ecosystem respiration
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2022 ◽  
Vol 314 ◽  
pp. 108807
Author(s):  
Xiuping Liu ◽  
Wenxu Dong ◽  
Jeffrey D. Wood ◽  
Yuying Wang ◽  
Xiaoxin Li ◽  
...  

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Marta Magnani ◽  
Ilaria Baneschi ◽  
Mariasilvia Giamberini ◽  
Brunella Raco ◽  
Antonello Provenzale

AbstractHigh-Arctic ecosystems are strongly affected by climate change, and it is still unclear whether they will become a carbon source or sink in the next few decades. In turn, such knowledge gaps on the drivers and the processes controlling CO2 fluxes and storage make future projections of the Arctic carbon budget a challenging goal. During summer 2019, we extensively measured CO2 fluxes at the soil–vegetation–atmosphere interface, together with basic meteoclimatic variables and ecological characteristics in the Bayelva river basin near Ny Ålesund, Spitzbergen, Svalbard (NO). By means of multi-regression models, we identified the main small-scale drivers of CO2 emission (Ecosystem Respiration, ER), and uptake (Gross Primary Production, GPP) in this tundra biome, showing that (i) at point scale, the temporal variability of fluxes is controlled by the classical drivers, i.e. air temperature and solar irradiance respectively for ER and GPP, (ii) at site scale, the heterogeneity of fractional vegetation cover, soil moisture and vegetation type acted as additional source of variability for both CO2 emissions and uptake. The assessment of the relative importance of such drivers in the multi-regression model contributes to a better understanding of the terrestrial carbon dioxide exchanges and of Critical Zone processes in the Arctic tundra.


Land ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 87
Author(s):  
Huimin Zou ◽  
Jiquan Chen ◽  
Changliang Shao ◽  
Gang Dong ◽  
Meihui Duan ◽  
...  

Selecting an appropriate model for simulating ecosystem respiration is critical in modeling the carbon cycle of terrestrial ecosystems due to their magnitude and high variations in time and space. There is no consensus on the ideal model for estimating ecosystem respiration in different ecosystems. We evaluated the performances of six respiration models, including Arrhenius, logistic, Gamma, Martin, Concilio, and time series model, against measured ecosystem respiration during 2014–2018 in four grassland ecosystems on the Mongolian Plateau: shrubland, dry steppe, temperate steppe, and meadow ecosystems. Ecosystem respiration increased exponentially with soil temperature within an apparent threshold of ~19.62 °C at shrubland, ~16.05 °C at dry steppe, ~16.92 °C at temperate steppe, and ~15.03 °C at meadow. The six models explained approximately 50–80% of the variabilities of ecosystem respiration during the study period. Both soil temperature and soil moisture played considerable roles in simulating ecosystem respiration with R square, ranging from 0.5 to 0.8. The Martin model performed better than the other models, with a relatively high R square, i.e., R2 = 0.68 at shrubland, R2 = 0.57 at dry steppe, R2 = 0.74 at temperate steppe, and R2 = 0.81 at meadow. These models achieved good performance for around 50–80% of the simulations. No single model performs best for all four grassland types, while each model appears suitable for at least one type of ecosystem. Models that oil moisture include models, especially the Martin model, are more suitable for the accurate prediction of ecosystem respiration than Ts-only models for the four grassland ecosystems.


2022 ◽  
Vol 312 ◽  
pp. 108709
Author(s):  
Nan Li ◽  
Junjiong Shao ◽  
Guiyao Zhou ◽  
Lingyan Zhou ◽  
Zhenggang Du ◽  
...  

2022 ◽  
Vol 312 ◽  
pp. 108721
Author(s):  
Xiaowen Song ◽  
Qian Chen ◽  
Kexin Wang ◽  
Xianjin Zhu ◽  
Tao Zhang ◽  
...  

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 44
Author(s):  
Yue Li ◽  
Zhongmei Wan ◽  
Li Sun

Climate change is accelerating its impact on northern ecosystems. Northern peatlands store a considerable amount of C, but their response to climate change remains highly uncertain. In order to explore the feedback of a peatland in the Great Hing’an Mountains to future climate change, we simulated the response of the overall net ecosystem exchange (NEE), ecosystem respiration (ER), and gross primary production (GPP) during 2020–2100 under three representative concentration pathways (RCP2.6, RCP6.0, and RCP8.5). Under the RCP2.6 and RCP6.0 scenarios, the carbon sink will increase slightly until 2100. Under the RCP8.5 scenario, the carbon sink will follow a trend of gradual decrease after 2053. These results show that when meteorological factors, especially temperature, reach a certain degree, the carbon source/sink of the peatland ecosystem will be converted. In general, although the peatland will remain a carbon sink until the end of the 21st century, carbon sinks will decrease under the influence of climate change. Our results indicate that in the case of future climate warming, with the growing seasons experiencing overall dryer and warmer environments and changes in vegetation communities, peatland NEE, ER, and GPP will increase and lead to the increase in ecosystem carbon accumulation.


2021 ◽  
Author(s):  
Chinmaya Kumar Swain ◽  
Amaresh Kumar Nayak ◽  
Dibyendu Chatterjee ◽  
Suchismita Pattanaik ◽  
Pratap Bhattacharyya ◽  
...  

Abstract Consecutive five-year long eddy covariance measurements in a lowland tropical rice-rice system were used to investigate the impacts of gross primary productivity (GPP), climate drivers and ecosystem responses (i.e. ecosystem respiration, RE) on the inter-annual variability (IAV) of the net ecosystem exchange (NEE), which is directly related to the agricultural productivity and climate change. The IAV of carbon dioxide fluxes in two crop growing phases i.e. dry and wet season along with fallow period were analysed. The respiratory fluxes build up during the non-growing season were lower by net uptake in growing season. Annual cumulative value of NEE was negative (sink) in both the crop growing season. The variability of climate drivers and changes in the ecosystem responses to drivers revealed a large intra-annual as well as inter-annual variability of net ecosystem fluxes. NEE was found to be strongly correlated with GPP and RE and also with other metrological variables such as photosynthetically active radiation (PAR), precipitation, air temperature and soil temperature. The anomalies of NEE, GPP and RE were observed to be less in 2017 and 2018 which may be due to lower temperature anomalies recorded in these years. Further understanding of biological mechanisms is needed which is involved in the variation of climatological variables to improve our ability to predict future IAV of NEE.


Author(s):  
Zihao Man ◽  
Shengquan Che ◽  
Changkun Xie ◽  
Ruiyuan Jiang ◽  
Anze Liang ◽  
...  

The interactions between CO2 flux, an important component of ecosystem carbon flux, and climate change vary significantly among different ecosystems. In this research, the inter-annual variation characteristics of ecosystem respiration (RE), gross ecosystem exchange (GEE), and net ecosystem exchange (NEE) were explored in the temperate grassland (TG) of Xilinhot (2004–2010), the subtropical artificial coniferous forest (SACF) of Qianyanzhou (2003–2010), and the tropical rain forest (TRF) of Xishuangbanna (2003–2010). The main factors of climate change affecting ecosystem CO2 flux were identified by redundancy analysis, and exponential models and temperature indicators were constructed to consider the relationship between climate change and CO2 flux. Every year from 2003 to 2010, RE and GEE first increased and then decreased, and NEE showed no significant change pattern. TG was a carbon source, whereas SACF and TRF were carbon sinks. The influence of air temperature on RE and GEE was greater than that of soil temperature, but the influence of soil moisture on RE and GEE was greater than that of air moisture. Compared with moisture and photosynthetically active radiation, temperature had the greatest impact on CO2 flux and the exponential model had the best fitting effect. In TG and SACF, the average temperature was the most influential factor, and in TRF, the accumulated temperature was the most influential factor. These results provide theoretical support for mitigating and managing climate change and provide references for achieving carbon neutrality.


2021 ◽  
Author(s):  
Anders Lindroth ◽  
Norbert Pirk ◽  
Ingibjörg S. Jónsdóttir ◽  
Christian Stiegler ◽  
Leif Klemedtsson ◽  
...  

Abstract. We measured CO2 and CH4 fluxes using chambers and eddy covariance (only CO2) from a moist moss tundra in Svalbard. The average net ecosystem exchange (NEE) during the summer (June–August) was −0.40 g C m−2 day−1 or −37 g C m−2 for the whole summer. Including spring and autumn periods the NEE was reduced to −6.8 g C m−2 and the annual NEE became positive, 24.7 gC m−2 due to the losses during the winter. The CH4 flux during the summer period showed a large spatial and temporal variability. The mean value of all 214 samples was 0.000511 ± 0.000315 µmol m−2s−1 which corresponds to a growing season estimate of 0.04 to 0.16 g CH4 m−2. We find that this moss tundra emits about 94–100 g CO2-equivalents m−2 yr−1 of which CH4 is responsible for 3.5–9.3 % using GWP100 of 27.9 respectively GWP20. Air temperature, soil moisture and greenness index contributed significantly to explain the variation in ecosystem respiration (Reco) while active layer depth, soil moisture and greenness index were the variables that best explained CH4 emissions. Estimate of temperature sensitivity of Reco and gross primary productivity showed that a modest increase in air temperature of 1 degree did not significantly change the NEE during the growing season but that the annual NEE would be even more positive adding another 8.5 g C m−2 to the atmosphere. We tentatively suggest that the warming of the Arctic that has already taken place is partly responsible for the fact that the moist moss tundra now is a source of CO2 to the atmosphere.


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