title: Primary Productivity and Precipitation-Use Efficiency in Temperate Grassland in the Loess Plateau of China.
abstract: Clarifying spatial variations in aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of grasslands is critical for effective prediction of the response of terrestrial ecosystem carbon and water cycle to future climate change. Though the combination use of remote sensing products and in situ ANPP measurements, we quantified the effects of climatic [mean annual precipitation (MAP) and precipitation seasonal distribution (PSD)], biotic [leaf area index (LAI)] and abiotic [slope gradient, aspect, soil water storage (SWS) and other soil physical properties] factors on the spatial variations in ANPP and PUE across different grassland types (i.e., meadow steppe, typical steppe and desert steppe) in the Loess Plateau. Based on the study, ANPP increased exponentially with MAP for the entire temperate grassland; suggesting that PUE increased with increasing MAP. Also PSD had a significant effect on ANPP and PUE; where more even PSD favored higher ANPP and PUE. Then MAP, more than PSD, explained spatial variations in typical steppe and desert steppe. However, PSD was the dominant driving factor of spatial variations in ANPP of meadow steppe. This suggested that in terms of spatial variations in ANPP of meadow steppe, change in PSD due to climate change was more important than that in total annual precipitation. LAI explained 78% of spatial PUE in the entire Loess Plateau temperate grassland. As such, LAI was the primary driving factor of spatial variations in PUE. Although the effect of SWS on ANPP and PUE was significant, it was nonetheless less than that of precipitation and vegetation. We therefore concluded that changes in vegetation structure and consequently in LAI and/or altered pattern of seasonal distribution of rainfall due to global climate change could significantly influence ecosystem carbon and water cycle in temperate grasslands.
authors: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
authors: Xiaoxu
authors: X
authors: Jia
authors: College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China.
authors: Baoni
authors: B
authors: Xie
authors: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China.
authors: Ming'an
authors: M
authors: Shao
authors: College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China; State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China.
authors: Chunlei
authors: C
authors: Zhao
mesh_terms: D018533:Biomass; D057486:Carbon Cycle; D057231:Climate Change; D065948:Grassland; D015233:Models, Statistical; D006109:Poaceae / Q000502:physiology*; D011891:Rain; D058998:Remote Sensing Technology; D012621:Seasons; D012987:Soil / Q000737:chemistry*; D058438:Water Cycle
chemical_list: D012987:Soil