The net primary production （NPP） of grasslands in northeastern Asia was estimated using improved CASA model with MODIS data distributed from 2000 and ground data as driving variables from 2000 to 2005. Average annua...The net primary production （NPP） of grasslands in northeastern Asia was estimated using improved CASA model with MODIS data distributed from 2000 and ground data as driving variables from 2000 to 2005. Average annual NPP was 146.05 g C m^-2 yr^-1 and average annual total NPP was 0.32 Pg C yr^-1 in all grasslands during the period. It was shown that average annual grassland NPP in the whole northeastern Asia changed dramatically from 2000 to 2005, with the highest value of 174.80 g C m^-2 yr^-1 in 2005 and the lowest value of 125.65 g C m^-2 yr^-1 in 2001. On regional scale, average annual grassland NPP of 179.71 g C m^-2 yr^-1 in southeastern Russia was the highest among the three main grassland regions in the six years. Grasslands in northern China exhibited the highest average annual total NPP of 0.16 Pg C yr^-1 and contributed 51.42% of the average annual total grassland NPP in northeastern Asia. Grassland NPP in northeastern Asia also showed a clear seasonal pattern with the highest NPP occurred in July every year. Average monthly grassland NPP in southeastern Russia was the highest from May to August while average monthly grassland NPP in northern China showed the highest NPP before May and after August. The change rate distribution of grassland NPP between the former three years and the latter three years showed grassland NPP changed slightly between the two stages in most regions, and that NPP change rate in 80.98% of northeastern Asia grasslands was between -0.2 and 0.2. Grassland NPP had close correlation with precipitation and temperature, that indicates climate change will influence the grassland NPP and thus have a great impact on domestic livestock in this region in future.展开更多
Kobresia pygmaea Willd.dominates the alpine meadow ecosystem on the Qinghai-Tibet Plateau.Knowledge of this species＇ distribution and ecological environment could provide valuable insights into the alpine ecosystem a...Kobresia pygmaea Willd.dominates the alpine meadow ecosystem on the Qinghai-Tibet Plateau.Knowledge of this species＇ distribution and ecological environment could provide valuable insights into the alpine ecosystem and key species living there,support species and ecosystem conservation in alpine regions,and build on species origin and evolutionary research.To avoid modelling uncertainty encountered in a single approach,four species distribution model algorithms（Surface Range Envelope（SRE）,Generalized Linear Model（GLM）,Generalized Boosted Regression（GBM） and Maximum Entropy（MAXENT））,were used to simulate the distribution of K.pygmaea based on occurrence samples that were verified using DNA sequencing techniques.Species distribution modelling revealed a vast distribution region of K.pygmaea in the northern Tibetan Highlands and alpine meadows in the southern and eastern declivity of the plateau.A high evaluation performance was found for the GLM,GBM and MAXENT models.Different potential range size patterns for the four models were found between 374340–482605 km^2（average = 421591 km^2）.Precipitation during growing seasons was found to be the dominant factor accounting for the distribution,consistent with patterns of heat and water patterns conditions of alpine ecosystems on the plateau.Species distribution models provide a simple and reliable approach to simulating the spatial patterns of species inhabiting the Qinghai-Tibet Plateau.展开更多
Ecosystems can simultaneously provide multiple functions and services. Knowledge on the combinations of such multi-dimensional functions is critical for accurately assessing the carrying capacity and implementing sust...Ecosystems can simultaneously provide multiple functions and services. Knowledge on the combinations of such multi-dimensional functions is critical for accurately assessing the carrying capacity and implementing sustainable management. However, accurately quantify the multifunctionality of ecosystems remains challenging due to the dependence and close association among individual functions. Here, we quantified spatial patterns in the multifunctionality of alpine grassland on the Tibetan Plateau by integrating four important individual functions based on data collected from a field survey and remote sensing NDVI. After mapping the spatial pattern of multifunctionality, we extracted multifunctionality values across four types of grassland along the northern Tibet Plateau transect. Effects of climate and grazing intensity on the multifunctionality were differentiated. Our results showed that the highest values of multifunctionality occurred in the alpine meadow. Low values of multifunctionality were comparable in different types of grassland. Annual precipitation explained the large variation of multifunctionality across the different types of grassland in the transect, which showed a significantly positive effect on the multifunctionality. Grazing intensity further explained the rest of the variation in the multifunctionality(residuals), which showed a shift from neutral or positive to negative effects on multifunctionality across the different types of grassland. The consistently rapid declines of belowground biomass, SOC, and species richness resulted in the collapse of the multifunctionality as bare ground cover amounted to 75%, which corresponded to a multifunctionality value of 0.233. Our results are the first to show the spatial pattern of grassland multifunctionality. The rapid decline of the multifunctionality suggests that a collapse in the multifunctionality can occur after the vegetation cover decreases to 25%, which is also accompanied by rapid losses of species and other individual functions. Our results are expected to provide evidence and direction for the sustainable development of alpine grassland and restoration management.展开更多
基金Basic Research Project of the Ministry of Science and Technology,No.2007FY110300National Basic Research Program of China,No.2005CB724801
文摘The net primary production （NPP） of grasslands in northeastern Asia was estimated using improved CASA model with MODIS data distributed from 2000 and ground data as driving variables from 2000 to 2005. Average annual NPP was 146.05 g C m^-2 yr^-1 and average annual total NPP was 0.32 Pg C yr^-1 in all grasslands during the period. It was shown that average annual grassland NPP in the whole northeastern Asia changed dramatically from 2000 to 2005, with the highest value of 174.80 g C m^-2 yr^-1 in 2005 and the lowest value of 125.65 g C m^-2 yr^-1 in 2001. On regional scale, average annual grassland NPP of 179.71 g C m^-2 yr^-1 in southeastern Russia was the highest among the three main grassland regions in the six years. Grasslands in northern China exhibited the highest average annual total NPP of 0.16 Pg C yr^-1 and contributed 51.42% of the average annual total grassland NPP in northeastern Asia. Grassland NPP in northeastern Asia also showed a clear seasonal pattern with the highest NPP occurred in July every year. Average monthly grassland NPP in southeastern Russia was the highest from May to August while average monthly grassland NPP in northern China showed the highest NPP before May and after August. The change rate distribution of grassland NPP between the former three years and the latter three years showed grassland NPP changed slightly between the two stages in most regions, and that NPP change rate in 80.98% of northeastern Asia grasslands was between -0.2 and 0.2. Grassland NPP had close correlation with precipitation and temperature, that indicates climate change will influence the grassland NPP and thus have a great impact on domestic livestock in this region in future.
基金National Natural Science Foundation of China(4140106831270503)National Development Project on Key Basic Research(2005CB422000)
文摘Kobresia pygmaea Willd.dominates the alpine meadow ecosystem on the Qinghai-Tibet Plateau.Knowledge of this species＇ distribution and ecological environment could provide valuable insights into the alpine ecosystem and key species living there,support species and ecosystem conservation in alpine regions,and build on species origin and evolutionary research.To avoid modelling uncertainty encountered in a single approach,four species distribution model algorithms（Surface Range Envelope（SRE）,Generalized Linear Model（GLM）,Generalized Boosted Regression（GBM） and Maximum Entropy（MAXENT））,were used to simulate the distribution of K.pygmaea based on occurrence samples that were verified using DNA sequencing techniques.Species distribution modelling revealed a vast distribution region of K.pygmaea in the northern Tibetan Highlands and alpine meadows in the southern and eastern declivity of the plateau.A high evaluation performance was found for the GLM,GBM and MAXENT models.Different potential range size patterns for the four models were found between 374340–482605 km^2（average = 421591 km^2）.Precipitation during growing seasons was found to be the dominant factor accounting for the distribution,consistent with patterns of heat and water patterns conditions of alpine ecosystems on the plateau.Species distribution models provide a simple and reliable approach to simulating the spatial patterns of species inhabiting the Qinghai-Tibet Plateau.
基金The National Key Research and Development Program(2016YFC0502001)The Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(2019QZKK0302)The National Natural Science Foundation of China(41671263)。
文摘Ecosystems can simultaneously provide multiple functions and services. Knowledge on the combinations of such multi-dimensional functions is critical for accurately assessing the carrying capacity and implementing sustainable management. However, accurately quantify the multifunctionality of ecosystems remains challenging due to the dependence and close association among individual functions. Here, we quantified spatial patterns in the multifunctionality of alpine grassland on the Tibetan Plateau by integrating four important individual functions based on data collected from a field survey and remote sensing NDVI. After mapping the spatial pattern of multifunctionality, we extracted multifunctionality values across four types of grassland along the northern Tibet Plateau transect. Effects of climate and grazing intensity on the multifunctionality were differentiated. Our results showed that the highest values of multifunctionality occurred in the alpine meadow. Low values of multifunctionality were comparable in different types of grassland. Annual precipitation explained the large variation of multifunctionality across the different types of grassland in the transect, which showed a significantly positive effect on the multifunctionality. Grazing intensity further explained the rest of the variation in the multifunctionality(residuals), which showed a shift from neutral or positive to negative effects on multifunctionality across the different types of grassland. The consistently rapid declines of belowground biomass, SOC, and species richness resulted in the collapse of the multifunctionality as bare ground cover amounted to 75%, which corresponded to a multifunctionality value of 0.233. Our results are the first to show the spatial pattern of grassland multifunctionality. The rapid decline of the multifunctionality suggests that a collapse in the multifunctionality can occur after the vegetation cover decreases to 25%, which is also accompanied by rapid losses of species and other individual functions. Our results are expected to provide evidence and direction for the sustainable development of alpine grassland and restoration management.
