Annual Loss Research Articles (Page 1)

Extensive soil degradation in the Tigray Highlands, Ethiopia, threatens agricultural sustainability. This study quantifies the critical imbalance between soil loss and formation in the severely affected Kola Embahasti Watershed. An integrated modeling approach was employed to assess the watershed's soil budget. Soil erosion was estimated using the Revised Universal Soil Loss Equation (RUSLE), with the land use/land cover (LULC) C-factor classified using a Support Vector Machine (SVM) model trained on field and satellite data (Sentinel-2B). Soil formation rates were calculated using the Arrhenius equation to model weathering processes. Statistical analysis was used to determine the relationship between erosion and formation rates. The results reveal a severe soil degradation, with a mean annual soil loss of 61.29 t ha⁻1yr⁻1, far exceeding the mean soil formation rate of 2.45 t ha⁻1yr⁻1. This yields a net annual soil loss of 58.84 t ha⁻1yr⁻1, indicating an unsustainable rate of degradation. A strong negative relationship was found between soil loss and formation, heavily influenced by land cover. Bare land exhibited the highest erosion (94 t ha⁻1yr⁻1) and lowest formation (0.98 t ha⁻1yr⁻1), while dense forest demonstrated the lowest erosion (5.14 t ha⁻1yr⁻1) and highest formation (4.9 t ha⁻1yr⁻1). The RUSLE model, physiochemical soil formation model, and SVM algorithm are integrated for innovative conservation action, recommending targeted interventions e.g., afforestation and sustainable land management.

Arctic amplification caused by global warming is accelerating an unprecedented loss of Arctic sea ice due to thinning of multi-year sea ice and increased export through Fram Strait, which is the largest Arctic gateway for ice export. The transition to a thinner and younger Arctic ice cover has resulted in a steady surface albedo decline of 1.25–1.51% per decade, weakening the radiative cooling effect of sea ice by 0.04–0.05 W m – ² per decade. The Fram Strait ice export (FSIE) is a major sink in the Arctic ice mass balance, accounting for approximately 14% of the annual sea ice volume loss. As the ice becomes thinner, it drifts faster, leading to enhanced ice export. The annual and summer FSIE have increased by about 6% and 11% per decade, respectively, further accelerating Arctic sea ice decline. Surface Albedo Modification (SAM) has been considered among variety of climate intervention solutions to slow down the transition of the Arctic into a seasonally ice-free ocean by mid-century, in concert with the greenhouse emissions mitigation efforts. Using climate model simulations, we evaluate the impacts of SAM application on the Arctic radiation budget and ice cover in two deployment scenarios: Arctic-wide and regional in Fram Strait. We model such an increase in sea ice albedo as a perturbation to the present-day climate state. Our results show that enhancing the surface albedo by up to 20% Arctic-wide during summer reduces the absorbed radiation at the surface by 11.16 W/m² and increases outgoing radiation at the top of the atmosphere by 10.70 W/m². This results in surface cooling of –1.33°C and recovers approximately 10% of the present-day Arctic sea ice radiative cooling power. These findings suggest that large-scale surface albedo modification could offset Arctic warming and contribute measurably to global cooling. The regional targeted deployment in Fram Strait yields more spatially limited but dynamically significant responses. SAM in Fram Strait enhances surface albedo both locally and in adjacent regions (Barents, Kara Sea) through advection of thicker, more reflective ice. The resulting radiative cooling alters atmospheric circulation, strengthening the low-pressure system over the Barents–Kara sector and triggering a negative Arctic Dipole pattern. This reduces sea-ice export by 2.4% through Fram Strait via weakening the Transpolar Drift in addition to the local thickening and slowing of the ice in the FS region, supporting ice retention within the Arctic basin. Furthermore, the modified atmospheric circulation induces dynamically driven nonlocal ice growth in areas of Central Arctic which persist year-round. These results highlight the potential of Fram Strait albedo enhancement to support multi-year ice recovery and reduce its loss via the Fram Strait. While basin-wide SAM offers the greatest potential benefits, it remains logistically challenging and carries higher risks of unintended consequences. Targeted regional interventions—such as in the Fram Strait and marginal seas (Barents, Kara, and Beaufort)—present a more feasible and cost-effective alternative, with lower risks and the potential to induce basin-wide responses through coupled atmosphere–ice–ocean interactions. These regions are dynamically linked to major circulation centers, including the Barents–Kara Low and Beaufort High, making them promising leverage points for intervention. A strategy for Arctic climate intervention, where a coordinated, regionally targeted, and seasonally adaptive deployment—combining summer albedo enhancement with winter ice thickening—may offer the greatest potential to stabilize Arctic sea ice while minimizing risks.

Corn (Zea mays L.) was planted on 375.1 million acres (151.8 million hectares) cumulative from 2020 to 2023 in the United States (U.S.) and Ontario, Canada. During these four years, 59.6 billion bushels (1.5 billion metric tons) of grain were produced, valued at $325.9 billion U.S. dollars (USD). Plant pathogens that cause diseases limit annual grain production and reduce associated economic returns, while also increasing management costs to prevent potential losses. Plant pathologists representing 29 U.S. states and Ontario, Canada were asked to estimate annual percent yield losses caused by 37 pathogens or pathogen groups through an online survey. Grain contaminated by mycotoxins was also estimated. According to survey results, estimated overall annual percent losses ranged from negligible in Texas in 2023 to 15.8% in Michigan in 2021, and averaged 3.0% across all surveyed regions for the four-year period. Diseases reduced corn yield by an estimated 2.5 billion bushels (63.7 million metric tons) across participating locations, with tar spot (caused by Phyllachora maydis), Fusarium stalk rot (caused by Fusarium spp.), and plant-parasitic nematodes causing the most significant losses. Total estimated economic loss caused by diseases was $13.8 billion USD; and the average economic loss was $37.76 USD per acre ($93.30 USD per hectare) across all years and locations. Survey data and the resulting analysis can help inform corn disease management, and guide pathology education, policy, and research priorities among scientists, government representatives, Extension educators, and other stakeholders.

ABSTRACT The impact of climate change on economic activities is an issue of widespread global concern. Using firm‐level data from China during 2000–2014, this paper examines how local extreme heat shocks affect firms' participation in global value chains, measured by the domestic value‐added ratio in exports (DVAR). Our results reveal that one additional day with a temperature exceeding 33°C in a given year leads to a decrease of 0.138% in the DVAR of Chinese firms. A back‐of‐the‐envelope calculation for the entire country suggests that each extra day of extremely high temperature was associated with an annual loss of USD 16.19 million in value‐added through export. The underlying mechanisms operate through two main channels: a direct productivity channel, in which extreme heat lowers labor productivity, and an indirect substitution channel, whereby firms increase their reliance on imported intermediate inputs from regions with lower climate risks. These mechanisms suggest that local heat shocks can propagate across supply chains, reshaping international production patterns. By emphasizing how climate risks transmit through production networks, this study provides new evidence that environmental shocks can become important determinants of comparative advantage in global trade.

Mental health disorders affect over 15% of the global working-age population, contributing to an annual economic loss of approximately USD 1 trillion due to diminished productivity and increased healthcare expenditures. In India, the post-pandemic surge in hospitalizations has placed additional strain on mental health infrastructure, exacerbating an already significant treatment gap. Overcrowding and inadequate forecasting mechanisms have resulted in occupancy rates that exceed hospital capacity, underscoring the urgent need for predictive tools to support admission planning and resource allocation. This study introduces a novel forecasting framework that applies Bayesian Model Averaging (BMA) with Zellner’s g-prior used here for the first time alongside deep learning models for predicting weekly bed occupancy at India’s second-largest mental health hospital. Time series data from 2008 to 2024 were used to train six models: Time Delay Neural Networks (TDNN), Recurrent Neural Networks (RNN), Gated Recurrent Units (GRU), Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and Bidirectional GRU (BiGRU). Model performance was optimized using random search (RS) and grid search (GS) hyperparameter tuning, allowing the framework to account for model uncertainty while improving predictive accuracy and consistency. Among all models, BiLSTM with GS tuning and BMA-GS model showed the best forecasting performance for bed-occupancy, achieving 98.06% accuracy (MAPE: 1.939%) and effectively capturing weekly fluctuations within ±13 beds. In contrast, RS-tuned models yielded higher errors (MAPE: 2.331%). Moreover, the average credible interval width decreased from 16.34 under BMA-RS to 13.28 with BMA-GS, indicating improved forecast precision and reliability. This study demonstrates that embedding Bayesian statistics specifically BMA with Zellner’s g-prior into deep learning architectures offers a robust and scalable solution for forecasting hospital bed occupancy. The proposed framework enhances predictive accuracy and reliability, supporting data-driven planning for hospital administrators and policymakers. It aligns with the objectives of India’s National Mental Health Programme (NMHP) and Sustainable Development Goal 3, advancing equitable and efficient access to mental healthcare.

Research objective . To conduct a comparative analysis of logistics risks in Kazakhstan and the USA, identifying key vulnerabilities, assessing their impact on supply chains, and developing specialized risk management strategies. Methodology . A mixed-method approach was used: quantitative analysis (World Bank LPI, trade statistics) and qualitative expert interviews. Applied SWOT analysis, risk mapping, and comparative assessment. Theoretical framework includes Sheffi (2022), ADB/WTO reports, state programs ("Nurly Zhol"). Originality/value . A comparative risk matrix for differently developed economies was created. Practical significance is evidenced by calculations: $2.1B rail gauge standardization reduces delays by 30%; NIST compliance cuts cyber incidents by 70%. Results . Structural disparities were identified: - Kazakhstan: infrastructure gaps (22% roads meet standards), geopolitical risks (68% EU transit via Russia); - USA: cyber threats ($4.3M damage/incident), climate risks ($18B annual losses). Priority solutions: for KZ – developing "Middle Corridor", for USA – port cybersecurity. This study contributes to the existing body of knowledge by providing a comparative analysis of logistical risk factors in different economic contexts (notably Kazakhstan and the USA) and proposing a novel integrated theoretical and methodological framework for risk assessment and management tailored for industrial enterprises.

Mastitis represents one of the most economically devastating diseases in dairy production, causing billions of dollars in annual losses through reduced milk quality and quantity. Recent advances in microbiome research have unveiled a critical gut–mammary axis that fundamentally influences mastitis susceptibility and pathogenesis in dairy cattle. Through comprehensive analysis of microbial communities across multiple anatomical sites, we demonstrate that mastitis development involves systematic disruption of both mammary and gastrointestinal microbiomes, characterized by reduced beneficial bacterial populations and increased pathogenic species. Healthy animals maintain balanced microbial ecosystems dominated by protective taxa including Firmicutes, Bacteroidetes, and beneficial Lactobacillus species, while mastitis-affected animals exhibit dysbiotic shifts toward Proteobacteria dominance, elevated Streptococcus and Staphylococcus populations, and compromised microbial diversity. Mechanistic investigations reveal that gut microbiota disruption compromises systemic immune competence, alters metabolite production including short-chain fatty acids and bile acids, and influences inflammatory mediators that circulate to mammary tissue. Therapeutic interventions targeting this axis, including probiotics, prebiotics, and plant-derived compounds, demonstrate significant efficacy in restoring microbiome homeostasis and reducing mastitis severity. These findings establish the gut–mammary axis as a fundamental regulatory mechanism in mastitis pathogenesis, opening new avenues for microbiome-based prevention and treatment strategies that could significantly enhance dairy health management while addressing antimicrobial resistance concerns.

Impact of tempering conditions on special spoilage, off-odor and the formation of volatile compounds in bulgur.

Exploring the potential of Flavobacterium covae catalase and DNA starvation/stationary phase protein as recombinant protein vaccines against columnaris disease in channel catfish.

Avoided mortality by particulate air pollution control measures in China.

Economic impact of productivity losses attributable to porcine reproductive and respiratory syndrome virus in United States pork production, 2016-2020.

Small-scale fishery as a driver of habitat loss in marine protected areas.

Unraveling the antiviral potential of multiprotein bridging factor 2 in silkworm immunity.

The focus of this study is to assess the annual soil loss in the lower watershed of the Chambal basin within the Agra district. This estimation is carried out using the Revised Universal Soil Loss Equation (RUSLE) in conjunction with Geographic Information System (GIS) tools and remote sensing data. Agra’s river channels and their tributaries are particularly susceptible to land degradation and soil erosion due to intense fluvial activity and the presence of infertile soils. These conditions contribute to the formation of ravines and gullies along the riverbanks. To calculate the rainfall-runoff erosivity (R) factor, average annual precipitation data from the past decade were analyzed. Soil data obtained from the Remote Sensing Applications Centre, Lucknow, at a scale of 1:10,000 were used to estimate the K factor for different soil types. The LS factor was derived from a 30-meter ASTER Digital Elevation Model (DEM). Additionally, the cropping management (C) factor was determined using NDVI values derived from Landsat 8 data, processed with GIS techniques. The P factor which distinguishes between agricultural and non-agricultural land, was also considered. The annual soil erosion estimates revealed that the region is predominantly affected by soil loss ranging from 77 to 1,359 tonnes per hectare per year, mainly concentrated in ravine and gully-affected areas. However, in certain regions, soil loss was estimated to be as high as 19,999 tonnes per hectare per year, highlighting the urgent need for intervention and management by local authorities and administrative bodies.

Loss of soil from river basins by water is a concerning issue for India which is an agricultural country. The particular distribution of quantitated soil erosion must be obtained to propose effective soil conservation practices. Revised Universal Soil Loss Equation (RUSLE) is a tool to estimate soil erosion distribution spatially. The properties of Vembanad lake that supports large biodiversity and ecosystem is altered by the sediments of Muvattupuzha River. The river, originating from the Western Ghats drains into Vembanad lake, has undergone many changes. In this work, an attempt has been made to determine the soil erosion in the Muvattupuha River basin through the years. Annual sediment loss from the basin is obtained for three consecutive decades. Maps of soil yield, sediment delivery ratio and sediment transportation index of the basin for 2021 are also developed.

Türkiye is one of the most vulnerable countries in the Mediterranean Basin; the assessment of changes in soil erosion driven by both climate variability and anthropogenic factors is of great importance. This study aims to examine the current state and potential future changes in soil erosion in Sakarya Province, situated in the eastern part of the Mediterranean Basin, by employing the GIS-based RUSLE (Revised Universal Soil Loss Equation) model. Considering the impact of climate change on precipitation regimes, rainfall projections for the 2061–2080 period under the high-emission SSP5-8.5 scenario were evaluated. The analysis revealed that the current average annual soil loss in Sakarya is 2.9 t/ha, with the highest erosion risk occurring on steep slopes, bare surfaces, and agricultural lands. By 2080, under the SSP5-8.5 scenario, the annual average soil loss is projected to be 2.6 t/ha, while slight and very slight erosion levels are expected to increase. These results provide important insights for identifying current risk areas and critical zones for conservation, as well as for projecting future erosion scenarios, thus contributing to sustainable land management policies at the watershed scale. The study suggests that strategies to reduce erosion risk in Sakarya should particularly focus on land management practices such as slope stabilization, afforestation, land cover improvement, and terracing. These approaches are crucial for mitigating land degradation (SDG 15.3) and ensuring sustainable agricultural production (SDG 2.4) within the framework of the Sustainable Development Goals.

Prickly pear (Opuntia spp.) is more than a conventional crop in Morocco; it serves as a keystone species sustaining rural livelihoods and enhancing ecosystem resilience. Owing to its remarkable tolerance to drought, poor soils, and heat stress, Opuntia has become integral to sustainable agriculture, land restoration, and national programs such as the Green Morocco Plan aimed at combating desertification. However, this success has been critically threatened by the rapid spread of the cochineal (Dactylopius opuntiae), a devastating pest that has decimated cactus plantations nationwide. To quantify the magnitude and spatial extent of this invasion, we performed a high-resolution geospatial analysis in Rhamna Province—one of Morocco’s main cactus-producing regions—between 2014 and 2020. A grid-based visual interpretation method was applied to sub-meter Google Earth imagery, supported by 3,305 ground control points and GIS post-processing. Cactus cover declined sharply from 23,326 ha in 2014 to only 267 ha in 2020 (−98.9%), with remaining stands highly fragmented across roughly ten communes. The corresponding annual revenue loss, estimated from fruit and biomass conversion factors and farm-gate prices, reached approximately 230.6 million MAD (≈ 23.8 million USD). Accuracy assessment based on confusion matrices yielded high overall agreement (overall accuracy and Cohen’s κ with 95% confidence intervals), confirming the reliability of the results. These spatially explicit, accuracy-controlled findings reveal the dramatic contraction of Opuntia cultivation and provide a quantitative baseline for recovery monitoring. The study highlights the urgent need for coordinated pest management and deployment of resistant genotypes, while demonstrating the value of expert-guided visual interpretation for monitoring bio-invasions in fragmented arid agroecosystems where conventional spectral classification often fails to capture fine-scale dynamics.

Phloem-restricted Candidatus Liberibacter species are the causative agents of economically significant crop diseases, including citrus Huanglongbing (HLB) and potato zebra chip disease (ZCD). ZCD, caused by Candidatus Liberibacter solanacearum (CLso), and transmitted by the potato psyllid, has spread to over 56% of United States potato production areas, resulting in millions of dollars in annual losses. Current control strategies rely on eliminating infected plants and reducing vector populations using insecticides, which have limited efficacy, pose risks to human and animal health, and raise environmental concerns and drug-resistant insect vectors. We have previously identified a novel stable antimicrobial peptide (SAMP) from Australian finger lime that can inhibit citrus HLB by suppressing C. Liberibacter asiaticus (CLas) growth and activating plant immune responses. In this study, we evaluated SAMP for controlling the CLso pathogen in solanaceous crops, as well as an unrelated vascular pathogen (Xanthomonas campestris pv. Campestris (Xcc)) in Arabidopsis thaliana. Topical application of SAMP on potato and tomato plants increased resistance to CLso in greenhouse trials. Potatoes and Arabidopsis internally expressing SAMP by the transgenic approach showed no growth defects and had significantly reduced bacterial titers after pathogen challenge. Remarkably, SAMP also suppressed CLso within the insect vector. These results highlight the broad-spectrum efficacy of SAMP, demonstrating its potential for bioengineering disease-resistant plants as a sustainable, cross-crop tool to combat vascular bacterial pathogens and enhance plant immunity beyond citrus species.

Air humidity and quality affect milk yield in Holsteinized Red Steppe cows, but this effect depends on the geographical location. The authorsanalyzed an eight-year period to identify the exact correlation between the air humidity and the physiological status of cows. The average daily yield per herd was determined in June, July, August, and September, and then the days with minimal and maximal yields were investigated for air humidity. The average air humidity remained almost the same over the entire study period, amounting to 66.5% for the maximal yield and 65.9% for the minimal yield. On the minimal-yield days in May, the yields exceeded those obtained on the maximal-yield days in other months while the difference between the yields was minimal (297.2 kg). Under pasture conditions, air humidity had no significant effect on milk yield. In May, June, and August, high air humidity correlated with minimal daily yields (4.6, 6.0, and 0.7%, respectively). In July and September, the air humidity on maximum-yield days was higher than on minimum-yield days by 0.4 and 3.2%, respectively. On average, the air humidity on maximum-yield days was higher by 0.6%. Across the entire study period of 1,200 days, the above-average daily yield was obtained on 291 days and amounted to 13,008.3 kg whereas the below-average yield was 12,346.8 kg for 271 days (22.6%), the overall difference being 661.5 kg. The annual milk loss during the grazing period amounted to 54.8 tons.

ABSTRACT The latex production in the natural rubber tree (Hevea brasiliensis) is adversely affected by phytopathogens, including Colletotrichum gloeosporioides, the causal agent of Anthracnose, and Pseudocercospora ulei, responsible for South American Rubber Leaf Disease (SALB). SALB, an endemic disease in the Amazon region, is the most significant constraint to H. brasiliensis cultivation, leading to annual losses of 15%–20% and the mortality of susceptible trees. The use of chemical inputs for SALB management is limited due to high costs and adverse environmental impacts. The aim of this study is to present biological control as an alternative strategy for the management of anthracnose and SALB. A screening of 50 bacterial isolates from marine environments was performed against C. gloeosporioides using dual confrontation and plate diffusion techniques. Metabolites produced by the selected bacterial isolates were evaluated for their capacity to inhibit the germination of P. ulei conidia. Isolates demonstrating high inhibitory activity were further assessed under controlled greenhouse conditions in seedlings of the RRIM 600 clone of natural rubber. Treatments with bacterial suspensions and filtrates showed that isolate 72, belonging to the genus Stenotrophomonas sp. and identified through 16S rRNA sequencing, effectively inhibited SALB symptoms compared to the control. This effect may be attributed to priming and a potential induction of systemic acquired resistance (SAR), as evidenced by differential RT-qPCR analysis of genes associated with the jasmonic acid (JA), salicylic acid (SA), and actin pathways.