a process-based permafrost hydrology model with a new soil parameterization to investigate soil F/T dynamics and their impact on runoff in a TP permafrost watershed, i.e., the source region of Yangtze River (SRYR). The revised model separates soil evaporation and plant transpiration, and accounts for the influence of soil gravel and organic carbon content, as well as variation in saturated hydraulic conductivity along the soil profile. Validation results demonstrate that the revised model accurately simulates daily soil temperature (mean RMSE of 1.3 °C), soil moisture (mean ubRMSE of 0.05 cm3 cm−3), and runoff discharge (NSE = 0.82). The results reveal different altitudinal patterns of warming trend between permafrost and seasonally frozen ground (SFG). Warming rates in SFG area increase monotonously with elevation, while a turning point is observed in permafrost region around 4800 m. With active layer deepening, deep-soil water content increases but primarily replenishes soil water storage rather than directly contributing to runoff recharge, while rootzone and the middle part of the active layer become drier. Soil F/T cycles in the permafrost region exert stronger influences on runoff process compared to SFG. Delayed soil thaw onset generally results in higher spring runoff coefficient, while delayed soil freeze onset is related to slower runoff recession. The freezing zero-curtain period is likely to impact the continuity of runoff recession processes by affecting the connectivity of groundwater flow channels. These findings uncover the regulatory mechanisms of soil F/T dynamics on runoff production and river discharge characteristics, providing a fundamental basis for predicting permafrost hydrology responses to future climate change in the TP.

Effect of strip tillage widths on soil moisture, soil temperature and soil structure in northeast China

Strip tillage is an effective tillage technique, which included the strip seedbed tilled area (ST-IR) and the straw-covered area between the seedbeds (ST-BR). However, soil hydrothermal conditions and soil disturbance varies with strip tillage widths, which might affect crop growth and yields. Therefore, this study explored the effect of strip tillage width on the soil hydrothermal conditions and soil structure of ST-IR and ST-BR, to determine the optimal strip tillage width. A field experiment with three replicates was conducted to analyze soil moisture and soil temperature variation and to clarify the difference of soil structure in the IR and BR. Three strip tillage widths, 20 cm (ST20), 30 cm (ST30), and 40 cm (ST40), were examined in this study. Soil temperature in both the ST-IR and ST-BR increased as the strip tillage width increased, and the average soil temperature of ST30-IR and ST40-IR in the seedling stage was 2.11°C and 2.62°C higher than that of ST20-IR, respectively. Moreover, the daily soil temperature range in both the IR and BR was greater for ST40 than for ST20 and ST30 in the seedling stage; soil temperature differences in other crop growth stages were small. No significant difference in soil temperature was observed between ST30-IR and ST40-IR. Conversely, soil moisture was greater in ST20-IR and ST30-IR than in ST40-IR; soil moisture was also greater in ST30-BR and ST40-BR than in ST20-BR during the monitoring period. Soil moisture in ST40-IR and ST20-BR increased and decreased more rapidly during rainfall events than in the other treatments. Moreover, soil temperature was higher in the ST-IR than in the ST-BR for all 3 strip tillage widths, and the opposite results were observed for soil moisture. In addition, strip tillage widths had no significant differences on soil structure. In conclusion, a 30 cm strip tillage width had higher soil temperature and remained more soil moisture than other strip tillage widths, so this strip tillage width is thus recommended for use by farmers in Northeast China.

Effects of biochar versus film mulching on soil hydrothermal properties and wheat crop performance in semi‐arid loess

AbstractFilm mulching and biochar have been applied as effective measures for increasing crop yields in arid and semi‐arid areas for many years. However, the effects of the temporal and spatial distributions of soil hydrothermal properties on crop yields are still unclear under film mulching and biochar addition. Thus, we conducted a field experiment with winter wheat on the Loess Plateau of China for two years (2020–2022) with three treatments: control, film mulching, and biochar. The results demonstrated that film mulching and biochar addition increased the average soil temperature in the 0–50 cm soil depth throughout the whole growth period and the influence depth exceeded 50 cm. Biochar addition only significantly increased soil temperature in the overwintering stage (p < 0.05). Film mulching increased the maximum and minimum temperatures in the 0–50 cm soil depth at seedling stage. Film mulching and biochar increased average ≥10°C accumulated soil temperature by increasing the ≥10°C accumulated soil temperature in the daytime and nighttime, and the number of days with a daily soil temperature ≥10°C during the whole growth period. Film mulching improved soil water storage in the 0–300 cm soil depth in each growth stage during both years, and also increased the wheat grain yield, aboveground biomass, and water use efficiency. Biochar addition increased the wheat grain yield and aboveground biomass of two years compared with control, but the increases were not significant (p > 0.05). In addition, correlation analysis showed that adequate temperatures in the 0–50 cm soil depth during the seedling and overwintering stages, and suitable soil moisture conditions in the 0–300 cm soil depth before sowing, jointing, and filling stages were important factors for increasing wheat grain yields under film mulching. In summary, film mulching mainly regulated the soil temperature in the 0–50 cm soil depth and moisture conditions in the 0–300 cm soil depth during different growth stages to increase grain yields. Film mulching has more obvious effects on moisture regulation, temperature regulation, and yield increases than biochar addition. Some environmentally friendly measures (such as conservation agriculture) with the same yield improving effect as mulching are also recommended to explore and promote in theLoess Plateau region.

Daily soil temperature simulation at different depths in the Red River Basin: a long short-term memory approach

Daily soil temperature simulation at different depths in the Red River Basin: a long short-term memory approach

Evaluation of the Potential of Using Machine Learning and the Savitzky–Golay Filter to Estimate the Daily Soil Temperature in Gully Regions of the Chinese Loess Plateau

Soil temperature directly affects the germination of seeds and the growth of crops. In order to accurately predict soil temperature, this study used RF and MLP to simulate shallow soil temperature, and then the shallow soil temperature with the best simulation effect will be used to predict the deep soil temperature. The models were forced by combinations of environmental factors, including daily air temperature (Tair), water vapor pressure (Pw), net radiation (Rn), and soil moisture (VWC), which were observed in the Hejiashan watershed on the Loess Plateau in China. The results showed that the accuracy of the model for predicting deep soil temperature proposed in this paper is higher than that of directly using environmental factors to predict deep soil temperature. In testing data, the range of MAE was 1.158–1.610 °C, the range of RMSE was 1.449–2.088 °C, the range of R2 was 0.665–0.928, and the range of KGE was 0.708–0.885 at different depths. The study not only provides a critical reference for predicting soil temperature but also helps people to better carry out agricultural production activities.

Responses of phenology to preseason drought and soil temperature for different land cover types on the Mongolian Plateau

Drought and heat caused major disturbance in nature by interfering with plant phenology, and can also alter the vulnerability and resilience of terrestrial ecosystems. Existing research on the Mongolian Plateau has primarily focused on studying the response of the start (SOS) and end (EOS) of the growing season to drought and heat variations. However, there is still a lack of comprehensive understanding regarding the coupled effects of drought and heat on phenology across different land cover types. In this study, we retrieved SOS and EOS based on 34-year (1982–2015) normalized difference vegetation index (NDVI) dataset from Global Inventory Modeling and Mapping Studies (GIMMS). Results showed that grasslands and the Gobi-Desert show rapid advancement in SOS, and forests presented the slowest advancement in SOS, but SOS in croplands were delayed. EOS across four land cover types advanced, with the Gobi-Desert showed the highest rate of advancement and forests the lowest. Using the Palmer Drought Severity Index (PDSI) and soil temperature as the indicators of drought and thermal conditions, the responses of SOS and EOS to these two climate variables were evaluated. The advanced SOS driven by lower drought severity was detected in forests, grasslands, croplands and the Gobi-Desert. The dominant response of EOS to drought severity was positive in croplands, grasslands and forests, except for the Gobi-Desert, where drought severity had negative effects on EOS. Compared with the daily average soil temperature (STmean), the daily maximum soil temperature (STmax, daytime), and the daily minimum soil temperature (STmin, nighttime), the daily diurnal soil temperature range (DSTR, where DSTR = STmax − STmin) between night and day were the most suitable indicators for assessing the response of SOS and EOS to soil temperature. Strong negative correlation between SOS and the preseason DSTR was pronounced in all land cover types on the Mongolian Plateau. However, EOS was negatively correlated with the preseason DSTR only in the Gobi-Desert. Last but not least, normalized sensitivity assessments reveal that the negative impacts of DSTR on SOS and EOS were the main controlling factors on the Mongolian Plateau phenology, followed by the couple negative effects of drought severity and DSTR.

Seasonal Variations in the Toughness of Leaves: A Case Study Using Griselinia littoralis.

Potential effects of climate change include greater extremes of temperature and increased severity of storms. Many plants have evolved to resist the challenges of winter (freezing, dehydration, and wind) in a process known as cold hardening. Sensing reducing temperatures, they make structural changes at the cellular level to increase their mechanical resistance and prevent damage. Previous work on this topic, though extensive, has been conducted under laboratory conditions rather than in the field, and while many workers have observed changes to cell wall thickness and composition, which imply increased mechanical strength, few have actually measured strength or any other parameter describing structural integrity. This paper describes experiments on a model system designed to measure the structural integrity of leaf laminae from plants growing naturally in the field over extended periods, allowing seasonal variations to be captured. Standard engineering properties-tensile strength and fracture toughness-were measured for leaves of Griselinia littoralis on 19 separate occasions over a 12-month period. Toughness (rather than strength) was found to be the controlling mechanical property. Toughness values were found to change significantly during the year, by more than a factor of 2. Toughness correlated strongly with average daily soil temperature, but with a lag of about 1-2 weeks, suggesting that this is the time needed for structural adjustments to take place. Highest toughness values occurred in winter, confirming cold hardening. Increasing temperature in the spring was associated with decreasing toughness, but in the summer, when highest temperatures occurred, toughness increased again. This apparent "hot hardening" may be a response to dehydration. Results imply that a given leaf is able to both increase and decrease its toughness in response to temperature changes, demonstrating excellent plasticity of response. This case study of a single species establishes a method of reliably measuring changes in a plant's structural integrity due to cold hardening and other seasonal variations, which may be used to investigate the effects of climate change and other variables.

Effects of inorganic mulching on soil hydrothermal environment and tomato characters in the presence of unheated greenhouse cultivation

The present study was conducted by cultivating tomato (Solanum lycopersicum ‘Provence’) using varied inorganic mulching to investigate soil hydrothermal environment and tomato characters under unheated greenhouse cultivation in the cold zone of China. A total of 6 different treatments were adopted: no mulching (control), white film mulching (white film), black film mulching (black film), the white film with hole mulching (white hole), the black film with hole mulching (black hole), and snake skin bag mulching (snake skin). Inorganic mulching treatment significantly improved soil temperature and moisture, water use efficiency, tomato yield, and reduced soil water consumption. There was no significant difference observed in the variation of daily mean soil temperature between different mulching treatments, and the variation was in the range of 1.95–2.20 °C, which was significantly lower compared with the control (3.42 °C). The daily mean soil moisture varied significantly after different mulching treatments, with the highest level achieved by snake skin (23.37%), followed by black hole (22.55%), white hole (22.08%), white film (21.48%), black film (20.12%), and control (18.78%) in descending order. According to the research results, plastic-hole mulching, which include white hole and black hole treatments, performed better in maintaining soil temperature and moisture.

Development of a robust daily soil temperature estimation in semi-arid continental climate using meteorological predictors based on computational intelligent paradigms.

Changes in soil temperature (ST) play an important role in the main mechanisms within the soil, including biological and chemical activities. For instance, they affect the microbial community composition, the speed at which soil organic matter breaks down and becomes minerals. Moreover, the growth and physiological activity of plants are directly influenced by the ST. Additionally, ST indirectly affects plant growth by influencing the accessibility of nutrients in the soil. Therefore, designing an efficient tool for ST estimating at different depths is useful for soil studies by considering meteorological parameters as input parameters, maximal air temperature, minimal air temperature, maximal air relative humidity, minimal air relative humidity, precipitation, and wind speed. This investigation employed various statistical metrics to evaluate the efficacy of the implemented models. These metrics encompassed the correlation coefficient (r), root mean square error (RMSE), Nash-Sutcliffe (NS) efficiency, and mean absolute error (MAE). Hence, this study presented several artificial intelligence-based models, MLPANN, SVR, RFR, and GPR for building robust predictive tools for daily scale ST estimation at 05, 10, 20, 30, 50, and 100cm soil depths. The suggested models are evaluated at two meteorological stations (i.e., Sulaimani and Dukan) located in Kurdistan region, Iraq. Based on assessment of outcomes of this study, the suggested models exhibited exceptional predictive capabilities and comparison of the results showed that among the proposed frameworks, GPR yielded the best results for 05, 10, 20, and 100cm soil depths, with RMSE values of 1.814°C, 1.652°C, 1.773°C, and 2.891°C, respectively. Also, for 50cm soil depth, MLPANN performed the best with an RMSE of 2.289°C at Sulaimani station using the RMSE during the validation phase. Furthermore, GPR produced the most superior outcomes for 10cm, 30cm, and 50cm soil depths, with RMSE values of 1.753°C, 2.270°C, and 2.631°C, respectively. In addition, for 05cm soil depth, SVR achieved the highest level of performance with an RMSE of 1.950°C at Dukan station. The results obtained in this research confirmed that the suggested models have the potential to be effectively used as daily predictive tools at different stations and various depths.

Dynamics and variability of microclimate in an unmanaged mountain forest after a bark beetle outbreak

Forest disturbances alter hydrological, energy, and microclimatic characteristics and their extents vary with the landscape characteristics of the terrain. We evaluated changes in evapotranspiration and latent heat rate in an unmanaged, central European mountain forest (Norway spruce) after a bark beetle-induced mortality of >75 % trees, and the spatial variability in microclimate during its natural regeneration. We observed that (1) the annual mean incident solar radiation to the treeless plots was 8.2 MJ m−2 day−1 (95 W m−2), being reduced by ∼45 % compared to its theoretical flux by high average cloudiness (70.6%) and short daily sunshine (4.3 hour day−1). The observed energy input to the forest floor beneath survived canopies (1.2 MJ m−2 day−1) was an order of magnitude lower than solar radiation to the canopy surface. (2) The mean annual evapotranspiration and the average annual latent heat rate decreased by 155 mm yr−1 and 385 MJ m−2 yr−1 (12 W m−2), respectively, after tree dieback. (3) The soil and air temperatures at individual plots correlated positively with the incident solar radiation and negatively with elevation. Mean soil and air temperatures exhibited similar lapse rates of 5.9–8.0 °C km−1 during the growing season (May-October). The energy input (positive relationship) and elevation (negative relationship) explained 74–83 % of the between-plot variability in mean soil and air temperatures and 51–77 % of their daily amplitudes during the growing season. (4) On sunny days, the observed soil and air temperatures were significantly lower (by ∼50 and 15 %, respectively) than ground surface temperature based on thermal satellite data (Landsat-8). The ground surface temperature explained 80–92 % of the observed variability in the soil and air temperatures. (5) The between-plot differences in daily soil and air temperatures and their amplitudes were from 24 to 70 % explained by solar radiation (positive correlation) and relative air humidity and wind speed (negative correlations).

Insights into variations of seasonal and daily soil temperatures under the effect of biocrusts in central-western Argentina

Background and Aims: Biocrusts play an essential role on the earth’s surface and have a direct influence on soil parameters. Their effects on soil temperature are considered one of the most important because they affect ecological and hydrological processes, as well as the diversity of natural ecosystems. Although there are several studies concerning biocrust effects on the soil surface, investigations about the effect of the biocrust on soil temperature are still scarce. Our objective was to evaluate the influence of biocrusts on soil temperature conditions in drylands of central-western Argentina. Methods: Temperature values were recorded in the Monte phytogeographic region in the central-western part of Argentina, in three sites, during the dry and wet seasons in 2017-2018. We collected samples from a total of 30 randomly selected plots. We recorded daily temperatures values in two paired plots with crusted and uncrusted zones using a calibrated data logger Ibutton. The sampling took 18 days in total, three days on each site.Key results: Our results indicate that biocrusts produce a change in micro-soil temperatures. Areas in which biocrusts are present show a temperature reduction both in the wet and dry seasons. This effect is observed in the three studied sites. Temperature reduction varies according to the time of the day, study site and season. The morning, noon, and afternoon recorded the highest mean temperatures.Conclusions: The presence of biocrusts reduces soil temperatures in drylands of central-western Argentina. Large differences in mean temperature values between crusted and uncrusted zones were observed. The thermal reduction was more notorious in the hyper-arid site. How they affect their surrounding environment can be related to multiple factors, such as the composition of the microphytic community, the local climate and environmental conditions.

Short-term effect of different returning methods of maize straw on the temperature of black soil plough layer

Clarifying the effect of different maize straw returning methods on soil temperature is crucial for optimizing the management of farmland straw and the efficient utilization of heat resources in the black soil region of Northeast China. To investigate the impacts of straw returning methods on soil temperature, we conducted a field experiment with four treatments during 2018 and 2020, including plough tillage with straw returning (PTSR), rotary tillage with straw returning (RTSR), no-tillage with straw returning (NTSR), and a control treatment of conventional ridge tillage without straw returning (CT). We measured soil temperature and water content at the 5 cm, 15 cm and 30 cm soil layer, and the straw coverage rate during the 3-year maize growth period. We further analyzed the differences of soil temperature in different soil layer under different treatments, accumulated soil temperature and growing degree-days (GDD) above 10 ℃, daily dynamics of soil temperature, the production efficiency of air accumulated temperature among different treatments, and explored factors causing the difference of soil temperature and the production efficiency of air accumulated temperature. Our results showed that different treatments mainly affected soil temperature from the sowing to emergence stage (S-VE) of maize. The daily average soil temperature showed a trend of CT>PTSR>RTSR>NTSR. The differences of soil temperature under different treatments showed a decreasing trend as growth process advanced and soil depth increased. Compared with the CT treatment, soil temperature at 5 cm depth was decreased by 0.86, 1.84 and 3.50 ℃ for PTSR, RTSR, and NTSR treatments, respectively. NTSR significantly reduced the accumulated temperature of ≥10 ℃ in different soil layers and GDD. The accumulated temperature ≥ 10 ℃ at the 5, 15, and 30 cm soil layers decreased by 216.2, 222.7, and 165.1 ℃·d, and the GDD decreased by 201.9, 138.7 and 123.9 ℃·d, respectively. In addition, production efficiency of air accumulated temperature decreased by 9.7% to 15.6% for NTSR. Conclusively, PTSR and RTSR had significant impacts on topsoil temperature during the maize growing period from sowing to emergence, but did not affect the accumulated soil temperature and the production efficiency of air accumulated temperature. However, NTSR significantly reduced topsoil temperature and production efficiency of air accumulated temperature.

Effects of Artificial Green Land on Land–Atmosphere Interactions in the Taklamakan Desert

Land–atmosphere interactions are influenced by the earth’s complex underlying subsurface, which in turn indirectly affects atmospheric motion and climate change. Human activities are increasingly exerting an influence on desert ecosystems, and artificial green land with clear functional orientation has been established in many desert areas. Consequently, the previously dominant, shifting, sand-covered, underlying surface in these desert regions is gradually transforming. This transformation has significant implications for the characteristics of land–atmosphere interactions, causing them to deviate from their original state. At present, existing studies still have not presented a systematic understanding of this change and have ignored the impact of human activities on land–atmosphere interactions in artificial green land. To address these research gaps, this study specifically targets artificial green land in the Tazhong region of Taklamakan Desert. We carried out observation experiments on land–atmosphere interactions in three different functional units from outside to inside: natural shifting sands, the shelter forest, and the living area. We also analyzed the differences and attribution of land–atmosphere interactions characteristics of different functional units. Compared with the natural shifting sands, the daily average maximum values of wind speed in the shelter forest decreased by 78%, and the daily average maximum air temperature and soil (0 cm) temperature decreased by 2.6 °C and 7 °C, respectively. Additionally, the soil moisture level was significantly increased throughout the green land due to the shelter forest. The surface albedo experienced a decrease, with an annual average of 0.21. Furthermore, the aerodynamic roughness and bulk transport coefficient increased by two orders of magnitude. The daily average maximum values of sensible heat flux and soil heat flux (G05) decreased by 18.7% and 75%, respectively, and the daily average maximum value of latent heat flux increased by 70.3%. This effectively improved the microclimate environment of the green land. The living area was greatly reduced by the shelter forest coverage and influenced by the buildings. Consequently, the environmental improvement was not as large as it was inside the shelter forest. However, it still provided a good shelter for production and living in the desert area. Throughout the year, a total of 4.60 × 105 t water was consumed through evapotranspiration in the artificial green land. The findings of this study have the potential to enhance our comprehension of land–atmosphere interactions in desert regions, thereby offering valuable insights for the establishment and effective management of artificial desert green lands.

Examining the bias of pitfall traps with enclosure experiments and removal sampling

Abstract Pitfall trapping is among the most widely used sampling methods for ground‐dwelling beetles. However, the sampled ground‐dwelling beetle abundance in pitfall traps may be biased, which can lead to difficulties when comparing the sampled abundance between different habitats. To better understand the comparability of the sampled abundance, we focused on two sampling processes: a temporary migration process (referring to the individual movements into and out of the effective trap area) and a removal process (determining the number of individuals collected given the number of individuals within the trap area). To examine the effects of the temporary migration process, we compared the sampled abundance of 10 ground‐dwelling beetle species inside and outside enclosures in 2 habitats (clear‐cut and forested sites) and found that installing the enclosure decreased the sampled abundance in both habitats, but the effects did not differ among habitats. To examine the effects of the removal process, we examined the effects of daily soil temperature on the daily sampled abundance (removal probability) of Pterostichus thunbergi using removal sampling within enclosures. We found that soil temperature increased the removal probability, but this effect was limited and not consistent across survey periods. The results suggest that the effects of the temporary migration process may not be habitat dependent and that the effects of the removal process may be small. Therefore, the traditional use of pitfall traps is, to some extent, a robust and comparable measure of the sampled abundance of ground‐dwelling beetles among different habitats.

Differential temperature sensitivity of intracellular metabolic processes and extracellular soil enzyme activities

Abstract. Predictions concerning the feedback of soil heterotrophic respiration to a warming climate often do not differentiate between the extracellular and intracellular steps involved in soil organic matter decomposition. This study examined the temperature sensitivities of intracellular metabolic processes and extracellular soil enzyme activities and how they are influenced by previous temperatures. We pre-incubated soils at 5, 15, or 26 ∘C to acclimatize the microbial communities to different thermal regimes for 60 d before measuring potential activities of β-glucosidase and chitinase (extracellular enzymes), glucose-induced respiration (intracellular metabolic processes), and basal respiration at a range of assay temperatures (5, 15, 26, 37, and 45 ∘C). A higher pre-incubation temperature decreased the soil pH and C/N ratio and decreased β-glucosidase potential activity and respiration but not chitinase potential activity. It is likely that this legacy effect on β-glucosidase and respiration is an indirect effect of substrate depletion rather than physiological acclimatation or genetic adaptation. Pre-incubation temperature effects on temperature sensitivity were subtle and restricted to extracellular activities, perhaps because of the short (60 d) duration of the pre-incubation at temperatures that were below the initial optimum (∼ 30 ∘C) for the mesophilic soil community. However, we found that the intracellular and extracellular steps differ in their temperature sensitivity, and this observation differs depending on the range of temperature used for Q10 estimates of temperature sensitivity. Between 5 and 15 ∘C intracellular and extracellular processes show equal temperature sensitivity, but between 15 and 26 ∘C intracellular metabolic processes were more temperature sensitive than extracellular enzyme activity, and between 26 and 37 ∘C extracellular enzyme activity was more temperature sensitive than intracellular metabolic processes. This result implies that depolymerization of higher molecular weight carbon is more sensitive to temperature changes at higher temperatures (e.g. higher temperatures on extremely warm days), but the respiration of the generated monomers is more sensitive to temperature changes at moderate temperatures (e.g. mean daily maximum soil temperature). However, studies using multiple soil types and a greater range of pre-incubation temperatures are required to generalize our results. Nevertheless, since climate change predictions currently indicate that there will be a greater frequency and severity of hot summers and heatwaves, it is possible that global warming may reduce the importance of extracellular depolymerization relative to intracellular metabolic processes as the rate-limiting step of soil organic matter mineralization. We conclude that extracellular and intracellular steps are not equally sensitive to changes in soil temperature and that the previous temperature a soil is exposed to may influence the potential activity, but not temperature sensitivity, of extracellular and intracellular processes.

Effects of organic mulching on moisture and temperature of soil in greenhouse production of tomato under unheated greenhouse cultivation in the cold zone of China.

In the cold zone of China, winter is cold and long and has a short duration of sunshine. Unheated earthen-wall solar greenhouses are used for tomato production in winter in this region. This was an experimental investigation of different organic mulching materials (newspaper, bran, and grass) on the soil temperature, soil moisture, tomato yield, fruit quality, and water use efficiency. Organic mulching variously improved soil temperature, soil moisture, water use efficiency, and tomato yield, which is very important for greenhouse winter cultivation in this cold zone. Organic mulching regulated the soil temperature, with daily soil temperature ranges of bran, newspaper, and grass treatments being 1.6, 1.9, and 2.1°C lower than for bare land, respectively. Compared to bare land, newspaper mulching had little effect on soil temperature and fruit quality, but increased soil moisture (14.1%) and water use efficiency (WUE: WUEb, 31.3%; WUEy, 30.6%), and greatly increased yield (81.8%) and biomass (82.7%); bran mulching greatly increased soil temperature, moisture (16%), and WUE (WUEb, 60.1%; WUEy, 44.3%) and increased biomass (30.2%) and yield (17.3%); grass mulching greatly increased soil temperature and moisture (20.9%) and increased biomass (17.9%), yield (11.2%), and WUE (WUEb, 20.5%; WUEy, 13.6%). In addition, organic mulching had a good water retention effect on soil layer above 30 cm. The total soil water consumption during tomato growth was in the following order: newspaper (103 mm) > bare (74 mm) > grass (73 mm) > bran (60 mm). Soil water consumption mainly occurred in the 0- to 10-cm soil layers.

A Convolutional Neural Network Model for Soil Temperature Prediction under Ordinary and Hot Weather Conditions: Comparison with a Multilayer Perceptron Model

Soil temperature is a critical parameter in soil science, agriculture, meteorology, hydrology, and water resources engineering, and its accurate and cost-effective determination and prediction are very important. Machine learning models are widely employed for surface, near-surface, and subsurface soil temperature predictions. The present study employed a properly designed one-dimensional convolutional neural network model to predict the hourly soil temperature at a subsurface depth of 0–7 cm. The annual input dataset for this model included eight hourly climatic features. The performance of this model was assessed using a wide range of evaluation metrics and compared to that of a multilayer perceptron model. A detailed sensitivity analysis was conducted on each feature to determine its importance in predicting the soil temperature. This analysis showed that air temperature had the greatest impact and surface thermal radiation had the least impact on soil temperature prediction. It was concluded that the one-dimensional convolutional model performed better than the multilayer perceptron model in predicting the soil temperature under both normal and hot weather conditions. The findings of this study demonstrated the capability of the model to predict the daily maximum soil temperature.

Spatiotemporal Variations of Soil Temperature at 10 and 50 cm Depths in Permafrost Regions along the Qinghai-Tibet Engineering Corridor

Soil temperature plays an essential role in the permafrost thermal state and degradation process. Especially the soil temperatures at 10 cm and 50 cm depths in the active layer, which are much easier to be observed in situ, have great effects on the surface water cycles and vegetation, and could be used as the upper boundary for permafrost models to simulate the thermal state of the permafrost and active layer thicknesses. However, due to the limitations of the observation data, there are still large uncertainties in the soil temperature data, including at these two depths, in the permafrost region of Qinghai–Tibet Plateau (QTP). In this study, we evaluated and calibrated the applicability of four daily shallow soil temperature datasets (i.e., MERRA-2, GLDAS-Noah, ERA5-Land, and CFSR) by using the in situ soil temperature data from eight observation sites from 2004 to 2018 in the permafrost region along the Qinghai–Tibet Engineering Corridor. The results revealed that there were different uncertainties for all four sets of reanalysis data, which were the largest (Bias = −2.44 °C) in CFSR and smallest (Bias= −0.43 °C) in GLDAS-Noah at depths of 10 cm and 50 cm. Overall, the reanalysis datasets reflect the trends of soil temperature, and the applicability of reanalysis data at 50 cm depth is better than at 10 cm depth. Furthermore, the GLDAS-Noah soil temperatures were recalibrated based on our observations using multiple linear regression and random forest models. The accuracy of the corrected daily soil temperature was significantly improved, and the RMSE was reduced by 1.49 °C and 1.28 °C at the depth of 10 cm and 50 cm, respectively. The random forest model performed better in the calibration of soil temperature data from GLDAS-Noah. Finally, the warming rates of soil temperature were analyzed, which were 0.0994 °C/a and 0.1005 °C/a at 10 cm and 50 cm depth from 2004 to 2018, respectively.