Influence Of Soil Moisture Research Articles

Observed Influence of Soil Moisture on the North American Monsoon: An Assessment Using the Stepwise Generalized Equilibrium Feedback Assessment Method

AbstractThe evidence shows that soil moisture has an important influence on North American monsoon (NAM) precipitation. This study evaluates the local and nonlocal feedbacks of soil moisture on summer (June–September) precipitation in the NAM region using observational data. We applied a multivariate statistical method known as the Stepwise Generalized Equilibrium Feedback Assessment (SGEFA) to control for internal atmospheric variability and sea surface temperature (SST) forcings so that we could isolate the impact of soil moisture feedbacks on NAM precipitation. Our results identify feedback pathways between soil moisture and precipitation in the NAM region and in the southern Rocky Mountains (SRM) region. Wet soils in the SRM result in lower-than-normal local surface temperature, weaker water vapor transport from the eastern Pacific and the Gulf of California (GOC), and less monsoon precipitation. Precipitation over the U.S. Great Plains also significantly increases when there are wet soils in the SRM. This occurs due to an enhanced water vapor influx into this region. On the other hand, anomalously wet soils in the NAM region increase NAM precipitation by enhancing local moist static energy and increasing the strength of the monsoonal circulation. Our observational results using SGEFA agree well with previous numerical modeling studies. This study highlights the critical role of land–atmosphere interactions for understanding NAM variability.

A new method for multicolor determination of organic matter in moist soil

Soil color is frequently used by researchers to determine soil properties such as soil organic matter (SOM). However, soil moisture can darken soil color, which seriously limits the accuracy of SOM estimates. This study focused on the influence of soil moisture on the SOM estimate by using our new moisture-based multicolor reconstruction (MMR) method. On the basis of RGB color and moisture values of moist soil samples, the optimal MMR (moist soil) model—root mean square error of validation = 4.537 g/kg, residual prediction deviation of validation = 1.681, ratio of performance to interquartile range of validation = 2.939—was obtained to develop the final model, which performed better than the RGB (moist soil) model. Our method can reduce the influence of soil moisture and increase accuracy for multicolor modeling, and explores a new way to accurately determine the SOM content.

Temperature Changes and Their Impact on Drought Conditions in Winter and Spring in the Vistula Basin

Inter-annual variability of hydro-meteorological variables indirectly influence soil moisture conditions in winter and early spring seasons. The interactions between temperature changes and drought conditions are studied by an application of statistical analyses of minimum temperature (Tmin), consecutive days with temperature exceeding the 0 °C threshold value, the number of melting pulses in the winter season and Standardized Evaporation Precipitation Index (SPEI). Additionally, shifts in the onset of days with spring temperature and snow cover occurrence are analysed. A Mann–Kendall test is applied for the trend analysis. Studies have shown significant changes in thermal characteristics in the winter season over the past 70 years, which affect the moisture conditions in the Vistula River Basin. As a result of those changes, the Vistula Basin is more prone to droughts.

Zinc and copper interactions under variable soil phosphorus and moisture conditions in selected Saskatchewan soils

This study evaluates the influence of phosphorus (P) fertilization (without and with added P fertilizer) and soil moisture (stress and no-stress) on efficacy, fate, and transformation of soil applied micronutrients such as copper (Cu), zinc (Zn), and Cu + Zn in a wheat and pea cropping sequence. Wheat was grown as first crop under controlled environment conditions in which micronutrient fertilizer treatments were applied, whereas pea was grown as following crop with recommended macronutrient fertilizers to understand the residual effects of micronutrient fertilization. The high-P fertilizer application and no-stress moisture condition produced the highest grain and straw yield of wheat. Without P fertilization, there were significant negative effects of a combined application of Cu and Zn on wheat yield in a Dark Gray Chernozem. Yield of the following pea crop did not show response to residual Cu and Zn. Micronutrient fertilization increased the Cu and Zn concentration in wheat and pea grain and straw and resulted in increased after-harvest availability and supply in soils. Apart from the increased concentration in labile fraction, a considerable amount of added Cu and Zn was occluded with organic matter and oxyhydroxide species, respectively. Molecular speciation analyses revealed that carbonate associated was the dominant form of Cu and Zn in the soils. Additional Cu species such as Cu-acetate and methoxide, and Zn species including Zn-sorbed montmorillonite species were identified. Insoluble Cu-phosphate and Zn-phosphate complexes were not identified by speciation analyses and do not appear to be a significant factor controlling Cu and Zn availability in these soils.

Study of methane migration in the shallow subsurface from a gas pipe leak

With the increased use of natural gas, safety and environmental concerns from underground leaking natural gas pipelines are becoming more widespread. What is not well understood in leakage incidents is how the soil conditions affect gas migration behavior, making it difficult to estimate the gas distribution. To shed light on these concerns, an increased understanding of subsurface methane migration after gas release is required to support efficient leak response and effective use of available technologies. In this study, three field-scale experiments were performed at the Methane Emission Technology Evaluation Center in Colorado State University to investigate the effect of soil textural heterogeneity, soil moisture, and leak rate (0.5 and 0.85 kg/h) on methane migration caused by leaking pipelines. Subsurface methane concentrations, in addition to soil moisture and meteorological data, were collected over time. A previously validated numerical model was modified and used to understand the observed methane distribution behavior. Results of this study illustrate that the influence of soil texture, leak rate, and moisture on subsurface methane distribution is determined by the relative contribution of advection and diffusion and closely related to the distance to the leak source. Advection dominates gas transport within 1–1.5 m of the leak source, driving the migration of high concentration contours. Beyond this distance, diffusion dominates migration of lower concentration contours to the far-field. Although large leak rates initially result in faster and further gas migration, the leak rate has little influence on the diffusion dominated migration farther from the leak source. Soil moisture and texture complicate gas behavior with texture variations and elevated soil moisture conditions playing a dominant role in locally increasing methane concentrations. Scenarios highlight the importance of understanding the effects of soil moisture, texture, and leak rate on gas migration behavior in an attempt to unravel their contribution to the gas concentration within the soil environment.

Soil moisture influences on Sierra Nevada dead fuel moisture content and fire risks

Dead fuel moisture influences the risk of fire ignition events, with implications for fire hazards, risk mitigation, and the design of prescribed burning activities. Because direct fuel moisture measurements are rarely available, fuel moisture must be estimated when evaluating fire risks. Most estimates rely primarily on atmospheric conditions and ignore the interaction of fuels with the soil surface with which they are in hydraulic contact. In this study we explore whether dead fuel moisture predictions can be improved with information about surface soil moisture. Despite the likelihood that dead fuels would exchange water with underlying soil, the influence of soil moisture on fuel moisture has been poorly studied. An analysis of 202 observations of co-located soil moisture, 1 and 10 h fuel moisture measurements, with environmental and meteorological covariates, showed that soil moisture had a small but significant effect on fuel moisture across all sampled conditions. The influence of soil moisture on fuel moisture was the most important among all other environmental factors for wet soil conditions and 10-h fuels, where a 1% increase in soil moisture content led to approximately a 0.6% increase in fuel moisture. The effect of soil moisture on 1-h fuel moisture although significant was small. Incorporating spatio-temporal variability of soil moisture into time-series or spatial predictions of fuel moisture tended to (i) reduce the seasonal duration in which fuels had a high probability of ignition by an average of 52–60 days across the tested years, and (ii) increased the heterogeneity of the probability of ignition through space, compared with similar models that did not incorporate soil moisture information.

Influence of Soil Moisture and Crust Formation on Soil Evaporation Rate: A Wind Tunnel Experiment in Hungary

In both arid and semiarid regions, erosion by wind is a significant threat against sustainability of natural resources. The objective of this work was to investigate the direct impact of various soil moisture levels with soil texture and organic matter on soil crust formation and evaporation. Eighty soil samples with different texture (sand: 19, loamy sand: 21, sandy loam: 26, loam: 8, and silty loam: 6 samples) were collected from the Nyírség region (Eastern Hungary). A wind tunnel experiment was conducted on four simulated irrigation rates (0.5, l.0, 2.0, and 5.0 mm) and four levels of wind speeds (4.5, 7.8, 9.2, and 15.5 m s−1). Results showed that watering with a quantity equal to 5 mm rainfall, with the exception of sandy soils, provided about 5–6 h protection against wind erosion, even in case of a wind velocity as high as 15.5 m s−1. An exponential connection was revealed between wind velocities and the times of evaporation (R2 = 0.88–0.99). Notably, a two-way ANOVA test revealed that both wind velocity (p < 0.001) and soil texture (p < 0.01) had a significant effect on the rate of evaporation, but their interaction was not significant (p = 0.26). In terms of surface crusts, silty loamy soils resulted in harder and more solid crusts in comparison with other textures. In contrast, crust formation in sandy soils was almost negligible, increasing their susceptibility to wind erosion risk. These results can support local municipalities in the development of a local plan against wind erosion phenomena in agricultural areas.

Using Generalized Regression Neural Network to Retrieve Bare Surface Soil Moisture From Radarsat-2 Backscatter Observations, Regardless of Roughness Effect

The combined influence of surface soil moisture and roughness on radar backscatters has been limiting SAR’s application in soil moisture retrieval. In the past research, multi-temporal analysis and artificial neural network (ANN) inversion of physically based forward models were regarded as promising methods to decouple that combined influence. However, the former does not consider soil roughness change over a relatively longer period and the latter makes it hard to thoroughly eliminate the effect of soil roughness. This study proposes to use generalized regression neural network (GRNN) to derive bare surface soil moisture (BSSM) from radar backscatter observations regardless of the effect of soil roughness (GRNN inversion of backscatter observations). This method not only can derive BSSM from radar backscatters, provided soil roughness is unknown in any long period, but also can train models based on small-size sample data so as to reduce the manual error of training data created by simulation of physically based models. The comparison of validations between BSSM-backscatter models and BSSM-roughness-backscatter models both analyzed by GRNN shows that the incorporation of soil roughness cannot raise the prediction accuracy of models and, instead, even reduce it, indicating that the combined influence is thoroughly decoupled when being analyzed by GRNN. Moreover, BSSM-backscatter models by GRNN are recommended due to their good prediction, even compared to those related models in past publications.

Evaluation of improved cassava genotypes for yield and related traits for a better breeding strategy under different agroecologies in Nigeria

This study aimed at determining shoot and root characteristics of cassava as affected by root yield and the influence of soil moisture on vegetative growth and yield. Thirty cassava genotypes were evaluated for morphological and physiological characterization in three locations in Nigeria: Ibadan, Mokwa and Zaria. Randomized complete block design was used with four replicates. Studies on the pasting properties of the genotypes were also carried out. Data were collected on plant height, stem girth, stay-green ability, garri and fresh root weight. Genotypes differed significantly (P < 0.05) across and within locations for shoot and root characteristics. Across locations, genotype 011663 had the highest plant height (132.4 cm); 30572 had the largest stem girth (8.6 cm); and 010040 was the best stay-green (2.2). Genotype 011086 had the highest number of roots per plot (95.7), 950289 had the highest fresh root yield (24.3 t/ha), and 990554 had the highest percentage of dry matter (35.2). Trends in root yields across locations were Ibadan (28.9 t/ha), Mokwa (20.3 t/ha), and Zaria (8 t/ha). Five genotypes IITA-TMS-IBA950289, 010034, 990554, 011807, and 980581 had negligible interactions with the environment and so have broad adaptation and are considered stable; and two clones 011807 and 950166 were found to be the best for pasting properties. Breeding strategies that consider root size, total root number, harvest index, dry matter, with applications for household foods and industrial uses, will be an effective and efficient way to select genotypes for high yield.

Climate Differently Impacts the Growth of Coexisting Trees and Shrubs under Semi-Arid Mediterranean Conditions

Background and Objectives—Coexisting tree and shrub species will have to withstand more arid conditions as temperatures keep rising in the Mediterranean Basin. However, we still lack reliable assessments on how climate and drought affect the radial growth of tree and shrub species at intra- and interannual time scales under semi-arid Mediterranean conditions. Materials and Methods—We investigated the growth responses to climate of four co-occurring gymnosperms inhabiting semi-arid Mediterranean sites in northeastern Spain: two tree species (Aleppo pine, Pinus halepensis Mill.; Spanish juniper, Juniperus thurifera L.) and two shrubs (Phoenicean juniper, Juniperus phoenicea L.; Ephedra nebrodensis Tineo ex Guss.). First, we quantified the intra-annual radial-growth rates of the four species by periodically sampling wood samples during one growing season. Second, we quantified the climate–growth relationships at an interannual scale at two sites with different soil water availability by using dendrochronology. Third, we simulated growth responses to temperature and soil moisture using the forward, process-based Vaganov‒Shashkin (VS-Lite) growth model to disentangle the main climatic drivers of growth. Results—The growth of all species peaked in spring to early summer (May–June). The pine and junipers grew after the dry summer, i.e., they showed a bimodal growth pattern. Prior wet winter conditions leading to high soil moisture before cambium reactivation in spring enhanced the growth of P. halepensis at dry sites, whereas the growth of both junipers and Ephedra depended more on high spring–summer soil moisture. The VS-Lite model identified these different influences of soil moisture on growth in tree and shrub species. Conclusions—Our approach (i) revealed contrasting growth dynamics of co-existing tree and shrub species under semi-arid Mediterranean conditions and (ii) provided novel insights on different responses as a function of growth habits in similar drought-prone regions.

Antecedent soil moisture and rain intensity control pathways and quality of organic carbon exports from arable land

Under conditions of climate change, the severity and probability of storm events and droughts are expected to increase, this may affect the partitioning into surface and subsurface runoff. However, there is still a debate on how such extreme weather conditions affect the leaching of soil organic carbon. The aim of this study was to ascertain the impact of rainfall intensity (63 vs 79 mm h−1) and antecedent soil moisture (Matric potential: −10 hPa vs −450 hPa) on flow partitioning in the transportation (fluxes and timing) of dissolved (DOC) and particulate organic carbon (POC). Rainfall simulation experiments using undisturbed soil monoliths (1 m × 0.5 m × 0.3 m) allowed to monitor the transport of water, sediments, DOC, and POC via surface and shallow subsurface runoff. In addition, the composition of the leached organic matter was analysed using photometric and fluorometric methods.Most of the organic carbon was transported as POC via surface runoff. In the surface runoff, the influence of antecedent soil moisture on POC loss was larger than rainfall intensity, while rainfall intensity had a greater influence on DOC losses. Under initially unsaturated conditions, surface sealing reduced the infiltration rate, thus fuelling the total surface runoff, which, in turn, enhanced the transported total sediment and POC load of the surface runoff. While POC dominated surface runoff, DOC played a crucial role in the subsurface runoff with higher DOC concentrations under unsaturated conditions. In contrast to other treatments, DOC exported from unsaturated soils rained with high intensity had a unique composition with the highest proportion of humic-like peaks (A, M, C), protein-like peaks (T) and components (C4), suggesting a concentrating effect on DOC at those soils. Altogether, this research acquires new insights into how flow partitioning under extreme weather conditions affects organic carbon losses and which transport mechanism might pose a risk for aquatic systems.

Effects of moisture and physical disturbance on pore-scale oxygen content and anaerobic metabolisms in upland soils.

Soils are the largest dynamic stock of carbon (C) on Earth, and microbial respiration of soil organic C accounts for over 25% of global carbon dioxide (CO2) emissions. Zones of oxygen depletion in upland soils (anaerobic microsites) are increasingly recognized as an important control on soil microbial respiration rates, but the factors governing the volume and distribution of anaerobic microsites are relatively unknown. We measured the dissolved oxygen (DO) content of porewater from incubated soil cores of varying moisture contents (<80% and >80% water saturation) and degrees of disturbance (undisturbed, conventionally tilled, and physically disturbed). Porewater was extracted sequentially from pores constrained by three effective pore diameters, ≥3.0μm, 3.0-1.0μm, and 1.0-0.6μm, from cores incubated for 7, 14, or 28days, using a modified Tempe cell extraction system. We observed a parabolic pattern in mean dissolved oxygen (DO) concentrations across pore sizes, independent of soil moisture and degree of disturbance. Specifically, DO values within the largest and smallest pore domains were relatively depleted (155±10μM and 160±11μM, respectively), while DO values within medium pores were closer to saturation (214±8μM). The observed DO pattern provides insight into the balance of microbial oxygen demand versus oxygen supply across pore domains within upland soils. Additionally, we observed iron and manganese reduction in all soils except samples subjected to disturbance and incubated at <80% water saturation, suggesting that disturbance enhances aeration and diminishes anaerobic metabolisms within upland soils. Our findings highlight the influence of soil moisture and management on soil redox and CO2 efflux rates.

Soil PM10 emission potential under specific mechanical stress and particles characteristics.

Soil can be resuspended in the atmosphere due to wind or mechanical disturbances, such as agricultural activities (sowing, tilling, etc.), producing fine particulate matter (PM). Agriculture is estimated to be the third PM10-emitting sector in Europe, emitting more than the transportation sector. However, very few emission figures are available for the different cropping operations. Moreover, soil Emission Potential (EP) is extremely variable, since is influenced by factors such as humidity, texture, chemical composition, and wind speed. Due to their similarity to tilling emission mechanisms, Soil Resuspension Chambers (SRC) are the most suitable method to estimate the impacts of these factors on soil susceptibility to emit PM10 during cropping operations (Emission Potential, EP). The main objective of this work is to assess the EP of different agricultural soils used for maize cropping in North-Western Italy, studying the influence of soil moisture and physico-chemical characteristics. Therefore, a SRC was developed, based on previous studies, with the goal of being relatively small, easy to operate and low-cost. Using the gathered data, a log-linear multiple regression model was developed to allow soil EP estimation from few physico-chemical parameters (moisture, sand/silt ratio and organic carbon content). The model allows to tailor field Emission Factors (EF) of specific cropping operations to different soil and moisture conditions and was applied to an EF for rotary harrowing, defined in a previous study. The concentration of Potentially Toxic Elements (PTE) in soil-emitted PM10 was determined, founding an enrichment up to 16 times higher than in the original soil, evidencing a possible cause of concern for operator's safety during agricultural activities.

Exposing wind stress as a driver of fine‐scale variation in plant communities

Abstract The effects of temperature and precipitation, and the impacts of changes in these climatic conditions, on plant communities have been investigated extensively. The roles of other climatic factors are, however, comparatively poorly understood, despite potentially also strongly structuring community patterns. Wind, for example, is seldom considered when forecasting species responses to climate change, despite having direct physiological and mechanical impacts on plants. It is, therefore, important to understand the magnitude of potential impacts of changing wind conditions on plant communities, particularly given that wind patterns are shifting globally. Here, we examine the relationship between wind stress (i.e. a combination of wind exposure and wind speed) and species richness, vegetation cover and community composition using fine‐scale, field‐collected data from 1,440 quadrats in a windy sub‐Antarctic environment. Wind stress was consistently a strong predictor of all three community characteristics, even after accounting for other potentially ecophysiologically important variables, including pH, potential direct incident solar radiation, winter and summer soil temperature, soil moisture, soil depth and rock cover. Plant species richness peaked at intermediate wind stress, and vegetation cover was highest in plots with the greatest wind stress. Community composition was also related to wind stress, and, after the influence of soil moisture and pH, had a similar strength of effect as winter soil temperature. Synthesis. Wind conditions are, therefore, clearly related to plant community characteristics in this ecosystem that experiences chronic winds. Based on these findings, wind conditions require greater attention when examining environment–community relationships, and changing wind patterns should be explicitly considered in climate change impact predictions.

Spatial distribution and influencing factors on urban land surface temperature of twelve megacities in China from 2000 to 2017

China witnessed a rapid urbanization progress in the past 20 years. Urbanization can greatly influence urban environment, especially thermal environment. Causes for urban heat island (UHI) formation vary in different climatic regions. Understanding characteristics of spatial distribution of urban land surface temperature (ULST) and influencing factors of UHI formation is important for sustainable urban development. In this study, twelve megalopolises in China, each with a population over 5 million, were selected as research sites. Built-up areas and ULST of these megalopolises were extracted from remote sensing data of earth observation satellites of Landsat program for the three periods of 2000–2017. Spatial variation characteristics of ULST were analyzed. Influences of soil moisture, surface water availability, surface albedo, vegetation, energy consumption, gross domestic product, latitudes, precipitation, topography, and distance to the downtown on ULST were investigated through multivariate regression analysis. Results show that: all the cities expanded continuously from 2000 to 2017, but expansion rates varied significantly among the megalopolises. Urban expansion has significant effects on the spatial distribution of ULST. ULST changes more quickly when the expanded area and expansion rate are higher. Simultaneously, spatial distribution of ULST was found to relate to the shape of an urban boundary. Circularly expanding cities showed the most concentrated distribution of high-temperature regions. Correlation analysis revealed that surface water use, evapotranspiration, electric energy consumption, surface albedo, and vegetation activity were the primary influencing factors on ULST, while GDP, latitude, distance, and precipitation had no significant effects on ULST. Among the primary influencing factors, surface water was the main controlling factor on ULST in cities with more surface water distribution. Building area played a more important role in ULST in cities with less surface water distribution. In addition, vegetation area played a relatively more important role in ULST in semi-humid cities than humid cities.

High Rainfall Inhibited Soil Respiration in an Asian Monsoon Forest in Taiwan

Soil respiration represents the second largest carbon flux, next to photosynthesis of the terrestrial biosphere, and thus plays a dual role in regional and global carbon cycles. However, soil respiration in Asian monsoon forests with high rainfall has rarely been studied. In this study, we continuously measured soil respiration using a 12-channel automated chamber system in a 61-year-old Japanese cedar forest in central Taiwan with annual rainfall greater than 2500 mm. A 4-year (2011–2014) continuous half-hourly dataset was used to quantify the influences of soil temperature and moisture, especially rainfall events, on both total soil respiration (Rs) and heterotrophic respiration (Rh). The annual mean Rs was approximately 10.8 t C ha−1 (ranging from 10.7 to 10.9) t C ha−1, with Rh contributing approximately 74.6% (ranging from 71.7% to 80.2%). Large seasonal variations in both Rs and Rh were primarily controlled by soil temperature. Over 45.8% of total annual rainfall amounts were provided by strong rainfall events (over 50 mm), and over 40% of rainfall events occurred during summers between 2012 and 2014. These strong rainfall events caused rainwater to enter soil pores and cover the soil surface, which resulted in limited soil microorganism activity and, consequently, restricted CO2 production. The mean Q10 values were 2.38 (ranging from 1.77 to 2.65) and 2.02 (ranging from 1.71 to 2.34) for Rs and Rh, respectively. The Q10 values in this study, which were lower than in global forest ecosystems, may imply that the interannual Rs values observed in this study that were caused by high rainfall were less temperature-dependent than the Rs levels in global forest ecosystems. Both Rs and Rh were negatively correlated with soil moisture, which indicated that the soil moisture levels in the studied forest were usually under saturated conditions. These results also provide the lack of data for respiration in the Asian monsoon region under high-rainfall conditions.

Influence of Soil Moisture vs. Climatic Factors in Pinus Halepensis Growth Variability in Spain: A Study with Remote Sensing and Modeled Data

The influence of soil water content on Aleppo pine growth variability is analyzed against climatic variables, using satellite and modeled soil moisture databases. The study was made with a dendrochronological series of 22 forest sites in Spain with different environmental conditions. From the results of the correlation analysis, at both daily and monthly scales, it was observed that soil moisture was the variable that correlated the most with tree growth and the one that better identified the critical periods for this growth. The maximum correlation coefficients obtained with the rest of the variables were less than half of that obtained for soil moisture. Multiple linear regression analysis with all combinations of variables indicated that soil moisture was the most important variable, showing the lowest p-values in all cases. While identifying the role of soil moisture, it was noted that there was appreciable variability between the sites, and that this variability is mainly modulated by water availability, rather than thermal conditions. These results can contribute to new insights into the ecohydrological dynamics of Aleppo pine and a methodological approach to the study of many other species.

Entomopathogenic nematodes for control of carrot weevil: efficacy and longevity in muck and mineral soils.

Carrot weevil is an important pest throughout carrot-producing regions in Canada. Pesticides to control carrot weevil adults require application when the majority of adults have emerged and often this occurs after oviposition has already commenced and damage will be realized. One alternative to conventional pesticides are entomopathogenic nematodes. We studied four commercially available entomopathogenic nematode products (Steinernema feltiae, S. carpocapsae, S. kraussei and Heterorhabditis bacteriophora) for efficacy against carrot weevil in Nova Scotia and Ontario carrot fields in 2017 and 2018. The longevity and infectivity of the products in fine sandy loam soil (Ontario) and sandy loam soil (Nova Scotia) were evaluated using Galleria mellonella larvae. In Nova Scotia soils, only S. kraussei when applied twice, showed some efficacy to reduce damage from carrot weevil in 2017. In Ontario, an early application of H. bacteriophora and S. feltiae significantly reduced the percentage of carrots with weevil damage in 2018. Longevity and infectivity of S. carpocapsae and S. feltiae (against G. mellonella) was obtained up to 6 weeks post application in Nova Scotia in 2017. Similarly, S. feltiae showed infectivity up to 9 weeks post application in Ontario and Nova Scotia in 2018. Entomopathogenic products showed an ability to survive and remain infective for up to 9 weeks in soils without irrigation. Timing of application to effect control of carrot weevil requires further study. The influence of soil moisture on the longevity and infectivity of these products is discussed. © 2021 Her Majesty the Queen in Right of Canada International Pest Management Science © 2021 Society of Chemical Industry. Reproduced with the permission of the Minister of Agriculture and Agri-Food Canada.

Modelling Soil Moisture in Hyper-Arid Conditions

In most land-surface models, the evolution of soil moisture is governed by soil-hydraulic processes. In hyper-arid soils, these processes break down, but soil moisture continues to show clear temporal variations, suggesting that other processes may be at work. We hypothesize that moisture in such soils varies due to evaporation in the soil and to vapour fluxes at the air–soil interface. To test this, we include vapour exchange between the air and soil in a land-surface model, apply the model to a desert site, and compare the simulated and observed soil moisture. The good agreement between the simulations and observations confirms our hypothesis. Using the model results, we examine the interactions between the soil-moisture and soil-vapour phases and influences of the soil-vapour phase on the surface energy balance.

Вплив щільності будови та вологості ґрунту на продуктивність інтенсивного та напівінтенсивного сортів ячменю ярого

Goal. To determine the influence of agrophysical parameters of arable soil layer on the productivity of spring barley varieties of different types of intensity under conditions of application of mineral fertilizers on the example of typical deep low humus deep-boiling heavy loam on loess-like loam chernozem of the Left Bank part of Forest-steppe of Ukraine. Methods. Laboratory-analytical, laboratory-model, field (small-area), mathematical-statistical, computational. Results. The improvement of conditions of germination, development, and increase of biological mass of cultivars of the studied culture at soil density and humidity at the level of 1.2 g/cm3 and 80% of the lowest moisture content (LMC) in comparison with compacted soil is established. The optimal values of structure density and soil moisture are determined, which ensure the maximum biomass of intensive variety of spring barley Vzirets: 1.2 g/cm3 and 100% of LMC (at the application of 90 kg/ha of the active substance (a.s.) of nitrogen, phosphorus and potassium fertilizers); semi-intensive variety Zdobutok: 1.2 g/cm3 and 80% of LMC (at the application of 45 kg/ha of nitrogen and phosphorus fertilizers, and 90 kg/ha of potassium fertilizers). In the course of field research, a decrease in the use of nutrients from the soil was revealed: nitrogen by 4.0% — for intensive and 2.0% — for semi-intensive varieties; phosphorus — by 3.4 and 4.7%; potassium — by 10.7 and 6.3%, respectively, at a high (1.4 g/cm3) level of compaction compared to its low (1.0 g/cm3) level. Under the same conditions, a decrease in the yield of spring barley grain was revealed: intensive variety — by 25, semi-intensive — by 22%. Conclusions. According to the results of experimental studies, the complex influence of soil moisture and compaction levels was revealed and their optimal parameters were established for growing intensive and semi-intensive varieties of spring barley, which achieved their maximum yield in soil fertilization.