Subcanopy tree species are an important component of temperate secondary forests.However,their biomass equations are rarely reported,which forms a“vertical gap”between canopy tree species and understory shrub specie...Subcanopy tree species are an important component of temperate secondary forests.However,their biomass equations are rarely reported,which forms a“vertical gap”between canopy tree species and understory shrub species.In this study,we destructively sampled six common subcanopy species(Syringa reticulate var.amurensis(Rupr.)Pringle,Padus racemosa(Lam.)Gilib.,Acer ginnala Maxim.,Malus baccata(Linn.)Borkh.,Rhamnus davurica Pall.,and Maackia amurensis Rupr.et Maxim.)to establish biomass equations in a temperate forest of Northeast China.The mixed-species and species-specifi c biomass allometric equations were well fi tted against diameter at breast height(DBH).Adding tree height(H)as the second predictor increased the R^(2)of the models compared with the DBH-only models by–1%to+3%.The R^(2)of DBH-only and DBH-H equations for the total biomass of mixed-species were 0.985 and 0.986,respectively.On average,the biomass allocation proportions for the six species were in the order of stem(45.5%)>branch(30.1%)>belowground(19.5%)>foliage(4.9%),with a mean root:shoot ratio of 0.24.Biomass allocation to each specifi c component diff ered among species,which aff ected the performance of the mixed-species model for particular biomass component.When estimating the biomass of subcanopy species using the equations for canopy species(e.g.,Betula platyphylla Suk.,Ulmus davidiana var.japonica(Rehd.)Nakai,and Acer mono Maxim.),the errors in individual biomass estimation increased with tree size(up to 68.8%at 30 cm DBH),and the errors in stand biomass estimation(up to 19.2%)increased with increasing percentage of basal area shared by subcanopy species.The errors caused by selecting such inappropriate models could be removed by multiplying adjustment factors,which were usually power functions of DBH for biomass components.These results provide methodological support for accurate biomass estimation in temperate China and useful guidelines for biomass estimation for subcanopy species in other regions,which can help to improve estimates of forest biomass and carbon stocks.展开更多
Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrolo...Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.展开更多
基金supported by the National Key Research and Development Program(2021YFD220040105)National Natural Science Foundation of China(32171765).
文摘Subcanopy tree species are an important component of temperate secondary forests.However,their biomass equations are rarely reported,which forms a“vertical gap”between canopy tree species and understory shrub species.In this study,we destructively sampled six common subcanopy species(Syringa reticulate var.amurensis(Rupr.)Pringle,Padus racemosa(Lam.)Gilib.,Acer ginnala Maxim.,Malus baccata(Linn.)Borkh.,Rhamnus davurica Pall.,and Maackia amurensis Rupr.et Maxim.)to establish biomass equations in a temperate forest of Northeast China.The mixed-species and species-specifi c biomass allometric equations were well fi tted against diameter at breast height(DBH).Adding tree height(H)as the second predictor increased the R^(2)of the models compared with the DBH-only models by–1%to+3%.The R^(2)of DBH-only and DBH-H equations for the total biomass of mixed-species were 0.985 and 0.986,respectively.On average,the biomass allocation proportions for the six species were in the order of stem(45.5%)>branch(30.1%)>belowground(19.5%)>foliage(4.9%),with a mean root:shoot ratio of 0.24.Biomass allocation to each specifi c component diff ered among species,which aff ected the performance of the mixed-species model for particular biomass component.When estimating the biomass of subcanopy species using the equations for canopy species(e.g.,Betula platyphylla Suk.,Ulmus davidiana var.japonica(Rehd.)Nakai,and Acer mono Maxim.),the errors in individual biomass estimation increased with tree size(up to 68.8%at 30 cm DBH),and the errors in stand biomass estimation(up to 19.2%)increased with increasing percentage of basal area shared by subcanopy species.The errors caused by selecting such inappropriate models could be removed by multiplying adjustment factors,which were usually power functions of DBH for biomass components.These results provide methodological support for accurate biomass estimation in temperate China and useful guidelines for biomass estimation for subcanopy species in other regions,which can help to improve estimates of forest biomass and carbon stocks.
基金Under the auspices of National High Technology Research and Development Program of China (No. 2007AA12Z176)National Natural Science Foundation of China (No. 40771170)Natural Science Foundation of Beijing (No. 8082010)
文摘Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.
