Agricultural Intensification Research Articles

Integrated Pest Management: An Update on the Sustainability Approach to Crop Protection.

Integrated Pest Management (IPM) emerged as a pest control framework promoting sustainable intensification of agriculture, by adopting a combined strategy to reduce reliance on chemical pesticides while improving crop productivity and ecosystem health. This critical review synthesizes the most recent advances in IPM research and practice, mostly focusing on studies published within the past five years. The Review discusses the key components of IPM, including cultural practices, biological control, genetic pest control, and targeted pesticide application, with a particular emphasis on the significant advancements made in biological control and targeted pesticide delivery systems. Recent findings highlight the growing importance of genetic control and conservation biological control, which involves the management of agricultural landscapes to promote natural enemy populations. Furthermore, the recent discovery of novel biopesticides, including microbial agents and plant-derived compounds, has expanded the arsenal of tools available for eco-friendly pest management. Substantial progress has recently also been made in the development of targeted pesticide delivery systems, such as nanoemulsions and controlled-release formulations, which can minimize the environmental impact of pesticides while maintaining their efficacy. The Review also analyzes the environmental, economic, and social dimensions of IPM adoption, showcasing its potential to promote biodiversity conservation and ensure food safety. Case studies from various agroecological contexts demonstrate the successful implementation of IPM programs, highlighting the importance of participatory approaches and effective knowledge exchange among stakeholders. The Review also identifies the main challenges and opportunities for the widespread adoption of IPM, including the need for transdisciplinary research, capacity building, and policy support. In conclusion, this critical review discusses the essential role of IPM components in achieving the sustainable intensification of agriculture, as it seeks to optimize crop production while minimizing adverse environmental impacts and enhancing the resilience of agricultural systems to global challenges such as climate change and biodiversity loss.

Supporting the development of climate-resilient water safety plans through a risk-screening framework for drinking water source protection

ABSTRACT Climate change-induced impacts on water-quality challenge risk management of drinking water. Uncertainty around future changes and limited resources require approaches that enable prioritisation at regional or national scale for planning and adaptive intervention. This paper presents a framework for risk screening drinking water supplies, providing a staged approach to building the capacity for integrating climate change into risk management. The framework is applied to drinking water sources of the Scottish national drinking water provider, developing raw water trajectories for indicative water-quality parameters (water colour and Escherichia coli). It establishes baseline understanding of water-quality controls through multivariate statistical analysis. It incorporates climate and land-use change into the model using climate (UKCP18) and land-use projections. The results suggest potential higher organic carbon production in soils from increased production with higher temperature, combined with reduced dilution and drought effects from reductions in summer rainfall. For E. coli, risks arise through land-use change leading to potential agricultural intensification. The framework supports the targeted development of climate-resilient Water Safety Plans, prioritising systems most at risk of raw water-quality deteriorations. It emphasises source protection to maintain or improve regulatory compliance, minimise socioeconomic and environmental harms, and generate additional benefits.

Context-dependent agricultural intensification pathways to increase rice production in India

Yield gap analysis is used to characterize the untapped production potential of cropping systems. With emerging large-n agronomic datasets and data science methods, pathways for narrowing yield gaps can be identified that provide actionable insights into where and how cropping systems can be sustainably intensified. Here we characterize the contributing factors to rice yield gaps across seven Indian states, with a case study region used to assess the power of intervention targeting. Primary yield constraints in the case study region were nitrogen and irrigation, but scenario analysis suggests modest average yield gains with universal adoption of higher nitrogen rates. When nitrogen limited fields are targeted for practice change (47% of the sample), yield gains are predicted to double. When nitrogen and irrigation co-limitations are targeted (20% of the sample), yield gains more than tripled. Results suggest that analytics-led strategies for crop intensification can generate transformative advances in productivity, profitability, and environmental outcomes.

Soil organic carbon sequestration can be promoted through the improvement of landscape configuration heterogeneity in typical agricultural regions of northeast China

Landscape heterogeneity is considered a promising option for building resilient and sustainable agroecosystems. Understanding the relationships between farmland soil organic carbon (SOC) and landscape heterogeneity can support soil carbon sequestration and better serve food security and climate change. However, the influence extent and optimal scale of farmland landscape heterogeneity (i.e. landscape composition and landscape configuration heterogeneity) on SOC remains unclear. In this study, we established the relationships between multi-scale landscape heterogeneity and SOC in a typical grain-production county of northeast China. Stepwise regression results showed that when the buffer radius was 2000 m, the interpretation of SOC by landscape heterogeneity was the largest. The effects of landscape composition and landscape configuration on SOC were further decomposed by Variance Partitioning Analysis, and we found that independent interpretation ability of landscape configuration (8%) exceeded landscape composition (7%). The result of soil mapping combined with landscape indexes also showed that landscape configuration contributed more to the increased accuracy. Moreover, we found that correlation between configuration indexes and SOC at the class level was less related than that at the landscape level, among which the two most important indexes were Mean Fractal Dimension Index (FRAC_MN) and Number of Patches (NP). FRAC_MN was even more important than natural factors, indicating the validity of landscape as an indicator of human activities should not be ignored when considering farmland SOC. Overall, the results of this study revealed that the negative effects of agricultural intensification on SOC can be buffered to a certain extent by increasing the complexity of patch shape and reducing the degree of landscape fragmentation at the landscape level, providing hope for the sustainable development in intensive agricultural areas. In addition, due to the scale effect of landscape heterogeneity on farmland SOC, we suggest that decision makers should consider the spatial scale in landscape allocation and planning. This study provides a scientific reference for realizing the balance between grain production and ecological function in intensive agricultural areas.

The multiscale response of global cropland cropping intensity to urban expansion

CONTEXTUrban expansion(UE) and multiple cropping(MC) are key factors in anthropogenic impacts on global environmental change. However, the multi-scale response patterns of UE and MC have not yet been revealed, and how urbanization affects cropland intensification is still not deeply explored. OBJECTIVEThis study examines the spatial and temporal trends in global UE and MC and analyses the multi-scale response patterns of both. METHODSThe GEE (Google Earth Engine) platform was used to count global cropland cropping intensity (CCI) and impervious surface rasters on an image-by-image basis, while GIS was employed for spatial analyses, and the generalized additive model (GAM) was applied to inscribe variable response trajectories. RESULTS AND CONCLUSIONThe global multiple cropping index(MCI) increased significantly (by 4.1 %) over the period 2001–2019, with growth in double- and triple-cropped cropland dominating this change. Double cropping, as a widespread global farming strategy, has led to a shift towards the intensification of agriculture, with countries in the northern hemisphere contributing more. Global UE significantly expands to twice the baseline level at an average annual growth rate of 2. 42 × 104 km2 over the period 2001–2019, with the expansion of world-class urban agglomerations in China, the United States and Europe dominates this trend. The spatial clustering of MC and UE has continued to intensify, with high-intensity cropping strategies progressively clustering towards areas of significant UE, and this tendency has a clear decreasing urban-rural gradient effect. The global CCI grows significantly and non-linearly with UE, but an important inflection point in the growth trajectory has occurred under the influence of threshold effects. Developed countries tend to be more flexible in their cropping intensity strategies as they move forward with urbanization. There is a clear increasing effect of the urban-rural gradient in the degree of non-linearity in the response of urbanization and cropping intensity. SIGNIFICANCEThe results of the study contribute to the understanding of the complex spatial and temporal coupling mechanisms between UE and MC, and provide useful insights for the development of trade-offs between urbanization and maturity strategies.

Sediment source tracing in a Brazilian subtropical catchment using diffuse reflectance: Effect of spectral ranges, pre-processing techniques, and multivariate model

ABSTRACT Agriculture intensification in Southern Brazil’s subtropical regions combined with the frequent occurrence of erosive rainfall has rendered the area a global water erosion hotspot. In this scenario, understanding and regulating erosion processes at the river catchment scale is critical for mitigating soil and water resource degradation. Traditional methods for tracing sediment sources are expensive and time-consuming and justify the development of alternative approaches. Therefore, in this study, we employed diffuse reflectance spectroscopy analyses in the ultraviolet-visible (UV-VIS), near-infrared (NIR), and mid-infrared (MIR) ranges, combined with multivariate models and spectral pre-processing techniques to estimate sediment source contributions in a homogeneous subtropical catchment (Conceição River, 804 km²). Soil samples (n = 181) were collected to characterize the four potential sediment sources, including: cropland (n = 78), stream bank (n = 36), unpaved road (n = 40) and pasture (n = 27). Moreover, 44 sediment samples were collected, including suspended sediment (n = 8), fine sediment deposited on the riverbed (n = 15), and suspended sediment samples collected in the water column during storm events (n = 21). Vector machine (SVM) model outperformed the others, with better accuracy and reliability. While UV-VIS spectra proved less effective due to soil homogeneity across the catchment, NIR and MIR spectra provided valuable information for discriminating sediment sources. Furthermore, reducing the number of potential sources (from four to three or two) improved model predictions, especially when distinguishing between surface sources (cropland and pasture) and subsurface sources (unpaved roads and stream banks). The study’s findings shed light on the power of efficient and cost-effective alternative methods for assessing sediment sources, which are vital for promoting effective erosion control and sustainable land management in similar regions.

Push-Pull Intercropping Increases the Antiherbivore Benzoxazinoid Glycoside Content in Maize Leaf Tissue.

Push-pull technology refers to a promising mixed cropping practice for sustainable agricultural intensification, which uses properties of intercrop and border crop species to defend a focal crop against pests. Currently, the most widely practiced system uses Desmodium spp. as intercrop and Brachiaria or Napier grass as border crops to protect maize (Zea mays) against both insect pests and parasitic weeds. Several previous studies have demonstrated the efficacy of the push-pull system, but research on the underlying chemical mechanisms has mostly been limited to laboratory and glasshouse experiments that may not fully reproduce the complexity of the system under natural conditions. To address this limitation, we performed a large-scale study in farmer-operated push-pull maize fields in three east African countries. We compared maize leaf extracts from plants grown on push-pull fields with maize from fields employing conventional agricultural practices to assess the influence of push-pull cultivation on the maize metabolome. We identified two benzoxazinoid glycosides, which are known to have antiherbivore properties and were present in greater relative abundance in push-pull-cultivated maize leaves across three countries. Our data thus suggest that maize cultivated under push-pull has an increased resistance to herbivore attack compared to maize grown under conventional local agricultural practices.

Semantic Segmentation and Classification of Active and Abandoned Agricultural Fields through Deep Learning in the Southern Peruvian Andes

The monumental scale agricultural infrastructure systems built by Andean peoples during pre-Hispanic times have enabled intensive agriculture in the high-relief, arid/semi-arid landscape of the Southern Peruvian Andes. Large tracts of these labor-intensive systems have been abandoned, however, owing in large measure to a range of demographic, economic, and political crises precipitated by the Spanish invasion of the 16th century CE. This research seeks to better understand the dynamics of agricultural intensification and deintensification in the Andes by inventorying through the semantic segmentation of active and abandoned agricultural fields in satellite imagery across approximately 77,000 km2 of the Southern Peruvian Highlands. While manual digitization of agricultural fields in satellite imagery is time-consuming and labor-intensive, deep learning-based semantic segmentation makes it possible to map and classify en masse Andean agricultural infrastructure. Using high resolution satellite imagery, training and validation data were manually produced in distributed sample areas and were used to transfer-train a convolutional neural network for semantic segmentation. The resulting dataset was compared to manual surveys of the region and results suggest that deep learning can generate larger and more accurate datasets than those generated by hand.

Sustainable land management and implications on incomes, food self-sufficiency and women

The adoption of Sustainable Land Management (SLM) practices among smallholder farmers remains low, particularly among women farmers. Understanding the relationship between assets, gender, and SLM adoption and how their interaction impinges on household food self-sufficiency and livelihoods is essential for developing gender-responsive SLM programmes that effectively promote sustainable livelihoods and address household food insecurity. This study examines the effects of asset type on SLM practices adoption, women farmers, and their implications on household incomes and food self-sufficiency. Data was collected through a cross-sectional survey of 761 households selected from 11 chiefdoms across six districts in Eastern Zambia. Analysis involved Structural Equation System framework and Propensity Score Matching techniques to examine relationships between SLM adoption, food self-sufficiency, and household incomes, considering various socio-economic factors. Results showed marital status and household size as significant demographics, with education positively correlating with household income and SLM participation (p < 0.05). Gender disparities persisted, with male-headed households having higher incomes. Labour allocation analysis revealed women’s involvement in labour-intensive tasks, while smaller farms showed higher income probabilities, supporting sustainable agricultural intensification. Social capital significantly influenced SLM participation, and access to financial capital. Livestock assets, land size, and crop diversity predicted food security, while male decision-making influenced food security and income. Incomes were higher for women participating in SLM projects. This study underscores the importance of SLM practices in influencing household incomes and food security, especially for women. Addressing gender disparities and promoting women’s empowerment in agriculture are crucial for achieving equitable and sustainable rural development. Policymakers can foster sustainable livelihoods in rural communities by prioritizing SLM and empowering women.

Organized labour migration of residents of Lithuania to the USSR in the sixth–ninth decades of the 20th century

Referring to archive and historiographic materials, in this paper problematics of labour migration to the USSR from Lithuania in 1953-1984 is analysed. Attention is drawn to migration directions, motivation of residents, quantitative indices, territorial aspects related to persons participating in labour migration process and social picture. Residents of Lithuania became participants of the campaign for organized all Soviet Union-wide labour force migration to participate in implementation of large and important land, forestry and industry projects. By the way, the residents of our Republic joined this campaign later than residents from other Republics – in 1953 only. Organized labour force migration from Lithuania to the USSR was of lower level that it had been planned in Moscow. The main directions of labour force migration were: 1) agriculture intensification program (virgin lands campaigns in Kazakhstan and Russia); 2) Russian forestry development program; 3) program of construction of gigantic transport and industrial objects in Russia (Siberia, etc.); 4) the “Third Semester” program – season-based works of students in industry and agriculture sectors of Russia, Kyrgyzstan, Uzbekistan and other Soviet Republics. In 6th-9th decades of the 20th century, about 75 thousand residents of Lithuanian Soviet Socialist Republic were sent to work in other regions of the Soviet Union; labour migrants worked on industrial objects, farms and forestry units. Mostly, they were men from urban areas, by ethnic composition – Russians and Lithuanians. The most intensive time period of sending to work as labour migrants was the 1953-1965 period, as at that time in Kazakhstan and Russia huge programs of economic development had been implemented (virgin lands campaign, forestry development). Namely during this period, over 80 per cent of residents of Lithuania who participated in this campaign were sent to labour destinations. Although in later years the migration campaign covered entire Lithuania, its scale diminished markedly. Due to certain national traits of Lithuanians (sedentary life, attachment to the land) and social-economic situation in the Lithuanian Soviet Socialist Republic (fast and intensive industry development ensuring quite good wages, well-developed social infrastructure, etc.), the residents of Lithuania liked to conclude short-term employment agreements, and after termination of these agreements made efforts to return to Lithuania and stay there not attracted by labour migration campaign anymore.

Prevalence and molecular characterization of ESBL/pAmpC producing faecal Escherichia coli strains with widespread detection of CTX-M-15 isolated from healthy poultry flocks in Eastern Algeria

The intensification of livestock farming has led to the widespread use of massive amounts of antibiotics worldwide. Poultry production, including white meat, eggs and the use of their manure as fertiliser, has been identified as one of the most crucial reservoirs for the emergence and spread of resistant bacteria, including E. coli in poultry as an important opportunistic pathogen representing the greatest biological hazard to human and wildlife health. Thus, this study aimed to analyse E. coli in the faecal carriage of healthy poultry flocks and to investigate the phenotypic and genotypic characteristics of antimicrobial resistance, including integrons genes and phylogenetic groups. A total of 431 cloacal swabs from apparently healthy poultry from four regions in Eastern Algeria from December 2021 to October 2022. 360 E. coli were isolated; from broilers (n = 151), broiler breeders (n = 91), laying hens (n = 72), and breeding hens (n = 46). Among this, 281 isolates exhibited multidrug resistance (MDR) phenotype, 17 of the 360 E. coli isolates exhibited ESBL, and one isolate exhibited both ESBL/pAmpC. A representative collection of 183 among 281 MDR E. coli was selected for further analysis by PCR to detect genes encoding resistance to different antibiotics, and sequencing was performed on all positive PCR products of blaCTX-M and blaCMY-2 genes. Phylogenetic groups were determined in 80 E. coli isolates (20 from each of the four kinds of poultry). The blaCTX-M gene was found in 16 (94.11 %) ESBL-producing E. coli isolates within 11 strains co-expressing the blaSHV gene and 8 strains co-expressing the blaTEM gene. Sequence analysis showed frequent diversity in CTX-M-group-1, with blaCTX-M-15 being the most predominant (n = 11), followed by blaCTX-M-1 (n = 5). The blaCMY-2 gene was detected only in one ESBL/pAmpC isolate. Among the 183 tested isolates, various antimicrobial resistance genes were found (number of strains) blaTEM (n = 121), blaSHV (n = 12), tetA (n = 100), tetB (n = 29), sul1(n = 67), sul2 (n = 32), qnrS (n = 45), qnrB (n = 10), qnrA (n = 1), catA1(n = 13), aac-(6′)-Ib (n = 3). Furthermore, class 1 and class 2 integrons were found in 113 and 2 E. coli, respectively. The isolates were classified into multiple phylogroups, including A (35 %), B1 (27.5 %), B2 and D each (18.75 %). The detection of integrons and different classes of resistance genes in the faecal carriage of healthy poultry production indicates that commensal E. coli could potentially act as a reservoir for antimicrobial resistance, posing a significant One Health challenge encompassing the interconnected domains of human, animal health and the environment. Here, we present the first investigation to describe the diversity of blaCTX-M producing E. coli isolates with widespread detection of CTX-M-15 and CTX-M-1 in healthy breeders (Broiler and breeding hens) in Eastern Algeria.

Impact of graded doses of enrofloxacin on the safety and biological responses of Nile tilapia Oreochromis niloticus

The cultivation of tilapias, the third most farmed fish group globally, has been rapidly growing, especially in Southeast Asia. This surge in tilapia farming intensification has led to increased use of antibiotics to control bacterial diseases. This study investigated the safety implications of administering graded doses of enrofloxacin (ENF) at 0 (control), 10, 30, 50 and 100 mg/kg biomass/day orally to Oreochromis niloticus. The 43-day study comprised 7 days of pre-dosing, 15 days of ENF-dosing, and a 21-day recovery period with a periodical assessment of the biological responses of fish. The results revealed that the overdosed groups experienced up to 21% reduction in feed consumption, 11% mortalities, and adverse impacts on hematology, including a decrease in erythrocytes, and monocytes and an increase in leukocytes, thrombocytes, lymphocytes, and neutrophils. Haematological indices like mean corpuscular volume and mean corpuscular hemoglobin decreased, while mean corpuscular hemoglobin concentration increased. The plasma biochemical parameters including glucose and liver and kidney enzymes unveiled a significant dose- and time-dependent increase, while calcium and chloride levels decreased. Erythrocytes displayed several erythrocyte cellular and nuclear abnormalities. The frequency of micronucleus increased with dose and time, suggesting potential genotoxicity of ENF. Additionally, a dose-dependent increase in residues in the tissues with the highest accumulation in muscle was documented. Nevertheless, the recovery of the measured parameters upon dose termination indicated that the ENF-induced alterations are reversible. The study affirmed the safety of ENF at the recommended dose (10 mg) in O. niloticus and their adoptive responses to higher doses.

Riparian buffer strips promote biomass, species richness and abundance of flying insects in agricultural landscapes

Agricultural intensification is debated as one of the major drivers for the decline of insect biodiversity. Agri-environmental schemes (AES) are a common measure to promote biodiversity in agriculture by granting compensational payments to farmers for environmentally friendly practices. In this study we examined the effect of buffer strips of at least 5 m width, adjacent to small watercourses and drainage ditches, on insect biomass and insect species richness in agricultural landscapes. We selected ten arable fields in each of four regions in lower and upper Bavaria, Southern Germany. 25 out of 40 sites had a buffer strip between arable crops and watercourse. Insects were sampled at three time periods (May/June, June/July and August/September) for two weeks each. In each period two samples were collected (one per week). On each site Malaise traps were set up in 5 and 80 m distance to the embankment of the watercourse. Half of the samples was then subjected to metabarcoding and the other half was classified into different insect groups by morphological identification and the number of the individuals for each group was counted. For hoverflies (Syrphidae), individuals were identified at species-level. Data on vegetation structure (cover of grasses and herbs) in the studied riparian buffer strips was collected and correlated with number of species, abundances and biomass of flying insects. The five taxonomic orders with the highest species richness and individual numbers were: Diptera, Hymenoptera, Coleoptera, Lepidoptera and Hemiptera. Diptera dominated hereby with 34% of all species and 81% of all individuals. On average, mixed models indicated 31% higher insect biomass, 15% higher species richness and 29% higher individual numbers of flying insects in buffer strips at 5 m distance to the watercourse compared to sites with no buffer strip. The effect was even stronger for butterflies (32% higher species species richness, 70% more individuals) and hoverflies (24% higher species richness, 51% more individuals). In the presence of a buffer strip significantly higher numbers were found for total individuals, Diptera, Hymenoptera and Coleoptera. In 80 m distance to the watercourse, the samples of flying insects were not significantly influenced by a riparian buffer strip. This study highlights the importance of buffer strips in agricultural regions and their multifunctional potential in fostering biodiversity additionally to their acknowledged use for water protection. Ideally, buffer strips are rich in herbs and inflorescences and are therefore beneficial for the insect fauna by serving as valuable habitat with high potential connectivity at landscape level.

Prevalence, antimicrobial resistance and genomic comparison of non-typhoidal salmonella isolated from pig farms with different levels of intensification in Yangon Region, Myanmar

In Myanmar, where backyard, semi-intensive, and intensive pig (Sus scrofa domesticus) farming coexist, there is limited understanding of the zoonotic risks and antimicrobial resistance (AMR) associated with these farming practices. This study was conducted to investigate the prevalence, AMR and genomic features of Salmonella in pig farms in the Yangon region and the impact of farm intensification to provide evidence to support risk-based future management approaches. Twenty-three farms with different production scales were sampled for two periods with three sampling-visit each. Antimicrobial susceptibility tests and whole-genome sequencing were performed on the isolates. The prevalence of Salmonella was 44.5% in samples collected from backyard farms, followed by intensive (39.5%) and semi-intensive farms (19.5%). The prevalence of multi-drug resistant isolates from intensive farms (45/84, 53.6%) was higher than those from backyard (32/171, 18.7%) and semi-intensive farms (25/161, 15.5%). Among 28 different serovars identified, S. Weltevreden (40; 14.5%), S. Kentucky (38; 13.8%), S. Stanley (35, 12.7%), S. Typhimurium (22; 8.0%) and S. Brancaster (20; 7.3%) were the most prevalent serovars and accounted for 56.3% of the genome sequenced strains. The diversity of Salmonella serovars was highest in semi-intensive and backyard farms (21 and 19 different serovars, respectively). The high prevalence of globally emerging S. Kentucky ST198 was detected on backyard farms. The invasive-infection linked typhoid-toxin gene (cdtB) was found in the backyard farm isolated S. Typhimurium, relatively enriched in virulence and AMR genes, presented an important target for future surveillance. While intensification, in terms of semi-intensive versus backyard production, maybe a mitigator for zoonotic risk through a lower prevalence of Salmonella, intensive production appears to enhance AMR-associated risks. Therefore, it remains crucial to closely monitor the AMR and virulence potential of this pathogen at all scales of production. The results underscored the complex relationship between intensification of animal production and the prevalence, diversity and AMR of Salmonella from pig farms in Myanmar.

Diversified crop rotations improve soil microbial communities and functions in a six-year field experiment

Diversified crop rotations can help mitigate the negative impacts of increased agricultural intensity on the sustainability of agroecosystems. However, the impact of crop rotation diversity on the complexity of soil microbial association networks and ecological functions is still not well understood. In this study, a 6-year field experiment was conducted to evaluate how six different crop rotations change the composition and network complexity of soil microbial communities, as well as their related ecological functions. Microbial traits were measured in six crop rotations with different crop diversity index (CDI) during 2016–2022, including winter wheat–summer maize (CDI 1, WM) as the control, sweet potato→winter wheat–summer maize (CDI 1.5, SpWM), peanut→winter wheat–summer maize (CDI 1.5, PWM), soybean→winter wheat–summer maize (CDI 1.5, SWM), spring maize→winter wheat–summer maize (CDI 1.5, SmWM), and ryegrass–sweet sorghum→winter wheat–summer maize (CDI 2, RSWM). The study findings indicated that diversified crop rotations significantly increased ASV richness of both bacterial and fungal communities after 6-year treatments, and the β-diversity profiles of bacterial and fungal communities significantly distinguished at the year of 2022 from 2016. The relative abundance of Acidobacteria and Chloroflexi was significantly enriched in SpWM rotation at 2022, while Basidiomycota significantly declined in five diversified rotations compared to WM. Diversified crop rotations at 2022 increased the complexity and density of bacterial and fungal networks than 2016. SpWM and PWM rotations had the highest functional groups involved in chemoheterotrophy and saprotroph, respectively. Structural equation modelling (SEM) also revealed that diversified crop rotations increased soil nutrients through improving the composition of bacterial communities and the augmented intricacy of the interconnections within both bacterial and fungal communities. This research underscores the importance of preserving the diversity and ecological functions of soil microorganisms in the nutrient-recycling processes for efficient agricultural practices.

Arbuscular mycorrhizal fungal diversity in agricultural fields is explained by the historical proximity to natural habitats

Soil microbes are essential to maintain terrestrial ecosystem functionality. However, their diversity is threatened by land-use change, such as agricultural expansion and intensification. One important microbial group mediating the exchange of nutrients between plants and soil is arbuscular mycorrhizal (AM) fungi. The response of microorganism diversity to present and past habitat amount has been poorly studied. Here, we evaluate the potential role of current and historical natural habitat availability in explaining the diversity of AM fungi in arable fields. We conducted a spatially intensive sampling of three agricultural fields in Estonia. Soil AM fungal diversity was determined by soil DNA metabarcoding. We related AM fungal species richness, along with beta diversity components (turnover and nestedness), to abiotic conditions and natural habitat area availability at different spatial scales and time periods. Our findings showed a positive relationship between AM fungal richness and the amount of natural habitat area. Specifically, current AM fungal species richness was best explained by the amount of natural habitat from 130 years earlier, indicating a legacy effect of past land use on current soil biodiversity. The amount of past natural areas was negatively related to the beta diversity turnover component, indicating a replacement of AM fungal species in disturbed sites. While biodiversity-friendly farming is useful in promoting diverse soil biota, historical legacies can be persistent. Maintaining natural habitats around agricultural fields can further promote soil AM fungal diversity for future generations.

Advanced prediction of rice yield gaps under climate uncertainty using machine learning techniques in Eastern India

The current study focuses on applying machine learning approaches to forecast future Kharif rice yield gaps in eastern India while accounting for climate change implications. To achieve the United Nations Sustainable Development Goals (SDGs), food security must be prioritized. Rice yield has been predicted using Cubist, GBM, MARS, RF, SVM, and XGB machine learning methods, considering six factors: elevation, soil moisture, precipitation, temperature, soil temperature, and actual evapotranspiration. Climatic change scenarios were generated using the latest climatic Coupled Model Intercomparison Project Phase 6 (CMIP6 MIROC6) Shared Socioeconomic Pathways (SSP) 2–4.5 and SSP5-8.5 datasets between 1990 and 2030. Finally, machine learning algorithms were used to identify rice yield gaps to achieve sustainable agricultural intensification. The rice yield validation was completed with 1889 field-based farmer observation records. The results suggest that Murshidabad and Purba Bardhaman districts had very high rice yields (5.60–3.45 t/ha) when using the Cubist model compared to another model. The findings also reveal a poor rice-yielding zone (1.44–0.39 t/ha) in the western region (Purulia) and a northwestern region (half of the west of Birbhum). The Cubist and RF models' maximum and minimum R2 values were 0.73 and 0.72, respectively. The R2 values were also negligible for the XGB, GBM, SVM, and MARS, machine learning models. Projections for rice production in 2030 indicate that the northern and north-eastern regions (Murshidabad and Purba Bardhaman) as well as the southeastern areas (Jhargram and Paschim Medinipur) have the highest yields, categorized as extremely very high (5.56–3.49 t/ha) and high (3.49–2.49 t/ha). A significant rice yield gap (50-40 %) was found in the center and south-east areas (Bankura, Jhargram, and Paschim Medinipur), the northern region (Murshidabad and Birbhum), and the western region (Purulia). In 2030, the north-western region (Birbhum), as well as the middle and south-eastern regions (Bankura, Jhargram, and Paschim Medinipur districts), had the highest proportion of high (50%–40 %) and very high (60%–50 %) rice yield gap. Our findings can contribute to a new viewpoint on agricultural planning and management for sustainable growth in the face of changing climate circumstances.

Seasonal Variations in Population Dynamics of Insect Pests in Tiruvallur District, Tamil Nadu, India

Understanding the complex relationship between seasonal changes and pest dynamics is essential for establishing effective protection methods in contemporary agriculture and guaranteeing long-term agricultural sustainability and food security. The study was conducted in the Tiruvallur District of Tamil Nadu, India, which is characterized by a tropical climate with distinct wet and dry seasons [1]. Shannon-Wiener Index and Simpson's Index biodiversity indices reflected the moderate to high pest diversity of species in the region. Values for Shannon-Wiener indexes ranged between about 1.93-1.95 for different species of insect pests, and Simpson's indexes were found to range between about 0.85-0.86. All these indices indicate a well-balanced insect pest community with high species richness and even distribution, which is necessary to maintain ecological resilience. The findings enrich our understanding of pest ecology in tropical agriculture and provide valuable insights applicable to other regions facing similar issues. The observed seasonal patterns emphasize the importance of ongoing monitoring and adaptive management to tackle the challenges posed by insect pests amid climate variability and agricultural intensification. Additionally, this research offers a thorough framework for comprehending and managing insect pest populations in the Tiruvallur District.

Systems Modeling of the Water-Energy-Food-Ecosystems Nexus: Insights from a Region Facing Structural Water Scarcity in Southern Spain

The complex relationship between water, energy, food, and ecological systems, known as the WEFE nexus, has emerged as a major topic in the debate about sustainable economic development and resource management. This subject is of special interest in Mediterranean coastal areas as rapid economic expansion driven by population growth, higher influx of tourists, and intensification of agriculture is leading to structural water scarcity conditions. However, addressing the diverse range of issues associated with the nexus is a difficult task due to the existence of intricate interconnections, interdependencies, and nonlinearities within and across its various components. Accordingly, this case study applies a combination of participatory systems modeling and network analysis tools to yield insights into the complexity of this nexus in Axarquia, a region with features that make it an example of water-stressed jurisdictions in the Mediterranean. Overall, our results provide a strong foundation to understand the dynamics that govern this nexus in regions where the availability of freshwater resources is a significant concern. Furthermore, they lay the groundwork for the development of models and scenarios to simulate the impact of various policies and interventions on the overall system.

Understanding the spatial patterns of atmospheric ammonia trends in South Asia

Ammonia (NH3) is the most abundant alkaline gas in the atmosphere, mainly emitted by agricultural activities. NH3 readily reacts with other atmospheric acidic pollutants, such as the oxidation products of sulfur dioxide (SO2) and nitrogen oxides (NOₓ), to create fine particulate matter, which has far-reaching effects on human health and ecosystems. Here, we investigated long-term atmospheric NH3 trends in South Asia (SA) using satellite observations from the Infrared Atmospheric Sounding Interferometer (IASI). We analyzed 15 years (2008–2022) of IASI-NH3 retrievals against climate, biophysical, and chemical variables using an ensemble of multivariate statistical methods to identify the major factors driving the observed patterns in the region. Trend analysis of IASI-NH3 data reveals a significant rise in atmospheric NH3 over 51 % of SA plains, but a downward trend over 31 % of the region. Spatial correlation analysis reveals that biophysical factors, representing cropland expansion and agriculture intensification, have the highest positive correlation over 56 % of SA plains experiencing positive NH3 trends. However, our results reveal that the chemical conversion of NH3 to ammonium compounds, driven by the positive trends in NOₓ and SO2 pollution, is driving the apparently declining trend of NH3 in the other regions. Our results provide important insights into the NH3 trends detected by satellite data and can better inform the policy design aimed at reducing NH3 emissions and improving air quality for developing regions of the world.