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Purpose The current knowledge of belowground interactions in intercropping systems is limited due to methodological constraints. The current study aimed to investigate cereal-brassica and cereal-legume-brassica cover crop mixtures regarding mixture effects on root and shoot biomass as well as root traits, vertical root niche differentiation, and complementarity. Methods Sole crops and two- and three-species-mixtures of winter rye ( Secale cereale L.), crimson clover ( Trifolium incarnatum L.), and oil radish ( Raphanus sativus L. var. oleiformis Pers.) were grown in Germany in a two-year organic field experiment. Root traits were analysed using the monolith method. For discrimination of species root mass Fourier transform infrared (FTIR) spectroscopy was used. Results Oil radish dominated mixtures above- and belowground. Oil radish and its mixtures had highest root length density (RLD) and root mass density (RMD) in subsoil. Rye had highest root biomass and RLD in topsoil. Clover was uncompetitive and had low RLD and RMD. Large but non-significant mixture effects occurred in the shoot, especially for shoot nutrient uptake. Mixture effects were positive for RLD and RMD in subsoil and positive for specific root length (SRL) throughout the whole profile. There was no clear evidence for vertical root niche differentiation and root mass complementarity. Conclusion Oil radish as a mixing partner increased rooting in subsoil. When comparing mixtures and sole crops, morphological changes, i.e. higher SRL in mixtures, were found. Contrary to expectations, changes in root allocation patterns, such as vertical niche differentiation or complementarity of root mass, were not observed.

Plant phenology differs largely among coexisting species within communities that share similar habitat conditions. However, the factors explaining such phenological diversity of plants have not been fully investigated. We hypothesize that species traits, including leaf mass per area (LMA), seed mass, stem tissue mass density (STD), maximum plant height (H max), and relative growth rate in height (RGRH), explain variation in plant phenology, and tested this hypothesis in an alpine meadow. Results showed that both LMA and STD were positively correlated with the onset (i.e., beginning) and offset (i.e., ending) times of the four life history events including two reproductive events (flowering and fruiting) and two vegetative events (leafing and senescing). In contrast, RGRH was negatively correlated with the four life phenological events. Moreover, H max was positively correlated with reproductive events but not with vegetative events. However, none of the eight phenological events was associated with seed size. In addition, the combination of LMA and STD accounted for 50% of the variation in plant phenologies. Phylogenetic generalized least squares analysis showed plant phylogeny weakened the relationships between species traits vs. phenologies. Phylogeny significantly regulated the variation in the ending but not the beginning of phenologies. Our results indicate that species traits are robust indicators for plant phenologies and can be used to explain the diversity of plant phenologies among co-occurring herbaceous species in grasslands. The findings highlight the important role of the combination of and trade-offs between functional traits in determing plant phenology diversity in the alpine meadow.

Soil water uptake is a function of root growth and distribution. Therefore, restrictions on root system growth may reduce water and nutrient uptake, which results in slower plant growth. The objective of this study was to determine the effects of different irrigation strategies, nitrogen application rates, and planting methods on the winter wheat root growth. The experimental factors included two irrigation strategies (variable alternate furrow irrigation defined as partial root-zone irrigation and ordinary furrow irrigation), two planting methods (in-furrow planting and on-ridge planting), and three nitrogen (N) application rates (0, 150, and 300 kg N ha −1 ) in 2015–2016 and 2016–2017 growing seasons. Results indicated that the in-furrow planting decreased mean root length density and root mass density (8% and 10%, respectively, in the fertilized treatments) compared to that obtained in the on-ridge planting. The partial root-zone irrigation reduced root length density by about 5% and 7% in the fertilized treatments compared to that obtained in full irrigation in the first and second year, respectively; however, these reductions were not statistically significant. Furthermore, the results implied that nitrogen fertilizer application increased root length density by 48% and 24% in the first and second year, respectively. Likely, root mass density increased by 32% and 5% in the first and second year, respectively. The exponential decaying relationship between root length density and soil depth indicated that the in-furrow planting with 300 kg N ha −1 produced the highest root density at the soil surface layer and reduced deep root penetration compared to the on-ridge planting and the other N treatments. Further analysis revealed that grain yield linearly correlated with root length density and root mass density in the first year. However, a polynomial (quadratic) relationship was obtained in the second year. Consequently, increasing the main root traits, including root length and root mass, enhanced winter wheat grain yield until it reached a threshold value. Higher values negatively affected grain yield, which might be due to allocating carbon to roots instead of grains.

Accurately modeling the density of atmospheric mass is critical for orbit determination and prediction of space objects. Existing atmospheric mass density models (ADMs) have an accuracy of about 15%. Developing high-precision ADMs is a long-term goal that requires a better understanding of atmospheric density characteristics, more accurate modeling methods, and improved spatiotemporal data. This study proposes a method for calibrating ADMs using sparse angular data of space objects in low-Earth orbit over a certain period of time. Applying the corrected ADM not only improves the accuracy of orbit determination, but also enhances the accuracy of orbit prediction beyond the correction period. The study compares the impact of two calibration methods: atmospheric mass density model coefficient (ADMC) calibration and high precision satellite drag model (HASDM) calibration on the accuracy of orbit prediction of space objects. One month of ground-based telescope array angular data is used to validate the results. Space objects are classified as calibration objects, participating in ADM calibration, and verification objects, inside and outside the calibration orbit region, respectively. The results show that applying the calibrated ADM can significantly increase the accuracy of orbit prediction. For objects within the calibration orbit region, the calibration object’s orbit prediction error was reduced by about 55%, while that of verification objects was reduced by about 45%. The reduction in orbit prediction error outside this region was about 30%. This proposed method contributes significantly to the development of more reliable ADMs for orbit prediction of space objects with sparse angular data and can provide significant academic value in the field of space situational awareness.

Cell dry mass is principally determined by the sum of biosynthesis and degradation. Measurable change in dry mass occurs on a time scale of hours. By contrast, cell volume can change in minutes by altering the osmotic conditions. How changes in dry mass and volume are coupled is a fundamental question in cell size control. If cell volume were proportional to cell dry mass during growth, the cell would always maintain the same cellular mass density, defined as cell dry mass dividing by cell volume. The accuracy and stability against perturbation of this proportionality has never been stringently tested. Normalized Raman Imaging (NoRI), can measure both protein and lipid dry mass density directly . Using this new technique , we have been able to investigate the stability of mass density in response to pharmaceutical and physiological perturbations in three cultured mammalian cell lines. We find a remarkably narrow mass density distribution within cells, that is, significantly tighter than the variability of mass or volume distribution. The measured mass density is independent of the cell cycle. We find that mass density can be modulated directly by extracellular osmolytes or by disruptions of the cytoskeleton. Yet, mass density is surprisingly resistant to pharmacological perturbations of protein synthesis or protein degradation, suggesting there must be some form of feedback control to maintain the homeostasis of mass density when mass is altered. By contrast, physiological perturbations such as starvation or senescence induce significant shifts in mass density. We have begun to shed light on how and why cell mass density remains fixed against some perturbations and yet is sensitive during transitions in physiological state.

The preservation of natural assets is nowadays an essential commitment. In this regard, root systems are endangered by fungal diseases which can undermine the health and stability of trees. Within this framework, ground penetrating radar (GPR) is emerging as a reliable non-destructive method for root investigation. A coherent GPR-based root-detection framework is presented in this paper. The proposed methodology is a multi-stage data analysis system that is applied to semi-circular measurements collected around the investigated tree. In the first step, the raw data are processed by applying several standard and advanced signal processing techniques in order to reduce noise-related information. In the second stage, the presence of any discontinuity element within the survey area is investigated by analysing the signal reflectivity. Then, a tracking algorithm aimed at identifying patterns compatible with tree roots is implemented. Finally, the mass density of roots is estimated by means of continuous functions in order to achieve a more realistic representation of the root paths and to identify their length in a continuous and more realistic domain. The method was validated in a case study in London (UK), where the root system of a real tree was surveyed using GPR and a soil test pit was excavated for validation purposes. Results support the feasibility of the data processing framework implemented in this study.

A nondestructive sampling method was developed for Lycorma delicatula egg masses based on fixed-radius plot (100 m2) in 2020. All trees >1.0 cm DBH (diameter at breast height, 1.37 m in height) on each plot were visually inspected from the ground 4 m from the tree with binoculars. Egg masses found on trees were separated into six within-tree positions (lower trunk, middle trunk, upper trunk, first branch, second branch, above second branch) and recorded by cardinal directions, whereas those laid on shrubs/vines and stones were recorded without such separation. In total, 146 trees were inventoried at 28 plots over seven study sites (four plots per site). Egg masses were found on 19 tree species plus summer grape (Vitis aestivalis) and stone. Of the 421 total egg masses recorded, 31.1% were on Norway maple (Acer platanoides), followed by tree-of-heaven (Ailanthus altissima; 14.7%), black birch (Betula lenta; 12.6%), tuliptree (Liriodendron tulipifera; 11.9%), and American beech (Fagus grandifolia; 10.2%). Egg mass density per tree was positively correlated with tree diameter, and egg mass density per plot was positively correlated with plot basal area. Egg mass density after conversion ranged from 600 to 3,930 eggs masses/ha with no significant difference among study sites. Cardinal direction had no effect; however, significantly more egg masses were found on the first branches and upper trunks than other within-tree positions. Overall, branches were better than trunks in predicting egg mass number for the tree. The role of distance and late season adult aggregation on oviposition substrate selection are discussed.

Atmospheric drag provides an indirect approach for evaluating atmospheric mass density, which can be derived from the Precise Orbit Determination (POD) of Low Earth Orbit (LEO) satellites. A method was developed to estimate nongravitational acceleration, which includes the drag acceleration of the thermospheric density model and empirical force acceleration in the velocity direction from the centimeter-level reduced-dynamic POD. The main research achievements include the study of atmospheric responses to geomagnetic storms, especially after the launch of the spherical Qiu Qiu (QQ)-Satellite (QQ-Satellite) with the global navigation system satellite (GNSS) receiver onboard tracking the Global Positioning System (GPS) and Beidou System (BDS) data. Using this derivation method, the high-accuracy POD atmospheric density was determined from these data, resulting in better agreement among the QQ-Satellite-derived densities and the NRLMSISE-00 model densities. In addition, the POD-derived density exhibited a more sensitive response to magnetic storms. Improved accuracy of short-term orbit predictions using derived density was one of the aims of this study. Preliminary experiments using densities derived from the QQ-Satellite showed promising and encouraging results in reducing orbit propagation errors within 24 h, especially during periods of geomagnetic activity.

Plasma content and distribution are key parameters in the dynamics of the inner magnetosphere. The plasmasphere contributes, for the most part, to the plasma mass density, and its properties are very dependent on the history of the magnetosphere and geomagnetic activity. In this work, we investigated plasmasphere dynamics and plasmasphere–ionosphere coupling, focusing on the refilling process that followed the geomagnetic storm that occurred on 1 June 2013. The equatorial plasma mass density used to evaluate the refilling rates was remotely sensed by observation of the field line resonance (FLR) frequencies of the geomagnetic field, driven by ultra-low-frequency magnetic waves. The FLR frequencies were retrieved by performing an analysis of signals detected by several station pairs of the European quasi-Meridional Magnetometer Array. We estimated the rate at which the refilling process occurred, concentrating on both the diurnal and the day-to-day refilling rates. The estimated contraction rate during the main phase of the storm was higher than ∼3.5 REd−1, while the average expansion rate was ∼0.4 REd−1. We investigated the radial dependence of the refilling rates, using a novel approach based on fit plasma mass density profiles, and we related their variation to the plasmasphere boundary layer and the zero-energy Alfvén boundary. We found evidence supporting the idea that flux tubes mapping in the region between these two boundaries experience an enhanced refilling process.

Potatoes are a high-value crop with a shallow root system and high fertilizer requirements. The primary emphasis in potato production is minimizing nitrogen-leaching losses from the shallow root zone through fertigation. Therefore, a field experiment was conducted for two consecutive years, 2018–2019 2019–2020 to assess the effect of nitrogen and irrigation amount and frequency on tuber yield, water balance components and water productivity of potatoes under surface and subsurface drip irrigation. The experiment was laid out in a split-plot design with three nitrogen levels (187.5 kg N ha−1 (N1), 150 kg N ha−1 (N2) and 112.5 kg N ha−1 (N3)) in main plots and six irrigation levels in the subsurface (drip lines were laid at 20 cm depth) and one surface drip in subplots. Irrigation scheduling was based on 100% of cumulative pan evaporation at an alternate (I1) and two-day interval (I2), 80% of cumulative pan evaporation at an alternate (I3) and two-day interval (I4), 60% of cumulative pan evaporation at an alternate (I5) and two-day interval (I6) and 80% of cumulative pan evaporation at alternate days with surface drip (I7). Our results showed that potato transpiration was higher in N1 and N2 compared to N3, while soil evaporation was higher in N3 over N1 and N2. Irrigation regimes I5 and I6 had lower transpiration than I1, I2, I3 and I7, while I7 had more soil evaporation than I1, I2 and I3. Leaf area index (LAI), dry matter accumulation (DMA), root mass density (RMD) and tuber yield in N1 and N2 were at par but significantly higher than N3. The LAI and DMA were statistically at par in I1, I2 and I3 but significantly higher than recommended irrigation (I7). Tuber yield was statistically at par in I1, I2, I3 and I7 but I3 and I7 saved 20% irrigation water compared to I1 and I2. On the other hand, real water productivity (WPET) under N1 and N2 were comparable in I3 and I4 but significantly higher than recommended practice (I7) as pooled evapotranspiration (ET) and soil evaporation (E) in I7 were 19.5 and 20.6 mm higher, respectively, than in I3. Among interactive treatment combinations, N1I1, N1I2, N1I3, N1I7, N2I1, N2I2 and N2I3 recorded the highest tuber yields without any significant differences among them. Treatment N2I3 saved 20% nitrogen and irrigation water compared to all other combinations. Water productivity in N1 and N2 was comparable in I3 and I4 but significantly higher than recommended practice (I7).