Feasibility of urban bird occurrence and nest amount evaluation by the street-view image virtual survey.

Bird observation mainly relies on field surveys, which are time-consuming and laborious. In this study, we explored using street-view images in the virtual survey of urban birds and nests. Using the coastal city of Qingdao as the study area, 47 201 seamless spherical photos at 2741 sites were collected using the Baidu street-view (BSV) map. Single-rater-all photo checks and seven-rater-metapopulation checks were used to find inter-rater repeatability, the best viewing layer for BSV collection, and possible environments affecting the results. We also collected community science data for comparison. The BSV time machine was used to assess the temporal dynamics. Kappa square test, generalized linear model, redundancy ordination and ArcMap were used in the analysis. Different rater repeatability was 79.1% in nest evaluations and 46.9% in bird occurrence. A re-check of the different-rating photos can increase them to 92% and 70%. Seven-rater statistics showed that more than 5% sampling ratio could produce a non-significant different bird and nest percentage of the whole data, and the higher sampling ratio could reduce the variation. The middle-viewing layer survey alone could produce 93% precision of the nest checks by saving 2/3 of the time used; in birds, selecting middle and upper-view photos could find 97% of bird occurrences. In the spatial distribution, the nest's hotspot areas from this method were much greater than the community science bird-watching sites. The BSV time machine made it possible to re-check nests in the same sites but challenging the re-check of bird occurrences. The nests and birds can be observed more in the leafless season, on wide, traffic-dense coastal streets with complex vertical structures of trees, and in the gaps of tall buildings dominated by road forests. Our results indicate that BSV photos could be used to virtually evaluate bird occurrence and nests from their numbers, spatial distribution and temporal dynamics. This method provides a pre-experimental and informative supplement to large-scale bird occurrence and nest abundance surveys in urban environments.

Big-sized trees and higher species diversity improve water holding capacities of forests in northeast China.

High water-holding forests are essential for adapting to drought climates under global warming, and a central issue is which type of forests could conserve more water in the ecosystem. This paper explores how forest structure, plant diversity, and soil physics impact forest water-holding capacities. We investigated 720 sampling plots by measuring water-holding capacities from 1440 soil and litter samples, 8400 leaves, and 1680 branches and surveying 18,054 trees in total (28 species). Water-holding capacities were measured as four soil indices (Maxwc, maximum water-holding capacity; Fcwc, field water-holding capacity; Cpwc, soil capillary water-holding capacity; Ncpwc, non-capillary water-holding capacity), two litter metrics (Maxwcl, maximum water-holding capacity of litters; Ewcl, effective water-holding capacity of litters), and canopy interception (C, the sum of estimated water interception of all branches and leaves of all tree species in the plot). We found that water-holding capacity in the big-sized tree plots was 4-25 % higher in the litters, 54-64 % in the canopy, and 6-37 % in the soils than in the small-sized plots. The higher species richness increased all soil water-holding capacities compared to the lowest richness plot. Higher Simpson and Shannon-Wiener plots had 10-27 % higher Ewcl and C than the lowest plots. Bulk density had the strongest negative relations with Maxwc, Cpwc, and Fcwc, whereas field soil water content positively affected them. Soil physics, forest structure, and plant diversity explained 90.5 %, 5.9 %, and 0.2 % of the water-holding variation, respectively. Tree sizes increased C, Ncpwc, Ewcl directly (p < 0.05), and richness increased Ewcl directly (p < 0.05). However, the direct effects from the uniform angle index (tree distribution evenness) were balanced by their indirect effect from soil physics. Our findings highlighted that the mixed forests with big-sized trees and rich species could effectively improve the water-holding capacities of the ecosystem.

Ultrasound-assisted enzymatic extraction of Scutellaria baicalensis root polysaccharide and its hypoglycemic and immunomodulatory activities.

Scutellaria baicalensis is a medicinal plant possessing abundant bioactive polysaccharides. This study aimed to optimize the ultrasound-assisted enzymatic extraction of S. baicalensis root polysaccharide (SRP) and investigate its hypoglycemic and immunomodulatory activities. The optimal extraction conditions found in this study were as follows: cellulase concentration 165.6 U/mL, temperature 57.3 °C, liquid-solid ratio 44.8 mL/g, time 50 min, and ultrasonic power 225 W; with the yield reached up to 12.27 %. The ion exchange and gel filtration chromatographies were used to obtain a purified SRP. The carbohydrate content of SRP was 85.09 %, with a relatively high content of uronic acids (11.27 %). The SRP had a molecular weight of 89.7 kDa and was composed of eight monosaccharides. The inhibitory activity of SRP against α-amylase and α-glucosidase was determined. It was revealed that SRP could effectively inhibit these two enzymes with IC50 values of 1.23 and 0.63 mg/mL, respectively. Finally, the immunomodulatory effect of SRP on the dendritic cell activation was investigated, and the expressions of MHC II, CD80, CD86, and CD40 increased by 1.56, 1.96, 1.75, and 1.70 times, respectively, by the SRP treatment. This work will provide a foundation for SRP's efficient extraction and utilization for diabetes and immune therapy.