Background：Information on above-ground biomass（AGB） is important for managing forest resource use at local levels,land management planning at regional levels,and carbon emissions reporting at national and internati...Background：Information on above-ground biomass（AGB） is important for managing forest resource use at local levels,land management planning at regional levels,and carbon emissions reporting at national and international levels.In many tropical developing countries,this information may be unreliable or at a scale too coarse for use at local levels.There is a vital need to provide estimates of AGB with quantifiable uncertainty that can facilitate land use management and policy development improvements.Model-based methods provide an efficient framework to estimate AGB.Methods：Using National Forest Inventory（NFI） data for a^1,000,000 ha study area in the miombo ecoregion,Zambia,we estimated AGB using predicted canopy cover,environmental data,disturbance data,and Landsat 8 OLI satellite imagery.We assessed different combinations of these datasets using three models,a semiparametric generalized additive model（GAM） and two nonlinear models（sigmoidal and exponential）,employing a genetic algorithm for variable selection that minimized root mean square prediction error（RMSPE）,calculated through cross-validation.We compared model fit statistics to a null model as a baseline estimation method.Using bootstrap resampling methods,we calculated 95% confidence intervals for each model and compared results to a simple estimate of mean AGB from the NFI ground plot data.Results：Canopy cover,soil moisture,and vegetation indices were consistently selected as predictor variables.The sigmoidal model and the GAM performed similarly;for both models the RMSPE was -36.8 tonnes per hectare（i.e.,57% of the mean）.However,the sigmoidal model was approximately 30% more efficient than the GAM,assessed using bootstrapped variance estimates relative to a null model.After selecting the sigmoidal model,we estimated total AGB for the study area at 64,526,209 tonnes（＋/- 477,730）,with a confidence interval 20 times more precise than a simple designbased estimate.Conclusions：Our findings demonstrate that NFI data may be combined with freely available satellite imagery and soils data to estimate total AGB with quantifiable uncertainty,while also providing spatially explicit AGB maps useful for management,planning,and reporting purposes.展开更多
In the early 1980s, Chinese meteorologists discovered the positive correlation in summer rainfall between India and North China and the correlation was later confirmed by some researches in and outside China. Based on...In the early 1980s, Chinese meteorologists discovered the positive correlation in summer rainfall between India and North China and the correlation was later confirmed by some researches in and outside China. Based on a variety of meteorological data from 1951 to 2005 and numerical simulations, the present study investigates such a correlation between Indian summer monsoon （ISM） and precipitation in North China. Furthermore, we discuss the intrinsic relations of the positive （Northwest India）-negative （the Tibetan Plateau）-positive （North China） precipitation anomaly teleconnection pattern from two aspects of thermal and dynamical factors, which not only confirms the precipitation teleconnection previously discovered again, but also reveals the influence mechanism of the ISM on the rainfall in North China. The results show that： （1） When the ISM is strong （weak）, the precipitation in North China tends to be more （less） than normal; however, when the rainfall in North China is more （less） than normal, the probability of the strengthening （weakening） of the ISM is relatively lower. This implies that the ISM anomaly has more impact on the rainfall in North China. （2） The Indian low usually dominantly impacts the intensity of the ISM. When the Indian low deepens, the low troughs in mid-high latitudes are frequently strengthened, and the ridge of the western Pacific subtropical high （WPSH） extends westward. The southwesterly water vapor transport originated from low-latitudes and the southeasterly water vapor transport along the southwestern flank of the WPSH converge in North China, which is favorable for more rainfall there than normal, and vice versa. （3） The simulations from the regional climate model developed by National Climate Center （ReGCM_NCC） capture the salient feature of the precipitation teleconnection between India and North China. The simulated anomalous atmospheric existence of such a teleconnection from another circulations are close to observations, which confirms the angle.展开更多
基金provided by the United States Agency for International Development under grant number 3FS-G-11-00002 to the Center for International Forestry Research,entitled the Nyimba Forest Projectprovided by The University of British Columbia
文摘Background：Information on above-ground biomass（AGB） is important for managing forest resource use at local levels,land management planning at regional levels,and carbon emissions reporting at national and international levels.In many tropical developing countries,this information may be unreliable or at a scale too coarse for use at local levels.There is a vital need to provide estimates of AGB with quantifiable uncertainty that can facilitate land use management and policy development improvements.Model-based methods provide an efficient framework to estimate AGB.Methods：Using National Forest Inventory（NFI） data for a^1,000,000 ha study area in the miombo ecoregion,Zambia,we estimated AGB using predicted canopy cover,environmental data,disturbance data,and Landsat 8 OLI satellite imagery.We assessed different combinations of these datasets using three models,a semiparametric generalized additive model（GAM） and two nonlinear models（sigmoidal and exponential）,employing a genetic algorithm for variable selection that minimized root mean square prediction error（RMSPE）,calculated through cross-validation.We compared model fit statistics to a null model as a baseline estimation method.Using bootstrap resampling methods,we calculated 95% confidence intervals for each model and compared results to a simple estimate of mean AGB from the NFI ground plot data.Results：Canopy cover,soil moisture,and vegetation indices were consistently selected as predictor variables.The sigmoidal model and the GAM performed similarly;for both models the RMSPE was -36.8 tonnes per hectare（i.e.,57% of the mean）.However,the sigmoidal model was approximately 30% more efficient than the GAM,assessed using bootstrapped variance estimates relative to a null model.After selecting the sigmoidal model,we estimated total AGB for the study area at 64,526,209 tonnes（＋/- 477,730）,with a confidence interval 20 times more precise than a simple designbased estimate.Conclusions：Our findings demonstrate that NFI data may be combined with freely available satellite imagery and soils data to estimate total AGB with quantifiable uncertainty,while also providing spatially explicit AGB maps useful for management,planning,and reporting purposes.
基金Supported by the National Plan on Key Basic Research and Development (2006CB403604).
文摘In the early 1980s, Chinese meteorologists discovered the positive correlation in summer rainfall between India and North China and the correlation was later confirmed by some researches in and outside China. Based on a variety of meteorological data from 1951 to 2005 and numerical simulations, the present study investigates such a correlation between Indian summer monsoon （ISM） and precipitation in North China. Furthermore, we discuss the intrinsic relations of the positive （Northwest India）-negative （the Tibetan Plateau）-positive （North China） precipitation anomaly teleconnection pattern from two aspects of thermal and dynamical factors, which not only confirms the precipitation teleconnection previously discovered again, but also reveals the influence mechanism of the ISM on the rainfall in North China. The results show that： （1） When the ISM is strong （weak）, the precipitation in North China tends to be more （less） than normal; however, when the rainfall in North China is more （less） than normal, the probability of the strengthening （weakening） of the ISM is relatively lower. This implies that the ISM anomaly has more impact on the rainfall in North China. （2） The Indian low usually dominantly impacts the intensity of the ISM. When the Indian low deepens, the low troughs in mid-high latitudes are frequently strengthened, and the ridge of the western Pacific subtropical high （WPSH） extends westward. The southwesterly water vapor transport originated from low-latitudes and the southeasterly water vapor transport along the southwestern flank of the WPSH converge in North China, which is favorable for more rainfall there than normal, and vice versa. （3） The simulations from the regional climate model developed by National Climate Center （ReGCM_NCC） capture the salient feature of the precipitation teleconnection between India and North China. The simulated anomalous atmospheric existence of such a teleconnection from another circulations are close to observations, which confirms the angle.
