Validation of the prognosis model SIMAGRIO‐W to predict larval activity in top soil layers for Agriotes larvae in eastern Austria

Do upper thermal tolerances differ in geographically separated populations of the beachflea Orchestia gammarellus (Crustacea: Amphipoda)?

Soil temperature increase in eastern Australia for the past 50 years

The dataset presented in this article is related to the work “Evaluation and Analysis of SMAP, AMSR2, and MEaSUREs Freeze/Thaw Products in China [1]”. Soil moisture and temperature are important variables of land-atmosphere energy exchange, monitoring vegetation growth, predicting drought disasters and climate and hydrological modelling [2–6]. This work provides detailed information on in situ soil moisture and temperature data network established in the Genhe watershed and Saihanba area in China, respectively. The Genhe watershed represents the complex surface heterogeneity in Northeast China. Therefore, data from 22 in situ sites were established in the Genhe watershed since March 2016 to improve the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Saihanba is currently China's largest manmade forest and has a unique alpine wetland and a complete aquatic ecosystem. There are 29 in situ sites deployed in Saihanba since August 2018 for studying the cold temperate continental monsoon climate and estimating forest carbon storage capacity and carbon emissions from manmade forests. Soil temperature and permittivity data in the network were measured using ECH2O EC-5TM probes (Decagon Devices, Inc., Washington, USA, https://www.metergroup.com/) and XingShiTu (XST) probes (BEIJING XST Co., Ltd., www.xingshitu.com) every 30 min at depths of 3, 5, and 10 cm for the Genhe watershed continuous automatic observation network, and depths of 5 and 10 cm for the Saihanba continuous automatic observation network. In the Genhe watershed, soil moisture and soil temperature data in the network were automatically collected using the EM50 data collection system. The Saihanba area has the XST data collection system to record soil temperature and permittivity. The permittivity data collected with the XST data collector were transformed to soil moisture data (volumetric water content) based on the formula developed by [7]. The datasets of the Genhe watershed and Saihanba area consist of raw data acquired by the data collector and processed data of soil moisture and temperature. The Saihanba dataset also includes the calibration data based on soil texture. The result of temporal variations analysis in observed data in the Genhe Watershed and the processing in observed data in the saihanba area show that the long-term in situ soil moisture and temperature datasets can be used for the validation/calibration and improvement of the soil moisture and soil freeze/thaw algorithm.

This paper outlines dynamics of near-surface hydrothermal processes and analyzes the characteristics of moisture distribution during the freeze–thaw period in a typical black soil zone around Harbin, Northeastern China, a region with a moderate depth of seasonally frozen ground and one of the most important granaries in China. At Field Site 1, we analyzed the soil temperature and soil moisture content data from November 2011 to April 2012 from soil depths of 1, 5, 10, and 15 cm in sunny slope, and from depths of 1, 5, and 10 cm in shady slope black soil farmland. At Field Site 2, soil samples were collected from a 168 m long sloping black soil field at locations 10, 50, 100, and 150 m from the bottom of the slope at different depths of 0–1 cm, 1–5 cm, and 5–10 cm at the same location. Analysis of the monitored Site 1 soil temperature and soil moisture content data showed that the soil moisture content and soil temperature fit line is consistent with a Gaussian distribution rather than a linear distribution during the freeze–thaw period. The soil moisture content and time with temperature fit line is in accordance with a Gaussian distribution during the freeze–thaw period. Site 2 soil samples were analyzed, and the soil moisture contents of the sloping black soil farmland were obtained during six different freeze–thaw periods. It was verified that the soil moisture content and time with temperature fit line is in accordance with a Gaussian distribution during the six different freeze–thaw periods. The maximum surface soil moisture content was reached during the early freeze–thaw period, which is consistent with the natural phenomenon of early spring peak soil moisture content under temperature rise and snow melt. The soil moisture contents gradually increased from the top to the bottom in sloping black soil farmland during the freeze–thaw period. Since the soil moisture content is related to soil temperature during the freeze–thaw cycle, we validated the correlation between soil temperature spatiotemporal China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model–Soil Temperature (CMADS-ST) data and monitored data. The practicality of CMADS-ST in black soil slope farmland in the seasonal frozen ground zone of the study area is very good. This research has important significance for decision-making for protecting water and soil environments in black soil slope farmland.

Revealing the characteristics of soil moisture and temperature under typical sloping land uses in the loess hilly region is of great significance for the efficient and sustainable use of sloping land resources. In this study, the soil moisture content in the 0–160 cm soil layer and the soil temperature in the 0–100 cm soil layer under soybean sloping field, maize terraced field, jujube orchard, and grassland were continuously observed during the 2014 and 2015 growing seasons (May to October). Traditional statistical analysis and wavelet fractal dimension method were used to study the characteristics and complexity of soil moisture and temperature changes under different sloping land uses. The main findings are as follows: (1) Maize terraced field obtained high soil moisture content in the 0–160 cm soil layer, showing the outstanding effect of soil moisture conservation, especially in the drought growing season. Maize terraced field minimized the changing amplitude (Ka), variation degree (Cv), and active layer of soil moisture in the 0–160 cm soil layer and the Ka and Cv of soil temperature in the 0−100 cm soil layer. The maize terraced field had the minimum fractal dimensions of soil moisture and temperature both in normal precipitation and drought growing seasons, indicating that the maize terraced field minimized the complexity of soil moisture and temperature changes. (2) The jujube orchard obtained the minimum soil moisture content in the 0−160 cm soil layer, and greatly increased the Ka, Cv, and active layer of soil moisture both in normal precipitation and drought growing seasons. The jujube orchard obtained the maximum soil temperature in the 0–100 cm soil layer, and greatly increased the Ka and Cv of soil temperature. The jujube orchard also had the maximum fractal dimensions of soil moisture and temperature, indicating that soil moisture and temperature changes in jujube orchard were the most complex. (3) Compared to jujube orchard, soybean sloping field and grassland increased soil moisture content, reduced the Ka and Cv of soil moisture and temperature, and weakened the complexity of soil moisture and temperature changes. (4) The analysis results of the complexity of soil moisture and temperature changes under the experimental sloping land uses based on the wavelet fractal dimension method were consistent with the traditional statistical analysis results, indicating that it is feasible to evaluate the complexity of soil moisture and temperature changes under the typical sloping land uses in the loess hilly region by using wavelet fractal dimension method. In summary, terraced fields were conducive to improving soil moisture content and maintaining the stability of soil moisture and temperature. It is recommended that the project of changing sloping fields into terraced fields should be popularized in the loess hilly region to effectively utilize limited natural precipitation. In order to prevent the jujube orchard from degenerating and dying due to long-term drought and water shortage, effective water management measures need to be taken to achieve the sustainable development of dry farming jujube orchard.

Soil temperature can exhibit considerable memory from weather and climate signals and is among the most important initial conditions in numerical weather and climate models. Consequently, a more accurate long-term land surface soil temperature dataset is needed to improve weather and climate simulation and prediction, and is also important for the simulation of agricultural crop yield and ecological processes. The North American Land Data Assimilation phase 2 (NLDAS-2) has generated 31 years (1979–2009) of simulated hourly soil temperature data with a spatial resolution of ⅛°. This dataset has not been comprehensively evaluated to date. Thus, the purpose of this paper is to assess Noah-simulated soil temperature for different soil depths and time scales. The authors used long-term (1979–2001) observed monthly mean soil temperatures from 137 cooperative stations over the United States to evaluate simulated soil temperature for three soil layers (0–10, 10–40, and 40–100 cm) for annual and monthly time scales. Short-term (1997–99) observed soil temperatures from 72 Oklahoma Mesonet stations were used to validate simulated soil temperatures for three soil layers and for daily and hourly time scales. The results showed that the Noah land surface model generally matches observed soil temperature well for different soil layers and time scales. At greater depths, the simulation skill (anomaly correlation) decreased for all time scales. The monthly mean diurnal cycle difference between simulated and observed soil temperature revealed large midnight biases in the cold season that are due to small downward longwave radiation and issues related to model parameters.

Geographic variation in temperature tolerance as an indicator of potential population responses to climate change

Changes in ambient temperature affect all biological processes. However, these effects are process specific and often vary non-linearly. It is thus a non-trivial problem for neuronal circuits to maintain coordinated, functional output across a range of temperatures. The cardiac nervous systems in two species of decapod crustaceans, Homarus americanus and Cancer borealis, can maintain function across a wide but physiologically relevant temperature range. However, the processes that underlie temperature resilience in neuronal circuits and muscle systems are not fully understood. Here, we demonstrate that the non-isolated cardiac nervous system (i.e., the whole heart: neurons, effector organs, intrinsic feedback systems) in the American lobster, H. americanus, is more sensitive to warm temperatures than the isolated cardiac ganglion (CG) that controls the heartbeat. This was surprising as modulatory processes known to stabilize the output from the CG are absent when the ganglion is isolated. One source of inhibitory feedback in the intact cardiac neuromuscular system is nitric oxide (NO), which is released in response to heart contractions. We hypothesized that the greater temperature tolerance observed in the isolated CG is due to the absence of NO feedback. Here, we demonstrate that applying an NO donor to the isolated CG reduces its temperature tolerance. Similarly, we show that the NO synthase inhibitor L-nitroarginine (LNA) increases the temperature tolerance of the non-isolated nervous system. This is sufficient to explain differences in temperature tolerance between the isolated CG and the whole heart. However, in an intact lobster, the heart and CG are modulated by an array of endogenous peptides and hormones, many of which are positive regulators of the heartbeat. Many studies have demonstrated that excitatory modulators increase temperature resilience. However, this neuromuscular system is regulated by both excitatory and inhibitory peptide modulators. Perfusing SGRNFLRFamide, a FLRFamide-like peptide, through the heart increases the non-isolated nervous system’s tolerance to high temperatures. In contrast, perfusing myosuppressin, a peptide that negatively regulates the heartbeat frequency, decreases the temperature tolerance. Our data suggest that, in this nervous system, positive regulators of neural output increase temperature tolerance of the neuromuscular system, while modulators that decrease neural output decrease temperature tolerance.

Studies have demonstrated differences in temperature tolerance between two Liriomyza species, L. huidobrensis and L. sativae. To investigate whether the heat shock proteins (Hsps) in the two species have different expression profiles during temperature stress, we cloned hsp90, 70, 60, 40 and 20, and analysed their expression profiles across temperature gradients by real-time quantitative PCR and Western blotting. The results revealed that the number of TATA-box-like elements and A/T-rich insertion/deletions within the 5' UTRs of the hsps are different in the two species. The temperatures for onset (T(on)) or maximal (T(max)) induction of hsp expression in L. huidobrensis were generally 2.5-10 degrees C lower than those in L. sativae, and the T(on) were highly consistent with the temperature limits of the northern boundary of the range of these two leafminer species. These studies confirmed, in terms of gene expression levels, that L. huidobrensis is more cold tolerant than L. sativae, which is more heat tolerant, and suggest that the T(on) (or T(max)) of hsps can represent the differences in temperature tolerance of these two leafminer species, and may be used to determine their natural geographical distribution limits.

Highlights To predict soil temperature, a new deep learning model called 1D-CNN-MLP is proposed, which has higher accuracy or faster convergence compared with MLP or LSTM. Convolutional neural network part in the model could extract and calculate transmission of soil temperature. Using the non-sequential data of several soil temperature layers combined with the model, we can predict other temperature layers. The model can greatly reduce the difficulty and cost of soil temperature measurement. Abstract. Soil temperature plays an important role in agriculture. In order to achieve cost reduction in the sensor arrangement when monitoring soil temperature, a novel model called 1D-CNN-MLP (One dimensional convolutional neural network-Multilayer perceptron) was proposed for soil temperature prediction. Meteorological data and soil temperature data on different soil layers collected for the 2018~2021 period from a weather station in Yangling, China, were used for calculation in our work. Our model was evaluated using statistical measures of MSE (Mean Square error). The model parameters with high operation efficiency and high accuracy are obtained, and the training result records much lower error than MLP (multilayer perceptron) and faster convergence than LSTM (long short-term memory) with an MSE of 0.288 x 10&-3. The 1D-CNN (One-dimensional convolutional neural network) part of the model is used to reveal and extrapolate the law of how soil temperature propagates in different soil layers. In the case where only three layers of soil temperature data are known, the characteristic temperature layer depths of 10 cm, 15 cm, and 40 cm, are selected to place sensors and obtain the best prediction effect of soil temperature at different depths of 5 to 160 cm with a RMSE (Root mean squared error) of 1.988?. The model may help users with improved and economical soil temperature prediction and control, thus boosting crop yield. Ultimately, we found the model has a relatively poor performance in the accuracy of deep soil temperature prediction when only three layers of soil temperature data are known, and it is suggested that the model can be further optimized in terms of kernel parameter setting, data composition, and the variation law of deep soil temperature. Keywords: 1D-CNN, MLP, Soil temperature prediction.

Rock fragment content alters spatiotemporal patterns of soil water content and temperature: Evidence from a field experiment

Abstract. Rural greenway systems passing through woodlands to connect urban societies are valuable in terms of not only transportation but also roadside tree phenology and ecophysiology and associated recreation. Therefore, particularly during their foliation periods, monitoring and analyses of that phenological and ecophysiological course of the roadside trees will primarily indicate their gradual degree of closure and will determine their gradual degree of coverage on the road and the roadside. Hence, the leaf area index (LAI) is a significant and comprehensive canopy parameter which is referred to for those monitoring and analyses procedures. This gradual-closure indicator and coverage determinant parameter can further be used for detecting shading and recreation potential, as well as the safety level of those greenways. Major driving factors of the phenological and ecophysiological course can also be investigated by monitoring and assessing the development of and change in the mean LAI under the influence of the mean temperature, height and diameter at breast height (DBH) values. Therefore, for this study, in order to monitor and determine the development of and change in LAI, hemispherical photographs were taken beneath the tree canopies at 10 different points along part of a regionally well known greenway system, which involves alleys of Platanus orientalis L. (oriental plane) trees. This point-based hemispherical photographing procedure was applied and repeated 20 times, particularly during the foliation period between mid-March and late June, when a total of 200 photographs were obtained and analysed using a digital image processing method. The seasonal course of the LAI values was graphed for each point, and principally the daily mean LAI (ranging between 0.35 and 2.76 m2 m−2) was evaluated referring to both the air and the soil (−10 cm) temperature data. The point-based maximum LAI values (average 2.76 m2 m−2, ranging between 2.42 and 3.16) were achieved during mid-June. They were examined comparing their ranking with the rankings of the basic physiological parameters: mean height (ranging between 17.0 and 26.7 m) and mean DBH (ranging between 26.5 and 38.2 cm) and number of trees (5 to 15) within the canopy frames of the relevant points. Afterwards, the phenologically based and daily mean LAI values were discussed dependent upon their high and significant correlation, particularly with the soil temperature data (r = 0.89, P < 0.01), and the point-based maximum LAI values were also discussed dependent upon their non-correlation with the point-based mean height and mean DBH. In conclusion, the overall results of this study primarily emphasize the influence of the soil temperature on the phenological course of oriental plane canopies and on the development of their daily mean LAI, particularly during their foliation period. This current effect of the soil temperature indicates the potential alarm triggered by the early budburst dates and associated possible advance of the tree foliation period, depending on the warming capacity of the road asphalt and roadside pavement on the soil underneath, particularly during and after new-pavement and resurfacing practices.

The most concerning recent ocean changes in temperature issues are known as marine heat waves. Under these conditions, it is important to evaluate the effects of temperature on zooplankton. In this study, we investigated the growth rates of three dominant copepod species (Eucalanus bungii, Metridia pacifica, and Neocalanus plumchrus) in the northern North Pacific under three different temperature conditions (3, 7, and 11°C) using an artificial cohort method. Experimental conditions for 42 hour incubations were set to light intensity and photoperiod corresponding to 50 m depth. The dissolved oxygen solubility after rearing ranged from 69.2% to 102.1%, suggesting sufficient conditions for copepod growth. Chlorophyll a increased in 83% of the experiments, indicating that the food conditions were sufficient for the copepods. The mean proportion of dead specimens evaluated using neutral red was 10.2%, corresponding with the reported values in the field. Thus, it can be concluded that the laboratory-rearing conditions used in this study provided sufficient food, and the only effect evaluated would be that of the three different temperatures. Since the developmental time for each stage is longer than the rearing period, it is important to conduct experiments with a large number of individuals to obtain accurate growth rate results. The specific growth rates of E. bungii and M. pacifica increased with increasing temperature. In contrast, N. plumchrus showed the highest growth rate under moderate water temperature conditions. In terms of weight units (dry, carbon, and nitrogen), the carbon weight-specific growth rates were higher than those of the other two units, a common characteristic of the three species. This reflected lipid accumulation during the late copepodite stages. The interspecies differences in growth rate responses to water temperature reflect species-specific differences in temperature tolerance or the optimum temperature for each species. As E. bungii and M. pacifica reproduce near the surface layer through income breeding, their temperature tolerance or optimum temperature is expected to be high. However, because the reproduction of N. plumchrus occurs in the cold deep layer by using capital breeding, its temperature tolerance and optimum temperature would be lower than those of the former two species.

As a result of increasing cultivation of corn and potatoes, the polyphagous larvae of the click beetles (Coleoptera: Elateridae), called wireworms, become a problem in agriculture (Parker and Howard 2001). The hypothesis that the vertical distribution of wireworms depends on soil moisture, soil temperature and soil type had to be verified. In field experiments, investigations on wireworm activity in relation to soil moisture and soil temperature were carried out over a period of 2 years. Bait traps were buried in soil, and the appearance of larvae was recorded during the seasons. In laboratory, the optimum soil moisture for larvae was tested with four soil types. Correlations between the percentage of observed wireworms and soil moisture were analysed.The results were taken as the basis for the prediction model SIMAGRIO‐W (SIMulation of the larvae of AGRIOtes (Wireworms)), which appraises the risk of damages on field culture caused by wireworms in relation to soil moisture and soil temperature. With logistic and Gaussian regressions, a first approach of a prediction model was developed. One output of the model displays the risk for damages in form of a binary response, which identifies two risk classes (risk and no risk). A second output displays for four soil types the percentage of appeared wireworms in relation to soil moisture, starting with an undefined amount of wireworms on a field. With a R² from 0.81 to 0.89, the percentage of occurred wireworms could be calculated well. The correlations were significant in all tested soil types (P ≤ 0.05). With data collected in 2010 and 2011, an independent validation was carried out to get information about the predictions quality of the developed model SIMAGRIO‐W. The hit rate was validated within two classes, risk and no risk. With correct results in over 85% of the cases, the class was predicted correctly.

The temperature, moisture, and salt content of soil in alpine regions are sensitive to changes in climatic factors and are important indicators of ecosystem functions. In this study, we collected soil moisture, temperature and electrical conductivity data at different depths at a sampling site on Bird Island in Qinghai Lake during winter using a continuous soil temperature, moisture and salt content monitoring system and analyzed their variations and influential factors. The variation in soil moisture showed an obvious ‘V-shaped’ pattern from 00:00 to 23:00 and an upward trend with soil layer depth. From 00:00 to 23:00, the overall soil temperature data fitted a ‘unimodal’ curve and showed a clear and continuous upward trend with soil layer depth at a rate of 0.684 (p < 0.001). Soil electrical conductivity data also exhibited a distinct ‘V-shaped’ pattern from 00:00 to 23:00 and a continuous increase with increasing soil depth. The correlation between soil temperature, moisture, and conductivity and the spatial distribution of five climate factors indicated that climate factors accounted for 53.6% of the changes in soil temperature, moisture, and salinity. Climate factors showed a significant positive correlation with soil temperature, moisture, and conductivity (p < 0.001), and air temperature was the most important factor influencing soil temperature and soil moisture changes, whereas wind direction was the most important factor influencing soil conductivity. (Wind direction and wind speed affect soil evapotranspiration, and then affect soil moisture and solute transport process). The results of this preliminary study reveal the characteristics associated with soil temperature, moisture, and salinity changes in winter within the wetlands of Bird Island on Qinghai Lake in the context of climate change, and they can be used as valuable reference data in further studies investigating associated changes in ecosystem functions.