Estimate Forest Aboveground Biomass of Mountain by ICESat-2/ATLAS Data Interacting Cokriging

Compared with the previous full-waveform data, the new generation of ICESat-2/ATLAS (Advanced Terrain Laser Altimeter System) has a larger footprint overlap density and a smaller footprint area. This study used ATLAS data to estimate forest aboveground biomass (AGB) in a high-altitude, ecologically fragile area. The paper used ATLAS data as the main information source and a typical mountainous area in Shangri-La, northwestern Yunnan Province, China, as the study area. Then, we combined biomass data from 54 ground samples to obtain the estimated AGB of 74,873 footprints using a hyperparametric optimized random forest (RF) model. The total AGB was estimated by combining the best variance function model in geostatistics with the slope that is the covariates. The results showed that among the 50 index parameters and three topographic variables extracted based on ATLAS, six variables showed a significant correlation with AGB. They were, in order, number of canopy photons, Landsat percentage canopy, canopy photon rate, slope, number of photons, and apparent surface reflectance. The optimized random forest model was used to estimate the AGB within the footprints. The model accuracy was the coefficient of determination (R2) = 0.93, the root mean square error (RMSE) = 10.13 t/hm2, and the population estimation accuracy was 83.3%. The optimized model has a good estimation effect and can be used for footprint AGB estimation. The spatial structure analysis of the variance function of footprint AGB showed that the spherical model had the largest fitting accuracy (R2 = 0.65, the residual sum of squares (RSS) = 2.65 × 10−4), the nugget (C0) was 0.21, and the spatial structure ratio was 94.0%. It showed that the AGB of footprints had strong spatial correlation and could be interpolated by kriging. Finally, the slope in the topographic variables was selected as the co-interpolation variable, and cokriging spatial interpolation was performed. Furthermore, a continuous map of AGB spatial distribution was obtained, and the total AGB was 6.07 × 107 t. The spatial distribution of AGB showed the same trend as the distribution of forest stock. The absolute accuracy of the estimation was 82.6%, using the statistical value of the forest resource planning and design survey as a reference. The ATLAS data can improve the accuracy of AGB estimation in mountain forests

Replication of Diener et al. (2010) at University of Toronto, tut5401, W19

we are a group of students completing this replication for advanced social psychology clas

Sulforaphane Prevents Neuronal Apoptosis and Memory Impairment in Diabetic Rats

Background/Aims: To explore the effects of sulforaphane (SFN) on neuronal apoptosis in hippocampus and memory impairment in diabetic rats. Methods: Thirty male rats were randomly divided into normal control, diabetic model and SFN treatment groups (N = 10 in each group). Streptozotocin (STZ) was applied to establish diabetic model. Water Morris maze task was applied to test learning and memory. Tunel assaying was used to detect apoptosis in hippocampus. The expressions of Caspase-3 and myeloid cell leukemia 1(MCL-1) were detected by western blotting. Neurotrophic factor levels and AKT/GSK3β pathway were also detected. Results: Compared with normal control, learning and memory were apparently impaired, with up-regulation of Caspase-3 and down-regulation of MCL-1 in diabetic rats. Apoptotic neurons were also found in CA1 region after diabetic modeling. By contrast, SFN treatment prevented the memory impairment, decreased the apoptosis of hippocampal neurons. SFN also attenuated the abnormal expression of Caspase-3 and MCL-1 in diabetic model. Mechanically, SFN treatment reversed diabetic modeling-induced decrease of p-Akt, p-GSK3β, NGF and BDNF expressions. Conclusion: SFN could prevent the memory impairment and apoptosis of hippocampal neurons in diabetic rat. The possible mechanism was related to the regulation of neurotropic factors and Akt/GSK3β pathway