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A two-year field experiment was conducted to address the effects of mixture composition and legume-grass seeding ratio on the biomass yield and nutritional quality of legume–grass mixtures. Alfalfa (Medicago sativa L.), white clover (Trifolium repens L.), red clover (Trifolium pratense L.), orchardgrass (Dactylis glomerata L.), perennial ryegrass (Lolium perenne L.), and tall fescue (Festuca arundinacea Schreb.) were selected as plant materials. A total of seven legume–grass mixtures (A1: white clover, orchardgrass, and tall fescue; A2: alfalfa, orchardgrass, and tall fescue; B1: alfalfa, white clover, orchardgrass, and tall fescue; B2: red clover, white clover, orchardgrass, and tall fescue; C1: alfalfa, white clover, orchardgrass, tall fescue, and perennial ryegrass; C2: red clover, white clover, orchardgrass, tall fescue, and perennial ryegrass; and D: alfalfa, red clover, white clover, orchardgrass, tall fescue, and perennial ryegrass) were sown in two legume-grass seeding ratios (L:G) of 4:6 and 5:5. The results showed that A2 produced a higher two-year average biomass yield (14.20 t/ha) in L:G of 4:6 than that of other mixtures. The grasses biomass yield proportion decreased while legume biomass yield proportion increased with prolonged establishment time. A2 showed a higher crude protein yield (2.5 t/ha) in L:G of 4:6. C2 and A1 showed lower neutral detergent fiber (4.6 t/ha) and acid detergent fiber (2.8 t/ha) yields in L:G 5:5, while diverse mixtures showed higher water-soluble carbohydrate yields. Overall, A2 showed a relative feed value of 146.50 in L:G of 4:6, indicating that it has not only produced the higher biomass yield but also had a better nutritional quality.

The scarcity of high-quality forage has a significant influence on the productivity and profitability of livestock. Addressing this concern, an investigation was undertaken to assess the effects of distinct Italian ryegrass genotypes, namely, Punjab ryegrass-1, Kashmir collection, and Makhan grass, in conjunction with varying seeding ratios of Italian ryegrass to Egyptian clover. The seeding ratios considered were 100:0 (Italian ryegrass to Egyptian clover), 75:25, 50:50, and 25:75. All possible combinations of Italian ryegrass and Egyptian clover with seeding ratios were set up in a randomized complete block design and replicated thrice. Co-cultivating Italian ryegrass and Egyptian clover at a 75:25 seeding ratio yields the best yield benefit, as determined by the land equivalent ratio. It is noteworthy that in this configuration, real yield loss is higher for Egyptian clover and for Italian ryegrass when the seeding ratio is 25:75. The higher competitiveness of Italian ryegrass in comparison to Egyptian clover is highlighted by the competitive ratio. Notably, the nutritive parameter, crude protein yield, was significantly higher in the Makhan grass-based 50:50 and 75:25 seeding ratio. Results of the study ascertained the compatibility of grass-legume co-cultivation with significantly higher quantity and quality forage harvested under mixed cropping systems whereas Makhan grass as the superior and dominant genotype in comparison to Kashmir collection. The outcomes of this study revealed that the 100:0 seeding ratio, coupled with the Makhan grass genotype, exhibited superior performance in terms of cumulative forage harvest, dry matter accumulation, net returns, and benefit–cost ratio.

Forage and grain production of an early sown, long-cycle wheat variety (ProINTA Super) was compared to that in its association with a short-cycle wheat variety (Buck Pronto), both varieties exposed to one or two defoliations. The purpose was producing an earlier and greater amount of dry matter in a dual-purpose wheat. Research was conducted in the Asociación de Cooperativas Argentinas experimental field (38º 36´ S, 61º 58´ W, 122 masl), 15 km SW from Cabildo (Bs. As), in the semi-arid V South wheat subregion. Experimental plots, 7 rows 4m long each and 0,20 m apart from each other, were seeded on 4 March 2004. Seeding rate used was 300 viable seeds/m2 for Super, adding 400 viable seeds/m2 for the association. The first defoliation was made on 30 April and the second one on 2 July, both to a 7 cm stubble height. Grain harvest was made on 17 December in all treatments. ProINTA Super, cultivated either exclusively for grain production (without defoliation), or dual purpose with one defoliation or associated with Buck Pronto, with one or two defoliations, produced equal grain amounts (average 1940 kg/ha). Seeded early either for dual purpose or associated, both varieties with one defoliation, also produced approximately 2400 kg dry matter/ha. However, when seeded early, associated with the other variety, and both exposed to two defoliations, produced 2080 kg of grain/ha and 4060 kg dry matter/ha.

Seeding strategies have strong influences on the success of viral marketing campaigns, but previous studies using computer simulations and analytical models have produced conflicting recommendations about the optimal seeding strategy. This study compares four seeding strategies in two complementary small-scale field experiments, as well as in one real-life viral marketing campaign involving more than 200,000 customers of a mobile phone service provider. The empirical results show that the best seeding strategies can be up to eight times more successful than other seeding strategies. Seeding to well-connected people is the most successful approach because these attractive seeding points are more likely to participate in viral marketing campaigns. This finding contradicts a common assumption in other studies. Well-connected people also actively use their greater reach but do not have more influence on their peers than do less well-connected people.

Kentucky bluegrass (KBG) is well-suited as a perennial groundcover in corn production due to its vigorous growth during the fall and spring and its natural dormancy during the summer, aligning with the corn growing season. However, seeds of KBG germinate slowly, potentially resulting in poor stand establishment in the Midwest, USA. This study was conducted to assess the effect of the seeding rate, the seed ratio in a perennial ryegrass/KBG mixture (PRG:KBG), and seed treatment on KBG percentage groundcover, green rating, the red/far-red ratio, soil temperature, soil moisture, and summer biomass. The split-plot design consisted of KBG seeds treated with the HydrolocTM hydrophilic polymer and untreated seeds with seeding rates and ratios in a randomized design. Hydroloc™ seed treatment showed a significant difference in the fall percentage of groundcover but did not affect the spring groundcover. The seed ratio had a significant effect on the fall and spring groundcover, with a ratio of 1:1 (PRG:KBG) performing best, followed by 1:3, 1:5, and 0:1. The seeding rate was also significant, with 44.8 kg ha−1 having the highest groundcover, followed by 22.4 kg ha−1 and 11.2 kg ha−1. The red/far-red readings, which reflect plant density, gave corresponding results to the percentage of groundcover. The Hydroloc™ hydrophilic polymer increases the groundcover percentage by improving KBG establishment. These results are important for farmers and seed companies interested in using KBG as a perennial groundcover in corn production systems. We recommend a seed ratio of 1:1 (PRG:KBG) and a seeding rate of 22.4 kg ha−1 to provide a dense and rapid-establishing groundcover that is also financially viable for the farmer.

The James Webb Space Telescope has identified a large population of supermassive (106–108 M⊙) black holes (BHs) in the early Universe (z ∼ 4–7). Current measurements suggest that many of these BHs exhibit higher BH-to-stellar mass ratios than local populations, opening a new window into the earliest stages of BH–galaxy coevolution and offering the potential to place tight constraints on BH seeding and growth in the early Universe. In this work, we use the BRAHMA simulations to investigate the impact of BH seeding on the M•–σ relation. These simulations adopt heavy ∼105 M⊙ seeds and systematically varied BH seeding models, resulting in distinct predictions for seed abundances. We find that different seed models lead to different normalizations of the M•–σ relation at higher redshifts (z > 2) across all σ, and at low redshift for systems with low σ (50 km s−1 ≲ σ ≲ 80 km s−1). The most lenient seed model also shows negligible evolution in the M•–σ relation across redshift, while more restrictive models have substantially lower normalization on the M•–σ relation for high σ (∼100 km s−1) at high redshifts, and evolve upward toward the local relation. We demonstrate that, while an evolving M*–σ relation mitigates changes in the M•–σ relation, any M•–σ evolution is a direct consequence of merger-dominated BH growth in low mass galaxies (≲109 M⊙) and accretion-dominated BH growth in high-mass (≳109 M⊙) galaxies. Furthermore, the scatter in the M•–σ relation is larger for the more restrictive models due to the inability of many BHs to grow significantly beyond their seed mass.

Aim We aimed to evaluate the performance of native tree species in the restoration of savanna vegetation by direct seeding, to assess whether weed control and intercropping with native grasses can contribute to the success of this method and to determine whether species performance can be explained by functional traits. Location Cerrado biome, southeastern Brazil. Old fields abandoned after decades of land use as pasture or croplands, occupied by ruderal plants and invasive grasses. Methods We established a direct seeding experiment with ten tree species native to the cerrado (Brazilian savanna) region. We used a factorial design in five blocks, with the following factors: (a) species; (b) weed control and (c) intercropping with native grasses. We evaluated the emergence, survival and growth of plants, and through multiple regressions we sought to explain the success of the species in direct seeding based on their functional traits. Results Emergence and survival in the field varied widely among species but with little or no difference between treatments. Growth was compromised by weed competition in all species. Intercropping with native grasses did not decrease weed competition. We found a functional pattern associated with species performance in direct seeding, where survival in the field is positively associated with seed mass, root depth and a greater root:shoot ratio. Conclusion Weed competition impairs seedling growth more than survival, considerably delaying restoration by direct seeding. The success of this method in the savanna will depend on the use of species that are best adapted to environments where water stress is the main obstacle to overcome and have large seeds and seedlings with a large and deep root system. Characterizing underground seedling systems is essential for predicting the success of cerrado species in direct seeding. Our study constitutes an advance in the ecology of restoration by providing guidance for the selection of species to be used in direct seeding in savannas ecosystems under restoration. We used survival in the field as an indicator of good performance, to find a set of functional traits that are good predictors of success in direct seeding.

Although the chaotic nature of the atmosphere may enable efficient control of tropical cyclones (TCs) via small‐scale perturbations, few studies have proposed data‐driven optimization methods to identify such perturbations. Here, we apply the recently proposed Ensemble Kalman Control (EnKC) to a TC simulation. We show that EnKC finds small‐scale perturbations that mitigate TC. An EnKC‐estimated reduction in surface water vapor, located approximately 250 km from the TC center, suppresses convective activity and latent heat release in the eye wall, leading to a reduction of TC intensity. To advance the discovery of feasible TC mitigation strategies, we discuss the potential of this data‐driven method for leveraging chaos, as well as its remaining challenges.

Ice aggregation in clouds plays a crucial role in cloud development and precipitation formation. Despite the significance of ice aggregation, direct in situ quantification of aggregation rates in natural clouds has been challenging due to the difficulty of tracking ice crystals. Here, we present in situ measurements of ice aggregation rates in persistent supercooled stratiform clouds. Using novel glaciogenic seeding experiments (CLOUDLAB), ice crystals are nucleated upwind and subsequently measured downwind after a known advection time in cloud, allowing us to estimate their age. A deep-learning-based detection algorithm (IceDetectNet) counts the individual monomers of aggregates to derive the initial ice crystal number concentration (ICNCt0). We considered several factors that may influence ice aggregation, including ICNCt0, temperature, ice crystal size, aspect ratio, and turbulence. Among these, ICNCt0 was found to be the dominant factor controlling aggregation rates by three independent approaches: causal inference, a physical equation, and machine learning models. We report, however, a subquadratic dependence of the aggregation rate on ICNCt0 (mean exponent ∼ 0.92; 95 % CI: 0.88–0.97), in contrast to theoretical expectations (quadratic dependence). One possible explanation is that aggregation may also involve smaller ice crystals, but this remains hypothetical. To predict aggregation rates, we evaluated 11 machine learning models and a physically based formulation. CatBoost achieved the best statistical performance, while the physical model proved more robust in sensitivity tests. These findings provide new insights into the microphysical and environmental controls of ice aggregation and establish a robust methodological foundation for studying aggregation processes in natural clouds.

PurposeAs a carbon sequestration material, biochar has attracted much attention due to its potential to enhance rice productivity and nitrogen retention in paddy fields. However, little information is available about the impacts of rice straw-derived biochar on coating materials of slow-release fertilizers especially with bentonite, starch, and humic acid.Materials and methodsIn this study, a biochar-based slow-release fertilizer was developed and evaluated at field scale. An orthogonal experimental design was applied to investigate the blending ratios of biochar, humic acid, and bentonite with three adhesives, and how these influenced N release.Results and discussionThe optimum coating combination was 25% biochar, 4% bentonite, and 10% humic acid with modified cornstarch as the adhesive (herein referred to as CF10). The product not only decreased N leaching and runoff losses at the seeding and tillering stages but also supplied more nutrients to the rice at the heading and maturing stages. The SEM and FT-IR observations revealed that an effective dense layer was formed that slowed N release from the granule.ConclusionsLaboratory- and field-scale studies showed that biochar has played a crucial role in developing a slow-release coating for the compound fertilizer based on its structural properties, porosity, and chemical interaction with other coating ingredients. We conclude that biochar-based slow-release fertilizer is a promising alternative N fertilizer for rice production.