The change of global terrestrial ecosystem net primary productivity (NPP) and its response to climate change in CMIP5

Li, Suosuo; Lü, Sihua; Zhang, Yongjun; Liu, Yuanpu; Gao, Yanhong; Ao, Yu‐Fei

doi:10.1007/s00704-014-1242-8

Cited by 21 publications

(20 citation statements)

References 33 publications

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“…The uncertainty of the HadGEM2-ES model was the largest, and the uncertainty of the MIROC5 model was the smallest. These results are consistent with those obtained by Li, Lu, Zhang, Liu, Gao, and Ao [71] and Fu et al [111]. In fact, multiple studies have found large uncertainty associated with the NPP of the global terrestrial ecosystem.…”

Section: Quantifiable Sources Of Uncertaintysupporting

confidence: 92%

“…Precipitation was found to be the second-most important factor (R > 0.017). These results are supported by those of Li et al [71] and Li et al [72], who used the Climate Model Intercomparison Project (CMIP5) multipattern to explore the response of global terrestrial NPP to climate change during the historical period from 1850-2005. However, our study also found that as emissions increased, the correlation between solar radiation and alterations in NPP content changed from positive under the low-emission scenario (RCP2.6) to negative under the high-emission scenario (RCP8.5).…”

Section: Impacts Of Climate Variations On Net Primary Productivity Insupporting

confidence: 75%

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Projection of Net Primary Productivity under Global Warming Scenarios of 1.5 °C and 2.0 °C in Northern China Sandy Areas

Huo

Zhao

et al. 2020

Atmosphere

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Empirical evidence suggests that variations in climate affect the net primary productivity (NPP) across sandy areas over time. However, little is known about the relative impacts of climate change on NPP with global warming of 1.5 and 2.0 °C (GW_1.5 °C_2.0 °C) relative to pre-industrial levels. Here, we used a new set of climate simulations from four Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP 2b) datasets, modified the Carnegie-Ames-Stanford approach (CASA) model and assessed the spatio-temporal variation in NPP in sandy areas of northern China (SAONC). Compared with the reference period (RP, 1986–2005), the NPP variation under four emission scenarios showed clear rising trends and increased most significantly under RCP8.5 with an annual average increase of 2.34 g C/m2. The estimated annual NPP under global warming of 1.5 °C (GW_1.5 °C) increased by 14.17, 10.72, 8.57, and 26.68% in different emission scenarios, and under global warming of 2.0 °C (GW_2.0 °C) it increased by 20.87, 24.01, 29.31, and 39.94%, respectively. In terms of seasonal change, the NPP value under the four emission scenarios changed most significantly in the summer relative to RP, exhibiting a growth of 16.48%. Temperature changes (p > 0.614) had a greater impact on NPP growth than precipitation (p > 0.017), but solar radiation showed a certain negative impact in the middle- and low-latitude regions. NPP showed an increasing trend that changed from the southeast to the central and western regions at GW_1.5 to GW_2.0 °C. NPP was consistent with the spatial change in climate factors and had a promoting role in high latitudes in SAONC, but it was characterized by a certain inhibitory effect at middle and low latitudes in SAONC. The uncertainty of NPP under the four models ranged from 16.29 to 26.52%. Our findings suggest that the impact of GW_1.5 °C is relatively high compared with the current conditions, whereas GW_2.0 °C implies significantly lower projected NPP growth in all areas.

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Section: Quantifiable Sources Of Uncertaintysupporting

confidence: 92%

Section: Impacts Of Climate Variations On Net Primary Productivity Insupporting

confidence: 75%

Projection of Net Primary Productivity under Global Warming Scenarios of 1.5 °C and 2.0 °C in Northern China Sandy Areas

Huo

Zhao

et al. 2020

Atmosphere

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“…Our simple models also have limitations; for example, we do not attempt to represent growth (or growth respiration) responses to temperature variation, nor do we attempt to extrapolate from leaf‐level respiration to other plant tissues or ecosystem‐level fluxes. It is expected that total global leaf area will increase under climate change (Betts et al ., ; Li et al ., ), which would increase total leaf and autotrophic respiration (as well as photosynthesis) independently from changes that occur at the leaf level. Also, our climate simulations assume that daytime and nighttime temperatures will change by the same amount, but many projections indicate that daily minimum temperatures will increase more than daily maximum temperatures (IPCC, ).…”

Section: Discussionmentioning

confidence: 99%

Global convergence in leaf respiration from estimates of thermal acclimation across time and space

et al. 2015

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SummaryRecent compilations of experimental and observational data have documented global temperature-dependent patterns of variation in leaf dark respiration (R), but it remains unclear whether local adjustments in respiration over time (through thermal acclimation) are consistent with the patterns in R found across geographical temperature gradients.We integrated results from two global empirical syntheses into a simple temperaturedependent respiration framework to compare the measured effects of respiration acclimationover-time and variation-across-space to one another, and to a null model in which acclimation is ignored. Using these models, we projected the influence of thermal acclimation on: seasonal variation in R; spatial variation in mean annual R across a global temperature gradient; and future increases in R under climate change.The measured strength of acclimation-over-time produces differences in annual R across spatial temperature gradients that agree well with global variation-across-space. Our models further project that acclimation effects could potentially halve increases in R (compared with the null model) as the climate warms over the 21st Century.Convergence in global temperature-dependent patterns of R indicates that physiological adjustments arising from thermal acclimation are capable of explaining observed variation in leaf respiration at ambient growth temperatures across the globe.

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“…Through modeling and simulation, one could reveal the quantitative changes and trends of NPP caused by climate changes. It was why the research of NPP model had attracted a vast amount of attention (Li et al 2015). This study establishes an estimation model for southern grassland NPP by using the statistical analysis results of southern grassland NPP and precipitation and temperature combined with biological process.…”

Section: Discussionmentioning

confidence: 99%

Evaluating the grassland net primary productivity of southern China from 2000 to 2011 using a new climate productivity model

Sun

Zhong

Chen

et al. 2016

Journal of Integrative Agriculture

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Grassland is the important component of the terrestrial ecosystems. Estimating net primary productivity (NPP) of grassland ecosystem has been a central focus in global climate change researches. To simulate the grassland NPP in southern China, we built a new climate productivity model, and validated the model with the measured data from different years in the past. The results showed that there was a logarithmic correlation between the grassland NPP and the mean annual temperature, and there was a linear positive correlation between the grassland NPP and the mean annual precipitation in southern China. All these results reached a very significant level (P<0.01). There was a good correlation between the simulated and the measured NPP, with R 2 of 0.8027, reaching the very significant level. Meanwhile, both RMSE and RRMSE stayed at a relatively low level, showing that the simulation results of the model were reliable. The NPP values in the study area had a decreasing trend from east to west and from south to north, and the mean NPP was 471.62 g C m −2 from 2000 to 2011. Additionally, there was a rising trend year by year for the mean annual NPP of southern grassland and the tilt rate of the mean annual NPP was 3.49 g C m −2 yr −1 in recent 12 years. The above results provided a new

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The change of global terrestrial ecosystem net primary productivity (NPP) and its response to climate change in CMIP5

Cited by 21 publications

References 33 publications

Projection of Net Primary Productivity under Global Warming Scenarios of 1.5 °C and 2.0 °C in Northern China Sandy Areas

Projection of Net Primary Productivity under Global Warming Scenarios of 1.5 °C and 2.0 °C in Northern China Sandy Areas

Global convergence in leaf respiration from estimates of thermal acclimation across time and space

Evaluating the grassland net primary productivity of southern China from 2000 to 2011 using a new climate productivity model

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