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2. Understanding water and energy fluxes in the Amazonia: Lessons from an observation‐model intercomparison

Author

Restrepo‐Coupe, Natalia, Albert, Loren P, Longo, Marcos, Baker, Ian, Levine, Naomi M, Mercado, Lina M, Araujo, Alessandro C, Christoffersen, Bradley O'Donnell, Costa, Marcos H, Fitzjarrald, David R, Galbraith, David, Imbuzeiro, Hewlley, Malhi, Yadvinder, Randow, Celso, Zeng, Xubin, Moorcroft, Paul, and Saleska, Scott R

Subjects
Earth Sciences, Biological Sciences, Environmental Sciences, Climate Action, Brazil, Ecosystem, Forests, Seasons, Water, Amazonia, climate interactions, ecosystem, eddy covariance flux seasonality, energy balance, evapotranspiration, land surface models, tropical forests, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land-atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia-along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry-season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%-30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%-15% of incoming solar radiation, compared to 0.15%-0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry-season ET and associated cooling). These partially compensating model-observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (Rn ), the key driver of water and energy fluxes (LE ~ 0.6 Rn and H ~ 0.15 Rn ), though these biases varied among sites and models. A better representation of energy-related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation-atmosphere exchange and reduce uncertainty of regional and global biogeochemical models.

Published
2021

4. Capítulo 23: Impactos de la deforestación y el cambio climático sobre la biodiversidad, los procesos ecológicos y la adaptación ambiental

Author

Artaxo, Paulo, primary, Fonseca de Almeida-Val, Vera Maria, additional, Bilbao, Bibiana, additional, Brando, Paulo M, additional, Bustamante, Mercedes, additional, Coe, Michael T, additional, Correa, Sandra Bibiana, additional, Cuesta, Francisco, additional, Costa, Marcos H, additional, Miralles-Wilhem, Fernando, additional, Salinas, Norma, additional, Silvério, Divino Vicente, additional, and Val, Adalberto Luis, additional

Published
2022
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6. Capítulo 6: Ciclos Biogeoquímicos de la Amazonía

Author

Malhi, Yadvinder, primary, Melack, John, additional, Gatti, Luciana V, additional, Ometto, Jean P, additional, Kesselmeier, Jürgen, additional, Wolff, Stefan, additional, Aragão, Luiz E O, additional, Costa, Marcos H, additional, Saleska, Scott R, additional, Pangala, Sunitha, additional, Basso, Luana S, additional, Rizzo, Luciana, additional, de Araújo, Alessandro C, additional, Restrepo-Coupe, Natalia, additional, and Silva Junior, Celso H L, additional

Published
2022
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11. Chapter 23: Impacts of deforestation and climate change on biodiversity, ecological processes, and environmental adaptation

Author

Artaxo, Paulo, primary, Fonseca de Almeida-Val, Vera Maria, additional, Bilbao, Bibiana, additional, Brando, Paulo M, additional, Bustamante, Mercedes, additional, Coe, Michael T, additional, Correa, Sandra Bibiana, additional, Cuesta, Francisco, additional, Costa, Marcos H, additional, Miralles-Wilhem, Fernando, additional, Salinas, Norma, additional, Silvério, Divino Vicente, additional, and Val, Adalberto Luis, additional

Published
2021
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12. Chapter 6: Biogeochemical Cycles in the Amazon

Author

Malhi, Yadvinder, primary, Melack, John, additional, Gatti, Luciana V, additional, Ometto, Jean P, additional, Kesselmeier, Jürgen, additional, Wolff, Stefan, additional, Aragão, Luiz E O, additional, Costa, Marcos H, additional, Saleska, Scott R, additional, Pangala, Sunitha, additional, Basso, Luana S, additional, Rizzo, Luciana, additional, de Araújo, Alessandro C, additional, Restrepo-Coupe, Natalia, additional, and Silva Junior, Celso H L, additional

Published
2021
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14. Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity

Author

Bustamante, Mercedes MC, Roitman, Iris, Aide, T Mitchell, Alencar, Ane, Anderson, Liana O, Aragão, Luiz, Asner, Gregory P, Barlow, Jos, Berenguer, Erika, Chambers, Jeffrey, Costa, Marcos H, Fanin, Thierry, Ferreira, Laerte G, Ferreira, Joice, Keller, Michael, Magnusson, William E, Morales-Barquero, Lucia, Morton, Douglas, Ometto, Jean PHB, Palace, Michael, Peres, Carlos A, Silvério, Divino, Trumbore, Susan, and Vieira, Ima CG

Subjects
Biological Sciences, Life on Land, Climate Action, Biodiversity, Carbon, Carbon Cycle, Climate Change, Conservation of Natural Resources, Ecosystem, Forestry, Forests, Models, Theoretical, Tropical Climate, carbon emissions, ecosystem modeling, field inventories, forest dynamics, remote sensing, Environmental Sciences, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation.

Published
2016

17. The drivers and impacts of Amazon forest degradation

Author

Lapola, David M., Pinho, Patricia, Barlow, Jos, Aragão, Luiz E. O. C., Berenguer, Erika, Carmenta, Rachel, Liddy, Hannah M., Seixas, Hugo, Silva, Camila V. J., Silva-Junior, Celso H. L., Alencar, Ane A. C., Anderson, Liana O., Armenteras, Dolors, Brovkin, Victor, Calders, Kim, Chambers, Jeffrey, Chini, Louise, Costa, Marcos H., Faria, Bruno L., Fearnside, Philip M., Ferreira, Joice, Gatti, Luciana, Gutierrez-Velez, Victor Hugo, Han, Zhangang, Hibbard, Kathleen, Koven, Charles, Lawrence, Peter, Pongratz, Julia, Portela, Bruno T. T., Rounsevell, Mark, Ruane, Alex C., Schaldach, Rüdiger, da Silva, Sonaira S., von Randow, Celso, Walker, Wayne S., Lapola, David M., Pinho, Patricia, Barlow, Jos, Aragão, Luiz E. O. C., Berenguer, Erika, Carmenta, Rachel, Liddy, Hannah M., Seixas, Hugo, Silva, Camila V. J., Silva-Junior, Celso H. L., Alencar, Ane A. C., Anderson, Liana O., Armenteras, Dolors, Brovkin, Victor, Calders, Kim, Chambers, Jeffrey, Chini, Louise, Costa, Marcos H., Faria, Bruno L., Fearnside, Philip M., Ferreira, Joice, Gatti, Luciana, Gutierrez-Velez, Victor Hugo, Han, Zhangang, Hibbard, Kathleen, Koven, Charles, Lawrence, Peter, Pongratz, Julia, Portela, Bruno T. T., Rounsevell, Mark, Ruane, Alex C., Schaldach, Rüdiger, da Silva, Sonaira S., von Randow, Celso, and Walker, Wayne S.

Abstract

Approximately 2.5 × 10 6 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year −1 ), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year −1 ). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.

Published
2023

19. The drivers and impacts of Amazon forest degradation

Author

Lapola, David M., primary, Pinho, Patricia, additional, Barlow, Jos, additional, Aragão, Luiz E. O. C., additional, Berenguer, Erika, additional, Carmenta, Rachel, additional, Liddy, Hannah M., additional, Seixas, Hugo, additional, Silva, Camila V. J., additional, Silva-Junior, Celso H. L., additional, Alencar, Ane A. C., additional, Anderson, Liana O., additional, Armenteras, Dolors, additional, Brovkin, Victor, additional, Calders, Kim, additional, Chambers, Jeffrey, additional, Chini, Louise, additional, Costa, Marcos H., additional, Faria, Bruno L., additional, Fearnside, Philip M., additional, Ferreira, Joice, additional, Gatti, Luciana, additional, Gutierrez-Velez, Victor Hugo, additional, Han, Zhangang, additional, Hibbard, Kathleen, additional, Koven, Charles, additional, Lawrence, Peter, additional, Pongratz, Julia, additional, Portela, Bruno T. T., additional, Rounsevell, Mark, additional, Ruane, Alex C., additional, Schaldach, Rüdiger, additional, da Silva, Sonaira S., additional, von Randow, Celso, additional, and Walker, Wayne S., additional

Published
2023
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20. Mechanisms of water supply and vegetation demand govern the seasonality and magnitude of evapotranspiration in Amazonia and Cerrado

Author

Christoffersen, Bradley O., Restrepo-Coupe, Natalia, Arain, M Altaf, Baker, Ian T., Cestaro, Bruno P., Ciais, Phillippe, Fisher, Joshua B., Galbraith, David, Guan, Xiaodan, Gulden, Lindsey, van den Hurk, Bart, Ichii, Kazuhito, Imbuzeiro, Hewlley, Jain, Atul, Levine, Naomi, Miguez-Macho, Gonzalo, Poulter, Ben, Roberti, Debora R., Sakaguchi, Koichi, Sahoo, Alok, Schaefer, Kevin, Shi, Mingjie, Verbeeck, Hans, Yang, Zong-Liang, Araújo, Alessandro C., Kruijt, Bart, Manzi, Antonio O., da Rocha, Humberto R., von Randow, Celso, Muza, Michel N., Borak, Jordan, Costa, Marcos H., Gonçalves de Gonçalves, Luis Gustavo, Zeng, Xubin, and Saleska, Scott R.

Published
2014
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21. Inter-annual variability of carbon and water fluxes in Amazonian forest, Cerrado and pasture sites, as simulated by terrestrial biosphere models

Author

von Randow, Celso, Zeri, Marcelo, Restrepo-Coupe, Natalia, Muza, Michel N., de Gonçalves, Luis Gustavo G., Costa, Marcos H., Araujo, Alessandro C., Manzi, Antonio O., da Rocha, Humberto R., Saleska, Scott R., Arain, M. Alaf, Baker, Ian T., Cestaro, Bruno P., Christoffersen, Bradley, Ciais, Philippe, Fisher, Joshua B., Galbraith, David, Guan, Xiaodan, van den Hurk, Bart, Ichii, Kazuhito, Imbuzeiro, Hewlley, Jain, Atul, Levine, Naomi, Miguez-Macho, Gonzalo, Poulter, Ben, Roberti, Debora R., Sahoo, Alok, Schaefer, Kevin, Shi, Mingjie, Tian, Hanqin, Verbeeck, Hans, and Yang, Zong-Liang

Published
2013
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27. Global Carbon and other Biogeochemical Cycles and Feedbacks

Author

Costa, Marcos H., Cotrim da Cunha, Leticia, Cox, Peter M., Eliseev, Alexey V., Hensen, Stephanie, Ishii, Masao, Jaccard, Samuel, Koven, Charles, Lohila, Annalea, Patra, Prabir K., Piao, Shilong, Rogelj, Joeri, Syampungani, Stephen, Zaehle, Sönke, Zickfeld, Kirsten, Alexandrov, Georgii, Bala, Govindasamy, Bopp, Laurent, Boysen, Lena, Cao, Long, Chandra, Naveen, Ciais, Philippe, Denisov, Sergey N., Dentener, Frank J., Douville, Herve, Fay, Amanda, Forster, Piers, Fox-Kemper, Baylor, Friedlingstein, Pierre, Fu, Weiwei, Fuss, Sabine, Garcon, Veronique, Gier, Bettina, Gillett, Nathan P., Gregor, Luke, Haustein, Karsten, Haverd, Vanessa, He, Jian, Hewitt, Helene T., Hoffman, Forrest M., Ilyina, Tatiana, Jackson, Robert, Jones, Christopher, Keller, David P., Kwiatkowski, Lester, Lamboll, Robin D., Lan, Xin, Laufkötter, Charlotte, Le Quere, Corinne, Lenton, Andrew, Lewis, Jared, Liddicoat, Spencer, Lorenzoni, Laura, Lovenduski, Nicole, MacDougall, Andrew H., Mathesius, Sabine, Matthews, Damon H., Meinshausen, Malte, Mokhov, Igor I., Naik, Vaishali, Nicholls, Zebedee R. J., Nurhati, Intan Suci, O'Sullivan, Michael, Peters, Glen, Pongratz, Julia, Poulter, Benjamin, Sallee, Jean-Baptiste, Saunois, Marielle, Schuur, Edward A. G., Seneviratne, Sonia I., Stavert, Ann, Suntharalingam, Parvadha, Tachiiri, Kaoru, Terhaar, Jens, Thompson, Rona, Tian, Hanqin, Turnbull, Jocelyn, Vicente-Serrano, Sergio M., Wang, Xuhui, Wanninkhof, Rik, Williamson, Phil, Masson-Delmotte, V., Zhai, P., Pirani, A., Conners, S. L., Pean, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekci, O., Yu, R., and Zhou, B.

Published
2021

28. Global Carbon and other Biogeochemical Cycles and Feedbacks

Author

Canadell, Josep G., Monteiro, Pedro M.S., Costa, Marcos H., Cunha, Leticia Cotrim Da, Cox, Peter M., Eliseev, Alexey V., Henson, Stephanie, Ishii, Masao, Jaccard, Samuel, Koven, Charles, Lohila, Annalea, Patra, Prabir K., Piao, Shilong, Syampungani, Stephen, Zaehle, Sönke, Zickfeld, Kirsten, Alexandrov, Georgii A., Bala, Govindasamy, Bopp, Laurent, Boysen, Lena, Cao, Long, Chandra, Naveen, Ciais, Philippe, Denisov, Sergey N., Dentener, Frank J., Douville, Hervé, Fay, Amanda, Forster, Piers, Fox-Kemper, Baylor, Friedlingstein, Pierre, Fu, Weiwei, Fuss, Sabine, Garçon, Véronique, Gier, Bettina, Gillett, Nathan P., Gregor, Luke, Haustein, Karsten, Haverd, Vanessa, He, Jian, Hewitt, Helene T., Hoffman, Forrest M., Ilyina, Tatiana, Jackson, Robert, Jones, Christopher, Keller, David P., Kwiatkowski, Lester, Lamboll, Robin D., Lan, Xin, Laufkötter, Charlotte, Quéré, Corinne Le, Lenton, Andrew, Lewis, Jared, Liddicoat, Spencer, Lorenzoni, Laura, Lovenduski, Nicole, Macdougall, Andrew H., Mathesius, Sabine, Matthews, Damon H., Meinshausen, Malte, Mokhov, Igor I., Naik, Vaishali, Nicholls, Zebedee R. J., Nurhati, Intan Suci, O’sullivan, Michael, Peters, Glen, Pongratz, Julia, Poulter, Benjamin, Sallée, Jean-Baptiste, Saunois, Marielle, Schuur, Edward A.G., I.Seneviratne, Sonia, Stavert, Ann, Suntharalingam, Parvadha, Tachiiri, Kaoru, Terhaar, Jens, Thompson, Rona, Tian, Hanqin, Turnbull, Jocelyn, Vicente-Serrano, Sergio M., Wang, Xuhui, Wanninkhof, Rik H., Williamson, Phil, Brovkin, Victor, Feely, Richard A., Lebehot, Alice D., Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Aptel, Florence, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of Exeter, Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of East Anglia [Norwich] (UEA), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Processus et interactions de fine échelle océanique (PROTEO), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, [SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

29. Understanding water and energy fluxes in the Amazonia: Lessons from an observation-model intercomparison.

Author

Restrepo-Coupe, Natalia, Restrepo-Coupe, Natalia, Albert, Loren P, Longo, Marcos, Baker, Ian, Levine, Naomi M, Mercado, Lina M, da Araujo, Alessandro C, Christoffersen, Bradley O'Donnell, Costa, Marcos H, Fitzjarrald, David R, Galbraith, David, Imbuzeiro, Hewlley, Malhi, Yadvinder, von Randow, Celso, Zeng, Xubin, Moorcroft, Paul, Saleska, Scott R, Restrepo-Coupe, Natalia, Restrepo-Coupe, Natalia, Albert, Loren P, Longo, Marcos, Baker, Ian, Levine, Naomi M, Mercado, Lina M, da Araujo, Alessandro C, Christoffersen, Bradley O'Donnell, Costa, Marcos H, Fitzjarrald, David R, Galbraith, David, Imbuzeiro, Hewlley, Malhi, Yadvinder, von Randow, Celso, Zeng, Xubin, Moorcroft, Paul, and Saleska, Scott R

Abstract

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land-atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia-along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry-season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%-30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%-15% of incoming solar radiation, compared to 0.15%-0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry-season ET and associated cooling). These partially compensating model-observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (Rn ), the key driver of water and energy fluxes (LE ~ 0.6 Rn and H ~ 0.15 Rn ), though these biases varied among sites and models. A better representation of energy-related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation-atmosphere exchange and reduce uncertainty of regional a

Published
2021

30. Global Carbon and other Biogeochemical Cycles and Feedbacks

Author

Masson-Delmotte, V., Zhai, P., Pirani, A., Conners, S. L., Pean, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekci, O., Yu, R., Zhou, B., Costa, Marcos H., Cotrim da Cunha, Leticia, Cox, Peter M., Eliseev, Alexey V., Hensen, Stephanie, Ishii, Masao, Jaccard, Samuel, Koven, Charles, Lohila, Annalea, Patra, Prabir K., Piao, Shilong, Rogelj, Joeri, Syampungani, Stephen, Zaehle, Sönke, Zickfeld, Kirsten, Alexandrov, Georgii, Bala, Govindasamy, Bopp, Laurent, Boysen, Lena, Cao, Long, Chandra, Naveen, Ciais, Philippe, Denisov, Sergey N., Dentener, Frank J., Douville, Herve, Fay, Amanda, Forster, Piers, Fox-Kemper, Baylor, Friedlingstein, Pierre, Fu, Weiwei, Fuss, Sabine, Garcon, Veronique, Gier, Bettina, Gillett, Nathan P., Gregor, Luke, Haustein, Karsten, Haverd, Vanessa, He, Jian, Hewitt, Helene T., Hoffman, Forrest M., Ilyina, Tatiana, Jackson, Robert, Jones, Christopher, Keller, David P., Kwiatkowski, Lester, Lamboll, Robin D., Lan, Xin, Laufkötter, Charlotte, Le Quere, Corinne, Lenton, Andrew, Lewis, Jared, Liddicoat, Spencer, Lorenzoni, Laura, Lovenduski, Nicole, MacDougall, Andrew H., Mathesius, Sabine, Matthews, Damon H., Meinshausen, Malte, Mokhov, Igor I., Naik, Vaishali, Nicholls, Zebedee R. J., Nurhati, Intan Suci, O'Sullivan, Michael, Peters, Glen, Pongratz, Julia, Poulter, Benjamin, Sallee, Jean-Baptiste, Saunois, Marielle, Schuur, Edward A. G., Seneviratne, Sonia I., Stavert, Ann, Suntharalingam, Parvadha, Tachiiri, Kaoru, Terhaar, Jens, Thompson, Rona, Tian, Hanqin, Turnbull, Jocelyn, Vicente-Serrano, Sergio M., Wang, Xuhui, Wanninkhof, Rik, Williamson, Phil, Masson-Delmotte, V., Zhai, P., Pirani, A., Conners, S. L., Pean, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekci, O., Yu, R., Zhou, B., Costa, Marcos H., Cotrim da Cunha, Leticia, Cox, Peter M., Eliseev, Alexey V., Hensen, Stephanie, Ishii, Masao, Jaccard, Samuel, Koven, Charles, Lohila, Annalea, Patra, Prabir K., Piao, Shilong, Rogelj, Joeri, Syampungani, Stephen, Zaehle, Sönke, Zickfeld, Kirsten, Alexandrov, Georgii, Bala, Govindasamy, Bopp, Laurent, Boysen, Lena, Cao, Long, Chandra, Naveen, Ciais, Philippe, Denisov, Sergey N., Dentener, Frank J., Douville, Herve, Fay, Amanda, Forster, Piers, Fox-Kemper, Baylor, Friedlingstein, Pierre, Fu, Weiwei, Fuss, Sabine, Garcon, Veronique, Gier, Bettina, Gillett, Nathan P., Gregor, Luke, Haustein, Karsten, Haverd, Vanessa, He, Jian, Hewitt, Helene T., Hoffman, Forrest M., Ilyina, Tatiana, Jackson, Robert, Jones, Christopher, Keller, David P., Kwiatkowski, Lester, Lamboll, Robin D., Lan, Xin, Laufkötter, Charlotte, Le Quere, Corinne, Lenton, Andrew, Lewis, Jared, Liddicoat, Spencer, Lorenzoni, Laura, Lovenduski, Nicole, MacDougall, Andrew H., Mathesius, Sabine, Matthews, Damon H., Meinshausen, Malte, Mokhov, Igor I., Naik, Vaishali, Nicholls, Zebedee R. J., Nurhati, Intan Suci, O'Sullivan, Michael, Peters, Glen, Pongratz, Julia, Poulter, Benjamin, Sallee, Jean-Baptiste, Saunois, Marielle, Schuur, Edward A. G., Seneviratne, Sonia I., Stavert, Ann, Suntharalingam, Parvadha, Tachiiri, Kaoru, Terhaar, Jens, Thompson, Rona, Tian, Hanqin, Turnbull, Jocelyn, Vicente-Serrano, Sergio M., Wang, Xuhui, Wanninkhof, Rik, and Williamson, Phil

Published
2021

33. Tradeoffs in the quest for climate smart agricultural intensification in Mato Grosso, Brazil

Author

Energy System Analysis, Energy and Resources, Gil, Juliana D.B., Garrett, Rachael D., Rotz, Alan, Daioglou, Vassilis, Valentim, Judson, Pires, Gabrielle F., Costa, Marcos H., Lopes, Luciano, Reis, Julio C., Energy System Analysis, Energy and Resources, Gil, Juliana D.B., Garrett, Rachael D., Rotz, Alan, Daioglou, Vassilis, Valentim, Judson, Pires, Gabrielle F., Costa, Marcos H., Lopes, Luciano, and Reis, Julio C.

Published
2018

34. Tradeoffs in the quest for climate smart agricultural intensification in Mato Grosso, Brazil

Author

Gil, Juliana D.B., Garrett, Rachael D., Rotz, Alan, Daioglou, Vassilis, Valentim, Judson, Pires, Gabrielle F., Costa, Marcos H., Lopes, Luciano, Reis, Julio C., Gil, Juliana D.B., Garrett, Rachael D., Rotz, Alan, Daioglou, Vassilis, Valentim, Judson, Pires, Gabrielle F., Costa, Marcos H., Lopes, Luciano, and Reis, Julio C.

Abstract

Low productivity cattle ranching, with its linkages to rural poverty, deforestation and greenhouse gas (GHG) emissions, remains one of the largest sustainability challenges in Brazil and has impacts worldwide. There is a nearly universal call to intensify extensive beef cattle production systems to spare land for crop production and nature and to meet Brazil's Intended Nationally Determined Contribution to reducing global climate change. However, different interventions aimed at the intensification of livestock systems in Brazil may involve substantial social and environmental tradeoffs. Here we examine these tradeoffs using a whole-farm model calibrated for the Brazilian agricultural frontier state of Mato Grosso, one of the largest soybean and beef cattle production regions in the world. Specifically, we compare the costs and benefits of a typical extensive, continuously grazed cattle system relative to a specialized soybean production system and two improved cattle management strategies (rotational grazing and integrated soybean-cattle) under different climate scenarios. We found clear tradeoffs in GHG and nitrogen emissions, climate resilience, and water and energy use across these systems. Relative to continuously grazed or rotationally grazed cattle systems, the integreated soybean-cattle system showed higher food production and lower GHG emissions per unit of human digestible protein, as well as increased resilience under climate change (both in terms of productivity and financial returns). All systems suffered productivity and profitability losses under severe climate change, highlighting the need for climate smart agricultural development strategies in the region. By underscoring the economic feasibility of improving the performance of cattle systems, and by quantifying the tradeoffs of each option, our results are useful for directing agricultural and climate policy.

Published
2018

35. The southern Amazon rainy season: The role of deforestation and its interactions with large‐scale mechanisms.

Author

Leite‐Filho, Argemiro T., Costa, Marcos H., and Fu, Rong

Subjects
*DEFORESTATION, *RAINFALL measurement, *OCEAN temperature, *GEOGRAPHICAL positions
Abstract

Past studies presented evidence that deforestation may affect the precipitation seasonality in southern Amazon. This study uses daily rainfall data from Tropical Rainfall Measurement Mission 3B42 product and a recent yearly 1‐km land use dataset to evaluate the quantitative effects of deforestation on the onset, demise and length of the rainy season in southern Amazon for a period of 15 years (1998–2012). Additionally, we use the Niño4 index, zonal wind data and deforestation data to explain and predict the interannual variability of the onset of the rainy season. During this period, onset has delayed ~0.38 ± 0.05 days per year (5.7 ± 0.75 days in 15 years), demise has advanced 1.34 ± 0.76 days per year (20 ± 11.4 days in 15 years) and the rainy season has shortened by 1.81 ± 0.97 days per year (27 ± 14.5 days in 15 years). Onset, demise and length also present meridional and zonal gradients linked to large‐scale climate mechanisms. After removing the effects related to geographical position and year, we verified a relationship between onset, demise and length and deforestation: Onset delays ~0.4 ± 0.12 day, demise advances ~1.0 ± 0.22 day and length decreases ~0.9 ± 0.34 day per each 10% deforestation increase relative to existing forested area. We also present empirical evidence of the interaction between large‐scale and local‐scale processes, with interannual variation of the onset in the region explained by Niño4 sea surface temperature anomalies, Southern Hemisphere subtropical jet position, deforestation and their interactions (r2 = 69%, p <.001, mean absolute error = 2.7 days). [ABSTRACT FROM AUTHOR]

Published
2020
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38. Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data‐model intercomparison

Author

Restrepo‐Coupe, Natalia, primary, Levine, Naomi M., additional, Christoffersen, Bradley O., additional, Albert, Loren P., additional, Wu, Jin, additional, Costa, Marcos H., additional, Galbraith, David, additional, Imbuzeiro, Hewlley, additional, Martins, Giordane, additional, da Araujo, Alessandro C., additional, Malhi, Yadvinder S., additional, Zeng, Xubin, additional, Moorcroft, Paul, additional, and Saleska, Scott R., additional

Published
2016
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41. Classificação espectral de área plantada com a cultura da cana-de-açúcar por meio da árvore de decisão

Author

Delgado, Rafael C., Sediyama, Gilberto C., Costa, Marcos H., Soares, Vicente P., and Andrade, Ricardo G.

Subjects
sensoriamento remoto, remote sensing, cana-de-açúcar, sugarcane, árvore de decisão, decision tree, SIG, GIS
Abstract

O objetivo deste trabalho foi testar o classificador "árvore de decisão", em dados provenientes de sensores orbitais, para identificar área plantada com cana-de-açúcar, em diferentes épocas de plantio na Fazenda Boa Fé, localizada no Triângulo Mineiro, mais especificamente no município de Conquista, Minas Gerais. Acoplaram-se técnicas de Sensoriamento Remoto (SR) em um módulo de Sistema de Informação Geográfica (SIG), permitindo uma análise temporal do uso e ocupação do solo, especialmente com vistas a identificar e a monitorar as áreas agrícolas. Com base no cálculo do viés médio (VM), o presente estudo mostrou que, em áreas de cana-de-açúcar, onde a irrigação é frequente e ocorrem chuvas significativas que antecedem a passagem do satélite Landsat-5, os valores foram ligeiramente subestimados, com valor deste indicador de -0,13 ha. Foi verificado, também, que os valores de NDVI mais altos proporcionaram uma leve superestimativa dos resultados, com valores de viés médio variando de 0,04 a 0,23 ha. Conforme os resultados, o classificador árvore de decisão apresentou um grande potencial para o mapeamento das áreas cultivadas com cana-de-açúcar. This study was carried out to test the "decision tree" classifier via remote sensing (RS), to identify planted areas with sugarcane, at different planting dates in Boa Fé, located in the Triângulo Mineiro, more specifically in the town of Conquista, Minas Gerais, Brazil. RS techniques, integrated into a Geographic Information System (GIS), allow a temporal analysis of land use and occupation, especially in order to identify and monitor agricultural areas. Based on the calculation of mean bias (VM), this study showed that in areas of sugarcane, where irrigation is frequent and significant rainfall occurring prior to the passage of Landsat-5, the estimated values were slightly underestimated, with the value of this indicator equal to -0.13 ha. It was also verified that the highest values of NDVI provided a slight overestimation of the results, with values of mean bias of 0.04 to 0.23 ha. According to the results, the decision tree classifier had a great potential for mapping the areas cultivated with sugar cane.

Published
2012

42. Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity

Author

Bustamante, Mercedes M. C., primary, Roitman, Iris, additional, Aide, T. Mitchell, additional, Alencar, Ane, additional, Anderson, Liana O., additional, Aragão, Luiz, additional, Asner, Gregory P., additional, Barlow, Jos, additional, Berenguer, Erika, additional, Chambers, Jeffrey, additional, Costa, Marcos H., additional, Fanin, Thierry, additional, Ferreira, Laerte G., additional, Ferreira, Joice, additional, Keller, Michael, additional, Magnusson, William E., additional, Morales-Barquero, Lucia, additional, Morton, Douglas, additional, Ometto, Jean P. H. B., additional, Palace, Michael, additional, Peres, Carlos A., additional, Silvério, Divino, additional, Trumbore, Susan, additional, and Vieira, Ima C. G., additional

Published
2015
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43. The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2, and land use

Author

Zhang, Ke, primary, de Almeida Castanho, Andrea D., additional, Galbraith, David R., additional, Moghim, Sanaz, additional, Levine, Naomi M., additional, Bras, Rafael L., additional, Coe, Michael T., additional, Costa, Marcos H., additional, Malhi, Yadvinder, additional, Longo, Marcos, additional, Knox, Ryan G., additional, McKnight, Shawna, additional, Wang, Jingfeng, additional, and Moorcroft, Paul R., additional

Published
2015
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44. Modelos físico-matemáticos para estimativa da umidade relativa do ar a partir de dados de temperatura

Author

Delgado, Rafael Coll, Sediyama, Gilberto C., Zolnier, Sérgio, and Costa, Marcos H.

Subjects
Climatologia, Psicrometria, Déficit de pressão de vapor d’água
Abstract

A determinação da umidade relativa do ar e o conhecimento de suas interações com outras variáveis meteorológicas são imprescindíveis nas mais diversas atividades agrícolas. Neste trabalho, três modelos físico-matemáticos foram avaliados para a estimativa da umidade relativa do ar a partir de dados de temperatura média horária (T m ) e/ou de um valor de temperatura (T a ) ponderada pelo déficit de pressão de vapor d’água no ar. Valores estimados de umidade relativa do ar foram comparados com os observados em 22 estações meteorológicas automáticas, situadas no Estado de Minas Gerais, durante um período de três meses (10/09/2006 a 10/12/2006). Os resultados demonstraram que a umidade relativa do ar pode ser estimada, satisfatoriamente, a partir de dados de temperatura do ar exclusivamente, desde que a ausência da temperatura do ponto de orvalho (T po ) seja substituída pela temperatura mínima (T n ) ou “T n - 2”, dependendo do modelo de estimativa. Com base no cálculo do erro médio de estimativa (EME), o modelo denomi- nado UR 3 , cujos dados de entrada foram T m , T a e T n , proporcionou melhor desempenho de estimativa, com valores deste indicador variando de -1,18 a 1,96%. Nesse modelo, a umidade relativa foi ligeiramente sub e superestimada em 9 e 13 localidades, respectivamente. Estes resultados sugerem que, para o período considerado, esse método não requer ajustes adicionais para a estimativa da umidade relativa do ar no Estado de Minas Gerais e, portanto, a T n pode ser utilizada para substituir a ausência de dados da T po . Determination of the air relative humidity and the knowledge of its interaction with other meteorological variables are crucial in many agricultural activities. In this work, three physic-mathematical models were evaluated for estimating hourly values of air relative humidity by using average hourly data of air temperature (T m ) and/or a temperature value (T a ) weighed by the air saturation vapor pressure deficit. Estimated values of air relative humidity were compared with observed values obtained from 22 automatic weather stations, located in the State of Minas Gerais, during a three month period (10/09/2006 a 10/12/2006). The results demonstrated that the relative humidity can be satisfactorily estimated by using air temperature exclusively, provided that the absence of dew point temperature (T po ) is replaced by the minimum daily air temperature (T n ) or “T n -2”, depending on the estimating model. Based on the mean bias error (MBE), the model whose input data were T m , T a and T n provided the best estimating performance with values of this statistical indicator ranging from -1.18 to 1.96%. In this model, relative humidity was slightly under and overestimated in 9 and 13 locations, respectively. These results suggest that for the considered period, this method does not require further adjustments for estimating relative humidity in the State of Minas Gerais and, therefore, T n can be used to replace missing data of T po .

Published
2009

45. Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison.

Author

Restrepo‐Coupe, Natalia, Levine, Naomi M., Christoffersen, Bradley O., Albert, Loren P., Wu, Jin, Costa, Marcos H., Galbraith, David, Imbuzeiro, Hewlley, Martins, Giordane, Araujo, Alessandro C., Malhi, Yadvinder S., Zeng, Xubin, Moorcroft, Paul, and Saleska, Scott R.

Subjects
VEGETATION & climate, TROPICAL forests, FORESTRY & climate, PLANT phenology, SOIL moisture
Abstract

To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models ( DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models ( IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity ( GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, 'soil water stress' and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange ( NEE) and respiration ( R e) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and R e consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index ( LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. Correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments. [ABSTRACT FROM AUTHOR]

Published
2017
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47. Pervasive transition of the Brazilian land-use system

Author

Lapola, David M., primary, Martinelli, Luiz A., additional, Peres, Carlos A., additional, Ometto, Jean P. H. B., additional, Ferreira, Manuel E., additional, Nobre, Carlos A., additional, Aguiar, Ana Paula D., additional, Bustamante, Mercedes M. C., additional, Cardoso, Manoel F., additional, Costa, Marcos H., additional, Joly, Carlos A., additional, Leite, Christiane C., additional, Moutinho, Paulo, additional, Sampaio, Gilvan, additional, Strassburg, Bernardo B. N., additional, and Vieira, Ima C. G., additional

Published
2013
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