Permanent plots in the montane tropical rain forests in Xishuangbanna, southwest China, were established, and different empirical models, based on observation data of these plots in 1992, were built to model diameter ...Permanent plots in the montane tropical rain forests in Xishuangbanna, southwest China, were established, and different empirical models, based on observation data of these plots in 1992, were built to model diameter frequency distributions. The focus of this study is on predicting accuracy of stem number in the larger diameter classes, which is much more important than that of the smaller trees, from the view of forest management, and must be adequately considered in the modelling and estimate. There exist 3 traditional ways of modelling the diameter frequency distribution: the negative exponential function model, limiting line function model, and Weibull distribution model. In this study, a new model, named as the logarithmic J-shape function, together with the others, was experimented and was found as a more suitable model for modelling works in the tropical forests.展开更多
Terrestrial ecosystems play an important role in the global carbon (C)cycle. Tropical forests in Southeast Asia are constantly changing as a result of harvesting and conversion to other land cover. As a result of thes...Terrestrial ecosystems play an important role in the global carbon (C)cycle. Tropical forests in Southeast Asia are constantly changing as a result of harvesting and conversion to other land cover. As a result of these changes, research on C budgets of forest ecosystems has intensified in the region over thelast few years. This paper reviews and synthesizes the available information. Natural forests in SE Asia typically contain a high C density (up to 500 Mg/ha). Logging activities are responsible for at least 50% decline in forest C density.Complete deforestation (conversion from forest to grassland or annual crops) results in C density of less than 40 Mg/ha. Conversion to tree plantations and other woody perennial crops also reduces C density to less than 50% of the originalC forest stocks. While much information has been generated recently, there are still large gaps of information on C budgets of tropical forests and its conversion to other land uses in SE Asia. There is therefore a need to intensify research in this area.展开更多
Numerous studies have shown that intact tropical forests account for half of the total terrestrial sink for anthropogenic carbon dioxide.Here,we analyzed and compared changes in three main tropical forest regions from...Numerous studies have shown that intact tropical forests account for half of the total terrestrial sink for anthropogenic carbon dioxide.Here,we analyzed and compared changes in three main tropical forest regions from 2000 to 2014,based on time-series analysis and landscape metrics derived from moderate-resolution imaging spectroradiometer data.We examined spatialpattern changes in percentage of tree cover and net primary production(NPP)for three tropical forest regions—Amazon basin,Congo basin,and Southeast Asia.The results show that:the Amazon basin region had the largest tropical forest area and total NPP and a better continuity of TC distribution;the Southeast Asia region exhibited a sharp decrease in NPP and had comparatively separate spatial patterns of both TC and NPP;and the Congo basin region exhibited a dramatic increase in NPP and had better aggregation of forest NPP distribution.Results also show that aggregative patterns likely correlate with high NPP values.展开更多
Bitterlich sampling is an extensively used technique in worldwide forest inventories. Although it has been proved that estimates of basal area from Bitterlich sampling are mathematically unbiased, its precision for in...Bitterlich sampling is an extensively used technique in worldwide forest inventories. Although it has been proved that estimates of basal area from Bitterlich sampling are mathematically unbiased, its precision for individual forest stands may be fairly poor. An extension of validation efforts to different forest biomes could therefore provide more comprehensive assessment and understanding of the Bitterlich sampling technique. In this study, this technique was quantitatively evaluated by using simulated sparse boreal forests and dense tropical forests from an empirical forest structure model (EFSM). Theoretical estimation of basal areas and practical estimation influenced by the hidden-tree effect were both compared with true basal areas of the simulated forests. The evaluation results indicated that: 1) Bitterlich sampling can yield acceptable accuracy and precision when the count number (CN) of trees was set to 10 for the studied boreal and tropical forests with distinct characteristics, 2) the theoretical estimation of basal area can be improved by increasing the CN values for both forests, and 3) when the hidden-tree effect is encountered, the accuracy for tropical forests will be decreased by increasing the CN values, whereas the accuracy for boreal forests can still be improved. Accordingly, a relatively high CN, at a reasonable cost, is recommended for sparse boreal forests to improve the accuracy of basal area estimation. In contrast, for dense tropical forests, a CN of ten is appropriate to mitigate the hidden-tree effect.展开更多
文摘Permanent plots in the montane tropical rain forests in Xishuangbanna, southwest China, were established, and different empirical models, based on observation data of these plots in 1992, were built to model diameter frequency distributions. The focus of this study is on predicting accuracy of stem number in the larger diameter classes, which is much more important than that of the smaller trees, from the view of forest management, and must be adequately considered in the modelling and estimate. There exist 3 traditional ways of modelling the diameter frequency distribution: the negative exponential function model, limiting line function model, and Weibull distribution model. In this study, a new model, named as the logarithmic J-shape function, together with the others, was experimented and was found as a more suitable model for modelling works in the tropical forests.
基金supported by the National Natural Science Foundation of China(31930072,31770559,31600387,31370489)the Postdoctoral Innovation Talents Program of China(BX20200133)supported by a Ramón y Cajal grant from the Spanish Ministry of Science and Innovation(RYC2018-025483-I).
文摘Terrestrial ecosystems play an important role in the global carbon (C)cycle. Tropical forests in Southeast Asia are constantly changing as a result of harvesting and conversion to other land cover. As a result of these changes, research on C budgets of forest ecosystems has intensified in the region over thelast few years. This paper reviews and synthesizes the available information. Natural forests in SE Asia typically contain a high C density (up to 500 Mg/ha). Logging activities are responsible for at least 50% decline in forest C density.Complete deforestation (conversion from forest to grassland or annual crops) results in C density of less than 40 Mg/ha. Conversion to tree plantations and other woody perennial crops also reduces C density to less than 50% of the originalC forest stocks. While much information has been generated recently, there are still large gaps of information on C budgets of tropical forests and its conversion to other land uses in SE Asia. There is therefore a need to intensify research in this area.
基金supported by the National Key Research and Development Program of China(Grant No.2016YFA0600304)the International Partnership Program of Chinese Academy of Sciences(Grant No.131C11KYSB20160061)the Hainan Provincial Department of Science and Technology(Grant No.ZDKJ2016021)
文摘Numerous studies have shown that intact tropical forests account for half of the total terrestrial sink for anthropogenic carbon dioxide.Here,we analyzed and compared changes in three main tropical forest regions from 2000 to 2014,based on time-series analysis and landscape metrics derived from moderate-resolution imaging spectroradiometer data.We examined spatialpattern changes in percentage of tree cover and net primary production(NPP)for three tropical forest regions—Amazon basin,Congo basin,and Southeast Asia.The results show that:the Amazon basin region had the largest tropical forest area and total NPP and a better continuity of TC distribution;the Southeast Asia region exhibited a sharp decrease in NPP and had comparatively separate spatial patterns of both TC and NPP;and the Congo basin region exhibited a dramatic increase in NPP and had better aggregation of forest NPP distribution.Results also show that aggregative patterns likely correlate with high NPP values.
文摘Bitterlich sampling is an extensively used technique in worldwide forest inventories. Although it has been proved that estimates of basal area from Bitterlich sampling are mathematically unbiased, its precision for individual forest stands may be fairly poor. An extension of validation efforts to different forest biomes could therefore provide more comprehensive assessment and understanding of the Bitterlich sampling technique. In this study, this technique was quantitatively evaluated by using simulated sparse boreal forests and dense tropical forests from an empirical forest structure model (EFSM). Theoretical estimation of basal areas and practical estimation influenced by the hidden-tree effect were both compared with true basal areas of the simulated forests. The evaluation results indicated that: 1) Bitterlich sampling can yield acceptable accuracy and precision when the count number (CN) of trees was set to 10 for the studied boreal and tropical forests with distinct characteristics, 2) the theoretical estimation of basal area can be improved by increasing the CN values for both forests, and 3) when the hidden-tree effect is encountered, the accuracy for tropical forests will be decreased by increasing the CN values, whereas the accuracy for boreal forests can still be improved. Accordingly, a relatively high CN, at a reasonable cost, is recommended for sparse boreal forests to improve the accuracy of basal area estimation. In contrast, for dense tropical forests, a CN of ten is appropriate to mitigate the hidden-tree effect.
