Effects of local neighbourhood diversity on crown structure and productivity of individual trees in mature mixed-species forests

Background:Species-specific genotypic features,local neighbourhood interactions and resource supply strongly influence the tree stature and growth rate.In mixed-species forests,diversity-mediated biomass allocation has been suggested to be a fundamental mechanism underlying the positive biodiversity-productivity relationships.Empirical evidence,however,is rare about the impact of local neighbourhood diversity on tree characteristics analysed at a very high level of detail.To address this issue we analysed these effects on the individual-tree crown architecture and tree productivity in a mature mixed forest in northern Germany.Methods:Our analysis considers multiple target tree species across a local neighbourhood species richness gradient ranging from 1 to 4.We applied terrestrial laser scanning to quantify a large number of individual mature trees(N=920)at very high accuracy.We evaluated two different neighbour inclusion approaches by analysing both a fixed radius selection procedure and a selection based on overlapping crowns.Results and conclusions:We show that local neighbourhood species diversity significantly increases crown dimension and wood volume of target trees.Moreover,we found a size-dependency of diversity effects on tree productivity(basal area and wood volume increment)with positive effects for large-sized trees(diameter at breast height(DBH)>40 cm)and negative effects for small-sized(DBH<40 cm)trees.In our analysis,the neighbour inclusion approach has a significant impact on the outcome.For scientific studies and the validation of growth models we recommend a neighbour selection by overlapping crowns,because this seems to be the relevant scale at which local neighbourhood interactions occur.Because local neighbourhood diversity promotes individual-tree productivity in mature European mixed-species forests,we conclude that a small-scale species mixture should be considered in management plans.

Non-invasive determination of hepatic steatosis by acoustic structure quantification from ultrasound echo amplitude

AIM:To use leptin-deficient(ob/ob) mice with demonstrated differences in steatosis levels to test a new diagnostic method using the acoustical structure quantification(ASQ) mode and the associated analytical parameter,"focal disturbance ratio"(FD-ratio).METHODS:Nine ob/ob mice,at 5,8,and 12 wk of age(n = 3 in each age group),were used as models for hepatic steatosis.Echo signals obtained from ultrasonography in the mice were analyzed by ASQ,which uses a statistical analysis of echo amplitude to estimate inhomogeneity in the diagnostic region.FD-ratio,as calculated from this analysis,was the focus of the present study.FD-ratio and fat droplet areas and sizes were compared between age groups.RESULTS:No fibrosis or inflammation was observed in any of the groups.The fat droplet area significantly(P < 0.01) increased with age from 1.25% ± 0.28% at 5 wk to 31.07% ± 0.48% at 8 wk to 51.69% ± 3.19% at 12 wk.The median fat droplet size also significantly(P < 0.01) increased with age,from 1.33(0.55-10.52) m at 5 wk,2.82(0.61-44.13) m at 8 wk and 6.34(0.66-81.83) m at 12 wk.The mean FD-ratio was 0.42 ± 0.11 at 5 wk,0.11 ± 0.05 at 8 wk,and 0.03 ± 0.02 at 12 wk.The FD-ratio was significantly lower at 12 wk than at 5 wk and 8 wk(P < 0.01).A significant negative correlation was observed between the FD-ratio and either the fat droplet area(r =-0.7211,P = 0.0017) or fat droplet size(r =-0.9811,P = 0.0052).CONCLUSION:This tool for statistical analysis of signals from ultrasonography using the FD-ratio can be used to accurately quantify fat in vivo in an animal model of hepatic steatosis,and may serve as a quantitative biomarker of hepatic steatosis.

In Silico Investigation of Agonist Activity of a Structurally Diverse Set of Drugs to hPXR Using HM-BSM and HM-PNN

The human pregnane X receptor（hPXR） plays a critical role in the metabolism, transport and clearance of xenobiotics in the liver and intestine. The hPXR can be activated by a structurally diverse of drugs to initiate clinically relevant drug-drug interactions. In this article, in silico investigation was performed on a structurally diverse set of drugs to identify critical structural features greatly related to their agonist activity towards h PXR. Heuristic method（HM）-Best Subset Modeling（BSM） and HM-Polynomial Neural Networks（PNN） were utilized to develop the linear and non-linear quantitative structure-activity relationship models. The applicability domain（AD） of the models was assessed by Williams plot. Statistically reliable models with good predictive power and explain were achieved（for HM-BSM, r^2=0.881, q^2_（LOO）=0.797, q^2_（EXT）=0.674; for HM-PNN, r^2=0.882, q^2_（LOO）=0.856, q^2_（EXT）=0.655）. The developed models indicated that molecular aromatic and electric property, molecular weight and complexity may govern agonist activity of a structurally diverse set of drugs to h PXR.