Author: "Vleminckx, J." - Searchworks@Jio Institute Digital Library Search Results

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31 results on '"Vleminckx, J."'

1. Utilité d'une typologie des exploitants artisanaux de bois pour contribuer à la formulation d'une politique publique en province Orientale (RD Congo)

Author: Tshimpanga, O., Lescuyer, G., Vleminckx, J., Adebu Abdala, B., and Lokombe, D.
Subjects: Economic policies, commodity markets, logging, natural resources management, Democratic Republic of Congo, Biotechnology, TP248.13-248.65, Environmental sciences, GE1-350
Abstract: Utility of a typology of timber artisanal loggers, in order to contribute to the formulation of public policy on logging in Orientale province (DRC). Description of the subject. This paper discusses the types of wood artisanal loggers, in order to assist in the formulation of public policy on logging in Orientale province (DRC). Objectives. The objective was to characterize artisanal timber in order to propose the establishment of legal channels to increase the contribution of this product to the national economy. Method. Surveys were conducted with 412 artisanal loggers active in 23 villages in Orientale province between 2010 and 2012. Factor analyses for mixed data (FAMD) and hierarchical classification on principal components (HCPC) were performed. Results. Three types of artisanal loggers were distinguished: (1) sawyers of provincial origin who supply local markets in Kinshasa; (2) sawyers of local origin that serve local markets; (3) sawyers from the other provinces of Orientale province, supplying markets in Kivu and Uganda. Conclusions. Taking into account the specificity of each of these groups of artisanal operators could improve the development and implementation of public policy measures needed to secure and formalize logging activity.
Published: 2016

2. Consistent patterns of common species across tropical tree communities

Author: Cooper, DLM, Lewis, SL, Sullivan, MJP, Prado, PI, ter Steege, H, Barbier, N, Slik, F, Sonké, B, Ewango, CEN, Adu-Bredu, S, Affum-Baffoe, K, de Aguiar, DPP, Reategui, MAA, Aiba, SI, Albuquerque, BW, Matos, FDD, Alonso, A, Amani, CA, do Amaral, DD, do Amaral, IL, Andrade, A, Miranda, IPD, Angoboy, IB, Araujo-Murakami, A, Arboleda, NC, Arroyo, L, Ashton, P, Aymard, CGA, Baider, C, Baker, TR, Balinga, MPB, Balslev, H, Banin, LF, Bánki, OS, Baraloto, C, Barbosa, EM, Barbosa, FR, Barlow, J, Bastin, JF, Beeckman, H, Begne, S, Bengone, NN, Berenguer, E, Berry, N, Bitariho, R, Boeckx, P, Bogaert, J, Bonyoma, B, Boundja, P, Bourland, N, Bosela, FB, Brambach, F, Brienen, R, Burslem, DFRP, Camargo, JL, Campelo, W, Cano, A, Cárdenas, S, López, DC, Carpanedo, RD, Márquez, YAC, Carvalho, FA, Casas, LF, Castellanos, H, Castilho, CV, Cerón, C, Chapman, CA, Chave, J, Chhang, P, Chutipong, W, Chuyong, GB, Cintra, BBL, Clark, CJ, de Souza, FC, Comiskey, JA, Coomes, DA, Valverde, FC, Correa, DF, Costa, FRC, Costa, JBP, Couteron, P, Culmsee, H, Cuni-Sanchez, A, Dallmeier, F, Damasco, G, Dauby, G, Dávila, N, Doza, HPD, De Alban, JDT, de Assis, RL, De Canniere, C, De Haulleville, T, Carim, MDV, Demarchi, LO, Dexter, KG, Di Fiore, A, Din, HHM, Disney, MI, Djiofack, BY, Djuikouo, MNK, Van Do, T, Doucet, JL, Draper, FC, Droissart, V, Duivenvoorden, JF, Engel, J, Estienne, V, Farfan-Rios, W, Fauset, S, Feeley, KJ, Feitosa, YO, Feldpausch, TR, Ferreira, C, Ferreira, J, Ferreira, LV, Fletcher, CD, Flores, BM, Fofanah, A, Foli, EG, Fonty, E, Fredriksson, GM, Fuentes, A, Galbraith, D, Gonzales, GPG, Garcia-Cabrera, K, García-Villacorta, R, Gomes, VHF, Gómez, RZ, Gonzales, T, Gribel, R, Guedes, MC, Guevara, JE, Hakeem, KR, Hall, JS, Hamer, KC, Harrison, RD, Harris, DJ, Hart, TB, Hector, A, Henkel, TW, Herbohn, J, Hockemba, MBN, Hoffman, B, Holmgren, M, Coronado, ENH, Huamantupa-Chuquimaco, I, Hubau, W, Imai, N, Irume, MV, Jansen, PA, Jeffery, KJ, Jimenez, EM, Jucker, T, Junqueira, AB, Kalamandeen, M, Kamdem, NG, Kartawinata, K, Yakusu, EK, Katembo, JM, Kearsley, E, Kenfack, D, Kessler, M, Khaing, TT, Killeen, TJ, Kitayama, K, Klitgaard, B, Labriere, N, Laumonier, Y, Laurance, SGW, Laurance, WF, Laurent, F, Le, TC, Leal, ME, Novo, EMLD, Levesley, A, Libalah, MB, Licona, JC, Lima, DD, Lindsell, JA, Lopes, A, Lopes, MA, Lovett, JC, Lowe, R, Lozada, JR, Lu, XH, Luambua, NK, Luize, BG, Maas, P, Magalhaes, JLL, Magnusson, WE, Mahayani, NPD, Makana, JR, Malhi, Y, Rincón, LM, Mansor, A, Manzatto, AG, Marimon, BS, Marimon, BH Jr, Marshall, AR, Martins, MP, Mbayu, FM, de Medeiros, MB, Mesones, I, Metali, F, Mihindou, V, Millet, J, Milliken, W, Mogollon, HF, Molino, JF, Said, MNM, Mendoza, AM, Montero, JC, Moore, S, Mostacedo, B, Pinto, LFM, Mukul, SA, Munishi, PKT, Nagamasu, H, Nascimento, HEM, Nascimento, MT, Neill, D, Nilus, R, Noronha, JC, Nsenga, L, Vargas, PN, Ojo, L, Oliveira, AA, de Oliveira, EA, Ondo, FE, Cuenca, WP, Pansini, S, Pansonato, MP, Paredes, MR, Paudel, E, Pauletto, D, Pearson, RG, Pena, JLM, Pennington, RT, Peres, CA, Permana, A, Petronelli, P, Mora, MCP, Phillips, JF, Phillips, OL, Pickavance, G, Piedade, MTF, Pitman, NCA, Ploton, P, Popelier, A, Poulsen, JR, Prieto, A, Primack, RB, Priyadi, H, Qie, L, Quaresma, AC, de Queiroz, HL, Ramirez-Angulo, H, Ramos, JF, Reis, NFC, Reitsma, J, Revilla, JDC, Riutta, T, Rivas-Torres, G, Robiansyah, I, Rocha, M, Rodrigues, DD, Rodriguez-Ronderos, ME, Rovero, F, Rozak, AH, Rudas, A, Rutishauser, E, Sabatier, D, Sagang, L, Sampaio, AF, Samsoedin, I, Satdichanh, M, Schietti, J, Schöngart, J, Scudeller, VV, Seuaturien, N, Sheil, D, Sierra, R, Silman, MR, Silva, TSF, Guimaraes, JRD, Simo-Droissart, M, Simon, MF, Sist, P, Sousa, TR, Farias, ED, Coelho, LD, Spracklen, DV, Stas, SM, Steinmetz, R, Stevenson, PR, Stropp, J, Sukri, RS, Sunderland, TCH, Suzuki, E, Swaine, MD, Tang, JW, Taplin, J, Taylor, DM, Tello, JS, Terborgh, J, Texier, N, Theilade, I, Thomas, DW, Thomas, R, Thomas, SC, Tirado, M, Toirambe, B, de Toledo, JJ, Tomlinson, KW, Torres-Lezama, A, Tran, HD, Mukendi, JT, Tumaneng, RD, Umaña, MN, Umunay, PM, Giraldo, LEU, Sandoval, EHV, Gamarra, LV, Van Andel, TR, van de Bult, M, van de Pol, J, van der Heijden, G, Vasquez, R, Vela, CIA, Venticinque, EM, Verbeeck, H, Veridiano, RKA, Vicentini, A, Vieira, ICG, Torre, EV, Villarroel, D, Zegarra, BEV, Vleminckx, J, von Hildebrand, P, Vos, VA, Vriesendorp, C, Webb, EL, White, LJT, Wich, S, Wittmann, F, Zagt, R, Zang, RG, Zartman, CE, Zemagho, L, Zent, EL, Zent, S, Cooper, DLM, Lewis, SL, Sullivan, MJP, Prado, PI, ter Steege, H, Barbier, N, Slik, F, Sonké, B, Ewango, CEN, Adu-Bredu, S, Affum-Baffoe, K, de Aguiar, DPP, Reategui, MAA, Aiba, SI, Albuquerque, BW, Matos, FDD, Alonso, A, Amani, CA, do Amaral, DD, do Amaral, IL, Andrade, A, Miranda, IPD, Angoboy, IB, Araujo-Murakami, A, Arboleda, NC, Arroyo, L, Ashton, P, Aymard, CGA, Baider, C, Baker, TR, Balinga, MPB, Balslev, H, Banin, LF, Bánki, OS, Baraloto, C, Barbosa, EM, Barbosa, FR, Barlow, J, Bastin, JF, Beeckman, H, Begne, S, Bengone, NN, Berenguer, E, Berry, N, Bitariho, R, Boeckx, P, Bogaert, J, Bonyoma, B, Boundja, P, Bourland, N, Bosela, FB, Brambach, F, Brienen, R, Burslem, DFRP, Camargo, JL, Campelo, W, Cano, A, Cárdenas, S, López, DC, Carpanedo, RD, Márquez, YAC, Carvalho, FA, Casas, LF, Castellanos, H, Castilho, CV, Cerón, C, Chapman, CA, Chave, J, Chhang, P, Chutipong, W, Chuyong, GB, Cintra, BBL, Clark, CJ, de Souza, FC, Comiskey, JA, Coomes, DA, Valverde, FC, Correa, DF, Costa, FRC, Costa, JBP, Couteron, P, Culmsee, H, Cuni-Sanchez, A, Dallmeier, F, Damasco, G, Dauby, G, Dávila, N, Doza, HPD, De Alban, JDT, de Assis, RL, De Canniere, C, De Haulleville, T, Carim, MDV, Demarchi, LO, Dexter, KG, Di Fiore, A, Din, HHM, Disney, MI, Djiofack, BY, Djuikouo, MNK, Van Do, T, Doucet, JL, Draper, FC, Droissart, V, Duivenvoorden, JF, Engel, J, Estienne, V, Farfan-Rios, W, Fauset, S, Feeley, KJ, Feitosa, YO, Feldpausch, TR, Ferreira, C, Ferreira, J, Ferreira, LV, Fletcher, CD, Flores, BM, Fofanah, A, Foli, EG, Fonty, E, Fredriksson, GM, Fuentes, A, Galbraith, D, Gonzales, GPG, Garcia-Cabrera, K, García-Villacorta, R, Gomes, VHF, Gómez, RZ, Gonzales, T, Gribel, R, Guedes, MC, Guevara, JE, Hakeem, KR, Hall, JS, Hamer, KC, Harrison, RD, Harris, DJ, Hart, TB, Hector, A, Henkel, TW, Herbohn, J, Hockemba, MBN, Hoffman, B, Holmgren, M, Coronado, ENH, Huamantupa-Chuquimaco, I, Hubau, W, Imai, N, Irume, MV, Jansen, PA, Jeffery, KJ, Jimenez, EM, Jucker, T, Junqueira, AB, Kalamandeen, M, Kamdem, NG, Kartawinata, K, Yakusu, EK, Katembo, JM, Kearsley, E, Kenfack, D, Kessler, M, Khaing, TT, Killeen, TJ, Kitayama, K, Klitgaard, B, Labriere, N, Laumonier, Y, Laurance, SGW, Laurance, WF, Laurent, F, Le, TC, Leal, ME, Novo, EMLD, Levesley, A, Libalah, MB, Licona, JC, Lima, DD, Lindsell, JA, Lopes, A, Lopes, MA, Lovett, JC, Lowe, R, Lozada, JR, Lu, XH, Luambua, NK, Luize, BG, Maas, P, Magalhaes, JLL, Magnusson, WE, Mahayani, NPD, Makana, JR, Malhi, Y, Rincón, LM, Mansor, A, Manzatto, AG, Marimon, BS, Marimon, BH Jr, Marshall, AR, Martins, MP, Mbayu, FM, de Medeiros, MB, Mesones, I, Metali, F, Mihindou, V, Millet, J, Milliken, W, Mogollon, HF, Molino, JF, Said, MNM, Mendoza, AM, Montero, JC, Moore, S, Mostacedo, B, Pinto, LFM, Mukul, SA, Munishi, PKT, Nagamasu, H, Nascimento, HEM, Nascimento, MT, Neill, D, Nilus, R, Noronha, JC, Nsenga, L, Vargas, PN, Ojo, L, Oliveira, AA, de Oliveira, EA, Ondo, FE, Cuenca, WP, Pansini, S, Pansonato, MP, Paredes, MR, Paudel, E, Pauletto, D, Pearson, RG, Pena, JLM, Pennington, RT, Peres, CA, Permana, A, Petronelli, P, Mora, MCP, Phillips, JF, Phillips, OL, Pickavance, G, Piedade, MTF, Pitman, NCA, Ploton, P, Popelier, A, Poulsen, JR, Prieto, A, Primack, RB, Priyadi, H, Qie, L, Quaresma, AC, de Queiroz, HL, Ramirez-Angulo, H, Ramos, JF, Reis, NFC, Reitsma, J, Revilla, JDC, Riutta, T, Rivas-Torres, G, Robiansyah, I, Rocha, M, Rodrigues, DD, Rodriguez-Ronderos, ME, Rovero, F, Rozak, AH, Rudas, A, Rutishauser, E, Sabatier, D, Sagang, L, Sampaio, AF, Samsoedin, I, Satdichanh, M, Schietti, J, Schöngart, J, Scudeller, VV, Seuaturien, N, Sheil, D, Sierra, R, Silman, MR, Silva, TSF, Guimaraes, JRD, Simo-Droissart, M, Simon, MF, Sist, P, Sousa, TR, Farias, ED, Coelho, LD, Spracklen, DV, Stas, SM, Steinmetz, R, Stevenson, PR, Stropp, J, Sukri, RS, Sunderland, TCH, Suzuki, E, Swaine, MD, Tang, JW, Taplin, J, Taylor, DM, Tello, JS, Terborgh, J, Texier, N, Theilade, I, Thomas, DW, Thomas, R, Thomas, SC, Tirado, M, Toirambe, B, de Toledo, JJ, Tomlinson, KW, Torres-Lezama, A, Tran, HD, Mukendi, JT, Tumaneng, RD, Umaña, MN, Umunay, PM, Giraldo, LEU, Sandoval, EHV, Gamarra, LV, Van Andel, TR, van de Bult, M, van de Pol, J, van der Heijden, G, Vasquez, R, Vela, CIA, Venticinque, EM, Verbeeck, H, Veridiano, RKA, Vicentini, A, Vieira, ICG, Torre, EV, Villarroel, D, Zegarra, BEV, Vleminckx, J, von Hildebrand, P, Vos, VA, Vriesendorp, C, Webb, EL, White, LJT, Wich, S, Wittmann, F, Zagt, R, Zang, RG, Zartman, CE, Zemagho, L, Zent, EL, and Zent, S
Abstract: Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations 1–6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories 7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.
Published: 2024

3. Consistent patterns of common species across tropical tree communities

Author: Sub Ecology and Biodiversity, Ecology and Biodiversity, Cooper, DLM, Lewis, SL, Sullivan, MJP, Prado, PI, ter Steege, H, Barbier, N, Slik, F, Sonké, B, Ewango, CEN, Adu-Bredu, S, Affum-Baffoe, K, de Aguiar, DPP, Reategui, MAA, Aiba, SI, Albuquerque, BW, Matos, FDD, Alonso, A, Amani, CA, do Amaral, DD, do Amaral, IL, Andrade, A, Miranda, IPD, Angoboy, IB, Araujo-Murakami, A, Arboleda, NC, Arroyo, L, Ashton, P, Aymard, CGA, Baider, C, Baker, TR, Balinga, MPB, Balslev, H, Banin, LF, Bánki, OS, Baraloto, C, Barbosa, EM, Barbosa, FR, Barlow, J, Bastin, JF, Beeckman, H, Begne, S, Bengone, NN, Berenguer, E, Berry, N, Bitariho, R, Boeckx, P, Bogaert, J, Bonyoma, B, Boundja, P, Bourland, N, Bosela, FB, Brambach, F, Brienen, R, Burslem, DFRP, Camargo, JL, Campelo, W, Cano, A, Cárdenas, S, López, DC, Carpanedo, RD, Márquez, YAC, Carvalho, FA, Casas, LF, Castellanos, H, Castilho, CV, Cerón, C, Chapman, CA, Chave, J, Chhang, P, Chutipong, W, Chuyong, GB, Cintra, BBL, Clark, CJ, de Souza, FC, Comiskey, JA, Coomes, DA, Valverde, FC, Correa, DF, Costa, FRC, Costa, JBP, Couteron, P, Culmsee, H, Cuni-Sanchez, A, Dallmeier, F, Damasco, G, Dauby, G, Dávila, N, Doza, HPD, De Alban, JDT, de Assis, RL, De Canniere, C, De Haulleville, T, Carim, MDV, Demarchi, LO, Dexter, KG, Di Fiore, A, Din, HHM, Disney, MI, Djiofack, BY, Djuikouo, MNK, Van Do, T, Doucet, JL, Draper, FC, Droissart, V, Duivenvoorden, JF, Engel, J, Estienne, V, Farfan-Rios, W, Fauset, S, Feeley, KJ, Feitosa, YO, Feldpausch, TR, Ferreira, C, Ferreira, J, Ferreira, LV, Fletcher, CD, Flores, BM, Fofanah, A, Foli, EG, Fonty, E, Fredriksson, GM, Fuentes, A, Galbraith, D, Gonzales, GPG, Garcia-Cabrera, K, García-Villacorta, R, Gomes, VHF, Gómez, RZ, Gonzales, T, Gribel, R, Guedes, MC, Guevara, JE, Hakeem, KR, Hall, JS, Hamer, KC, Harrison, RD, Harris, DJ, Hart, TB, Hector, A, Henkel, TW, Herbohn, J, Hockemba, MBN, Hoffman, B, Holmgren, M, Coronado, ENH, Huamantupa-Chuquimaco, I, Hubau, W, Imai, N, Irume, MV, Jansen, PA, Jeffery, KJ, Jimenez, EM, Jucker, T, Junqueira, AB, Kalamandeen, M, Kamdem, NG, Kartawinata, K, Yakusu, EK, Katembo, JM, Kearsley, E, Kenfack, D, Kessler, M, Khaing, TT, Killeen, TJ, Kitayama, K, Klitgaard, B, Labriere, N, Laumonier, Y, Laurance, SGW, Laurance, WF, Laurent, F, Le, TC, Leal, ME, Novo, EMLD, Levesley, A, Libalah, MB, Licona, JC, Lima, DD, Lindsell, JA, Lopes, A, Lopes, MA, Lovett, JC, Lowe, R, Lozada, JR, Lu, XH, Luambua, NK, Luize, BG, Maas, P, Magalhaes, JLL, Magnusson, WE, Mahayani, NPD, Makana, JR, Malhi, Y, Rincón, LM, Mansor, A, Manzatto, AG, Marimon, BS, Marimon, BH Jr, Marshall, AR, Martins, MP, Mbayu, FM, de Medeiros, MB, Mesones, I, Metali, F, Mihindou, V, Millet, J, Milliken, W, Mogollon, HF, Molino, JF, Said, MNM, Mendoza, AM, Montero, JC, Moore, S, Mostacedo, B, Pinto, LFM, Mukul, SA, Munishi, PKT, Nagamasu, H, Nascimento, HEM, Nascimento, MT, Neill, D, Nilus, R, Noronha, JC, Nsenga, L, Vargas, PN, Ojo, L, Oliveira, AA, de Oliveira, EA, Ondo, FE, Cuenca, WP, Pansini, S, Pansonato, MP, Paredes, MR, Paudel, E, Pauletto, D, Pearson, RG, Pena, JLM, Pennington, RT, Peres, CA, Permana, A, Petronelli, P, Mora, MCP, Phillips, JF, Phillips, OL, Pickavance, G, Piedade, MTF, Pitman, NCA, Ploton, P, Popelier, A, Poulsen, JR, Prieto, A, Primack, RB, Priyadi, H, Qie, L, Quaresma, AC, de Queiroz, HL, Ramirez-Angulo, H, Ramos, JF, Reis, NFC, Reitsma, J, Revilla, JDC, Riutta, T, Rivas-Torres, G, Robiansyah, I, Rocha, M, Rodrigues, DD, Rodriguez-Ronderos, ME, Rovero, F, Rozak, AH, Rudas, A, Rutishauser, E, Sabatier, D, Sagang, L, Sampaio, AF, Samsoedin, I, Satdichanh, M, Schietti, J, Schöngart, J, Scudeller, VV, Seuaturien, N, Sheil, D, Sierra, R, Silman, MR, Silva, TSF, Guimaraes, JRD, Simo-Droissart, M, Simon, MF, Sist, P, Sousa, TR, Farias, ED, Coelho, LD, Spracklen, DV, Stas, SM, Steinmetz, R, Stevenson, PR, Stropp, J, Sukri, RS, Sunderland, TCH, Suzuki, E, Swaine, MD, Tang, JW, Taplin, J, Taylor, DM, Tello, JS, Terborgh, J, Texier, N, Theilade, I, Thomas, DW, Thomas, R, Thomas, SC, Tirado, M, Toirambe, B, de Toledo, JJ, Tomlinson, KW, Torres-Lezama, A, Tran, HD, Mukendi, JT, Tumaneng, RD, Umaña, MN, Umunay, PM, Giraldo, LEU, Sandoval, EHV, Gamarra, LV, Van Andel, TR, van de Bult, M, van de Pol, J, van der Heijden, G, Vasquez, R, Vela, CIA, Venticinque, EM, Verbeeck, H, Veridiano, RKA, Vicentini, A, Vieira, ICG, Torre, EV, Villarroel, D, Zegarra, BEV, Vleminckx, J, von Hildebrand, P, Vos, VA, Vriesendorp, C, Webb, EL, White, LJT, Wich, S, Wittmann, F, Zagt, R, Zang, RG, Zartman, CE, Zemagho, L, Zent, EL, Zent, S, Sub Ecology and Biodiversity, Ecology and Biodiversity, Cooper, DLM, Lewis, SL, Sullivan, MJP, Prado, PI, ter Steege, H, Barbier, N, Slik, F, Sonké, B, Ewango, CEN, Adu-Bredu, S, Affum-Baffoe, K, de Aguiar, DPP, Reategui, MAA, Aiba, SI, Albuquerque, BW, Matos, FDD, Alonso, A, Amani, CA, do Amaral, DD, do Amaral, IL, Andrade, A, Miranda, IPD, Angoboy, IB, Araujo-Murakami, A, Arboleda, NC, Arroyo, L, Ashton, P, Aymard, CGA, Baider, C, Baker, TR, Balinga, MPB, Balslev, H, Banin, LF, Bánki, OS, Baraloto, C, Barbosa, EM, Barbosa, FR, Barlow, J, Bastin, JF, Beeckman, H, Begne, S, Bengone, NN, Berenguer, E, Berry, N, Bitariho, R, Boeckx, P, Bogaert, J, Bonyoma, B, Boundja, P, Bourland, N, Bosela, FB, Brambach, F, Brienen, R, Burslem, DFRP, Camargo, JL, Campelo, W, Cano, A, Cárdenas, S, López, DC, Carpanedo, RD, Márquez, YAC, Carvalho, FA, Casas, LF, Castellanos, H, Castilho, CV, Cerón, C, Chapman, CA, Chave, J, Chhang, P, Chutipong, W, Chuyong, GB, Cintra, BBL, Clark, CJ, de Souza, FC, Comiskey, JA, Coomes, DA, Valverde, FC, Correa, DF, Costa, FRC, Costa, JBP, Couteron, P, Culmsee, H, Cuni-Sanchez, A, Dallmeier, F, Damasco, G, Dauby, G, Dávila, N, Doza, HPD, De Alban, JDT, de Assis, RL, De Canniere, C, De Haulleville, T, Carim, MDV, Demarchi, LO, Dexter, KG, Di Fiore, A, Din, HHM, Disney, MI, Djiofack, BY, Djuikouo, MNK, Van Do, T, Doucet, JL, Draper, FC, Droissart, V, Duivenvoorden, JF, Engel, J, Estienne, V, Farfan-Rios, W, Fauset, S, Feeley, KJ, Feitosa, YO, Feldpausch, TR, Ferreira, C, Ferreira, J, Ferreira, LV, Fletcher, CD, Flores, BM, Fofanah, A, Foli, EG, Fonty, E, Fredriksson, GM, Fuentes, A, Galbraith, D, Gonzales, GPG, Garcia-Cabrera, K, García-Villacorta, R, Gomes, VHF, Gómez, RZ, Gonzales, T, Gribel, R, Guedes, MC, Guevara, JE, Hakeem, KR, Hall, JS, Hamer, KC, Harrison, RD, Harris, DJ, Hart, TB, Hector, A, Henkel, TW, Herbohn, J, Hockemba, MBN, Hoffman, B, Holmgren, M, Coronado, ENH, Huamantupa-Chuquimaco, I, Hubau, W, Imai, N, Irume, MV, Jansen, PA, Jeffery, KJ, Jimenez, EM, Jucker, T, Junqueira, AB, Kalamandeen, M, Kamdem, NG, Kartawinata, K, Yakusu, EK, Katembo, JM, Kearsley, E, Kenfack, D, Kessler, M, Khaing, TT, Killeen, TJ, Kitayama, K, Klitgaard, B, Labriere, N, Laumonier, Y, Laurance, SGW, Laurance, WF, Laurent, F, Le, TC, Leal, ME, Novo, EMLD, Levesley, A, Libalah, MB, Licona, JC, Lima, DD, Lindsell, JA, Lopes, A, Lopes, MA, Lovett, JC, Lowe, R, Lozada, JR, Lu, XH, Luambua, NK, Luize, BG, Maas, P, Magalhaes, JLL, Magnusson, WE, Mahayani, NPD, Makana, JR, Malhi, Y, Rincón, LM, Mansor, A, Manzatto, AG, Marimon, BS, Marimon, BH Jr, Marshall, AR, Martins, MP, Mbayu, FM, de Medeiros, MB, Mesones, I, Metali, F, Mihindou, V, Millet, J, Milliken, W, Mogollon, HF, Molino, JF, Said, MNM, Mendoza, AM, Montero, JC, Moore, S, Mostacedo, B, Pinto, LFM, Mukul, SA, Munishi, PKT, Nagamasu, H, Nascimento, HEM, Nascimento, MT, Neill, D, Nilus, R, Noronha, JC, Nsenga, L, Vargas, PN, Ojo, L, Oliveira, AA, de Oliveira, EA, Ondo, FE, Cuenca, WP, Pansini, S, Pansonato, MP, Paredes, MR, Paudel, E, Pauletto, D, Pearson, RG, Pena, JLM, Pennington, RT, Peres, CA, Permana, A, Petronelli, P, Mora, MCP, Phillips, JF, Phillips, OL, Pickavance, G, Piedade, MTF, Pitman, NCA, Ploton, P, Popelier, A, Poulsen, JR, Prieto, A, Primack, RB, Priyadi, H, Qie, L, Quaresma, AC, de Queiroz, HL, Ramirez-Angulo, H, Ramos, JF, Reis, NFC, Reitsma, J, Revilla, JDC, Riutta, T, Rivas-Torres, G, Robiansyah, I, Rocha, M, Rodrigues, DD, Rodriguez-Ronderos, ME, Rovero, F, Rozak, AH, Rudas, A, Rutishauser, E, Sabatier, D, Sagang, L, Sampaio, AF, Samsoedin, I, Satdichanh, M, Schietti, J, Schöngart, J, Scudeller, VV, Seuaturien, N, Sheil, D, Sierra, R, Silman, MR, Silva, TSF, Guimaraes, JRD, Simo-Droissart, M, Simon, MF, Sist, P, Sousa, TR, Farias, ED, Coelho, LD, Spracklen, DV, Stas, SM, Steinmetz, R, Stevenson, PR, Stropp, J, Sukri, RS, Sunderland, TCH, Suzuki, E, Swaine, MD, Tang, JW, Taplin, J, Taylor, DM, Tello, JS, Terborgh, J, Texier, N, Theilade, I, Thomas, DW, Thomas, R, Thomas, SC, Tirado, M, Toirambe, B, de Toledo, JJ, Tomlinson, KW, Torres-Lezama, A, Tran, HD, Mukendi, JT, Tumaneng, RD, Umaña, MN, Umunay, PM, Giraldo, LEU, Sandoval, EHV, Gamarra, LV, Van Andel, TR, van de Bult, M, van de Pol, J, van der Heijden, G, Vasquez, R, Vela, CIA, Venticinque, EM, Verbeeck, H, Veridiano, RKA, Vicentini, A, Vieira, ICG, Torre, EV, Villarroel, D, Zegarra, BEV, Vleminckx, J, von Hildebrand, P, Vos, VA, Vriesendorp, C, Webb, EL, White, LJT, Wich, S, Wittmann, F, Zagt, R, Zang, RG, Zartman, CE, Zemagho, L, Zent, EL, and Zent, S
Published: 2024

4. Co-limitation towards lower latitudes shapes global forest diversity gradients

Author: Liang, J., Gamarra, J.G.P., Picard, N., Zhou, M., Pijanowski, B., Jacobs, D.F., Reich, P.B., Crowther, T.W., Nabuurs, G.-J., de-Miguel, S., Fang, J., Woodall, C.W., Svenning, J.-C., Jucker, T., Bastin, J.-F., Wiser, S.K., Slik, F., Hérault, B., Alberti, G., Keppel, G., Hengeveld, G.M., Ibisch, P.L., Silva, C.A., ter Steege, H., Peri, P.L., Coomes, D.A., Searle, E.B., von Gadow, K., Jaroszewicz, B., Abbasi, A.O., Abegg, M., Yao, Y.C. A., Aguirre-Gutiérrez, J., Zambrano, A.M.A., Altman, J., Alvarez-Dávila, E., Álvarez-González, J.G., Alves, L.F., Amani, B.H.K., Amani, C.A., Ammer, C., Ilondea, B.A., Antón-Fernández, C., Avitabile, V., Aymard, G.A., Azihou, A.F., Baard, J.A., Baker, T.R., Balazy, R., Bastian, M.L., Batumike, R., Bauters, M., Beeckman, H., Benu, N.M.H., Bitariho, R., Boeckx, P., Bogaert, J., Bongers, F., Bouriaud, O., Brancalion, P.H.S., Brandl, S., Brearley, F. Q., Briseno-Reyes, J., Broadbent, E.N., Bruelheide, H., Bulte, E., Catlin, A.C., Cazzolla Gatti, R., César, R.G., Chen, H.Y. H., Chisholm, C., Cienciala, E., Colletta, G.D., Corral-Rivas, J.J., Cuchietti, A., Cuni-Sanchez, A., Dar, J.A., Dayanandan, S., de Haulleville, T., Decuyper, M., Delabye, S., Derroire, G., DeVries, B., Diisi, J., Do, T.V., Dolezal, J., Dourdain, A., Durrheim, G.P., Obiang, N.L.E., Ewango, C.E.N., Eyre, T.J., Fayle, T.M., Feunang, L.F.N., Finér, L., Fischer, M., Fridman, J., Frizzera, Lorenzo., de Gasper, A.L., Gianelle, D., Glick, H.B., Gonzalez-Elizondo, M.S., Gorenstein, Lev., Habonayo, R., Hardy, O.J., Harris, D.J., Hector, A., Hemp, A., Herold, M., Hillers, A., Hubau, W., Ibanez, T., Imai, N., Imani, G., Jagodzinski, A.M., Janecek, S., Johannsen, V.K., Joly, C.A., Jumbam, B., Kabelong, B. L. P. R., Kahsay, G.A., Karminov, V., Kartawinata, K., Kassi, J.ustin N., Kearsley, E., Kennard, D.K., Kepfer-Rojas, S., Khan, M. L., Kigomo, J.N., Kim, H.S., Klauberg, C., Klomberg, Y., Korjus, H., Kothandaraman, S., Kraxner, F., Kumar, A., Kuswandi, R., Lang, M., Lawes, M.J., Leite, R.V., Lentner, G., Lewis, S.L., Libalah, M.B., Lisingo, Janvier, López-Serrano, P.M., Lu, H., Lukina, N.V., Lykke, A.M., Maicher, V., Maitner, B.S., Marcon, E., Marshall, A.R., Martin, E. H., Martynenko, O., Mbayu, F.M., Mbuvi, M. T. E., Meave, J. A., Merow, C., Miscicki, S., Moreno, V. S., Morera, A., Mukul, S.A., Müller, J.C., Murdjoko, A., Nava-Miranda, M.G., Ndive, L.E., Neldner, V.J., Nevenic, R.V., Nforbelie, L.N., Ngoh, M.L., N’Guessan, A.E., Ngugi, M.R., Ngute, A. S. K., Njila, E. N. N., Nyako, M.C., Ochuodho, T.O., Oleksyn, J., Paquette, A., Parfenova, E.I., Park, M., Parren, M., Parthasarathy, N., Pfautsch, S., Phillips, O. L., Piedade, M.T. F., Piotto, D., Pollastrini, M., Poorter, L., Poulsen, J. R., Poulsen, A.D., Pretzsch, H., Rodeghiero, M., Rolim, S.G., Rovero, F., Rutishauser, E., Sagheb-Talebi, K., Saikia, P., Sainge, M.N., Salas-Eljatib, C., Salis, A., Schall, P., Shchepashchenko, D., Scherer-Lorenzen, M., Schmid, B., Schöngart, J., Šebeň, V., Sellan, G., Selvi, F., Serra-Diaz, J.M., Sheil, D., Shvidenko, A., Sist, P., Souza, A.F., Stereńczak, K.J., Sullivan, M. J. P., Sundarapandian, S., Svoboda, M., Swaine, M.D., Targhetta, N., Tchebakova, N., Trethowan, L.A., Tropek, R., Mukendi, J.T., Umunay, P.M., Usoltsev, V.A., Vaglio Laurin, G., Valentini, R., Valladares, F., van der Plas, F., Vega-Nieva, D.J., Verbeeck, H., Viana, H., Vibrans, A.C., Vieira, S.A., Vleminckx, J., Waite, C.E., Wang, H.-F., Wasingya, E.K., Wekesa, C., Westerlund, B., Wittmann, F., Wortel, V., Zawiła-Niedźwiecki, T., Zhang, C., Zhao, X., Zhu, J., Zhu, X., Zhu, Z.-X., Zo-Bi, I.C., Hui, C., Liang, J., Gamarra, J.G.P., Picard, N., Zhou, M., Pijanowski, B., Jacobs, D.F., Reich, P.B., Crowther, T.W., Nabuurs, G.-J., de-Miguel, S., Fang, J., Woodall, C.W., Svenning, J.-C., Jucker, T., Bastin, J.-F., Wiser, S.K., Slik, F., Hérault, B., Alberti, G., Keppel, G., Hengeveld, G.M., Ibisch, P.L., Silva, C.A., ter Steege, H., Peri, P.L., Coomes, D.A., Searle, E.B., von Gadow, K., Jaroszewicz, B., Abbasi, A.O., Abegg, M., Yao, Y.C. A., Aguirre-Gutiérrez, J., Zambrano, A.M.A., Altman, J., Alvarez-Dávila, E., Álvarez-González, J.G., Alves, L.F., Amani, B.H.K., Amani, C.A., Ammer, C., Ilondea, B.A., Antón-Fernández, C., Avitabile, V., Aymard, G.A., Azihou, A.F., Baard, J.A., Baker, T.R., Balazy, R., Bastian, M.L., Batumike, R., Bauters, M., Beeckman, H., Benu, N.M.H., Bitariho, R., Boeckx, P., Bogaert, J., Bongers, F., Bouriaud, O., Brancalion, P.H.S., Brandl, S., Brearley, F. Q., Briseno-Reyes, J., Broadbent, E.N., Bruelheide, H., Bulte, E., Catlin, A.C., Cazzolla Gatti, R., César, R.G., Chen, H.Y. H., Chisholm, C., Cienciala, E., Colletta, G.D., Corral-Rivas, J.J., Cuchietti, A., Cuni-Sanchez, A., Dar, J.A., Dayanandan, S., de Haulleville, T., Decuyper, M., Delabye, S., Derroire, G., DeVries, B., Diisi, J., Do, T.V., Dolezal, J., Dourdain, A., Durrheim, G.P., Obiang, N.L.E., Ewango, C.E.N., Eyre, T.J., Fayle, T.M., Feunang, L.F.N., Finér, L., Fischer, M., Fridman, J., Frizzera, Lorenzo., de Gasper, A.L., Gianelle, D., Glick, H.B., Gonzalez-Elizondo, M.S., Gorenstein, Lev., Habonayo, R., Hardy, O.J., Harris, D.J., Hector, A., Hemp, A., Herold, M., Hillers, A., Hubau, W., Ibanez, T., Imai, N., Imani, G., Jagodzinski, A.M., Janecek, S., Johannsen, V.K., Joly, C.A., Jumbam, B., Kabelong, B. L. P. R., Kahsay, G.A., Karminov, V., Kartawinata, K., Kassi, J.ustin N., Kearsley, E., Kennard, D.K., Kepfer-Rojas, S., Khan, M. L., Kigomo, J.N., Kim, H.S., Klauberg, C., Klomberg, Y., Korjus, H., Kothandaraman, S., Kraxner, F., Kumar, A., Kuswandi, R., Lang, M., Lawes, M.J., Leite, R.V., Lentner, G., Lewis, S.L., Libalah, M.B., Lisingo, Janvier, López-Serrano, P.M., Lu, H., Lukina, N.V., Lykke, A.M., Maicher, V., Maitner, B.S., Marcon, E., Marshall, A.R., Martin, E. H., Martynenko, O., Mbayu, F.M., Mbuvi, M. T. E., Meave, J. A., Merow, C., Miscicki, S., Moreno, V. S., Morera, A., Mukul, S.A., Müller, J.C., Murdjoko, A., Nava-Miranda, M.G., Ndive, L.E., Neldner, V.J., Nevenic, R.V., Nforbelie, L.N., Ngoh, M.L., N’Guessan, A.E., Ngugi, M.R., Ngute, A. S. K., Njila, E. N. N., Nyako, M.C., Ochuodho, T.O., Oleksyn, J., Paquette, A., Parfenova, E.I., Park, M., Parren, M., Parthasarathy, N., Pfautsch, S., Phillips, O. L., Piedade, M.T. F., Piotto, D., Pollastrini, M., Poorter, L., Poulsen, J. R., Poulsen, A.D., Pretzsch, H., Rodeghiero, M., Rolim, S.G., Rovero, F., Rutishauser, E., Sagheb-Talebi, K., Saikia, P., Sainge, M.N., Salas-Eljatib, C., Salis, A., Schall, P., Shchepashchenko, D., Scherer-Lorenzen, M., Schmid, B., Schöngart, J., Šebeň, V., Sellan, G., Selvi, F., Serra-Diaz, J.M., Sheil, D., Shvidenko, A., Sist, P., Souza, A.F., Stereńczak, K.J., Sullivan, M. J. P., Sundarapandian, S., Svoboda, M., Swaine, M.D., Targhetta, N., Tchebakova, N., Trethowan, L.A., Tropek, R., Mukendi, J.T., Umunay, P.M., Usoltsev, V.A., Vaglio Laurin, G., Valentini, R., Valladares, F., van der Plas, F., Vega-Nieva, D.J., Verbeeck, H., Viana, H., Vibrans, A.C., Vieira, S.A., Vleminckx, J., Waite, C.E., Wang, H.-F., Wasingya, E.K., Wekesa, C., Westerlund, B., Wittmann, F., Wortel, V., Zawiła-Niedźwiecki, T., Zhang, C., Zhao, X., Zhu, J., Zhu, X., Zhu, Z.-X., Zo-Bi, I.C., and Hui, C.
Published: 2022
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5. High aboveground carbon stock of African tropical montane forest

Author: Cuni-Sanchez, A, Sullivan, MJP, Platts, PJ, Lewis, SL, Marchant, R, Imani, G, Hubau, W, Abiem, I, Adhikari, H, Albrecht, T, Altman, J, Amani, C, Aneseyee, AB, Avitabile, V, Banin, L, Batumike, R, Bauters, M, Beeckman, H, Begne, S, Bennett, AC, Bitariho, R, Boeckx, P, Bogaert, J, Bräuning, A, Bulonvu, F, Burgess, F, Calders, K, Chapman, C, Chapman, H, Comiskey, J, de Haulleville, T, Decuyper, M, DeVries, B, Dolezal, J, Droissart, V, Ewango, C, Feyera, S, Gebrekirstos, A, Gereau, R, Gilpin, M, Hakizimana, D, Hall, J, Hamilton, A, Hardy, O, Hart, T, Heiskanen, J, Hemp, A, Herold, M, Hiltner, U, Horak, D, Kamdem, M, Kayijamahe, C, Kenfack, D, Kinyanjui, MJ, Klein, J, Lisingo, J, Lovett, J, Lung, M, Makana, J-R, Malhi, Y, Marshall, A, Martin, EH, Mitchard, ETA, Morel, A, Mukendi, JT, Muller, T, Nchu, F, Nyirambangutse, B, Okello, J, Peh, KS-H, Pellikka, P, Phillips, OL, Plumptre, A, Qie, L, Rovero, F, Sainge, MN, Schmitt, CB, Sedlacek, O, Ngute, ASK, Sheil, D, Sheleme, D, Simegn, TY, Simo-Droissart, M, Sonké, B, Soromessa, T, Sunderland, T, Svoboda, M, Taedoumg, H, Taplin, J, Taylor, D, Thomas, SC, Timberlake, J, Tuagben, D, Umunay, P, Uzabaho, E, Verbeeck, H, Vleminckx, J, Wallin, G, Wheeler, C, Willcock, S, Woods, JT, and Zibera, E
Abstract: Tropical forests store 40–50 per cent of terrestrial vegetation carbon 1. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests 2. Owing to climatic and soil changes with increasing elevation 3, AGC stocks are lower in tropical montane forests compared with lowland forests 2. 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 4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane 2,5,6 and lowland 7 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 8. We find that the low stem density and high abundance of large trees of African lowland forests4 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 9,10 and carbon-rich ecosystems.
Published: 2021

6. Taking the pulse of Earth's tropical forests using networks of highly distributed plots

Author: Blundo, C, Carilla, J, Grau, R, Malizia, A, Malizia, L, Osinaga-Acosta, O, Bird, M, Bradford, M, Catchpole, D, Ford, A, Graham, A, Hilbert, D, Kemp, J, Laurance, S, Laurance, W, Ishida, FY, Marshall, A, Waite, C, Woell, H, Bastin, JF, Bauters, M, Beeckman, H, Boeckx, P, Bogaert, J, De Canniere, C, de Haulleville, T, Doucet, JL, Hardy, O, Hubau, W, Kearsley, E, Verbeeck, H, Vleminckx, J, Brewer, SW, Alarcón, A, Araujo-Murakami, A, Arets, E, Arroyo, L, Chavez, E, Fredericksen, T, Villaroel, RG, Sibauty, GG, Killeen, T, Licona, JC, Lleigue, J, Mendoza, C, Murakami, S, Gutierrez, AP, Pardo, G, Peña-Claros, M, Poorter, L, Toledo, M, Cayo, JV, Viscarra, LJ, Vos, V, Ahumada, J, Almeida, E, Almeida, J, de Oliveira, EA, da Cruz, WA, de Oliveira, AA, Carvalho, FA, Obermuller, FA, Andrade, A, Vieira, SA, Aquino, AC, Aragão, L, Araújo, AC, Assis, MA, Gomes, JAMA, Baccaro, F, de Camargo, PB, Barni, P, Barroso, J, Bernacci, LC, Bordin, K, de Medeiros, MB, Broggio, I, Camargo, JL, Cardoso, D, Carniello, MA, Rochelle, ALC, Castilho, C, Castro, AAJF, Castro, W, Ribeiro, SC, Costa, F, de Oliveira, RC, Coutinho, I, Cunha, J, da Costa, L, da Costa Ferreira, L, da Costa Silva, R, da Graça Zacarias Simbine, M, de Andrade Kamimura, V, de Lima, HC, de Oliveira Melo, L, de Queiroz, L, de Sousa Lima, JR, do Espírito Santo, M, Blundo, C, Carilla, J, Grau, R, Malizia, A, Malizia, L, Osinaga-Acosta, O, Bird, M, Bradford, M, Catchpole, D, Ford, A, Graham, A, Hilbert, D, Kemp, J, Laurance, S, Laurance, W, Ishida, FY, Marshall, A, Waite, C, Woell, H, Bastin, JF, Bauters, M, Beeckman, H, Boeckx, P, Bogaert, J, De Canniere, C, de Haulleville, T, Doucet, JL, Hardy, O, Hubau, W, Kearsley, E, Verbeeck, H, Vleminckx, J, Brewer, SW, Alarcón, A, Araujo-Murakami, A, Arets, E, Arroyo, L, Chavez, E, Fredericksen, T, Villaroel, RG, Sibauty, GG, Killeen, T, Licona, JC, Lleigue, J, Mendoza, C, Murakami, S, Gutierrez, AP, Pardo, G, Peña-Claros, M, Poorter, L, Toledo, M, Cayo, JV, Viscarra, LJ, Vos, V, Ahumada, J, Almeida, E, Almeida, J, de Oliveira, EA, da Cruz, WA, de Oliveira, AA, Carvalho, FA, Obermuller, FA, Andrade, A, Vieira, SA, Aquino, AC, Aragão, L, Araújo, AC, Assis, MA, Gomes, JAMA, Baccaro, F, de Camargo, PB, Barni, P, Barroso, J, Bernacci, LC, Bordin, K, de Medeiros, MB, Broggio, I, Camargo, JL, Cardoso, D, Carniello, MA, Rochelle, ALC, Castilho, C, Castro, AAJF, Castro, W, Ribeiro, SC, Costa, F, de Oliveira, RC, Coutinho, I, Cunha, J, da Costa, L, da Costa Ferreira, L, da Costa Silva, R, da Graça Zacarias Simbine, M, de Andrade Kamimura, V, de Lima, HC, de Oliveira Melo, L, de Queiroz, L, de Sousa Lima, JR, and do Espírito Santo, M
Abstract: Tropical forests are the most diverse and productive ecosystems on Earth. While better understanding of these forests is critical for our collective future, until quite recently efforts to measure and monitor them have been largely disconnected. Networking is essential to discover the answers to questions that transcend borders and the horizons of funding agencies. Here we show how a global community is responding to the challenges of tropical ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots. We review the major scientific discoveries of this work and show how this process is changing tropical forest science. Our core approach involves linking long-term grassroots initiatives with standardized protocols and data management to generate robust scaled-up results. By connecting tropical researchers and elevating their status, our Social Research Network model recognises the key role of the data originator in scientific discovery. Conceived in 1999 with RAINFOR (South America), our permanent plot networks have been adapted to Africa (AfriTRON) and Southeast Asia (T-FORCES) and widely emulated worldwide. Now these multiple initiatives are integrated via ForestPlots.net cyber-infrastructure, linking colleagues from 54 countries across 24 plot networks. Collectively these are transforming understanding of tropical forests and their biospheric role. Together we have discovered how, where and why forest carbon and biodiversity are responding to climate change, and how they feedback on it. This long-term pan-tropical collaboration has revealed a large long-term carbon sink and its trends, as well as making clear which drivers are most important, which forest processes are affected, where they are changing, what the lags are, and the likely future responses of tropical forests as the climate continues to change. By leveraging a remarkably old technology, plot networks are sparking a very modern revolution in tropical forest sc
Published: 2021

7. Amazon tree dominance across forest strata

Author: Draper, F.C., Costa, F.R.C., Arellano, G., Phillips, O.L., Duque, A., Macía, M.J., ter Steege, H., Asner, G.P., Berenguer, E., Schietti, J., Socolar, J.B., de Souza, F.C., Dexter, K.G., Jørgensen, P.M., Tello, J.S., Magnusson, W.E., Baker, T.R., Castilho, C.V., Monteagudo-Mendoza, A., Fine, P.V.A., Ruokolainen, K., Coronado, E.N.H., Aymard, G., Dávila, N., Sáenz, M.S., Paredes, M.A.R., Engel, J., Fortunel, C., Paine, C.E.T., Goret, J.-Y., Dourdain, A., Petronelli, P., Allie, E., Andino, J.E.G., Brienen, R.J.W., Pérez, L.C., Manzatto, Â.G., Zambrana, N.Y.P., Molino, J.-F., Sabatier, D., Chave, J., Fauset, S., Villacorta, R.G., Réjou-Méchain, M., Berry, P.E., Melgaço, K., Feldpausch, T.R., Sandoval, E.V., Martinez, R.V., Mesones, I., Junqueira, A.B., Roucoux, K.H., de Toledo, J.J., Andrade, A.C., Camargo, J.L., del Aguila Pasquel, J., Santana, F.D., Laurance, W.F., Laurance, S.G., Lovejoy, T.E., Comiskey, J.A., Galbraith, D.R., Kalamandeen, M., Aguilar, G.E.N., Arenas, J.V., Guerra, C.A.A., Flores, M., Llampazo, G.F., Montenegro, L.A.T., Gomez, R.Z., Pansonato, M.P., Moscoso, V.C., Vleminckx, J., Barrantes, O.J.V., Duivenvoorden, J.F., de Sousa, S.A., Arroyo, L., Perdiz, R.O., Cravo, J.S., Marimon, B.S., Junior, B.H.M., Carvalho, F.A., Damasco, G., Disney, M., Vital, M.S., Diaz, P.R.S., Vicentini, A., Nascimento, H., Higuchi, N., Van Andel, T., Malhi, Y., Ribeiro, S.C., Terborgh, J.W., Thomas, R.S., Dallmeier, F., Prieto, A., Hilário, R.R., Salomão, R.P., Silva, R.C., Casas, L.F., Vieira, I.C.G., Araujo-Murakami, A., Arevalo, F.R., Ramírez-Angulo, H., Torre, E.V., Peñuela, M.C., Killeen, T.J., Pardo, G., Jimenez-Rojas, E., Castro, W., Cabrera, D.G., Pipoly, J., de Sousa, T.R., Silvera, M., Vos, V., Neill, D., Vargas, P.N., Vela, D.M., Aragão, L.E.O.C., Umetsu, R.K., Sierra, R., Wang, O., Young, K.R., Prestes, N.C.C.S., Massi, K.G., Huaymacari, J.R., Gutierrez, G.A.P., Aldana, A.M., Alexiades, M.N., Baccaro, F., Céron, C., Muelbert, A.E., Rios, J.M.G., Lima, A.S., Lloyd, J.L., Pitman, N.C.A., Gamarra, L.V., Oroche, C.J.C., Fuentes, A.F., Palacios, W., Patiño, S., Torres-Lezama, A., Baraloto, C., Draper, F.C., Costa, F.R.C., Arellano, G., Phillips, O.L., Duque, A., Macía, M.J., ter Steege, H., Asner, G.P., Berenguer, E., Schietti, J., Socolar, J.B., de Souza, F.C., Dexter, K.G., Jørgensen, P.M., Tello, J.S., Magnusson, W.E., Baker, T.R., Castilho, C.V., Monteagudo-Mendoza, A., Fine, P.V.A., Ruokolainen, K., Coronado, E.N.H., Aymard, G., Dávila, N., Sáenz, M.S., Paredes, M.A.R., Engel, J., Fortunel, C., Paine, C.E.T., Goret, J.-Y., Dourdain, A., Petronelli, P., Allie, E., Andino, J.E.G., Brienen, R.J.W., Pérez, L.C., Manzatto, Â.G., Zambrana, N.Y.P., Molino, J.-F., Sabatier, D., Chave, J., Fauset, S., Villacorta, R.G., Réjou-Méchain, M., Berry, P.E., Melgaço, K., Feldpausch, T.R., Sandoval, E.V., Martinez, R.V., Mesones, I., Junqueira, A.B., Roucoux, K.H., de Toledo, J.J., Andrade, A.C., Camargo, J.L., del Aguila Pasquel, J., Santana, F.D., Laurance, W.F., Laurance, S.G., Lovejoy, T.E., Comiskey, J.A., Galbraith, D.R., Kalamandeen, M., Aguilar, G.E.N., Arenas, J.V., Guerra, C.A.A., Flores, M., Llampazo, G.F., Montenegro, L.A.T., Gomez, R.Z., Pansonato, M.P., Moscoso, V.C., Vleminckx, J., Barrantes, O.J.V., Duivenvoorden, J.F., de Sousa, S.A., Arroyo, L., Perdiz, R.O., Cravo, J.S., Marimon, B.S., Junior, B.H.M., Carvalho, F.A., Damasco, G., Disney, M., Vital, M.S., Diaz, P.R.S., Vicentini, A., Nascimento, H., Higuchi, N., Van Andel, T., Malhi, Y., Ribeiro, S.C., Terborgh, J.W., Thomas, R.S., Dallmeier, F., Prieto, A., Hilário, R.R., Salomão, R.P., Silva, R.C., Casas, L.F., Vieira, I.C.G., Araujo-Murakami, A., Arevalo, F.R., Ramírez-Angulo, H., Torre, E.V., Peñuela, M.C., Killeen, T.J., Pardo, G., Jimenez-Rojas, E., Castro, W., Cabrera, D.G., Pipoly, J., de Sousa, T.R., Silvera, M., Vos, V., Neill, D., Vargas, P.N., Vela, D.M., Aragão, L.E.O.C., Umetsu, R.K., Sierra, R., Wang, O., Young, K.R., Prestes, N.C.C.S., Massi, K.G., Huaymacari, J.R., Gutierrez, G.A.P., Aldana, A.M., Alexiades, M.N., Baccaro, F., Céron, C., Muelbert, A.E., Rios, J.M.G., Lima, A.S., Lloyd, J.L., Pitman, N.C.A., Gamarra, L.V., Oroche, C.J.C., Fuentes, A.F., Palacios, W., Patiño, S., Torres-Lezama, A., and Baraloto, C.
Abstract: The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare but a few are common across the region. Indeed, just 227 ‘hyperdominant’ species account for >50% of all individuals >10 cm diameter at 1.3 m in height. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size class and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a large floristic dataset to show that, while hyperdominance is a universal phenomenon across forest strata, different species dominate the forest understory, midstory and canopy. We further find that, although species belonging to a range of phylogenetically dispersed lineages have become hyperdominant in small size classes, hyperdominants in large size classes are restricted to a few lineages. Our results demonstrate that it is essential to consider all forest strata to understand regional patterns of dominance and composition in Amazonia. More generally, through the lens of 654 hyperdominant species, we outline a tractable pathway for understanding the functioning of half of Amazonian forests across vertical strata and geographical locations.
Published: 2021

8. Long-term thermal sensitivity of Earth's tropical forests

Author: Sullivan, M.J.P., Lewis, S.L., Affum-Baffoe, K., Castilho, C., Costa, F., Sanchez, A.C., Ewango, C.E.N., Hubau, W., Marimon, B., Monteagudo-Mendoza, A., Qie, L., Sonké, B., Martinez, R.V., Baker, T.R., Brienen, R.J.W., Feldpausch, T.R., Galbraith, D., Gloor, M., Malhi, Y., Aiba, S.-I., Alexiades, M.N., Almeida, E.C., de Oliveira, E.A., Dávila, E.Á., Loayza, P.A., Andrade, A., Vieira, S.A., Aragão, L.E.O.C., Araujo-Murakami, A., Arets, E.J.M.M., Arroyo, L., Ashton, P., Aymard C, G., Baccaro, F.B., Banin, L.F., Baraloto, C., Camargo, P.B., Barlow, J., Barroso, J., Bastin, J.-F., Batterman, S.A., Beeckman, H., Begne, S.K., Bennett, A.C., Berenguer, E., Berry, N., Blanc, L., Boeckx, P., Bogaert, J., Bonal, D., Bongers, F., Bradford, M., Brearley, F.Q., Brncic, T., Brown, F., Burban, B., Camargo, J.L., Castro, W., Céron, C., Ribeiro, S.C., Moscoso, V.C., Chave, J., Chezeaux, E., Clark, C.J., de Souza, F.C., Collins, M., Comiskey, J.A., Valverde, F.C., Medina, M.C., da Costa, L., Dančák, M., Dargie, G.C., Davies, S., Cardozo, N.D., de Haulleville, T., de Medeiros, M.B., Del Aguila Pasquel, J., Derroire, G., Di Fiore, A., Doucet, J.-L., Dourdain, A., Droissant, V., Duque, L.F., Ekoungoulou, R., Elias, F., Erwin, T., Esquivel-Muelbert, A., Fauset, S., Ferreira, J., Llampazo, G.F., Foli, E., Ford, A., Gilpin, M., Hall, J.S., Hamer, K.C., Hamilton, A.C., Harris, D.J., Hart, T.B., Hédl, R., Herault, B., Herrera, R., Higuchi, N., Hladik, A., Coronado, E.H., Huamantupa-Chuquimaco, I., Huasco, W.H., Jeffery, K.J., Jimenez-Rojas, E., Kalamandeen, M., Djuikouo, M.N.K., Kearsley, E., Umetsu, R.K., Kho, L.K., Killeen, T., Kitayama, K., Klitgaard, B., Koch, A., Labrière, N., Laurance, W., Laurance, S., Leal, M.E., Levesley, A., Lima, A.J.N., Lisingo, J., Lopes, A.P., Lopez-Gonzalez, G., Lovejoy, T., Lovett, J.C., Lowe, R., Magnusson, W.E., Malumbres-Olarte, J., Manzatto, ÂG., Marimon B.H., Jr, Marshall, A.R., Marthews, T., de Almeida Reis, S.M., Maycock, C., Melgaço, K., Mendoza, C., Metali, F., Mihindou, V., Milliken, W., Mitchard, E.T.A., Morandi, P.S., Mossman, H.L., Nagy, L., Nascimento, H., Neill, D., Nilus, R., Vargas, P.N., Palacios, W., Camacho, N.P., Peacock, J., Pendry, C., Peñuela Mora, M.C., Pickavance, G.C., Pipoly, J., Pitman, N., Playfair, M., Poorter, L., Poulsen, J.R., Poulsen, A.D., Preziosi, R., Prieto, A., Primack, R.B., Ramírez-Angulo, H., Reitsma, J., Réjou-Méchain, M., Correa, Z.R., de Sousa, T.R., Bayona, L.R., Roopsind, A., Rudas, A., Rutishauser, E., Abu Salim, K., Salomão, R.P., Schietti, J., Sheil, D., Silva, R.C., Espejo, J.S., Valeria, C.S., Silveira, M., Simo-Droissart, M., Simon, M.F., Singh, J., Soto Shareva, Y.C., Stahl, C., Stropp, J., Sukri, R., Sunderland, T., Svátek, M., Swaine, M.D., Swamy, V., Taedoumg, H., Talbot, J., Taplin, J., Taylor, D., Ter Steege, H., Terborgh, J., Thomas, R., Thomas, S.C., Torres-Lezama, A., Umunay, P., Gamarra, L.V., van der Heijden, G., van der Hout, P., van der Meer, P., van Nieuwstadt, M., Verbeeck, H., Vernimmen, R., Vicentini, A., Vieira, I.C.G., Torre, E.V., Vleminckx, J., Vos, V., Wang, O., White, L.J.T., Willcock, S., Woods, J.T., Wortel, V., Young, K., Zagt, R., Zemagho, L., Zuidema, P.A., Zwerts, J.A., Phillips, O.L., Sullivan, M.J.P., Lewis, S.L., Affum-Baffoe, K., Castilho, C., Costa, F., Sanchez, A.C., Ewango, C.E.N., Hubau, W., Marimon, B., Monteagudo-Mendoza, A., Qie, L., Sonké, B., Martinez, R.V., Baker, T.R., Brienen, R.J.W., Feldpausch, T.R., Galbraith, D., Gloor, M., Malhi, Y., Aiba, S.-I., Alexiades, M.N., Almeida, E.C., de Oliveira, E.A., Dávila, E.Á., Loayza, P.A., Andrade, A., Vieira, S.A., Aragão, L.E.O.C., Araujo-Murakami, A., Arets, E.J.M.M., Arroyo, L., Ashton, P., Aymard C, G., Baccaro, F.B., Banin, L.F., Baraloto, C., Camargo, P.B., Barlow, J., Barroso, J., Bastin, J.-F., Batterman, S.A., Beeckman, H., Begne, S.K., Bennett, A.C., Berenguer, E., Berry, N., Blanc, L., Boeckx, P., Bogaert, J., Bonal, D., Bongers, F., Bradford, M., Brearley, F.Q., Brncic, T., Brown, F., Burban, B., Camargo, J.L., Castro, W., Céron, C., Ribeiro, S.C., Moscoso, V.C., Chave, J., Chezeaux, E., Clark, C.J., de Souza, F.C., Collins, M., Comiskey, J.A., Valverde, F.C., Medina, M.C., da Costa, L., Dančák, M., Dargie, G.C., Davies, S., Cardozo, N.D., de Haulleville, T., de Medeiros, M.B., Del Aguila Pasquel, J., Derroire, G., Di Fiore, A., Doucet, J.-L., Dourdain, A., Droissant, V., Duque, L.F., Ekoungoulou, R., Elias, F., Erwin, T., Esquivel-Muelbert, A., Fauset, S., Ferreira, J., Llampazo, G.F., Foli, E., Ford, A., Gilpin, M., Hall, J.S., Hamer, K.C., Hamilton, A.C., Harris, D.J., Hart, T.B., Hédl, R., Herault, B., Herrera, R., Higuchi, N., Hladik, A., Coronado, E.H., Huamantupa-Chuquimaco, I., Huasco, W.H., Jeffery, K.J., Jimenez-Rojas, E., Kalamandeen, M., Djuikouo, M.N.K., Kearsley, E., Umetsu, R.K., Kho, L.K., Killeen, T., Kitayama, K., Klitgaard, B., Koch, A., Labrière, N., Laurance, W., Laurance, S., Leal, M.E., Levesley, A., Lima, A.J.N., Lisingo, J., Lopes, A.P., Lopez-Gonzalez, G., Lovejoy, T., Lovett, J.C., Lowe, R., Magnusson, W.E., Malumbres-Olarte, J., Manzatto, ÂG., Marimon B.H., Jr, Marshall, A.R., Marthews, T., de Almeida Reis, S.M., Maycock, C., Melgaço, K., Mendoza, C., Metali, F., Mihindou, V., Milliken, W., Mitchard, E.T.A., Morandi, P.S., Mossman, H.L., Nagy, L., Nascimento, H., Neill, D., Nilus, R., Vargas, P.N., Palacios, W., Camacho, N.P., Peacock, J., Pendry, C., Peñuela Mora, M.C., Pickavance, G.C., Pipoly, J., Pitman, N., Playfair, M., Poorter, L., Poulsen, J.R., Poulsen, A.D., Preziosi, R., Prieto, A., Primack, R.B., Ramírez-Angulo, H., Reitsma, J., Réjou-Méchain, M., Correa, Z.R., de Sousa, T.R., Bayona, L.R., Roopsind, A., Rudas, A., Rutishauser, E., Abu Salim, K., Salomão, R.P., Schietti, J., Sheil, D., Silva, R.C., Espejo, J.S., Valeria, C.S., Silveira, M., Simo-Droissart, M., Simon, M.F., Singh, J., Soto Shareva, Y.C., Stahl, C., Stropp, J., Sukri, R., Sunderland, T., Svátek, M., Swaine, M.D., Swamy, V., Taedoumg, H., Talbot, J., Taplin, J., Taylor, D., Ter Steege, H., Terborgh, J., Thomas, R., Thomas, S.C., Torres-Lezama, A., Umunay, P., Gamarra, L.V., van der Heijden, G., van der Hout, P., van der Meer, P., van Nieuwstadt, M., Verbeeck, H., Vernimmen, R., Vicentini, A., Vieira, I.C.G., Torre, E.V., Vleminckx, J., Vos, V., Wang, O., White, L.J.T., Willcock, S., Woods, J.T., Wortel, V., Young, K., Zagt, R., Zemagho, L., Zuidema, P.A., Zwerts, J.A., and Phillips, O.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

9. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass [data paper]

Author: Schepaschenko, D., Chave, J., Phillips, O. L., Lewis, S. L., Davies, S. J., Réjou-Méchain, Maxime, Sist, P., Scipal, K., Perger, C., Herault, B., Labriere, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Balazy, R., Bedeau, C., Berry, N., Bilous, A. M., Bilous, S. Y., Bissiengou, P., Blanc, L., Bobkova, K. S., Braslavskaya, T., Brienen, R., Burslem, Dfrp, Condit, R., Cuni-Sanchez, A., Danilina, D., Torres, D. D., Derroire, G., Descroix, L., Sotta, E. D., d'Oliveira, M. V. N., Dresel, C., Erwin, T., Evdokimenko, M. D., Falck, J., Feldpausch, T. R., Foli, E. G., Foster, R., Fritz, S., Garcia-Abril, A. D., Gornov, A., Gornova, M., Gothard-Bassebe, E., Gourlet-Fleury, S., Guedes, M., Hamer, K. C., Susanty, F. H., Higuchi, N., Coronado, E. N. H., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V. V., Kanashiro, M., Karlsson, A., Karminov, V. N., Killeen, T., Koffi, J. C. K., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L. V., Kuznetsov, M. A., Lakyda, I., Lakyda, P. I., Licona, J. C., Lucas, R. M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J. A., Marimon, B., Martinez, R. V., Martynenko, O. V., Matsala, M., Matyashuk, R. K., Mazzei, L., Memiaghe, H., Mendoza, C., Mendoza, A. M., Moroziuk, O. V., Mukhortova, L., Musa, S., Nazimova, D. I., Okuda, T., Oliveira, L. C., Ontikov, P. V., Osipov, A. F., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V. G., Rodney, K., Rozak, A. H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silveira, M., Singh, J., Sonke, B., Souza, C., Sterenczak, K., Stonozhenko, L., Sullivan, M. J. P., Szatniewska, J., Aedoumg, H. T., Ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O. V., Valbuena, R., Gamarra, L. V., Vasiliev, S., Vedrova, E. F., Verhovets, S. V., Vidal, E., Vladimirova, N. A., Vleminckx, J., Vos, V. A., Vozmitel, F. K., Wanek, W., West, T. A. P., Woell, H., Woods, J. T., Wortel, V., Yamada, T., Hajar, Z. S. N., and Zo-Bi, I. C.
Abstract: Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS- based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.
Published: 2019

10. A global reference dataset for remote sensing of forest biomass. The Forest Observation System approach

Author: Shchepashchenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B., Labrière, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Bałazy, R., Banki, O., Bedeau, C., Berry, N., Bilous, A.M., Bilous, S.Y., Bissiengou, P., Blanc, L., Bobkova, K.S., Braslavskaya, T., Brienen, R., Burslem, D., Condit, R., Cuni-Sanchez, A., Danilina, D., del Castillo Torres, D., Derroire, G., Descroix, L., Doff Sotta, E., d'Oliveira, M.V.N., Dresel, C., Erwin, T., Evdokimenko, M.D., Falck, J., Feldpausch, T.R., Foli, E.G., Foster, R., Fritz, S., Garcia-Abril, A.D., Gornov, A., Gornova, M., Gothard-Bassébé, E., Gourlet-Fleury, S., Guedes, M., Hamer, K., Susanty, F.H., Higuchi, N., Honorio Coronado, E.N., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V., Kanashiro, M., Karlsson, A., Karminov, V.N., Killeen, T., Konan, J.K., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L.V., Kuznetsov, M.A., Lakyda, I., Lakyda, P.I., Licona, J.C., Lucas, R.M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J.A., Marimon, B., Marimon Junior, B.H., Martinez, R.V., Martynenko, O.V., Matsala, M.S., Matyashuk, R.K., Mazzei, L., Memiaghe, H., Mendoza, C., Monteagudo-Mendoza, A., Morozyuk, O.V., Mukhortova, L., Musa, S., Nazimova, D.I., Okuda, T., Oliveira, L.C., Ontikov, P.V., Osipov, A.F., Gutierrez, A.P., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V., Rodney, K., Rozak, A.H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silva-Espejo, J.E., Silveira, M., Singh, J., Sonké, B., Souza, C., Stereńczak, K., Sullivan, M.J.P., Szatniewska, J., Taedoumg, H., ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O.V., Valbuena, R., Valenzuela Gamarra, L.V., Vedrova, E.F., Verhovets, S.V., Vidal, E., Vladimirova, N.A., Vleminckx, J., Vos, V.A., Vozmitel, F.K., Wanek, W., West, T.A.P., Woell, H., Woods, J.T., Wortel, V., Yamada, T., Zamah Shari, N.H., Zo-Bi, I.C., Shchepashchenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B., Labrière, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Bałazy, R., Banki, O., Bedeau, C., Berry, N., Bilous, A.M., Bilous, S.Y., Bissiengou, P., Blanc, L., Bobkova, K.S., Braslavskaya, T., Brienen, R., Burslem, D., Condit, R., Cuni-Sanchez, A., Danilina, D., del Castillo Torres, D., Derroire, G., Descroix, L., Doff Sotta, E., d'Oliveira, M.V.N., Dresel, C., Erwin, T., Evdokimenko, M.D., Falck, J., Feldpausch, T.R., Foli, E.G., Foster, R., Fritz, S., Garcia-Abril, A.D., Gornov, A., Gornova, M., Gothard-Bassébé, E., Gourlet-Fleury, S., Guedes, M., Hamer, K., Susanty, F.H., Higuchi, N., Honorio Coronado, E.N., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V., Kanashiro, M., Karlsson, A., Karminov, V.N., Killeen, T., Konan, J.K., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L.V., Kuznetsov, M.A., Lakyda, I., Lakyda, P.I., Licona, J.C., Lucas, R.M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J.A., Marimon, B., Marimon Junior, B.H., Martinez, R.V., Martynenko, O.V., Matsala, M.S., Matyashuk, R.K., Mazzei, L., Memiaghe, H., Mendoza, C., Monteagudo-Mendoza, A., Morozyuk, O.V., Mukhortova, L., Musa, S., Nazimova, D.I., Okuda, T., Oliveira, L.C., Ontikov, P.V., Osipov, A.F., Gutierrez, A.P., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V., Rodney, K., Rozak, A.H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silva-Espejo, J.E., Silveira, M., Singh, J., Sonké, B., Souza, C., Stereńczak, K., Sullivan, M.J.P., Szatniewska, J., Taedoumg, H., ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O.V., Valbuena, R., Valenzuela Gamarra, L.V., Vedrova, E.F., Verhovets, S.V., Vidal, E., Vladimirova, N.A., Vleminckx, J., Vos, V.A., Vozmitel, F.K., Wanek, W., West, T.A.P., Woell, H., Woods, J.T., Wortel, V., Yamada, T., Zamah Shari, N.H., and Zo-Bi, I.C.
Abstract: Forest biomass is an essential indicator for monitoring the Earth’s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities. Live, most up-to-date dataset is available at https://forest-observation-system.net
Published: 2019

11. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

Author: Schepaschenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B., Labrière, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Bałazy, R., Bedeau, C., Berry, N., Bilous, A.M., Bilous, S., Bissiengou, P., Blanc, L., Bobkova, .S., Braslavskaya, T., Brienen, R., Burslem, D., Condit, R., Cuni-Sanchez, A., Danilina, D., del Castillo Torres, D., Derroire, G., Descroix, L., Sotta, E.D., d’Oliveira, M.V.N., Dresel, C., Erwin, T., Evdokimenko, M.D., Falck, J., Feldpausch, T.R., Foli, E.G., Foster, R., Fritz, S., Garcia-Abril, A.D., Gornov, A., Gornova, M., Gothard-Bassébé, E., Gourlet-Fleury, S., Guedes, M., Hamer, K.C., Susanty, F.H., Higuchi, N., Coronado, E.N.H., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V.V., Kanashiro, M., Karlsson, A., Karminov, V.N., Killeen, T., Koffi, J.-C., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L.V., Kuznetsov, M.A., Lakyda, I., Lakyda, P.I., Licona, J.C., Lucas, R.M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J.A., Marimon, B., Marimon, B.H., Martinez, R.V., Martynenko, O.V., Matsala, M., Matyashuk, R.K., Mazzei, L., Memiaghe, H., Mendoza, C., Mendoza, A.M., Moroziuk, Olga V., Mukhortova, L., Musa, S., Nazimova, D.I., Okuda, T., Oliveira, L.C., Ontikov, P.V., Osipov, A., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V.G., Rodney, K., Rozak, A.H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silveira, M., Singh, J., Sonké, B., Souza, C., Stereńczak, K., Stonozhenko, L., Sullivan, M., Szatniewska, J., Taedoumg, H., ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O.V., Valbuena, R., Gamarra, L.V., Vasiliev, S., Vedrova, E.F., Verhovets, S.V., Vidal, E., Vladimirova, N.A., Vleminckx, J., Vos, V.A., Vozmitel, F.K., Wanek, W., West, T., Woell, H., Woods, J.T., Wortel, V., Yamada, T., Nur Hajar, Z., Zo-Bi, I., Schepaschenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B., Labrière, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Bałazy, R., Bedeau, C., Berry, N., Bilous, A.M., Bilous, S., Bissiengou, P., Blanc, L., Bobkova, .S., Braslavskaya, T., Brienen, R., Burslem, D., Condit, R., Cuni-Sanchez, A., Danilina, D., del Castillo Torres, D., Derroire, G., Descroix, L., Sotta, E.D., d’Oliveira, M.V.N., Dresel, C., Erwin, T., Evdokimenko, M.D., Falck, J., Feldpausch, T.R., Foli, E.G., Foster, R., Fritz, S., Garcia-Abril, A.D., Gornov, A., Gornova, M., Gothard-Bassébé, E., Gourlet-Fleury, S., Guedes, M., Hamer, K.C., Susanty, F.H., Higuchi, N., Coronado, E.N.H., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V.V., Kanashiro, M., Karlsson, A., Karminov, V.N., Killeen, T., Koffi, J.-C., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L.V., Kuznetsov, M.A., Lakyda, I., Lakyda, P.I., Licona, J.C., Lucas, R.M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J.A., Marimon, B., Marimon, B.H., Martinez, R.V., Martynenko, O.V., Matsala, M., Matyashuk, R.K., Mazzei, L., Memiaghe, H., Mendoza, C., Mendoza, A.M., Moroziuk, Olga V., Mukhortova, L., Musa, S., Nazimova, D.I., Okuda, T., Oliveira, L.C., Ontikov, P.V., Osipov, A., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V.G., Rodney, K., Rozak, A.H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silveira, M., Singh, J., Sonké, B., Souza, C., Stereńczak, K., Stonozhenko, L., Sullivan, M., Szatniewska, J., Taedoumg, H., ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O.V., Valbuena, R., Gamarra, L.V., Vasiliev, S., Vedrova, E.F., Verhovets, S.V., Vidal, E., Vladimirova, N.A., Vleminckx, J., Vos, V.A., Vozmitel, F.K., Wanek, W., West, T., Woell, H., Woods, J.T., Wortel, V., Yamada, T., Nur Hajar, Z., and Zo-Bi, I.
Abstract: Forest biomass is an essential indicator for monitoring the Earth’s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world’s forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.
Published: 2019

12. Field methods for sampling tree height for tropical forest biomass estimation

Author: Sullivan, MJP, Lewis, SL, Hubau, W, Qie, L, Baker, TR, Banin, LF, Chave, J, Sanchez, AC, Feldpausch, T, Lopez Gonzalez, G, Arets, E, Ashton, P, Bastin, JF, Berry, NJ, Bogaert, J, Boot, R, Brearley, FQ, Brienen, R, Burslem, DFRP, de Canniere, C, Chudomelová, M, Dančák, M, Ewango, C, Hédl, R, Lloyd, J, Makana, J-R, Malhi, Y, Marimon, BS, Marimon Junior, BH, Metali, F, Moore, S, Nagy, L, Vargas, PN, Pendry, C, Ramírez-Angulo, H, Reitsma, J, Rutishauser, E, Salim, KA, Sonké, B, Sukri, RS, Sunderland, T, Svátek, M, Umunay, PM, Vasquez Martinez, R, Vernimmen, RRE, Vilanova Torre, E, Vleminckx, J, Vos, V, and Phillips, OL
Subjects: Allometry, Sample size, ALLOMETRIC MODELS, DIAMETER, Above-ground biomass estimation, Ecology and Environment, Carbon stocks, Forest structure, Earth and Environmental Sciences, MAP, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, EQUATIONS, ABOVEGROUND BIOMASS, Forest inventory
Abstract: © 2018 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height–diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height. Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally derived height–diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement. Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with biomass estimates using field measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height–diameter models with low height prediction error) entirely random or diameter size-class stratified approaches. Our results indicate that even limited sampling of heights can be used to refine height–diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.
Published: 2018

13. Above-ground biomass and structure of 260 African tropical forests

Author: Lewis, S.L., Sonke, B., Sunderland, T., Begne, S.K., Lopez-Gonzalez, G., van der Heijden, G.M.F., Phillips, O.L., Affum-Baffoe, K., Baker, T.R., Banin, L., Bastin, J-F., Beeckman, H., Boeckx, P., Bogaert, J., De Canniere, C., Chezeaux, E., Clark, C.J., Collins, M., Djagbletey, G., Djuikouo, M.N.K., Droissart, V., Doucet, J.-L., Ewango, C.E.N., Fauset, S., Feldpausch, T.R., Foli, E.G., Gillet, J.-F., Hamilton, A.C., Harris, D.J., Hart, T.B., de Haulleville, T., Hladik, A., Hufkens, K., Huygens, D., Jeanmart, P., Jeffery, K., Kearsley, E., Leal, M. E., Lloyd, J., Lovett, J. C., Makana, J.-R., Malhi, Y., Marshall, A. R., Ojo, L., Peh, K. S.- H., Pickavance, G., Poulsen, J. R., Reitsma, J. M., Sheil, D., Simo, M., Steppe, K., Taedoumg, H. E., Talbot, J., Taplin, J. R. D., Taylor, D., Thomas, S. C., Toirambe, B., Verbeeck, H., Vleminckx, J., White, L. J. T., Willcock, S., Woell, H., Zemagho, L., Lewis, S.L., Sonke, B., Sunderland, T., Begne, S.K., Lopez-Gonzalez, G., van der Heijden, G.M.F., Phillips, O.L., Affum-Baffoe, K., Baker, T.R., Banin, L., Bastin, J-F., Beeckman, H., Boeckx, P., Bogaert, J., De Canniere, C., Chezeaux, E., Clark, C.J., Collins, M., Djagbletey, G., Djuikouo, M.N.K., Droissart, V., Doucet, J.-L., Ewango, C.E.N., Fauset, S., Feldpausch, T.R., Foli, E.G., Gillet, J.-F., Hamilton, A.C., Harris, D.J., Hart, T.B., de Haulleville, T., Hladik, A., Hufkens, K., Huygens, D., Jeanmart, P., Jeffery, K., Kearsley, E., Leal, M. E., Lloyd, J., Lovett, J. C., Makana, J.-R., Malhi, Y., Marshall, A. R., Ojo, L., Peh, K. S.- H., Pickavance, G., Poulsen, J. R., Reitsma, J. M., Sheil, D., Simo, M., Steppe, K., Taedoumg, H. E., Talbot, J., Taplin, J. R. D., Taylor, D., Thomas, S. C., Toirambe, B., Verbeeck, H., Vleminckx, J., White, L. J. T., Willcock, S., Woell, H., and Zemagho, L.
Abstract: We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha21 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha21) similar to those of Bornean forests, and significantly greater than east or west African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426+11 stems ha21 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C :N ratio (suggesting a positive soil phosphorus–AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes.
Published: 2013

14. Above-ground biomass and structure of 260 African tropical forests

Author: Lewis, S. L., Sonke, B., Sunderland, T., Begne, S. K., Lopez-Gonzalez, G., van der Heijden, G. M. F., Phillips, O. L., Affum-Baffoe, K., Baker, T. R., Banin, L., Bastin, J.-F., Beeckman, H., Boeckx, P., Bogaert, J., De Canniere, C., Chezeaux, E., Clark, C. J., Collins, Murray, Djagbletey, G., Djuikouo, M. N. K., Droissart, V., Doucet, J.-L., Ewango, C. E. N., Fauset, S., Feldpausch, T. R., Foli, E. G., Gillet, J.-F., Hamilton, A. C., Harris, D. J., Hart, T. B., de Haulleville, T., Hladik, A., Hufkens, K., Huygens, D., Jeanmart, P., Jeffery, K. J., Kearsley, E., Leal, M. E., Lloyd, J., Lovett, J. C., Makana, J.-R., Malhi, Y., Marshall, A. R., Ojo, L., Peh, K. S.- H., Pickavance, G., Poulsen, J. R., Reitsma, J. M., Sheil, D., Simo, M., Steppe, K., Taedoumg, H. E., Talbot, J., Taplin, J. R. D., Taylor, D., Thomas, S. C., Toirambe, B., Verbeeck, H., Vleminckx, J., White, L. J. T., Willcock, S., Woell, H., Zemagho, L., Lewis, S. L., Sonke, B., Sunderland, T., Begne, S. K., Lopez-Gonzalez, G., van der Heijden, G. M. F., Phillips, O. L., Affum-Baffoe, K., Baker, T. R., Banin, L., Bastin, J.-F., Beeckman, H., Boeckx, P., Bogaert, J., De Canniere, C., Chezeaux, E., Clark, C. J., Collins, Murray, Djagbletey, G., Djuikouo, M. N. K., Droissart, V., Doucet, J.-L., Ewango, C. E. N., Fauset, S., Feldpausch, T. R., Foli, E. G., Gillet, J.-F., Hamilton, A. C., Harris, D. J., Hart, T. B., de Haulleville, T., Hladik, A., Hufkens, K., Huygens, D., Jeanmart, P., Jeffery, K. J., Kearsley, E., Leal, M. E., Lloyd, J., Lovett, J. C., Makana, J.-R., Malhi, Y., Marshall, A. R., Ojo, L., Peh, K. S.- H., Pickavance, G., Poulsen, J. R., Reitsma, J. M., Sheil, D., Simo, M., Steppe, K., Taedoumg, H. E., Talbot, J., Taplin, J. R. D., Taylor, D., Thomas, S. C., Toirambe, B., Verbeeck, H., Vleminckx, J., White, L. J. T., Willcock, S., Woell, H., and Zemagho, L.
Abstract: We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha-1 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha-1) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low(426±11 stems ha-1 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C:Nratio (suggesting a positive soil phosphorus- AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes.

15. Co-limitation towards lower latitudes shapes global forest diversity gradients

Author: Jingjing Liang, Javier G. P. Gamarra, Nicolas Picard, Mo Zhou, Bryan Pijanowski, Douglass F. Jacobs, Peter B. Reich, Thomas W. Crowther, Gert-Jan Nabuurs, Sergio de-Miguel, Jingyun Fang, Christopher W. Woodall, Jens-Christian Svenning, Tommaso Jucker, Jean-Francois Bastin, Susan K. Wiser, Ferry Slik, Bruno Hérault, Giorgio Alberti, Gunnar Keppel, Geerten M. Hengeveld, Pierre L. Ibisch, Carlos A. Silva, Hans ter Steege, Pablo L. Peri, David A. Coomes, Eric B. Searle, Klaus von Gadow, Bogdan Jaroszewicz, Akane O. Abbasi, Meinrad Abegg, Yves C. Adou Yao, Jesús Aguirre-Gutiérrez, Angelica M. Almeyda Zambrano, Jan Altman, Esteban Alvarez-Dávila, Juan Gabriel Álvarez-González, Luciana F. Alves, Bienvenu H. K. Amani, Christian A. Amani, Christian Ammer, Bhely Angoboy Ilondea, Clara Antón-Fernández, Valerio Avitabile, Gerardo A. Aymard, Akomian F. Azihou, Johan A. Baard, Timothy R. Baker, Radomir Balazy, Meredith L. Bastian, Rodrigue Batumike, Marijn Bauters, Hans Beeckman, Nithanel Mikael Hendrik Benu, Robert Bitariho, Pascal Boeckx, Jan Bogaert, Frans Bongers, Olivier Bouriaud, Pedro H. S. Brancalion, Susanne Brandl, Francis Q. Brearley, Jaime Briseno-Reyes, Eben N. Broadbent, Helge Bruelheide, Erwin Bulte, Ann Christine Catlin, Roberto Cazzolla Gatti, Ricardo G. César, Han Y. H. Chen, Chelsea Chisholm, Emil Cienciala, Gabriel D. Colletta, José Javier Corral-Rivas, Anibal Cuchietti, Aida Cuni-Sanchez, Javid A. Dar, Selvadurai Dayanandan, Thales de Haulleville, Mathieu Decuyper, Sylvain Delabye, Géraldine Derroire, Ben DeVries, John Diisi, Tran Van Do, Jiri Dolezal, Aurélie Dourdain, Graham P. Durrheim, Nestor Laurier Engone Obiang, Corneille E. N. Ewango, Teresa J. Eyre, Tom M. Fayle, Lethicia Flavine N. Feunang, Leena Finér, Markus Fischer, Jonas Fridman, Lorenzo Frizzera, André L. de Gasper, Damiano Gianelle, Henry B. Glick, Maria Socorro Gonzalez-Elizondo, Lev Gorenstein, Richard Habonayo, Olivier J. Hardy, David J. Harris, Andrew Hector, Andreas Hemp, Martin Herold, Annika Hillers, Wannes Hubau, Thomas Ibanez, Nobuo Imai, Gerard Imani, Andrzej M. Jagodzinski, Stepan Janecek, Vivian Kvist Johannsen, Carlos A. Joly, Blaise Jumbam, Banoho L. P. R. Kabelong, Goytom Abraha Kahsay, Viktor Karminov, Kuswata Kartawinata, Justin N. Kassi, Elizabeth Kearsley, Deborah K. Kennard, Sebastian Kepfer-Rojas, Mohammed Latif Khan, John N. Kigomo, Hyun Seok Kim, Carine Klauberg, Yannick Klomberg, Henn Korjus, Subashree Kothandaraman, Florian Kraxner, Amit Kumar, Relawan Kuswandi, Mait Lang, Michael J. Lawes, Rodrigo V. Leite, Geoffrey Lentner, Simon L. Lewis, Moses B. Libalah, Janvier Lisingo, Pablito Marcelo López-Serrano, Huicui Lu, Natalia V. Lukina, Anne Mette Lykke, Vincent Maicher, Brian S. Maitner, Eric Marcon, Andrew R. Marshall, Emanuel H. Martin, Olga Martynenko, Faustin M. Mbayu, Musingo T. E. Mbuvi, Jorge A. Meave, Cory Merow, Stanislaw Miscicki, Vanessa S. Moreno, Albert Morera, Sharif A. Mukul, Jörg C. Müller, Agustinus Murdjoko, Maria Guadalupe Nava-Miranda, Litonga Elias Ndive, Victor J. Neldner, Radovan V. Nevenic, Louis N. Nforbelie, Michael L. Ngoh, Anny E. N’Guessan, Michael R. Ngugi, Alain S. K. Ngute, Emile Narcisse N. Njila, Melanie C. Nyako, Thomas O. Ochuodho, Jacek Oleksyn, Alain Paquette, Elena I. Parfenova, Minjee Park, Marc Parren, Narayanaswamy Parthasarathy, Sebastian Pfautsch, Oliver L. Phillips, Maria T. F. Piedade, Daniel Piotto, Martina Pollastrini, Lourens Poorter, John R. Poulsen, Axel Dalberg Poulsen, Hans Pretzsch, Mirco Rodeghiero, Samir G. Rolim, Francesco Rovero, Ervan Rutishauser, Khosro Sagheb-Talebi, Purabi Saikia, Moses Nsanyi Sainge, Christian Salas-Eljatib, Antonello Salis, Peter Schall, Dmitry Schepaschenko, Michael Scherer-Lorenzen, Bernhard Schmid, Jochen Schöngart, Vladimír Šebeň, Giacomo Sellan, Federico Selvi, Josep M. Serra-Diaz, Douglas Sheil, Anatoly Z. Shvidenko, Plinio Sist, Alexandre F. Souza, Krzysztof J. Stereńczak, Martin J. P. Sullivan, Somaiah Sundarapandian, Miroslav Svoboda, Mike D. Swaine, Natalia Targhetta, Nadja Tchebakova, Liam A. Trethowan, Robert Tropek, John Tshibamba Mukendi, Peter Mbanda Umunay, Vladimir A. Usoltsev, Gaia Vaglio Laurin, Riccardo Valentini, Fernando Valladares, Fons van der Plas, Daniel José Vega-Nieva, Hans Verbeeck, Helder Viana, Alexander C. Vibrans, Simone A. Vieira, Jason Vleminckx, Catherine E. Waite, Hua-Feng Wang, Eric Katembo Wasingya, Chemuku Wekesa, Bertil Westerlund, Florian Wittmann, Verginia Wortel, Tomasz Zawiła-Niedźwiecki, Chunyu Zhang, Xiuhai Zhao, Jun Zhu, Xiao Zhu, Zhi-Xin Zhu, Irie C. Zo-Bi, Cang Hui, Liang, Jingjing, Gamarra, Javier GP, Picard, Nicolas, Zhou, Mo, Keppel, Gunnar, Hui, Cang, Liang J., Gamarra J.G.P., Picard N., Zhou M., Pijanowski B., Jacobs D.F., Reich P.B., Crowther T.W., Nabuurs G.-J., de-Miguel S., Fang J., Woodall C.W., Svenning J.-C., Jucker T., Bastin J.-F., Wiser S.K., Slik F., Herault B., Alberti G., Keppel G., Hengeveld G.M., Ibisch P.L., Silva C.A., ter Steege H., Peri P.L., Coomes D.A., Searle E.B., von Gadow K., Jaroszewicz B., Abbasi A.O., Abegg M., Yao Y.C.A., Aguirre-Gutierrez J., Zambrano A.M.A., Altman J., Alvarez-Davila E., Alvarez-Gonzalez J.G., Alves L.F., Amani B.H.K., Amani C.A., Ammer C., Ilondea B.A., Anton-Fernandez C., Avitabile V., Aymard G.A., Azihou A.F., Baard J.A., Baker T.R., Balazy R., Bastian M.L., Batumike R., Bauters M., Beeckman H., Benu N.M.H., Bitariho R., Boeckx P., Bogaert J., Bongers F., Bouriaud O., Brancalion P.H.S., Brandl S., Brearley F.Q., Briseno-Reyes J., Broadbent E.N., Bruelheide H., Bulte E., Catlin A.C., Cazzolla Gatti R., Cesar R.G., Chen H.Y.H., Chisholm C., Cienciala E., Colletta G.D., Corral-Rivas J.J., Cuchietti A., Cuni-Sanchez A., Dar J.A., Dayanandan S., de Haulleville T., Decuyper M., Delabye S., Derroire G., DeVries B., Diisi J., Do T.V., Dolezal J., Dourdain A., Durrheim G.P., Obiang N.L.E., Ewango C.E.N., Eyre T.J., Fayle T.M., Feunang L.F.N., Finer L., Fischer M., Fridman J., Frizzera L., de Gasper A.L., Gianelle D., Glick H.B., Gonzalez-Elizondo M.S., Gorenstein L., Habonayo R., Hardy O.J., Harris D.J., Hector A., Hemp A., Herold M., Hillers A., Hubau W., Ibanez T., Imai N., Imani G., Jagodzinski A.M., Janecek S., Johannsen V.K., Joly C.A., Jumbam B., Kabelong B.L.P.R., Kahsay G.A., Karminov V., Kartawinata K., Kassi J.N., Kearsley E., Kennard D.K., Kepfer-Rojas S., Khan M.L., Kigomo J.N., Kim H.S., Klauberg C., Klomberg Y., Korjus H., Kothandaraman S., Kraxner F., Kumar A., Kuswandi R., Lang M., Lawes M.J., Leite R.V., Lentner G., Lewis S.L., Libalah M.B., Lisingo J., Lopez-Serrano P.M., Lu H., Lukina N.V., Lykke A.M., Maicher V., Maitner B.S., Marcon E., Marshall A.R., Martin E.H., Martynenko O., Mbayu F.M., Mbuvi M.T.E., Meave J.A., Merow C., Miscicki S., Moreno V.S., Morera A., Mukul S.A., Muller J.C., Murdjoko A., Nava-Miranda M.G., Ndive L.E., Neldner V.J., Nevenic R.V., Nforbelie L.N., Ngoh M.L., N'Guessan A.E., Ngugi M.R., Ngute A.S.K., Njila E.N.N., Nyako M.C., Ochuodho T.O., Oleksyn J., Paquette A., Parfenova E.I., Park M., Parren M., Parthasarathy N., Pfautsch S., Phillips O.L., Piedade M.T.F., Piotto D., Pollastrini M., Poorter L., Poulsen J.R., Poulsen A.D., Pretzsch H., Rodeghiero M., Rolim S.G., Rovero F., Rutishauser E., Sagheb-Talebi K., Saikia P., Sainge M.N., Salas-Eljatib C., Salis A., Schall P., Schepaschenko D., Scherer-Lorenzen M., Schmid B., Schongart J., Seben V., Sellan G., Selvi F., Serra-Diaz J.M., Sheil D., Shvidenko A.Z., Sist P., Souza A.F., Sterenczak K.J., Sullivan M.J.P., Sundarapandian S., Svoboda M., Swaine M.D., Targhetta N., Tchebakova N., Trethowan L.A., Tropek R., Mukendi J.T., Umunay P.M., Usoltsev V.A., Vaglio Laurin G., Valentini R., Valladares F., van der Plas F., Vega-Nieva D.J., Verbeeck H., Viana H., Vibrans A.C., Vieira S.A., Vleminckx J., Waite C.E., Wang H.-F., Wasingya E.K., Wekesa C., Westerlund B., Wittmann F., Wortel V., Zawila-Niedzwiecki T., Zhang C., Zhao X., Zhu J., Zhu X., Zhu Z.-X., Zo-Bi I.C., Hui C., Purdue University [West Lafayette], Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Groupement d'Interêt Public Ecosystèmes Forestiers GIP ECOFOR (GIP ECOFOR ), Forêts et Sociétés (UPR Forêts et Sociétés), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Département Environnements et Sociétés (Cirad-ES), Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-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)-Université de Montpellier (UM), SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National Polytechnique Félix Houphouët-Boigny, and Stellenbosch University
Subjects: Bos- en Landschapsecologie, WASS, Plant Ecology and Nature Conservation, Forests, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, Co-limitation, Ontwikkelingseconomie, Forest and Nature Conservation Policy, Trees, Soil, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Development Economics, Laboratory of Geo-information Science and Remote Sensing, Settore BIO/07 - ECOLOGIA, Life Science, Laboratorium voor Moleculaire Biologie, Bos- en Natuurbeleid, Forest and Landscape Ecology, Bosecologie en Bosbeheer, Laboratorium voor Geo-informatiekunde en Remote Sensing, BIOS Plant Development Systems, Vegetatie, Ecology, Evolution, Behavior and Systematics, biogeography, biodiversity, Vegetation, Ecology, Biodiversity, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, Latitudinal gradients, PE&RC, Forest Ecology and Forest Management, Bioclimatic dominance, Biogeography, LATITUDE, Plantenecologie en Natuurbeheer, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, Laboratory of Molecular Biology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Corporate Governance & Legal Services, Tree, Global LDG
Abstract: The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers. The team collaboration and manuscript development are supported by the web-based team science platform: science-i.org, with the project number 202205GFB2. We thank the following initiatives, agencies, teams and individuals for data collection and other technical support: the Global Forest Biodiversity Initiative (GFBI) for establishing the data standards and collaborative framework; United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program; University of Alaska Fairbanks; the SODEFOR, Ivory Coast; University Félix Houphouët-Boigny (UFHB, Ivory Coast); the Queensland Herbarium and past Queensland Government Forestry and Natural Resource Management departments and staff for data collection for over seven decades; and the National Forestry Commission of Mexico (CONAFOR). We thank M. Baker (Carbon Tanzania), together with a team of field assistants (Valentine and Lawrence); all persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3); the French National Forest Inventory (NFI campaigns (raw data 2005 and following annual surveys, were downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159; site accessed on 1 January 2015)); the Italian Forest Inventory (NFI campaigns raw data 2005 and following surveys were downloaded by GFBI at https://inventarioforestale.org/; site accessed on 27 April 2019); Swiss National Forest Inventory, Swiss Federal Institute for Forest, Snow and Landscape Research WSL and Federal Office for the Environment FOEN, Switzerland; the Swedish NFI, Department of Forest Resource Management, Swedish University of Agricultural Sciences SLU; the National Research Foundation (NRF) of South Africa (89967 and 109244) and the South African Research Chair Initiative; the Danish National Forestry, Department of Geosciences and Natural Resource Management, UCPH; Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES, grant number 88881.064976/2014-01); R. Ávila and S. van Tuylen, Instituto Nacional de Bosques (INAB), Guatemala, for facilitating Guatemalan data; the National Focal Center for Forest condition monitoring of Serbia (NFC), Institute of Forestry, Belgrade, Serbia; the Thünen Institute of Forest Ecosystems (Germany) for providing National Forest Inventory data; the FAO and the United Nations High Commissioner for Refugees (UNHCR) for undertaking the SAFE (Safe Access to Fuel and Energy) and CBIT-Forest projects; and the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network (AfriTRON) and the ForestPlots.net initiative for their contributions from Amazonian and African forests. The Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment are provided by the New Zealand National Vegetation Survey Databank https://nvs.landcareresearch.co.nz/. We thank the International Boreal Forest Research Association (IBFRA); the Forestry Corporation of New South Wales, Australia; the National Forest Directory of the Ministry of Environment and Sustainable Development of the Argentine Republic (MAyDS) for the plot data of the Second National Forest Inventory (INBN2); the National Forestry Authority and Ministry of Water and Environment of Uganda for their National Biomass Survey (NBS) dataset; and the Sabah Biodiversity Council and the staff from Sabah Forest Research Centre. All TEAM data are provided by the Tropical Ecology Assessment and Monitoring (TEAM) Network, a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors, with thanks to all current and previous TEAM site manager and other collaborators that helped collect data. We thank the people of the Redidoti, Pierrekondre and Cassipora village who were instrumental in assisting with the collection of data and sharing local knowledge of their forest and the dedicated members of the field crew of Kabo 2012 census. We are also thankful to FAPESC, SFB, FAO and IMA/SC for supporting the IFFSC. This research was supported in part through computational resources provided by Information Technology at Purdue, West Lafayette, Indiana.This work is supported in part by the NASA grant number 12000401 ‘Multi-sensor biodiversity framework developed from bioacoustic and space based sensor platforms’ (J. Liang, B.P.); the USDA National Institute of Food and Agriculture McIntire Stennis projects 1017711 (J. Liang) and 1016676 (M.Z.); the US National Science Foundation Biological Integration Institutes grant NSF‐DBI‐2021898 (P.B.R.); the funding by H2020 VERIFY (contract 776810) and H2020 Resonate (contract 101000574) (G.-J.N.); the TEAM project in Uganda supported by the Moore foundation and Buffett Foundation through Conservation International (CI) and Wildlife Conservation Society (WCS); the Danish Council for Independent Research | Natural Sciences (TREECHANGE, grant 6108- 00078B) and VILLUM FONDEN grant number 16549 (J.-C.S.); the Natural Environment Research Council of the UK (NERC) project NE/T011084/1 awarded to J.A.-G. and NE/S011811/1; ERC Advanced Grant 291585 (‘T-FORCES’) and a Royal Society-Wolfson Research Merit Award (O.L.P.); RAINFOR plots supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council, notably NERC Consortium Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘BIO-RED’ (NE/N012542/1); CIFOR’s Global Comparative Study on REDD+ funded by the Norwegian Agency for Development Cooperation, the Australian Department of Foreign Affairs and Trade, the European Union, the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) and donors to the CGIAR Fund; AfriTRON network plots funded by the local communities and NERC, ERC, European Union, Royal Society and Leverhume Trust; a grant from the Royal Society and the Natural Environment Research Council, UK (S.L.L.); National Science Foundation CIF21 DIBBs: EI: number 1724728 (A.C.C.); National Natural Science Foundation of China (31800374) and Shandong Provincial Natural Science Foundation (ZR2019BC083) (H.L.). UK NERC Independent Research Fellowship (grant code: NE/S01537X/1) (T.J.); a Serra-Húnter Fellowship provided by the Government of Catalonia (Spain) (S.d.-M.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.A.S.); a grant from the Franklinia Foundation (D.A.C.); Russian Science Foundation project number 19-77-300-12 (R.V.); the Takenaka Scholarship Foundation (A.O.A.); the German Research Foundation (DFG), grant number Am 149/16-4 (C.A.); the Romania National Council for Higher Education Funding, CNFIS, project number CNFIS-FDI-2022-0259 (O.B.); Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-05109 and STPGP506284) and the Canadian Foundation for Innovation (36014) (H.Y.H.C.); the project SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797) (E.C.); Consejo de Ciencia y Tecnología del estado de Durango (2019-01-155) (J.J.C.-R.); Science and Engineering Research Board (SERB), New Delhi, Government of India (file number PDF/2015/000447)— ‘Assessing the carbon sequestration potential of different forest types in Central India in response to climate change’ (J.A.D.); Investissement d’avenir grant of the ANR (CEBA: ANR-10-LABEX-0025) (G.D.); National Foundation for Science & Technology Development of Vietnam, 106-NN.06-2013.01 (T.V.D.); Queensland government, Department of Environment and Science (T.J.E.); a Czech Science Foundation Standard grant (19-14620S) (T.M.F.); European Union Seventh Framework Program (FP7/2007– 2013) under grant agreement number 265171 (L. Finer, M. Pollastrini, F. Selvi); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (J.F.); CNPq productivity grant number 311303/2020-0 (A.L.d.G.); DFG grant HE 2719/11-1,2,3; HE 2719/14-1 (A. Hemp); European Union’s Horizon Europe research project OpenEarthMonitor grant number 101059548, CGIAR Fund INIT-32-MItigation and Transformation Initiative for GHG reductions of Agrifood systems RelaTed Emissions (MITIGATE+) (M.H.); General Directorate of the State Forests, Poland (1/07; OR-2717/3/11; OR.271.3.3.2017) and the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (A.M.J.); Czech Science Foundation 18-10781 S (S.J.); Danish of Ministry of Environment, the Danish Environmental Protection Agency, Integrated Forest Monitoring Program—NFI (V.K.J.); State of São Paulo Research Foundation/FAPESP as part of the BIOTA/FAPESP Program Project Functional Gradient-PELD/BIOTA-ECOFOR 2003/12595-7 & 2012/51872-5 (C.A.J.); Danish Council for Independent Research—social sciences—grant DFF 6109– 00296 (G.A.K.); Russian Science Foundation project 21-46-07002 for the plot data collected in the Krasnoyarsk region (V.K.); BOLFOR (D.K.K.); Department of Biotechnology, New Delhi, Government of India (grant number BT/PR7928/ NDB/52/9/2006, dated 29 September 2006) (M.L.K.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (J.N.K.); Korea Forest Service (2018113A00-1820-BB01, 2013069A00-1819-AA03, and 2020185D10- 2022-AA02) and Seoul National University Big Data Institute through the Data Science Research Project 2016 (H.S.K.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.K.); CSIR, New Delhi, government of India (grant number 38(1318)12/EMR-II, dated: 3 April 2012) (S.K.); Department of Biotechnology, New Delhi, government of India (grant number BT/ PR12899/ NDB/39/506/2015 dated 20 June 2017) (A.K.); Coordination for the Improvement of Higher Education Personnel (CAPES) #88887.463733/2019-00 (R.V.L.); National Natural Science Foundation of China (31800374) (H.L.); project of CEPF RAS ‘Methodological approaches to assessing the structural organization and functioning of forest ecosystems’ (AAAA-A18-118052590019-7) funded by the Ministry of Science and Higher Education of Russia (N.V.L.); Leverhulme Trust grant to Andrew Balmford, Simon Lewis and Jon Lovett (A.R.M.); Russian Science Foundation, project 19-77-30015 for European Russia data processing (O.M.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (M.T.E.M.); the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (S.M.); the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund (A. Morera); Queensland government, Department of Environment and Science (V.J.N.); Pinnacle Group Cameroon PLC (L.N.N.); Queensland government, Department of Environment and Science (M.R.N.); the Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05201) (A.P.); the Russian Foundation for Basic Research, project number 20-05-00540 (E.I.P.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 778322 (H.P.); Science and Engineering Research Board, New Delhi, government of India (grant number YSS/2015/000479, dated 12 January 2016) (P.S.); the Chilean Government research grants Fondecyt number 1191816 and FONDEF number ID19 10421 (C.S.-E.); the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 Biodiversity Exploratories (P.S.); European Space Agency projects IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) (D. Schepaschenko); FunDivEUROPE, European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 265171 (M.S.-L.); APVV 20-0168 from the Slovak Research and Development Agency (V.S.); Manchester Metropolitan University’s Environmental Science Research Centre (G.S.); the project ‘LIFE+ ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques’ which is co-funded by the EU Life Plus programme (contract number LIFE13 ENV/PL/000048) and the National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D) (K.J.S.); Global Challenges Research Fund (QR allocation, MMU) (M.J.P.S.); Czech Science Foundation project 21-27454S (M.S.); the Russian Foundation for Basic Research, project number 20-05-00540 (N. Tchebakova); Botanical Research Fund, Coalbourn Trust, Bentham Moxon Trust, Emily Holmes scholarship (L.A.T.); the programmes of the current scientific research of the Botanical Garden of the Ural Branch of Russian Academy of Sciences (V.A.U.); FCT—Portuguese Foundation for Science and Technology—Project UIDB/04033/2020. Inventário Florestal Nacional—ICNF (H. Viana); Grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (C.W.); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (B.W.); ATTO project (grant number MCTI-FINEP 1759/10 and BMBF 01LB1001A, 01LK1602F) (F.W.); ReVaTene/ PReSeD-CI 2 is funded by the Education and Research Ministry of Côte d’Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD (I.C.Z.-B.); the National Research Foundation of South Africa (NRF, grant 89967) (C.H.). The Tropical Plant Exploration Group 70 1 ha plots in Continental Cameroon Mountains are supported by Rufford Small Grant Foundation, UK and 4 ha in Sierra Leone are supported by the Global Challenge Research Fund through Manchester Metropolitan University, UK; the National Geographic Explorer Grant, NGS-53344R-18 (A.C.-S.); University of KwaZulu-Natal Research Office grant (M.J.L.); Universidad Nacional Autónoma de México, Dirección General de Asuntos de Personal Académico, Grant PAPIIT IN-217620 (J.A.M.). Czech Science Foundation project 21-24186M (R.T., S. Delabye). Czech Science Foundation project 20-05840Y, the Czech Ministry of Education, Youth and Sports (LTAUSA19137) and the long-term research development project of the Czech Academy of Sciences no. RVO 67985939 (J.A.). The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (grant number 0452995) and the Wenner-Gren Foundation for Anthropological Research (grant number 7330) (M.B.). Research grants from Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq, Brazil) (309764/2019; 311303/2020) (A.C.V., A.L.G.). The Project of Sanya Yazhou Bay Science and Technology City (grant number CKJ-JYRC-2022-83) (H.-F.W.). The Ugandan NBS was supported with funds from the Forest Carbon Partnership Facility (FCPF), the Austrian Development Agency (ADC) and FAO. FAO’s UN-REDD Program, together with the project on ‘Native Forests and Community’ Loan BIRF number 8493-AR UNDP ARG/15/004 and the National Program for the Protection of Native Forests under UNDP funded Argentina’s INBN2.
Published: 2022

16. Flower production decreases with warmer and more humid atmospheric conditions in a western Amazonian forest.

Author: Vleminckx J, Hogan JA, Metz MR, Comita LS, Queenborough SA, Wright SJ, Valencia R, Zambrano M, and Garwood NC
Subjects: Reproducibility of Results, Forests, Plants, Climate Change, Flowers physiology, Trees physiology, Tropical Climate
Abstract: Climate models predict that everwet western Amazonian forests will face warmer and wetter atmospheric conditions, and increased cloud cover. It remains unclear how these changes will impact plant reproductive performance, such as flowering, which plays a central role in sustaining food webs and forest regeneration. Warmer and wetter nights may cause reduced flower production, via increased dark respiration rates or alteration in the reliability of flowering cue-based processes. Additionally, more persistent cloud cover should reduce the amounts of solar irradiance, which could limit flower production. We tested whether interannual variation in flower production has changed in response to fluctuations in irradiance, rainfall, temperature, and relative humidity over 18 yrs in an everwet forest in Ecuador. Analyses of 184 plant species showed that flower production declined as nighttime temperature and relative humidity increased, suggesting that warmer nights and greater atmospheric water saturation negatively impacted reproduction. Species varied in their flowering responses to climatic variables but this variation was not explained by life form or phylogeny. Our results shed light on how plant communities will respond to climatic changes in this everwet region, in which the impacts of these changes have been poorly studied compared with more seasonal Neotropical areas., (© 2023 The Authors. New Phytologist © 2023 New Phytologist Foundation.)
Published: 2024
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17. Consistent patterns of common species across tropical tree communities.

Author: Cooper DLM, Lewis SL, Sullivan MJP, Prado PI, Ter Steege H, Barbier N, Slik F, Sonké B, Ewango CEN, Adu-Bredu S, Affum-Baffoe K, de Aguiar DPP, Ahuite Reategui MA, Aiba SI, Albuquerque BW, de Almeida Matos FD, Alonso A, Amani CA, do Amaral DD, do Amaral IL, Andrade A, de Andrade Miranda IP, Angoboy IB, Araujo-Murakami A, Arboleda NC, Arroyo L, Ashton P, Aymard C GA, Baider C, Baker TR, Balinga MPB, Balslev H, Banin LF, Bánki OS, Baraloto C, Barbosa EM, Barbosa FR, Barlow J, Bastin JF, Beeckman H, Begne S, Bengone NN, Berenguer E, Berry N, Bitariho R, Boeckx P, Bogaert J, Bonyoma B, Boundja P, Bourland N, Boyemba Bosela F, Brambach F, Brienen R, Burslem DFRP, Camargo JL, Campelo W, Cano A, Cárdenas S, Cárdenas López D, de Sá Carpanedo R, Carrero Márquez YA, Carvalho FA, Casas LF, Castellanos H, Castilho CV, Cerón C, Chapman CA, Chave J, Chhang P, Chutipong W, Chuyong GB, Cintra BBL, Clark CJ, Coelho de Souza F, Comiskey JA, Coomes DA, Cornejo Valverde F, Correa DF, Costa FRC, Costa JBP, Couteron P, Culmsee H, Cuni-Sanchez A, Dallmeier F, Damasco G, Dauby G, Dávila N, Dávila Doza HP, De Alban JDT, de Assis RL, De Canniere C, De Haulleville T, de Jesus Veiga Carim M, Demarchi LO, Dexter KG, Di Fiore A, Din HHM, Disney MI, Djiofack BY, Djuikouo MK, Do TV, Doucet JL, Draper FC, Droissart V, Duivenvoorden JF, Engel J, Estienne V, Farfan-Rios W, Fauset S, Feeley KJ, Feitosa YO, Feldpausch TR, Ferreira C, Ferreira J, Ferreira LV, Fletcher CD, Flores BM, Fofanah A, Foli EG, Fonty É, Fredriksson GM, Fuentes A, Galbraith D, Gallardo Gonzales GP, Garcia-Cabrera K, García-Villacorta R, Gomes VHF, Gómez RZ, Gonzales T, Gribel R, Guedes MC, Guevara JE, Hakeem KR, Hall JS, Hamer KC, Hamilton AC, Harris DJ, Harrison RD, Hart TB, Hector A, Henkel TW, Herbohn J, Hockemba MBN, Hoffman B, Holmgren M, Honorio Coronado EN, Huamantupa-Chuquimaco I, Hubau W, Imai N, Irume MV, Jansen PA, Jeffery KJ, Jimenez EM, Jucker T, Junqueira AB, Kalamandeen M, Kamdem NG, Kartawinata K, Kasongo Yakusu E, Katembo JM, Kearsley E, Kenfack D, Kessler M, Khaing TT, Killeen TJ, Kitayama K, Klitgaard B, Labrière N, Laumonier Y, Laurance SGW, Laurance WF, Laurent F, Le TC, Le TT, Leal ME, Leão de Moraes Novo EM, Levesley A, Libalah MB, Licona JC, Lima Filho DA, Lindsell JA, Lopes A, Lopes MA, Lovett JC, Lowe R, Lozada JR, Lu X, Luambua NK, Luize BG, Maas P, Magalhães JLL, Magnusson WE, Mahayani NPD, Makana JR, Malhi Y, Maniguaje Rincón L, Mansor A, Manzatto AG, Marimon BS, Marimon-Junior BH, Marshall AR, Martins MP, Mbayu FM, de Medeiros MB, Mesones I, Metali F, Mihindou V, Millet J, Milliken W, Mogollón HF, Molino JF, Mohd Said MN, Monteagudo Mendoza A, Montero JC, Moore S, Mostacedo B, Mozombite Pinto LF, Mukul SA, Munishi PKT, Nagamasu H, Nascimento HEM, Nascimento MT, Neill D, Nilus R, Noronha JC, Nsenga L, Núñez Vargas P, Ojo L, Oliveira AA, de Oliveira EA, Ondo FE, Palacios Cuenca W, Pansini S, Pansonato MP, Paredes MR, Paudel E, Pauletto D, Pearson RG, Pena JLM, Pennington RT, Peres CA, Permana A, Petronelli P, Peñuela Mora MC, Phillips JF, Phillips OL, Pickavance G, Piedade MTF, Pitman NCA, Ploton P, Popelier A, Poulsen JR, Prieto A, Primack RB, Priyadi H, Qie L, Quaresma AC, de Queiroz HL, Ramirez-Angulo H, Ramos JF, Reis NFC, Reitsma J, Revilla JDC, Riutta T, Rivas-Torres G, Robiansyah I, Rocha M, Rodrigues DJ, Rodriguez-Ronderos ME, Rovero F, Rozak AH, Rudas A, Rutishauser E, Sabatier D, Sagang LB, Sampaio AF, Samsoedin I, Satdichanh M, Schietti J, Schöngart J, Scudeller VV, Seuaturien N, Sheil D, Sierra R, Silman MR, Silva TSF, da Silva Guimarães JR, Simo-Droissart M, Simon MF, Sist P, Sousa TR, de Sousa Farias E, de Souza Coelho L, Spracklen DV, Stas SM, Steinmetz R, Stevenson PR, Stropp J, Sukri RS, Sunderland TCH, Suzuki E, Swaine MD, Tang J, Taplin J, Taylor DM, Tello JS, Terborgh J, Texier N, Theilade I, Thomas DW, Thomas R, Thomas SC, Tirado M, Toirambe B, de Toledo JJ, Tomlinson KW, Torres-Lezama A, Tran HD, Tshibamba Mukendi J, Tumaneng RD, Umaña MN, Umunay PM, Urrego Giraldo LE, Valderrama Sandoval EH, Valenzuela Gamarra L, Van Andel TR, van de Bult M, van de Pol J, van der Heijden G, Vasquez R, Vela CIA, Venticinque EM, Verbeeck H, Veridiano RKA, Vicentini A, Vieira ICG, Vilanova Torre E, Villarroel D, Villa Zegarra BE, Vleminckx J, von Hildebrand P, Vos VA, Vriesendorp C, Webb EL, White LJT, Wich S, Wittmann F, Zagt R, Zang R, Zartman CE, Zemagho L, Zent EL, and Zent S
Subjects: Biodiversity, Africa, Asia, Southeastern, Forests, Trees anatomy & histology, Trees classification, Trees growth & development, Tropical Climate
Abstract: Trees structure the Earth's most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations 1-6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth's 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories 7 , we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world's most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees., (© 2024. The Author(s).)
Published: 2024
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18. Niche breadth of Amazonian trees increases with niche optimum across broad edaphic gradients.

Author: Vleminckx J, Barrantes OV, Fortunel C, Paine CET, Bauman D, Engel J, Petronelli P, Dávila N, Rios M, Valderrama Sandoval EH, Mesones I, Allié E, Goret JY, Draper FC, Guevara Andino JE, Béroujon S, Fine PVA, and Baraloto C
Subjects: Forests, Wood, Soil, Tropical Climate, Trees, Ecosystem
Abstract: Understanding how biotic interactions and environmental filtering mediated by soil properties shape plant community assembly is a major challenge in ecology, especially when studying complex and hyperdiverse ecosystems like tropical forests. To shed light on the influence of both factors, we examined how the edaphic optimum of species (their niche position) related to their edaphic range (their niche breadth) along different environmental gradients and how this translates into functional strategies. Here we tested four scenarios describing the shape of the niche breadth-niche position relationship, including one neutral scenario and three scenarios proposing different relative influences of abiotic and biotic factors on community assembly along a soil resource gradient. To do so, we used soil concentration data for five key nutrients (N, P, Ca, Mg, and K), along with accurate measurements of 14 leaf, stem, and root traits for 246 tree species inventoried in 101 plots located across Eastern (French Guiana) and Western (Peru) Amazonia. We found that species niche breadth increased linearly with species niche position along each soil nutrient gradient. This increase was associated with more resource acquisitive traits in the leaves and the roots for soil N, Ca, Mg, and K concentration, while it was negatively associated with wood density for soil P concentration. These observations agreed with one of our hypothetical scenarios in which species with resource conservation traits are confined to the most nutrient-depleted soils (abiotic filter), but they are outperformed by faster-growing species in more fertile conditions (biotic filter). Our results refine and strengthen support for niche theories of species assembly while providing an integrated approach to improving forest management policies., (© 2023 The Ecological Society of America.)
Published: 2023
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19. Co-limitation towards lower latitudes shapes global forest diversity gradients.

Author: Liang J, Gamarra JGP, Picard N, Zhou M, Pijanowski B, Jacobs DF, Reich PB, Crowther TW, Nabuurs GJ, de-Miguel S, Fang J, Woodall CW, Svenning JC, Jucker T, Bastin JF, Wiser SK, Slik F, Hérault B, Alberti G, Keppel G, Hengeveld GM, Ibisch PL, Silva CA, Ter Steege H, Peri PL, Coomes DA, Searle EB, von Gadow K, Jaroszewicz B, Abbasi AO, Abegg M, Yao YCA, Aguirre-Gutiérrez J, Zambrano AMA, Altman J, Alvarez-Dávila E, Álvarez-González JG, Alves LF, Amani BHK, Amani CA, Ammer C, Ilondea BA, Antón-Fernández C, Avitabile V, Aymard GA, Azihou AF, Baard JA, Baker TR, Balazy R, Bastian ML, Batumike R, Bauters M, Beeckman H, Benu NMH, Bitariho R, Boeckx P, Bogaert J, Bongers F, Bouriaud O, Brancalion PHS, Brandl S, Brearley FQ, Briseno-Reyes J, Broadbent EN, Bruelheide H, Bulte E, Catlin AC, Cazzolla Gatti R, César RG, Chen HYH, Chisholm C, Cienciala E, Colletta GD, Corral-Rivas JJ, Cuchietti A, Cuni-Sanchez A, Dar JA, Dayanandan S, de Haulleville T, Decuyper M, Delabye S, Derroire G, DeVries B, Diisi J, Do TV, Dolezal J, Dourdain A, Durrheim GP, Obiang NLE, Ewango CEN, Eyre TJ, Fayle TM, Feunang LFN, Finér L, Fischer M, Fridman J, Frizzera L, de Gasper AL, Gianelle D, Glick HB, Gonzalez-Elizondo MS, Gorenstein L, Habonayo R, Hardy OJ, Harris DJ, Hector A, Hemp A, Herold M, Hillers A, Hubau W, Ibanez T, Imai N, Imani G, Jagodzinski AM, Janecek S, Johannsen VK, Joly CA, Jumbam B, Kabelong BLPR, Kahsay GA, Karminov V, Kartawinata K, Kassi JN, Kearsley E, Kennard DK, Kepfer-Rojas S, Khan ML, Kigomo JN, Kim HS, Klauberg C, Klomberg Y, Korjus H, Kothandaraman S, Kraxner F, Kumar A, Kuswandi R, Lang M, Lawes MJ, Leite RV, Lentner G, Lewis SL, Libalah MB, Lisingo J, López-Serrano PM, Lu H, Lukina NV, Lykke AM, Maicher V, Maitner BS, Marcon E, Marshall AR, Martin EH, Martynenko O, Mbayu FM, Mbuvi MTE, Meave JA, Merow C, Miscicki S, Moreno VS, Morera A, Mukul SA, Müller JC, Murdjoko A, Nava-Miranda MG, Ndive LE, Neldner VJ, Nevenic RV, Nforbelie LN, Ngoh ML, N'Guessan AE, Ngugi MR, Ngute ASK, Njila ENN, Nyako MC, Ochuodho TO, Oleksyn J, Paquette A, Parfenova EI, Park M, Parren M, Parthasarathy N, Pfautsch S, Phillips OL, Piedade MTF, Piotto D, Pollastrini M, Poorter L, Poulsen JR, Poulsen AD, Pretzsch H, Rodeghiero M, Rolim SG, Rovero F, Rutishauser E, Sagheb-Talebi K, Saikia P, Sainge MN, Salas-Eljatib C, Salis A, Schall P, Schepaschenko D, Scherer-Lorenzen M, Schmid B, Schöngart J, Šebeň V, Sellan G, Selvi F, Serra-Diaz JM, Sheil D, Shvidenko AZ, Sist P, Souza AF, Stereńczak KJ, Sullivan MJP, Sundarapandian S, Svoboda M, Swaine MD, Targhetta N, Tchebakova N, Trethowan LA, Tropek R, Mukendi JT, Umunay PM, Usoltsev VA, Vaglio Laurin G, Valentini R, Valladares F, van der Plas F, Vega-Nieva DJ, Verbeeck H, Viana H, Vibrans AC, Vieira SA, Vleminckx J, Waite CE, Wang HF, Wasingya EK, Wekesa C, Westerlund B, Wittmann F, Wortel V, Zawiła-Niedźwiecki T, Zhang C, Zhao X, Zhu J, Zhu X, Zhu ZX, Zo-Bi IC, and Hui C
Subjects: Soil, Trees, Biodiversity, Forests
Abstract: The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2022
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20. High aboveground carbon stock of African tropical montane forests.

Author: Cuni-Sanchez A, Sullivan MJP, Platts PJ, Lewis SL, Marchant R, Imani G, Hubau W, Abiem I, Adhikari H, Albrecht T, Altman J, Amani C, Aneseyee AB, Avitabile V, Banin L, Batumike R, Bauters M, Beeckman H, Begne SK, Bennett AC, Bitariho R, Boeckx P, Bogaert J, Bräuning A, Bulonvu F, Burgess ND, Calders K, Chapman C, Chapman H, Comiskey J, de Haulleville T, Decuyper M, DeVries B, Dolezal J, Droissart V, Ewango C, Feyera S, Gebrekirstos A, Gereau R, Gilpin M, Hakizimana D, Hall J, Hamilton A, Hardy O, Hart T, Heiskanen J, Hemp A, Herold M, Hiltner U, Horak D, Kamdem MN, Kayijamahe C, Kenfack D, Kinyanjui MJ, Klein J, Lisingo J, Lovett J, Lung M, Makana JR, Malhi Y, Marshall A, Martin EH, Mitchard ETA, Morel A, Mukendi JT, Muller T, Nchu F, Nyirambangutse B, Okello J, Peh KS, Pellikka P, Phillips OL, Plumptre A, Qie L, Rovero F, Sainge MN, Schmitt CB, Sedlacek O, Ngute ASK, Sheil D, Sheleme D, Simegn TY, Simo-Droissart M, Sonké B, Soromessa T, Sunderland T, Svoboda M, Taedoumg H, Taplin J, Taylor D, Thomas SC, Timberlake J, Tuagben D, Umunay P, Uzabaho E, Verbeeck H, Vleminckx J, Wallin G, Wheeler C, Willcock S, Woods JT, and Zibera E
Subjects: Africa, Biomass, Climate Change, Conservation of Natural Resources, Datasets as Topic, Geographic Mapping, Attitude, Carbon analysis, Carbon Sequestration, Rainforest, Trees metabolism, Tropical Climate
Abstract: Tropical forests store 40-50 per cent of terrestrial vegetation carbon 1 . However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests 2 . Owing to climatic and soil changes with increasing elevation 3 , AGC stocks are lower in tropical montane forests compared with lowland forests 2 . 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 4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane 2,5,6 and lowland 7 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 8 . We find that the low stem density and high abundance of large trees of African lowland forests 4 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 9,10 and carbon-rich ecosystems., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2021
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21. Amazon tree dominance across forest strata.

Author: Draper FC, Costa FRC, Arellano G, Phillips OL, Duque A, Macía MJ, Ter Steege H, Asner GP, Berenguer E, Schietti J, Socolar JB, de Souza FC, Dexter KG, Jørgensen PM, Tello JS, Magnusson WE, Baker TR, Castilho CV, Monteagudo-Mendoza A, Fine PVA, Ruokolainen K, Coronado ENH, Aymard G, Dávila N, Sáenz MS, Paredes MAR, Engel J, Fortunel C, Paine CET, Goret JY, Dourdain A, Petronelli P, Allie E, Andino JEG, Brienen RJW, Pérez LC, Manzatto ÂG, Zambrana NYP, Molino JF, Sabatier D, Chave J, Fauset S, Villacorta RG, Réjou-Méchain M, Berry PE, Melgaço K, Feldpausch TR, Sandoval EV, Martinez RV, Mesones I, Junqueira AB, Roucoux KH, de Toledo JJ, Andrade AC, Camargo JL, Del Aguila Pasquel J, Santana FD, Laurance WF, Laurance SG, Lovejoy TE, Comiskey JA, Galbraith DR, Kalamandeen M, Aguilar GEN, Arenas JV, Guerra CAA, Flores M, Llampazo GF, Montenegro LAT, Gomez RZ, Pansonato MP, Moscoso VC, Vleminckx J, Barrantes OJV, Duivenvoorden JF, de Sousa SA, Arroyo L, Perdiz RO, Cravo JS, Marimon BS, Junior BHM, Carvalho FA, Damasco G, Disney M, Vital MS, Diaz PRS, Vicentini A, Nascimento H, Higuchi N, Van Andel T, Malhi Y, Ribeiro SC, Terborgh JW, Thomas RS, Dallmeier F, Prieto A, Hilário RR, Salomão RP, Silva RDC, Casas LF, Vieira ICG, Araujo-Murakami A, Arevalo FR, Ramírez-Angulo H, Torre EV, Peñuela MC, Killeen TJ, Pardo G, Jimenez-Rojas E, Castro W, Cabrera DG, Pipoly J, de Sousa TR, Silvera M, Vos V, Neill D, Vargas PN, Vela DM, Aragão LEOC, Umetsu RK, Sierra R, Wang O, Young KR, Prestes NCCS, Massi KG, Huaymacari JR, Gutierrez GAP, Aldana AM, Alexiades MN, Baccaro F, Céron C, Muelbert AE, Rios JMG, Lima AS, Lloyd JL, Pitman NCA, Gamarra LV, Oroche CJC, Fuentes AF, Palacios W, Patiño S, Torres-Lezama A, and Baraloto C
Subjects: Biodiversity, Brazil, Humans, Forests, Trees
Abstract: The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare but a few are common across the region. Indeed, just 227 'hyperdominant' species account for >50% of all individuals >10 cm diameter at 1.3 m in height. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size class and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a large floristic dataset to show that, while hyperdominance is a universal phenomenon across forest strata, different species dominate the forest understory, midstory and canopy. We further find that, although species belonging to a range of phylogenetically dispersed lineages have become hyperdominant in small size classes, hyperdominants in large size classes are restricted to a few lineages. Our results demonstrate that it is essential to consider all forest strata to understand regional patterns of dominance and composition in Amazonia. More generally, through the lens of 654 hyperdominant species, we outline a tractable pathway for understanding the functioning of half of Amazonian forests across vertical strata and geographical locations.
Published: 2021
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22. Resistance of African tropical forests to an extreme climate anomaly.

Author: Bennett AC, Dargie GC, Cuni-Sanchez A, Tshibamba Mukendi J, Hubau W, Mukinzi JM, Phillips OL, Malhi Y, Sullivan MJP, Cooper DLM, Adu-Bredu S, Affum-Baffoe K, Amani CA, Banin LF, Beeckman H, Begne SK, Bocko YE, Boeckx P, Bogaert J, Brncic T, Chezeaux E, Clark CJ, Daniels AK, de Haulleville T, Djuikouo Kamdem MN, Doucet JL, Evouna Ondo F, Ewango CEN, Feldpausch TR, Foli EG, Gonmadje C, Hall JS, Hardy OJ, Harris DJ, Ifo SA, Jeffery KJ, Kearsley E, Leal M, Levesley A, Makana JR, Mbayu Lukasu F, Medjibe VP, Mihindu V, Moore S, Nssi Begone N, Pickavance GC, Poulsen JR, Reitsma J, Sonké B, Sunderland TCH, Taedoumg H, Talbot J, Tuagben DS, Umunay PM, Verbeeck H, Vleminckx J, White LJT, Woell H, Woods JT, Zemagho L, and Lewis SL
Subjects: Carbon Cycle, Droughts, El Nino-Southern Oscillation, Hot Temperature, Humans, Seasons, Climate Change, Rainforest, Trees growth & development, Tropical Climate
Abstract: The responses of tropical forests to environmental change are critical uncertainties in predicting the future impacts of climate change. The positive phase of the 2015-2016 El Niño Southern Oscillation resulted in unprecedented heat and low precipitation in the tropics with substantial impacts on the global carbon cycle. The role of African tropical forests is uncertain as their responses to short-term drought and temperature anomalies have yet to be determined using on-the-ground measurements. African tropical forests may be particularly sensitive because they exist in relatively dry conditions compared with Amazonian or Asian forests, or they may be more resistant because of an abundance of drought-adapted species. Here, we report responses of structurally intact old-growth lowland tropical forests inventoried within the African Tropical Rainforest Observatory Network (AfriTRON). We use 100 long-term inventory plots from six countries each measured at least twice prior to and once following the 2015-2016 El Niño event. These plots experienced the highest temperatures and driest conditions on record. The record temperature did not significantly reduce carbon gains from tree growth or significantly increase carbon losses from tree mortality, but the record drought did significantly decrease net carbon uptake. Overall, the long-term biomass increase of these forests was reduced due to the El Niño event, but these plots remained a live biomass carbon sink (0.51 ± 0.40 Mg C ha -1 y -1 ) despite extreme environmental conditions. Our analyses, while limited to African tropical forests, suggest they may be more resistant to climatic extremes than Amazonian and Asian forests., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)
Published: 2021
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23. Long-term thermal sensitivity of Earth's tropical forests.

Author: Sullivan MJP, Lewis SL, Affum-Baffoe K, Castilho C, Costa F, Sanchez AC, Ewango CEN, Hubau W, Marimon B, Monteagudo-Mendoza A, Qie L, Sonké B, Martinez RV, Baker TR, Brienen RJW, Feldpausch TR, Galbraith D, Gloor M, Malhi Y, Aiba SI, Alexiades MN, Almeida EC, de Oliveira EA, Dávila EÁ, Loayza PA, Andrade A, Vieira SA, Aragão LEOC, Araujo-Murakami A, Arets EJMM, Arroyo L, Ashton P, Aymard C G, Baccaro FB, Banin LF, Baraloto C, Camargo PB, Barlow J, Barroso J, Bastin JF, Batterman SA, Beeckman H, Begne SK, Bennett AC, Berenguer E, Berry N, Blanc L, Boeckx P, Bogaert J, Bonal D, Bongers F, Bradford M, Brearley FQ, Brncic T, Brown F, Burban B, Camargo JL, Castro W, Céron C, Ribeiro SC, Moscoso VC, Chave J, Chezeaux E, Clark CJ, de Souza FC, Collins M, Comiskey JA, Valverde FC, Medina MC, da Costa L, Dančák M, Dargie GC, Davies S, Cardozo ND, de Haulleville T, de Medeiros MB, Del Aguila Pasquel J, Derroire G, Di Fiore A, Doucet JL, Dourdain A, Droissart V, Duque LF, Ekoungoulou R, Elias F, Erwin T, Esquivel-Muelbert A, Fauset S, Ferreira J, Llampazo GF, Foli E, Ford A, Gilpin M, Hall JS, Hamer KC, Hamilton AC, Harris DJ, Hart TB, Hédl R, Herault B, Herrera R, Higuchi N, Hladik A, Coronado EH, Huamantupa-Chuquimaco I, Huasco WH, Jeffery KJ, Jimenez-Rojas E, Kalamandeen M, Djuikouo MNK, Kearsley E, Umetsu RK, Kho LK, Killeen T, Kitayama K, Klitgaard B, Koch A, Labrière N, Laurance W, Laurance S, Leal ME, Levesley A, Lima AJN, Lisingo J, Lopes AP, Lopez-Gonzalez G, Lovejoy T, Lovett JC, Lowe R, Magnusson WE, Malumbres-Olarte J, Manzatto ÂG, Marimon BH Jr, Marshall AR, Marthews T, de Almeida Reis SM, Maycock C, Melgaço K, Mendoza C, Metali F, Mihindou V, Milliken W, Mitchard ETA, Morandi PS, Mossman HL, Nagy L, Nascimento H, Neill D, Nilus R, Vargas PN, Palacios W, Camacho NP, Peacock J, Pendry C, Peñuela Mora MC, Pickavance GC, Pipoly J, Pitman N, Playfair M, Poorter L, Poulsen JR, Poulsen AD, Preziosi R, Prieto A, Primack RB, Ramírez-Angulo H, Reitsma J, Réjou-Méchain M, Correa ZR, de Sousa TR, Bayona LR, Roopsind A, Rudas A, Rutishauser E, Abu Salim K, Salomão RP, Schietti J, Sheil D, Silva RC, Espejo JS, Valeria CS, Silveira M, Simo-Droissart M, Simon MF, Singh J, Soto Shareva YC, Stahl C, Stropp J, Sukri R, Sunderland T, Svátek M, Swaine MD, Swamy V, Taedoumg H, Talbot J, Taplin J, Taylor D, Ter Steege H, Terborgh J, Thomas R, Thomas SC, Torres-Lezama A, Umunay P, Gamarra LV, van der Heijden G, van der Hout P, van der Meer P, van Nieuwstadt M, Verbeeck H, Vernimmen R, Vicentini A, Vieira ICG, Torre EV, Vleminckx J, Vos V, Wang O, White LJT, Willcock S, Woods JT, Wortel V, Young K, Zagt R, Zemagho L, Zuidema PA, Zwerts JA, and Phillips OL
Subjects: Acclimatization, Biomass, Carbon metabolism, Earth, Planet, Wood, Carbon Cycle, Climate Change, Forests, Hot Temperature, Trees metabolism, Tropical Climate
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., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
Published: 2020
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24. Asynchronous carbon sink saturation in African and Amazonian tropical forests.

Author: Hubau W, Lewis SL, Phillips OL, Affum-Baffoe K, Beeckman H, Cuní-Sanchez A, Daniels AK, Ewango CEN, Fauset S, Mukinzi JM, Sheil D, Sonké B, Sullivan MJP, Sunderland TCH, Taedoumg H, Thomas SC, White LJT, Abernethy KA, Adu-Bredu S, Amani CA, Baker TR, Banin LF, Baya F, Begne SK, Bennett AC, Benedet F, Bitariho R, Bocko YE, Boeckx P, Boundja P, Brienen RJW, Brncic T, Chezeaux E, Chuyong GB, Clark CJ, Collins M, Comiskey JA, Coomes DA, Dargie GC, de Haulleville T, Kamdem MND, Doucet JL, Esquivel-Muelbert A, Feldpausch TR, Fofanah A, Foli EG, Gilpin M, Gloor E, Gonmadje C, Gourlet-Fleury S, Hall JS, Hamilton AC, Harris DJ, Hart TB, Hockemba MBN, Hladik A, Ifo SA, Jeffery KJ, Jucker T, Yakusu EK, Kearsley E, Kenfack D, Koch A, Leal ME, Levesley A, Lindsell JA, Lisingo J, Lopez-Gonzalez G, Lovett JC, Makana JR, Malhi Y, Marshall AR, Martin J, Martin EH, Mbayu FM, Medjibe VP, Mihindou V, Mitchard ETA, Moore S, Munishi PKT, Bengone NN, Ojo L, Ondo FE, Peh KS, Pickavance GC, Poulsen AD, Poulsen JR, Qie L, Reitsma J, Rovero F, Swaine MD, Talbot J, Taplin J, Taylor DM, Thomas DW, Toirambe B, Mukendi JT, Tuagben D, Umunay PM, van der Heijden GMF, Verbeeck H, Vleminckx J, Willcock S, Wöll H, Woods JT, and Zemagho L
Subjects: Africa, Atmosphere chemistry, Biomass, Brazil, Droughts, History, 20th Century, History, 21st Century, Models, Theoretical, Temperature, Carbon Dioxide metabolism, Carbon Sequestration, Forests, Trees metabolism, Tropical Climate
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 1-3 . Climate-driven vegetation models typically predict that this tropical forest 'carbon sink' will continue for decades 4,5 . 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 6 . 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 7-9 . 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 10 reinforce our conclusion that the intact tropical forest carbon sink has already peaked. This saturation and ongoing decline of the tropical forest carbon sink has consequences for policies intended to stabilize Earth's climate.
Published: 2020
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25. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass.

Author: Schepaschenko D, Chave J, Phillips OL, Lewis SL, Davies SJ, Réjou-Méchain M, Sist P, Scipal K, Perger C, Herault B, Labrière N, Hofhansl F, Affum-Baffoe K, Aleinikov A, Alonso A, Amani C, Araujo-Murakami A, Armston J, Arroyo L, Ascarrunz N, Azevedo C, Baker T, Bałazy R, Bedeau C, Berry N, Bilous AM, Bilous SY, Bissiengou P, Blanc L, Bobkova KS, Braslavskaya T, Brienen R, Burslem DFRP, Condit R, Cuni-Sanchez A, Danilina D, Del Castillo Torres D, Derroire G, Descroix L, Sotta ED, d'Oliveira MVN, Dresel C, Erwin T, Evdokimenko MD, Falck J, Feldpausch TR, Foli EG, Foster R, Fritz S, Garcia-Abril AD, Gornov A, Gornova M, Gothard-Bassébé E, Gourlet-Fleury S, Guedes M, Hamer KC, Susanty FH, Higuchi N, Coronado ENH, Hubau W, Hubbell S, Ilstedt U, Ivanov VV, Kanashiro M, Karlsson A, Karminov VN, Killeen T, Koffi JK, Konovalova M, Kraxner F, Krejza J, Krisnawati H, Krivobokov LV, Kuznetsov MA, Lakyda I, Lakyda PI, Licona JC, Lucas RM, Lukina N, Lussetti D, Malhi Y, Manzanera JA, Marimon B, Junior BHM, Martinez RV, Martynenko OV, Matsala M, Matyashuk RK, Mazzei L, Memiaghe H, Mendoza C, Mendoza AM, Moroziuk OV, Mukhortova L, Musa S, Nazimova DI, Okuda T, Oliveira LC, Ontikov PV, Osipov AF, Pietsch S, Playfair M, Poulsen J, Radchenko VG, Rodney K, Rozak AH, Ruschel A, Rutishauser E, See L, Shchepashchenko M, Shevchenko N, Shvidenko A, Silveira M, Singh J, Sonké B, Souza C, Stereńczak K, Stonozhenko L, Sullivan MJP, Szatniewska J, Taedoumg H, Ter Steege H, Tikhonova E, Toledo M, Trefilova OV, Valbuena R, Gamarra LV, Vasiliev S, Vedrova EF, Verhovets SV, Vidal E, Vladimirova NA, Vleminckx J, Vos VA, Vozmitel FK, Wanek W, West TAP, Woell H, Woods JT, Wortel V, Yamada T, Nur Hajar ZS, and Zo-Bi IC
Subjects: Conservation of Natural Resources, Environmental Monitoring methods, Biomass, Forests, Remote Sensing Technology
Abstract: Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.
Published: 2019
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26. Coordinated community structure among trees, fungi and invertebrate groups in Amazonian rainforests.

Author: Vleminckx J, Schimann H, Decaëns T, Fichaux M, Vedel V, Jaouen G, Roy M, Lapied E, Engel J, Dourdain A, Petronelli P, Orivel J, and Baraloto C
Subjects: Animals, Ants physiology, French Guiana, Fungi physiology, Invertebrates physiology, Phylogeny, Soil, Trees physiology, Biodiversity, Ecosystem, Rainforest, Tropical Climate
Abstract: Little is known regarding how trophic interactions shape community assembly in tropical forests. Here we assess multi-taxonomic community assembly rules using a rare standardized coordinated inventory comprising exhaustive surveys of five highly-diverse taxonomic groups exerting key ecological functions: trees, fungi, earthworms, ants and spiders. We sampled 36 1.9-ha plots from four remote locations in French Guiana including precise soil measurements, and we tested whether species turnover was coordinated among groups across geographic and edaphic gradients. All species group pairs exhibited significant compositional associations that were independent from soil conditions. For some of the pairs, associations were also partly explained by soil properties, especially soil phosphorus availability. Our study provides evidence for coordinated turnover among taxonomic groups beyond simple relationships with environmental factors, thereby refining our understanding regarding the nature of interactions occurring among these ecologically important groups.
Published: 2019
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27. The persistence of carbon in the African forest understory.

Author: Hubau W, De Mil T, Van den Bulcke J, Phillips OL, Angoboy Ilondea B, Van Acker J, Sullivan MJP, Nsenga L, Toirambe B, Couralet C, Banin LF, Begne SK, Baker TR, Bourland N, Chezeaux E, Clark CJ, Collins M, Comiskey JA, Cuni-Sanchez A, Deklerck V, Dierickx S, Doucet JL, Ewango CEN, Feldpausch TR, Gilpin M, Gonmadje C, Hall JS, Harris DJ, Hardy OJ, Kamdem MD, Kasongo Yakusu E, Lopez-Gonzalez G, Makana JR, Malhi Y, Mbayu FM, Moore S, Mukinzi J, Pickavance G, Poulsen JR, Reitsma J, Rousseau M, Sonké B, Sunderland T, Taedoumg H, Talbot J, Tshibamba Mukendi J, Umunay PM, Vleminckx J, White LJT, Zemagho L, Lewis SL, and Beeckman H
Subjects: Carbon Cycle, Democratic Republic of the Congo, Time Factors, Trees growth & development, Tropical Climate, Carbon analysis, Carbon Sequestration, Forests, Trees physiology
Abstract: Quantifying carbon dynamics in forests is critical for understanding their role in long-term climate regulation 1-4 . Yet little is known about tree longevity in tropical forests 3,5-8 , a factor that is vital for estimating carbon persistence 3,4 . Here we calculate mean carbon age (the period that carbon is fixed in trees 7 ) in different strata of African tropical forests using (1) growth-ring records with a unique timestamp accurately demarcating 66 years of growth in one site and (2) measurements of diameter increments from the African Tropical Rainforest Observation Network (23 sites). We find that in spite of their much smaller size, in understory trees mean carbon age (74 years) is greater than in sub-canopy (54 years) and canopy (57 years) trees and similar to carbon age in emergent trees (66 years). The remarkable carbon longevity in the understory results from slow and aperiodic growth as an adaptation to limited resource availability 9-11 . Our analysis also reveals that while the understory represents a small share (11%) of the carbon stock 12,13 , it contributes disproportionally to the forest carbon sink (20%). We conclude that accounting for the diversity of carbon age and carbon sequestration among different forest strata is critical for effective conservation management 14-16 and for accurate modelling of carbon cycling 4 .
Published: 2019
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28. Divergent Secondary Metabolites and Habitat Filtering Both Contribute to Tree Species Coexistence in the Peruvian Amazon.

Author: Vleminckx J, Salazar D, Fortunel C, Mesones I, Dávila N, Lokvam J, Beckley K, Baraloto C, and Fine PVA
Abstract: Little is known about the mechanisms promoting or limiting the coexistence of functionally divergent species in hyperdiverse tropical tree genera. Density-dependent enemy attacks have been proposed to be a major driver for the local coexistence of chemically divergent congeneric species. At the same time, we expect local soil conditions to favor the coexistence of species sharing similar functional traits related to resource use strategies, while environmental heterogeneity would promote the diversity of these traits at both local and large spatial scales. To test how these traits mediate species coexistence, we used functional trait data for 29 species from the tree genus Protium (Burseraceae), collected in 19 plots (2 ha each) in the Peruvian Amazon. We characterized the presence-absence of 189 plant secondary metabolites (SM) for 27 of these species, and 14 functional traits associated with resource use strategies (RUT) for 16 species. Based on these data, we found that SM were significantly more dissimilar than null expectations for species co-occurring within plots, whereas RUT were significantly more similar. These results were consistent with the hypothesis that density-dependent enemy attacks contribute to the local coexistence of congeneric species displaying divergent chemical defenses, whereas local habitat conditions filter species with similar RUT. Using measurements of nine soil properties in each plot, we also found a significant turnover of RUT traits with increasing dissimilarity of soil texture and nutrient availabilities, providing support for the hypothesis that soil heterogeneity maintains functional diversity at larger spatial scales (from 500 m up to ca. 200 km) in Protium communities. Our study provides new evidence suggesting that density-dependent enemy attacks and soil heterogeneity both contribute to maintaining high species richness in diverse tropical forests.
Published: 2018
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29. Field methods for sampling tree height for tropical forest biomass estimation.

Author: Sullivan MJP, Lewis SL, Hubau W, Qie L, Baker TR, Banin LF, Chave J, Cuni-Sanchez A, Feldpausch TR, Lopez-Gonzalez G, Arets E, Ashton P, Bastin JF, Berry NJ, Bogaert J, Boot R, Brearley FQ, Brienen R, Burslem DFRP, de Canniere C, Chudomelová M, Dančák M, Ewango C, Hédl R, Lloyd J, Makana JR, Malhi Y, Marimon BS, Junior BHM, Metali F, Moore S, Nagy L, Vargas PN, Pendry CA, Ramírez-Angulo H, Reitsma J, Rutishauser E, Salim KA, Sonké B, Sukri RS, Sunderland T, Svátek M, Umunay PM, Martinez RV, Vernimmen RRE, Torre EV, Vleminckx J, Vos V, and Phillips OL
Abstract: Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height.Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement.Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with biomass estimates using field measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches.Our results indicate that even limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.
Published: 2018
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30. Soil charcoal to assess the impacts of past human disturbances on tropical forests.

Author: Vleminckx J, Morin-Rivat J, Biwolé AB, Daïnou K, Gillet JF, Doucet JL, Drouet T, and Hardy OJ
Subjects: Cameroon, Fires, Geography, Humans, Trees, Tropical Climate, Agriculture, Charcoal analysis, Forests, Radiometric Dating, Soil chemistry
Abstract: The canopy of many central African forests is dominated by light-demanding tree species that do not regenerate well under themselves. The prevalence of these species might result from ancient slash-and-burn agricultural activities that created large openings, while a decline of these activities since the colonial period could explain their deficit of regeneration. To verify this hypothesis, we compared soil charcoal abundance, used as a proxy for past slash-and-burn agriculture, and tree species composition assessed on 208 rainforest 0.2 ha plots located in three areas from Southern Cameroon. Species were classified in regeneration guilds (pioneer, non-pioneer light-demanding, shade-bearer) and characterized by their wood-specific gravity, assumed to reflect light requirement. We tested the correlation between soil charcoal abundance and: (i) the relative abundance of each guild, (ii) each species and family abundance and (iii) mean wood-specific gravity. Charcoal was found in 83% of the plots, indicating frequent past forest fires. Radiocarbon dating revealed two periods of fires: "recent" charcoal were on average 300 years old (up to 860 BP, n = 16) and occurred in the uppermost 20 cm soil layer, while "ancient" charcoal were on average 1900 years old (range: 1500 to 2800 BP, n = 43, excluding one sample dated 9400 BP), and found in all soil layers. While we expected a positive correlation between the relative abundance of light-demanding species and charcoal abundance in the upper soil layer, overall there was no evidence that the current heterogeneity in tree species composition can be explained by charcoal abundance in any soil layer. The absence of signal supporting our hypothesis might result from (i) a relatively uniform impact of past slash-and-burn activities, (ii) pedoturbation processes bringing ancient charcoal to the upper soil layer, blurring the signal of centuries-old Human disturbances, or (iii) the prevalence of other environmental factors on species composition.
Published: 2014
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31. Above-ground biomass and structure of 260 African tropical forests.

Author: Lewis SL, Sonké B, Sunderland T, Begne SK, Lopez-Gonzalez G, van der Heijden GM, Phillips OL, Affum-Baffoe K, Baker TR, Banin L, Bastin JF, Beeckman H, Boeckx P, Bogaert J, De Cannière C, Chezeaux E, Clark CJ, Collins M, Djagbletey G, Djuikouo MN, Droissart V, Doucet JL, Ewango CE, Fauset S, Feldpausch TR, Foli EG, Gillet JF, Hamilton AC, Harris DJ, Hart TB, de Haulleville T, Hladik A, Hufkens K, Huygens D, Jeanmart P, Jeffery KJ, Kearsley E, Leal ME, Lloyd J, Lovett JC, Makana JR, Malhi Y, Marshall AR, Ojo L, Peh KS, Pickavance G, Poulsen JR, Reitsma JM, Sheil D, Simo M, Steppe K, Taedoumg HE, Talbot J, Taplin JR, Taylor D, Thomas SC, Toirambe B, Verbeeck H, Vleminckx J, White LJ, Willcock S, Woell H, and Zemagho L
Subjects: Africa, Biomass, Carbon Cycle, Climate Change, Conservation of Natural Resources, Models, Biological, Soil, Trees anatomy & histology, Trees growth & development, Trees metabolism, Tropical Climate
Abstract: We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha⁻¹ (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha⁻¹) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426 ± 11 stems ha⁻¹ greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C : N ratio (suggesting a positive soil phosphorus-AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes.
Published: 2013
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31 results on '"Vleminckx, J."'

1. Utilité d'une typologie des exploitants artisanaux de bois pour contribuer à la formulation d'une politique publique en province Orientale (RD Congo)

2. Consistent patterns of common species across tropical tree communities

3. Consistent patterns of common species across tropical tree communities

4. Co-limitation towards lower latitudes shapes global forest diversity gradients

5. High aboveground carbon stock of African tropical montane forest

6. Taking the pulse of Earth's tropical forests using networks of highly distributed plots

7. Amazon tree dominance across forest strata

8. Long-term thermal sensitivity of Earth's tropical forests

9. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass [data paper]

10. A global reference dataset for remote sensing of forest biomass. The Forest Observation System approach

11. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

12. Field methods for sampling tree height for tropical forest biomass estimation

13. Above-ground biomass and structure of 260 African tropical forests

14. Above-ground biomass and structure of 260 African tropical forests

15. Co-limitation towards lower latitudes shapes global forest diversity gradients

16. Flower production decreases with warmer and more humid atmospheric conditions in a western Amazonian forest.

17. Consistent patterns of common species across tropical tree communities.

18. Niche breadth of Amazonian trees increases with niche optimum across broad edaphic gradients.

19. Co-limitation towards lower latitudes shapes global forest diversity gradients.

20. High aboveground carbon stock of African tropical montane forests.

21. Amazon tree dominance across forest strata.

22. Resistance of African tropical forests to an extreme climate anomaly.

23. Long-term thermal sensitivity of Earth's tropical forests.

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

25. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass.

26. Coordinated community structure among trees, fungi and invertebrate groups in Amazonian rainforests.

27. The persistence of carbon in the African forest understory.

28. Divergent Secondary Metabolites and Habitat Filtering Both Contribute to Tree Species Coexistence in the Peruvian Amazon.

29. Field methods for sampling tree height for tropical forest biomass estimation.

30. Soil charcoal to assess the impacts of past human disturbances on tropical forests.

31. Above-ground biomass and structure of 260 African tropical forests.

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31 results on '"Vleminckx, J."'

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