scholarly journals Empirical and model-based estimates of spatial and temporal variations in net primary productivity in semi-arid grasslands of Northern China

2017 ◽  
Author(s):  
Shengwei Zhang ◽  
Rui Zhang ◽  
Tingxi Liu ◽  
Xin Song ◽  
Mark A. Adams
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Northern China ◽  
Ecosystem Model ◽  
Temporal Variations ◽  
Temperature And Precipitation ◽  
Summer Temperatures ◽  
Arid Grasslands ◽  
Annual Scale ◽  
Pixel Scale

Abstract. Spatiotemporal variations in net primary productivity (NPP) of vegetation offer insights to surface water and carbon dynamics, and are closely related to temperature and precipitation. We employed the Carnegie-Ames-Stanford Approach ecosystem model to estimate NPP of semiarid grassland in northern China between 2001 and 2013. Model estimates were strongly linearly correlated with observed values (R2 = 0.67, RMSE = 35 g C m−2 year−1). We also quantified inter-annual changes in NPP over the 13-year study period. NPP varied between 141 and 313 g C m−2 year−1, with a mean of 240 g C m−2 year−1. NPP increased from west to east each year, and mean precipitation in each county was significantly positively correlated with NPP in annually, summer and autumn. Mean precipitation was also positively correlated with NPP in spring, but the correlation was not significant. Annual and summer temperatures were mostly negatively correlated with NPP, but temperature was positively correlated with spring and autumn NPP. Spatial correlation and partial correlation analyses at the pixel scale confirmed precipitation as a major driver of NPP. Temperature was negatively correlated with NPP in 99 % of the regions at the annual scale, but after removing the effect of precipitation, temperature was positively correlated with the NPP in 77 % of the regions.

scholarly journals Impacts of 1.5 °C and 2 °C Global Warming on Net Primary Productivity and Carbon Balance in China’s Terrestrial Ecosystems

2020 ◽  
Vol 12 (7) ◽  
pp. 2849
Author(s):  
Li Yu ◽  
Fengxue Gu ◽  
Mei Huang ◽  
Bo Tao ◽  
Man Hao ◽  
...  
Keyword(s):  
Global Warming ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Climate Adaptation ◽  
Coupled Model ◽  
Terrestrial Ecosystems ◽  
Northern China ◽  
Ecosystem Model ◽  
Intercomparison Project ◽  
Potential Risks

Assessing potential impacts of 1.5 °C and 2 °C global warming and identifying the risks of further 0.5 °C warming are crucial for climate adaptation and disaster risk management. Four earth system models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and a process-based ecosystem model are used in this study to assess the impacts and potential risks of the two warming targets on the carbon cycle of China’s terrestrial ecosystems. Results show that warming generally stimulates the increase of net primary productivity (NPP) and net ecosystem productivity (NEP) under both representative concentration pathway (RCP) 4.5 and RCP8.5 scenarios. The projected increments of NPP are higher at 2 °C warming than that at 1.5 °C warming for both RCP4.5 and RCP8.5 scenarios; approximately 13% and 19% under RCP4.5, and 12.5% and 20% under RCP8.5 at 1.5 °C and 2 °C warming, respectively. However, the increasing rate of NPP was projected to decline at 2 °C warming under the RCP4.5 scenario, and the further 0.5 °C temperature rising induces the decreased NPP linear slopes in more than 81% areas of China’s ecosystems. The total NEP is projected to be increased by 53% at 1.5 °C, and by 81% at 2 °C warming. NEP was projected to increase approximately by 28% with the additional 0.5 °C warming. Furthermore, the increasing rate of NEP weakens at 2 °C warming, especially under the RCP8.5 scenario. In summary, China’s total NPP and NEP were projected to increase under both 1.5 °C and 2 °C warming scenarios, although adverse effects (i.e., the drop of NPP growth and the reduction of carbon sequestration capacity) would occur in some regions such as northern China in the process of global warming.

scholarly journals Effects of climatic factors on the net primary productivity in the source region of Yangtze River, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhe Yuan ◽  
Yongqiang Wang ◽  
Jijun Xu ◽  
Zhiguang Wu
Keyword(s):  
Climate Change ◽  
Primary Productivity ◽  
Yangtze River ◽  
Net Primary Productivity ◽  
Climatic Factors ◽  
Source Region ◽  
Primary Reason ◽  
Vegetation Types ◽  
Temperature And Precipitation ◽  
Increasing Trend

AbstractThe ecosystem of the Source Region of Yangtze River (SRYR) is highly susceptible to climate change. In this study, the spatial–temporal variation of NPP from 2000 to 2014 was analyzed, using outputs of Carnegie–Ames–Stanford Approach model. Then the correlation characteristics of NPP and climatic factors were evaluated. The results indicate that: (1) The average NPP in the SRYR is 100.0 gC/m2 from 2000 to 2014, and it shows an increasing trend from northwest to southeast. The responses of NPP to altitude varied among the regions with the altitude below 3500 m, between 3500 to 4500 m and above 4500 m, which could be attributed to the altitude associated variations of climatic factors and vegetation types; (2) The total NPP of SRYR increased by 0.18 TgC per year in the context of the warmer and wetter climate during 2000–2014. The NPP was significantly and positively correlated with annual temperature and precipitation at interannual time scales. Temperature in February, March, May and September make greater contribution to NPP than that in other months. And precipitation in July played a more crucial role in influencing NPP than that in other months; (3) Climatic factors caused the NPP to increase in most of the SRYR. Impacts of human activities were concentrated mainly in downstream region and is the primary reason for declines in NPP.

scholarly journals Simulating Spatiotemporal Dynamics of Sichuan Grassland Net Primary Productivity Using the CASA Model and In Situ Observations

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Chuanjiang Tang ◽  
Xinyu Fu ◽  
Dong Jiang ◽  
Jingying Fu ◽  
Xinyue Zhang ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Alpine Meadow ◽  
Growth Period ◽  
Temporal Variations ◽  
Light Use Efficiency ◽  
Important Indicator ◽  
Casa Model ◽  
Use Efficiency

Net primary productivity (NPP) is an important indicator for grassland resource management and sustainable development. In this paper, the NPP of Sichuan grasslands was estimated by the Carnegie-Ames-Stanford Approach (CASA) model. The results were validated with in situ data. The overall precision reached 70%; alpine meadow had the highest precision at greater than 75%, among the three types of grasslands validated. The spatial and temporal variations of Sichuan grasslands were analyzed. The absorbed photosynthetic active radiation (APAR), light use efficiency (ε), and NPP of Sichuan grasslands peaked in August, which was a vigorous growth period during 2011. High values of APAR existed in the southwest regions in altitudes from 2000 m to 4000 m. Light use efficiency (ε) varied in the different types of grasslands. The Sichuan grassland NPP was mainly distributed in the region of 3000–5000 m altitude. The NPP of alpine meadow accounted for 50% of the total NPP of Sichuan grasslands.

Net primary productivity and seasonality of temperature and precipitation are predictors of the species richness of the Damselflies in the Amazon

2019 ◽  
Vol 35 ◽  
pp. 45-53 ◽  
Author(s):  
Leandro Schlemmer Brasil ◽  
Divino Vicente Silverio ◽  
Helena Soares Ramos Cabette ◽  
Joana Darc Batista ◽  
Thiago Bernardi Vieira ◽  
...  
Keyword(s):  
Species Richness ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Temperature And Precipitation

Climate Variability in Tallgrass Prairie at Multiple Timescales: Konza Prairie Biological Station

2003 ◽  
Author(s):  
Douglas G. Goodin ◽  
Philip A. Fay
Keyword(s):  
Climate Variability ◽  
Tallgrass Prairie ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Konza Prairie ◽  
Central Plains ◽  
Atmospheric Processes ◽  
Biological Station ◽  
The North ◽  
Temperature And Precipitation

Climate is a fundamental driver of ecosystem structure and function (Prentice et al. 1992). Historically, North American grassland and forest biomes have fluctuated across the landscape in step with century- to millennialscale climate variability (Axelrod 1985; Ritchie 1986). Climate variability of at decadal scale, such as the severe drought of the 1930s in the Central Plains of North America, caused major shifts in grassland plant community composition (Weaver 1954, 1968). However, on a year-to-year basis, climate variability is more likely to affect net primary productivity (NPP; Briggs and Knapp 1995; Knapp et al. 1998; Briggs and Knapp 2001). This is especially true for grasslands, which have recently been shown to display greater variability in net primary production in response to climate variability than forest, desert, or arctic/alpine systems (Knapp and Smith 2001). Although the basic relationships among interannual variability in rainfall, temperature, and grassland NPP have been well studied (Sala et al. 1988; Knapp et al. 1998; Alward et al. 1999), the linkages to major causes of climate variability at quasi-quintennial (~5 years) or interdecadal (~10 year) timescales in the North American continental interior, such as solar activity cycles, the El Niño–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the North Pacific Index (NP), are less well understood. In this chapter, we will examine how interannual, quasi-quintennial, and interdecadal variation in annual precipitation and mean annual temperature at a tallgrass prairie site (Konza Prairie Biological Station) may be related to indexes of solar activity, ENSO, NAO, and NP, and in turn how these indexes may be related to aboveground net primary productivity (ANPP). Specifically, we present (1) period-spectrum analyses to characterize the predominant timescales of temperature and precipitation variability at Konza Prairie, (2) correlation analyses of quantitative indexes of the major atmospheric processes with Konza temperature and precipitation records, and (3) the implications of variation in major atmospheric processes for seasonal and interannual patterns of ANPP. The Konza Prairie Biological Station (KNZ), which lies in the Flint Hills (39º05' N, 96º35' W), is a 1.6-million-ha region spanning eastern Kansas from the Nebraska border to northeastern Oklahoma (figure 20.1). This region is the largest remaining tract of unbroken tallgrass prairie in North America (Samson and Knopf 1994) and falls in the more mesic eastern portion of the Central Plains grasslands.

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