- EC| GHG EUROPE
Niu, S.; Luo, Y.; Fei, S.; Yuan, W.; Schimel, D.; Ammann, C.; Ammann, C.
Harvested from ORCID Public Data FileAmmann, C. in OpenAIRE Arain, M. A.; Arain, M. A.
Harvested from ORCID Public Data FileArain, M. A. in OpenAIRE Arneth, A.; Aubinet, M.; Bar, A.;Arneth, A.
Harvested from ORCID Public Data FileArneth, A. in OpenAIRE Beringer, J.; Beringer, J.
Harvested from ORCID Public Data FileBeringer, J. in OpenAIRE Bernhofer, C.; Black, A. T.;Bernhofer, C.
Harvested from ORCID Public Data FileBernhofer, C. in OpenAIRE Buchmann, N.; Cescatti, A.;Buchmann, N.
Harvested from ORCID Public Data FileBuchmann, N. in OpenAIRE Chen, J.; Davis, K. J.; Davis, K. J.
Harvested from ORCID Public Data FileDavis, K. J. in OpenAIRE Dellwik, E.; Dellwik, E.
Harvested from ORCID Public Data FileDellwik, E. in OpenAIRE Desai, A. R.; Dolman, H.;Desai, A. R.
Harvested from ORCID Public Data FileDesai, A. R. in OpenAIRE Etzold, S.; Etzold, S.
Harvested from ORCID Public Data FileEtzold, S. in OpenAIRE Francois, L.; Francois, L.
Harvested from ORCID Public Data FileFrancois, L. in OpenAIRE Gianelle, Damiano; Gielen, B.;Gianelle, Damiano
Harvested from ORCID Public Data FileGianelle, Damiano in OpenAIRE Goldstein, A.; Groenendijk, M.;Goldstein, A.
Harvested from ORCID Public Data FileGoldstein, A. in OpenAIRE Gu, L.; Hanan, N.; Helfter, C.; Helfter, C.
Harvested from ORCID Public Data FileHelfter, C. in OpenAIRE Hirano, T.; Hollinger, D. Y.; Jones, M. B.;Hirano, T.
Harvested from ORCID Public Data FileHirano, T. in OpenAIRE Kiely, G.; Kolb, T. E.; Kutsch, W. L.; Lafleur, P.; Law, B. E.; Law, B. E.
Harvested from ORCID Public Data FileLaw, B. E. in OpenAIRE Lawrence, D. M.; Li, L.;Lawrence, D. M.
Harvested from ORCID Public Data FileLawrence, D. M. in OpenAIRE Lindroth, A.; Litvak, M.;Lindroth, A.
Harvested from ORCID Public Data FileLindroth, A. in OpenAIRE Loustau, D.; Loustau, D.
Harvested from ORCID Public Data FileLoustau, D. in OpenAIRE Lund, M.; Ma, S.; Marek, M.; Martin, T. A.; Martin, T. A.
Harvested from ORCID Public Data FileMartin, T. A. in OpenAIRE Matteucci, G.; Migliavacca, M.;Matteucci, G.
Harvested from ORCID Public Data FileMatteucci, G. in OpenAIRE Montagnani, L.; Moors, E.;Montagnani, L.
Harvested from ORCID Public Data FileMontagnani, L. in OpenAIRE Munger, J. W.; Munger, J. W.
Harvested from ORCID Public Data FileMunger, J. W. in OpenAIRE Noormets, A.; Noormets, A.
Harvested from ORCID Public Data FileNoormets, A. in OpenAIRE Oechel, W.; Oechel, W.
Harvested from ORCID Public Data FileOechel, W. in OpenAIRE Olejnik, J.; Paw, U.;Olejnik, J.
Harvested from ORCID Public Data FileOlejnik, J. in OpenAIRE Pilegaard, K.; Pilegaard, K.
Harvested from ORCID Public Data FilePilegaard, K. in OpenAIRE Rambal, S.; Rambal, S.
Harvested from ORCID Public Data FileRambal, S. in OpenAIRE Raschi, A.; Saleska, S.;Raschi, A.
Harvested from ORCID Public Data FileRaschi, A. in OpenAIRE Scott, R. L.; Scott, R. L.
Harvested from ORCID Public Data FileScott, R. L. in OpenAIRE Seufert, G.; Seufert, G.
Harvested from ORCID Public Data FileSeufert, G. in OpenAIRE Spano, D.; Stoy, P.; Sutton, M. A.; Varlagin, A.; Varlagin, A.
Harvested from ORCID Public Data FileVarlagin, A. in OpenAIRE Vesala, T.; Weng, E.;Vesala, T.
Harvested from ORCID Public Data FileVesala, T. in OpenAIRE Wohlfahrt, G.; Wohlfahrt, G.
Harvested from ORCID Public Data FileWohlfahrt, G. in OpenAIRE Yang, B.; Zhang, Z.; Zhou, X.; • 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 ecosystem-climate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.
Access RoutesGreen bronze 125 citations 125 popularity Top 1% influence Top 10% impulse Top 10% 
Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/j.1469-8137.2012.04095.x&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - EC| GHG EUROPE Niu, S.; Luo, Y.; Fei, S.; Yuan, W.; Schimel, D.; Ammann, C.;
Ammann, C.
Harvested from ORCID Public Data FileAmmann, C. in OpenAIRE Arain, M. A.; Arain, M. A.
Harvested from ORCID Public Data FileArain, M. A. in OpenAIRE Arneth, A.; Aubinet, M.; Bar, A.;Arneth, A.
Harvested from ORCID Public Data FileArneth, A. in OpenAIRE Beringer, J.; Beringer, J.
Harvested from ORCID Public Data FileBeringer, J. in OpenAIRE Bernhofer, C.; Black, A. T.;Bernhofer, C.
Harvested from ORCID Public Data FileBernhofer, C. in OpenAIRE Buchmann, N.; Cescatti, A.;Buchmann, N.
Harvested from ORCID Public Data FileBuchmann, N. in OpenAIRE Chen, J.; Davis, K. J.; Davis, K. J.
Harvested from ORCID Public Data FileDavis, K. J. in OpenAIRE Dellwik, E.; Dellwik, E.
Harvested from ORCID Public Data FileDellwik, E. in OpenAIRE Desai, A. R.; Dolman, H.;Desai, A. R.
Harvested from ORCID Public Data FileDesai, A. R. in OpenAIRE Etzold, S.; Etzold, S.
Harvested from ORCID Public Data FileEtzold, S. in OpenAIRE Francois, L.; Francois, L.
Harvested from ORCID Public Data FileFrancois, L. in OpenAIRE Gianelle, Damiano; Gielen, B.;Gianelle, Damiano
Harvested from ORCID Public Data FileGianelle, Damiano in OpenAIRE Goldstein, A.; Groenendijk, M.;Goldstein, A.
Harvested from ORCID Public Data FileGoldstein, A. in OpenAIRE Gu, L.; Hanan, N.; Helfter, C.; Helfter, C.
Harvested from ORCID Public Data FileHelfter, C. in OpenAIRE Hirano, T.; Hollinger, D. Y.; Jones, M. B.;Hirano, T.
Harvested from ORCID Public Data FileHirano, T. in OpenAIRE Kiely, G.; Kolb, T. E.; Kutsch, W. L.; Lafleur, P.; Law, B. E.; Law, B. E.
Harvested from ORCID Public Data FileLaw, B. E. in OpenAIRE Lawrence, D. M.; Li, L.;Lawrence, D. M.
Harvested from ORCID Public Data FileLawrence, D. M. in OpenAIRE Lindroth, A.; Litvak, M.;Lindroth, A.
Harvested from ORCID Public Data FileLindroth, A. in OpenAIRE Loustau, D.; Loustau, D.
Harvested from ORCID Public Data FileLoustau, D. in OpenAIRE Lund, M.; Ma, S.; Marek, M.; Martin, T. A.; Martin, T. A.
Harvested from ORCID Public Data FileMartin, T. A. in OpenAIRE Matteucci, G.; Migliavacca, M.;Matteucci, G.
Harvested from ORCID Public Data FileMatteucci, G. in OpenAIRE Montagnani, L.; Moors, E.;Montagnani, L.
Harvested from ORCID Public Data FileMontagnani, L. in OpenAIRE Munger, J. W.; Munger, J. W.
Harvested from ORCID Public Data FileMunger, J. W. in OpenAIRE Noormets, A.; Noormets, A.
Harvested from ORCID Public Data FileNoormets, A. in OpenAIRE Oechel, W.; Oechel, W.
Harvested from ORCID Public Data FileOechel, W. in OpenAIRE Olejnik, J.; Paw, U.;Olejnik, J.
Harvested from ORCID Public Data FileOlejnik, J. in OpenAIRE Pilegaard, K.; Pilegaard, K.
Harvested from ORCID Public Data FilePilegaard, K. in OpenAIRE Rambal, S.; Rambal, S.
Harvested from ORCID Public Data FileRambal, S. in OpenAIRE Raschi, A.; Saleska, S.;Raschi, A.
Harvested from ORCID Public Data FileRaschi, A. in OpenAIRE Scott, R. L.; Scott, R. L.
Harvested from ORCID Public Data FileScott, R. L. in OpenAIRE Seufert, G.; Seufert, G.
Harvested from ORCID Public Data FileSeufert, G. in OpenAIRE Spano, D.; Stoy, P.; Sutton, M. A.; Varlagin, A.; Varlagin, A.
Harvested from ORCID Public Data FileVarlagin, A. in OpenAIRE Vesala, T.; Weng, E.;Vesala, T.
Harvested from ORCID Public Data FileVesala, T. in OpenAIRE Wohlfahrt, G.; Wohlfahrt, G.
Harvested from ORCID Public Data FileWohlfahrt, G. in OpenAIRE Yang, B.; Zhang, Z.; Zhou, X.; • 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 ecosystem-climate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.
Access RoutesGreen bronze 125 citations 125 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/j.1469-8137.2012.04095.x&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Alexandra Henrot; Louis François; Eric Favre; Pierre Warnant; +3 Authors
Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIREAlexandra Henrot; Louis François; Eric Favre; Pierre Warnant;Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Alain Hambuckers; Mohamed Ouberdous; Marie Dury;Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRESignificant climatic changes are currently observed and, according to projections, will be strengthened over the 21st century throughout the world with the continuing increase of the atmospheric CO2 concentration. Climate will be generally warmer with notably changes in the seasonality and in the precipitation regime. These changes will have major impacts on the biodiversity and the functioning of natural ecosystems. The CARAIB dynamic vegetation model driven by the ARPEGE/Climate model under forcing from the A2 IPCC emission scenario is used to illustrate and analyse the potential impacts of climate change on forest productivity and distribution as well as fire intensity over Europe. The potential CO2 fertilizing effect is studied throughout transient runs of the vegetation model over the 1961-2100 period assuming constant and increasing atmospheric CO2 concentration. Without fertilisation effect, the net primary productivity (NPP) might increase in high latitudes and altitudes (by up to 40 % or even 60-100 %) while it might decrease in temperate (by up to 50 %) and in warmer regions, e.g., Mediterranean area (by up to 80 %). This strong decrease in NPP is associated with recurrent drought events occurring mostly in summer time. Under rising CO2 concentration, NPP increases all over Europe by as much as 25-75%, but it is not clear whether or not soils might sustain such an increase. The model indicates also that interannual NPP variability might strongly increase in the areas which will undergo recurrent water stress in the future. During the years exhibiting summer drought, the NPP might decrease to values much lower than present-day average NPP even when CO2 fertilization is included. Moreover, years with such events will happen much more frequently than today. Regions with more severe droughts might also be affected by an increase of wildfire frequency and intensity, which may have large impacts on vegetation density and distribution. For instance, in the Mediterranean basin, the area burned by wildfire can be expected to increase by a factor of 3-5 at the end of the 21st century compared to present.
Access Routesgold 88 citations 88 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3832/ifor0572-004&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Alexandra Henrot; Louis François; Eric Favre; Pierre Warnant; +3 Authors
Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIREAlexandra Henrot; Louis François; Eric Favre; Pierre Warnant;Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Alain Hambuckers; Mohamed Ouberdous; Marie Dury;Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRESignificant climatic changes are currently observed and, according to projections, will be strengthened over the 21st century throughout the world with the continuing increase of the atmospheric CO2 concentration. Climate will be generally warmer with notably changes in the seasonality and in the precipitation regime. These changes will have major impacts on the biodiversity and the functioning of natural ecosystems. The CARAIB dynamic vegetation model driven by the ARPEGE/Climate model under forcing from the A2 IPCC emission scenario is used to illustrate and analyse the potential impacts of climate change on forest productivity and distribution as well as fire intensity over Europe. The potential CO2 fertilizing effect is studied throughout transient runs of the vegetation model over the 1961-2100 period assuming constant and increasing atmospheric CO2 concentration. Without fertilisation effect, the net primary productivity (NPP) might increase in high latitudes and altitudes (by up to 40 % or even 60-100 %) while it might decrease in temperate (by up to 50 %) and in warmer regions, e.g., Mediterranean area (by up to 80 %). This strong decrease in NPP is associated with recurrent drought events occurring mostly in summer time. Under rising CO2 concentration, NPP increases all over Europe by as much as 25-75%, but it is not clear whether or not soils might sustain such an increase. The model indicates also that interannual NPP variability might strongly increase in the areas which will undergo recurrent water stress in the future. During the years exhibiting summer drought, the NPP might decrease to values much lower than present-day average NPP even when CO2 fertilization is included. Moreover, years with such events will happen much more frequently than today. Regions with more severe droughts might also be affected by an increase of wildfire frequency and intensity, which may have large impacts on vegetation density and distribution. For instance, in the Mediterranean basin, the area burned by wildfire can be expected to increase by a factor of 3-5 at the end of the 21st century compared to present.
Access Routesgold 88 citations 88 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3832/ifor0572-004&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - NSF| DMUU: Center for Robust Decision-Making Tools for Climate and Energy Policy ,NSF| Graduate Research Fellowship Program (GRFP) ,EC| IMBALANCE-P ,NSF| NRT INFEWS: computational data science to advance research at the energy-environment nexus ,EC| IMPREXJ. A. Franke; J. A. Franke; C. Müller; J. Elliott; J. Elliott; A. C. Ruane; J. Jägermeyr; J. Jägermeyr; J. Jägermeyr; J. Jägermeyr; A. Snyder; M. Dury; P. D. Falloon;
J. Jägermeyr
Harvested from ORCID Public Data FileJ. Jägermeyr in OpenAIRE C. Folberth; C. Folberth
Harvested from ORCID Public Data FileC. Folberth in OpenAIRE L. François; L. François
Harvested from ORCID Public Data FileL. François in OpenAIRE T. Hank; R. C. Izaurralde; R. C. Izaurralde; I. Jacquemin; C. Jones; M. Li; M. Li;R. C. Izaurralde
Harvested from ORCID Public Data FileR. C. Izaurralde in OpenAIRE W. Liu; W. Liu; S. Olin; M. Phillips; M. Phillips; T. A. M. Pugh; T. A. M. Pugh; A. Reddy; K. Williams; K. Williams;T. A. M. Pugh
Harvested from ORCID Public Data FileT. A. M. Pugh in OpenAIRE Z. Wang; Z. Wang; F. Zabel; E. J. Moyer; E. J. Moyer;Abstract. Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: that growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.
Access RoutesGreen gold 32 citations 32 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5194/gmd-13-3995-2020&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - NSF| DMUU: Center for Robust Decision-Making Tools for Climate and Energy Policy ,NSF| Graduate Research Fellowship Program (GRFP) ,EC| IMBALANCE-P ,NSF| NRT INFEWS: computational data science to advance research at the energy-environment nexus ,EC| IMPREXJ. A. Franke; J. A. Franke; C. Müller; J. Elliott; J. Elliott; A. C. Ruane; J. Jägermeyr; J. Jägermeyr; J. Jägermeyr; J. Jägermeyr; A. Snyder; M. Dury; P. D. Falloon;
J. Jägermeyr
Harvested from ORCID Public Data FileJ. Jägermeyr in OpenAIRE C. Folberth; C. Folberth
Harvested from ORCID Public Data FileC. Folberth in OpenAIRE L. François; L. François
Harvested from ORCID Public Data FileL. François in OpenAIRE T. Hank; R. C. Izaurralde; R. C. Izaurralde; I. Jacquemin; C. Jones; M. Li; M. Li;R. C. Izaurralde
Harvested from ORCID Public Data FileR. C. Izaurralde in OpenAIRE W. Liu; W. Liu; S. Olin; M. Phillips; M. Phillips; T. A. M. Pugh; T. A. M. Pugh; A. Reddy; K. Williams; K. Williams;T. A. M. Pugh
Harvested from ORCID Public Data FileT. A. M. Pugh in OpenAIRE Z. Wang; Z. Wang; F. Zabel; E. J. Moyer; E. J. Moyer;Abstract. Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: that growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.
Access RoutesGreen gold 32 citations 32 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5194/gmd-13-3995-2020&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - ANR| VULPES
Rachid Cheddadi; Alexandra-Jane Henrot;Rachid Cheddadi
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesRachid Cheddadi in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Frédéric Boyer; +17 AuthorsFrédéric Boyer
Harvested from ORCID Public Data FileFrédéric Boyer in OpenAIRE Rachid Cheddadi; Alexandra-Jane Henrot;Rachid Cheddadi
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesRachid Cheddadi in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Frédéric Boyer; Mark Bush;Frédéric Boyer
Harvested from ORCID Public Data FileFrédéric Boyer in OpenAIRE Matthieu Carré; Matthieu Carré;Matthieu Carré
Harvested from ORCID Public Data FileMatthieu Carré in OpenAIRE Eric Coissac; Paulo E. De Oliveira; Paulo E. De Oliveira;Eric Coissac
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesEric Coissac in OpenAIRE Francesco Ficetola; Francesco Ficetola
Harvested from ORCID Public Data FileFrancesco Ficetola in OpenAIRE Alain Hambuckers; Kangyou Huang;Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRE Anne-Marie Lézine; Majda Nourelbait;Anne-Marie Lézine
Harvested from ORCID Public Data FileAnne-Marie Lézine in OpenAIRE Ali Rhoujjati; Ali Rhoujjati
Harvested from ORCID Public Data FileAli Rhoujjati in OpenAIRE Pierre Taberlet; Pierre Taberlet
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesPierre Taberlet in OpenAIRE Fausto Sarmiento; Fausto Sarmiento
Harvested from ORCID Public Data FileFausto Sarmiento in OpenAIRE Daniel Abel-Schaad; Daniel Abel-Schaad
Harvested from ORCID Public Data FileDaniel Abel-Schaad in OpenAIRE Francisca Alba-Sánchez; Zhuo Zheng;Francisca Alba-Sánchez
Harvested from ORCID Public Data FileFrancisca Alba-Sánchez in OpenAIRECette étude reconstruit et interprète l'évolution de l'aire de répartition du cèdre de l'Atlas dans le nord du Maroc au cours des 9 000 dernières années. Une synthèse des enregistrements de pollen fossile a indiqué que les cèdres de l'Atlas occupaient une aire de répartition plus large à des altitudes plus basses au milieu de l'Holocène qu'aujourd' hui. L'expansion géographique du milieu de l'Holocène reflétait de faibles températures hivernales et une disponibilité en eau plus élevée sur toute la gamme des montagnes du Rif par rapport aux conditions modernes. Une tendance à l'augmentation de l'aridité observée après 6000 ans BP a progressivement réduit l'aire de répartition du cèdre de l'Atlas et a incité sa migration vers des élévations supérieures à 1400 masl. Pour évaluer l'impact du changement climatique sur les populations de cèdres au cours des dernières décennies, nous avons effectué une simulation de modèle transitoire pour la période comprise entre 1960 et 2010. Notre simulation a montré que l'aire de répartition du cèdre de l'Atlas a diminué d'environ 75 % au cours des 50 dernières années et que les populations orientales de l'aire de répartition dans les montagnes du Rif étaient encore plus menacées par le manque global de disponibilité en eau que les populations occidentales. Aujourd'hui, les populations de cèdres de l'Atlas dans les montagnes du Rif persistent dans des zones restreintes et isolées (Jbel Kelti, Talassemtane, Jbel Tiziren, Oursane, Tidighine) que nous considérons comme des microrefuges modernes. La conservation de ces populations isolées est essentielle pour la survie future de l'espèce, la préservation des polymorphismes et le potentiel de rétablissement des populations dans différentes conditions climatiques. Este estudio reconstruye e interpreta el rango cambiante del cedro del Atlas en el norte de Marruecos durante los últimos 9.000 años. Una síntesis de los registros de polen fósil indicó que los cedros del Atlas ocupaban un rango más amplio en altitudes más bajas durante el Holoceno medio que en la actualidad. La expansión geográfica del Holoceno medio reflejó bajas temperaturas invernales y una mayor disponibilidad de agua en toda la cordillera del Rif en relación con las condiciones modernas. Una tendencia de aumento de la aridez observada después de 6000 años BP redujo progresivamente el rango del cedro del Atlas y provocó su migración hacia elevaciones superiores a 1400 msnm. Para evaluar el impacto del cambio climático en las poblaciones de cedros en las últimas décadas, realizamos una simulación de modelo transitorio para el período comprendido entre 1960 y 2010. Nuestra simulación mostró que el rango del cedro del Atlas disminuyó en aproximadamente un 75% en los últimos 50 años y que las poblaciones orientales del rango en las montañas del Rif estaban aún más amenazadas por la falta general de disponibilidad de agua que las occidentales. Hoy en día, las poblaciones de cedro del Atlas en las montañas del Rif persisten en áreas restringidas y aisladas (Jbel Kelti, Talassemtane, Jbel Tiziren, Oursane, Tidighine) que consideramos micro-refugios modernos. Conservar estas poblaciones aisladas es esencial para la supervivencia futura de la especie, preservando los polimorfismos y el potencial de recuperación de la población en diferentes condiciones climáticas. This study reconstructs and interprets the changing range of Atlas cedar in northern Morocco over the last 9,000 years. A synthesis of fossil pollen records indicated that Atlas cedars occupied a wider range at lower elevations during the mid-Holocene than today. The mid-Holocene geographical expansion reflected low winter temperatures and higher water availability over the whole range of the Rif Mountains relative to modern conditions. A trend of increasing aridity observed after 6000 years BP progressively reduced the range of Atlas cedar and prompted its migration towards elevations above 1400 masl. To assess the impact of climate change on cedar populations over the last decades, we performed a transient model simulation for the period between 1960 and 2010. Our simulation showed that the range of Atlas cedar decreased by about 75% over the last 50 years and that the eastern populations of the range in the Rif Mountains were even more threatened by the overall lack of water availability than the western ones. Today, Atlas cedar populations in the Rif Mountains are persisting in restricted and isolated areas (Jbel Kelti, Talassemtane, Jbel Tiziren, Oursane, Tidighine) that we consider to be modern microrefugia. Conservation of these isolated populations is essential for the future survival of the species, preserving polymorphisms and the potential for population recovery under different climatic conditions. تعيد هذه الدراسة بناء وتفسير النطاق المتغير لأرز الأطلس في شمال المغرب على مدار الـ 9000 عام الماضية. أشار توليف لسجلات حبوب اللقاح الأحفورية إلى أن أرز الأطلس احتل نطاقًا أوسع على ارتفاعات أقل خلال منتصف عصر الهولوسين مما هو عليه اليوم. يعكس التوسع الجغرافي في منتصف العصر الهولوسيني انخفاض درجات الحرارة في فصل الشتاء وزيادة توافر المياه على نطاق كامل من جبال الريف بالنسبة للظروف الحديثة. أدى اتجاه الجفاف المتزايد الذي لوحظ بعد 6000 عام من BP إلى تقليل نطاق أرز الأطلس تدريجياً ودفع هجرته نحو ارتفاعات فوق 1400 مل. لتقييم تأثير تغير المناخ على تجمعات الأرز على مدى العقود الماضية، أجرينا محاكاة نموذجية عابرة للفترة بين عامي 1960 و 2010. أظهرت محاكاتنا أن نطاق أرز الأطلس انخفض بنحو 75 ٪ على مدى السنوات الخمسين الماضية وأن السكان الشرقيين للنطاق في جبال الريف كانوا أكثر عرضة للتهديد بسبب النقص العام في توافر المياه من السكان الغربيين. اليوم، تستمر مجموعات أرز الأطلس في جبال الريف في المناطق المحظورة والمعزولة (جبل كلتي، تلسمتان، جبل تيزيرين، أورسان، تيديجين) التي نعتبرها ملاذًا دقيقًا حديثًا. يعد الحفاظ على هذه التجمعات المعزولة أمرًا ضروريًا لبقاء الأنواع في المستقبل، والحفاظ على تعدد الأشكال وإمكانية تعافي التجمعات في ظل ظروف مناخية مختلفة.
Access RoutesGreen gold 55 citations 55 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3389/fevo.2017.00114&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - ANR| VULPES Rachid Cheddadi; Alexandra-Jane Henrot;
Rachid Cheddadi
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesRachid Cheddadi in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Frédéric Boyer; +17 AuthorsFrédéric Boyer
Harvested from ORCID Public Data FileFrédéric Boyer in OpenAIRE Rachid Cheddadi; Alexandra-Jane Henrot;Rachid Cheddadi
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesRachid Cheddadi in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Frédéric Boyer; Mark Bush;Frédéric Boyer
Harvested from ORCID Public Data FileFrédéric Boyer in OpenAIRE Matthieu Carré; Matthieu Carré;Matthieu Carré
Harvested from ORCID Public Data FileMatthieu Carré in OpenAIRE Eric Coissac; Paulo E. De Oliveira; Paulo E. De Oliveira;Eric Coissac
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesEric Coissac in OpenAIRE Francesco Ficetola; Francesco Ficetola
Harvested from ORCID Public Data FileFrancesco Ficetola in OpenAIRE Alain Hambuckers; Kangyou Huang;Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRE Anne-Marie Lézine; Majda Nourelbait;Anne-Marie Lézine
Harvested from ORCID Public Data FileAnne-Marie Lézine in OpenAIRE Ali Rhoujjati; Ali Rhoujjati
Harvested from ORCID Public Data FileAli Rhoujjati in OpenAIRE Pierre Taberlet; Pierre Taberlet
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesPierre Taberlet in OpenAIRE Fausto Sarmiento; Fausto Sarmiento
Harvested from ORCID Public Data FileFausto Sarmiento in OpenAIRE Daniel Abel-Schaad; Daniel Abel-Schaad
Harvested from ORCID Public Data FileDaniel Abel-Schaad in OpenAIRE Francisca Alba-Sánchez; Zhuo Zheng;Francisca Alba-Sánchez
Harvested from ORCID Public Data FileFrancisca Alba-Sánchez in OpenAIRECette étude reconstruit et interprète l'évolution de l'aire de répartition du cèdre de l'Atlas dans le nord du Maroc au cours des 9 000 dernières années. Une synthèse des enregistrements de pollen fossile a indiqué que les cèdres de l'Atlas occupaient une aire de répartition plus large à des altitudes plus basses au milieu de l'Holocène qu'aujourd' hui. L'expansion géographique du milieu de l'Holocène reflétait de faibles températures hivernales et une disponibilité en eau plus élevée sur toute la gamme des montagnes du Rif par rapport aux conditions modernes. Une tendance à l'augmentation de l'aridité observée après 6000 ans BP a progressivement réduit l'aire de répartition du cèdre de l'Atlas et a incité sa migration vers des élévations supérieures à 1400 masl. Pour évaluer l'impact du changement climatique sur les populations de cèdres au cours des dernières décennies, nous avons effectué une simulation de modèle transitoire pour la période comprise entre 1960 et 2010. Notre simulation a montré que l'aire de répartition du cèdre de l'Atlas a diminué d'environ 75 % au cours des 50 dernières années et que les populations orientales de l'aire de répartition dans les montagnes du Rif étaient encore plus menacées par le manque global de disponibilité en eau que les populations occidentales. Aujourd'hui, les populations de cèdres de l'Atlas dans les montagnes du Rif persistent dans des zones restreintes et isolées (Jbel Kelti, Talassemtane, Jbel Tiziren, Oursane, Tidighine) que nous considérons comme des microrefuges modernes. La conservation de ces populations isolées est essentielle pour la survie future de l'espèce, la préservation des polymorphismes et le potentiel de rétablissement des populations dans différentes conditions climatiques. Este estudio reconstruye e interpreta el rango cambiante del cedro del Atlas en el norte de Marruecos durante los últimos 9.000 años. Una síntesis de los registros de polen fósil indicó que los cedros del Atlas ocupaban un rango más amplio en altitudes más bajas durante el Holoceno medio que en la actualidad. La expansión geográfica del Holoceno medio reflejó bajas temperaturas invernales y una mayor disponibilidad de agua en toda la cordillera del Rif en relación con las condiciones modernas. Una tendencia de aumento de la aridez observada después de 6000 años BP redujo progresivamente el rango del cedro del Atlas y provocó su migración hacia elevaciones superiores a 1400 msnm. Para evaluar el impacto del cambio climático en las poblaciones de cedros en las últimas décadas, realizamos una simulación de modelo transitorio para el período comprendido entre 1960 y 2010. Nuestra simulación mostró que el rango del cedro del Atlas disminuyó en aproximadamente un 75% en los últimos 50 años y que las poblaciones orientales del rango en las montañas del Rif estaban aún más amenazadas por la falta general de disponibilidad de agua que las occidentales. Hoy en día, las poblaciones de cedro del Atlas en las montañas del Rif persisten en áreas restringidas y aisladas (Jbel Kelti, Talassemtane, Jbel Tiziren, Oursane, Tidighine) que consideramos micro-refugios modernos. Conservar estas poblaciones aisladas es esencial para la supervivencia futura de la especie, preservando los polimorfismos y el potencial de recuperación de la población en diferentes condiciones climáticas. This study reconstructs and interprets the changing range of Atlas cedar in northern Morocco over the last 9,000 years. A synthesis of fossil pollen records indicated that Atlas cedars occupied a wider range at lower elevations during the mid-Holocene than today. The mid-Holocene geographical expansion reflected low winter temperatures and higher water availability over the whole range of the Rif Mountains relative to modern conditions. A trend of increasing aridity observed after 6000 years BP progressively reduced the range of Atlas cedar and prompted its migration towards elevations above 1400 masl. To assess the impact of climate change on cedar populations over the last decades, we performed a transient model simulation for the period between 1960 and 2010. Our simulation showed that the range of Atlas cedar decreased by about 75% over the last 50 years and that the eastern populations of the range in the Rif Mountains were even more threatened by the overall lack of water availability than the western ones. Today, Atlas cedar populations in the Rif Mountains are persisting in restricted and isolated areas (Jbel Kelti, Talassemtane, Jbel Tiziren, Oursane, Tidighine) that we consider to be modern microrefugia. Conservation of these isolated populations is essential for the future survival of the species, preserving polymorphisms and the potential for population recovery under different climatic conditions. تعيد هذه الدراسة بناء وتفسير النطاق المتغير لأرز الأطلس في شمال المغرب على مدار الـ 9000 عام الماضية. أشار توليف لسجلات حبوب اللقاح الأحفورية إلى أن أرز الأطلس احتل نطاقًا أوسع على ارتفاعات أقل خلال منتصف عصر الهولوسين مما هو عليه اليوم. يعكس التوسع الجغرافي في منتصف العصر الهولوسيني انخفاض درجات الحرارة في فصل الشتاء وزيادة توافر المياه على نطاق كامل من جبال الريف بالنسبة للظروف الحديثة. أدى اتجاه الجفاف المتزايد الذي لوحظ بعد 6000 عام من BP إلى تقليل نطاق أرز الأطلس تدريجياً ودفع هجرته نحو ارتفاعات فوق 1400 مل. لتقييم تأثير تغير المناخ على تجمعات الأرز على مدى العقود الماضية، أجرينا محاكاة نموذجية عابرة للفترة بين عامي 1960 و 2010. أظهرت محاكاتنا أن نطاق أرز الأطلس انخفض بنحو 75 ٪ على مدى السنوات الخمسين الماضية وأن السكان الشرقيين للنطاق في جبال الريف كانوا أكثر عرضة للتهديد بسبب النقص العام في توافر المياه من السكان الغربيين. اليوم، تستمر مجموعات أرز الأطلس في جبال الريف في المناطق المحظورة والمعزولة (جبل كلتي، تلسمتان، جبل تيزيرين، أورسان، تيديجين) التي نعتبرها ملاذًا دقيقًا حديثًا. يعد الحفاظ على هذه التجمعات المعزولة أمرًا ضروريًا لبقاء الأنواع في المستقبل، والحفاظ على تعدد الأشكال وإمكانية تعافي التجمعات في ظل ظروف مناخية مختلفة.
Access RoutesGreen gold 55 citations 55 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3389/fevo.2017.00114&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - NSF| Collaborative Research: EaSM2--Wildfires and Regional Climate Variability - Mechanisms, Modeling, and Prediction ,NSF| CNH: Pluvials, Droughts, Energetics, and the Mongol Empire ,EC| HELIX Jia Yang;
Jia Yang
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesJia Yang in OpenAIRE Kazuya Nishina; Richard Betts; Richard Betts; +17 AuthorsKazuya Nishina
Harvested from ORCID Public Data FileKazuya Nishina in OpenAIRE Jia Yang; Jia Yang
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesJia Yang in OpenAIRE Kazuya Nishina; Richard Betts; Richard Betts;Kazuya Nishina
Harvested from ORCID Public Data FileKazuya Nishina in OpenAIRE Sibyll Schaphoff; Sibyll Schaphoff
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesSibyll Schaphoff in OpenAIRE Louis François; Alexandra-Jane Henrot;Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Jinfeng Chang; Christopher P. O. Reyer; Catherine Morfopoulos; Katja Frieler;Jinfeng Chang
Harvested from ORCID Public Data FileJinfeng Chang in OpenAIRE Philippe Ciais; Jörg Steinkamp; Rashid Rafique;Philippe Ciais
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesPhilippe Ciais in OpenAIRE Fang Zhao; Fang Zhao
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesFang Zhao in OpenAIRE Thomas Hickler; Thomas Hickler
Harvested from ORCID Public Data FileThomas Hickler in OpenAIRE Hanqin Tian; Hanqin Tian
Harvested from ORCID Public Data FileHanqin Tian in OpenAIRE Sebastian Ostberg; Sebastian Ostberg
Harvested from ORCID Public Data FileSebastian Ostberg in OpenAIRE Anselmo García Cantú; Anselmo García Cantú
Harvested from ORCID Public Data FileAnselmo García Cantú in OpenAIRE Akihiko Ito; Akihiko Ito
Harvested from ORCID Public Data FileAkihiko Ito in OpenAIRE Shufen Pan; Shufen Pan
Harvested from ORCID Public Data FileShufen Pan in OpenAIREThis paper evaluates the ability of eight global vegetation models to reproduce recent trends and inter-annual variability of biomass in natural terrestrial ecosystems. For the purpose of this evaluation, the simulated trajectories of biomass are expressed in terms of the relative rate of change in biomass (RRB), defined as the deviation of the actual rate of biomass turnover from its equilibrium counterpart. Cumulative changes in RRB explain long-term changes in biomass pools. RRB simulated by the global vegetation models is compared with its observational equivalent, derived from vegetation optical depth reconstructions of above-ground biomass (AGB) over the period 1993–2010. According to the RRB analysis, the rate of global biomass growth described by the ensemble of simulations substantially exceeds the observation. The observed fluctuations of global RRB are significantly correlated with El Niño Southern Oscillation events (ENSO), but only some of the simulations reproduce this correlation. However, the ENSO sensitivity of RRB in the tropics is not significant in the observation, while it is in some of the simulations. This mismatch points to an important limitation of the observed AGB reconstruction to capture biomass variations in tropical forests. Important discrepancies in RRB were also identified at the regional scale, in the tropical forests of Amazonia and Central Africa, as well as in the boreal forests of north-western America, western and central Siberia. In each of these regions, the RRBs derived from the simulations were analyzed in connection with underlying differences in net primary productivity and biomass turnover rate ̶as a basis for exploring in how far differences in simulated changes in biomass are attributed to the response of the carbon uptake to CO _2 increments, as well as to the model representation of factors affecting the rates of mortality and turnover of foliage and roots. Overall, our findings stress the usefulness of using RRB to evaluate complex vegetation models and highlight the importance of conducting further evaluations of both the actual rate of biomass turnover and its equilibrium counterpart, with special focus on their background values and sources of variation. In turn, this task would require the availability of more accurate multi-year observational data of biomass and net primary productivity for natural ecosystems, as well as detailed and updated information on land-cover classification.
Access RoutesGreen gold 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1748-9326/aac63c&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - NSF| Collaborative Research: EaSM2--Wildfires and Regional Climate Variability - Mechanisms, Modeling, and Prediction ,NSF| CNH: Pluvials, Droughts, Energetics, and the Mongol Empire ,EC| HELIX Jia Yang;
Jia Yang
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesJia Yang in OpenAIRE Kazuya Nishina; Richard Betts; Richard Betts; +17 AuthorsKazuya Nishina
Harvested from ORCID Public Data FileKazuya Nishina in OpenAIRE Jia Yang; Jia Yang
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesJia Yang in OpenAIRE Kazuya Nishina; Richard Betts; Richard Betts;Kazuya Nishina
Harvested from ORCID Public Data FileKazuya Nishina in OpenAIRE Sibyll Schaphoff; Sibyll Schaphoff
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesSibyll Schaphoff in OpenAIRE Louis François; Alexandra-Jane Henrot;Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Jinfeng Chang; Christopher P. O. Reyer; Catherine Morfopoulos; Katja Frieler;Jinfeng Chang
Harvested from ORCID Public Data FileJinfeng Chang in OpenAIRE Philippe Ciais; Jörg Steinkamp; Rashid Rafique;Philippe Ciais
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesPhilippe Ciais in OpenAIRE Fang Zhao; Fang Zhao
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesFang Zhao in OpenAIRE Thomas Hickler; Thomas Hickler
Harvested from ORCID Public Data FileThomas Hickler in OpenAIRE Hanqin Tian; Hanqin Tian
Harvested from ORCID Public Data FileHanqin Tian in OpenAIRE Sebastian Ostberg; Sebastian Ostberg
Harvested from ORCID Public Data FileSebastian Ostberg in OpenAIRE Anselmo García Cantú; Anselmo García Cantú
Harvested from ORCID Public Data FileAnselmo García Cantú in OpenAIRE Akihiko Ito; Akihiko Ito
Harvested from ORCID Public Data FileAkihiko Ito in OpenAIRE Shufen Pan; Shufen Pan
Harvested from ORCID Public Data FileShufen Pan in OpenAIREThis paper evaluates the ability of eight global vegetation models to reproduce recent trends and inter-annual variability of biomass in natural terrestrial ecosystems. For the purpose of this evaluation, the simulated trajectories of biomass are expressed in terms of the relative rate of change in biomass (RRB), defined as the deviation of the actual rate of biomass turnover from its equilibrium counterpart. Cumulative changes in RRB explain long-term changes in biomass pools. RRB simulated by the global vegetation models is compared with its observational equivalent, derived from vegetation optical depth reconstructions of above-ground biomass (AGB) over the period 1993–2010. According to the RRB analysis, the rate of global biomass growth described by the ensemble of simulations substantially exceeds the observation. The observed fluctuations of global RRB are significantly correlated with El Niño Southern Oscillation events (ENSO), but only some of the simulations reproduce this correlation. However, the ENSO sensitivity of RRB in the tropics is not significant in the observation, while it is in some of the simulations. This mismatch points to an important limitation of the observed AGB reconstruction to capture biomass variations in tropical forests. Important discrepancies in RRB were also identified at the regional scale, in the tropical forests of Amazonia and Central Africa, as well as in the boreal forests of north-western America, western and central Siberia. In each of these regions, the RRBs derived from the simulations were analyzed in connection with underlying differences in net primary productivity and biomass turnover rate ̶as a basis for exploring in how far differences in simulated changes in biomass are attributed to the response of the carbon uptake to CO _2 increments, as well as to the model representation of factors affecting the rates of mortality and turnover of foliage and roots. Overall, our findings stress the usefulness of using RRB to evaluate complex vegetation models and highlight the importance of conducting further evaluations of both the actual rate of biomass turnover and its equilibrium counterpart, with special focus on their background values and sources of variation. In turn, this task would require the availability of more accurate multi-year observational data of biomass and net primary productivity for natural ecosystems, as well as detailed and updated information on land-cover classification.
Access RoutesGreen gold 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1748-9326/aac63c&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - EC| IMPACT2C ,EC| HELIX Jeroen Steenbeek;
Jeroen Steenbeek
Harvested from ORCID Public Data FileJeroen Steenbeek in OpenAIRE Erwin Schmid; Tyler D. Eddy; Tyler D. Eddy; +55 AuthorsErwin Schmid
Harvested from ORCID Public Data FileErwin Schmid in OpenAIRE Jeroen Steenbeek; Jeroen Steenbeek
Harvested from ORCID Public Data FileJeroen Steenbeek in OpenAIRE Erwin Schmid; Tyler D. Eddy; Tyler D. Eddy; Tyler D. Eddy;Erwin Schmid
Harvested from ORCID Public Data FileErwin Schmid in OpenAIRE Derek P. Tittensor; Derek P. Tittensor;Derek P. Tittensor
Harvested from ORCID Public Data FileDerek P. Tittensor in OpenAIRE Rene Orth; Rene Orth; Yadu Pokhrel; Joshua Elliott; Yusuke Satoh; Yusuke Satoh;Yusuke Satoh
Harvested from ORCID Public Data FileYusuke Satoh in OpenAIRE Christian Folberth; Christian Folberth
Harvested from ORCID Public Data FileChristian Folberth in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Andrew D. Friend; Andrew D. Friend
Harvested from ORCID Public Data FileAndrew D. Friend in OpenAIRE Catherine Morfopoulos; Catherine Morfopoulos
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesCatherine Morfopoulos in OpenAIRE Nikolay Khabarov; Peter Lawrence; Naota Hanasaki;Nikolay Khabarov
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesNikolay Khabarov in OpenAIRE Michelle T. H. van Vliet; Michelle T. H. van Vliet
Harvested from ORCID Public Data FileMichelle T. H. van Vliet in OpenAIRE Akihiko Ito; Akihiko Ito
Harvested from ORCID Public Data FileAkihiko Ito in OpenAIRE Sonia I. Seneviratne; Sonia I. Seneviratne
Harvested from ORCID Public Data FileSonia I. Seneviratne in OpenAIRE Veronika Huber; Veronika Huber
Harvested from ORCID Public Data FileVeronika Huber in OpenAIRE Thomas A. M. Pugh; Thomas A. M. Pugh
Harvested from ORCID Public Data FileThomas A. M. Pugh in OpenAIRE Jinfeng Chang; Jinfeng Chang
Harvested from ORCID Public Data FileJinfeng Chang in OpenAIRE Tobias Stacke; Tobias Stacke
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesTobias Stacke in OpenAIRE Philippe Ciais; Lila Warszawski; Jan Volkholz;Philippe Ciais
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesPhilippe Ciais in OpenAIRE Matthias Büchner; Matthias Büchner
Harvested from ORCID Public Data FileMatthias Büchner in OpenAIRE Yoshihide Wada; Christopher P. O. Reyer;Yoshihide Wada
Harvested from ORCID Public Data FileYoshihide Wada in OpenAIRE Xuhui Wang; Xuhui Wang; Xuhui Wang;Xuhui Wang
Harvested from ORCID Public Data FileXuhui Wang in OpenAIRE Dieter Gerten; Dieter Gerten;Dieter Gerten
Harvested from ORCID Public Data FileDieter Gerten in OpenAIRE Sebastian Ostberg; Qiuhong Tang;Sebastian Ostberg
Harvested from ORCID Public Data FileSebastian Ostberg in OpenAIRE Gen Sakurai; Gen Sakurai
Harvested from ORCID Public Data FileGen Sakurai in OpenAIRE David A. Carozza; David A. Carozza;David A. Carozza
Harvested from ORCID Public Data FileDavid A. Carozza in OpenAIRE Christoph Müller; Christoph Müller
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesChristoph Müller in OpenAIRE Jacob Schewe; Jacob Schewe
Harvested from ORCID Public Data FileJacob Schewe in OpenAIRE Lutz Breuer; Lutz Breuer
Harvested from ORCID Public Data FileLutz Breuer in OpenAIRE Delphine Deryng; Delphine Deryng
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesDelphine Deryng in OpenAIRE Heike K. Lotze; Heike K. Lotze
Harvested from ORCID Public Data FileHeike K. Lotze in OpenAIRE Hannes Müller Schmied; Robert Vautard;Hannes Müller Schmied
Harvested from ORCID Public Data FileHannes Müller Schmied in OpenAIRE Hyungjun Kim; Fang Zhao;Hyungjun Kim
Harvested from ORCID Public Data FileHyungjun Kim in OpenAIRE Allard de Wit; Jörg Steinkamp; Katja Frieler;Allard de Wit
Harvested from ORCID Public Data FileAllard de Wit in OpenAIRE Simon N. Gosling; Simon N. Gosling
Harvested from ORCID Public Data FileSimon N. Gosling in OpenAIRE Lukas Gudmundsson; Lukas Gudmundsson
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesLukas Gudmundsson in OpenAIRE Marta Coll; Marta Coll
Harvested from ORCID Public Data FileMarta Coll in OpenAIRE Hanqin Tian; Hanqin Tian
Harvested from ORCID Public Data FileHanqin Tian in OpenAIREAbstractGlobal impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
Access RoutesGreen 202 citations 202 popularity Top 0.1% influence Top 10% impulse Top 0.1% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-019-08745-6&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - EC| IMPACT2C ,EC| HELIX Jeroen Steenbeek;
Jeroen Steenbeek
Harvested from ORCID Public Data FileJeroen Steenbeek in OpenAIRE Erwin Schmid; Tyler D. Eddy; Tyler D. Eddy; +55 AuthorsErwin Schmid
Harvested from ORCID Public Data FileErwin Schmid in OpenAIRE Jeroen Steenbeek; Jeroen Steenbeek
Harvested from ORCID Public Data FileJeroen Steenbeek in OpenAIRE Erwin Schmid; Tyler D. Eddy; Tyler D. Eddy; Tyler D. Eddy;Erwin Schmid
Harvested from ORCID Public Data FileErwin Schmid in OpenAIRE Derek P. Tittensor; Derek P. Tittensor;Derek P. Tittensor
Harvested from ORCID Public Data FileDerek P. Tittensor in OpenAIRE Rene Orth; Rene Orth; Yadu Pokhrel; Joshua Elliott; Yusuke Satoh; Yusuke Satoh;Yusuke Satoh
Harvested from ORCID Public Data FileYusuke Satoh in OpenAIRE Christian Folberth; Christian Folberth
Harvested from ORCID Public Data FileChristian Folberth in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Andrew D. Friend; Andrew D. Friend
Harvested from ORCID Public Data FileAndrew D. Friend in OpenAIRE Catherine Morfopoulos; Catherine Morfopoulos
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesCatherine Morfopoulos in OpenAIRE Nikolay Khabarov; Peter Lawrence; Naota Hanasaki;Nikolay Khabarov
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesNikolay Khabarov in OpenAIRE Michelle T. H. van Vliet; Michelle T. H. van Vliet
Harvested from ORCID Public Data FileMichelle T. H. van Vliet in OpenAIRE Akihiko Ito; Akihiko Ito
Harvested from ORCID Public Data FileAkihiko Ito in OpenAIRE Sonia I. Seneviratne; Sonia I. Seneviratne
Harvested from ORCID Public Data FileSonia I. Seneviratne in OpenAIRE Veronika Huber; Veronika Huber
Harvested from ORCID Public Data FileVeronika Huber in OpenAIRE Thomas A. M. Pugh; Thomas A. M. Pugh
Harvested from ORCID Public Data FileThomas A. M. Pugh in OpenAIRE Jinfeng Chang; Jinfeng Chang
Harvested from ORCID Public Data FileJinfeng Chang in OpenAIRE Tobias Stacke; Tobias Stacke
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesTobias Stacke in OpenAIRE Philippe Ciais; Lila Warszawski; Jan Volkholz;Philippe Ciais
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesPhilippe Ciais in OpenAIRE Matthias Büchner; Matthias Büchner
Harvested from ORCID Public Data FileMatthias Büchner in OpenAIRE Yoshihide Wada; Christopher P. O. Reyer;Yoshihide Wada
Harvested from ORCID Public Data FileYoshihide Wada in OpenAIRE Xuhui Wang; Xuhui Wang; Xuhui Wang;Xuhui Wang
Harvested from ORCID Public Data FileXuhui Wang in OpenAIRE Dieter Gerten; Dieter Gerten;Dieter Gerten
Harvested from ORCID Public Data FileDieter Gerten in OpenAIRE Sebastian Ostberg; Qiuhong Tang;Sebastian Ostberg
Harvested from ORCID Public Data FileSebastian Ostberg in OpenAIRE Gen Sakurai; Gen Sakurai
Harvested from ORCID Public Data FileGen Sakurai in OpenAIRE David A. Carozza; David A. Carozza;David A. Carozza
Harvested from ORCID Public Data FileDavid A. Carozza in OpenAIRE Christoph Müller; Christoph Müller
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesChristoph Müller in OpenAIRE Jacob Schewe; Jacob Schewe
Harvested from ORCID Public Data FileJacob Schewe in OpenAIRE Lutz Breuer; Lutz Breuer
Harvested from ORCID Public Data FileLutz Breuer in OpenAIRE Delphine Deryng; Delphine Deryng
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesDelphine Deryng in OpenAIRE Heike K. Lotze; Heike K. Lotze
Harvested from ORCID Public Data FileHeike K. Lotze in OpenAIRE Hannes Müller Schmied; Robert Vautard;Hannes Müller Schmied
Harvested from ORCID Public Data FileHannes Müller Schmied in OpenAIRE Hyungjun Kim; Fang Zhao;Hyungjun Kim
Harvested from ORCID Public Data FileHyungjun Kim in OpenAIRE Allard de Wit; Jörg Steinkamp; Katja Frieler;Allard de Wit
Harvested from ORCID Public Data FileAllard de Wit in OpenAIRE Simon N. Gosling; Simon N. Gosling
Harvested from ORCID Public Data FileSimon N. Gosling in OpenAIRE Lukas Gudmundsson; Lukas Gudmundsson
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesLukas Gudmundsson in OpenAIRE Marta Coll; Marta Coll
Harvested from ORCID Public Data FileMarta Coll in OpenAIRE Hanqin Tian; Hanqin Tian
Harvested from ORCID Public Data FileHanqin Tian in OpenAIREAbstractGlobal impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
Access RoutesGreen 202 citations 202 popularity Top 0.1% influence Top 10% impulse Top 0.1% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-019-08745-6&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - ANR| PACMEDY ,ANR| VULPES Rachid Cheddadi;
Rachid Cheddadi
Harvested from ORCID Public Data FileRachid Cheddadi in OpenAIRE Matthieu Carré; Matthieu Carré
Harvested from ORCID Public Data FileMatthieu Carré in OpenAIRE Majda Nourelbait; Majda Nourelbait
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMajda Nourelbait in OpenAIRE Louis François; +4 AuthorsLouis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Rachid Cheddadi; Rachid Cheddadi
Harvested from ORCID Public Data FileRachid Cheddadi in OpenAIRE Matthieu Carré; Matthieu Carré
Harvested from ORCID Public Data FileMatthieu Carré in OpenAIRE Majda Nourelbait; Majda Nourelbait
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMajda Nourelbait in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Ali Rhoujjati; Ali Rhoujjati
Harvested from ORCID Public Data FileAli Rhoujjati in OpenAIRE Roger Manay; Roger Manay
Harvested from ORCID Public Data FileRoger Manay in OpenAIRE Diana Ochoa; Diana Ochoa
Harvested from ORCID Public Data FileDiana Ochoa in OpenAIRE Enno Schefuß; Enno Schefuß
Harvested from ORCID Public Data FileEnno Schefuß in OpenAIRESignificance Explaining the greening of the Sahara during the Holocene has been a challenge for decades. A strengthening of the African monsoon caused by increased summer insolation is usually cited to explain why the Sahara was vegetated from 14,000 to 5,000 y ago. Here, we provide a unique climate record of quantified winter, spring, and summer precipitation in Morocco over the past 18,500 y, and numeric simulations, which show that moisture contributions from the Mediterranean Sea and the North Atlantic Ocean in winter, were as important as the expanded summer monsoon for the greening of the Sahara during the African humid period. The findings of this study will help to better understand and simulate climate variability over northern Africa.
Access RoutesGreen hybrid 40 citations 40 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1073/pnas.2024898118&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - ANR| PACMEDY ,ANR| VULPES Rachid Cheddadi;
Rachid Cheddadi
Harvested from ORCID Public Data FileRachid Cheddadi in OpenAIRE Matthieu Carré; Matthieu Carré
Harvested from ORCID Public Data FileMatthieu Carré in OpenAIRE Majda Nourelbait; Majda Nourelbait
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMajda Nourelbait in OpenAIRE Louis François; +4 AuthorsLouis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Rachid Cheddadi; Rachid Cheddadi
Harvested from ORCID Public Data FileRachid Cheddadi in OpenAIRE Matthieu Carré; Matthieu Carré
Harvested from ORCID Public Data FileMatthieu Carré in OpenAIRE Majda Nourelbait; Majda Nourelbait
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMajda Nourelbait in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Ali Rhoujjati; Ali Rhoujjati
Harvested from ORCID Public Data FileAli Rhoujjati in OpenAIRE Roger Manay; Roger Manay
Harvested from ORCID Public Data FileRoger Manay in OpenAIRE Diana Ochoa; Diana Ochoa
Harvested from ORCID Public Data FileDiana Ochoa in OpenAIRE Enno Schefuß; Enno Schefuß
Harvested from ORCID Public Data FileEnno Schefuß in OpenAIRESignificance Explaining the greening of the Sahara during the Holocene has been a challenge for decades. A strengthening of the African monsoon caused by increased summer insolation is usually cited to explain why the Sahara was vegetated from 14,000 to 5,000 y ago. Here, we provide a unique climate record of quantified winter, spring, and summer precipitation in Morocco over the past 18,500 y, and numeric simulations, which show that moisture contributions from the Mediterranean Sea and the North Atlantic Ocean in winter, were as important as the expanded summer monsoon for the greening of the Sahara during the African humid period. The findings of this study will help to better understand and simulate climate variability over northern Africa.
Access RoutesGreen hybrid 40 citations 40 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1073/pnas.2024898118&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - NSF| Graduate Research Fellowship Program (GRFP) ,NSF| NRT INFEWS: computational data science to advance research at the energy-environment nexus ,NSF| DMUU: Center for Robust Decision-Making Tools for Climate and Energy Policy James A. Franke;
James A. Franke
Harvested from ORCID Public Data FileJames A. Franke in OpenAIRE Tobias Hank; Elisabeth J. Moyer;Tobias Hank
Harvested from ORCID Public Data FileTobias Hank in OpenAIRE Thomas A. M. Pugh; +18 AuthorsThomas A. M. Pugh
Harvested from ORCID Public Data FileThomas A. M. Pugh in OpenAIRE James A. Franke; James A. Franke
Harvested from ORCID Public Data FileJames A. Franke in OpenAIRE Tobias Hank; Elisabeth J. Moyer;Tobias Hank
Harvested from ORCID Public Data FileTobias Hank in OpenAIRE Thomas A. M. Pugh; Thomas A. M. Pugh;Thomas A. M. Pugh
Harvested from ORCID Public Data FileThomas A. M. Pugh in OpenAIRE Karina Williams; Karina Williams;Karina Williams
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesKarina Williams in OpenAIRE Pete Falloon; Pete Falloon
Harvested from ORCID Public Data FilePete Falloon in OpenAIRE R. Cesar Izaurralde; R. Cesar Izaurralde
Harvested from ORCID Public Data FileR. Cesar Izaurralde in OpenAIRE Jonas Jägermeyr; Jonas Jägermeyr; Jonas Jägermeyr;Jonas Jägermeyr
Harvested from ORCID Public Data FileJonas Jägermeyr in OpenAIRE Louis François; Ingrid Jacquemin; Jens Heinke;Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Wenfeng Liu; Joshua Elliott;Wenfeng Liu
Harvested from ORCID Public Data FileWenfeng Liu in OpenAIRE Christian Folberth; Christian Folberth
Harvested from ORCID Public Data FileChristian Folberth in OpenAIRE Alex C. Ruane; Alex C. Ruane
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesAlex C. Ruane in OpenAIRE Florian Zabel; Florian Zabel
Harvested from ORCID Public Data FileFlorian Zabel in OpenAIRE Christoph Müller; Christoph Müller
Harvested from ORCID Public Data FileChristoph Müller in OpenAIRE Stefan Olin; Stefan Olin
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesStefan Olin in OpenAIREAbstract Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.
Access RoutesGreen gold 71 citations 71 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1748-9326/abd8fc&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - NSF| Graduate Research Fellowship Program (GRFP) ,NSF| NRT INFEWS: computational data science to advance research at the energy-environment nexus ,NSF| DMUU: Center for Robust Decision-Making Tools for Climate and Energy Policy James A. Franke;
James A. Franke
Harvested from ORCID Public Data FileJames A. Franke in OpenAIRE Tobias Hank; Elisabeth J. Moyer;Tobias Hank
Harvested from ORCID Public Data FileTobias Hank in OpenAIRE Thomas A. M. Pugh; +18 AuthorsThomas A. M. Pugh
Harvested from ORCID Public Data FileThomas A. M. Pugh in OpenAIRE James A. Franke; James A. Franke
Harvested from ORCID Public Data FileJames A. Franke in OpenAIRE Tobias Hank; Elisabeth J. Moyer;Tobias Hank
Harvested from ORCID Public Data FileTobias Hank in OpenAIRE Thomas A. M. Pugh; Thomas A. M. Pugh;Thomas A. M. Pugh
Harvested from ORCID Public Data FileThomas A. M. Pugh in OpenAIRE Karina Williams; Karina Williams;Karina Williams
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesKarina Williams in OpenAIRE Pete Falloon; Pete Falloon
Harvested from ORCID Public Data FilePete Falloon in OpenAIRE R. Cesar Izaurralde; R. Cesar Izaurralde
Harvested from ORCID Public Data FileR. Cesar Izaurralde in OpenAIRE Jonas Jägermeyr; Jonas Jägermeyr; Jonas Jägermeyr;Jonas Jägermeyr
Harvested from ORCID Public Data FileJonas Jägermeyr in OpenAIRE Louis François; Ingrid Jacquemin; Jens Heinke;Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRE Wenfeng Liu; Joshua Elliott;Wenfeng Liu
Harvested from ORCID Public Data FileWenfeng Liu in OpenAIRE Christian Folberth; Christian Folberth
Harvested from ORCID Public Data FileChristian Folberth in OpenAIRE Alex C. Ruane; Alex C. Ruane
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesAlex C. Ruane in OpenAIRE Florian Zabel; Florian Zabel
Harvested from ORCID Public Data FileFlorian Zabel in OpenAIRE Christoph Müller; Christoph Müller
Harvested from ORCID Public Data FileChristoph Müller in OpenAIRE Stefan Olin; Stefan Olin
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesStefan Olin in OpenAIREAbstract Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.
Access RoutesGreen gold 71 citations 71 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1748-9326/abd8fc&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Arpita Verma;
Arpita Verma
Harvested from ORCID Public Data FileArpita Verma in OpenAIRE Benjamin Lanssens; Benjamin Lanssens
Harvested from ORCID Public Data FileBenjamin Lanssens in OpenAIRE Merja Tölle; Merja Tölle
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMerja Tölle in OpenAIRE Ingrid Jacquemin; +3 AuthorsIngrid Jacquemin
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesIngrid Jacquemin in OpenAIRE Arpita Verma; Arpita Verma
Harvested from ORCID Public Data FileArpita Verma in OpenAIRE Benjamin Lanssens; Benjamin Lanssens
Harvested from ORCID Public Data FileBenjamin Lanssens in OpenAIRE Merja Tölle; Merja Tölle
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMerja Tölle in OpenAIRE Ingrid Jacquemin; Tarunsinh Chaudhari;Ingrid Jacquemin
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesIngrid Jacquemin in OpenAIRE Alain Hambuckers; Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIREAccurate quantification of carbon dynamics is critical for developing effective climate mitigation strategies. In this study, we employed the CARAIB dynamic vegetation model (DVM) to analyze carbon fluxes and stocks (biomass and total soil carbon) in Wallonia, Belgium (1980-2070), integrating species-level traits, high-resolution land use/land cover (LULC) data, climate data, and type-1 fuzzy logic for uncertainty quantification. We provide insights into ecosystem resilience and carbon sequestration under Representative Concentration Pathways (RCPs) 2.6 and 8.5. Historical results (1980-2020) demonstrated strong model performance, with gross primary production (GPP) validation achieving R2 > 0.85 against MODIS and GOSIF datasets, and aboveground biomass correlating well with GEDI (R2 = 0.77) and ESA-CCI (R2 = 0.91) datasets. Grasslands emerged as critical carbon sinks, exhibiting the highest mean GPP (2480 g C m-2 yr-1), surpassing forests due to rapid growth and belowground carbon storage. Future projections (2021-2070) identified afforestation as a robust mitigation strategy, increasing forest GPP by 18% and total biomass by 60-110 Mt C under RCP 8.5. Under RCP 2.6, total biomass was more stable due to the milder emissions trajectory, emphasizing its potential for long-term ecosystem resilience. Interestingly, total soil carbon showed similar levels across both RCPs, indicating belowground carbon resilience despite emissions differences. Sensitivity analyses of LULC scenarios highlighted grassland resilience, with grasslands sustaining a high GPP (2604-2728 g C m-2 yr-1) and contributing significantly to soil carbon storage, while deforestation caused substantial carbon losses. These findings underscore the need for nuanced land management, integrating afforestation and grassland conservation, to enhance resilience and sustainable carbon sequestration under climate change.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jenvman.2025.124329&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Arpita Verma;
Arpita Verma
Harvested from ORCID Public Data FileArpita Verma in OpenAIRE Benjamin Lanssens; Benjamin Lanssens
Harvested from ORCID Public Data FileBenjamin Lanssens in OpenAIRE Merja Tölle; Merja Tölle
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMerja Tölle in OpenAIRE Ingrid Jacquemin; +3 AuthorsIngrid Jacquemin
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesIngrid Jacquemin in OpenAIRE Arpita Verma; Arpita Verma
Harvested from ORCID Public Data FileArpita Verma in OpenAIRE Benjamin Lanssens; Benjamin Lanssens
Harvested from ORCID Public Data FileBenjamin Lanssens in OpenAIRE Merja Tölle; Merja Tölle
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMerja Tölle in OpenAIRE Ingrid Jacquemin; Tarunsinh Chaudhari;Ingrid Jacquemin
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesIngrid Jacquemin in OpenAIRE Alain Hambuckers; Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIREAccurate quantification of carbon dynamics is critical for developing effective climate mitigation strategies. In this study, we employed the CARAIB dynamic vegetation model (DVM) to analyze carbon fluxes and stocks (biomass and total soil carbon) in Wallonia, Belgium (1980-2070), integrating species-level traits, high-resolution land use/land cover (LULC) data, climate data, and type-1 fuzzy logic for uncertainty quantification. We provide insights into ecosystem resilience and carbon sequestration under Representative Concentration Pathways (RCPs) 2.6 and 8.5. Historical results (1980-2020) demonstrated strong model performance, with gross primary production (GPP) validation achieving R2 > 0.85 against MODIS and GOSIF datasets, and aboveground biomass correlating well with GEDI (R2 = 0.77) and ESA-CCI (R2 = 0.91) datasets. Grasslands emerged as critical carbon sinks, exhibiting the highest mean GPP (2480 g C m-2 yr-1), surpassing forests due to rapid growth and belowground carbon storage. Future projections (2021-2070) identified afforestation as a robust mitigation strategy, increasing forest GPP by 18% and total biomass by 60-110 Mt C under RCP 8.5. Under RCP 2.6, total biomass was more stable due to the milder emissions trajectory, emphasizing its potential for long-term ecosystem resilience. Interestingly, total soil carbon showed similar levels across both RCPs, indicating belowground carbon resilience despite emissions differences. Sensitivity analyses of LULC scenarios highlighted grassland resilience, with grasslands sustaining a high GPP (2604-2728 g C m-2 yr-1) and contributing significantly to soil carbon storage, while deforestation caused substantial carbon losses. These findings underscore the need for nuanced land management, integrating afforestation and grassland conservation, to enhance resilience and sustainable carbon sequestration under climate change.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jenvman.2025.124329&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Alain Hambuckers;
Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRE Simon de Harenne; Eberth Rocha Ledezma; Lilian Zúñiga Zeballos; +1 AuthorsSimon de Harenne
Harvested from ORCID Public Data FileSimon de Harenne in OpenAIRE Alain Hambuckers; Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRE Simon de Harenne; Eberth Rocha Ledezma; Lilian Zúñiga Zeballos;Simon de Harenne
Harvested from ORCID Public Data FileSimon de Harenne in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRESpecies distribution models (SDMs) are commonly used with climate only to predict animal distribution changes. This approach however neglects the evolution of other components of the niche, like food resource availability. SDMs are also commonly used with plants. This also suffers limitations, notably an inability to capture the fertilizing effect of the rising CO2 concentration strengthening resilience to water stress. Alternatively, process-based dynamic vegetation models (DVMs) respond to CO2 concentration. To test the impact of the plant modelling method to model plant resources of animals, we studied the distribution of a Bolivian macaw, assuming that, under future climate, DVMs produce more conservative results than SDMs. We modelled the bird with an SDM driven by climate. For the plant, we used SDMs or a DVM. Under future climates, the macaw SDM showed increased probabilities of presence over the area of distribution and connected range extensions. For plants, SDMs did not forecast overall response. By contrast, the DVM produced increases of productivity, occupancy and diversity, also towards higher altitudes. The results offered positive perspectives for the macaw, more optimistic with the DVM than with the SDMs, than initially assumed. Nevertheless, major common threats remain, challenging the short-term survival of the macaw.
Access Routesgold 5 citations 5 popularity Top 10% influence Average impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/d13020094&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Alain Hambuckers;
Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRE Simon de Harenne; Eberth Rocha Ledezma; Lilian Zúñiga Zeballos; +1 AuthorsSimon de Harenne
Harvested from ORCID Public Data FileSimon de Harenne in OpenAIRE Alain Hambuckers; Alain Hambuckers
Harvested from ORCID Public Data FileAlain Hambuckers in OpenAIRE Simon de Harenne; Eberth Rocha Ledezma; Lilian Zúñiga Zeballos;Simon de Harenne
Harvested from ORCID Public Data FileSimon de Harenne in OpenAIRE Louis François; Louis François
Harvested from ORCID Public Data FileLouis François in OpenAIRESpecies distribution models (SDMs) are commonly used with climate only to predict animal distribution changes. This approach however neglects the evolution of other components of the niche, like food resource availability. SDMs are also commonly used with plants. This also suffers limitations, notably an inability to capture the fertilizing effect of the rising CO2 concentration strengthening resilience to water stress. Alternatively, process-based dynamic vegetation models (DVMs) respond to CO2 concentration. To test the impact of the plant modelling method to model plant resources of animals, we studied the distribution of a Bolivian macaw, assuming that, under future climate, DVMs produce more conservative results than SDMs. We modelled the bird with an SDM driven by climate. For the plant, we used SDMs or a DVM. Under future climates, the macaw SDM showed increased probabilities of presence over the area of distribution and connected range extensions. For plants, SDMs did not forecast overall response. By contrast, the DVM produced increases of productivity, occupancy and diversity, also towards higher altitudes. The results offered positive perspectives for the macaw, more optimistic with the DVM than with the SDMs, than initially assumed. Nevertheless, major common threats remain, challenging the short-term survival of the macaw.
Access Routesgold 5 citations 5 popularity Top 10% influence Average impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/d13020094&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu
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