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1. A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps

Author

Araza, Arnan, de Bruin, Sytze, Herold, Martin, Quegan, Shaun, Labriere, Nicolas, Rodriguez-Veiga, Pedro, Avitabile, Valerio, Santoro, Maurizio, Mitchard, Edward T.A., Ryan, Casey M., Phillips, Oliver L., Willcock, Simon, Verbeeck, Hans, Carreiras, Joao, Hein, Lars, Schelhaas, Mart-Jan, Pacheco-Pascagaza, Ana Maria, da Conceição Bispo, Polyanna, Laurin, Gaia Vaglio, Vieilledent, Ghislain, Slik, Ferry, Wijaya, Arief, Lewis, Simon L., Morel, Alexandra, Liang, Jingjing, Sukhdeo, Hansrajie, Schepaschenko, Dmitry, Cavlovic, Jura, Gilani, Hammad, and Lucas, Richard

Published
2022
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3. Mapping water levels across a region of the Cuvette Centrale peatland complex

Author

Georgiou, Selena, Mitchard, Edward T.A., Crezee, Bart, Dargie, Greta C., Young, Dylan M., Jovani-Sancho, Antonio J., Kitambo, Benjamin, Papa, Fabrice, Bocko, Yannick E., Bola, Pierre, Crabtree, Dafydd E., Emba, Ovide B., Ewango, Corneille E.N., Girkin, Nicholas T., Ifo, Suspense A., Kanyama, Joseph T., Mampouya, Yeto Emmanuel Wenina, Mbemba, Mackline, Ndjango, Jean-Bosco N., Palmer, Paul I., Sjögersten, Sofie, Lewis, Simon L., Georgiou, Selena, Mitchard, Edward T.A., Crezee, Bart, Dargie, Greta C., Young, Dylan M., Jovani-Sancho, Antonio J., Kitambo, Benjamin, Papa, Fabrice, Bocko, Yannick E., Bola, Pierre, Crabtree, Dafydd E., Emba, Ovide B., Ewango, Corneille E.N., Girkin, Nicholas T., Ifo, Suspense A., Kanyama, Joseph T., Mampouya, Yeto Emmanuel Wenina, Mbemba, Mackline, Ndjango, Jean-Bosco N., Palmer, Paul I., Sjögersten, Sofie, and Lewis, Simon L.

Abstract

Inundation dynamics are the primary control on greenhouse gas emissions from peatlands. Situated in the central Congo Basin, the Cuvette Centrale is the largest tropical peatland complex. However, our knowledge of the spatial and temporal variations in its water levels is limited. By addressing this gap, we can quantify the relationship between the Cuvette Centrale’s water levels and greenhouse gas emissions, and further provide a baseline from which deviations caused by climate or land-use change can be observed, and their impacts understood. We present here a novel approach that combines satellite-derived rainfall, evapotranspiration and L-band Synthetic Aperture Radar (SAR) data to estimate spatial and temporal changes in water level across a sub-region of the Cuvette Centrale. Our key outputs are a map showing the spatial distribution of rainfed and flood-prone locations and a daily, 100 m resolution map of peatland water levels. This map is validated using satellite altimetry data and in situ water table data from water loggers. We determine that 50% of peatlands within our study area are largely rainfed, and a further 22.5% are somewhat rainfed, receiving hydrological input mostly from rainfall (directly and via surface/sub-surface inputs in sloped areas). The remaining 27.5% of peatlands are mainly situated in riverine floodplain areas to the east of the Congo River and between the Ubangui and Congo rivers. The mean amplitude of the water level across our study area and over a 20-month period is 22.8 ± 10.1 cm to 1 standard deviation. Maximum temporal variations in water levels occur in the riverine floodplain areas and in the inter-fluvial region between the Ubangui and Congo rivers. Our results show that spatial and temporal changes in water levels can be successfully mapped over tropical peatlands using the pattern of net water input (rainfall minus evapotranspiration, not accounting for run-off) and L-band SAR data.

Published
2023

4. Sociocultural and ecological perspectives on the peatlands of Peruvian Amazonia

Author

Roucoux, Katherine H., primary, Laurie, Nina D., additional, Davies, Althea L., additional, Mitchard, Edward T.A., additional, Honorio Coronado, Euridice N., additional, Martín Brañas, Manuel, additional, Davila, Nallarett, additional, Schulz, Christopher, additional, Andueza, Luis, additional, Cole, Lydia E.S., additional, Wheeler, Charlotte E., additional, Lawson, Ian T., additional, del Aguila Pasquel, Jhon, additional, and del Castillo Torres, Dennis, additional

Published
2023
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5. Les tourbières de la cuvette centrale du bassin du Congo. Réalités et perspectives

Author

Sonwa, Denis Jean, Lewis, Simon L., Ifo, Suspens Averti, Ewango, Corneille, Mitchard, Edward T.A., Dargie, Greta C., Lawson, Ian T., Gourlet-Fleury, Sylvie, Doumenge, Charles, Gond, Valéry, Betbeder, Julie, Kamdem Toham, Andre, Van Offelen, Julie, Kopansky, Dianna, D'Annunzio, Rémi, Monsembula, Raoul, Nuutinen, Maria, Villegas, Laura, Milliken, Kai, Philippon, Nathalie, Bigot, Sylvain, Freeman, Olivia E., Bambuta, Jean-Jacques, Jungers, Quentin, Roman-Cuesta, Rosa, Sonwa, Denis Jean, Lewis, Simon L., Ifo, Suspens Averti, Ewango, Corneille, Mitchard, Edward T.A., Dargie, Greta C., Lawson, Ian T., Gourlet-Fleury, Sylvie, Doumenge, Charles, Gond, Valéry, Betbeder, Julie, Kamdem Toham, Andre, Van Offelen, Julie, Kopansky, Dianna, D'Annunzio, Rémi, Monsembula, Raoul, Nuutinen, Maria, Villegas, Laura, Milliken, Kai, Philippon, Nathalie, Bigot, Sylvain, Freeman, Olivia E., Bambuta, Jean-Jacques, Jungers, Quentin, and Roman-Cuesta, Rosa

Abstract

Au niveau mondial, ce sont les écosystèmes des tourbières, ces zones humides dont le sol présente une accumulation de matière organique partiellement décomposée, qui stockent le volume le plus important de carbone terrestre par unité de surface (Rydin and Jeglum 2006 ; Leifeld and Menichetti 2018). Elles couvrent près de 3 % de la surface terrestre du globe (Yu et al. 2010 ; Page et al. 2011 ; Dargie et al. 2017), ce qui représente plus du carbone total stocké dans la végétation de la Terre et près de deux fois le volume de carbone présent dans ses forêts (Crump 2017). Les tourbières drainées et dégradées émettent énormément de gaz à effet de serre, c'est-à-dire 5 % des émissions mondiales d'origine anthropique (IPCC 2014), qui sont censées augmenter. Par conséquent, la protection et la gestion durable de ces milieux naturels, tout comme des mesures de restauration à prendre d'urgence (notamment par la réhumidification) peuvent éviter des émissions et conserver le carbone stocké dans ces écosystèmes (Leifeld and Menichetti 2018 ; FAO 2020b).

Published
2022

7. High aboveground carbon stock of African tropical montane forests

Author

Cuni-Sanchez, Aida, Sullivan, Martin J.P., Platts, Philip J., Lewis, Simon L., Marchant, Rob, Imani, Gérard, Hubau, Wannes, Abiem, Iveren, Adhikari, Hari, Albrecht, Tomas, Altman, Jan, Amani, Christian, Aneseyee, Abreham B., Avitabile, Valerio, Banin, Lindsay, Batumike, Rodrigue, Bauters, Marijn, Beeckman, Hans, Begne, Serge K., Bennett, Amy C., Bitariho, Robert, Boeckx, Pascal, Bogaert, Jan, Bräuning, Achim, Bulonvu, Franklin, Burgess, Neil D., Calders, Kim, Chapman, Colin, Chapman, Hazel, Comiskey, James, de Haulleville, Thales, Decuyper, Mathieu, DeVries, Ben, Dolezal, Jiri, Droissart, Vincent, Ewango, Corneille, Feyera, Senbeta, Gebrekirstos, Aster, Gereau, Roy, Gilpin, Martin, Hakizimana, Dismas, Hall, Jefferson, Hamilton, Alan, Hardy, Olivier, Hart, Terese, Heiskanen, Janne, Hemp, Andreas, Herold, Martin, Hiltner, Ulrike, Horak, David, Kamdem, Marie-Noel, Kayijamahe, Charles, Kenfack, David, Kinyanjui, Mwangi J., Klein, Julia, Lisingo, Janvier, Lovett, Jon, Lung, Mark, Makana, Jean-Remy, Malhi, Yadvinder, Marshall, Andrew, Martin, Emanuel H., Mitchard, Edward T.A., Morel, Alexandra, Mukendi, John T., Muller, Tom, Nchu, Felix, Nyirambangutse, Brigitte, Okello, Joseph, Peh, Kelvin S.-H., Pellikka, Petri, Phillips, Oliver L., Plumptre, Andrew, Qie, Lan, Rovero, Francesco, Sainge, Moses N., Schmitt, Christine B., Sedlacek, Ondrej, Ngute, Alain S.K., Sheil, Douglas, Sheleme, Demisse, Simegn, Tibebu Y., Simo-Droissart, Murielle, Sonké, Bonaventure, Soromessa, Teshome, Sunderland, Terry, Svoboda, Miroslav, Taedoumg, Hermann, Taplin, James, Taylor, David, Thomas, Sean C., Timberlake, Jonathan, Tuagben, Darlington, Umunay, Peter, Uzabaho, Eustrate, Verbeeck, Hans, Vleminckx, Jason, Wallin, Göran, Wheeler, Charlotte, Willcock, Simon, Woods, John T., Zibera, Etienne, Cuni-Sanchez, Aida, Sullivan, Martin J.P., Platts, Philip J., Lewis, Simon L., Marchant, Rob, Imani, Gérard, Hubau, Wannes, Abiem, Iveren, Adhikari, Hari, Albrecht, Tomas, Altman, Jan, Amani, Christian, Aneseyee, Abreham B., Avitabile, Valerio, Banin, Lindsay, Batumike, Rodrigue, Bauters, Marijn, Beeckman, Hans, Begne, Serge K., Bennett, Amy C., Bitariho, Robert, Boeckx, Pascal, Bogaert, Jan, Bräuning, Achim, Bulonvu, Franklin, Burgess, Neil D., Calders, Kim, Chapman, Colin, Chapman, Hazel, Comiskey, James, de Haulleville, Thales, Decuyper, Mathieu, DeVries, Ben, Dolezal, Jiri, Droissart, Vincent, Ewango, Corneille, Feyera, Senbeta, Gebrekirstos, Aster, Gereau, Roy, Gilpin, Martin, Hakizimana, Dismas, Hall, Jefferson, Hamilton, Alan, Hardy, Olivier, Hart, Terese, Heiskanen, Janne, Hemp, Andreas, Herold, Martin, Hiltner, Ulrike, Horak, David, Kamdem, Marie-Noel, Kayijamahe, Charles, Kenfack, David, Kinyanjui, Mwangi J., Klein, Julia, Lisingo, Janvier, Lovett, Jon, Lung, Mark, Makana, Jean-Remy, Malhi, Yadvinder, Marshall, Andrew, Martin, Emanuel H., Mitchard, Edward T.A., Morel, Alexandra, Mukendi, John T., Muller, Tom, Nchu, Felix, Nyirambangutse, Brigitte, Okello, Joseph, Peh, Kelvin S.-H., Pellikka, Petri, Phillips, Oliver L., Plumptre, Andrew, Qie, Lan, Rovero, Francesco, Sainge, Moses N., Schmitt, Christine B., Sedlacek, Ondrej, Ngute, Alain S.K., Sheil, Douglas, Sheleme, Demisse, Simegn, Tibebu Y., Simo-Droissart, Murielle, Sonké, Bonaventure, Soromessa, Teshome, Sunderland, Terry, Svoboda, Miroslav, Taedoumg, Hermann, Taplin, James, Taylor, David, Thomas, Sean C., Timberlake, Jonathan, Tuagben, Darlington, Umunay, Peter, Uzabaho, Eustrate, Verbeeck, Hans, Vleminckx, Jason, Wallin, Göran, Wheeler, Charlotte, Willcock, Simon, Woods, John T., and Zibera, Etienne

Abstract

Tropical forests store 40–50 per cent of terrestrial vegetation carbon. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests. Owing to climatic and soil changes with increasing elevation, AGC stocks are lower in tropical montane forests compared with lowland forests. Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1–164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network and about 70 per cent and 32 per cent higher than averages from plot networks in montane and lowland forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa. We find that the low stem density and high abundance of large trees of African lowland forests is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse and carbon-rich ecosystems.

Published
2021

8. Pantropical variability in tree crown allometry

Author

Loubota Panzou, Grace Jopaul, Fayolle, Adeline, Jucker, Tommaso, Phillips, Oliver L., Bohlman, Stephanie, Banin, Lindsay F., Lewis, Simon L., Affum‐Baffoe, Kofi, Alves, Luciana F., Antin, Cécile, Arets, Eric, Arroyo, Luzmila, Baker, Timothy R., Barbier, Nicolas, Beeckman, Hans, Berger, Uta, Bocko, Yannick Enock, Bongers, Frans, Bowers, Sam, Brade, Thom, Brondizio, Eduardo S., Chantrain, Arthur, Chave, Jerome, Compaore, Halidou, Coomes, David, Diallo, Adama, Dias, Arildo S., Dimobe, Kangbéni, Djagbletey, Gloria Djaney, Domingues, Tomas, Doucet, Jean‐Louis, Drouet, Thomas, Forni, Eric, Godlee, John L., Goodman, Rosa C., Gourlet‐Fleury, Sylvie, Hien, Fidele, Iida, Yoshiko, Ilondea, Bhely Angoboy, Ilunga Muledi, Jonathan, Jacques, Pierre, Kuyah, Shem, López‐Portillo, Jorge, Loumeto, Jean Joël, Marimon‐Junior, Ben Hur, Marimon, Beatriz Schwantes, Mensah, Sylvanus, Mitchard, Edward T.A., Moncrieff, Glenn R., Narayanan, Ayyappan, O’Brien, Sean T., Ouedraogo, Korotimi, Palace, Michael W., Pelissier, Raphael, Ploton, Pierre, Poorter, Lourens, Ryan, Casey M., Saiz, Gustavo, Santos, Karin, Schlund, Michael, Sellan, Giacomo, Sonke, Bonaventure, Sterck, Frank, Thibaut, Quentin, Van Hoef, Yorick, Veenendaal, Elmar, Vovides, Alejandra G., Xu, Yaozhan, Yao, Tze Leong, Feldpausch, Ted R., Loubota Panzou, Grace Jopaul, Fayolle, Adeline, Jucker, Tommaso, Phillips, Oliver L., Bohlman, Stephanie, Banin, Lindsay F., Lewis, Simon L., Affum‐Baffoe, Kofi, Alves, Luciana F., Antin, Cécile, Arets, Eric, Arroyo, Luzmila, Baker, Timothy R., Barbier, Nicolas, Beeckman, Hans, Berger, Uta, Bocko, Yannick Enock, Bongers, Frans, Bowers, Sam, Brade, Thom, Brondizio, Eduardo S., Chantrain, Arthur, Chave, Jerome, Compaore, Halidou, Coomes, David, Diallo, Adama, Dias, Arildo S., Dimobe, Kangbéni, Djagbletey, Gloria Djaney, Domingues, Tomas, Doucet, Jean‐Louis, Drouet, Thomas, Forni, Eric, Godlee, John L., Goodman, Rosa C., Gourlet‐Fleury, Sylvie, Hien, Fidele, Iida, Yoshiko, Ilondea, Bhely Angoboy, Ilunga Muledi, Jonathan, Jacques, Pierre, Kuyah, Shem, López‐Portillo, Jorge, Loumeto, Jean Joël, Marimon‐Junior, Ben Hur, Marimon, Beatriz Schwantes, Mensah, Sylvanus, Mitchard, Edward T.A., Moncrieff, Glenn R., Narayanan, Ayyappan, O’Brien, Sean T., Ouedraogo, Korotimi, Palace, Michael W., Pelissier, Raphael, Ploton, Pierre, Poorter, Lourens, Ryan, Casey M., Saiz, Gustavo, Santos, Karin, Schlund, Michael, Sellan, Giacomo, Sonke, Bonaventure, Sterck, Frank, Thibaut, Quentin, Van Hoef, Yorick, Veenendaal, Elmar, Vovides, Alejandra G., Xu, Yaozhan, Yao, Tze Leong, and Feldpausch, Ted R.

Abstract

Aim: Tree crowns determine light interception, carbon and water exchange. Thus, understanding the factors causing tree crown allometry to vary at the tree and stand level matters greatly for the development of future vegetation modelling and for the calibration of remote sensing products. Nevertheless, we know little about large‐scale variation and determinants in tropical tree crown allometry. In this study, we explored the continental variation in scaling exponents of site‐specific crown allometry and assessed their relationships with environmental and stand‐level variables in the tropics. Location: Global tropics. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 87,737 trees distributed among 245 forest and savanna sites across the tropics, we fitted site‐specific allometric relationships between crown dimensions (crown depth, diameter and volume) and stem diameter using power‐law models. Stand‐level and environmental drivers of crown allometric relationships were assessed at pantropical and continental scales. Results: The scaling exponents of allometric relationships between stem diameter and crown dimensions were higher in savannas than in forests. We identified that continental crown models were better than pantropical crown models and that continental differences in crown allometric relationships were driven by both stand‐level (wood density) and environmental (precipitation, cation exchange capacity and soil texture) variables for both tropical biomes. For a given diameter, forest trees from Asia and savanna trees from Australia had smaller crown dimensions than trees in Africa and America, with crown volumes for some Asian forest trees being smaller than those of trees in African forests. Main conclusions: Our results provide new insight into geographical variability, with large continental differences in tropical tree crown allometry that were driven by stand‐level and environmental variables. They have implic

Published
2021

9. The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations

Author

Santoro, Maurizio, Cartus, Oliver, Carvalhais, Nuno, Rozendaal, Danaë M.A., Avitabile, Valerio, Araza, Arnan, de Bruin, Sytze, Herold, Martin, Quegan, Shaun, Rodríguez-Veiga, Pedro, Balzter, Heiko, Carreiras, João, Schepaschenko, Dmitry, Korets, Mikhail, Shimada, Masanobu, Itoh, Takuya, Moreno Martínez, Álvaro, Cavlovic, Jura, Cazzolla Gatti, Roberto, Da Conceição Bispo, Polyanna, Dewnath, Nasheta, Labrière, Nicolas, Liang, Jingjing, Lindsell, Jeremy, Mitchard, Edward T.A., Morel, Alexandra, Pacheco Pascagaza, Ana Maria, Ryan, Casey M., Slik, Ferry, Vaglio Laurin, Gaia, Verbeeck, Hans, Wijaya, Arief, Willcock, Simon, Santoro, Maurizio, Cartus, Oliver, Carvalhais, Nuno, Rozendaal, Danaë M.A., Avitabile, Valerio, Araza, Arnan, de Bruin, Sytze, Herold, Martin, Quegan, Shaun, Rodríguez-Veiga, Pedro, Balzter, Heiko, Carreiras, João, Schepaschenko, Dmitry, Korets, Mikhail, Shimada, Masanobu, Itoh, Takuya, Moreno Martínez, Álvaro, Cavlovic, Jura, Cazzolla Gatti, Roberto, Da Conceição Bispo, Polyanna, Dewnath, Nasheta, Labrière, Nicolas, Liang, Jingjing, Lindsell, Jeremy, Mitchard, Edward T.A., Morel, Alexandra, Pacheco Pascagaza, Ana Maria, Ryan, Casey M., Slik, Ferry, Vaglio Laurin, Gaia, Verbeeck, Hans, Wijaya, Arief, and Willcock, Simon

Abstract

The terrestrial forest carbon pool is poorly quantified, in particular in regions with low forest inventory capacity. By combining multiple satellite observations of synthetic aperture radar (SAR) backscatter around the year 2010, we generated a global, spatially explicit dataset of above-ground live biomass (AGB; dry mass) stored in forests with a spatial resolution of 1 ha. Using an extensive database of 110 897 AGB measurements from field inventory plots, we show that the spatial patterns and magnitude of AGB are well captured in our map with the exception of regional uncertainties in high-carbon-stock forests with AGB >250 Mg ha−1, where the retrieval was effectively based on a single radar observation. With a total global AGB of 522 Pg, our estimate of the terrestrial biomass pool in forests is lower than most estimates published in the literature (426–571 Pg). Nonetheless, our dataset increases knowledge on the spatial distribution of AGB compared to the Global Forest Resources Assessment (FRA) by the Food and Agriculture Organization (FAO) and highlights the impact of a country's national inventory capacity on the accuracy of the biomass statistics reported to the FRA. We also reassessed previous remote sensing AGB maps and identified major biases compared to inventory data, up to 120 % of the inventory value in dry tropical forests, in the subtropics and temperate zone. Because of the high level of detail and the overall reliability of the AGB spatial patterns, our global dataset of AGB is likely to have significant impacts on climate, carbon, and socio-economic modelling schemes and provides a crucial baseline in future carbon stock change estimates. The dataset is available at https://doi.org/10.1594/PANGAEA.894711 (Santoro, 2018).

Published
2021

10. Long-term thermal sensitivity of Earth’s tropical forests

Author

Sullivan, Martin J.P., Lewis, Simon L., Affum-Baffoe, Kofi, Castilho, Carolina, Costa, Flávia, Sanchez, Aida Cuni, Ewango, Corneille E.N., Hubau, Wannes, Marimon, Beatriz, Monteagudo-Mendoza, Abel, Qie, Lan, Sonké, Bonaventure, Martinez, Rodolfo Vasquez, Baker, Timothy R., Brienen, Roel J.W., Feldpausch, Ted R., Galbraith, David, Gloor, Manuel, Malhi, Yadvinder, Aiba, Shin-Ichiro, Alexiades, Miguel N., Almeida, Everton C., de Oliveira, Edmar Almeida, Dávila, Esteban Álvarez, Loayza, Patricia Alvarez, Andrade, Ana, Vieira, Simone Aparecida, Aragão, Luiz E.O.C., Araujo-Murakami, Alejandro, Arets, Eric J.M.M., Arroyo, Luzmila, Ashton, Peter, Aymard C., Gerardo, Baccaro, Fabrício B., Banin, Lindsay F., Baraloto, Christopher, Camargo, Plínio Barbosa, Barlow, Jos, Barroso, Jorcely, Bastin, Jean-François, Batterman, Sarah A., Beeckman, Hans, Begne, Serge K., Bennett, Amy C., Berenguer, Erika, Berry, Nicholas, Blanc, Lilian, Boeckx, Pascal, Bogaert, Jan, Bonal, Damien, Bongers, Frans, Bradford, Matt, Brearley, Francis Q., Brncic, Terry, Brown, Foster, Burban, Benoit, Camargo, José Luís, Castro, Wendeson, Céron, Carlos, Ribeiro, Sabina Cerruto, Moscoso, Victor Chama, Chave, Jerôme, Chezeaux, Eric, Clark, Connie J., de Souza, Fernanda Coelho, Collins, Murray, Comiskey, James A., Valverde, Fernando Cornejo, Medina, Massiel Corrales, da Costa, Lola, Dančák, Martin, Dargie, Greta C., Davies, Stuart, Cardozo, Nallaret Davila, de Haulleville, Thales, de Medeiros, Marcelo Brilhante, del Aguila Pasquel, Jhon, Derroire, Géraldine, Di Fiore, Anthony, Doucet, Jean-Louis, Dourdain, Aurélie, Droissart, Vincent, Duque, Luisa Fernanda, Ekoungoulou, Romeo, Elias, Fernando, Erwin, Terry, Esquivel-Muelbert, Adriane, Fauset, Sophie, Ferreira, Joice, Llampazo, Gerardo Flores, Foli, Ernest, Ford, Andrew, Gilpin, Martin, Hall, Jefferson S., Hamer, Keith C., Hamilton, Alan C., Harris, David J., Hart, Terese B., Hédl, Radim, Herault, Bruno, Herrera, Rafael, Higuchi, Niro, Hladik, Annette, Coronado, Eurídice Honorio, Huamantupa-Chuquimaco, Isau, Huasco, Walter Huaraca, Jeffery, Kathryn J., Jimenez-Rojas, Eliana, Kalamandeen, Michelle, Djuikouo, Marie Noël Kamdem, Kearsley, Elizabeth, Umetsu, Ricardo Keichi, Kho, Lip Khoon, Killeen, Timothy, Kitayama, Kanehiro, Klitgaard, Bente, Koch, Alexander, Labrière, Nicolas, Laurance, William, Laurance, Susan, Leal, Miguel E., Levesley, Aurora, Lima, Adriano J.N., Lisingo, Janvier, Lopes, Aline P., Lopez-Gonzalez, Gabriela, Lovejoy, Tom, Lovett, Jon C., Lowe, Richard, Magnusson, William E., Malumbres-Olarte, Jagoba, Manzatto, Ângelo Gilberto, Marimon, Ben Hur, Marshall, Andrew R., Marthews, Toby, de Almeida Reis, Simone Matias, Maycock, Colin, Melgaço, Karina, Mendoza, Casimiro, Metali, Faizah, Mihindou, Vianet, Milliken, William, Mitchard, Edward T.A., Morandi, Paulo S., Mossman, Hannah L., Nagy, Laszlo, Nascimento, Henrique, Neill, David, Nilus, Reuben, Vargas, Percy Núñez, Palacios, Walter, Camacho, Nadir Pallqui, Peacock, Julie, Pendry, Colin, Peñuela Mora, Maria Cristina, Pickavance, Georgia C., Pipoly, John, Pitman, Nigel, Playfair, Maureen, Poorter, Lourens, Poulsen, John R., Poulsen, Axel Dalberg, Preziosi, Richard, Prieto, Adriana, Primack, Richard B., Ramírez-Angulo, Hirma, Reitsma, Jan, Réjou-Méchain, Maxime, Correa, Zorayda Restrepo, de Sousa, Thaiane Rodrigues, Bayona, Lily Rodriguez, Roopsind, Anand, Rudas, Agustín, Rutishauser, Ervan, Abu Salim, Kamariah, Salomão, Rafael P., Schietti, Juliana, Sheil, Douglas, Silva, Richarlly C., Espejo, Javier Silva, Valeria, Camila Silva, Silveira, Marcos, Simo-Droissart, Murielle, Simon, Marcelo Fragomeni, Singh, James, Soto Shareva, Yahn Carlos, Stahl, Clement, Stropp, Juliana, Sukri, Rahayu, Sunderland, Terry, Svátek, Martin, Swaine, Michael D., Swamy, Varun, Taedoumg, Hermann, Talbot, Joey, Taplin, James, Taylor, David, ter Steege, Hans, Terborgh, John, Thomas, Raquel, Thomas, Sean C., Torres-Lezama, Armando, Umunay, Peter, Gamarra, Luis Valenzuela, van der Heijden, Geertje, van der Hout, Peter, van der Meer, Peter, van Nieuwstadt, Mark, Verbeeck, Hans, Vernimmen, Ronald, Vicentini, Alberto, Vieira, Ima Célia Guimarães, Torre, Emilio Vilanova, Vleminckx, Jason, Vos, Vincent, Wang, Ophelia, White, Lee J.T., Willcock, Simon, Woods, John T., Wortel, Verginia, Young, Kenneth, Zagt, Roderick, Zemagho, Lise, Zuidema, Pieter A., Zwerts, Joeri A., Phillips, Oliver L., Sullivan, Martin J.P., Lewis, Simon L., Affum-Baffoe, Kofi, Castilho, Carolina, Costa, Flávia, Sanchez, Aida Cuni, Ewango, Corneille E.N., Hubau, Wannes, Marimon, Beatriz, Monteagudo-Mendoza, Abel, Qie, Lan, Sonké, Bonaventure, Martinez, Rodolfo Vasquez, Baker, Timothy R., Brienen, Roel J.W., Feldpausch, Ted R., Galbraith, David, Gloor, Manuel, Malhi, Yadvinder, Aiba, Shin-Ichiro, Alexiades, Miguel N., Almeida, Everton C., de Oliveira, Edmar Almeida, Dávila, Esteban Álvarez, Loayza, Patricia Alvarez, Andrade, Ana, Vieira, Simone Aparecida, Aragão, Luiz E.O.C., Araujo-Murakami, Alejandro, Arets, Eric J.M.M., Arroyo, Luzmila, Ashton, Peter, Aymard C., Gerardo, Baccaro, Fabrício B., Banin, Lindsay F., Baraloto, Christopher, Camargo, Plínio Barbosa, Barlow, Jos, Barroso, Jorcely, Bastin, Jean-François, Batterman, Sarah A., Beeckman, Hans, Begne, Serge K., Bennett, Amy C., Berenguer, Erika, Berry, Nicholas, Blanc, Lilian, Boeckx, Pascal, Bogaert, Jan, Bonal, Damien, Bongers, Frans, Bradford, Matt, Brearley, Francis Q., Brncic, Terry, Brown, Foster, Burban, Benoit, Camargo, José Luís, Castro, Wendeson, Céron, Carlos, Ribeiro, Sabina Cerruto, Moscoso, Victor Chama, Chave, Jerôme, Chezeaux, Eric, Clark, Connie J., de Souza, Fernanda Coelho, Collins, Murray, Comiskey, James A., Valverde, Fernando Cornejo, Medina, Massiel Corrales, da Costa, Lola, Dančák, Martin, Dargie, Greta C., Davies, Stuart, Cardozo, Nallaret Davila, de Haulleville, Thales, de Medeiros, Marcelo Brilhante, del Aguila Pasquel, Jhon, Derroire, Géraldine, Di Fiore, Anthony, Doucet, Jean-Louis, Dourdain, Aurélie, Droissart, Vincent, Duque, Luisa Fernanda, Ekoungoulou, Romeo, Elias, Fernando, Erwin, Terry, Esquivel-Muelbert, Adriane, Fauset, Sophie, Ferreira, Joice, Llampazo, Gerardo Flores, Foli, Ernest, Ford, Andrew, Gilpin, Martin, Hall, Jefferson S., Hamer, Keith C., Hamilton, Alan C., Harris, David J., Hart, Terese B., Hédl, Radim, Herault, Bruno, Herrera, Rafael, Higuchi, Niro, Hladik, Annette, Coronado, Eurídice Honorio, Huamantupa-Chuquimaco, Isau, Huasco, Walter Huaraca, Jeffery, Kathryn J., Jimenez-Rojas, Eliana, Kalamandeen, Michelle, Djuikouo, Marie Noël Kamdem, Kearsley, Elizabeth, Umetsu, Ricardo Keichi, Kho, Lip Khoon, Killeen, Timothy, Kitayama, Kanehiro, Klitgaard, Bente, Koch, Alexander, Labrière, Nicolas, Laurance, William, Laurance, Susan, Leal, Miguel E., Levesley, Aurora, Lima, Adriano J.N., Lisingo, Janvier, Lopes, Aline P., Lopez-Gonzalez, Gabriela, Lovejoy, Tom, Lovett, Jon C., Lowe, Richard, Magnusson, William E., Malumbres-Olarte, Jagoba, Manzatto, Ângelo Gilberto, Marimon, Ben Hur, Marshall, Andrew R., Marthews, Toby, de Almeida Reis, Simone Matias, Maycock, Colin, Melgaço, Karina, Mendoza, Casimiro, Metali, Faizah, Mihindou, Vianet, Milliken, William, Mitchard, Edward T.A., Morandi, Paulo S., Mossman, Hannah L., Nagy, Laszlo, Nascimento, Henrique, Neill, David, Nilus, Reuben, Vargas, Percy Núñez, Palacios, Walter, Camacho, Nadir Pallqui, Peacock, Julie, Pendry, Colin, Peñuela Mora, Maria Cristina, Pickavance, Georgia C., Pipoly, John, Pitman, Nigel, Playfair, Maureen, Poorter, Lourens, Poulsen, John R., Poulsen, Axel Dalberg, Preziosi, Richard, Prieto, Adriana, Primack, Richard B., Ramírez-Angulo, Hirma, Reitsma, Jan, Réjou-Méchain, Maxime, Correa, Zorayda Restrepo, de Sousa, Thaiane Rodrigues, Bayona, Lily Rodriguez, Roopsind, Anand, Rudas, Agustín, Rutishauser, Ervan, Abu Salim, Kamariah, Salomão, Rafael P., Schietti, Juliana, Sheil, Douglas, Silva, Richarlly C., Espejo, Javier Silva, Valeria, Camila Silva, Silveira, Marcos, Simo-Droissart, Murielle, Simon, Marcelo Fragomeni, Singh, James, Soto Shareva, Yahn Carlos, Stahl, Clement, Stropp, Juliana, Sukri, Rahayu, Sunderland, Terry, Svátek, Martin, Swaine, Michael D., Swamy, Varun, Taedoumg, Hermann, Talbot, Joey, Taplin, James, Taylor, David, ter Steege, Hans, Terborgh, John, Thomas, Raquel, Thomas, Sean C., Torres-Lezama, Armando, Umunay, Peter, Gamarra, Luis Valenzuela, van der Heijden, Geertje, van der Hout, Peter, van der Meer, Peter, van Nieuwstadt, Mark, Verbeeck, Hans, Vernimmen, Ronald, Vicentini, Alberto, Vieira, Ima Célia Guimarães, Torre, Emilio Vilanova, Vleminckx, Jason, Vos, Vincent, Wang, Ophelia, White, Lee J.T., Willcock, Simon, Woods, John T., Wortel, Verginia, Young, Kenneth, Zagt, Roderick, Zemagho, Lise, Zuidema, Pieter A., Zwerts, Joeri A., and Phillips, Oliver L.

Abstract

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate.

Published
2020

11. Asynchronous carbon sink saturation in African and Amazonian tropical forests

Author

Hubau, Wannes, Lewis, Simon L., Phillips, Oliver L., Affum-Baffoe, Kofi, Beeckman, Hans, Cuní-Sanchez, Aida, Daniels, Armandu K., Ewango, Corneille E.N., Fauset, Sophie, Mukinzi, Jacques M., Sheil, Douglas, Sonké, Bonaventure, Sullivan, Martin J.P., Sunderland, Terry C.H., Taedoumg, Hermann, Thomas, Sean C., White, Lee J.T., Abernethy, Katharine A., Adu-Bredu, Stephen, Amani, Christian A., Baker, Timothy R., Banin, Lindsay F., Baya, Fidèle, Begne, Serge K., Bennett, Amy C., Benedet, Fabrice, Bitariho, Robert, Bocko, Yannick E., Boeckx, Pascal, Boundja, Patrick, Brienen, Roel J.W., Brncic, Terry, Chezeaux, Eric, Chuyong, George B., Clark, Connie J., Collins, Murray, Comiskey, James A., Coomes, David A., Dargie, Greta C., de Haulleville, Thales, Kamdem, Marie Noel Djuikouo, Doucet, Jean-Louis, Esquivel-Muelbert, Adriane, Feldpausch, Ted R., Fofanah, Alusine, Foli, Ernest G., Gilpin, Martin, Gloor, Emanuel, Gonmadje, Christelle, Gourlet-Fleury, Sylvie, Hall, Jefferson S., Hamilton, Alan C., Harris, David J., Hart, Terese B., Hockemba, Mireille B.N., Hladik, Annette, Ifo, Suspense A., Jeffery, Kathryn J., Jucker, Tommaso, Yakusu, Emmanuel Kasongo, Kearsley, Elizabeth, Kenfack, David, Koch, Alexander, Leal, Miguel E., Levesley, Aurora, Lindsell, Jeremy A., Lisingo, Janvier, Lopez-Gonzalez, Gabriela, Lovett, Jon C., Makana, Jean-Remy, Malhi, Yadvinder, Marshall, Andrew R., Martin, Jim, Martin, Emanuel H., Mbayu, Faustin M., Medjibe, Vincent P., Mihindou, Vianet, Mitchard, Edward T.A., Moore, Sam, Munishi, Pantaleo K.T., Bengone, Natacha Nssi, Ojo, Lucas, Ondo, Fidèle Evouna, Peh, Kelvin S.-H., Pickavance, Georgia C., Poulsen, Axel Dalberg, Poulsen, John R., Qie, Lan, Reitsma, Jan, Rovero, Francesco, Swaine, Michael D., Talbot, Joey, Taplin, James, Taylor, David M., Thomas, Duncan W., Toirambe, Benjamin, Mukendi, John Tshibamba, Tuagben, Darlington, Umunay, Peter M., van der Heijden, Geertje M. F., Verbeeck, Hans, Vleminckx, Jason, Willcock, Simon, Wöll, Hannsjörg, Woods, John T., Zemagho, Lise, Hubau, Wannes, Lewis, Simon L., Phillips, Oliver L., Affum-Baffoe, Kofi, Beeckman, Hans, Cuní-Sanchez, Aida, Daniels, Armandu K., Ewango, Corneille E.N., Fauset, Sophie, Mukinzi, Jacques M., Sheil, Douglas, Sonké, Bonaventure, Sullivan, Martin J.P., Sunderland, Terry C.H., Taedoumg, Hermann, Thomas, Sean C., White, Lee J.T., Abernethy, Katharine A., Adu-Bredu, Stephen, Amani, Christian A., Baker, Timothy R., Banin, Lindsay F., Baya, Fidèle, Begne, Serge K., Bennett, Amy C., Benedet, Fabrice, Bitariho, Robert, Bocko, Yannick E., Boeckx, Pascal, Boundja, Patrick, Brienen, Roel J.W., Brncic, Terry, Chezeaux, Eric, Chuyong, George B., Clark, Connie J., Collins, Murray, Comiskey, James A., Coomes, David A., Dargie, Greta C., de Haulleville, Thales, Kamdem, Marie Noel Djuikouo, Doucet, Jean-Louis, Esquivel-Muelbert, Adriane, Feldpausch, Ted R., Fofanah, Alusine, Foli, Ernest G., Gilpin, Martin, Gloor, Emanuel, Gonmadje, Christelle, Gourlet-Fleury, Sylvie, Hall, Jefferson S., Hamilton, Alan C., Harris, David J., Hart, Terese B., Hockemba, Mireille B.N., Hladik, Annette, Ifo, Suspense A., Jeffery, Kathryn J., Jucker, Tommaso, Yakusu, Emmanuel Kasongo, Kearsley, Elizabeth, Kenfack, David, Koch, Alexander, Leal, Miguel E., Levesley, Aurora, Lindsell, Jeremy A., Lisingo, Janvier, Lopez-Gonzalez, Gabriela, Lovett, Jon C., Makana, Jean-Remy, Malhi, Yadvinder, Marshall, Andrew R., Martin, Jim, Martin, Emanuel H., Mbayu, Faustin M., Medjibe, Vincent P., Mihindou, Vianet, Mitchard, Edward T.A., Moore, Sam, Munishi, Pantaleo K.T., Bengone, Natacha Nssi, Ojo, Lucas, Ondo, Fidèle Evouna, Peh, Kelvin S.-H., Pickavance, Georgia C., Poulsen, Axel Dalberg, Poulsen, John R., Qie, Lan, Reitsma, Jan, Rovero, Francesco, Swaine, Michael D., Talbot, Joey, Taplin, James, Taylor, David M., Thomas, Duncan W., Toirambe, Benjamin, Mukendi, John Tshibamba, Tuagben, Darlington, Umunay, Peter M., van der Heijden, Geertje M. F., Verbeeck, Hans, Vleminckx, Jason, Willcock, Simon, Wöll, Hannsjörg, Woods, John T., and Zemagho, Lise

Abstract

Structurally intact tropical forests sequestered about half of the global terrestrial carbon uptake over the 1990s and early 2000s, removing about 15 per cent of anthropogenic carbon dioxide emissions. Climate-driven vegetation models typically predict that this tropical forest ‘carbon sink’ will continue for decades. Here we assess trends in the carbon sink using 244 structurally intact African tropical forests spanning 11 countries, compare them with 321 published plots from Amazonia and investigate the underlying drivers of the trends. The carbon sink in live aboveground biomass in intact African tropical forests has been stable for the three decades to 2015, at 0.66 tonnes of carbon per hectare per year (95 per cent confidence interval 0.53–0.79), in contrast to the long-term decline in Amazonian forests. Therefore the carbon sink responses of Earth’s two largest expanses of tropical forest have diverged. The difference is largely driven by carbon losses from tree mortality, with no detectable multi-decadal trend in Africa and a long-term increase in Amazonia. Both continents show increasing tree growth, consistent with the expected net effect of rising atmospheric carbon dioxide and air temperature. Despite the past stability of the African carbon sink, our most intensively monitored plots suggest a post-2010 increase in carbon losses, delayed compared to Amazonia, indicating asynchronous carbon sink saturation on the two continents. A statistical model including carbon dioxide, temperature, drought and forest dynamics accounts for the observed trends and indicates a long-term future decline in the African sink, whereas the Amazonian sink continues to weaken rapidly. Overall, the uptake of carbon into Earth’s intact tropical forests peaked in the 1990s. Given that the global terrestrial carbon sink is increasing in size, independent observations indicating greater recent carbon uptake into the Northern Hemisphere landmass reinforce our conclusion that the intac

Published
2020

12. Data from Sullivan et al. (2020) Long-term thermal sensitivity of Earth’s tropical forests. Science. DOI: 10.1126/science.aaw7578.

Author

Sullivan, Martin J.P., Lewis, Simon L., Affum-Baffoe, Kofi, Castilho, Carolina, Costa, Flávia, Sanchez, Aida Cuni, Ewango, Corneille E.N., Hubau, Wannes, Marimon, Beatriz, Monteagudo-Mendoza, Abel, Qie, Lan, Sonké, Bonaventure, Martinez, Rodolfo Vasquez, Baker, Timothy R., Brienen, Roel J.W., Feldpausch, Ted R., Galbraith, David, Gloor, Manuel, Malhi, Yadvinder, Aiba, Shin Ichiro, Alexiades, Miguel N., Almeida, Everton C., de Oliveira, Edmar Almeida, Dávila, Esteban Álvarez, Loayza, Patricia Alvarez, Andrade, Ana, Vieira, Simone Aparecida, Aragão, Luiz E.O.C., Araujo-Murakami, Alejandro, Arets, Eric J.M.M., Arroyo, Luzmila, Ashton, Peter, Aymard C, Gerardo, Baccaro, Fabrício B., Banin, Lindsay F., Baraloto, Christopher, Camargo, Plínio Barbosa, Barlow, Jos, Barroso, Jorcely, Bastin, Jean François, Batterman, Sarah A., Beeckman, Hans, Begne, Serge K., Bennett, Amy C., Berenguer, Erika, Berry, Nicholas, Blanc, Lilian, Boeckx, Pascal, Bogaert, Jan, Bonal, Damien, Bongers, Frans, Bradford, Matt, Brearley, Francis Q., Brncic, Terry, Brown, Foster, Burban, Benoit, Camargo, José Luís, Castro, Wendeson, Céron, Carlos, Ribeiro, Sabina Cerruto, Moscoso, Victor Chama, Chave, Jerôme, Chezeaux, Eric, Clark, Connie J., de Souza, Fernanda Coelho, Collins, Murray, Comiskey, James A., Valverde, Fernando Cornejo, Medina, Massiel Corrales, da Costa, Lola, Dančák, Martin, Dargie, Greta C., Davies, Stuart, Cardozo, Nallaret Davila, de Haulleville, Thales, de Medeiros, Marcelo Brilhante, Del Aguila Pasquel, Jhon, Derroire, Géraldine, Di Fiore, Anthony, Doucet, Jean Louis, Dourdain, Aurélie, Droissant, Vincent, Duque, Luisa Fernanda, Ekoungoulou, Romeo, Elias, Fernando, Erwin, Terry, Esquivel-Muelbert, Adriane, Fauset, Sophie, Ferreira, Joice, Llampazo, Gerardo Flores, Foli, Ernest, Ford, Andrew, Gilpin, Martin, Hall, Jefferson S., Hamer, Keith C., Hamilton, Alan C., Harris, David J., Hart, Terese B., Hédl, Radim, Herault, Bruno, Herrera, Rafael, Higuchi, Niro, Hladik, Annette, Coronado, Eurídice Honorio, Huamantupa-Chuquimaco, Isau, Huasco, Walter Huaraca, Jeffery, Kathryn J., Jimenez-Rojas, Eliana, Kalamandeen, Michelle, Djuikouo, Marie Noël Kamdem, Kearsley, Elizabeth, Umetsu, Ricardo Keichi, Kho, Lip Khoon, Killeen, Timothy, Kitayama, Kanehiro, Klitgaard, Bente, Koch, Alexander, Labrière, Nicolas, Laurance, William, Laurance, Susan, Leal, Miguel E., Levesley, Aurora, Lima, Adriano J.N., Lisingo, Janvier, Lopes, Aline P., Lopez-Gonzalez, Gabriela, Lovejoy, Tom, Lovett, Jon C., Lowe, Richard, Magnusson, William E., Malumbres-Olarte, Jagoba, Manzatto, Ângelo Gilberto, Marimon, Ben Hur, Marshall, Andrew R., Marthews, Toby, de Almeida Reis, Simone Matias, Maycock, Colin, Melgaço, Karina, Mendoza, Casimiro, Metali, Faizah, Mihindou, Vianet, Milliken, William, Mitchard, Edward T.A., Morandi, Paulo S., Mossman, Hannah L., Nagy, Laszlo, Nascimento, Henrique, Neill, David, Nilus, Reuben, Vargas, Percy Núñez, Palacios, Walter, Camacho, Nadir Pallqui, Peacock, Julie, Pendry, Colin, Peñuela Mora, Maria Cristina, Pickavance, Georgia C., Pipoly, John, Pitman, Nigel, Playfair, Maureen, Poorter, Lourens, Poulsen, John R., Poulsen, Axel Dalberg, Preziosi, Richard, Prieto, Adriana, Primack, Richard B., Ramírez-Angulo, Hirma, Reitsma, Jan, Réjou-Méchain, Maxime, Correa, Zorayda Restrepo, de Sousa, Thaiane Rodrigues, Bayona, Lily Rodriguez, Roopsind, Anand, Rudas, Agustín, Rutishauser, Ervan, Abu Salim, Kamariah, Salomão, Rafael P., Schietti, Juliana, Sheil, Douglas, Silva, Richarlly C., Espejo, Javier Silva, Valeria, Camila Silva, Silveira, Marcos, Simo-Droissart, Murielle, Simon, Marcelo Fragomeni, Singh, James, Soto Shareva, Yahn Carlos, Stahl, Clement, Stropp, Juliana, Sukri, Rahayu, Sunderland, Terry, Svátek, Martin, Swaine, Michael D., Swamy, Varun, Taedoumg, Hermann, Talbot, Joey, Taplin, James, Taylor, David, Ter Steege, Hans, Terborgh, John, Thomas, Raquel, Thomas, Sean C., Torres-Lezama, Armando, Umunay, Peter, Gamarra, Luis Valenzuela, van der Heijden, Geertje, van der Hout, Peter, van der Meer, Peter, van Nieuwstadt, Mark, Verbeeck, Hans, Vernimmen, Ronald, Vicentini, Alberto, Vieira, Ima Célia Guimarães, Torre, Emilio Vilanova, Vleminckx, Jason, Vos, Vincent, Wang, Ophelia, White, Lee J.T., Willcock, Simon, Woods, John T., Wortel, Verginia, Young, Kenneth, Zagt, Roderick, Zemagho, Lise, Zuidema, Pieter A., Zwerts, Joeri A., Phillips, Oliver L., Sullivan, Martin J.P., Lewis, Simon L., Affum-Baffoe, Kofi, Castilho, Carolina, Costa, Flávia, Sanchez, Aida Cuni, Ewango, Corneille E.N., Hubau, Wannes, Marimon, Beatriz, Monteagudo-Mendoza, Abel, Qie, Lan, Sonké, Bonaventure, Martinez, Rodolfo Vasquez, Baker, Timothy R., Brienen, Roel J.W., Feldpausch, Ted R., Galbraith, David, Gloor, Manuel, Malhi, Yadvinder, Aiba, Shin Ichiro, Alexiades, Miguel N., Almeida, Everton C., de Oliveira, Edmar Almeida, Dávila, Esteban Álvarez, Loayza, Patricia Alvarez, Andrade, Ana, Vieira, Simone Aparecida, Aragão, Luiz E.O.C., Araujo-Murakami, Alejandro, Arets, Eric J.M.M., Arroyo, Luzmila, Ashton, Peter, Aymard C, Gerardo, Baccaro, Fabrício B., Banin, Lindsay F., Baraloto, Christopher, Camargo, Plínio Barbosa, Barlow, Jos, Barroso, Jorcely, Bastin, Jean François, Batterman, Sarah A., Beeckman, Hans, Begne, Serge K., Bennett, Amy C., Berenguer, Erika, Berry, Nicholas, Blanc, Lilian, Boeckx, Pascal, Bogaert, Jan, Bonal, Damien, Bongers, Frans, Bradford, Matt, Brearley, Francis Q., Brncic, Terry, Brown, Foster, Burban, Benoit, Camargo, José Luís, Castro, Wendeson, Céron, Carlos, Ribeiro, Sabina Cerruto, Moscoso, Victor Chama, Chave, Jerôme, Chezeaux, Eric, Clark, Connie J., de Souza, Fernanda Coelho, Collins, Murray, Comiskey, James A., Valverde, Fernando Cornejo, Medina, Massiel Corrales, da Costa, Lola, Dančák, Martin, Dargie, Greta C., Davies, Stuart, Cardozo, Nallaret Davila, de Haulleville, Thales, de Medeiros, Marcelo Brilhante, Del Aguila Pasquel, Jhon, Derroire, Géraldine, Di Fiore, Anthony, Doucet, Jean Louis, Dourdain, Aurélie, Droissant, Vincent, Duque, Luisa Fernanda, Ekoungoulou, Romeo, Elias, Fernando, Erwin, Terry, Esquivel-Muelbert, Adriane, Fauset, Sophie, Ferreira, Joice, Llampazo, Gerardo Flores, Foli, Ernest, Ford, Andrew, Gilpin, Martin, Hall, Jefferson S., Hamer, Keith C., Hamilton, Alan C., Harris, David J., Hart, Terese B., Hédl, Radim, Herault, Bruno, Herrera, Rafael, Higuchi, Niro, Hladik, Annette, Coronado, Eurídice Honorio, Huamantupa-Chuquimaco, Isau, Huasco, Walter Huaraca, Jeffery, Kathryn J., Jimenez-Rojas, Eliana, Kalamandeen, Michelle, Djuikouo, Marie Noël Kamdem, Kearsley, Elizabeth, Umetsu, Ricardo Keichi, Kho, Lip Khoon, Killeen, Timothy, Kitayama, Kanehiro, Klitgaard, Bente, Koch, Alexander, Labrière, Nicolas, Laurance, William, Laurance, Susan, Leal, Miguel E., Levesley, Aurora, Lima, Adriano J.N., Lisingo, Janvier, Lopes, Aline P., Lopez-Gonzalez, Gabriela, Lovejoy, Tom, Lovett, Jon C., Lowe, Richard, Magnusson, William E., Malumbres-Olarte, Jagoba, Manzatto, Ângelo Gilberto, Marimon, Ben Hur, Marshall, Andrew R., Marthews, Toby, de Almeida Reis, Simone Matias, Maycock, Colin, Melgaço, Karina, Mendoza, Casimiro, Metali, Faizah, Mihindou, Vianet, Milliken, William, Mitchard, Edward T.A., Morandi, Paulo S., Mossman, Hannah L., Nagy, Laszlo, Nascimento, Henrique, Neill, David, Nilus, Reuben, Vargas, Percy Núñez, Palacios, Walter, Camacho, Nadir Pallqui, Peacock, Julie, Pendry, Colin, Peñuela Mora, Maria Cristina, Pickavance, Georgia C., Pipoly, John, Pitman, Nigel, Playfair, Maureen, Poorter, Lourens, Poulsen, John R., Poulsen, Axel Dalberg, Preziosi, Richard, Prieto, Adriana, Primack, Richard B., Ramírez-Angulo, Hirma, Reitsma, Jan, Réjou-Méchain, Maxime, Correa, Zorayda Restrepo, de Sousa, Thaiane Rodrigues, Bayona, Lily Rodriguez, Roopsind, Anand, Rudas, Agustín, Rutishauser, Ervan, Abu Salim, Kamariah, Salomão, Rafael P., Schietti, Juliana, Sheil, Douglas, Silva, Richarlly C., Espejo, Javier Silva, Valeria, Camila Silva, Silveira, Marcos, Simo-Droissart, Murielle, Simon, Marcelo Fragomeni, Singh, James, Soto Shareva, Yahn Carlos, Stahl, Clement, Stropp, Juliana, Sukri, Rahayu, Sunderland, Terry, Svátek, Martin, Swaine, Michael D., Swamy, Varun, Taedoumg, Hermann, Talbot, Joey, Taplin, James, Taylor, David, Ter Steege, Hans, Terborgh, John, Thomas, Raquel, Thomas, Sean C., Torres-Lezama, Armando, Umunay, Peter, Gamarra, Luis Valenzuela, van der Heijden, Geertje, van der Hout, Peter, van der Meer, Peter, van Nieuwstadt, Mark, Verbeeck, Hans, Vernimmen, Ronald, Vicentini, Alberto, Vieira, Ima Célia Guimarães, Torre, Emilio Vilanova, Vleminckx, Jason, Vos, Vincent, Wang, Ophelia, White, Lee J.T., Willcock, Simon, Woods, John T., Wortel, Verginia, Young, Kenneth, Zagt, Roderick, Zemagho, Lise, Zuidema, Pieter A., Zwerts, Joeri A., and Phillips, Oliver L.

Abstract

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater rate of decline in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate., The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater rate of decline in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate.

Published
2020

15. Extending the baseline of tropical dry forest loss in Ghana (1984–2015) reveals drivers of major deforestation inside a protected area

Author

Janssen, Thomas A.J., Ametsitsi, George K.D., Collins, Murray, Adu-Bredu, Stephen, Oliveras, Imma, Mitchard, Edward T.A., Veenendaal, Elmar M., and Earth and Climate

Subjects
Life Science, Plantenecologie en Natuurbeheer, Plant Ecology and Nature Conservation, PE&RC, SDG 15 - Life on Land
Abstract

Tropical dry forests experience the highest deforestation rates on Earth, with major implications for the biodiversity of these ecosystems, as well as for its human occupants. Global remote sensing based forest cover data (2000 − 2012) point to the rapid loss of tropical dry forest in South America and Africa, also, if not foremost, inside formally protected areas. Here, we significantly extend the baseline of tropical dry forest loss inside a protected area in Ghana using a generalizable change detection technique. The forest cover change detection is based on the normalized difference vegetation index (NDVI) derived from historical Landsat data (1984–2015). Field measurements were carried out in dry semi-deciduous forest and in the adjacent savanna and woodland. Estimates of the canopy area index and above ground woody biomass were related to NDVI derived from Landsat 8 data. The change detection indicated significant NDVI decrease in a large area initially covered by tropical dry forest, associated with deforestation. The peak in deforestation was found to have occurred between 1990 and 2002, hereafter, the conservation status of the area was improved. A combination of remote sensing data corroborated by secondary data sources provides evidence for the almost complete clearance of a tropical dry forest inside a strictly protected area, attributable to logging and land clearing for arable farming. The NDVI change detection also revealed NDVI increase in the adjacent woodlands from 2002 to 2015, demonstrating woody encroachment. Historical fire data from the MODIS burned area product indicate that the deforested area experienced a high frequency of anthropogenic burning since 2004, which may have caused further degradation and largely prevents forest regeneration. The results show the ongoing destruction of tropical ecosystems even within ostensibly protected areas and ask for the revision of protection and management strategies of such areas.

Published
2018

16. Implications of the World Bank's environmental and social framework for biodiversity.

Author

Morley, Jonathan, Buchanan, Graeme, Mitchard, Edward T.A., and Keane, Aidan

Subjects
BIODIVERSITY, BANK accounts, BANKING industry, ENVIRONMENTAL policy
Abstract

The World Bank is the single largest source of development finance, with wide‐reaching influence. The Bank's safeguards aim to minimize the negative impacts of the projects it funds. These policies have recently been updated in a new Environmental and Social Framework. For conservation, the key changes include a mechanism for the use of biodiversity offsets and borrowers' own frameworks to manage impacts. Concerns have been raised that these changes may weaken protections as there is substantial flexibility about when offsets or borrowers' frameworks can be used, and uncertainty around the efficacy of offsets. The project‐by‐project nature of these mechanisms and the lack of clear criteria may also hinder future efforts to hold the Bank to account. Concerns about these changes were raised by conservation organizations during the consultation process, but the framework's formulation does not fully reflect recommendations made. Although elements of the new policy have the potential to benefit conservation, the flexibility presents a risk to biodiversity. It is vital for conservation organizations to engage effectively to ensure that any negative impacts arising do not go unchallenged. [ABSTRACT FROM AUTHOR]

Published
2021
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17. Phenotypic plasticity of hermaphrodite sex allocation promotes the evolution of separate sexes: an experimental test of the sex-differential plasticity hypothesis using Sagittaria latifolia (Alismataceae)

Author

Dorken, Marcel E. and Mitchard, Edward T.A.

Subjects
Hermaphroditism -- Analysis, Biological sciences
Abstract

Several experiments on the aquatic herb, Sagittaria latifolia (Alismataceae) are conducted to test the sex-differential plasticity hypothesis, which says that the phenotypic plasticity of hermaphrodite sex allocation promotes the evolution of separate sexes.

Published
2008

18. An integrated pan-tropical biomass map using multiple reference datasets

Author

Avitabile, Valerio, Herold, Martin, Heuvelink, Gerard B.M., Lewis, Simon L., Phillips, Oliver L., Asner, Gregory P., Armston, John, Ashton, Peter S., Banin, Lindsay, Bayol, Nicolas, Berry, Nicholas J., Boeckx, Pascal, de Jong, Bernardus H.J., DeVries, Ben, Girardin, Cecile A.J., Kearsley, Elizabeth, Lindsell, Jeremy A., Lopez-Gonzalez, Gabriela, Lucas, Richard, Malhi, Yadvinder, Morel, Alexandra, Mitchard, Edward T.A., Nagy, Laszlo, Qie, Lan, Quinones, Marcela J., Ryan, Casey M., Ferry, Slik J.W., Sunderland, Terry, Laurin, Gaia Vaglio, Gatti, Roberto Cazzolla, Valentini, Riccardo, Verbeeck, Hans, Wijaya, Arief, Willcock, Simon, Avitabile, Valerio, Herold, Martin, Heuvelink, Gerard B.M., Lewis, Simon L., Phillips, Oliver L., Asner, Gregory P., Armston, John, Ashton, Peter S., Banin, Lindsay, Bayol, Nicolas, Berry, Nicholas J., Boeckx, Pascal, de Jong, Bernardus H.J., DeVries, Ben, Girardin, Cecile A.J., Kearsley, Elizabeth, Lindsell, Jeremy A., Lopez-Gonzalez, Gabriela, Lucas, Richard, Malhi, Yadvinder, Morel, Alexandra, Mitchard, Edward T.A., Nagy, Laszlo, Qie, Lan, Quinones, Marcela J., Ryan, Casey M., Ferry, Slik J.W., Sunderland, Terry, Laurin, Gaia Vaglio, Gatti, Roberto Cazzolla, Valentini, Riccardo, Verbeeck, Hans, Wijaya, Arief, and Willcock, Simon

Abstract

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N–23.4 S) of 375 Pg dry mass, 9–18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15–21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha−1 vs. 21 and 28 Mg ha−1 for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.

Published
2016

19. Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites

Author

Mitchard, Edward T.A, Feldpausch, T R, Brienen, Roel J.W., Lopez-Gonzalez, Gabriela, Monteagudo, Abel, Baker, Timothy R, Lewis, Simon, Lloyd, Jon, Quesada, Carlos A., Gloor, Manuel, ter Steege, Hans, Meir, Patrick, Mitchard, Edward T.A, Feldpausch, T R, Brienen, Roel J.W., Lopez-Gonzalez, Gabriela, Monteagudo, Abel, Baker, Timothy R, Lewis, Simon, Lloyd, Jon, Quesada, Carlos A., Gloor, Manuel, ter Steege, Hans, and Meir, Patrick

Abstract

Aim: The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Location: Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1 Methods: Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. Results: The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by >25%, whereas regional uncertainties for the maps were reported to be <5%. Main conclusions: Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because

Published
2014

20. Fusing radar and optical remote sensing for biomass prediction in mountainous tropical forests

Author

Fedrigo, Melissa, Meir, Patrick, Sheil, Douglas, Van Heist, Miriam, Woodhouse, Iain H, Mitchard, Edward T.A, Fedrigo, Melissa, Meir, Patrick, Sheil, Douglas, Van Heist, Miriam, Woodhouse, Iain H, and Mitchard, Edward T.A

Abstract

Field measured estimates of aboveground biomass (AGB) in the mountainous region of Bwindi Impenetrable National Park ('Bwindi'), Uganda were used to train remote sensing models in order to estimate AGB within the park. AGB estimates were extrapolated usin

Published
2013

21. A novel application of satellite radar data: Measuring carbon sequestration and detecting degradation in a community forestry project in Mozambique

Author

Mitchard, Edward T.A, Meir, Patrick, Ryan, Casey M, Woollen, Emily S, Williams, Mathew, Goodman, Lucy E, Mucavele, Joey A, Watts , Paul, Woodhouse, Iain H, Saatchi, Sassan S, Mitchard, Edward T.A, Meir, Patrick, Ryan, Casey M, Woollen, Emily S, Williams, Mathew, Goodman, Lucy E, Mucavele, Joey A, Watts , Paul, Woodhouse, Iain H, and Saatchi, Sassan S

Abstract

Background: It is essential that systems for measuring changes in carbon stocks for Reducing Emissions from Deforestation and Forest Degradation (REDD) projects are accurate, reliable and low cost. Widely used systems involving classifying optical satelli

Published
2013

22. Mapping tropical forest biomass with radar and spaceborne LiDAR in Lope National Park, Gabon: Overcoming problems of high biomass and persistent cloud

Author

Mitchard, Edward T.A, Saatchi, Sassan S, White, L J T, Abernethy, K A, Jeffery, K J, Lewis, S. L., Collins, Murray, Lefsky, Michael Andrew, Leal, Miguel E., Woodhouse, Iain H, Meir, Patrick, Mitchard, Edward T.A, Saatchi, Sassan S, White, L J T, Abernethy, K A, Jeffery, K J, Lewis, S. L., Collins, Murray, Lefsky, Michael Andrew, Leal, Miguel E., Woodhouse, Iain H, and Meir, Patrick

Abstract

Spatially-explicit maps of aboveground biomass are essential for calculating the losses and gains in forest carbon at a regional to national level. The production of such maps across wide areas will become increasingly necessary as international efforts to protect primary forests, such as the REDD+ (Reducing Emissions from Deforestation and forest Degradation) mechanism, come into effect, alongside their use for management and research more generally. However, mapping biomass over high-biomass tropical forest is challenging as (1) direct regressions with optical and radar data saturate, (2) much of the tropics is persistently cloud-covered, reducing the availability of optical data, (3) many regions include steep topography, making the use of radar data complex, (5) while LiDAR data does not suffer from saturation, expensive aircraft-derived data are necessary for complete coverage. We present a solution to the problems, using a combination of terrain-corrected L-band radar data (ALOS PALSAR), spaceborne LiDAR data (ICESat GLAS) and ground-based data. We map Gabon's Lopé National Park (5000 km2) because it includes a range of vegetation types from savanna to closed-canopy tropical forest, is topographically complex, has no recent contiguous cloud-free high-resolution optical data, and the dense forest is above the saturation point for radar. Our 100 m resolution biomass map is derived from fusing spaceborne LiDAR (7142 ICESat GLAS footprints), 96 ground-based plots (average size 0.8 ha) and an unsupervised classification of terrain-corrected ALOS PALSAR radar data, from which we derive the aboveground biomass stocks of the park to be 78 Tg C (173 Mg C ha-1). This value is consistent with our field data average of 181 Mg C ha-1, from the field plots measured in 2009 covering a total of 78 ha, and which are independent as they were not used for the GLAS-biomass estimation. We estimate an uncertainty of ± 25% on our carbon stock value for the park. This error term incl

Published
2012

23. Measuring biomass changes due to woody encroachment and deforestation/degradation in a forest-savanna boundary region of central Africa using multi-temporal L-band radar backscatter

Author

Mitchard, Edward T.A, Saatchi, Sassan S, Lewis, S. L., Feldpausch, T R, Woodhouse, Iain H, Sonké, B, Rowland, C, Meir, Patrick, Mitchard, Edward T.A, Saatchi, Sassan S, Lewis, S. L., Feldpausch, T R, Woodhouse, Iain H, Sonké, B, Rowland, C, and Meir, Patrick

Abstract

Satellite L-band synthetic aperture radar backscatter data from 1996 and 2007 (from JERS-1 and ALOS PALSAR respectively), were used with field data collected in 2007 and a back-calibration method to produce biomass maps of a 15000km2 forest-savanna ecotone region of central Cameroon. The relationship between the radar backscatter and aboveground biomass (AGB) was strong (r2=0.86 for ALOS HV to biomass plots, r2=0.95 relating ALOS-derived biomass for 40 suspected unchanged regions to JERS-1 HH). The root mean square error (RMSE) associated with AGB estimation varied from ~25% for AGB<100Mgha-1 to ~40% for AGB>100Mgha-1 for the ALOS HV data. Change detection showed a significant loss of AGB over high biomass forests, due to suspected deforestation and degradation, and significant biomass gains along the forest-savanna boundary, particularly in areas of low population density. Analysis of the errors involved showed that radar data can detect changes in broad AGB class in forest-savanna transition areas with an accuracy >95%. However, quantitative assessment of changes in AGB in Mgha-1 at a pixel level will require radar images from sensors with similar characteristics collecting data from the same season over multiple years.

Published
2011

24. Comment on 'A first map of tropical Africa's above-ground biomass derived from satellite imagery'

Author

Mitchard, Edward T.A, Saatchi, Sassan S, Lewis , S. L., Feldpausch, T R, Gerard, F F, Woodhouse, Iain H, Meir, Patrick, Mitchard, Edward T.A, Saatchi, Sassan S, Lewis , S. L., Feldpausch, T R, Gerard, F F, Woodhouse, Iain H, and Meir, Patrick

Abstract

We present a critical evaluation of the above-ground biomass (AGB) map of Africa published in this journal by Baccini et al (2008 Environ. Res. Lett. 3 045011). We first test their map against an independent dataset of 1154 scientific inventory plots from 16 African countries, and find only weak correspondence between our field plots and the AGB value given for the surrounding 1km pixel by Baccini et al. Separating our field data using a continental landcover classification suggests that the Baccini et al map underestimates the AGB of forests and woodlands, while overestimating the AGB of savannas and grasslands. Secondly, we compare their map to 216 000 × 0.25ha spaceborne LiDAR footprints. A comparison between Lorey's height (basal-area-weighted average height) derived from the LiDAR data for 1km pixels containing at least five LiDAR footprints again does not support the hypothesis that the Baccini et al map is accurate, and suggests that it significantly underestimates the AGB of higher AGB areas. We conclude that this is due to the unsuitability of some of the field data used by Baccini et al to create their map, and overfitting in their model, resulting in low accuracies outside the small areas from which their field data are drawn.

Published
2011

25. A Biomass map of Africa's woodlands and savannas

Author

Mitchard, Edward T.A., Meir, Patrick, Saatchi, Sassan S., Gerard, France, Mitchard, Edward T.A., Meir, Patrick, Saatchi, Sassan S., and Gerard, France

Abstract

We present the first high-resolution (500 m) map of biomass covering the woodlands and savannas of Africa. This is based on 9.5 years of daily remote sensing data and a unique dataset of over 3000 biomass plots from 11 countries across the continent. The few extant global maps are of too low resolution to be of much use for conservation planning or estimating carbon stocks and emissions accurately in this ecosystem, as savannas and woodlands are highly heterogeneous at every scale. Hitherto, the one Africa-specific map that has been published at a relatively high resolution (1 km) [1] is focused on forests, and only covers a small subset of the African continent. Our data from savannas, woodlands and forest-savanna transition regions across the continent should produce a map of higher accuracy for these biomes.

Published
2010

26. Using satellite radar backscatter to predict above-ground woody biomass: A consistent relationship across four different African landscapes

Author

Mitchard, Edward T.A, Saatchi, Sassan S, Woodhouse, Iain H, Nangendo, G, Ribeiro, N S, Williams, Mathew, Ryan, Casey M, Lewis, S. L., Feldpausch, T R, Meir, Patrick, Mitchard, Edward T.A, Saatchi, Sassan S, Woodhouse, Iain H, Nangendo, G, Ribeiro, N S, Williams, Mathew, Ryan, Casey M, Lewis, S. L., Feldpausch, T R, and Meir, Patrick

Abstract

Regional-scale above-ground biomass (AGB) estimates of tropical savannas and woodlands are highly uncertain, despite their global importance for ecosystems services and as carbon stores. In response, we collated field inventory data from 253 plots at four study sites in Cameroon, Uganda and Mozambique, and examined the relationships between field-measured AGB and cross-polarized radar backscatter values derived from ALOS PALSAR, an L-band satellite sensor. The relationships were highly significant, similar among sites, and displayed high prediction accuracies up to 150 Mg ha-1 (±∼20%). AGB predictions for any given site obtained using equations derived from data from only the other three sites generated only small increases in error. The results suggest that a widely applicable general relationship exists between AGB and L-band backscatter for lower-biomass tropical woody vegetation. This relationship allows regional-scale AGB estimation, required for example by planned REDD (Reducing Emissions from Deforestation and Degradation) schemes.

Published
2009

27. Measuring woody encroachment along a forest-savanna boundary in Central Africa

Author

Mitchard, Edward T.A, Saatchi, Sassan S, Gerard, F F, Lewis , S. L., Meir, Patrick, Mitchard, Edward T.A, Saatchi, Sassan S, Gerard, F F, Lewis , S. L., and Meir, Patrick

Abstract

Changes in net area of tropical forest are the sum of several processes: deforestation, regeneration of previously deforested areas, and the changing spatial location of the forest-savanna boundary. The authors conducted a long-term (1986-2006) quantification of vegetation change in a 5400 km 2.

Published
2009

29. A novel application of satellite radar data: measuring carbon sequestration and detecting degradation in a community forestry project in Mozambique

Author

Mitchard, Edward T.A., primary, Meir, Patrick, additional, Ryan, Casey M., additional, Woollen, Emily S., additional, Williams, Mathew, additional, Goodman, Lucy E., additional, Mucavele, Joey A., additional, Watts, Paul, additional, Woodhouse, Iain H., additional, and Saatchi, Sassan S., additional

Published
2012
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30. A novel application of satellite radar data: measuring carbon sequestration and detecting degradation in a community forestry project in Mozambique.

Author

Mitchard, Edward T.A., Meir, Patrick, Ryan, Casey M., Woollen, Emily S., Williams, Mathew, Goodman, Lucy E., Mucavele, Joey A., Watts, Paul, Woodhouse, Iain H., and Saatchi, Sassan S.

Subjects
*CARBON sequestration, *FOREST monitoring, *FOREST degradation, *COMMUNITY forestry, *AGROFORESTRY
Abstract

Background:It is essential that systems for measuring changes in carbon stocks for Reducing Emissions from Deforestation and Forest Degradation (REDD) projects are accurate, reliable and low cost. Widely used systems involving classifying optical satellite data can underestimate degradation, and by classifying the landscape ignore the natural heterogeneity of biomass. Aims:To assess the ability of repeat L-band radar to detect areas of small increases or decreases in above-ground biomass (AGB) across a Miombo woodland landscape. Methods:ALOS PALSAR L-band cross-polarised (HV) radar data from 2007 and 2009 were used to create maps of AGB, calibrated using 58 field plots. The change in AGB was assessed for land parcels with known landcover histories: (i) 500 ha of new agroforestry; (ii) 9500 ha of protected (REDD) areas; and (iii) 23 ha of land where degradation occurred between 2007 and 2009. Results:Increases in AGB were detected in both the agroforestry and REDD areas (0.4 and 1.1 Mg C ha−1year−1, respectively), while the degraded areas showed a decrease of 3 Mg C ha−1year−1. Conclusions:PALSAR data can be used to detect losses and gains in AGB in woodland ecosystems. However, further work is needed to precisely quantify the uncertainties in the change estimates, and the extent of false-positive and false-negative change detections that would result from using such a system. [ABSTRACT FROM PUBLISHER]

Published
2013
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