Authors and Contributors, Acknowledgments

{"Glossary":{"51":{"name":"agricultural tree crops","description":"Trees cultivated for their food, cultural, or economic values. These include oil palm, rubber, cocoa, cashew, mango, oranges (citrus), plantain, banana, and coconut.\r\n"},"141":{"name":"agroforestry","description":"A diversified set of agricultural or agropastoral production systems that integrate trees in the agricultural landscape.\r\n"},"101":{"name":"albedo","description":"The ability of surfaces to reflect sunlight.\u0026nbsp;Light-colored surfaces return a large part of the sunrays back to the atmosphere (high albedo). Dark surfaces absorb the rays from the sun (low albedo).\r\n"},"94":{"name":"biodiversity intactness","description":"The proportion and abundance of a location\u0027s original forest community (number of species and individuals) that remain.\u0026nbsp;\r\n"},"95":{"name":"biodiversity significance","description":"The importance of an area for the persistence of forest-dependent species based on range rarity.\r\n"},"142":{"name":"boundary plantings","description":"Trees planted along boundaries or property lines to mark them well.\r\n"},"98":{"name":"carbon dioxide equivalent (CO2e)","description":"Carbon dioxide equivalent (CO2e) is a measure used to aggregate emissions from various greenhouse gases (GHGs) on the basis of their 100-year global warming potentials by equating non-CO2 GHGs to the equivalent amount of CO2.\r\n"},"99":{"name":"CO2e","description":"Carbon dioxide equivalent (CO2e) is a measure used to aggregate emissions from various greenhouse gases (GHGs) on the basis of their 100-year global warming potentials by equating non-CO2 GHGs to the equivalent amount of CO2.\r\n"},"1":{"name":"deforestation","description":"The change from forest to another land cover or land use, such as forest to plantation or forest to urban area.\r\n"},"77":{"name":"deforested","description":"The change from forest to another land cover or land use, such as forest to plantation or forest to urban area.\r\n"},"76":{"name":"degradation","description":"The reduction in a forest\u2019s ability to perform ecosystem services, such as carbon storage and water regulation, due to natural and anthropogenic changes.\r\n"},"75":{"name":"degraded","description":"The reduction in a forest\u2019s ability to perform ecosystem services, such as carbon storage and water regulation, due to natural and anthropogenic changes.\r\n"},"79":{"name":"disturbances","description":"A discrete event that changes the structure of a forest ecosystem.\r\n"},"68":{"name":"disturbed","description":"A discrete event that changes the structure of a forest ecosystem.\r\n"},"65":{"name":"driver of tree cover loss","description":"The direct cause of forest disturbance.\r\n"},"70":{"name":"drivers of loss","description":"The direct cause of forest disturbance.\r\n"},"81":{"name":"drivers of tree cover loss","description":"The direct cause of forest disturbance.\r\n"},"102":{"name":"evapotranspiration","description":"When solar energy hitting a forest converts liquid water into water vapor (carrying energy as latent heat) through evaporation and transpiration.\r\n"},"2":{"name":"forest","description":"Forests include tree cover greater than 30 percent tree canopy density and greater than 5 meters in height as mapped at a 30-meter Landsat pixel scale.\r\n"},"3":{"name":"forest concession","description":"A legal agreement allowing an entity the right to manage a public forest for production purposes.\r\n"},"90":{"name":"forest concessions","description":"A legal agreement allowing an entity the right to manage a public forest for production purposes.\r\n"},"53":{"name":"forest degradation","description":"The reduction in a forest\u2019s ability to perform ecosystem services, such as carbon storage and water regulation, due to natural and anthropogenic changes.\r\n"},"54":{"name":"forest disturbance","description":"A discrete event that changes the structure of a forest ecosystem.\r\n"},"100":{"name":"forest disturbances","description":"A discrete event that changes the structure of a forest ecosystem.\r\n"},"5":{"name":"forest fragmentation","description":"The breaking of large, contiguous forests into smaller pieces, with other land cover types interspersed.\r\n"},"6":{"name":"forest management plan","description":"A plan that documents the stewardship and use of forests and other wooded land to meet environmental, economic, social, and cultural objectives. Such plans are typically implemented by companies in forest concessions.\r\n"},"62":{"name":"forests","description":"Forests include tree cover greater than 30 percent tree canopy density and greater than 5 meters in height as mapped at a 30-meter Landsat pixel scale.\r\n"},"69":{"name":"fragmentation","description":"The breaking of large, contiguous forests into smaller pieces, with other land cover types interspersed.\r\n"},"80":{"name":"fragmented","description":"The breaking of large, contiguous forests into smaller pieces, with other land cover types interspersed.\r\n"},"74":{"name":"gain","description":"The establishment of tree canopy in an area that previously had no tree cover. Tree cover gain may indicate a number of potential activities, including natural forest growth or the crop rotation cycle of tree plantations.\r\n"},"143":{"name":"global land squeeze","description":"Pressure on finite land resources to produce food, feed and fuel for a growing human population while also sustaining biodiversity and providing ecosystem services.\r\n"},"7":{"name":"hectare","description":"One hectare equals 100 square meters, 2.47 acres, or 0.01 square kilometers and is about the size of a rugby field. A football pitch is slightly smaller than a hectare (pitches are between 0.62 and 0.82 hectares).\r\n"},"66":{"name":"hectares","description":"One hectare equals 100 square meters, 2.47 acres, or 0.01 square kilometers and is about the size of a rugby field. A football pitch is slightly smaller than a hectare (pitches are between 0.62 and 0.82 hectares).\r\n"},"67":{"name":"intact","description":"A forest that contains no signs of human activity or habitat fragmentation as determined by remote sensing images and is large enough to maintain all native biological biodiversity.\r\n"},"78":{"name":"intact forest","description":"A forest that contains no signs of human activity or habitat fragmentation as determined by remote sensing images and is large enough to maintain all native biological biodiversity.\r\n"},"8":{"name":"intact forests","description":"A forest that contains no signs of human activity or habitat fragmentation as determined by remote sensing images and is large enough to maintain all native biological biodiversity.\r\n"},"55":{"name":"land and environmental defenders","description":"People who peacefully promote and protect rights related to land and\/or the environment.\r\n"},"9":{"name":"loss driver","description":"The direct cause of forest disturbance.\r\n"},"10":{"name":"low tree canopy density","description":"Less than 30 percent tree canopy density.\r\n"},"84":{"name":"managed forest concession","description":"Areas where governments have given rights to private companies to harvest timber and other wood products from natural forests on public lands.\r\n"},"83":{"name":"managed forest concession maps for nine countries","description":"Cameroon, Canada, Central African Republic, Democratic Republic of the Congo, Equatorial Guinea, Gabon, Indonesia, Liberia, and the Republic of the Congo\r\n"},"104":{"name":"managed natural forests","description":"Naturally regenerated forests with signs of management, including logging, clear cuts, etc.\r\n"},"91":{"name":"megacities","description":"A city with more than 10 million people.\r\n"},"57":{"name":"megacity","description":"A city with more than 10 million people."},"56":{"name":"mosaic restoration","description":"Restoration that integrates trees into mixed-use landscapes, such as agricultural lands and settlements, where trees can support people through improved water quality, increased soil fertility, and other ecosystem services. This type of restoration is more likely in deforested or degraded forest landscapes with moderate population density (10\u2013100 people per square kilometer). "},"86":{"name":"natural","description":"A forest that is grown without human intervention.\r\n"},"12":{"name":"natural forest","description":"A forest that is grown without human intervention.\r\n"},"63":{"name":"natural forests","description":"A forest that is grown without human intervention.\r\n"},"144":{"name":"open canopy systems","description":"Individual tree crowns that do not overlap to form a continuous canopy layer.\r\n"},"82":{"name":"persistent gain","description":"Forests that have experienced one gain event from 2001 to 2016.\r\n"},"13":{"name":"persistent loss and gain","description":"Forests that have experienced one loss or one gain event from 2001 to 2016."},"97":{"name":"plantation","description":"An area in which trees have been planted, generally for commercial purposes.\u0026nbsp;\r\n"},"93":{"name":"plantations","description":"An area in which trees have been planted, generally for commercial purposes.\u0026nbsp;\r\n"},"88":{"name":"planted","description":"A forest composed of trees that have been deliberately planted and\/or seeded by humans.\r\n"},"14":{"name":"planted forest","description":"A forest composed of trees that have been deliberately planted and\/or seeded by humans.\r\n"},"73":{"name":"planted forests","description":"A forest composed of trees that have been deliberately planted and\/or seeded by humans.\r\n"},"15":{"name":"primary forest","description":"Old-growth forests that are typically high in carbon stock and rich in biodiversity. The GFR uses a humid tropical primary rainforest data set, representing forests in the humid tropics that have not been cleared in recent years.\r\n"},"64":{"name":"primary forests","description":"Old-growth forests that are typically high in carbon stock and rich in biodiversity. The GFR uses a humid tropical primary rainforest data set, representing forests in the humid tropics that have not been cleared in recent years.\r\n"},"58":{"name":"production forest","description":"A forest where the primary management objective is to produce timber, pulp, fuelwood, and\/or nonwood forest products."},"89":{"name":"production forests","description":"A forest where the primary management objective is to produce timber, pulp, fuelwood, and\/or nonwood forest products.\r\n"},"87":{"name":"seminatural","description":"A managed forest modified by humans, which can have a different species composition from surrounding natural forests.\r\n"},"59":{"name":"seminatural forests","description":"A managed forest modified by humans, which can have a different species composition from surrounding natural forests. "},"96":{"name":"shifting agriculture","description":"Temporary loss or permanent deforestation due to small- and medium-scale agriculture.\r\n"},"103":{"name":"surface roughness","description":"Surface roughness of forests creates\u0026nbsp;turbulence that slows near-surface winds and cools the land as it lifts heat from low-albedo leaves and moisture from evapotranspiration high into the atmosphere and slows otherwise-drying winds. \r\n"},"17":{"name":"tree cover","description":"All vegetation greater than five meters in height and may take the form of natural forests or plantations across a range of canopy densities. Unless otherwise specified, the GFR uses greater than 30 percent tree canopy density for calculations.\r\n"},"71":{"name":"tree cover canopy density is low","description":"Less than 30 percent tree canopy density.\r\n"},"60":{"name":"tree cover gain","description":"The establishment of tree canopy in an area that previously had no tree cover. Tree cover gain may indicate a number of potential activities, including natural forest growth or the crop rotation cycle of tree plantations.\u0026nbsp;As such, tree cover gain does not equate to restoration.\r\n"},"18":{"name":"tree cover loss","description":"The removal or mortality of tree cover, which can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, loss does not equate to deforestation.\r\n"},"19":{"name":"tree plantation","description":"An agricultural plantation of fast-growing tree species on short rotations for the production of timber, pulp, or fruit.\r\n"},"72":{"name":"tree plantations","description":"An agricultural plantation of fast-growing tree species on short rotations for the production of timber, pulp, or fruit.\r\n"},"85":{"name":"trees outside forests","description":"Trees found in urban areas, alongside roads, or within agricultural land\u0026nbsp;are often referred to as Trees Outside Forests (TOF).\u202f\r\n"},"105":{"name":"unmanaged natural forests","description":"Naturally regenerated forests without any signs of management, including primary forest.\r\n"}}}

Authors and Contributors, Acknowledgments

  • Authors and Contributors

    Tim Searchinger (WRI and Princeton University)

    Lead author

    Richard Waite (WRI) Craig Hanson (WRI) Janet Ranganathan (WRI)

    Lead modeler: Patrice Dumas (CIRAD)

    Editor: Emily Matthews

    Tim Searchinger, Richard Waite, and Tim Beringer (Humboldt University at Berlin) contributed to development of the GlobAgri-WRR model, as did a number of researchers from the Centre de coopération internationale en recherche agronomique pour le développement, and the Institut national de la recherche agronomique, including Agneta Forslund, Hervé Guyomard, Chantal Le Mouël, Stéphane Manceron, and Elodie Marajo-Petitzon.

    Major GlobAgri-WRR model subcomponents include a livestock model with lead developers Mario Herrero (Commonwealth Scientific and Industrial Research Organisation) and Petr Havlík (IIASA), with additional contributions from Stefan Wirsenius (Chalmers University of Technology); a land-use model with lead developer Fabien Ramos (European Commission Joint Research Centre); a rice model with lead developer Xiaoyuan Yan (Chinese Institute for Soil Science); a nitrogen emissions model with lead developer Xin Zhang (Princeton University); and an aquaculture model with lead developers Mike Phillips (WorldFish) and Rattanawan Mungkung (Kasetsart University).

    A number of individuals were coauthors on working papers that serve as the foundation for the full report, this synthesis report, and many of the menu items profiled therein. They include Tapan K. Adhya (KIIT University, India), Tamara Ben Ari (INRA), Maryline Boval (INRA), Tim Beringer (Humboldt University at Berlin), Malcolm Beveridge (WorldFish), Randall Brummett (World Bank), Sarah Castine (WorldFish), Philippe Chemineau (INRA), Nuttapon Chaiyawannakarn (Kasetsart University), Ayesha Dinshaw (WRI), Patrice Dumas (CIRAD), Dennis Garrity (World Agroforestry Centre), Jerry Glover (U.S. Agency for International Development), Sarah Harper (Oxford Institute of Population Ageing and University of Oxford), Ralph Heimlich (Agricultural Conservation Economics), Debbie Hellums (International Fertilizer Development Center), Norbert Henninger (WRI), Sadasivam Kaushik (INRA), Lisa Kitinoja (The Postharvest Education Foundation), Jean-Marc Lacape (CIRAD), George Leeson (Oxford Institute of Population Ageing and University of Oxford), Bruce Linquist (University of California at Davis), Brian Lipinski (WRI), David Makowski (INRA), Mike McGahuey (U.S. Agency for International Development), Rattanawan Mungkung (Kasetsart University), Supawat Nawapakpilai (Kasetsart University), Michael Phillips (WorldFish), Chris Reij (WRI), Katie Reytar (WRI), Sara Scherr (EcoAgiculture Partners), Daniel Vennard (WRI), Reiner Wassmann (International Rice Research Institute, Philippines), Robert Winterbottom (WRI), and Xiaoyuan Yan (Institute for Soil Science, Chinese Academy of Sciences).

    Acknowledgments 

    We are pleased to acknowledge our institutional strategic partners, who provide core funding to WRI: Netherlands Ministry of Foreign Affairs, Royal Danish Ministry of Foreign Affairs, and Swedish International Development Cooperation Agency.

    The authors are grateful to the following peers who provided critical reviews and helpful suggestions to this synthesis report: Gary Atlin (Bill and Melinda Gates Foundation), Tobias Baedeker (World Bank), Erin Biehl (Johns Hopkins University Center for a Livable Future—JHU-CLF), Randall Brummett (World Bank), Rebecca Carter (WRI), Tim Christophersen (UN Environment), Ed Davey (WRI), Chris Delgado (WRI), Adriana Dinu (UNDP), Natalie Elwell (WRI), Jamison Ervin (UNDP), Roger Freedman (2Blades Foundation), James Gaffney (DuPont), Tess Geers (Oceana), Charles Godfray (Oxford Martin Programme on the Future of Food), Hidayah Hamzah (WRI), Nancy Harris (WRI), Mario Herrero (Commonwealth Scientific and Industrial Research Organisation), Jillian Holzer (WRI), Lisa Johnston (WRI), Doyle Karr (DuPont), Kelly Levin (WRI), David Lobell (Stanford Center on Food Security and the Environment), James Lomax (UN Environment), Jared Messinger (WRI), Charles McNeill (UN Environment), Joseph Monfort (DuPont), James Mulligan (WRI), Carlos Nobre (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior), Lily Odarno (WRI), Mark Peterson (DuPont), Michael Phillips (WorldFish), Becky Ramsing (JHU-CLF), Raychel Santo (JHU-CLF), Frances Seymour (WRI), Fred Stolle (WRI), Guntur Subbarao (Japan International Research Center for Agricultural Sciences), Rod Taylor (WRI), Philip Thornton (International Livestock Research Institute), Robert Townsend (World Bank), Peter Veit (WRI), Sara Walker (WRI), Arief Wijaya (WRI), Stefan Wirsenius (Chalmers University of Technology), Christy Wright (DuPont), Graham Wynne (WRI), and Edoardo Zandri (UN Environment).

    The authors extend a special thanks to Nikos Alexandratos (FAO) and Jelle Bruinsma (FAO), who were generous in providing information and guidance about the FAO agricultural projections to 2050; Michael Obersteiner (IIASA), who provided information about the GLOBIOM model; Tom Kram Fam (Netherlands Environmental Assessment Agency), who provided information for analyzing the IMAGE model results, and Benjamin Bodirsky (Potsdam Institute for Climate Research) for his thorough review of the GlobAgri-WRR model.

    In addition, the authors thank several WRI colleagues who provided research, data, analysis, and editing services in support of this synthesis report: Abraar Ahmad, Austin Clowes, Ayesha Dinshaw, Tyler Ferdinand, Rutger Hofste, Tara Mahon, Cecelia Mercer, Gerard Pozzi, Yangshengjing Qiu, and Paul Reig. We thank our colleague Liz Goldman for preparing several of the maps in the synthesis report.

    This synthesis report was improved by the careful review of its framing and argumentation by Emily Matthews, Daryl Ditz, Laura Malaguzzi Valeri, and Liz Goodwin. The synthesis report was shepherded through the publication process by WRI’s experienced publications team, particularly Emily Matthews and Maria Hart. We thank Alex Martin and Bob Livernash for their careful copyediting. We thank Carni Klirs for synthesis report design and layout. In addition, we thank Bill Dugan, Billie Kanfer, Julie Moretti, Sarah Parsons, Romain Warnault, and Lauren Zelin, for additional design, strategy, and editorial support.

    WRI is deeply grateful for the generous financial support for this synthesis report—and for the series of working papers underlying this report—from the Norwegian Ministry of Foreign Affairs, the United Nations Development Programme, United Nations Environment, the World Bank, and the institutional strategic partners listed above. In addition, we would like to thank the Bill & Melinda Gates Foundation for supporting background research on the “improving soil and water management” menu item.

    Photo credits
    Cover: Getty images, Pgs. ii, iii Sande Murunga/CIFOR, Pg. iv Pacific Disaster Center, Pg. 4 Thomas Hawk, Pg. 6 Julien Harne, Pg. 12 Ella Olsson, Pg. 20 Ollivier Girard/CIFOR, Pg. 24 IAEA Image Lab, Pg. 25 World Agroforestry Centre, Page 26. Dennis Jarvis, Pg. 28 Neil Palmer/CIAT, Pg. 30 Mokhamad Edliadi/CIFOR, Pg. 33 Patrick Shepherd/CIFOR, Pg. 35. Pedro Brancalion/Bioflora, Pg. 37 Nanang Sujana/CIFOR, Pg. 38 Heba El-Begawi/WorldFish, Pg. 42 Isabell Schulz, Pg. 46 Bob Nichols/USDA Natural Resources Conservation Service, Pg. 47 CIAT, Pg. 49 Africa Rice Center, Pg. 50 InnoAfrica, Pg. 52 Michael Trolove, Pg. 53 Kyle Spradley/Curators of the University of Missouri, Pg. 54 Anguskirk, Pg. 60 Kate Evans/CIFOR, Pg. 64 Ollivier Girard/CIFOR, Pg. 66. Axel Fassio/CIFOR, Pg. 67 Icaro Cooke Vieira/CIFOR, Pg. 73 RachelC.Photography, Pg. 74 Aditya Basrur, Pg. 77 Sharada Prasad.

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