A Comparison of Hierarchical and Non-Hierarchical Bayesian Approaches for Fitting Allometric Larch (Larix.spp.) Biomass Equations

Accurate biomass estimations are important for assessing and monitoring forest carbon storage. Bayesian theory has been widely applied to tree biomass models. Recently, a hierarchical Bayesian approach has received increasing attention for improving biomass models. In this study, tree biomass data were obtained by sampling 310 trees from 209 permanent sample plots from larch plantations in six regions across China. Non-hierarchical and hierarchical Bayesian approaches were used to model allometric biomass equations. We found that the total, root, stem wood, stem bark, branch and foliage biomass model relationships were statistically significant (p-values \u3c 0.001) for both the non-hierarchical and hierarchical Bayesian approaches, but the hierarchical Bayesian approach increased the goodness-of-fit statistics over the non-hierarchical Bayesian approach. The R2 values of the hierarchical approach were higher than those of the non-hierarchical approach by 0.008, 0.018, 0.020, 0.003, 0.088 and 0.116 for the total tree, root, stem wood, stem bark, branch and foliage models, respectively. The hierarchical Bayesian approach significantly improved the accuracy of the biomass model (except for the stem bark) and can reflect regional differences by using random parameters to improve the regional scale model accuracy

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Spatial Patterns and Drivers of Soil Chemical Properties in Typical Hickory Plantations

Soil nutrients play critical roles in regulating and improving the sustainable development of economic forests. Consequently, an elucidation of the spatial patterns and drivers of soil nutrients in these forests is fundamental to their management. For this study, we collected 314 composite soils at a 0–30 cm depth from a typical hickory plantation in Lin’an, Zhejiang Province, China. We determined the concentrations of macronutrients (i.e., soil organic carbon, available potassium, available phosphorus, available sulfur, and hydrolyzed nitrogen) and micronutrients (i.e., soil available boron, iron, manganese, zinc, and copper) of the soils. We employed random forest analysis to quantify the relative importance of factors affecting soil nutrients to predict the concentrations, which could then be extrapolated to the entire hickory region. Random forest models explained 43–80% of the variations in soil nutrient concentrations. The mean annual temperature, mean annual precipitation, and altitude were key predictors of soil macronutrient and micronutrient concentrations. Moreover, slope and parent material were important predictors of soil nutrients concentrations. Distinct spatial patterns of soil nutrient concentrations were driven by climate, parent material, and topography. Our study highlights the various environmental controls over soil macronutrient and micronutrient concentrations, which have significant implications for the management of soil nutrients in hickory plantations

Characterization of the complete chloroplast genome of Camellia yuhsienensis Hu, a resilient shrub with strong floral fragrance

Camellia yuhsienensis Hu is an economically valuable species in the genus Camellia. It is widely used for breeding ornaments and oil varieties. In this study, the complete chloroplast (cp) genome sequence of C. yuhsienensis is assembled and annotated. The whole cp genome of C. yuhsienensis is 156,912 bp in size, composed of a small single copy (SSC) region of 18,296 bp and a large single copy (LSC) region of 86,560 bp, separated by a pair of inverted repeats (IRs, IRA: 86,561–112,588; IRB: 130,885–156,912). The overall GC content of C. yuhsienensis cp genome is 37.3%, with the base content A (31.08%), T (31.63%), C (19.02%), and G (18.27%). The phylogenetic analysis of 15 Camellia species based on 77 protein-coding genes shows that C. yuhsienensis is evolutionarily close to Camellia taliensis

How Do Landscape Heterogeneity, Community Structure, and Topographical Factors Contribute to the Plant Diversity of Urban Remnant Vegetation at Different Scales?

In highly fragmented urban areas, plant diversity of remnant vegetation may depend not only on community structure and topographical factors, but also on landscape heterogeneity. Different buffer radius settings can affect the relative importance of these factors to plant diversity. The aim of this study was to examine the relative importance of landscape heterogeneity, community structure, and topographical factors on plant diversity under different buffer radii in biodiversity hotspots. We established 48 plots of remnant vegetation in Guangzhou city, one of the biodiversity hotspots. A buffer radius of 500 m, 1000 m, and 2000 m was established around the center of each sample plot, and 17 landscape heterogeneity indices in each buffer were calculated by FRAGSTATS 4.2 software. Combined with the community structure and topographical factors, the impact factors of plant diversity under different buffer radii were analyzed by multiple regression analysis. We found the following: (1) The combined explanatory power of the three factors accounted for 43% of the species diversity indices and 62% of the richness index at its peak. The three impact factors rarely act independently and usually create comprehensive cumulative effects. (2) Scale does matter in urban landscape studies. At a 500 m buffer radius, community structure combined with road disturbance indices was strongly related to diversity indices in herb and shrub layers. The stand age was negatively correlated with the tree-layer richness index. As the scale increased, the diversity indices and richness index in the three layers decreased or increased under the influence of comprehensive factors. (3) The richness index in the herb layer was more responsive to impact factors than other biodiversity indices. Except for the herb layer, the interpretation of landscape heterogeneity for each plant diversity index was more stable than that for the other two factors. Road disturbance indices, combined with the other six landscape pattern metrics, can well indicate species diversity and richness. We suggest that the vegetation area of remnant patches within a radius of 500–2000 m should be appropriately increased to protect plant diversity, and the negative effects of road disturbance should also be considered

Selection by current compliance of negative and positive bipolar resistive switching behaviour in ZrO2−x/ZrO2 bilayer memory

This dataset contains the raw data of figure 1-7 in the journal paper entitled &quot;Selection by current compliance of negative and positive bipolar resistive switching behaviour in ZrO2&minus;x/ZrO2 bilayer memory&quot; published in IOP Journal of Physics D: Applied Physics</span