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2篇 您的检索式:作者名="Ram PSharma"
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1Comparing independent climate-sensitive models of aboveground biomass and diame ter grow th with their compatible simultaneous model system for three larch species in China显示文摘Accurate estimate of tree biomass is essential for forest management.In recent years,several climate-sensitive allometric biomass models with diameter at breast height(D)as a predictor have been proposed for various tree species and climate zones to estimate tree aboveground biomass(AGB).But the allometric models only account for the potential effects of climate on tree biomass and do not simultaneously explain the influence of climate on D growth.In this study,based on the AGB data from 256 destructively sampled trees of three larch species randomly distributed across the five secondary climate zones in northeastern and northern China,we first developed a climate-sensitive AGB base model and a climate-sensitive D growth base model using a nonlinear least square regression separately.A compatible simultaneous model system was then developed with the climate-sensitive AGB and D growth models using a nonlinear seemingly unrelated regression.The potential effects of several temperature and precipitation variables on AGB and D growth were evaluated.The fitting results of climatic sensitive base models were compared against those of their compatible simultaneous model system.It was found that a decreased isothermality([mean of monthly(maximum temperatureminimum temperature)]/(Maximum temperature of the warmest month-Minimum temperature of the coldest month))and total growing season precipitation,and increased annual precipitation significantly increased the values of AGB;an increase of temperature seasonality(a standard deviation of the mean monthly temperature)and precipitation seasonality(a standard deviation of the mean monthly precipitation)could lead to the increase of D.The differences of the model fitting results between the compatible simultaneous system with the consideration of climate effects on both AGB and D growth and its corresponding climate-sensitive AGB and D growth base models were very small and insignificant(p>0.05).Compared to the base models,the inhere nt correlation of AGB with D was taken into account effectively by the proposed compatible model system developed with the climate-sensitive AGB and D grow th models.In addition,the compatible properties of the estimated AGB and D were also addressed substantially in the proposed model system.Zhigang Gao Qiuyan Wang Zongda Hus Peng Luo Guangshuang Duan Ram PSharma Qiaolin Ye Wenqiang Gao Xinyu Song Liyong Fut 2019International Journal of Biomathematics2019,12,7:1
2Generalized or general mixed-effect modelling of tree morality of Larix gmelinii subsp.principis-rupprechtii in Northern China显示文摘Tree mortality models play an important role in predicting tree growth and yield,but existing mortality models for Larix gmelinii subsp.principis-rupprechtii,an important species used for regeneration and afforestation in northern China,have overlooked potential regional influences on tree mortality.This study used data acquired from 102 temporary sample plots(TSPs)in natural stands of Prince Rupprecht larch in the state-owned Guandi Mountain Forest(n=67)and state-owned Boqiang Forest(n=35)in northern China.To model stand-level tree mortality,we compared seven model forms of county data.Three continuous(dominant height,plot mean diameter,and basal area per hectare)and one dummy variable with two levels(region)were used as fixed effects variables.Tree morality variations caused by forest blocks were accounted for using forest blocks as a random effect in selected models.Results showed that tree mortality significantly positively correlated with stand basal area and dominant height,but negatively correlated with stand mean diameter.Incorporating both the dummy variables and random effects into the tree mortality models significantly increased the fitting improvements,and Hurdle Poisson mixed-effects model showed the most attractive fit statistics(largest R^(2)and smallest RMSE)when employing leave-one-out cross-validation.These mixed-effects dummy variable models will be useful for accurately predicting Larix tree mortality in different regions.Xiao Zhou Liyong Fu Ram PSharma Peng He Yuancai Lei Jinping Guo 2021Journal of Forestry Research2021,32,6:0
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