| 2 | Effects of stand density on soil respiration and labile organic carbon in different aged Larix principis-rupprechtii plantations显示文摘Background:The carbon pools of forest soils play a vital role in global carbon sequestration and emissions.Forest management can regulate the sequestration and output of forest soil carbon pools to a certain extent;however,the kinetics of the effects of forest density on soil carbon pools require further investigation.Methods:We established sample plots with stand density gradients in three different aged Larix principis-rupprechtii plantations and quantified the soil respiration,soil organic carbon(SOC),soil dissolved organic carbon(DOC),microbial biomass carbon(MBC),light fraction organic carbon(LFOC),and readily oxidized carbon(ROC).Results and conclusions:During the growth and development of plantations,stand density is an essential factor that impacts soil respiration and its associated elements.Moderate density was observed to promote both the soil and heterotrophic respiration rates and the sequestration of MBC and LFOC,whereas it inhibited the sequestration of ROC.The soil,heterotrophic,and autotrophic respiration rates of older forest stands were relatively rapid,whereas the contents of SOC,MBC,LFOC,DOC,and ROC were higher and more sensitive to changes in stand density.The MBC,LFOC,and ROC in soil labile organic carbon were closely related to both the soil and heterotrophic respiration,but not the SOC.Among them,the LFOC and MBC played the roles of“warehouse”and“tool”and were significantly correlated with soil and heterotrophic respiration.The ROC,as a“raw material”,exhibited a significantly negative correlation with the soil and heterotrophic respiration.When the soil and heterotrophic respiration rates were rapid,the ROC content in the soil maintained the low level of a“dynamically stabilized”state.The stand density regulated heterotrophic respiration by affecting the soil labile organic carbon,which provided an essential path for the stand density to regulate soil respiration. | Tairui Liu Daoli Peng Zhijie Tan Jinping Guo Yunxiang Zhang | 2021 | Ecological Processes2021，10，1： | 1 |
| 4 | Prediction of Forest Stock Volume Based on Neural Network Model显示文摘BP and RBF neural network to predict forest stock volume were studied,but the study in evaluating both networks’ application effects was not conducted.In order to find a higher forecast precision,more strong applicative method,the comprehensive analysis and evaluation on the two methods were carried out in the practical application. By the correlation analysis,crown density,shady-slope and sunny-slope,TM1,TM2,TM3,TM5, TM7,NDVI,TM,(4-3),TM4/3 were selected as input variables,and the forest volume of Miyun County as output variables,RBF and BP neural network models for forecasting the forest volume were established.And the neural network training step length,training time,prediction accuracy and the applicability model of the two methods were comprehensively analyzed.The results show that the RBF neural network model is superior to the BP neural network model. | Tu Yunyan Peng Daoli | 2012 | Chinese Forestry Science and Technology2012，11，3： | 0 |
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