Soil Variables Research Articles

Soil loss due to crop harvesting in highly mechanized agriculture: A case study of sugar beet harvest in northern Germany

Soil loss due to crop harvesting (SLCH) is a globally occurring and underestimated process that promotes soil degradation. Despite its negative effects on soil functionality and fertility SLCH has received comparatively little scientific attention to date. In Europe, sugar beets hold particular significance due to high production rates, while research in commercial mechanized farming of sugar beets is lacking. The aim of this study is to measure SLCH for sugar beets including nutrient and SOC losses using typical state of the art harvesters and compare that values to estimated SLCH provided by sugar beet factories. In addition, we tried to identify crop and soil variables that influence SLCH. Therefore, sugar beets and soil samples were collected for 14 sampling sites over a three-year period in Northern Germany to measure SLCH dependent on different crop characteristics, soil properties and weather conditions. The results indicate that SLCH is 0.064 kg per kg harvested sugar beet (SLCHspec) on the average, which corresponds to a loss of 5.7 Mg ha-1 harvest-1 (SLCHcrop). These numbers are higher than former comparable studies but also of about 83.3% higher than SLCH estimated by sugar beet factories. Additionally, amounts of SLCH considerably varied between years and fields, but also within fields. The most influential variables on SLCH are soil water content (SWC) and clay content, and we also observed that soil properties impact SLCH differently in relation to SWC. Moreover, we estimated that SLCH of sugar beets can lead to significant SOC and nutrient losses, latter resulting in direct costs for farmers of 18–34.4 € ha-1 harvest-1. The results confirm the importance of considering SLCH for soil degradation analyses and estimations and the need for models which spatially assess SLCH from field to global scales. This is important to explore soil conservation measures and strategies to reduce ongoing soil degradation especially in highly mechanized agriculture.

Medium-Term Comparative Effects of Prescribed Burning and Mechanical Shredding on Soil Characteristics in Heathland and Shrubland Habitats: Insights from a Protected Natural Area

Parts of the Cantabrian Mountains (N Spain) have been colonized by woody species in the past six or seven decades as a result of a decline in livestock activity and changes in the fire regime. Various management strategies have been used to prevent the expansion of shrubs and recover grassland ecosystems for grazing activities. However, it is not clear how different vegetation treatments affect soils, which are crucial in supporting life and providing nutrients in these ecosystems. The aim of the present study was to compare the dynamics of the physicochemical and biological soil properties after two vegetation treatments: prescribed burning and shredding. Samples were obtained from plots representing alkaline and acidic soils dominated by gorse shrub (Genista hispanica subsp. occidentalis) and heath (Calluna vulgaris) plant communities, respectively. The soil samples were collected immediately before and after the treatments and one and two years later. The level of available P varied depending on the soil pH, and it only increased after the treatments in the acidic soils in the heathland community. The total N and available P concentrations were higher after the prescribed burning, and the enzymatic activity tended to be higher after the shredding treatment. Despite the significant effects on some soil variables, prescribed burning and shredding did not have important short- and medium-term effects on the chemical and soil enzymatic properties. These treatments can therefore be considered sustainable vegetation management tools, at least in the medium term.

How do soil and topographic drivers determine tree diameter spatial distribution in even aged cork oak stands installed in average to high productivity areas

Local terrain or microsite conditions influence the development of trees, particularly at early ages. These conditions might be described by edaphic or topographic variables. We mapped soil and topographic variables from four even-aged and even-spaced cork oak plantations located in two climatically distinct Portuguese regions. The major goal of this research was to understand the relation between soil and topographic fine-scale conditions and tree growth expressed by diameter without cork annual growth (idu). The methodology consisted in (1) analysing the spatial variability and autocorrelation of idu; (2) modelling idu with ordinary least squares (OLS) regressions; (3) comparing with spatial modelling of idu, incorporating spatial autocorrelation. The driest stands A and B, exhibited weaker spatial autocorrelation, distributed in smaller clusters (R2 < 0.03, OLS models), while stands C (R2 = 0.18, OLS models) and D (R2 = 0.11, OLS models) showed higher predictive capacity. Spatial models increased R2 scores, keeping most variables from OLS models and accounting for spatial autocorrelation. A + B + C + D OLS model obtained an R2 = 0.34 and respective spatial model R2 = 0.58. Apparent electrical conductivity at 0.5 (ECa0.5) and 1 m of soil depth, slope, elevation and topography position index were included as predictors (OLS), but only ECa0.5, slope and elevation were selected in the spatial model. Models were fitted using average to high productivity stands and should be used cautiously outside this range. Local terrain conditions determine the growth of young cork oak trees. Mapping soil and topographic variables before establishing new plantations may identify limiting microsite conditions where using cork oak species is not suitable due to low growth rates expectations.

Morphological responses of root hairs to changes in soil and climate depend on plant life form

IntroductionRoot hairs increase the surface area of a plant’s root system that is in contact with the soil, thus facilitating plant water and nutrient uptake. However, little is known about the characteristics of the root hairs of herbaceous and woody plants and their specific response patterns to biotic and abiotic variables from the perspective of resource acquisition strategies in the context of global change.MethodsHere, we analyzed 74 published case studies with 1074 observations of root hair traits to identify patterns of root hair length, density and diameter in relation to soil (e.g., soil pH, nutrient levels), growing environments (e.g., greenhouse, field) and climatic factors (e.g., air temperature), as well as genome size and plant age.ResultsRoot hairs were longer, denser and thicker in woody plants compared with herbaceous plants, and the length and diameter of root hairs in herbaceous plants increased with genome size. With increasing plant age, woody plants had significantly longer and thicker root hairs, while root hair density and diameter declined significantly for herbaceous plants. Soil-cultured plants had longer root hairs than solution-cultured plants. The length and density of root hairs were greater in greenhouse-cultured plants than in field-grown plants, and the latter had thicker root hairs than the former. As soil pH increased, root hair length increased but diameter decreased in woody plants, while root hair density increased in herbaceous plants. Increased soil total nitrogen (N) and potassium (K) significantly increased root hair length, density and diameter in herbaceous plants, while soil total N significantly decreased root hair density in woody plants. Root hair length increased significantly, while root hair density decreased significantly, with higher mean annual temperature and greater precipitation seasonality, while the opposite pattern was true for a wider annual temperature range.DiscussionOur findings emphasize the life-form-specific responses of root hairs to soil and climatic variables. These findings will help deepen our understanding of resource acquisition strategies and their mechanisms in different plant forms under global climate change.

Diversity and Carbon Storage in Fodder Trees of the Lower and Middle Ouémé Valley, Benin: Ecological and Pastoral Sustainability

This study examines the species composition and carbon stock of fodder trees within the Lower and Middle Ouémé Valley (LMOV), highlighting the key role these species play in pastoral ecosystems and carbon sequestration. A total of 22 species were identified, with Leguminosae dominating at 36%. Noteworthy six species such as M. inermis, L. sericeus, P. santalinoides D. oliveri, P. erinaceus, and A. leiocarpa exhibited the highest Importance Value Index (IVI), signifying their importance in local pastoral practices. Our research utilized nondestructive allometric equations to estimate both above and belowground biomass, further assessing the effects of soil and climatic variables on carbon stocks. The carbon stock varied significantly with vegetation type, influenced predominantly by the density and basal area per hectare. Additionally, the study validated the positive correlation between species richness and carbon storage capacity, supporting the role of biodiversity in enhancing ecosystem resilience. Significant findings from regression models indicated that climate variables generally increased carbon stock, whereas certain soil parameters reduced it. This study underscores the necessity of conserving diverse fodder species to support sustainable pastoralism and carbon mitigation efforts in sub-Saharan Africa.

Lichen biocrusts contribute to soil microbial biomass carbon in the northern temperate zone: A meta‐analysis

AbstractBiological soil crusts (biocrusts) have crucial ecological functions in dryland ecosystems, yet understanding the variations in soil microbial biomass within biocrusts across diverse ecosystems, climates and soil conditions remains limited. This knowledge gap constrains our understanding of how microbial communities within biocrusts regulate terrestrial carbon and nitrogen cycling. Hence, we conducted a meta‐analysis using 255 paired observations from 42 study sites across the northern temperate ecosystem. The analysis revealed that biocrusts harbour significantly higher soil microbial biomass carbon and nitrogen (SMBC and SMBN, respectively) levels than bare (non‐biocrust) soil across all habitat types. Notably, deeper soil layers (5–10 and &gt;10 cm) accumulated less SMBC and SMBN than biocrust and biocrust–5‐cm soil, revealing that biocrusts influence shallow soil environments. Ecosystem type, soil texture, depth and season emerged as key factors influencing the distribution of SMBC within biocrusts. Of particular interest, lichen biocrusts accumulated the most SMBC compared with other biocrust types. Furthermore, the difference in SMBC between biocrust and non‐biocrust soils was more pronounced in oligotrophic habitats (e.g., desert, grassland, sand and sandy loam soils) than in eutrophic habitats (e.g., forest and loam soils). Random forest analysis confirmed that soil variables affected SMBC accumulation in biocrusts more than climatic factors. Soil organic carbon (SOC), as the primary source of SMBC, could be the most important determinant. Moreover, the disparity between non‐biocrust SMBC and biocrust SMBC increased with increasing mean annual temperature (MAT) or decreasing altitude. These insights underscore the substantial contribution of lichen biocrusts to SMBC and emphasize the need to incorporate this knowledge into regional models for predicting the effects of climate change on soil carbon budgets within biocrust microbiomes in temperate ecosystems of the Northern Hemisphere.

Relationship of selected properties of Cambisols to altitude and forest ecosystems of four vegetation grades

Currently, little is known about the spatial variability of significant soil properties and their relationships to forest ecosystems of different vegetation grades. This work evaluates the variability of the properties of the upper layer of Cambisol taxa and their relationship to altitude and forest ecosystems of 2nd to 5th forest vegetation grades selected in the Western Carpathians using PCA and regression analysis. The content of clay, total carbon and total nitrogen, humus, energy, and ash in the soils varied between 5.43 and 11.53 %, 21–65 mg g−1, 1.9–4.7 mg g−1, 36–112 mg g−1, 438.4–5845.7 J g−1 and 852.9–946.3 mg g−1, and C/N, pHH2O, and pHKCl values ranged between 11.2 and 16.7, 4.0–5.8 and 3.1–4.6. PCA showed that EAC in the 3rd oak-beech vegetation grade had significantly higher pH values and significantly lower energy content, ESC in the 4th beech vegetation grade had a significantly higher ash content and a significantly lower energy content, and DC in the 5th fir-beech vegetation grade had a significantly higher content of Ct, Nt, and humus. Linear regression revealed a strong negative correlation between the energy content and soil reaction (R2 for pHH2O = 0.48; R2 for pHKCl = 0.38) for all Cambisol taxa. Ct content and ash show a strong negative correlation (R2 = 0.78). The positive relationship between altitude and FVGs was found only for the soil Ct (R2 = 0.87), Nt (R2 = 0.81), and humus content (R2 = 0.87). A strong negative linear relationship between altitude and FVGs showed the ash content (R2 = 0.77). In turn, the oscillatory, polynomial course had a relationship between the clay content (R2 = 0.65) and energy (R2 = 0.75) to altitude and FVGs. Recognizing significant soil variables and better understanding their impact on the development of forest ecosystems is a prerequisite for distinguishing areas with the highest risk of their damage under conditions of various anthropogenic interventions and climate change. Therefore, this topic continues to require increased research efforts. For this reason, a better understanding of the relationships between soil properties and ecologically differentiated communities of forest ecosystems will allow us to identify areas with the highest risk of ecological changes that could lead to the degradation of European forests in the future.

A general pattern of plant traits and their relationships with environmental factors and microbial life-history strategies

The trait-based unidimensional plant economics spectrum provides a valuable framework for understanding plant adaptation strategies to the environment. However, it is still uncertain whether there is a general multidimensionality of how variation of both leaf and fine root traits are influenced by environmental factors, and how these relate to microbial resource strategies. Here, we examined the coordination patterns of four pairs of similar leaf and fine root traits of herbaceous plants in an alpine meadow at the community-level, and their environmental driving patterns. We then assessed their correlation with microbial life-history strategies, as these exhibit analogous resource strategies with plants in terms of growth and resource utilization efficiency. Results exhibited an analogous multidimensionality of the economics spectrum for leaf and fine root traits: the first dimension, collaboration gradient, primarily represented a tradeoff between lifespan and resource foraging efficiency; the second dimension, conservation gradient, primarily represented a tradeoff between conservation and acquisition in resource uptake. Climate variables had a stronger impact on both dimensions for leaf and fine root traits than soil variables did; whereas, the primary drivers were more complex for fine root traits than for leaf traits. The collaboration gradient of leaf and fine root traits exhibited consistent relationships with soil microbial life-history strategies, both showed negative and positive correlation with bacterial and fungal strategies, respectively. Our findings suggest that both leaves and fine roots have general multidimensional strategies for adapting to new environments and provide a solid basis for further understanding the relationships between the adaptive strategies of plants and microbes.

Light grazing alleviates aeolian erosion–deposition effects on microbial communities in a semi-arid grassland

BackgroundSoil erosion affects the stability of terrestrial ecosystems and ecosystem services by directly or indirectly impacting the cycling of soil materials and energy and reducing the fertility of grassland soils. However, research on microbial adaptation to grazing and soil erosion is limited, particularly in relation to grassland ecosystem restoration. Here, we assess microbial communities subjected to simulated soil erosion and grazing in a semi-arid grassland of Inner Mongolia, China.ResultsNo significant change was observed in soil variables. However, the structure of the soil microbial community underwent significant changes as a result of soil erosion and soil erosion plus grazing, leading to a significant increase in the relative abundance of Cyanobacteria (116.80% vs 116.38%). Wind erosion and deposition contributed to an increase in the network complexity of soil bacterial and fungal communities. However, much of this effect was alleviated by grazing. Simultaneously, aeolian processes and grazing regulate soil microbial community assembly, leading to inconsistent patterns of change in bacterial and fungal communities. Under wind erosion and deposition, the relative contribution of deterministic processes (4.44% vs 31.11%) in bacterial communities increased, while the relative contribution of stochastic processes (2.23% vs 20%) in fungal communities reduced. Grazing resulted in a decrease in the relative contribution of deterministic processes (8.89%) in the bacterial community and an increase in the relative contribution of stochastic processes (8.89%) in the fungal community.ConclusionThis study presents a comprehensive investigation of the response of soil microbial communities to aeolian erosion–deposition and grazing in a semi-arid grassland. Our findings indicate that microbial communities in the semi-arid grassland show resistance to external disturbances and that light grazing mitigates the effects of aeolian erosion–deposition on microbial communities, which is essential for maintaining the stability and biodiversity of grassland ecosystems.

Climate-Change-Driven Shifts in Aegilops tauschii Species Distribution: Implications for Food Security and Ecological Conservation

Climate change has diverse effects on the planet’s environment, including changes and shifts in the distribution and abundance of species. In this paper, we present a robust prediction ensemble algorithm for the current and future species distribution of Aegilops tauschii. Four modeling approaches were trained using various environmental variables (bioclimatic and soil variables) to accurately predict the species distribution for future scenarios. The results showed that GBM and RF demonstrated the most accurate predictions with an Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.80 and 0.83, respectively. The results of variable importance depicted that the temperature seasonality (bio4) was the most important and effective factor in determining the habitat suitability of Ae. tauschii, followed closely by the precipitation seasonality (bioclimate 15) and the mean temperature of the warmest quarter (bio10). Then, the distribution maps of Ae. tauschii were produced under climate change scenarios for 2050 and 2070. The results showed that Ae. tauschii will lose some of its suitable habitats under climate change and that this loss will be more severe in the east part of the study area. The results of the present study have important implications for ecological conservation as they can assist in identifying critical habitats and inform conservation planning efforts. Our model provides a valuable tool for understanding the potential future distribution of Ae. tauschii and highlights the need for continuous monitoring and protection of this species.

Aggregated database of forest soil chemical properties in the Czech Republic based on surveys from 2000 to 2020

Key messageThe dataset includes data from forest soil surveys conducted in the period 2000–2020. It provides soil and site variables from 8269 locations. Data are aggregated in three basic soil layers: upper organic soil horizon (FH, 6875 locations), upper mineral layer 0–30 cm (M03, 8051 locations) and deeper mineral soil layer 30–80 cm (M38, 2260 locations).The dataset is available at https://doi.org/10.5281/zenodo.10608814, and access to the metadata is at https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/38f24573-3c0d-469a-a66a-7060ce082155.

Differences in shrimp pond bottom soil properties and bacterial load between acute hepatopancreatic necrosis disease (AHPND)‐infected ponds and AHPND‐free ponds and their relation to AHPND

AbstractThis study investigated the disparities in soil characteristics and pathogenic bacteria prevalence between shrimp ponds affected by acute hepatopancreatic necrosis disease (AHPND) and unaffected ponds, alongside examining the spatial distribution of soil attributes in flat‐oriented pond soil strata. Using Pearson correlation and logistic regression analyses, relationships among variables and indicators associated with AHPND prevalence were discerned, leading to the formulation of a predictive model for AHPND occurrence. Soil samples were collected from distinct locations and depths within ponds across three southern provinces of Thailand's Andaman Seaboard. The analysis revealed significantly higher concentrations of several variables, including SOD, TIC, NO2−‐N, Ca, Mn, Cu, Zn, and specified Vibrio strains, in AHPND‐afflicted ponds, especially at 0–5 cm depth. A prominent differentiation was the escalated concentration of easily decomposable organic matter (EDOM) within infected ponds, implicating potential soil and water quality deterioration alongside heightened shrimp susceptibility to AHPND. Correlational analysis showed links between bacterial densities and organic matter groupings, trace elements, exchangeable bases, and soil pH, in AHPND‐infected ponds. The logistic regression model encapsulated three soil variables (TOC, Mg, and Mn) and one pathogen variable (V. parahaemolyticus) and furnished an equation to estimate the log (odds) of AHPND occurrence, facilitating better understanding and potential forecasting of AHPND prevalence in shrimp cultivation environments.

Evolutionary history shapes variation of wood density of tree species across the world

The effect of evolutionary history on wood density variation may play an important role in shaping variation in wood density, but this has largely not been tested. Using a comprehensive global dataset including 27,297 measurements of wood density from 2621 tree species worldwide, we test the hypothesis that the legacy of evolutionary history plays an important role in driving the variation of wood density among tree species. We assessed phylogenetic signal in different taxonomic (e.g., angiosperms and gymnosperms) and ecological (e.g., tropical, temperate, and boreal) groups of tree species, explored the biogeographical and phylogenetic patterns of wood density, and quantified the relative importance of current environmental factors (e.g., climatic and soil variables) and evolutionary history (i.e., phylogenetic relatedness among species and lineages) in driving global wood density variation. We found that wood density displayed a significant phylogenetic signal. Wood density differed among different biomes and climatic zones, with higher mean values of wood density in relatively drier regions (highest in subtropical desert). Our study revealed that at a global scale, for angiosperms and gymnosperms combined, phylogeny and species (representing the variance explained by taxonomy and not direct explained by long-term evolution process) explained 84.3% and 7.7% of total wood density variation, respectively, whereas current environment explained 2.7% of total wood density variation when phylogeny and species were taken into account. When angiosperms and gymnosperms were considered separately, the three proportions of explained variation are, respectively, 84.2%, 7.5% and 6.7% for angiosperms, and 45.7%, 21.3% and 18.6% for gymnosperms. Our study shows that evolutionary history outpaced current environmental factors in shaping global variation in wood density.

Patterns and drivers of plant carbon, nitrogen, and phosphorus stoichiometry in a novel riparian ecosystem.

Carbon (C), nitrogen (N), and phosphorus (P) stoichiometry serve as valuable indices for plant nutrient utilization and biogeochemical cycling within ecosystems. However, the allocation of these nutrients among different plant organs and the underlying drivers in dynamic riparian ecosystems remain inadequately understood. In this study, we gathered plant samples from diverse life forms (annuals and perennials) and organs (leaves, stems, and roots) in the riparian zone of the Three Gorges Reservoir Region (TGRR) in China-a novel ecosystem subject to winter flooding. We used random forest analysis and structural equation modeling to find out how flooding, life forms, plant communities, and soil variables affect organs C, N, and P levels. Results showed that the mean concentrations of plant C, N, and P in the riparian zone of the TGRR were 386.65, 19.31, and 5.27 mg/g for leaves respectively, 404.02, 11.23, and 4.81 mg/g for stems respectively, and 388.22, 9.32, and 3.27 mg/g for roots respectively. The C:N, C:P and N:P ratios were 16.15, 191.7 and 5.56 for leaves respectively; 26.98, 273.72 and 4.6 for stems respectively; and 16.63, 223.06 and 4.77 for roots respectively. Riparian plants exhibited nitrogen limitation, with weak carbon sequestration, low nutrient utilization efficiency, and a high capacity for nutrient uptake. Plant C:N:P stoichiometry was significantly different across life forms and organs, with higher N and P concentrations in leaves than stems and roots, and higher in annuals than perennials. While flooding stress triggered distinct responses in the C, N, and P concentrations among annual and perennial plants, they maintained similar stoichiometric ratios along flooding gradients. Furthermore, our investigation identified soil properties and life forms as more influential factors than plant communities in shaping variations in C:N:P stoichiometry in organs. Flooding indirectly impacts plant C:N:P stoichiometry primarily through alterations in plant community composition and soil factors. This study underscores the potential for hydrologic changes to influence plant community composition and soil nutrient dynamics, and further alter plant ecological strategies and biogeochemical cycling in riparian ecosystems.

Predicting Current and Future Habitat Suitability of an Endemic Species Using Data-Fusion Approach: Responses to Climate Change

Fritillaria imperialis L., an indicator plant species in Iran, is facing threats and its population has declined in recent years. To provide insights into the drivers affecting its loss, this research aims to identify the effects of three groups of factors, including climate, soil, and physiographic variables, on the current and future spatial distributions of F. imperialis. For this purpose, we used five machine learning algorithms as well as an ensemble forecasting of species distribution approach to explain the geographical distributions of the species as a function of these factors. In addition, we used two shared socio-economic pathways scenarios – SSP 1-2.6 and SSP 5-8.5 – to project the future distributions of F. imperialis in 2030, 2050, 2070, and 2090. Based on evaluation indices, area under the ROC curve (AUC) and true skill statistic (TSS), the Random Forest (RF) model generated the strongest prediction of the distribution of F. imperialis (TSS>0.9 and AUC>0.9). No significant difference observed among the three datasets (climate-only variables, climate + physiography variables, and climate + physiography + soil variables) in terms of AUC values. In models using climate + physiography + soil datasets, soil electrical conductivity, clay, and pH emerged as the most important variables affecting the growth and development of F. imperialis while climate factors played a lesser role in its distribution. Future projections revealed different patterns when using the optimistic (SSP 1-2.6) and pessimistic (SSP 5-8.5) socio-economic pathway scenarios and either the climate only or climate + physiography models. The climate + physiography + soil model produced similar prediction patterns for the scenarios. The climate-only models predicted larger areas suitable for crown imperial in the future than did the climate + physiography + soil model. These results emphasize the consideration of factors beyond climate scenarios when modeling biological responses to global warming and regional climate change.

Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method

Abstract. Radar at high frequency is a promising technique for fine-resolution snow water equivalent (SWE) mapping. In this paper, we extend the Bayesian-based Algorithm for SWE Estimation (BASE) from passive to active microwave (AM) application and test it using ground-based backscattering measurements at three frequencies (X and dual Ku bands; 10.2, 13.3, and 16.7 GHz), with VV polarization obtained at a 50° incidence angle from the Nordic Snow Radar Experiment (NoSREx) in Sodankylä, Finland. We assumed only an uninformative prior for snow microstructure, in contrast with an accurate prior required in previous studies. Starting from a biased monthly SWE prior from land surface model simulation, two-layer snow state variables and single-layer soil variables were iterated until their posterior distribution could stably reproduce the observed microwave signals. The observation model is the Microwave Emission Model of Layered Snowpacks 3 and Active (MEMLS3&amp;amp;a) based on the improved Born approximation. Results show that BASE-AM achieved an RMSE of ∼ 10 cm for snow depth and less than 30 mm for SWE, compared with the RMSE of ∼ 20 cm snow depth and ∼ 50 mm SWE from priors. Retrieval errors are significantly larger when BASE-AM is run using a single snow layer. The results support the potential of X- and Ku-band radar for SWE retrieval and show that the role of a precise snow microstructure prior in SWE retrieval may be substituted by an SWE prior from exterior sources.

Analyzing the Impact of Storm ‘Daniel’ and Subsequent Flooding on Thessaly’s Soil Chemistry through Causal Inference

Storm ‘Daniel’ caused the most severe flood phenomenon that Greece has ever experienced, with thousands of hectares of farmland submerged for days. This led to sediment deposition in the inundated areas, which significantly altered the chemical properties of the soil, as revealed by extensive soil sampling and laboratory analysis. The causal relationships between the soil chemical properties and sediment deposition were extracted using the DirectLiNGAM algorithm. The results of the causality analysis showed that the sediment deposition affected the CaCO3 concentration in the soil. Also, causal relationships were identified between CaCO3 and the available phosphorus (P-Olsen), as well as those between the sediment deposit depth and available manganese. The quantified relationships between the soil variables were then used to generate data using a Multiple Linear Perceptron (MLP) regressor for various levels of deposit depth (0, 5, 10, 15, 20, 25, and 30 cm). Then, linear regression equations were fitted across the different levels of deposit depth to determine the effect of the deposit depth on CaCO3, P, and Mn. The results revealed quadratic equations for CaCO3, P, and Mn as follows: 0.001XCaCO32 + 0.08XCaCO3 + 6.42, 0.004XP2 − 0.26XP + 12.29, and 0.003XMn2 − 0.08XMn + 22.47, respectively. The statistical analysis indicated that corn growing in soils with a sediment over 10 cm requires a 31.8% increase in the P rate to prevent yield decline. Additional notifications regarding cropping strategies in the near future are also discussed.

Association of Plant-Parasitic Nematodes and Soil Physicochemical Properties in Tomatoes in Turfloop, Limpopo Province, South Africa

Turfloop constitutes an area in Mankweng, situated in the Limpopo Province of South Africa, where several villages are home to smallholder farmers who specialize in vegetable farming. Among the most crucial crops cultivated in this region is tomato, a fruit that has gained significant commercial importance due to its high demand and versatility in various culinary applications. To determine the relationship of plant-parasitic nematodes and soil physicochemical properties, soil samples were collected from tomato fields. Overall, our results showed that seven nematode genera were in the tomato fields. There was a significant positive correlation between the number of Meloidogyne and potassium (r = 0.903) and a negative correlation with Na (r = −0.684). In contrast, there was no association between the number of Meloidogyne spp. and the pH and texture of the fields. The number of Criconema in the field was negatively correlated with pH (r = −0.732). Soil texture percentages, including clay (r = 0.744), sand (r = −0.744), and silt (r = 0.706), were only correlated with the number of Criconema. The number of dagger nematodes, Xiphinema, was only correlated negatively with NH4+ (r = −0.589) and positively with boron (B) (r = 0.779). None of the soil variables were correlated with the number of Pratylenchus. The principal component analysis (PCA) placed soil samples of tomatoes together, in which the number of Meloidogyne was not correlated to any soil sample site. In conclusion, plant-parasitic nematodes that were associated with tomatoes are of high economic importance as they can reduce the yield. Criconema was found to be sensitive to the soil’s physicochemical properties. In addition, Helicotylenchus was found in all soil samples. Our results suggest that the plant-parasitic nematodes in tomatoes have high diversity with the potential to reduce crop production.

Exploring the driving forces and digital mapping of soil biological properties in semi-arid regions

Soil biological properties (SBPSs) are crucial for soil health and ecosystem functioning. Mapping these properties can provide insights into soil ecosystems and help develop management and conservation strategies. The objective of this study was to map five important indicators of SBPSs, namely urease (Ur), acid phosphatase (ACP), alkaline phosphatase enzyme (ALP) activity, metabolic quotient (qCO2), and soil microbial biomass to soil organic carbon ratio (MBC: SOC) using machine learning algorithms (MLA) and to identify the most important driving factors of these properties. The study was conducted in Honam sub-basin, Lorestan, Iran, on an area of 14,000 ha. 90 surface soil samples (0–30 cm) were collected and analyzed in the laboratory. 60 soil and environmental covariates, including soil, topography, and remote sensing data (RS), were used to represent influencing factors. The most relevant covariates were selected based on correlation and recursive feature elimination (RFE) analysis using two state-of-the-art MLAs, Random Forest (RF) and Extreme Gradient Boosting (XGBoost) trees, were used to predict SBPSs based on the selected covariates. Relative importance analysis and partial dependence plots were used to evaluate the effects of different factors on the prediction of SBPSs. The results showed that 28 soil and environmental covariates were selected as relevant factors. Both RF and XGBoost models performed well and achieved acceptable accuracy (as measured by R2 value). XGBoost outperformed RF on qCO2 (R2 = 0.61), ALP (R2 = 0.73) and Ur (R2 = 0.75), while RF performed better on ACP (R2 = 0.65) and the MBC: SOC (R2 = 0.81). Relative importance analysis showed that ACP and Ur were most strongly associated with the soil variables at 79 % and 42 %, respectively. ALP and qCO2 were strongly correlated with topographic attributes at 56 % and 52 %, respectively. MBS: SOC was about 40 % associated with the RS indices. The influence of each SBPS varied depending on the specific types of covariates. These results highlight the potential of targeted strategies for effective management and protection of soil ecosystem leading to improved soil health and ecosystem function. Further research should focus on developing methods that encompass a broader range of indices that influence soil microbial activity in drylands.

The Importance of Variety and Regional Identity on the Dextrin-Reducing Enzymatic Activity of Cascade and Mosaic® Hops Grown in Washington and Oregon

This study analyzed hops from 35 fields located in two states (Washington and Oregon) repeatedly over 2 harvest years (2020 and 2021) to determine the impact that hop variety and regional identity, or “terroir,” might have on hops’ dextrin reducing enzymatic potential. Cascade and Mosaic® hops were harvested, kilned, pelletized, and analyzed for dextrin-reducing enzymatic activity using a bench-top dry-hopping assay in a high-dextrin beer. In addition, data for 25 soil, 14 management, 13 climate, and 27 chemistry variables were collected and compared to the enzyme activity results from the bench-top dry-hopping assay. There existed a highly significant difference in enzymatic activity based on hop variety (two sample t-test p-value = 1.18 × 10−14) with Cascade hops being approximately 60% higher on average than Mosaic® hops regardless of growing region or harvest year. The soil and farm management variables also showed statistically significant interactions with enzymatic activity (p-values of 7.82 × 10−9 for Cascade and < 2 × 10−16 for Mosaic®), though there was little clarity with respect to the specific “terroir” variables that might relate to hop creep. Further research is needed to better understand causal interactions between farm, soil, climate, and management practices and dry-hop-induced dextrin-reducing enzymatic activity.