Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years

Yao, Yitong; Wang, Xuhui; Li, Yue; Wang, Tao; Shen, Miaogen; Du, Mingyuan; He, Honglin; Li, Yingnian; Luo, Weijun; Ma, Ming; Ma, Yaoming; Tang, Yanhong; Wang, Huimin; Zhang, Xianzhou; Zhang, Yiping; Zhao, Liang; Zhou, Guangsheng; Piao, Shilong

doi:10.1111/gcb.13830

Cited by 191 publications

(122 citation statements)

References 87 publications

Supporting

Mentioning

110

Contrasting

Unclassified

Order By: Relevance

“…Fortunately, several researches focus on productivity dynamics. The consistent conclusion is that the vegetation productivity of Mu Us sandy land has significant increased trends [19,66], which agree with our results based on the threshold method. Furthermore, more obvious latitude and longitude trends of the mean values of phenology via the threshold method are related to thermal and hydrological conditions.…”

Section: Uncertainty Analysissupporting

confidence: 91%

The Response of Vegetation Phenology and Productivity to Drought in Semi-Arid Regions of Northern China

2018

Self Cite

View full text Add to dashboard Cite

A major disturbance in nature, drought, has a significant impact on the vulnerability and resilience of semi-arid ecosystems by shifting phenology and productivity. However, due to the various disturbance mechanisms, phenology and primary productivity have remained largely ambiguous until now. This paper evaluated the spatio-temporal changes of phenology and productivity based on GIMMS NDVI3g time series data, and demonstrated the responses of vegetation phenology and productivity to drought disturbances with the standardized precipitation evapotranspiration index (SPEI) in semi-arid ecosystems of northern China. The results showed that (1): vegetation phenology exhibited dramatic spatial heterogeneity with different rates, mostly presented in the regions with high chances of land cover type variation. The delayed onset of growing season (SOS) and advanced end of growing season (EOS) occurred in Horqin Sandy Land and the eastern Ordos Plateau with a one to three days/decade (p < 0.05) rate and in the middle and east of Inner Mongolia with a two days/decade rate, respectively. Vegetation productivity presented a clear pattern: south increased and north decreased. (2) Spring drought delayed SOS in grassland, barren/sparsely vegetated land, and cropland, while autumn drought significantly advanced EOS in grassland and barren/sparsely vegetated lands. Annual drought reduced vegetation productivity and the sensitivity of productivity regarding drought disturbance was higher than that of phenology.

show abstract

Section: Uncertainty Analysissupporting

confidence: 91%

The Response of Vegetation Phenology and Productivity to Drought in Semi-Arid Regions of Northern China

2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…Among the selected explanatory variables, mean annual CO 2 concentration was the most highly correlated with annual GEP (Figure S6), and only CO 2 concentration exhibited a similar increasing trend to that of GEP over the 19 year observation period (Figure 1). A CO 2 -driven increasing trend in GEP is consistent with many modeling and manipulation experimental studies (Mekonnen, 2015;Norby & Zak, 2011;Yao et al, 2018). A CO 2 -driven increasing trend in GEP is consistent with many modeling and manipulation experimental studies (Mekonnen, 2015;Norby & Zak, 2011;Yao et al, 2018).…”

Section: Gross Ecosystem Productionsupporting

confidence: 80%

Divergent long‐term trends and interannual variation in ecosystem resource use efficiencies of a southern boreal old black spruce forest 1999–2017

Liu

Black

Jassal

et al. 2019

Global Change Biology

View full text Add to dashboard Cite

Long‐term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999–2017 from a 120‐year‐old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long‐term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p < 0.01), which may be attributed to rising atmospheric CO2 concentration. Interannual variability in GEP, aside from its increasing trend, was most strongly related to spring temperatures. Associated with the significant increase in annual GEP were relatively small changes in NPP, APAR, and E, so that annual CUE showed a decreasing trend and annual LUE and WUE showed increasing trends over the 19 years. The long‐term trends in the RUEs were related to the increasing CO2 concentration. Further analysis of detrended RUEs showed that their interannual variation was impacted most strongly by air temperature. Two‐factor linear models combining CO2 concentration and air temperature performed well (R2~0.60) in simulating annual RUEs. LUE and WUE were positively correlated both annually and seasonally, while LUE and CUE were mostly negatively correlated. Our results showed divergent long‐term trends among CUE, LUE, and WUE and highlighted the need to account for the combined effects of climatic controls and the ‘CO2 fertilization effect’ on long‐term variations in RUEs. Since most RUE‐based models rely primarily on one resource limitation, the observed patterns of relative change among the three RUEs may have important implications for RUE‐based modeling of C fluxes.

show abstract

“…Many previous studies have reported the overestimation of global or regional GPP by current TBMs (Peng et al, ; Xia et al, ; Yao et al, ). In the East Asian monsoon region, such model overestimation is mainly attributable to the overestimation of vegetation functional properties (especially in SLA and LAI).…”

Section: Discussionmentioning

confidence: 94%

“…A large number of studies have been conducted to assess intermodel differences and model performance on ecosystem productivity (Anav et al, ; Ito et al, ; Xia et al, ; Yao et al, ). Most of these studies have revealed a twofold to threefold difference in simulated ecosystem productivity among models.…”

Section: Introductionmentioning

confidence: 99%

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region

Cui

Huang

Arain

et al. 2019

Global Biogeochemical Cycles

View full text Add to dashboard Cite

Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe‐Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon‐use efficiency (CUE), vegetation C turnover time (τveg), leaf C fraction (Fleaf), specific leaf area (SLA), and leaf area index (LAI)‐level photosynthesis (PLAI), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901–2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 ± 21.3%), τveg (18.2 ± 26.9%), and SLA (27.4±36.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. These results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems.

show abstract

Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years

Abstract: The uncertainties of China's gross primary productivity (GPP) estimates by global data-oriented products and ecosystem models justify a development of high-resolution data-oriented GPP dataset over China. We applied a machine learning algorithm

Cited by 191 publications

References 87 publications

The Response of Vegetation Phenology and Productivity to Drought in Semi-Arid Regions of Northern China

The Response of Vegetation Phenology and Productivity to Drought in Semi-Arid Regions of Northern China

Divergent long‐term trends and interannual variation in ecosystem resource use efficiencies of a southern boreal old black spruce forest 1999–2017

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region

Contact Info

Product

Resources

About