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1. Aboveground forest biomass varies across continents, ecological zones and successional stages: refined IPCC default values for tropical and subtropical forests

Author

Danaë M A Rozendaal, Daniela Requena Suarez, Veronique De Sy, Valerio Avitabile, Sarah Carter, C Y Adou Yao, Esteban Alvarez-Davila, Kristina Anderson-Teixeira, Alejandro Araujo-Murakami, Luzmila Arroyo, Benjamin Barca, Timothy R Baker, Luca Birigazzi, Frans Bongers, Anne Branthomme, Roel J W Brienen, João M B Carreiras, Roberto Cazzolla Gatti, Susan C Cook-Patton, Mathieu Decuyper, Ben DeVries, Andres B Espejo, Ted R Feldpausch, Julian Fox, Javier G P Gamarra, Bronson W Griscom, Nancy Harris, Bruno Hérault, Eurídice N Honorio Coronado, Inge Jonckheere, Eric Konan, Sara M Leavitt, Simon L Lewis, Jeremy A Lindsell, Justin Kassi N’Dja, Anny Estelle N’Guessan, Beatriz Marimon, Edward T A Mitchard, Abel Monteagudo, Alexandra Morel, Anssi Pekkarinen, Oliver L Phillips, Lourens Poorter, Lan Qie, Ervan Rutishauser, Casey M Ryan, Maurizio Santoro, Dos Santos Silayo, Plinio Sist, J W Ferry Slik, Bonaventure Sonké, Martin J P Sullivan, Gaia Vaglio Laurin, Emilio Vilanova, Maria M H Wang, Eliakimu Zahabu, Martin Herold, Rozendaal D.M.A., Requena Suarez D., De Sy V., Avitabile V., Carter S., Adou Yao C.Y., Alvarez-Davila E., Anderson-Teixeira K., Araujo-Murakami A., Arroyo L., Barca B., Baker T.R., Birigazzi L., Bongers F., Branthomme A., Brienen R.J.W., Carreiras J.M.B., Cazzolla Gatti R., Cook-Patton S.C., Decuyper M., Devries B., Espejo A.B., Feldpausch T.R., Fox J., G P Gamarra J., Griscom B.W., Harris N., Herault B., Honorio Coronado E.N., Jonckheere I., Konan E., Leavitt S.M., Lewis S.L., Lindsell J.A., N'Dja J.K., N'Guessan A.E., Marimon B., Mitchard E.T.A., Monteagudo A., Morel A., Pekkarinen A., Phillips O.L., Poorter L., Qie L., Rutishauser E., Ryan C.M., Santoro M., Silayo D.S., Sist P., Slik J.W.F., Sonke B., Sullivan M.J.P., Vaglio Laurin G., Vilanova E., Wang M.M.H., Zahabu E., Herold M., and University of St Andrews. School of Geography & Sustainable Development

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Suivi et d’évaluation, forest plot, forêt tropicale, E-DAS, Tropical and subtropical forests, 7. Clean energy, 01 natural sciences, biomasse aérienne des arbres, Laboratory of Geo-information Science and Remote Sensing, Environmental Science(all), надземная биомасса, SDG 13 - Climate Action, старовозрастные леса, General Environmental Science, GE, Enquête, IPCC, tropical and subtropical forests, Aboveground biomass, PE&RC, Forest plots, secondary and old-growth forest, Plant Production Systems, aboveground bioma, Collecte de données, P01 - Conservation de la nature et ressources foncières, Crop and Weed Ecology, aboveground biomass, GE Environmental Sciences, Monitoring, тропические леса, Secondary and old-growth forests, 010603 evolutionary biology, Objectif 13 Mesures relatives à la lutte contre les changements climatique, лесные участки, forest plots, SDG 3 - Good Health and Well-being, вторичные леса, forêt primaire, Bosecologie en Bosbeheer, Laboratorium voor Geo-informatiekunde en Remote Sensing, SDG 7 - Affordable and Clean Energy, 0105 earth and related environmental sciences, MCC, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, субтропические леса, 15. Life on land, Forest Ecology and Forest Management, K10 - Production forestière, secondary and old-growth forests, monitoring, 13. Climate action, Plantaardige Productiesystemen, forêt secondaire
Abstract

Funding: We acknowledge funding from the following organizations: Norwegian Agency for Development Cooperation (Norad); Norwegian International Climate and Forest Initiative (NICFI); International Climate Initiative (IKI) of the German; Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB); CGIAR Research Program on Forests, Trees and Agroforestry (CRP‐FTA) with financial support from the CGIAR Fund Donors; EU Horizon 2020 project VERIFY (776810); European Space Agency GlobBiomass project (ESRIN Contract No. 4000113100/14/I-NB); European Research Council (ERC) Advanced Grants T-FORCES (291585) and PANTROP (834775); JAXA (RA-6, EO-RA2); UK Natural Environment Research Council (NERC; including NE/F005806/, NE/D005590/1, NE/T01279X/1, NE/P008755/1 and NE/N012542/1); agreement PR140015 between NERC and the National Centre for Earth Observation; Gordon and Betty Moore Foundation; CNPq (National Council of Science and Technology, Brazil), Grants #401279/2014‐4 (PVE) and #441244/2016‐5 (PELD); Doris Duke Charitable Foundation; the Children's Investment 309 Fund Foundation; COmON Foundation and Good Energies Foundation. For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0-7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps. Publisher PDF

Published
2022

2. Climatic controls of decomposition drive the global biogeography of forest-tree symbioses

Author

Steidinger, B. S., Crowther, T. W., Liang, J., Van Nuland, M. E., Werner, G. D. A., Reich, P. B., Nabuurs, G., de-Miguel, S., Zhou, M., Picard, N., Herault, B., Zhao, X., Zhang, C., Routh, D., Peay, K. G., Abegg, Meinrad, Yao, C. Yves Adou, Alberti, Giorgio, Zambrano, Angelica Almeyda, Alvarez-Davila, Esteban, Alvarez-Loayza, Patricia, Alves, Luciana F., Ammer, Christian, Anton-Fernandez, Clara, Araujo-Murakami, Alejandro, Arroyo, Luzmila, Avitabile, Valerio, Aymard, Gerardo, Baker, Timothy, Balazy, Radomir, Banki, Olaf, Barroso, Jorcely, Bastian, Meredith, Bastin, Jean-Francois, Birigazzi, Luca, Birnbaum, Philippe, Bitariho, Robert, Boeckx, Pascal, Bongers, Frans, Bouriaud, Olivier, Brancalion, Pedro H. S., Brandl, Susanne, Brearley, Francis Q., Brienen, Roel, Broadbent, Eben, Bruelheide, Helge, Bussotti, Filippo, Gatti, Roberto Cazzolla, Cesar, Ricardo, Cesljar, Goran, Chazdon, Robin, Chen, Han Y. H., Chisholm, Chelsea, Cienciala, Emil, Clark, Connie J., Clark, David, Colletta, Gabriel, Condit, Richard, Coomes, David, Cornejo Valverde, Fernando, Corral-Rivas, Jose J., Crim, Philip, Cumming, Jonathan, Dayanandan, Selvadurai, de Gasper, Andre L., Decuyper, Mathieu, Derroire, Geraldine, DeVries, Ben, Djordjevic, Ilija, Ieda, Amaral, Dourdain, Aurelie, Obiang, Nestor Laurier Engone, Enquist, Brian, Eyre, Teresa, Fandohan, Adande Belarmain, Fayle, Tom M., Feldpausch, Ted R., Finer, Leena, Fischer, Markus, Fletcher, Christine, Fridman, Jonas, Frizzera, Lorenzo, Gamarra, Javier G. P., Gianelle, Damiano, Glick, Henry B., Harris, David, Hector, Andrew, Hemp, Andreas, Hengeveld, Geerten, Herbohn, John, Herold, Martin, Hillers, Annika, Honorio Coronado, Euridice N., Huber, Markus, Hui, Cang, Cho, Hyunkook, Ibanez, Thomas, Jung, Ilbin, Imai, Nobuo, Jagodzinski, Andrzej M., Jaroszewicz, Bogdan, Johannsen, Vivian, Joly, Carlos A., Jucker, Tommaso, Karminov, Viktor, Kartawinata, Kuswata, Kearsley, Elizabeth, Kenfack, David, Kennard, Deborah, Kepfer-Rojas, Sebastian, Keppel, Gunnar, Khan, Mohammed Latif, Killeen, Timothy, Kim, Hyun Seok, Kitayama, Kanehiro, Kohl, Michael, Korjus, Henn, Kraxner, Florian, Laarmann, Diana, Lang, Mait, Lewis, Simon, Lu, Huicui, Lukina, Natalia, Maitner, Brian, Malhi, Yadvinder, Marcon, Eric, Marimon, Beatriz Schwantes, Marimon-Junior, Ben Hur, Marshall, Andrew Robert, Martin, Emanuel, Martynenko, Olga, Meave, Jorge A., Melo-Cruz, Omar, Mendoza, Casimiro, Merow, Cory, Mendoza, Abel Monteagudo, Moreno, Vanessa, Mukul, Sharif A., Mundhenk, Philip, Nava-Miranda, Maria G., Neill, David, Neldner, Victor, Nevenic, Radovan, Ngugi, Michael, Niklaus, Pascal, Oleksyn, Jacek, Ontikov, Petr, Ortiz-Malavasi, Edgar, Pan, Yude, Paquette, Alain, Parada-Gutierrez, Alexander, Parfenova, Elena, Park, Minjee, Parren, Marc, Parthasarathy, Narayanaswamy, Peri, Pablo L., Pfautsch, Sebastian, Phillips, Oliver, Piedade, Maria Teresa, Piotto, Daniel, Pitman, Nigel C. A., Polo, Irina, Poorter, Lourens, Poulsen, Axel Dalberg, Poulsen, John R., Pretzsch, Hans, Arevalo, Freddy Ramirez, Restrepo-Correa, Zorayda, Rodeghiero, Mirco, Rolim, Samir, Roopsind, Anand, Rovero, Francesco, Rutishauser, Ervan, Saikia, Purabi, Saner, Philippe, Schall, Peter, Schelhaas, Mart-Jan, Schepaschenko, Dmitry, Scherer-Lorenzen, Michael, Schmid, Bernhard, Schongart, Jochen, Searle, Eric, Seben, Vladimir, Serra-Diaz, Josep M., Salas-Eljatib, Christian, Sheil, Douglas, Shvidenko, Anatoly, Silva-Espejo, Javier, Silveira, Marcos, Singh, James, Sist, Plinio, Slik, Ferry, Sonke, Bonaventure, Souza, Alexandre F., Sterenczak, Krzysztof, Svenning, Jens-Christian, Svoboda, Miroslav, Targhetta, Natalia, Tchebakova, Nadja, ter Steege, Hans, Thomas, Raquel, Tikhonova, Elena, Umunay, Peter, Usoltsev, Vladimir, Valladares, Fernando, van der Plas, Fons, Tran Van Do, Vasquez Martinez, Rodolfo, Verbeeck, Hans, Viana, Helder, Vieira, Simone, von Gadow, Klaus, Wang, Hua-Feng, Watson, James, Westerlund, Bertil, Wiser, Susan, Wittmann, Florian, Wortel, Verginia, Zagt, Roderick, Zawila-Niedzwiecki, Tomasz, Zhu, Zhi-Xin, Zo-Bi, Irie Casimir, Valladares, Fernando, Stanford University, Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Purdue University [West Lafayette], Beijing Forestry University, University of Oxford [Oxford], University of Minnesota [Twin Cities] (UMN), University of Minnesota System, Western Sydney University, Wageningen University and Research [Wageningen] (WUR), Universitat de Lleida, Centre de Ciència i Tecnologia Forestal de Catalunya (CTFC), Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Forêts et Sociétés (UPR Forêts et Sociétés), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut National Polytechnique Yamoussoukro, Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), SILVA (SILVA), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, Stanford University [Stanford], Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), University of Minnesota [Twin Cities], Western Sydney University (UWS), Wageningen University and Research Centre [Wageningen] (WUR), Forest Science and Technology Centre of Catalonia, Food and Agricultural Organization of the United Nations (FAO), United Nations Organization, Forêts et Sociétés (Cirad-Es-UPR 105 Forêts et Sociétés), Département Environnements et Sociétés (Cirad-ES), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Lorraine (UL), Steidinger B.S., Crowther T.W., Liang J., Van Nuland M.E., Werner G.D.A., Reich P.B., Nabuurs G., de-Miguel S., Zhou M., Picard N., Herault B., Zhao X., Zhang C., Routh D., Peay K.G., Abegg M., AdouYao C.Y., Alberti G., AlmeydaZambrano A., Alvarez-Davila E., Alvarez-Loayza P., Alves L.F., Ammer C., Anton-Fernandez C., Araujo-Murakami A., Arroyo L., Avitabile V., Aymard G., Baker T., Balazy R., Banki O., Barroso J., Bastian M., Bastin J.-F., Birigazzi L., Birnbaum P., Bitariho R., Boeckx P., Bongers F., Bouriaud O., Brancalion P.H.S., Brandl S., Brearley F.Q., Brienen R., Broadbent E., Bruelheide H., Bussotti F., Cazzolla Gatti R., Cesar R., Cesljar G., Chazdon R., Chen H.Y.H., Chisholm C., Cienciala E., Clark C.J., Clark D., Colletta G., Condit R., Coomes D., CornejoValverde F., Corral-Rivas J.J., Crim P., Cumming J., Dayanandan S., de Gasper A.L., Decuyper M., Derroire G., DeVries B., Djordjevic I., Ieda A., Dourdain A., Obiang N.L.E., Enquist B., Eyre T., Fandohan A.B., Fayle T.M., Feldpausch T.R., Finer L., Fischer M., Fletcher C., Fridman J., Frizzera L., Gamarra J.G.P., Gianelle D., Glick H.B., Harris D., Hector A., Hemp A., Hengeveld G., Herbohn J., Herold M., Hillers A., Honorio Coronado E.N., Huber M., Hui C., Cho H., Ibanez T., Jung I., Imai N., Jagodzinski A.M., Jaroszewicz B., Johannsen V., Joly C.A., Jucker T., Karminov V., Kartawinata K., Kearsley E., Kenfack D., Kennard D., Kepfer-Rojas S., Keppel G., Khan M.L., Killeen T., Kim H.S., Kitayama K., Kohl M., Korjus H., Kraxner F., Laarmann D., Lang M., Lewis S., Lu H., Lukina N., Maitner B., Malhi Y., Marcon E., Marimon B.S., Marimon-Junior B.H., Marshall A.R., Martin E., Martynenko O., Meave J.A., Melo-Cruz O., Mendoza C., Merow C., MonteagudoMendoza A., Moreno V., Mukul S.A., Mundhenk P., Nava-Miranda M.G., Neill D., Neldner V., Nevenic R., Ngugi M., Niklaus P., Oleksyn J., Ontikov P., Ortiz-Malavasi E., Pan Y., Paquette A., Parada-Gutierrez A., Parfenova E., Park M., Parren M., Parthasarathy N., Peri P.L., Pfautsch S., Phillips O., Piedade M.T., Piotto D., Pitman N.C.A., Polo I., Poorter L., Poulsen A.D., Poulsen J.R., Pretzsch H., RamirezArevalo F., Restrepo-Correa Z., Rodeghiero M., Rolim S., Roopsind A., Rovero F., Rutishauser E., Saikia P., Saner P., Schall P., Schelhaas M.-J., Schepaschenko D., Scherer-Lorenzen M., Schmid B., Schongart J., Searle E., Seben V., Serra-Diaz J.M., Salas-Eljatib C., Sheil D., Shvidenko A., Silva-Espejo J., Silveira M., Singh J., Sist P., Slik F., Sonke B., Souza A.F., Sterenczak K., Svenning J.-C., Svoboda M., Targhetta N., Tchebakova N., Steege H., Thomas R., Tikhonova E., Umunay P., Usoltsev V., Valladares F., van der Plas F., Van Do T., VasquezMartinez R., Verbeeck H., Viana H., Vieira S., von Gadow K., Wang H.-F., Watson J., Westerlund B., Wiser S., Wittmann F., Wortel V., Zagt R., Zawila-Niedzwiecki T., Zhu Z.-X., Zo-Bi I.C., Systems Ecology, Steidinger, BS, Crowther, TW, Liang, J, Van Nuland, ME, Werner, GDA, Reich, PB, Nabuurs, G, de-Miguel, S, Zhou, M, Picard, N, Herault, B, Zhao, X, Zhang, C, Routh, D, Peay, KG, Keppel, G, GFBI consortium, and Valladares, Fernando [0000-0002-5374-4682]

Subjects
symbiosi, 0106 biological sciences, Forest Ecology, SOM decomposition, biogeography, forest-tree symbioses, Bos- en Landschapsecologie, Biome, 01 natural sciences, forest-tree symbioses, Microbial ecology, Laboratory of Geo-information Science and Remote Sensing, K01 - Foresterie - Considérations générales, Bos- en Natuurbeleid, Forest and Landscape Ecology, Multidisciplinary, Ecology, forest ecosystems, PE&RC, séquestration du carbone, Biometris, Biogeography, Forêt, Écosystème forestier, Vegetatie, Bos- en Landschapsecologie, P33 - Chimie et physique du sol, Climate control, Forest Ecology, P40 - Météorologie et climatologie, Symbiose, 010603 evolutionary biology, Forest and Nature Conservation Policy, Symbiosis, Settore BIO/07 - ECOLOGIA, Forest ecology, Temperate climate, Symbioses, Life Science, Bosecologie en Bosbeheer, Laboratorium voor Geo-informatiekunde en Remote Sensing, Forest, climate, Vegetatie, biogeography, Changement climatique, decomposition, Vegetation, Forest inventory, симбиозы, P34 - Biologie du sol, FUNGI, климат, 15. Life on land, Arid, Forest Ecology and Forest Management, SOM decomposition, forest inventory plots, лесные экосистемы, Environmental science, Vegetation, Forest and Landscape Ecology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, 010606 plant biology & botany
Abstract

[EN] The identity of the dominant root-associated microbial symbionts in a forest determines the ability of trees to access limiting nutrients from atmospheric or soil pools, sequester carbon and withstand the effects of climate change. Characterizing the global distribution of these symbioses and identifying the factors that control this distribution are thus integral to understanding the present and future functioning of forest ecosystems. Here we generate a spatially explicit global map of the symbiotic status of forests, using a database of over 1.1 million forest inventory plots that collectively contain over 28,000 tree species. Our analyses indicate that climate variables—in particular, climatically controlled variation in the rate of decomposition—are the primary drivers of the global distribution of major symbioses. We estimate that ectomycorrhizal trees, which represent only 2% of all plant species, constitute approximately 60% of tree stems on Earth. Ectomycorrhizal symbiosis dominates forests in which seasonally cold and dry climates inhibit decomposition, and is the predominant form of symbiosis at high latitudes and elevation. By contrast, arbuscular mycorrhizal trees dominate in aseasonal, warm tropical forests, and occur with ectomycorrhizal trees in temperate biomes in which seasonally warm-and-wet climates enhance decomposition. Continental transitions between forests dominated by ectomycorrhizal or arbuscular mycorrhizal trees occur relatively abruptly along climate-driven decomposition gradients; these transitions are probably caused by positive feedback effects between plants and microorganisms. Symbiotic nitrogen fixers—which are insensitive to climatic controls on decomposition (compared with mycorrhizal fungi)—are most abundant in arid biomes with alkaline soils and high maximum temperatures. The climatically driven global symbiosis gradient that we document provides a spatially explicit quantitative understanding of microbial symbioses at the global scale, and demonstrates the critical role of microbial mutualisms in shaping the distribution of plant species., This work was made possible by the Global Forest Biodiversity Database, which represents the work of over 200 independent investigators and their public and private funding agencies (see Supplementary Acknowledgements), Supplementary information is available for this paper at https://doi.org/10.1038/s41586-019-1128-0.

Published
2019

3. Assessing forest availability for wood supply in Europe

Author

V. Seben, Jonas Fridman, Stein Tomter, Alexandra Freudenschuß, O. Boriaud, Michal Bosela, B. Pesty, Andrea Camia, B.T. Kjartansson, Monica Notarangelo, Laura Hernández, V. Avitable, Thomas Gschwantner, Thomas Riedel, Milos Kucera, Arnór Snorrason, Adrian Lanz, Leónia Nunes, S. Mubareka, T. Pikula, Silvia Guerrero, Isabel Cañellas, Maria Rizzo, Christoph Fischer, F. Castro Rego, Patrizia Gasparini, Gheorghe Marin, Susann Bender, John Redmond, Iciar Alberdi, European Commission, Ministerio de Agricultura, Pesca y Alimentación (España), Ministerio de Ciencia e Innovación (España), Slovak Research and Development Agency, Alberdi, Iciar, Bender, Susann, Avitabile, V., Boriaud, O., Bosela, Michal, Cañellas, I., Castro Rego, Francisco, Fischer, Christoph, Freudenschuss, A., Fridman, Jonas, Gasparini, P., Gschwantner, Thomas, Notarangelo, Monica, Nunes, Leónia, Rizzo, M., Sebeň, Vladimír, Snorrason, A., Tomter, Stein Michael, and Hernández, Laura

Subjects
Economics and Econometrics, Wood resources, Sociology and Political Science, National forest inventory, 0211 other engineering and technologies, restriction, Harmonization, 02 engineering and technology, 010501 environmental sciences, Management, Monitoring, Policy and Law, 01 natural sciences, Article, FAWS, Country level, Restriction, Biomass, national forest inventory, 0105 earth and related environmental sciences, Biomass (ecology), biomass, Agroforestry, wood resources, 021107 urban & regional planning, Forestry, Limiting, Forest resource, Geography, harmonization, Profitability index
Abstract

14 Pág., The quantification of forests available for wood supply (FAWS) is essential for decision-making with regard to the maintenance and enhancement of forest resources and their contribution to the global carbon cycle. The provision of harmonized forest statistics is necessary for the development of forest associated policies and to support decision-making. Based on the National Forest Inventory (NFI) data from 13 European countries, we quantify and compare the areas and aboveground dry biomass (AGB) of FAWS and forest not available for wood supply (FNAWS) according to national and reference definitions by determining the restrictions and associated thresholds considered at country level to classify forests as FAWS or FNAWS. FAWS represent between 75 and 95 % of forest area and AGB for most of the countries in this study. Economic restrictions are the main factor limiting the availability of forests for wood supply, accounting for 67 % of the total FNAWS area and 56 % of the total FNAWS AGB, followed by environmental restrictions. Profitability, slope and accessibility as economic restrictions, and protected areas as environmental restrictions are the factors most frequently considered to distinguish between FAWS and FNAWS. With respect to the area of FNAWS associated with each type of restriction, an overlap among the restrictions of 13.7 % was identified. For most countries, the differences in the FNAWS areas and AGB estimates between national and reference definitions ranged from 0 to 5 %. These results highlight the applicability and reliability of a FAWS reference definition for most of the European countries studied, thereby facilitating a consistent approach to assess forests available for supply for the purpose of international reporting., This research was supported by the Specific contract n. 18 “Use of National Forest Inventories data to estimate area and above ground biomass in European forests not available for wood supply” in the context of the Framework contract for the provision of forest data and services supporting the European Forest Data Centre 2012/ S 78-127532 of 21/04/2012 of the Joint Research Centre of the European Commission; the EG-013-72 agreement of the Ministry of Agriculture, Fisheries and Food (MAPA) and the INIA belonging to the Spanish Ministry of Science and Innovation (MICINN); and the project No.APVV-15-0265 granted by the Slovak Research and Development Agency.

Published
2020

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

Author

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

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Mean squared error, Forest plot, Climate change, Datasets as Topic, Structural basin, 010603 evolutionary biology, 01 natural sciences, Ecology and Environment, Trees, Laboratory of Geo-information Science and Remote Sensing, Tropical forest, Environmental Chemistry, Satellite imagery, Laboratorium voor Geo-informatiekunde en Remote Sensing, Biomass, Aboveground bioma, 0105 earth and related environmental sciences, General Environmental Science, Remote sensing, Global and Planetary Change, Tropical Climate, Forest inventory, Ecology, Tropics, Aboveground biomass, Carbon cycle, 15. Life on land, Models, Theoretical, Sensor fusion, PE&RC, Forest plots, Satellite mapping, 13. Climate action, Spatial ecology, Environmental science, Physical geography, REDD+, ISRIC - World Soil Information, Maps as Topic
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 14477 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 5Mg dry massha-1 vs. 21 and 28Mgha-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

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

Author

M. Santoro, O. Cartus, N. Carvalhais, D. M. A. Rozendaal, V. Avitabile, A. Araza, S. de Bruin, M. Herold, S. Quegan, P. Rodríguez-Veiga, H. Balzter, J. Carreiras, D. Schepaschenko, M. Korets, M. Shimada, T. Itoh, Á. Moreno Martínez, J. Cavlovic, R. Cazzolla Gatti, P. da Conceição Bispo, N. Dewnath, N. Labrière, J. Liang, J. Lindsell, E. T. A. Mitchard, A. Morel, A. M. Pacheco Pascagaza, C. M. Ryan, F. Slik, G. Vaglio Laurin, H. Verbeeck, A. Wijaya, S. Willcock, DCEA - Departamento de Ciências e Engenharia do Ambiente, Santoro M., Cartus O., Carvalhais N., Rozendaal D.M.A., Avitabile V., Araza A., De Bruin S., Herold M., Quegan S., Rodriguez-Veiga P., Balzter H., Carreiras J., Schepaschenko D., Korets M., Shimada M., Itoh T., Moreno Martinez A., Cavlovic J., Cazzolla Gatti R., Da Conceicao Bispo P., Dewnath N., Labriere N., Liang J., Lindsell J., Mitchard E.T.A., Morel A., Pacheco Pascagaza A.M., Ryan C.M., Slik F., Vaglio Laurin G., Verbeeck H., Wijaya A., and Willcock S.

Subjects
010504 meteorology & atmospheric sciences, ALOS PALSAR, 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, Laboratory of Geo-information Science and Remote Sensing, SDG 13 - Climate Action, GE1-350, Biomass, EMISSIONS, SDG 15 - Life on Land, QE1-996.5, GROWING STOCK VOLUME, Taiga, Geology, PE&RC, Plant Production Systems, MAP, bioma, CARBON-CYCLE, Crop and Weed Ecology, Synthetic aperture radar, Physical geography, RETRIEVAL, UNITED-STATES, Earth and Planetary Sciences(all), Subtropics, Spatial distribution, Environmental science, Carbon cycle, tropics, Temperate climate, BOREAL FORESTS, MANAGEMENT, Life Science, Spatial ecology, Laboratorium voor Geo-informatiekunde en Remote Sensing, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Forest inventory, Radar, Environmental sciences, Satellite, Earth and Environmental Sciences, DENSITY, Plantaardige Productiesystemen, General Earth and Planetary Sciences, cavelab
Abstract

Funding Information: We are thankful to the GlobBiomass project team and Frank Martin Seifert (ESA) for valuable suggestions and stimulating scientific discussions. We are thankful to Takeo Tadono (JAXA EORC), Masato Hayashi, (JAXA EORC), Kazufumi Kobayashi (RESTEC), Åke Rosenqvist (soloEO), and Josef Kellndorfer (EBD) for support with the use and interpretation of the ALOS PALSAR mosaics. Support by the CCI Land Cover project team, in particular Sophie Bontemps (UCL), is greatly acknowledged. The help from Martin Jung (MPI-BGC) in feature selection and Ulrich Weber (MPI-BGC) for data processing for the GSV-to-AGB conversions is greatly acknowledged. Forest inventory data for the validation of the AGB map were made available by, among others, Ben de Jong; the Prince Edward Island Department of Communities, Land and Environment – Forests, Fish and Wildlife Division; and the Nova Scotia Department of Natural Resources. Inventory data were also provided by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, the USAID, and the US Department of State. We thank the three anonymous reviewers, contributors to the short comments, Geerten Hengeveld, and Jérôme Chave for reviewing and improving the manuscript. Funding Information: Financial support. This research has been supported by the European Space Agency (ESRIN contract no. 4000113100/14/I-NB) and the Russian Science Foundation (grant no. 19-77-30015). Funding Information: Acknowledgements. The National Centre for Earth Observation was supported by the UK Natural Environment Research Council. The FOS data collection for Russia was performed within the framework of the state assignment of the Center for Forest Ecology and Productivity of the Russian Academy of Sciences (no. AAAA-A18-118052590019-7). The Russian ground data preparation and pre-processing were financially supported by the Russian Science Foundation (project no. 19-77-30015). Publisher Copyright: © 2021 Maurizio Santoro et al. 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 Mgha-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. publishersversion published

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