Fallow Land Research Articles

Mapping winter fallow arable lands in Southern China by using a multi-temporal overlapped area minimization threshold method

ABSTRACT In China, a nation facing farmland scarcity, accurate mapping of winter fallow arable lands is crucial for enhancing crop rotation and land use efficiency. The Dynamic Threshold (DT) method commonly used in phenology and winter fallow land studies often employs empirically set subjective thresholds. This approach tends to uniformly apply a single threshold across diverse vegetation types and geographical regions, neglecting the variations in physiological traits and spatial heterogeneity. This study developed a multitemporal overlapping area minimization threshold method (MOAMT). This approach constructed Normalized difference vegetation index (NDVI) probability density functions for both winter fallow and non-winter fallow arable land across a time series to attain a statistically significant threshold. We use MOAMT and DT methods for winter fallow arable land extraction in southern China, respectively. And then, comparison of identification accuracy between MOAMT and DT has been implemented by using confusion matrix method. Compared to the DT method, MOAMT exhibits better performance. The mapping of winter fallow arable lands highlighted their predominant distribution in the middle and lower reaches of the Yangtze River (MLR-YR) Basin, covering approximately 20.8 million hectares, with potential for development. This study will provide information support for the optimization of planting layouts in China, offering new opportunities for further increasing grain production. While in the sense of research approach, this study indicates the superiority of threshold obtained through statistical probability calibration over empirical universal thresholds for classification accuracy. We advocate for prioritizing threshold calibration in future applications of threshold classification methods.

Technical and technological support for the involvement of fallow lands in agriculture

Sustainable development of agricultural production is a key factor in ensuring food security and growth of the country's export potential. One of the main reserves for the development of the agro-industrial complex is the involvement of fallow lands in agricultural industry, which is associated with the problem of technical and technological support for these works. The purpose of the work is to intensify the process of involving fallow lands in agriculture by developing a program of technical and technological support for this type of works, aimed at creating and accelerated implementation of a system of specialized machines. The authors systematized technologies and complexes of technical means, used in the involvement of fallow lands in crop production, depending on the stages of wild species overgrowth. For active involvement of fallow lands in agriculture, it is proposed to create a network of regional machine-technological stations equipped with modern domestic specialized equipment, providing services in removal of woody and shrubby vegetation and in initial tillage to agricultural producers in regions. The program assumes the development and organization of mass production of modern equipment for the involvement of fallow lands in agriculture, as well as implementation of a set of support measures aimed at accelerated technical equipment of machine-technological stations. Such an approach should make it possible for small and medium-sized agricultural producers to use financially affordable machinery services to involve fallow lands in agriculture, eliminating the need for its acquisition and maintenance, hiring and training of additional stuff. The implementation of the proposed program should allow agricultural producers to involve fallow lands in agricultural production with minimal costs, at the same time ensuring high growth rates of acreage and agricultural production volumes.

Can Landuse Landcover changes influence the success of India's national clean air plans ?

India implemented a range of multifarious strategies to address the issue of substandard air quality. One such flagship scheme of government of India is National Clean Air Programme (NCAP), which recommends sector specific reduction in emissions and increase in forest cover etc. To reduce particulate matter concentrations by 40% in 2026 compared to 2019. The present study aims to gauge the impact of Land Use Land Cover (LULC) changes alone on success of NCAP, using weather research forecasting model with chemistry (WRF-Chem) and integrated geographical information system and remote sensing software Terrset. The findings elucidate that, by the year 2026, the Ventilation Coefficient (VC) in India's eastern, central, northern, and north-eastern regions is anticipated to register a decline ranging from 18% to 50% compared to the baseline year of 2019. Conversely, an increase of 17% is expected in the southern region. The alterations in Fallow Land, Barren and sparsely vegetated land, Urban and Built-up Land, and Tundra, contribute to these shifts, displaying varying percentage changes across distinct zones. Simulations indicate that these LULC changes are impeding the planned reduction in PM2.5 levels. Projections suggest an increase in PM2.5 levels as high as 13% in the eastern, central, northern, and north-eastern regions, accompanied by a decrease of 33% in the Southern zone of the country. Significantly, non-attainment cities in Himachal Pradesh and Maharashtra are expected to witness a substantial rise in PM2.5-induced premature mortality, with Pune city projected to experience over 24,525 additional premature deaths by 2026. A comparable examination conducted for the year 2022, utilizing actual LULC data, suggests that if the NCAP fails to effectively implement LULC changes, it may reduce this anticipated trade-off. Addressing this concern, the study employed WRF-Chem to simulate 60 combinations, proposing LULC enhancements conducive to improving VC. The results underscore the critical importance of preserving at least 36% of the LULC category of mixed forest land, encompassing plantations, orchards, and areas under shifting agriculture. Additionally, a reduction in barren land and fallow land emerges as pivotal for enhancing the ventilation coefficient. The study accentuates the necessity of refraining from further expansion in densely populated areas to counter these anticipated VC trends. This study provides valuable insights, highlighting the need to prioritize LULC management to effectively combat the alarming air pollution.

Assessment of land use/ land cover change derived catchment hydrologic response: An integrated parsimonious hydrological modeling and alteration analysis based approach

Land use/land cover (LULC) change, often a consequence of natural or anthropogenic drivers, plays a decisive role in governing global catchment dynamics, and subsequent impact on regional hydrology. Insight into the complex relationship between the drivers of LULC change and catchment hydrology is of utmost importance to decision makers. Contemplating the dynamic rainfall-runoff response of the Indian catchments, this study proposes an integrated modeling-based approach to identify the drivers and relative contribution to catchment hydrology. The proposed approach was evaluated in the tropical climate Nagavali River Basin (NRB) (9512 km2) of India. The Soil and Water Assessment Tool (SWAT) hydrological model, which uses daily-scale rainfall, temperature, wind speed, relative humidity, solar radiation, and streamflow information was integrated with the Indicators of Hydrologic Alteration (IHA) technique to characterize the plausible changes in the flow regime of the NRB. Subsequently, the Partial Least Squares Regression (PLSR) based modeling analysis was performed to quantify the relative contribution of individual LULC components on the catchment water balance. The outcomes of the study revealed that forest land has been significantly converted to agricultural land (45–59%) across the NRB resulting in mean annual streamflow increase of 3.57 m3/s during the monsoon season. The affinity between land use class and streamflow revealed that barren land (CN = 83–87) exhibits the maximum positive response to streamflow followed by the built-up land (CN = 89–91) and fallow land (CN = 88–93). The period 1985–1995 experienced an increased ET scenario (911–1050 mm), while the recent period (2005–2020) experienced reduced ET scenario owing to conversion of forest to agricultural land. Certainly, the study endorses adopting the developed methodology for understanding the complex land use and catchment-scale hydrologic interactions across global-scales for early watershed management planning.

Cultural heritage and urban morphology: land use transformation in ‘Kumbh Mela’ of Prayagraj, India

A Hindu pilgrimage site where millions of people gather to seek solutions to problems related to everyday life, the “Kumbh Mela” is recognised as one of India’s intangible cultural heritages. The site of the observance rotates between four cities, Haridwar, Ujjain, Nashik and Prayagraj. The infrastructure and services in the city that is hosting such a gathering undergo numerous changes as a result of the sizeable gathering. The goal of the study is to monitor the changes in Land Use and Land Cover (LULC) in the city of Prayagraj before and after the “Kumbh Mela” and to evaluate the effect on infrastructure changes in the citry. Analyzing the changes that such pilgrimages and events bring about in cities are fascinating. In 2019, the city of Prayagraj hosted the “Kumbh”, hence, Pre-Kumbh (2016), Kumbh (2019), and Post-Kumbh (2022) phases were taken under consideration for LULC change assessment. Supervised classification was conducted using Maximum Likelihood Classifier to prepare LULC maps. It was observed that urbanisation has significantly increased at the expense of vegetation, fallow land, and agricultural land. The success of the local agroforestry policy and plantation drive is demonstrated by the interesting increase in vegetation that has been observed. The construction of a civil airport, the widening of existing roads, the installation of new railroad tracks, and the adornment of roundabouts on existing roads are the major infrastructure changes. The findings offer fresh insights of increasing urban infrastructure from a cultural perspective. The findings will aid in better planning and policy development for the resilient and sustainable infrastructure, as well as in the development of a long-term strategy for the temporary habitation in the “Kumbh” area of such cities.

Assessing the performance of wind erosion prediction models of RWEQ and SWEEP by direct measurements in an arid region

Wind erosion field studies allow researchers to conduct simulations under natural conditions, thus play a significant role in investigating wind erosion processes. Direct measurements are also used to validate and improve existing erosion models. There is a need to develop sustainable land-use practices and management strategies and to assess potential current and future trends of wind erosion risk in arid and semi-arid regions. This study assessed wind erosion-induced soil losses in 11 different wind cases encountered within the wheat-fallow production system in a semi-arid region of Türkiye between 2017 and 2020 to eliminate the wind erosion threats on soil resources. Direct measurements and two estimation models (RWEQ and SWEEP) were employed to assess soil loss. Grid sampling method and BEST® sediment traps were utilized to measure wind-blown soil in the field directly. Present findings revealed that wind erosion threatened both plots in different seasons. The wheat-cultivated plot was highly susceptible to wind erosion in autumn when winter cereals are sown, while the fallow plot showed susceptibility in spring. Throughout the entire measurement period (3-years), wind erosion-induced soil transportation was measured as 1383 kg ha−1 for fallow plots and 2548 kg ha−1 for wheat-cultivated plots. Model performance was assessed through correlations (r), root mean square error (RMSE) and d-test results. The results demonstrated that the calibrated RWEQ (RWEQcal) model provided reasonably accurate estimates of wind erosion for both fallow and wheat-cultivated lands, with relatively low RMSE values of 0.34 and 0.46, d-test values of 0.26 and 0.27, and correlation coefficients of 0.69 and 0.85, respectively. Model results highlighted the importance of model calibration for local conditions; otherwise, they may produce underestimated and overestimated results.

Efecto del pastoreo en la composición y la diversidad florística durante el barbecho en El-Tarf, Argeli

In the El-Tarf region, located in northeastern Algeria, fallow lands are frequently used as grazing grounds for sheep flocks, where they are left all day with a significant grazing load. Limited studies conducted to assess the effects of grazing have yielded varied and sometimes contradictory results, thus underscoring the need for reliable local data. The study aims to assess the impact of grazing on the floristic richness, diversity, production, and chemical composition of fallow lands in the El-Tarf region (northeast Algeria). Measurements were taken during the optimal vegetation period from March to June over a period of 2 years (2019 and 2020). The experimental design included a single factor: grazing intensity (no grazing, moderate grazing, and intense grazing). The results indicated that grazing reduced floristic richness and diversity (Maximum Diversity, Shannon and Weaver Index, Evenness Index), but it did not have an effect on coverage. The non-grazed fallow land is richer, hosting 23 herbaceous species distributed among 8 botanical families, with the most represented being Asteraceae (39 %), followed by Poaceae (26 %). The Fabaceae, on the other hand, display a more modest representation, accounting for only 13 %.Grazing also decreased significantly the biomass and total aboveground herbaceous phytomass, with improvements noted in non-grazed conditions, recording values of 3.80 t.DM.ha-1 and 1.77 t.DM.ha-1, respectively. In addition, grazing had a significant impact on chemical composition, with the highest values recorded for moderate grazing, reaching 14.7 % for total nitrogen content and 11.66 % for mineral content.

Comparative Performance of Aerial RGB vs. Ground Hyperspectral Indices for Evaluating Water and Nitrogen Status in Sweet Maize

This study analyzed the capability of aerial RGB (red-green-blue) and hyperspectral-derived vegetation indices to assess the response of sweet maize (Zea mays var. saccharata L.) to different water and nitrogen inputs. A field experiment was carried out during 2020 by using both remote RGB images and ground hyperspectral sensor data. Physiological parameters (i.e., leaf area index, relative water content, leaf chlorophyll content index, and gas exchange parameters) were measured. Correlation and multivariate data analysis (principal component analysis and stepwise linear regression) were performed to assess the strength of the relationships between eco-physiological measured variables and both RGB indices and hyperspectral data. The results revealed that the red-edge indices including CIred-edge, NDRE and DD were the best predictors of the maize physiological traits. In addition, stepwise linear regression highlighted the importance of both WI and WI:NDVI for prediction of relative water content and crop temperature. Among the RGB indices, the green-area index showed a significant contribution in the prediction of leaf area index, stomatal conductance, leaf transpiration and relative water content. Moreover, the coefficients of correlation between studied crop variables and GGA, NDLuv and NDLab were higher than with the hyperspectral indices measured at the ground level. The findings confirmed the capacity of selected RGB and hyperspectral indices to evaluate the water and nitrogen status of sweet maize and provided opportunity to expand experimentation on other crops, diverse pedo-climatic conditions and management practices. Hence, the aerially collected RGB vegetation indices might represent a cost-effective solution for crop status assessment.

Assessing Soil Quality Under Different Land-Uses Through Constructing Minimum Datasets from Soil Profiles in a Fragile Ecosystem of Northeastern Region of India

ABSTRACT The conversion of forest to agricultural land has been a major worldwide concern and a cause of deterioration of soil quality. The study examined the influence of land uses on the soil quality index (SQI) using minimum datasets (MDS) constructed from soil profiles through two methods namely, additive (SQIa) and weighted (SQIw). In this study, 29 geo-referenced soil profiles (116 layers) up to a depth of 150 cm were collected in Northeastern India, representing forest, jhum, jhum fallow, and agricultural land uses. Principal component analysis (PCA) with multiple correlation analysis is found to be a suitable statistical method for selecting the key soil quality indicators. From PCA, organic carbon (OC), sand, clay, available P and available S were selected as soil quality indicators in MDS. Our results showed that these MDS significantly varied within the profiles depending on the land-uses. The estimated values of SQIs showed that SQIa was higher than SQIw across the soil depths and land-uses. For the surface soil, SQIa values were in the order of forest (2.97) > jhum fallow (2.82) > agriculture (2.68) > jhum land (1.97) and for profile soil jhum fallow (2.38) > forest (2.37) > agriculture (2.33) > jhum (1.88). Similarly, SQIw followed the trend of forest > jhum fallow > agriculture > jhum for all the three studied depths. The statistical analysis showed that the surface, subsurface, and profile soil had no significant impact on SQIw for agriculture, fallow jhum, and forest. The overall data indicated that jhum land had a significantly lower SQI than other land-uses for all soil depths. From this study, the information generated can be useful to assess the soil quality in different land-uses for managing soil health in similar areas of the Northeastern region of India. The findings are also useful in the ecosystems in which soils develop in an acid edaphic environment.

Crop sequence intensification: Meta‐analysis of soil organic carbon and aggregate stability in Argentina

AbstractIntensification of crop sequence (ICS) has been proposed as a key field practice to preserve soil health and achieve more sustainable agricultural systems. However, the effects of ICS are site‐specific and vary according to soil characteristics, climatic conditions, the duration of the crop sequencing and the types of crop involved. Soil aggregate stability (AS) and soil organic carbon (SOC) stock are useful indicators of soil health as they are closely linked to diverse soil services and functions and are sensitive to management practices. We performed a meta‐analysis of 33 studies to analyse the impact of ICS on SOC stock and AS in field experiments in the central‐eastern region of Argentina. Our results showed that ICS increased SOC stock and AS, with an overall mean change of 7% and 22%, respectively. Fine‐textured soils showed the greatest SOC stock increase (12%), comparable to the increase observed in coarse‐textured soils (11%); in medium‐textured soils this increase was less than half (5%). Coarse‐textured soils had the greatest increase in AS (32%), followed by medium‐textured and fine‐textured soils, which also showed notable improvements (25% and 19%, respectively). Greater diversity of crops resulted in larger increases in both AS and SOC. ICS generated a larger increase of SOC stock in the soil surface (0–10 cm) than in the subsurface (10–20 cm), whereas the opposite was found for AS. Long‐term studies (≥9 years) had the greatest effect on AS and SOC stock. Regression analysis revealed that the initial carbon stock influenced SOC stock results following ICS, increases being greater when initial carbon stock contents were smaller. Introducing gramineous species into the crop sequence was associated with a greater improvement of AS and SOC stock. Finally, the mean rate of carbon sequestration from ICS in all the studies amounted to 0.28 Mg ha−1 yr−1. Overall, ICS is a useful strategy for improving SOC storage and AS in this region, though results may vary according to soil characteristics and management practices.

Mapping and Monitoring of Land Use/Land Cover Transformation Using Geospatial Techniques in Varanasi City Development Region, India

Assessing the dynamics and patterns of Land Use and Land Cover (LULC) and its transformation is an important practice of urban planners and environmentalists for a variety of applications, including land management, urban climate modeling, and sustainability of any urban region. Monitoring changes in LULC using geospatial techniques can help to identify areas at risk for indefensible land use, low-grade environment, and especially for sustainable urban planning. This study aims to analyze the changing pattern, dynamics, and alteration of LULC using Google Earth Engine (GEE) and Machine Learning Applications for the years 1991, 2001, 2011, and 2022 in the Varanasi City Development Region (VCDR). The LULC classification was divided into seven classes using random forest classification, and Landsat-5(TM) and 9(OLI-2) satellite data were used. Saga GIS has been utilized for the detection of LULC change during the 1991-2022 period. For validation of classification results, accuracy assessment was estimated using error matrices and through user, producer, and overall accuracy estimation. The Kappa statistics were applied for the reliability of the accuracy assessment result. As a result, the built-up area increased by 507.8 percent, and other classes like agricultural, barren, fallow land, and vegetation cover rapidly declined and altered into concrete areas over the period. Water bodies and river sand classes have been slightly converted into different classes. The finding explains that 114.8 km2 of fertile agricultural land, 14.81 km2 barren land, and 12.93 km2 of vegetation cover transformed into impervious surface, which is unsustainable and causes various problems like food scarcity, environmental degradation, and low quality of urban life. This study can be a useful guide for urban planners, academicians, and policymakers by providing a scientific background for sustainable urban planning and management of VCDR and other cities as well.

Optimizing winter climate control in high-altitude smart greenhouse through renewable energy integration

In the context of food security in mountain regions, this study explores the potential of a Smart Greenhouse (SGH) to address the challenges posed by climate change and limited resources. The SGH utilizes an 8 m2 solar water heating system, weather stations for external temperature and humidity monitoring, as well as internal light, humidity, and temperature sensors to create an optimized environment for crop cultivation. Experiments were conducted with various crops within the SGH during the harsh winter months, typically rendering the cultivable land fallow due to extreme cold conditions. The SGH is equipped with sensors and communication technologies, ensuring continuous data collection and the automated regulation of heating, ventilation, and air conditioning systems. Located in Genekha, Thimphu, this pilot SGH seamlessly integrates renewable energy technology to provide heat during the cold winter season, obviating the need for external heating sources in the summer. The study employed TRNSYS and OpenStudio simulation software to assess the SGH's performance, focusing on temperature and humidity control inside and outside the greenhouse. Additionally, soil pH and nutrient content were examined, and the time required for crop growth and harvesting was recorded. In conclusion, this paper acknowledges some of the current design's limitations and presents recommendations for future enhancements, with a focus on the specific context of improving crop production and food security in mountainous regions.

GIS-based Characterization of Land Use, Land Cover Patterns and Microclimate of Agricultural and Agroforestry Landscapes in a Rainforest Zone of Nigeria

There is increasing need for development of sustainable land use and landscape management practices to avert accelerating trends of land, water and ecosystem degradation and for climate mitigation. This study characterized land use and land cover patterns and microclimate of permanent (forest, agroforestry, fallow, cocoa, oil palm, citrus and ornamental plant field) and annual crop land use systems in a rainforest zone of Nigeria using space-based remote sensing technology. The goal is to evaluate land use and land cover patterns and microclimate along agricultural and agroforestry landscapes in a rainforest zone of Nigeria. Land use types were: permanent (forest, agroforestry, fallow, cocoa, oil palm, citrus and ornamental plant field) and annual cropland. Vegetation indices (Normalized Difference Vegetation Index: NDVI, Normalized Difference Water Index: NDWI and Soil Adjusted Vegetation Index: SAVI) were deployed for characterizing land use vegetation cover patterns in relation to vigour and health in addition to responses to weather variables (temperature and rainfall). The NDVI intensities of vegetation cover from the land use types showed differences in vigour and health of vegetation during the rainy and dry seasons of 2017 to 2019. The NDWI of vegetation cover intensity indicates differences in moisture conditions of vegetation cover, the vegetation of the land use systems had more water content (received more rainfall) in 2017 compared to 2018 and 2019 during the rainy season while during the dry season of 2019, NDWI intensity was highest compare to 2018 and 2017. NDVI and NDWI also showed that vegetation cover of permanent land uses had better vigour and health compared to annual (maize) field. SAVI was applied to correct NDVI of vegetation cover patterns of land use types with reference to canopy gaps (soil brightness within canopy especially in spots where vegetation cover is sparse). High SAVI intensities were obtained during rainy compared to the low values during dry season (sparse vegetation cover). Decreasing order of SAVI intensities were agroforestry, oil palm, ornamental plant field, citrus, cocoa, fallow land and maize crop field. Result from the correlations among vegetation indices (NDVI, NDWI and DSAVI) were strong association (R2 = 1) among the years and seasons. The strong R2 values imply that less than 10% of changes in NDWI (the explanatory variables) can be explained by changes in NDVI and SAVI (the dependent variable). Temperature and rainfall differed within months and years of study. Temperatures were highest for March, April and May while rainfall was highest for September of 2017 and 2018 and in October, 2019. Significantly lower rainfall amounts were received for January, February, November and December. The vegetation indices (NDVI, NDWI and SAVI) indicated vigour and water contents of the land use types within seasons and years as well as responses to weather variables (rainfall and temperature in particular). The biophysical findings from this study may advance capacities to cope with climate change challenges and ecosystem conservation. Information generated will find use as strategies for ecologically sound and sustainable land use systems and policy for mainstreaming climate mitigation in in the study area.

Hydrogeochemical evaluation of Groundwater Suitability for Drinking and Irrigation Purposes in Coastal Community of Gbaramatu Kingdom, Nigeria

The aim of this paper was to evaluate the hydrogeochemistry of groundwater suitability for drinking and irrigation purposes in Okerenkoko Gbaramatu Kingdom, South-South Region, Nigeria using standard methods. The results obtained in the study indicates that over 70% of the groundwater under investigation fell in the category of C3S1 and C4S1 in the USSL salinity diagram implying high to very high salinity. The concentration of Lead (Pb) in all the samples collected exceeded the recommended value of 0.01 mg/L set by the World Health Organization and the Standard Organization of Nigeria respectively. Groundwater from the study area can only serve as irrigation purpose for salt tolerant crops like the sweet potato, grain-sorghum, sugar beet, cotton and carrot. The production of these crops on the vast arable fallow land will contribute significantly to food security and economic advancement of the study area and the global community at large. Conversely, the groundwater cannot be consumed unless treatment is administered.

Seasonal dynamics of fallow and cropping lands in the broadacre cropping region of Australia

Fallowing is an important strategy for enhancing soil health, water harvesting and crop yields, thus improving sustainability and reducing production risks in dryland farming systems in Australia. However, accurate data regarding the location, frequency, extent, and duration of fallow land is not readily available at high spatio-temporal resolutions before and during a cropping season. As a result, continental maps depicting seasonal dynamics of fallow and cropping lands and their responses to climate change and human activities remain missing. This study set out to develop an automated approach to discriminate fallow areas from cropping areas within Australian broadacre cropping region. This was done by applying a mathematical algorithm of turning point detection technique to a curve fitted vegetation index time series from 2016 to 2022, derived from high spatial (10 m) and temporal (5-days) resolution Sentinel-2 data. Specifically, we aimed to derive: (i) 5-day revisit fallow/cropping map layers; (ii) key attributes of the fallow and cropping periods (e.g., start, end, duration); (iii) cropping intensity and area. The proposed approach yielded a high and significant overall accuracy, surpassing 92% with substantial balanced accuracy (>0.9) against >3000 fields for individual winter and summer seasons across Australia. In addition, this study's temporal and geographical outputs, encompassing seasonal attributes, cropping intensity and cropping areas, robustly enhanced the understanding of seasonal cropping dynamics and historical shifts in dryland farming practices. Findings derived from this analysis aligned well with extreme climatic events and changes in crop activities adopted in response to such events. Future research will aim to extract key seasonal dynamics attributes influenced by cropping practices, enhancing the conversion of high-resolution earth observation data into actionable industry knowledge.

Soil Microbiome of Abandoned Plaggic Podzol of Different-Aged Fallow Lands and Native Podzol in South Taiga (Leningrad Region)

The soil microbiome is composed of various communities that play an important role in the existence of ecosystem services and the sustainable functioning of ecosystems under high anthropogenic loads. The transition of soils to a fallow state and their subsequent transformation lead to a notable alteration in the taxonomic composition of the soil microbiome, impacting the biochemical processes within the soil and its fertility levels. The object of this study comprised different-aged fallow soils of the southern taiga in the vicinity of Ban’kovo village, Leningrad region. The method comprising the high-throughput sequencing of 16S rRNA gene fragments using an Illumina MiSEQ sequencer was used to analyze the microbial community. The general processing of sequences was carried out with the dada2 (v1.14.1) package. It was found that the morphological organization of fallow soils has significant differences from the native podzol. In fallow soils, there are signs of leaching expressed in the accumulation of leached mineral particles, which indicates the degradation of the fallow–arable horizon. At the same time, there is a decrease in the content of P2O5 and K2O and an increase in the content of N-NH4 and N-NO3 in fallow soil. The analysis of alpha diversity index values showed that the highest level of alpha diversity in the microbial community is characteristic of 40-year-old soil, the alpha diversity index decreased with the increasing time of the fallow state, and the lowest alpha diversity index was observed in the native podzol. According to the values of the beta diversity index, a high correlation between the soil microbiome and the physicochemical characteristics of the soil was revealed, which indicates the formation of functional specialization in the studied microbial communities. As a result of the study of the taxonomic composition of microbial communities in fallow soils, it was found that the most represented microbial communities in fallow soils belong to Nitrosomonadaceae (Pseudomonadota), Mycobacterium (Actinobacteria), Nitrospira (Nitrospirota), and Luteolibacter (Verrucomicrobiota). The duration of post-agrogenic transformation is the leading factor influencing the changes in microbial communities; so, with an increase in the time that soils were in a fallow state, an increase in the oligotrophic microbial community was observed.

N-Dimensional Lattice Integrable Systems and Their bi-Hamiltonian Structure on the Time Scale Using the R-Matrix Approach

A time scale is a special measure chain that can unify continuous and discrete spaces, enabling the construction of integrable equations. In this paper, with the Lax operator generated by the displacement operator, N-dimensional lattice integrable systems on the time scale are given by the R-matrix approach. The recursion operators of the lattice systems are derived on the time scale. Finally, two integrable hierarchies of the discrete chain with a bi-Hamiltonian structure are obtained. In particular, we give the structure of two-field and four-field systems.

Impact of artisanal refining activities on bacterial diversity in a Niger Delta fallow land

Hydrocarbon pollution is a major ecological problem facing oil-producing countries, especially in the Niger Delta region of Nigeria. In this study, a site that had been previously polluted by artisanal refining activity was investigated using 16S rRNA Illumina high-throughput sequencing technology and bioinformatics tools. These were used to investigate the bacterial diversity in soil with varying degrees of contamination, determined with a gas chromatography-flame ionization detector (GC-FID). Soil samples were collected from a heavily polluted (HP), mildly polluted (MP), and unpolluted (control sample, CS) portion of the study site. DNA was extracted using the Zymo Research (ZR) Fungi/Bacteria DNA MiniPrep kit, followed by PCR amplification and agarose gel electrophoresis. The microbiome was characterized based on the V3 and V4 hypervariable regions of the 16S rRNA gene. QIIME (Quantitative Insights Into Microbial Ecology) 2 software was used to analyse the sequence data. The final data set covered 20,640 demultiplexed high-quality reads and a total of 160 filtered bacterial OTUs. Proteobacteria dominated samples HP and CS, while Actinobacteria dominated sample MP. Denitratisoma, Pseudorhodoplanes, and Spirilospora were the leading genera in samples HP, CS, and MP respectively. Diversity analysis indicated that CS [with 25.98 ppm of total petroleum hydrocarbon (TPH)] is more diverse than HP (with 490,630 ppm of TPH) and MP (with 5398 ppm of TPH). A functional prediction study revealed that six functional modules dominated the dataset, with metabolism covering up to 70%, and 11 metabolic pathways. This study demonstrates that a higher hydrocarbon concentration in soil adversely impacts microbial diversity, creating a narrow bacterial diversity dominated by hydrocarbon-degrading species, in addition to the obvious land and ecosystem degradation caused by artisanal refining activities. Overall, the artisanal refining business is significantly driving ecosystem services losses in the Niger Delta, which calls for urgent intervention, with focus on bioremediation.

Residual Effect of Foliar Application of Nano Fertlizers and Organic Source of Nitrogen on the Productivity and Economics of Zero Tilled Green Pea in Rice-green Pea Cropping Sequence

Background: After rice harvest, the majority of farmers in Manipur leave their land fallow without planting anything, despite the fact that it has a great deal of potential for growing a second crop in the rabi season with the remaining moisture and nutrients. One of the most crucial options for Manipur’s farmers is green pea, which not only boosts their revenue but also makes use of the nutrients and residual moisture in the soil. The current fertilizer application system ignores the carryover effect of the manure or fertilizer applied to the previous crop and instead bases its decisions on the nutritional requirements of the specific crop. Applying organic sources of nutrients to the previous crop greatly benefits the following crop. In light of the aforementioned considerations, an experiment was set up to determine whether the foliar application of nano fertlizers and organic source of nitrogen in the previous kharif rice crop had any lasting effects on the productivity of the following green pea crop. Methods: A field experiment was conducted during the kharif and rabi season of 2020-21 and 2021-22 at Hiyanglam Mayai Leikai in the Kakching district of Manipur, in order to research the residual effect of foliar application of nano fertlizers and organic source of nitrogen on the productivity and economics of zero tilled green pea in rice- green pea cropping sequence. A factorial randomized block design (FRBD) with three replications was used to set up the experiment. Result: The pooled data showed that vermicompost @100% RDN had the highest growth and yield characterictics over the vermicompost @ 75% RDN and 50% RDN. The combinations of nano NPK @ 1.5% + 100% RDN through vermicompost resulted in the highest increase growth and yield attributing characters of green pea and lowest was observed in the control + @ 50% RDN treated plot.

Geostatistical modeling approach for studying total soil nitrogen and phosphorus under various land uses of North-Western Himalayas

The distribution of total soil nitrogen (TSN) and total soil phosphorus (TSP) plays a pivotal role in shaping soil quality, fertility, agricultural practices, and environmental balance, especially in ecologically sensitive regions like the North-Western Himalayas (NWH). The primary objectives of this study were to contribute to clarify the impact and the rationale of various land uses on the spatial variation of TSN and TSP in the corresponding soils. This study aimed to explore the relation of TSN and TSP distribution in NWH soils with various factors like landscape physiography and soil physical and chemical properties using random sampling and geostatistical analyses. Employing random sampling, 300 soil surface samples (at a depth of 0–20 cm) were collected across various 500 m × 500 m grids from agriculture, horticulture, forest and fallow lands in the NWH region. The spatial land heterogeneity of TSN and TSP were systematically analyzed using standard statistical and geostatistical approaches (Gaussian, spherical, exponential, and linear). Results revealed a decreasing order of TSN and TSP levels i.e., horticulture (0.410 and 0.723 mg/kg) > agriculture (0.314 and 0.597 mg/kg) > forest (0.236 and 0.572 mg/kg) > fallow (0.275 and 0.342 mg/kg). Stepwise multiple regression results demonstrated a correlation between TSN and soil organic carbon (SOC), while TSP was correlated with soil organic carbon (SOC) and fine-grained soil particles. Nugget % values indicated the following spatial variability for TSN: agricultural (1.4) > horticultural (3.2) > forest (3.9) > fallow land (4.8) > mixed land (5.8), whereas the spatial variability of TSP showed a similar trend for all land uses. The optimized conceptual framework and isotropy models varied for TSN and TSP on dependence on land use type. The results of this study revealed the spatial patterns and land use-related variations and improved the prediction of nutrient distribution, so contributing an optimized conceptual framework for future studies. Finally, this study provided crucial insights to enhance soil quality, fertility, agricultural sustainability, and environmental equilibrium in the ecologically fragile NWH region, contributing to solve a significant research gap in the global understanding of soil dynamics.