Search Results (273)

Staphylococcus aureus frequently causes intramammary infections in dairy cows (bovine mastitis), which impair animal welfare, milk yield, and food safety. This study determined the prevalence and genetic diversity of S. aureus in bulk tank milk (BTM) samples from community-based Alpine dairy pastures in Tyrol, a major milk-producing region in Austria. Throughout the 2023 Alpine season (May–September), 60.3% (94/156) of BTM samples tested positive for S. aureus at least once over the course of up to four samplings. A total of 140 isolates collected from the 94 S. aureus-positive community-based Alpine dairy pastures revealed 33 distinct spa types, with t2953 (n = 33), t529 (n = 12), t267 (n = 11), and t024 (n = 10) being the most common. Selected isolates representing the different spa types were characterised by DNA microarray-based genotyping, multi-locus sequence typing (MLST), and antimicrobial susceptibility testing. Isolates with spa types associated with bovine-adapted CC8 (CC8bov/GTB) were identified as the most common subtype, being detected in BTM samples from 35.3% (55/156) of the pastures. This emphasises the high prevalence of this subtype in dairy herds across European Alpine countries. Other common bovine-associated subtypes were also detected, including CC97, CC151, and CC479. While antimicrobial resistance was rare, enterotoxin-producing genes were detected in all CC8bov-associated spa types. Overall, these findings underscore the importance of rigorous hygiene practices in dairy farming, particularly in community-based Alpine dairy pastures, where the risk of transmission is particularly high. It also emphasises the need for continued surveillance and subtyping to improve animal health, ensure food safety, and promote sustainable milk production. Full article

To accurately assess the water quality, ecosystem status, distribution of large benthic organisms, and ecological restoration under human intervention, an analysis of benthic organisms on Caofeidian in September and November 2023 and January and May of the following year was conducted in this work. By performing CCA (canonical correspondence analysis) and cluster and correlation coefficient (Pearson) analyses, the temporal variation characteristics of benthic abundance, dominant species, community structure and biodiversity were analyzed. A total of 79 species of macro-benthic animals were found in four months, including 32 species of polychaetes, cnidarians, 1 species of Nemertean, 19 species of crustaceans, and 24 species of molluscs. The use of conventional grab-type mud collectors revealed that the Musculus senhousei dominated the survey (Y > 0.02). While only a small number of Ruditapes philippinarum were collected from bottom-dwelling species, a certain number of bottom-dwelling species (Ruditapes philippinarum and Scapharca subcrenata) were also collected during the trawl survey. Additionally, a significant population of Rapana venosa was found in the area. It is speculated that the dual effects of predation and competition are likely the primary reasons for the relatively low abundance of bottom-dwelling species. The density and biomass of macro-benthos were consistent over time, which was the highest in May, the second highest in January, and the lowest in September and November. The main environmental factors affecting the large benthic communities in the surveyed sea areas were pH, DO, NO₂⁻-N, T, SAL and PO₄³⁻-P. Combined with historical data, it was found that although the environmental condition in the Caofeidian sea area has improved, the Musculus senhousei has been dominant. In addition, the abundance of other species is much less than that of the Musculus senhousei, and the diversity of the benthic community is still reduced. Our work provides valuable data support for the management and improvement of bottom Marine pasture and promotes the transformation of Marine resources from resource plunder to a sustainable resource. Full article

As one component of a study to improve Medicago spp. germplasm in eastern Australia, fifteen phenotypic and agronomic attributes were recorded for 4715 plants grown from the seed of 90 accessions of the widely naturalized pasture legume Medicago polymorpha from 90 sites in eight regions of inland New South Wales. The species expressed wide polymorphism. However, many leaflet attributes were associated with specific climate and soil characteristics, which varied from east to west across the collection zone. Discriminant analysis showed that accessions from the four most northern (summer dominant rainfall) and western (arid–semiarid) regions (Group A) differed from accessions from the most southern, temperate (winter dominant rainfall) and eastern (higher rainfall) regions (Group B). Group A flowered earlier and had shorter pod spines. Group B had lower plant vigor. Regions from which Group A accessions were collected had higher soil pH, lower winter rainfall, and higher minimum winter temperature than Group B regions. The diversity in the population, particularly the difference in flowering times among accessions collected from drier, warmer regions and those from more mesic, cooler regions, and the wide variation in flowering time measured among plants grown from accessions within all collection regions, is likely to ensure the long-term persistence of M. polymorpha in a changing climate. Elite lines were subsequently identified and lodged in National and International Genebanks for future research. Full article

As power grids scale and aging assets edge toward obsolescence, grounding grid corrosion has become a critical vulnerability. Conventional diagnosis must fit high-dimensional electrical data to a physical model, typically yielding a nonlinear under-determined system fraught with computational burden and uncertainty. We propose the Enhanced Biomimetic Hippopotamus Optimization (EBOHO) algorithm, which distills the river-dwelling hippo’s ecological wisdom into three synergistic strategies: a beta-function herd seeding that replicates the genetic diversity of juvenile hippos diffusing through wetlands, an elite–mean cooperative foraging rule that echoes the way dominant bulls steer the herd toward nutrient-rich pastures, and a lens imaging opposition maneuver inspired by moonlit water reflections that spawn mirror candidates to avert premature convergence. Benchmarks on the CEC 2017 suite and four classical design problems show EBOHO’s superior global search, robustness, and convergence speed over numerous state-of-the-art meta-heuristics, including prior hippo variants. An industrial case study on grounding grid corrosion further confirms that EBOHO swiftly resolves the under-determined equations and pinpoints corrosion sites with high precision, underscoring its promise as a nature-inspired diagnostic engine for aging power system infrastructure. Full article

Livestock farming is a vital component of global food security, yet it remains a major contributor to greenhouse gas (GHG) emissions, particularly methane (CH₄), which has a global warming potential 28 times greater than carbon dioxide (CO₂). This review provides a comprehensive synthesis of current knowledge surrounding the sources, biological mechanisms, and mitigation strategies related to CH₄ emissions from ruminant livestock. We first explore the process of methanogenesis within the rumen, detailing the role of methanogenic archaea and the environmental factors influencing CH₄ production. A thorough assessment of both direct and indirect methods used to quantify CH₄ emissions is presented, including in vitro techniques (e.g., syringe method, batch culture, RUSITEC), in vivo techniques (e.g., respiration chambers, Greenfeed, laser CH₄ detectors), and statistical modeling approaches. The advantages and limitations of each method are critically analyzed in terms of accuracy, cost, feasibility, and applicability to different farming systems. We then examine a wide range of mitigation strategies, organized into four core pillars: (1) animal and feed management (e.g., genetic selection, pasture quality improvement), (2) diet formulation (e.g., feed additives such as oils, tannins, saponins, and seaweed), (3) rumen manipulation (e.g., probiotics, ionophores, defaunation, vaccination), and (4) manure management practices and policy-level interventions. These strategies are evaluated not only for their environmental impact but also for their economic and practical viability in diverse livestock systems. By integrating technological innovations with sustainable agricultural practices, this review highlights pathways to reduce CH₄ emissions while maintaining animal productivity. It aims to support decision-makers, researchers, and livestock producers in the global effort to transition toward climate-smart, low-emission livestock farming. Full article

Habitat loss and land-use intensification are major threats to biodiversity in the Brazilian Atlantic Forest, particularly for bat assemblages that provide key ecosystem services. In this study, we examined how landscape composition (forest and pasture cover) and local forest structure influence the richness and abundance of phyllostomid bats across 20 forest fragments in southern Bahia. Bat sampling was conducted using mist nets, and forest structure was quantified using tree measurements and vertical foliage stratification. We applied structural equation modeling to test the direct and indirect effects of landscape and local variables. Our results show that forest cover has both direct and indirect positive effects on bat diversity, mediated by improved forest structure. In contrast, increased pasture cover negatively affected forest structure and was weakly associated with bat diversity. The most abundant species were generalist frugivores, such as Carollia perspicillata and Rhinophylla pumilio. These findings highlight the importance of maintaining forest cover and structural complexity to support bat diversity in agroforestry-dominated landscapes. Conservation strategies that integrate habitat protection with sustainable land-use practices are crucial to maintaining biodiversity and the ecological functions provided by bats in this globally threatened biome. Full article

Monitoring parturient cattle during calving is crucial for reducing cow and calf mortality, enhancing reproductive and production performance, and minimizing labor costs. Traditional monitoring methods include direct animal inspection or the use of specialized sensors. These methods can be effective, but impractical in large-scale ranching operations due to time, cost, and logistical constraints. To address this challenge, a network of low-power and long-range IoT sensors combining the Global Navigation Satellite System (GNSS) and tri-axial accelerometers was deployed to monitor in real-time 15 parturient Brangus cows on a 700-hectare pasture at the Chihuahuan Desert Rangeland Research Center (CDRRC). A two-stage machine learning approach was tested. In the first stage, a fully connected autoencoder with time encoding was used for unsupervised detection of anomalous behavior. In the second stage, a Random Forest classifier was applied to distinguish calving events from other detected anomalies. A 5-fold cross-validation, using 12 cows for training and 3 cows for testing, was applied at each iteration. While 100% of the calving events were successfully detected by the autoencoder, the Random Forest model failed to classify the calving events of two cows and misidentified the onset of calving for a third cow by 46 h. The proposed framework demonstrates the value of combining unsupervised and supervised machine learning techniques for detecting calving events in rangeland cattle under extensive management conditions. The real-time application of the proposed AI-driven monitoring system has the potential to enhance animal welfare and productivity, improve operational efficiency, and reduce labor demands in large-scale ranching. Future advancements in multi-sensor platforms and model refinements could further boost detection accuracy, making this approach increasingly adaptable across diverse management systems, herd structures, and environmental conditions. Full article

Silage is an effective method for alleviating winter feed shortages, but the mechanisms by which the silage microorganisms and metabolites respond to a mixture of oats and vetch at low temperatures remain unclear. In this study, the quality, microorganisms, and metabolites of oats mixed with vetch as a silage material, as well as after 90 days of silage, were analyzed. The traditional view holds that a decrease in microorganism diversity during silage indicates successful fermentation. However, in the present study, microorganism diversity was found to increase after silage under alpine and low-temperature conditions, with a significant rise in the abundance of microorganisms such as Levilactobacillus and Kazachstania. This phenomenon may be explained by the inhibition of rapid lactic acid bacteria proliferation by low temperatures, which allows for the survival of other cold-tolerant microorganisms and their involvement in metabolism. These microorganisms significantly increased the levels of metabolites such as l-methionine, l-glutamine, arachidonic acid, and linolenic acid in the mixed feeds, while simultaneously significantly decreasing the levels of metabolites such as l-leucine, l-arginine, l-asparagine, and glyceric acid. These metabolites possess antioxidant and anti-inflammatory properties that enhance the nutritional value of the feed and indirectly improve the immunity and performance of ruminants. This study comprehensively revealed the complex network of interactions between microorganisms and metabolites in the mixed forage of oats and vetch in alpine pastures and elucidated the regulatory mechanism of silage under low temperatures. The subsequent development of microorganism preparations for the targeted regulation of silage quality provides a theoretical foundation for producing high-quality silage in alpine pastures. Full article

The objective of this work was to explore the effect of taxonomically and phytochemically rich swards, as opposed to ‘status quo’ monoculture of ryegrass and white clover swards, on animals and milk, by assessing the metabolomic profile of plant and milk samples. The results of this study suggest that metabolomic profiles and metabolism are altered by dietary diversity and grazing management. Several metabolites associated with enhanced consumer health were elevated in milk from cows that were grazed in functionally diverse swards as opposed to monoculture of ryegrass and white clover swards. The results show the value of metabolomics for the identification of metabolites associated with a ‘pasture-fed diet’, which is considered beneficial to human health compared with grain-fed milk products. Metabolomics also provide evidence that grazing management and the presence of key forages may be more beneficial for market differentiation of milk products that can enhance consumer health than maximisation of sward species diversification. Full article

Cultivated pasture grasses contribute forage to more than 40% of cattle produced in 11 southern states in the USA. In recent years the increasing intoxication of cattle feeding on pasture grasses raised serious concerns about their palatability. While molecular and metagenomics techniques have revealed the great diversity of microbial composition and functional richness of the grass endosphere microbiome, meta-sequencing techniques enable us to gain a bird’s-eye view of all plant-associated microbiomes as a ‘holobiont’. Plant holobionts provide a more comprehensive approach where one can define the functions of microbial communities and feedback between the core and satellite microbiomes of a targeted host. In the near future we will be able to tailor our grasses and their endosphere microbiomes through the host-directed selection of a ‘modular microbiome’, leading to ‘plant enhanced holobionts’ as a microbiome-driven solution to managing the intoxication of pasture grasses in livestock. The present review aims to understand the potential co-relation between the endosphere microbiome community composition and mycotoxin production in forage grasses in the southern United States. Full article

Salinity stress is a major environmental challenge that adversely impacts the physiological and biochemical processes of pasture, consequently resulting in reduced yields and compromised quality. Biochar amendment has recently emerged as a promising strategy to alleviate the deleterious effects of salinity stress. However, the interactive influences of salinity stress and wheat straw biochar on the physiological, biochemical, and growth characteristics of alfalfa (Medicago sativa L.) remain underexplored. A factorial experiment was conducted using a randomized complete design with five salinity levels (0, 25, 50, 75, and 100 mM NaCl) and three application rates of biochar (0, 25, and 50 g kg⁻¹) to evaluate wheat straw biochar’s potential in alleviating salinity stress in alfalfa. Results showed that salinity stress increased oxidative stress (hydrogen peroxide and malondialdehyde) and reduced chlorophyll fluorescence (maximum quantum efficiency of photosystem II by 1–27%), leading to decreasing photosynthetic parameters, thereby constraining biomass accumulation by 9–77%. Wheat straw biochar amendment under the highest salinity stress, particularly at 25 g kg⁻¹, mitigated oxidative stress by reducing H₂O₂ and MDA levels by 35% and 33%, respectively, while decreasing the antioxidant enzymes activities of CAT, POD, and SOD by 47%, 42%, and 39%, respectively, compared to the control (non-biochar addition). Concurrently, biochar restored the osmoregulatory substance concentrations of proline and soluble sugar by 59% and 33%, respectively, compared to the control. Furthermore, wheat straw biochar amendment increased the net CO₂ assimilation rate by 98%, thereby increasing biomass by 63%. Our study demonstrates that wheat straw biochar can contribute to protecting alfalfa against salinity stress by modulating physiological and biochemical responses. These findings demonstrate that the 25 g kg⁻¹ wheat straw biochar application had the best performance, suggesting this amendment could be a viable strategy for improving alfalfa productivity in salt-affected soils. Future research should explore long-term field applications and the underlying mechanisms of biochar–plant–soil–plant interactions under diverse saline-alkali environments. Full article

Land management decisions and conservation value are heavily influenced by land ownership, land cover, and land use. Our research aimed to examine ownership and land cover distribution, classify landowners based on land cover composition, and evaluate the ability of land cover clustering to be predictive of landowner motivations and behaviors in Maryland, USA. We tabulated a high-resolution land cover map against ownership boundaries, applied hierarchical clustering, and identified five landowner types characterized by a dominant land cover: (1) forest, (2) turf grass, (3) developed, (4) hay/pasture, and (5) crops. We analyzed a landowner survey of 3344 respondents to reveal how clusters predicted recreation, conservation, income, and other motivations. We found a skewed ownership distribution: 95.3% of smaller ownerships (<5 acres) cover 27.3% of the land, while 4.7% of larger owners hold 72.7%. Ownership patterns vary by cover, with forests and wetlands showing bimodal distributions, unimodal for cropland and hay/pasture, and turf grass concentrated in smaller properties. Survey analysis showed that crop, hay/pasture, and forest clusters had income percentages increasing with property size, with crop and hay/pasture accelerating more; conservation interest rose with size for forest and crop, but not hay/pasture; hunting motivation was highest in forest but increased with size similarly across clusters; non-hunting recreation motivation was highest in smaller hay/pasture properties, but decreased with size for all. Although each landowner has unique motivations and goals, our results reveal trends mediated by size of property and land cover that can be used to target outreach and improve conservation outcomes across Maryland’s diverse landscape. Full article

The drive towards carbon neutrality has prompted the worldwide expansion of utility-scale solar facilities. Previous studies have reported the positive effects of solar facilities’ installation on pasture productivity and biodiversity in arid regions. However, our understanding of how solar facilities influence a wide range of ecosystem functions simultaneously, and the relative contributions of soil microbial attributes, remains incomplete. To address this gap, we assessed the changes in ecosystem multifunctionality following solar facility installation in an alpine desert grassland in the Qinghai–Tibet plateau by measuring twenty-three ecosystem function indicators comprising primary production, the soil nutrient pool, carbon cycling, nitrogen cycling, phosphorus cycling and oxidation–reduction. Furthermore, we estimated the soil microbial diversity, microbial indicator taxa and microbial activity to identify the primary driving factors. The results showed that solar facilities had positive effects on ecosystem multifunctionality; the positive effect size was higher in the initial installation period (31.4%) than in the constant running period (3.5%). The enhancements in ecosystem multifunctionality were mainly due to enhanced nutrient cycling induced by the increased abundance of fungal indicator taxa and microbial activity. Moreover, the structural equation model revealed distinct regulatory paths between the two periods and a transition in the primary driving factors of ecosystem multifunctionality from microbial indicator taxa to microbial activity. In conclusion, our study demonstrates the positive influence of solar facilities on multiple ecosystem functions, emphasizing the critical role of soil microbial mechanisms in regulating ecosystem multifunctionality. These findings provide valuable insights into soil biota-driven processes that could inform strategies aimed at enhancing soil health and ecosystem functionality in arid grasslands under human-managed systems. Full article

Small mammals are common in farmland, where their communities are affected by agricultural management. However, so far, no clear patterns have emerged, its effect varying in accordance with the ecological context, spatial scale, and geographic area. We aimed to assess whether the discontinuation of land cultivation and pasture grazing leads to significant changes in the abundance, diversity, and composition of small mammal communities. These were surveyed in transects of live traps set in used and abandoned arable fields and pastures in highly patched agricultural landscapes in Transylvania (Romania). Farmland abandonment was positively related to species richness, taxonomic and functional diversity, and abundance. Its effect was stronger in pastures, where intensive grazing is a limiting factor for small mammals. Functional trait composition was also sensitive to fallowing and abandonment of grazing, which promote diurnal activity, broader niches, and lower fertility. In conclusion, small mammals benefit from the maintenance of uncultivated plots and low numbers of grazing livestock, which we recommend as management strategy in traditional mosaic landscapes, to support taxonomic and functional biodiversity with implications in ecosystem service functionality. Our results also revealed more diverse communities than those showcased by similar studies in central and western Europe, with similar overall abundances. Full article

Pastoral activities are an essential part of the cultural and ecological landscape of Central Italy. This traditional practice supports local economies, maintains biodiversity, and contributes to the sustainable use of natural resources. Understanding livestock behavior in response to environmental variability is essential for improving grazing management and animal welfare and ensuring the sustainability of these systems. This study evaluated the movement patterns of sheep grazing on pastures with differing vegetation indices in the Sibillini Mountains. Twenty lactating ewes foraging on two different pastures were monitored from June to October 2023 using GPS collars and accelerometers. GPS tracks were segmented using the Expectation Maximization Binary Clustering (EmBC) method to characterize movement behaviors, such as foraging, traveling, and resting. The NDVI was used to characterize vegetation dynamics, showing notable differences between the two pastures and across the grazing season. Additive mixed models were used to analyze data, accounting for individual variability and temporal autocorrelation in the sample. The results suggest that variations in the NDVI influence grazing behavior, with sheep in areas of lower vegetation density exhibiting increased movement during foraging. These findings provide valuable insights for optimizing grazing practices and promoting sustainable land use. Full article