Browsing by Author "Arneth, Almut"

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Land use change and El Niño-Southern Oscillation drive decadal carbon balance shifts in Southeast Asia
(2018-03) Kondo, Masayuki; Ichii, Kazuhito; Patra, Prabir K.; Canadell, Joseph G.; Poulter, Benjamin; Stitch, Stephen; Calle, Leonardo; Liu, Yi Y.; van Dijk, Albert I. J. M.; Saeki, Tazu; Saigusa, Nobuko; Friedlingstein, Pierre; Arneth, Almut; Harper, Anna B.; Jain, Atul K.; Kato, Etsushi; Koven, Charles D.; Li, Fang; Pugh, Thomas A. M.; Zaehle, Sonke; Wiltshire, Andy; Chevallier, Frederic; Maki, Takashi; Nakamura, Takashi; Niwa, Yosuke; Rödenbeck, Christian
An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.
Regional Carbon Fluxes from Land Use and Land Cover Change in Asia, 1980-2009
(2016-07) Calle, Leonardo; Canadell, Josep; Patra, Prabir K.; Ciais, Philippe; Ichii, Kazuhito; Tian, Hui; Kondo, Masayuki; Piao, Shilong; Arneth, Almut; Harper, Anna B.
We present a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia using multiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food and Agriculture Organization-Forest Resource Assessment (FAO-FRA 2015; country-level inventory estimates), the Emission Database for Global Atmospheric Research (EDGARv4.3), the 'Houghton' bookkeeping model that incorporates FAO-FRA data, an ensemble of 8 state-of-the-art Dynamic Global Vegetation Models (DGVM), and 2 recently published independent studies using primarily remote sensing techniques. The estimates are aggregated spatially to Southeast, East, and South Asia and temporally for three decades, 1980–1989, 1990–1999 and 2000–2009. Since 1980, net carbon emissions from LULCC in Asia were responsible for 20%–40% of global LULCC emissions, with emissions from Southeast Asia alone accounting for 15%–25% of global LULCC emissions during the same period. In the 2000s and for all Asia, three estimates (FAO-FRA, DGVM, Houghton) were in agreement of a net source of carbon to the atmosphere, with mean estimates ranging between 0.24 to 0.41 Pg C yr−1, whereas EDGARv4.3 suggested a net carbon sink of −0.17 Pg C yr−1. Three of 4 estimates suggest that LULCC carbon emissions declined by at least 34% in the preceding decade (1990–2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to include emissions from carbon rich peatlands and land management, such as shifting cultivation and wood harvesting, which appear to be consistently underreported.
Separation of Net Ecosystem Exchange into Assimilation and Respiration Using a Light Response Curve Approach: Critical Issues and Global Evaluation
(2010-01) Lasslop, Gitta; Reichstein, Markus; Papale, Dario; Richardson, Andrew D.; Arneth, Almut; Barr, Alan G.; Stoy, Paul C.; Wohlfahrt, Georg
The measured net ecosystem exchange (NEE) of CO2 between the ecosystem and the atmosphere reflects the balance between gross CO2 assimilation [gross primary production (GPP)] and ecosystem respiration (Reco). For understanding the mechanistic responses of ecosystem processes to environmental change it is important to separate these two flux components. Two approaches are conventionally used: (1) respiration measurements made at night are extrapolated to the daytime or (2) light–response curves are fit to daytime NEE measurements and respiration is estimated from the intercept of the ordinate, which avoids the use of potentially problematic nighttime data. We demonstrate that this approach is subject to biases if the effect of vapor pressure deficit (VPD) modifying the light response is not included. We introduce an algorithm for NEE partitioning that uses a hyperbolic light response curve fit to daytime NEE, modified to account for the temperature sensitivity of respiration and the VPD limitation of photosynthesis. Including the VPD dependency strongly improved the model's ability to reproduce the asymmetric diurnal cycle during periods with high VPD, and enhances the reliability of Reco estimates given that the reduction of GPP by VPD may be otherwise incorrectly attributed to higher Reco. Results from this improved algorithm are compared against estimates based on the conventional nighttime approach. The comparison demonstrates that the uncertainty arising from systematic errors dominates the overall uncertainty of annual sums (median absolute deviation of GPP: 47 g C m−2 yr−1), while errors arising from the random error (median absolute deviation: ∼2 g C m−2 yr−1) are negligible. Despite site‐specific differences between the methods, overall patterns remain robust, adding confidence to statistical studies based on the FLUXNET database. In particular, we show that the strong correlation between GPP and Reco is not spurious but holds true when quasi‐independent, i.e. daytime and nighttime based estimates are compared.
The terrestrial carbon budget of South and Southeast Asia
(2016-10) Cervarich, Matthew; Shu, Shijie; Jain, Atul K.; Arneth, Almut; Canadell, Josep; Friedlingstein, Pierre; Houghton, Richard A; Kato, Etsushi; Koven, Charles D.; Patra, Prabir K.; Poulter, Benjamin; Sitch, Stephen; Stocker, Benjamin D.; Viovy, Nicolas; Wiltshire, Andy; Zeng, Ning
Accomplishing the objective of the current climate policies will require establishing carbon budget and flux estimates in each region and county of the globe by comparing and reconciling multiple estimates including the observations and the results of top-down atmospheric carbon dioxide (CO2) inversions and bottom-up dynamic global vegetation models. With this in view, this study synthesizes the carbon source/sink due to net ecosystem productivity (NEP), land cover land use change (E-LUC), fires and fossil burning (E-FIRE) for the South Asia (SA), Southeast Asia (SEA) and South and Southeast Asia (SSEA = SA + SEA) and each country in these regions using the multiple top-down and bottom-up modeling results. The terrestrial net biome productivity (NBP = NEP - E-LUC - E-FIRE) calculated based on bottom-up models in combination with E-FIRE based on GFED4s data show net carbon sinks of 217 +/- 147, 10 +/- 55, and 227 +/- 279 TgC yr(-1) for SA, SEA, and SSEA. The top-down models estimated NBP net carbon sinks were 20 +/- 170, 4 +/- 90 and 24 +/- 180 TgC yr(-1). In comparison, regional emissions from the combustion of fossil fuels were 495, 275, and 770 TgC yr(-1), which are many times higher than the NBP sink estimates, suggesting that the contribution of the fossil fuel emissions to the carbon budget of SSEA results in a significant net carbon source during the 2000s. When considering both NBP and fossil fuel emissions for the individual countries within the regions, Bhutan and Laos were net carbon sinks and rest of the countries were net carbon source during the 2000s. The relative contributions of each of the fluxes (NBP, NEP, ELUC, and EFIRE, fossil fuel emissions) to a nation\'s net carbon flux varied greatly from country to country, suggesting a heterogeneous dominant carbon fluxes on the country-level throughout SSEA.
Thermal optimality of net ecosystem exchange of carbon dioxide and underlying mechanisms
(2012-03-07) Niu, Shuli; Luo, Yiqi; Fei, Shenfeng; Yuan, Wenping; Schimel, David; Law, Beverly E.; Ammann, Christof; Arain, M. Altaf; Arneth, Almut; Aubinet, Marc; Barr, Alan G.; Beringer, Jason; Bernhofer, Christian; Black, T. Andrew; Buchmann, Nina; Cescatti, Alessandro; Chen, Jiquan; Davis, Kenneth J.; Dellwik, Ebba; Desai, Ankur R.; Etzold, Sophia; Francois, Louis; Gianelle, Damiano; Gielen, Bert; Goldstein, Allen; Groenendijk, Margriet; Gu, Lianhong; Hanan, Niall; Helfter, Carole; Hirano, Takashi; Hollinger, David Y.; Jones, Mike B.; Kiely, Gerard; Kolb, Thomas E.; Kutsch, Werner L.; Lafleur, Peter; Lawrence, David M.; Li, Linghao; Lindroth, Anders; Litvak, Marcy; Loustau, Denis; Lund, Magnus; Marek, Michal; Martin, Timothy A.; Matteucci, Giorgio; Migliavacca, Mirco; Montagnani, Leonardo; Moors, Eddy; Munger, J. William; Noormets, Asko; Oechel, Walter C.; Olejnik, Janusz; Pilegaard, Kim; Paw U, Kyaw Tha; Pilegaard, Kim; Rambal, Serge; Raschi, Antonio; Scott, Russell L.; Seufert, Günther; Spano, Donatella; Stoy, Paul C.; Sutton, Mark A.; Varlagin, Andrej; Vesala, Timo; Weng, Ensheng; Wohlfahrt, Georg; Yang, Bai; Zhang, Zhongda; Zhou, Xuhui
It is well established that individual organisms can acclimate and adapt to temperature to optimize their functioning. However, thermal optimization of ecosystems, as an assemblage of organisms, has not been examined at broad spatial and temporal scales. Here, we compiled data from 169 globally distributed sites of eddy covariance and quantified the temperature response functions of net ecosystem exchange (NEE), an ecosystem-level property, to determine whether NEE shows thermal optimality and to explore the underlying mechanisms. We found that the temperature response of NEE followed a peak curve, with the optimum temperature (corresponding to the maximum magnitude of NEE) being positively correlated with annual mean temperature over years and across sites. Shifts of the optimum temperature of NEE were mostly a result of temperature acclimation of gross primary productivity (upward shift of optimum temperature) rather than changes in the temperature sensitivity of ecosystem respiration. Ecosystem-level thermal optimality is a newly revealed ecosystem property, presumably reflecting associated evolutionary adaptation of organisms within ecosystems, and has the potential to significantly regulate ecosystemclimate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.