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1. Assessing the impact of abiotic and biotic factors on seedling survival in an African montane forest

Author

Iveren Abiem, David Kenfack, and Hazel M. Chapman

Subjects
Afromontane forest, biotic neighbourhood, negative density dependence, Ngel Nyaki, Nigeria, seedling survival, Forestry, SD1-669.5, Environmental sciences, GE1-350
Abstract

Tree seedling dynamics underpin subsequent forest structure and diversity as different species/guilds respond variously to abiotic and biotic stresses. Thus, understanding differential seedling responses to stresses helps us to predict forest trajectories. Because forests vary in both environment and species composition, generalisations across tropical forests are difficult. Afromontane forests are important carbon stores, harbour high diversity and provide critical ecosystem services, yet they are vulnerable to climate change. Here, we investigate the importance of key abiotic and biotic factors on survival of seedling guilds along spatial and temporal scales in a montane forest in south-eastern Nigeria. We use data from 318 seedling plots censused every 3 months from 2017 to 2020 to identify seven key abiotic and four biotic factors influencing seedling survival. We used the Kaplan–Meier method to estimate the persistence time of 1,145 seedlings at community and guild levels. At the community level, newly recruited seedlings had a median survival time of 15 months and about 37% of the seedlings sampled where still alive after 24 months. Understory tree species survived significantly longer than the other growth form guilds and seedling survival did not differ across shade tolerance guilds. Conspecific adult density and steeper, more north facing slopes had a negative effect on tree seedlings survival. In addition, tree seedlings that recruited in October (end of wet season/beginning of dry) had lower survival probabilities compared to those that recruited in the other months. Except for initial height, seedling survival in lianas was not impacted by any of the abiotic and biotic variables tested. Our results suggest that under the current environment forest structure and diversity is changing, most noticeably lianas are increasing in abundance relative to trees.

Published
2023
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2. Gradients in the Diversity of Plants and Large Herbivores Revealed with DNA Barcoding in a Semi-Arid African Savanna

Author

Patrick T. Freeman, Robert O. Ang’ila, Duncan Kimuyu, Paul M. Musili, David Kenfack, Peter Lokeny Etelej, Molly Magid, Brian A. Gill, and Tyler R. Kartzinel

Subjects
behavioral ecology, DNA barcoding, elephant (Loxodonta africana), ForestGEO, geographic mosaic of species interactions, phylogenetic community ecology, Biology (General), QH301-705.5
Abstract

Do hotspots of plant biodiversity translate into hotspots in the abundance and diversity of large mammalian herbivores? A common expectation in community ecology is that the diversity of plants and animals should be positively correlated in space, as with the latitudinal diversity gradient and the geographic mosaic of biodiversity. Whether this pattern ‘scales down’ to landscape-level linkages between the diversity of plants or the activities of highly mobile megafauna has received less attention. We investigated spatial associations between plants and large herbivores by integrating data from a plant-DNA-barcode phylogeny, camera traps, and a comprehensive map of woody plants across the 1.2-km2 Mpala Forest Global Earth Observatory (ForestGEO) plot, Kenya. Plant and large herbivore communities were strongly associated with an underlying soil gradient, but the richness of large herbivore species was negatively correlated with the richness of woody plants. Results suggest thickets and steep terrain create associational refuges for plants by deterring megaherbivores from browsing on otherwise palatable species. Recent work using dietary DNA metabarcoding has demonstrated that large herbivores often directly control populations of the plant species they prefer to eat, and our results reinforce the important role of megaherbivores in shaping vegetation across landscapes.

Published
2022
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3. The Efficiency of DNA Barcoding in the Identification of Afromontane Forest Tree Species

Author

David Kenfack, Iveren Abiem, and Hazel Chapman

Subjects
DNA barcoding, ForestGEO, montane forest, Ngel Nyaki, species identification, Biology (General), QH301-705.5
Abstract

The identification of flowering plants using DNA barcoding proposed in last decades has slowly gained ground in Africa, where it has been successfully used to elucidate the systematics and ecology of several plant groups, and to understand their evolutionary history. Existing inferences on the effectiveness of DNA barcoding to identify African trees are mostly based on lowland forests, whereas adjacent montane forests significantly differ from the latter floristically and structurally. Here, we tested the efficiency of chloroplast DNA barcodes (rbcLa, matK, and trnH-psbA) to identify Afromontane Forest tree species in a 20.28 ha permanent plot in Ngel Nyaki, Taraba state, Nigeria. We collected, identified, and vouchered 274 individuals with diameter at breast height ≥ 1 cm belonging to 101 morphospecies, 92 genera, and 48 families. rbcLa and matK used alone or in combination performed better than in lowland forests, with the best species discrimination obtained with the two-locus combination of matK + rbcLa. The intragenic spacer trnH-psbA was too variable to align and could not be tested using the genetic distance method employed. Classic DNA barcode can be a powerful tool to identify Afromontane tree species, mainly due to the non-prevalence in these communities of species—rich genera (low species-to-genus ratio) that constitute the biggest challenge of DNA barcoding of flowering plants.

Published
2022
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6. Distribution of biomass dynamics in relation to tree size in forests across the world

Author

Camille Piponiot, Kristina J. Anderson‐Teixeira, Stuart J. Davies, David Allen, Norman A. Bourg, David F. R. P. Burslem, Dairon Cárdenas, Chia‐Hao Chang‐Yang, George Chuyong, Susan Cordell, Handanakere Shivaramaiah Dattaraja, Álvaro Duque, Sisira Ediriweera, Corneille Ewango, Zacky Ezedin, Jonah Filip, Christian P. Giardina, Robert Howe, Chang‐Fu Hsieh, Stephen P. Hubbell, Faith M. Inman‐Narahari, Akira Itoh, David Janík, David Kenfack, Kamil Král, James A. Lutz, Jean‐Remy Makana, Sean M. McMahon, William McShea, Xiangcheng Mi, Mohizah Bt. Mohamad, Vojtěch Novotný, Michael J. O'Brien, Rebecca Ostertag, Geoffrey Parker, Rolando Pérez, Haibao Ren, Glen Reynolds, Mohamad Danial Md Sabri, Lawren Sack, Ankur Shringi, Sheng‐Hsin Su, Raman Sukumar, I‐Fang Sun, Hebbalalu S. Suresh, Duncan W. Thomas, Jill Thompson, Maria Uriarte, John Vandermeer, Yunquan Wang, Ian M. Ware, George D. Weiblen, Timothy J. S. Whitfeld, Amy Wolf, Tze Leong Yao, Mingjian Yu, Zuoqiang Yuan, Jess K. Zimmerman, Daniel Zuleta, and Helene C. Muller‐Landau

Subjects
Tropical Climate, Physiology, Temperature, Biomass, Plant Science, Wood, Carbon
Abstract

Tree size shapes forest carbon dynamics and determines how trees interact with their environment, including a changing climate. Here, we conduct the first global analysis of among-site differences in how aboveground biomass stocks and fluxes are distributed with tree size. We analyzed repeat tree censuses from 25 large-scale (4-52 ha) forest plots spanning a broad climatic range over five continents to characterize how aboveground biomass, woody productivity, and woody mortality vary with tree diameter. We examined how the median, dispersion, and skewness of these size-related distributions vary with mean annual temperature and precipitation. In warmer forests, aboveground biomass, woody productivity, and woody mortality were more broadly distributed with respect to tree size. In warmer and wetter forests, aboveground biomass and woody productivity were more right skewed, with a long tail towards large trees. Small trees (1-10 cm diameter) contributed more to productivity and mortality than to biomass, highlighting the importance of including these trees in analyses of forest dynamics. Our findings provide an improved characterization of climate-driven forest differences in the size structure of aboveground biomass and dynamics of that biomass, as well as refined benchmarks for capturing climate influences in vegetation demographic models.

Published
2022
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7. Major axes of variation in tree demography across global forests

Author

Melina de Souza Leite, Sean M. McMahon, Paulo Inácio Prado, Stuart J. Davies, Alexandre Adalardo de Oliveira, Hannes P. De Deurwaerder, Salomón Aguilar, Kristina J. Anderson-Teixeira, Nurfarah Aqilah, Norman A. Bourg, Warren Y. Brockelman, Nicolas Castaño, Chia-Hao Chang-Yang, Yu-Yun Chen, George Chuyong, Keith Clay, Álvaro Duque, Sisira Ediriweera, Corneille E.N. Ewango, Gregory Gilbert, I.A.U.N. Gunatilleke, C.V.S. Gunatilleke, Robert Howe, Walter Huaraca Huasco, Akira Itoh, Daniel J. Johnson, David Kenfack, Kamil Král, Yao Tze Leong, James A. Lutz, Jean-Remy Makana, Yadvinder Malhi, William J. McShea, Mohizah Mohamad, Musalmah Nasardin, Anuttara Nathalang, Geoffrey Parker, Renan Parmigiani, Rolando Pérez, Richard P. Phillips, Pavel Šamonil, I-Fang Sun, Sylvester Tan, Duncan Thomas, Jill Thompson, María Uriarte, Amy Wolf, Jess Zimmerman, Daniel Zuleta, Marco D. Visser, and Lisa Hülsmann

Abstract

AimGlobal forests and their structural and functional features are shaped by many mechanisms that impact tree vital rates. Although many studies have tried to quantify how specific mechanisms influence vital rates, their relative importance among forests remains unclear. We aimed to assess the patterns of variation in vital rates among species and in space and time across forests to understand and provide a baseline for expectations of the relative importance of the different mechanisms in different contexts.Location21 forest plots worldwide.Time period1981-2021Major taxa studiedWoody plantsMethodsWe developed a conceptual and statistical framework (variance partitioning of multilevel models) that attributes the variability in growth, mortality, and recruitment to variation in species, space, and time, and their interactions, which we refer to asorganising principles(OPs). We applied it to data from 21 forest plots covering more than 2.9 million trees of approximately 6,500 species.ResultsDifferences among species, thespeciesOP, were a major source of variability in tree vital rates, explaining 28-33% of demographic variance alone, and in interaction withspace14-17%, totalling 40-43%. Models with small spatial grain sizes (quadrats at 5 × 5 m) retained most of the spatial OP, but a large proportion of variance remained unexplained (31-55%). The average variability among species declined with species richness across forests, indicating that diverse forests featured smaller interspecific differences in vital rates.Main conclusionsDecomposing variance in vital rates into the proposed OPs showed that taxonomy is crucial to predictions and understanding of tree demography. Our framework has a high potential for identifying the structuring mechanisms of global forest dynamics as it highlights the most promising avenues for future research both in terms of understanding the relative contributions of mechanisms to forest demography and diversity and for improving projections of forest ecosystems.

Published
2023
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8. Making forest data fair and open

Author

Renato A. F. de Lima, Oliver L. Phillips, Alvaro Duque, J. Sebastian Tello, Stuart J. Davies, Alexandre Adalardo de Oliveira, Sandra Muller, Euridice N. Honorio Coronado, Emilio Vilanova, Aida Cuni-Sanchez, Timothy R. Baker, Casey M. Ryan, Agustina Malizia, Simon L. Lewis, Hans ter Steege, Joice Ferreira, Beatriz Schwantes Marimon, Hong Truong Luu, Gerard Imani, Luzmila Arroyo, Cecilia Blundo, David Kenfack, Moses N. Sainge, Bonaventure Sonké, and Rodolfo Vásquez

Subjects
Ecology, Forests, Ecology, Evolution, Behavior and Systematics, Trees
Published
2022
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9. Author response for 'Evenness mediates the global relationship between forest productivity and richness'

Author

null Iris Hordijk, null Daniel S. Maynard, null Simon P. Hart, null Mo Lidong, null Hans ter Steege, null Jingjing Liang, null Sergio de‐Miguel, null Gert‐Jan Nabuurs, null Peter B. Reich, null Meinrad Abegg, null C. Yves Adou Yao, null Giorgio Alberti, null Angelica M. Almeyda Zambrano, null Braulio V. Alvarado, null Alvarez‐Davila Esteban, null Patricia Alvarez‐Loayza, null Luciana F. Alves, null Christian Ammer, null Clara Antón‐Fernández, null Alejandro Araujo‐Murakami, null Luzmila Arroyo, null Valerio Avitabile, null Gerardo A. Aymard C, null Timothy Baker, null Radomir Bałazy, null Olaf Banki, null Jorcely Barroso, null Meredith L. Bastian, null Jean‐Francois Bastin, null Luca Birigazzi, null Philippe Birnbaum, null Robert Bitariho, null Pascal Boeckx, null Frans Bongers, null Olivier Bouriaud, null Pedro H. S. Brancalion, null Susanne Brandl, null Roel Brienen, null Eben N. Broadbent, null Helge Bruelheide, null Filippo Bussotti, null Roberto Cazzolla Gatti, null Ricardo G. César, null Goran Cesljar, null Robin Chazdon, null Han Y. H. Chen, null Chelsea Chisholm, null Emil Cienciala, null Connie J. Clark, null David B. Clark, null Gabriel Colletta, null David Coomes, null Fernando Cornejo Valverde, null Jose J. Corral‐Rivas, null Philip Crim, null Jonathan Cumming, null Selvadurai Dayanandan, null André L. de Gasper, null Mathieu Decuyper, null Géraldine Derroire, null Ben DeVries, null Ilija Djordjevic, null Amaral Iêda, null Aurélie Dourdain, null Engone Obiang Nestor Laurier, null Brian Enquist, null Teresa Eyre, null Adandé Belarmain Fandohan, null Tom M. Fayle, null Leandro V. Ferreira, null Ted R. Feldpausch, null Leena Finér, null Markus Fischer, null Christine Fletcher, null Lorenzo Frizzera, null Javier G. P. Gamarra, null Damiano Gianelle, null Henry B. Glick, null David Harris, null Andrew Hector, null Andreas Hemp, null Geerten Hengeveld, null Bruno Hérault, null John Herbohn, null Annika Hillers, null Eurídice N. Honorio Coronado, null Cang Hui, null Hyunkook Cho, null Thomas Ibanez, null Il Bin Jung, null Nobuo Imai, null Andrzej M. Jagodzinski, null Bogdan Jaroszewicz, null Vivian Johanssen, null Carlos A. Joly, null Tommaso Jucker, null Viktor Karminov, null Kuswata Kartawinata, null Elizabeth Kearsley, null David Kenfack, null Deborah Kennard, null Sebastian Kepfer‐Rojas, null Gunnar Keppel, null Mohammed Latif Khan, null Timothy Killeen, null Kim Hyun Seok, null Kanehiro Kitayama, null Michael Köhl, null Henn Korjus, null Florian Kraxner, null Diana Laarmann, null Mait Lang, null Simon Lewis, null Huicui Lu, null Natalia Lukina, null Brian Maitner, null Yadvinder Malhi, null Eric Marcon, null Beatriz Schwantes Marimon, null Ben Hur Marimon‐Junior, null Andrew Robert Marshall, null Emanuel Martin, null Olga Martynenko, null Jorge A. Meave, null Omar Melo‐Cruz, null Casimiro Mendoza, null Cory Merow, null Miscicki Stanislaw, null Abel Monteagudo Mendoza, null Vanessa Moreno, null Sharif A. Mukul, null Philip Mundhenk, null Maria G. Nava‐Miranda, null David Neill, null Victor Neldner, null Radovan Nevenic, null Michael Ngugi, null Pascal A. Niklaus, null Jacek Oleksyn, null Petr Ontikov, null Edgar Ortiz‐Malavasi, null Yude Pan, null Alain Paquette, null Alexander Parada‐Gutierrez, null Elena Parfenova, null Minjee Park, null Marc Parren, null Narayanaswamy Parthasarathy, null Pablo L. Peri, null Sebastian Pfautsch, null Oliver L. Phillips, null Nicolas Picard, null Maria Teresa Piedade, null Daniel Piotto, null Nigel C. A. Pitman, null Irina Polo, null Lourens Poorter, null Axel Dalberg Poulsen, null John R. Poulsen, null Hans Pretzsch, null Freddy Ramirez Arevalo, null Zorayda Restrepo‐Correa, null Mirco Rodeghiero, null Samir Rolim, null Anand Roopsind, null Francesco Rovero, null Ervan Rutishauser, null Purabi Saikia, null Christian Salas‐Eljatib, null Peter Schall, null Dmitry Schepaschenko, null Michael Scherer‐Lorenzen, null Bernhard Schmid, null Jochen Schöngart, null Eric B. Searle, null Vladimír Šebeň, null Josep M. Serra‐Diaz, null Douglas Sheil, null Anatoly Shvidenko, null Javier Silva‐Espejo, null Marcos Silveira, null James Singh, null Plinio Sist, null Ferry Slik, null Bonaventure Sonké, null Alexandre F. Souza, null Krzysztof Stereńczak, null Jens‐Christian Svenning, null Miroslav Svoboda, null Ben Swanepoel, null Natalia Targhetta, null Nadja Tchebakova, null Raquel Thomas, null Elena Tikhonova, null Peter Umunay, null Vladimir Usoltsev, null Renato Valencia, null Fernando Valladares, null Fons van der Plas, null Do Van Tran, null Michael E. Van Nuland, null Rodolfo Vasquez Martinez, null Hans Verbeeck, null Helder Viana, null Alexander C. Vibrans, null Simone Vieira, null Klaus von Gadow, null Hua‐Feng Wang, null James Watson, null Gijsbert D. A. Werner, null Susan K. Wiser, null Florian Wittmann, null Verginia Wortel, null Roderick Zagt, null Tomasz Zawila‐Niedzwiecki, null Chunyu Zhang, null Xiuhai Zhao, null Mo Zhou, null Zhi‐Xin Zhu, null Irie Casimir Zo‐Bi, and null Thomas W. Crowther

Published
2022
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10. Consistency of demographic trade-offs across 13 (sub)tropical forests

Author

Stephan Kambach, Richard Condit, Salomón Aguilar, Helge Bruelheide, Sarayudh Bunyavejchewin, Chia‐Hao Chang‐Yang, Yu‐Yun Chen, George Chuyong, Stuart J. Davies, Sisira Ediriweera, Corneille E. N. Ewango, Edwino S. Fernando, Nimal Gunatilleke, Savitri Gunatilleke, Stephen P. Hubbell, Akira Itoh, David Kenfack, Somboon Kiratiprayoon, Yi‐Ching Lin, Jean‐Remy Makana, Mohizah Bt. Mohamad, Nantachai Pongpattananurak, Rolando Pérez, Lillian Jennifer V. Rodriguez, I‐Fang Sun, Sylvester Tan, Duncan Thomas, Jill Thompson, Maria Uriarte, Renato Valencia, Christian Wirth, S. Joseph Wright, Shu‐Hui Wu, Takuo Yamakura, Tze Leong Yao, Jess Zimmerman, and Nadja Rüger

Subjects
Ecology, Plant Science, Ecology and Environment, Ecology, Evolution, Behavior and Systematics
Abstract

1. Organisms of all species must balance their allocation to growth, survival and recruitment. Among tree species, evolution has resulted in different life-history strategies for partitioning resources to these key demographic processes. Life-history strategies in tropical forests have often been shown to align along a trade-off between fast growth and high survival, that is, the well-known fast–slow continuum. In addition, an orthogonal trade-off has been proposed between tall stature—resulting from fast growth and high survival—and recruitment success, that is, a stature−recruitment trade-off. However, it is not clear whether these two independent dimensions of life-history variation structure tropical forests worldwide. 2. We used data from 13 large-scale and long-term tropical forest monitoring plots in three continents to explore the principal trade-offs in annual growth, survival and recruitment as well as tree stature. These forests included relatively undisturbed forests as well as typhoon-disturbed forests. Life-history variation in 12 forests was structured by two orthogonal trade-offs, the growth−survival trade-off and the stature−recruitment trade-off. Pairwise Procrustes analysis revealed a high similarity of demographic relationships among forests. The small deviations were related to differences between African and Asian plots. 3. Synthesis. The fast–slow continuum and tree stature are two independent dimensions structuring many, but not all tropical tree communities. Our discovery of the consistency of demographic trade-offs and life-history strategies across different forest types from three continents substantially improves our ability to predict tropical forest dynamics worldwide.

Published
2022

11. Demographic composition, not demographic diversity, predicts biomass and turnover across temperate and tropical forests

Author

Jessica F. Needham, Daniel J. Johnson, Kristina J. Anderson‐Teixeira, Norman Bourg, Sarayudh Bunyavejchewin, Nathalie Butt, Min Cao, Dairon Cárdenas, Chia‐Hao Chang‐Yang, Yu‐Yun Chen, George Chuyong, Handanakere S. Dattaraja, Stuart J. Davies, Alvaro Duque, Corneille E. N. Ewango, Edwino S. Fernando, Rosie Fisher, Christine D. Fletcher, Robin Foster, Zhanqing Hao, Terese Hart, Chang‐Fu Hsieh, Stephen P. Hubbell, Akira Itoh, David Kenfack, Charles D. Koven, Andrew J. Larson, James A. Lutz, William McShea, Jean‐Remy Makana, Yadvinder Malhi, Toby Marthews, Mohizah Bt. Mohamad, Michael D. Morecroft, Natalia Norden, Geoffrey Parker, Ankur Shringi, Raman Sukumar, Hebbalalu S. Suresh, I‐Fang Sun, Sylvester Tan, Duncan W. Thomas, Jill Thompson, Maria Uriarte, Renato Valencia, Tze Leong Yao, Sandra L. Yap, Zuoqiang Yuan, Hu Yuehua, Jess K. Zimmerman, Daniel Zuleta, and Sean M. McMahon

Subjects
forest dynamics, Global and Planetary Change, Tropical Climate, Ecology, carbon residence time, Climate Change, Biological Sciences, Ecology and Environment, Environmental Chemistry, Biomass, species richness, aboveground biomass, ForestGEO, size-dependent survival, tree demography, Environmental Sciences, Ecosystem, General Environmental Science, Demography
Abstract

The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.

Published
2022
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12. Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

Author

Laura Duncanson, James R. Kellner, John Armston, Ralph Dubayah, David M. Minor, Steven Hancock, Sean P. Healey, Paul L. Patterson, Svetlana Saarela, Suzanne Marselis, Carlos E. Silva, Jamis Bruening, Scott J. Goetz, Hao Tang, Michelle Hofton, Bryan Blair, Scott Luthcke, Lola Fatoyinbo, Katharine Abernethy, Alfonso Alonso, Hans-Erik Andersen, Paul Aplin, Timothy R. Baker, Nicolas Barbier, Jean Francois Bastin, Peter Biber, Pascal Boeckx, Jan Bogaert, Luigi Boschetti, Peter Brehm Boucher, Doreen S. Boyd, David F.R.P. Burslem, Sofia Calvo-Rodriguez, Jérôme Chave, Robin L. Chazdon, David B. Clark, Deborah A. Clark, Warren B. Cohen, David A. Coomes, Piermaria Corona, K.C. Cushman, Mark E.J. Cutler, James W. Dalling, Michele Dalponte, Jonathan Dash, Sergio de-Miguel, Songqiu Deng, Peter Woods Ellis, Barend Erasmus, Patrick A. Fekety, Alfredo Fernandez-Landa, Antonio Ferraz, Rico Fischer, Adrian G. Fisher, Antonio García-Abril, Terje Gobakken, Jorg M. Hacker, Marco Heurich, Ross A. Hill, Chris Hopkinson, Huabing Huang, Stephen P. Hubbell, Andrew T. Hudak, Andreas Huth, Benedikt Imbach, Kathryn J. Jeffery, Masato Katoh, Elizabeth Kearsley, David Kenfack, Natascha Kljun, Nikolai Knapp, Kamil Král, Martin Krůček, Nicolas Labrière, Simon L. Lewis, Marcos Longo, Richard M. Lucas, Russell Main, Jose A. Manzanera, Rodolfo Vásquez Martínez, Renaud Mathieu, Herve Memiaghe, Victoria Meyer, Abel Monteagudo Mendoza, Alessandra Monerris, Paul Montesano, Felix Morsdorf, Erik Næsset, Laven Naidoo, Reuben Nilus, Michael O’Brien, David A. Orwig, Konstantinos Papathanassiou, Geoffrey Parker, Christopher Philipson, Oliver L. Phillips, Jan Pisek, John R. Poulsen, Hans Pretzsch, Christoph Rüdiger, Sassan Saatchi, Arturo Sanchez-Azofeifa, Nuria Sanchez-Lopez, Robert Scholes, Carlos A. Silva, Marc Simard, Andrew Skidmore, Krzysztof Stereńczak, Mihai Tanase, Chiara Torresan, Ruben Valbuena, Hans Verbeeck, Tomas Vrska, Konrad Wessels, Joanne C. White, Lee J.T. White, Eliakimu Zahabu, Carlo Zgraggen, Department of Natural Resources, UT-I-ITC-FORAGES, Faculty of Geo-Information Science and Earth Observation, University of Maryland [College Park], University of Maryland System, Brown University, University of Edinburgh, USDA Forest Service Rocky Mountain Forest and Range Experiment Station, United States Department of Agriculture (USDA), Swedish University of Agricultural Sciences (SLU), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Gembloux Agro-Bio Tech [Gembloux], and Université de Liège

Subjects
0106 biological sciences, CANOPY STRUCTURE, LiDAR, 010504 meteorology & atmospheric sciences, Soil Science, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, Geological & Geomatics Engineering, 010603 evolutionary biology, 01 natural sciences, Physical Geography and Environmental Geoscience, CARBON, Remote Sensing, ITC-HYBRID, BOREAL FOREST, HEIGHT, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Settore BIO/07 - ECOLOGIA, GEDI, Waveform, Forest, Aboveground biomass, Modeling, ddc:630, INVERSION, Computers in Earth Sciences, 0105 earth and related environmental sciences, GROUND BIOMASS, Geology, VDP::Matematikk og Naturvitenskap: 400, 15. Life on land, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, REGIONS, ddc, Geomatic Engineering, 13. Climate action, AIRBORNE LIDAR, Earth and Environmental Sciences, ITC-ISI-JOURNAL-ARTICLE, TROPICAL FOREST BIOMASS, cavelab, VEGETATION, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

© 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to- biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g., RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Published
2022
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