Based on the Terrestrial Ecosystem Model(TEM 5.0), together with the data of climate(temperature, precipitation and solar radiation) and environment(grassland vegetation types, soil texture, altitude, longitude and la...Based on the Terrestrial Ecosystem Model(TEM 5.0), together with the data of climate(temperature, precipitation and solar radiation) and environment(grassland vegetation types, soil texture, altitude, longitude and latitude, and atmospheric CO2 concentration data), the spatiotemporal variations of carbon storage and density, and their controlling factors were discussed in this paper. The results indicated that:(1) the total carbon storage of China's grasslands with a total area of 394.93×104 km2 was 59.47 Pg C. Among them, there were 3.15 Pg C in vegetation and 56.32 Pg C in soil carbon. China's grasslands covering 7.0–11.3% of the total world's grassland area had 1.3–11.3% of the vegetation carbon and 9.7–22.5% of the soil carbon in the world grasslands. The total carbon storage increased from 59.13 to 60.16 Pg C during 1961–2013 with an increasing rate of 19.4 Tg C yr^(-1).(2) The grasslands in the Qinghai-Tibetan Plateau contributed most to the total carbon storage during 1961–2013, accounting for 63.2% of the total grassland carbon storage, followed by Xinjiang grasslands(15.8%) and Inner Mongolia grasslands(11.1%).(3) The vegetation carbon storage showed an increasing trend, with the average annual growth rate of 9.62 Tg C yr^(-1) during 1961–2013, and temperature was the main determinant factor, explaining approximately 85% of its variation. The vegetation carbon storage showed an increasing trend in most grassland regions, however, a decreasing trend in the central grassland in the southern China, the western and central parts of the Inner Mongolian grasslands as well as some parts on the Qinghai-Tibetan Plateau. The soil carbon storage showed a significantly increasing trend with a rate of 7.96 Tg C yr^(-1), which resulted from the interaction of more precipitation and low temperature in the 1980 s and 1990 s. Among them, precipitation was the main determinant factor of increasing soil carbon increases of China's grasslands.展开更多
Using the fuzzy rule-based classification method, normalized difference vegetation index (NDVI) images acquired from 1982 to 1998 were classified into seventeen phases. Based on these classification images, a probabil...Using the fuzzy rule-based classification method, normalized difference vegetation index (NDVI) images acquired from 1982 to 1998 were classified into seventeen phases. Based on these classification images, a probabilistic cellular automata-Markov Chain model was developed and used to simulate a land cover scenario of China for the year 2014. Spatiotemporal dynamics of land use/cover in China from 1982 to 2014 were then analyzed and evaluated. The results showed that the change trends of land cover type from 1998 to 2014 would be contrary to those from 1982 to 1998. In particular, forestland and grassland areas decreased by 1.56% and 1.46%, respectively, from 1982 to 1998, and should increase by 1.5% and 2.3% from 1998 to 2014, respectively.展开更多
Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions(ESFs) are the basis of constructing an ecological prote...Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions(ESFs) are the basis of constructing an ecological protection pattern of territorial space, which has important theoretical significance and application value. At present, most research on the identification, functional partitioning and pattern reconstruction of ecological space refers to the current ESFs and their structural information, which ignores the spatial-temporal dynamic nature of the comprehensive and dominant ESFs, and does not seriously consider the change simulation in the dominant ESFs of the future ecological space. This affects the rationality of constructing an ecological space protection pattern to some extent. In this study, we propose an ecological space delimitation method based on the dynamic change characteristics of the ESFs, realize the identification of the ecological space range in Qionglai City and solve the problem of ignoring the spatial-temporal changes of ESFs in current research. On this basis, we also apply the Markov-CA model to integrate the spatial-temporal change characteristics of the dominant ESFs, successfully realize the simulation of the spatial-temporal changes in the dominant ESFs in Qionglai City’s ecological space in 2025, find a suitable method for simulating ecological spatial-temporal changes and also provide a basis for constructing a reasonable ecological space protection pattern. This study finds that the comprehensive quantity of ESF and its annual rate of change in Qionglai City show obvious dynamics, which confirms the necessity of considering the dynamic characteristics of ESFs when identifying ecological space. The areas of ecological space in Qionglai city represent 98307 ha by using the ecological space identification method proposed in this study, which is consistent with the ecological spatial distribution in the local ecological civilization construction plan. This confirms the reliability of the ecological space identification method based on the dynamic characteristics of the ESFs. The results also show that the dominant ESFs in Qionglai City represented strong non-stationary characteristics during 2003–2019,which showed that we should fully consider the influence of the dynamics in the dominant ESFs on the future ESF pattern during the process of constructing the ecological spatial protection pattern. The Markov-CA model realized the simulation of spatial-temporal changes in the dominant ESFs with a high precision Kappa coefficient of above 0.95, which illustrated the feasibility of using this model to simulate the future dominant ESF spatial pattern. The simulation results showed that the dominant ESFs in Qionglai will still undergo mutual conversions during 2019–2025 due to the effect of the their non-stationary nature. The ecological space will still maintain the three dominant ESFs of primary product production, climate regulation and hydrological regulation in 2025, but their areas will change to 32793 ha, 52490 ha and 13024 ha, respectively. This study can serve as a scientific reference for the delimitation of the ecological conservation redline, ecological function regionalization and the construction of an ecological spatial protection pattern.展开更多
基金supported by the Strategic Priority Research Program–Climate Change:Carbon Budget and Related Issues of the Chinese Academy of Sciences(Grant No.XDA-05050408)
文摘Based on the Terrestrial Ecosystem Model(TEM 5.0), together with the data of climate(temperature, precipitation and solar radiation) and environment(grassland vegetation types, soil texture, altitude, longitude and latitude, and atmospheric CO2 concentration data), the spatiotemporal variations of carbon storage and density, and their controlling factors were discussed in this paper. The results indicated that:(1) the total carbon storage of China's grasslands with a total area of 394.93×104 km2 was 59.47 Pg C. Among them, there were 3.15 Pg C in vegetation and 56.32 Pg C in soil carbon. China's grasslands covering 7.0–11.3% of the total world's grassland area had 1.3–11.3% of the vegetation carbon and 9.7–22.5% of the soil carbon in the world grasslands. The total carbon storage increased from 59.13 to 60.16 Pg C during 1961–2013 with an increasing rate of 19.4 Tg C yr^(-1).(2) The grasslands in the Qinghai-Tibetan Plateau contributed most to the total carbon storage during 1961–2013, accounting for 63.2% of the total grassland carbon storage, followed by Xinjiang grasslands(15.8%) and Inner Mongolia grasslands(11.1%).(3) The vegetation carbon storage showed an increasing trend, with the average annual growth rate of 9.62 Tg C yr^(-1) during 1961–2013, and temperature was the main determinant factor, explaining approximately 85% of its variation. The vegetation carbon storage showed an increasing trend in most grassland regions, however, a decreasing trend in the central grassland in the southern China, the western and central parts of the Inner Mongolian grasslands as well as some parts on the Qinghai-Tibetan Plateau. The soil carbon storage showed a significantly increasing trend with a rate of 7.96 Tg C yr^(-1), which resulted from the interaction of more precipitation and low temperature in the 1980 s and 1990 s. Among them, precipitation was the main determinant factor of increasing soil carbon increases of China's grasslands.
基金Supported by the National Natural Science Foundation of China(No.30730021)the Applied Basic Research Programs of Yunnan Province,China(Nos.2011FZ140 and 2010CD047)
文摘Using the fuzzy rule-based classification method, normalized difference vegetation index (NDVI) images acquired from 1982 to 1998 were classified into seventeen phases. Based on these classification images, a probabilistic cellular automata-Markov Chain model was developed and used to simulate a land cover scenario of China for the year 2014. Spatiotemporal dynamics of land use/cover in China from 1982 to 2014 were then analyzed and evaluated. The results showed that the change trends of land cover type from 1998 to 2014 would be contrary to those from 1982 to 1998. In particular, forestland and grassland areas decreased by 1.56% and 1.46%, respectively, from 1982 to 1998, and should increase by 1.5% and 2.3% from 1998 to 2014, respectively.
基金The Sichuan Science and Technology Program (2020YFS0335, 2021YFH0121)The National College Students’ Innovative Entrepreneurial Training Plan Program of Sichuan Agricultural University (202110626038)The Double Support Program Project of Discipline Construction of Sichuan Agricultural University of China (2018, 2019, 2020)。
文摘Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions(ESFs) are the basis of constructing an ecological protection pattern of territorial space, which has important theoretical significance and application value. At present, most research on the identification, functional partitioning and pattern reconstruction of ecological space refers to the current ESFs and their structural information, which ignores the spatial-temporal dynamic nature of the comprehensive and dominant ESFs, and does not seriously consider the change simulation in the dominant ESFs of the future ecological space. This affects the rationality of constructing an ecological space protection pattern to some extent. In this study, we propose an ecological space delimitation method based on the dynamic change characteristics of the ESFs, realize the identification of the ecological space range in Qionglai City and solve the problem of ignoring the spatial-temporal changes of ESFs in current research. On this basis, we also apply the Markov-CA model to integrate the spatial-temporal change characteristics of the dominant ESFs, successfully realize the simulation of the spatial-temporal changes in the dominant ESFs in Qionglai City’s ecological space in 2025, find a suitable method for simulating ecological spatial-temporal changes and also provide a basis for constructing a reasonable ecological space protection pattern. This study finds that the comprehensive quantity of ESF and its annual rate of change in Qionglai City show obvious dynamics, which confirms the necessity of considering the dynamic characteristics of ESFs when identifying ecological space. The areas of ecological space in Qionglai city represent 98307 ha by using the ecological space identification method proposed in this study, which is consistent with the ecological spatial distribution in the local ecological civilization construction plan. This confirms the reliability of the ecological space identification method based on the dynamic characteristics of the ESFs. The results also show that the dominant ESFs in Qionglai City represented strong non-stationary characteristics during 2003–2019,which showed that we should fully consider the influence of the dynamics in the dominant ESFs on the future ESF pattern during the process of constructing the ecological spatial protection pattern. The Markov-CA model realized the simulation of spatial-temporal changes in the dominant ESFs with a high precision Kappa coefficient of above 0.95, which illustrated the feasibility of using this model to simulate the future dominant ESF spatial pattern. The simulation results showed that the dominant ESFs in Qionglai will still undergo mutual conversions during 2019–2025 due to the effect of the their non-stationary nature. The ecological space will still maintain the three dominant ESFs of primary product production, climate regulation and hydrological regulation in 2025, but their areas will change to 32793 ha, 52490 ha and 13024 ha, respectively. This study can serve as a scientific reference for the delimitation of the ecological conservation redline, ecological function regionalization and the construction of an ecological spatial protection pattern.
