Author: "Baraloto C." - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Baraloto C."' showing total 165 results

Start Over Author "Baraloto C."

165 results on '"Baraloto C."'

1. 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

2. 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

3. Globally, functional traits are weak predictors of juvenile tree growth, and we do not know why

Author: Paine, CET, Amissah, L, Auge, H, Baraloto, C, Baruffol, M, Bourland, N, Bruelheide, H, Daïnou, K, de Gouvenain, RC, Doucet, JL, Doust, S, Fine, PVA, Fortunel, C, Haase, J, Holl, KD, Jactel, H, Li, X, Kitajima, K, Koricheva, J, Martínez-Garza, C, Messier, C, Paquette, A, Philipson, C, Piotto, D, Poorter, L, Posada, JM, Potvin, C, Rainio, K, Russo, SE, Ruiz-Jaen, M, Scherer-Lorenzen, M, Webb, CO, Wright, SJ, Zahawi, RA, and Hector, A
Subjects: functional ecology, FunDivEurope, growth, hierarchical models, plant population and community dynamics, relative growth rate, size-standardized growth rate, TreeDivNet, Ecology, Environmental Sciences, Biological Sciences, Agricultural and Veterinary Sciences
Abstract: Plant functional traits, in particular specific leaf area (SLA), wood density and seed mass, are often good predictors of individual tree growth rates within communities. Individuals and species with high SLA, low wood density and small seeds tend to have faster growth rates. If community-level relationships between traits and growth have general predictive value, then similar relationships should also be observed in analyses that integrate across taxa, biogeographic regions and environments. Such global consistency would imply that traits could serve as valuable proxies for the complex suite of factors that determine growth rate, and, therefore, could underpin a new generation of robust dynamic vegetation models. Alternatively, growth rates may depend more strongly on the local environment or growth-trait relationships may vary along environmental gradients. We tested these alternative hypotheses using data on 27 352 juvenile trees, representing 278 species from 27 sites on all forested continents, and extensive functional trait data, 38% of which were obtained at the same sites at which growth was assessed. Data on potential evapotranspiration (PET), which summarizes the joint ecological effects of temperature and precipitation, were obtained from a global data base. We estimated size-standardized relative height growth rates (SGR) for all species, then related them to functional traits and PET using mixed-effect models for the fastest growing species and for all species together. Both the mean and 95th percentile SGR were more strongly associated with functional traits than with PET. PET was unrelated to SGR at the global scale. SGR increased with increasing SLA and decreased with increasing wood density and seed mass, but these traits explained only 3.1% of the variation in SGR. SGR-trait relationships were consistently weak across families and biogeographic zones, and over a range of tree statures. Thus, the most widely studied functional traits in plant ecology were poor predictors of tree growth over large scales. Synthesis. We conclude that these functional traits alone may be unsuitable for predicting growth of trees over broad scales. Determining the functional traits that predict vital rates under specific environmental conditions may generate more insight than a monolithic global relationship can offer. The most widely studied functional traits in plant ecology, specific leaf area, wood density and seed mass, were only weakly associated with tree growth rates over broad scales. Assessing trait-growth relationships under specific environmental conditions may generate more insight than a global relationship can offer.
Published: 2015

4. Persistent effects of pre-Columbian plant domestication on Amazonian forest composition

Author: Levis, C., Costa, F. R. C., Bongers, F., Peña-Claros, M., Clement, C. R., Junqueira, A. B., Neves, E. G., Tamanaha, E. K., Figueiredo, F. O. G., Salomão, R. P., Castilho, C. V., Magnusson, W. E., Phillips, O. L., Guevara, J. E., Sabatier, D., Molino, J.-F., López, D. Cárdenas, Mendoza, A. M., Pitman, N. C. A., Duque, A., Vargas, P. Núñez, Zartman, C. E., Vasquez, R., Andrade, A., Camargo, J. L., Feldpausch, T. R., Laurance, S. G. W., Laurance, W. F., Killeen, T. J., Nascimento, H. E. Mendonça, Montero, J. C., Mostacedo, B., Amaral, I. L., Vieira, I. C. Guimarães, Brienen, R., Castellanos, H., Terborgh, J., de Jesus Veiga Carim, M., da Silva Guimarães, J. R., de Souza Coelho, L., de Almeida Matos, F. D., Wittmann, F., Mogollón, H. F., Damasco, G., Dávila, N., García-Villacorta, R., Coronado, E. N. H., Emilio, T., de Andrade Lima Filho, D., Schietti, J., Souza, P., Targhetta, N., Comiskey, J. A., Marimon, B. S., Marimon, B.-H., Neill, D., Alonso, A., Arroyo, L., Carvalho, F. A., de Souza, F. C., Dallmeier, F., Pansonato, M. P., Duivenvoorden, J. F., Fine, P. V. A., Stevenson, P. R., Araujo-Murakami, A., Aymard C., G. A., Baraloto, C., do Amaral, D. D., Engel, J., Henkel, T. W., Maas, P., Petronelli, P., Revilla, J. D. Cardenas, Stropp, J., Daly, D., Gribel, R., Paredes, M. Ríos, Silveira, M., Thomas-Caesar, R., Baker, T. R., da Silva, N. F., Ferreira, L. V., Peres, C. A., Silman, M. R., Cerón, C., Valverde, F. C., Di Fiore, A., Jimenez, E. M., Mora, M. C. Peñuela, Toledo, M., Barbosa, E. M., de Matos Bonates, L. C., Arboleda, N. C., de Sousa Farias, E., Fuentes, A., Guillaumet, J.-L., Jørgensen, P. Møller, Malhi, Y., de Andrade Miranda, I. P., Phillips, J. F., Prieto, A., Rudas, A., Ruschel, A. R., Silva, N., von Hildebrand, P., Vos, V. A., Zent, E. L., Zent, S., Cintra, B. B. L., Nascimento, M. T., Oliveira, A. A., Ramirez-Angulo, H., Ramos, J. F., Rivas, G., Schöngart, J., Sierra, R., Tirado, M., van der Heijden, G., Torre, E. V., Wang, O., Young, K. R., Baider, C., Cano, A., Farfan-Rios, W., Ferreira, C., Hoffman, B., Mendoza, C., Mesones, I., Torres-Lezama, A., Medina, M. N. U., van Andel, T. R., Villarroel, D., Zagt, R., Alexiades, M. N., Balslev, H., Garcia-Cabrera, K., Gonzales, T., Hernandez, L., Huamantupa-Chuquimaco, I., Manzatto, A. G., Milliken, W., Cuenca, W. P., Pansini, S., Pauletto, D., Arevalo, F. R., Reis, N. F. Costa, Sampaio, A. F., Giraldo, L. E. Urrego, Sandoval, E. H. Valderrama, Gamarra, L. Valenzuela, Vela, C. I. A., and ter Steege, H.
Published: 2017

5. Branch xylem density variations across the Amazon Basin

Author: Patiño, S., Lloyd, J., Paiva, R., Baker, T. R, Quesada, C. A, Mercado, L. M, Schmerler, J., Schwarz, M., Santos, A. J. B, Aguilar, A., Czimczik, C. I, Gallo, J., Horna, V., Hoyos, E. J, Jimenez, E. M, Palomino, W., Peacock, J., Peña-Cruz, A., Sarmiento, C., Sota, A., Turriago, J. D, Villanueva, B., Vitzthum, P., Alvarez, E., Arroyo, L., Baraloto, C., Bonal, D., Chave, J., Costa, A. C. L, Herrera, R., Higuchi, N., Killeen, T., Leal, E., Luizão, F., Meir, P., Monteagudo, A., Neil, D., Núñez-Vargas, P., Peñuela, M. C, Pitman, N., Priante Filho, N., Prieto, A., Panfil, S. N, Rudas, A., Salomão, R., Silva, N., Silveira, M., Soares deAlmeida, S., Torres-Lezama, A., Vásquez-Martínez, R., Vieira, I., Malhi, Y., and Phillips, O. L
Subjects: wood specific-gravity, tropical rain-forest, long-term plots, hydraulic architecture, cavitation resistance, carbon gain, functional-significance, water transport, savanna trees, canopy trees
Abstract: Xylem density is a physical property of wood that varies between individuals, species and environments. It reflects the physiological strategies of trees that lead to growth, survival and reproduction. Measurements of branch xylem density, ρx, were made for 1653 trees representing 598 species, sampled from 87 sites across the Amazon basin. Measured values ranged from 218 kg m−3for a Cordia sagotii (Boraginaceae) from Mountagne de Tortue, French Guiana to 1130 kg m−3 for an Aiouea sp. (Lauraceae) from Caxiuana, Central Pará, Brazil. Analysis of variance showed significant differences in average ρx across regions and sampled plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that species identity (family, genera and species) accounted for 33% with environment (geographic location and plot) accounting for an additional 26%; the remaining "residual" variance accounted for 41% of the total variance. Variations in plot means, were, however, not only accountable by differences in species composition because xylem density of the most widely distributed species in our dataset varied systematically from plot to plot. Thus, as well as having a genetic component, branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing in a predictable manner. Within the analysed taxa, exceptions to this general rule seem to be pioneer species belonging for example to the Urticaceae whose branch xylem density is more constrained than most species sampled in this study. These patterns of variation of branch xylem density across Amazonia suggest a large functional diversity amongst Amazonian trees which is not well understood.
Published: 2009

6. Geographic patterns of tree dispersal modes in Amazonia and their ecological correlates

Author: Correa, DF, Stevenson, PR, Umaña, MN, Coelho, LDS, Lima Filho, DDA, Salomão, RP, Amaral, ILD, Wittmann, F, Matos, FDDA, Castilho, CV, Phillips, OL, Guevara, JE, Carim, MDJV, Magnusson, WE, Sabatier, D, Molino, JF, Irume, MV, Martins, MP, Guimarães, JRDS, Bánki, OS, Piedade, MTF, Pitman, NCA, Monteagudo Mendoza, A, Ramos, JF, Luize, BG, Novo, EMMDL, Núñez Vargas, P, Silva, TSF, Venticinque, EM, Manzatto, AG, Reis, NFC, Terborgh, JW, Casula, KR, Honorio Coronado, EN, Montero, JC, Schöngart, J, Cárdenas López, D, Costa, FRC, Quaresma, AC, Zartman, CE, Killeen, TJ, Marimon, BS, Marimon-Junior, BH, Vasquez, R, Mostacedo, B, Demarchi, LO, Feldpausch, TR, Assis, RL, Baraloto, C, Engel, J, Petronelli, P, Castellanos, H, Medeiros, MBD, Simon, MF, Andrade, A, Camargo, JL, Laurance, SGW, Laurance, WF, Maniguaje Rincón, L, Schietti, J, Sousa, TR, Farias, EDS, Lopes, MA, Magalhães, JLL, Nascimento, HEM, Queiroz, HLD, Aymard C., GA, Brienen, R, Cardenas Revilla, JD, Vieira, ICG, Cintra, BBL, Feitosa, YO, Duivenvoorden, JF, Mogollón, HF, Araujo-Murakami, A, Ferreira, LV, Lozada, Comiskey, JA, De Toledo, JJ, Damasco, G, Dávila, N, García-Villacorta, R, Lopes, A, Vicentini, A, Draper, FC, Castaño Arboleda, N, Cornejo Valverde, F, Alonso, A, Dallmeier, F, Gomes, VHF, Neill, D, De Aguiar, DPP, Arroyo, L, Carvalho, FA, De Souza, FC, Amaral, DDD, Feeley, KJ, Gribel, R, Pansonato, MP, Barlow, J, Correa, DF [0000-0002-6510-4906], Stevenson, PR [0000-0003-2394-447X], Umaña, MN [0000-0001-5876-7720], Luize, BG [0000-0002-8384-8386], Sousa, TR [0000-0003-0598-4996], Comiskey, JA [0000-0001-6710-1269], Alonso, A [0000-0001-6860-8432], and Apollo - University of Cambridge Repository
Subjects: anemochory, synzoochory, resource-availability hypothesis, hydrochory, flooded forests, dispersal agents, disperser-availability hypothesis, terra-firme forests, endozoochory, Amazonian rain forests
Abstract: Funder: Brazilian Program for Biodiversity Research, Funder: Fundação de Amparo à Pesquisa do Estado do Amazonas; Id: http://dx.doi.org/10.13039/501100004916, Funder: National Institute for Amazonian Biodiversity, Aim: To investigate the geographic patterns and ecological correlates in the geographic distribution of the most common tree dispersal modes in Amazonia (endozoochory, synzoochory, anemochory and hydrochory). We examined if the proportional abundance of these dispersal modes could be explained by the availability of dispersal agents (disperser‐availability hypothesis) and/or the availability of resources for constructing zoochorous fruits (resource‐availability hypothesis). Time period: Tree‐inventory plots established between 1934 and 2019. Major taxa studied: Trees with a diameter at breast height (DBH) ≥ 9.55 cm. Location: Amazonia, here defined as the lowland rain forests of the Amazon River basin and the Guiana Shield. Methods: We assigned dispersal modes to a total of 5433 species and morphospecies within 1877 tree‐inventory plots across terra‐firme, seasonally flooded, and permanently flooded forests. We investigated geographic patterns in the proportional abundance of dispersal modes. We performed an abundance‐weighted mean pairwise distance (MPD) test and fit generalized linear models (GLMs) to explain the geographic distribution of dispersal modes. Results: Anemochory was significantly, positively associated with mean annual wind speed, and hydrochory was significantly higher in flooded forests. Dispersal modes did not consistently show significant associations with the availability of resources for constructing zoochorous fruits. A lower dissimilarity in dispersal modes, resulting from a higher dominance of endozoochory, occurred in terra‐firme forests (excluding podzols) compared to flooded forests. Main conclusions: The disperser‐availability hypothesis was well supported for abiotic dispersal modes (anemochory and hydrochory). The availability of resources for constructing zoochorous fruits seems an unlikely explanation for the distribution of dispersal modes in Amazonia. The association between frugivores and the proportional abundance of zoochory requires further research, as tree recruitment not only depends on dispersal vectors but also on conditions that favour or limit seedling recruitment across forest types.
Published: 2023

7. The number of tree species on Earth

Author: Gatti, RC, Reich, PB, Gamarra, JGP, Crowther, T, Hui, C, Morera, A, Bastin, JF, de-Miguel, S, Nabuurs, GJ, Svenning, JC, Serra-Diaz, JM, Merow, C, Enquist, B, Kamenetsky, M, Lee, J, Zhu, J, Fang, J, Jacobs, DF, Pijanowski, B, Banerjee, A, Giaquinto, RA, Alberti, G, Zambrano, AMA, Alvarez-Davila, E, Araujo-Murakami, A, Avitabile, V, Aymard, GA, Balazy, R, Baraloto, C, Barroso, JG, Bastian, ML, Birnbaum, P, Bitariho, R, Bogaert, J, Bongers, F, Bouriaud, O, Brancalion, PHS, Brearley, FQ, Broadbent, EN, Bussotti, F, da Silva, WC, César, RG, Češljar, G, Moscoso, VC, Chen, HYH, Cienciala, E, Clark, CJ, Coomes, DA, Dayanandan, S, Decuyper, M, Dee, LE, Del Aguila Pasquel, J, Derroire, G, Djuikouo, MNK, van Do, T, Dolezal, J, Đorđevic, I, Engel, J, Fayle, TM, Feldpausch, TR, Fridman, JK, Harris, DJ, Hemp, A, Hengeveld, G, Herault, B, Herold, M, Ibanez, T, Jagodzinski, AM, Jaroszewicz, B, Jeffery, KJ, Johannsen, VK, Jucker, T, Kangur, A, Karminov, VN, Kartawinata, K, Kennard, DK, Kepfer-Rojas, S, Keppel, G, Khan, ML, Khare, PK, Kileen, TJ, Kim, HS, Korjus, H, Kumar, A, Laarmann, D, Labrière, N, Lang, M, Lewis, SL, Lukina, N, Maitner, BS, Malhi, Y, Marshall, AR, Martynenko, OV, Monteagudo Mendoza, AL, Ontikov, PV, Ortiz-Malavasi, E, Pallqui Camacho, NC, Paquette, A, Park, M, Gatti, RC, Reich, PB, Gamarra, JGP, Crowther, T, Hui, C, Morera, A, Bastin, JF, de-Miguel, S, Nabuurs, GJ, Svenning, JC, Serra-Diaz, JM, Merow, C, Enquist, B, Kamenetsky, M, Lee, J, Zhu, J, Fang, J, Jacobs, DF, Pijanowski, B, Banerjee, A, Giaquinto, RA, Alberti, G, Zambrano, AMA, Alvarez-Davila, E, Araujo-Murakami, A, Avitabile, V, Aymard, GA, Balazy, R, Baraloto, C, Barroso, JG, Bastian, ML, Birnbaum, P, Bitariho, R, Bogaert, J, Bongers, F, Bouriaud, O, Brancalion, PHS, Brearley, FQ, Broadbent, EN, Bussotti, F, da Silva, WC, César, RG, Češljar, G, Moscoso, VC, Chen, HYH, Cienciala, E, Clark, CJ, Coomes, DA, Dayanandan, S, Decuyper, M, Dee, LE, Del Aguila Pasquel, J, Derroire, G, Djuikouo, MNK, van Do, T, Dolezal, J, Đorđevic, I, Engel, J, Fayle, TM, Feldpausch, TR, Fridman, JK, Harris, DJ, Hemp, A, Hengeveld, G, Herault, B, Herold, M, Ibanez, T, Jagodzinski, AM, Jaroszewicz, B, Jeffery, KJ, Johannsen, VK, Jucker, T, Kangur, A, Karminov, VN, Kartawinata, K, Kennard, DK, Kepfer-Rojas, S, Keppel, G, Khan, ML, Khare, PK, Kileen, TJ, Kim, HS, Korjus, H, Kumar, A, Laarmann, D, Labrière, N, Lang, M, Lewis, SL, Lukina, N, Maitner, BS, Malhi, Y, Marshall, AR, Martynenko, OV, Monteagudo Mendoza, AL, Ontikov, PV, Ortiz-Malavasi, E, Pallqui Camacho, NC, Paquette, A, and Park, M
Abstract: One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.
Published: 2022

8. The global spectrum of plant form and function: enhanced species-level trait dataset

Author: Díaz, S., Kattge, J., Cornelissen, J.H.C., Wright, I.J., Lavorel, S., Dray, S., Reu, B., Kleyer, M., Wirth, C., Prentice, I.C., Garnier, E., Bönisch, G., Westoby, M., Poorter, H., Reich, P.B., Moles, A.T., Dickie, J., Zanne, A.E., Chave, J., Wright, S.J., Sheremetiev, S.N., Jactel, H., Baraloto, C., Cerabolini, B.E.L., Pierce, S., Shipley, B., Casanoves, F., Joswig, J.S., Günther, A., Falczuk, V., Mahecha, M.D., Gorné, L.D., Amiaud, B., Atkin, O.K., Bahn, M., Baldocchi, D., Beckmann, Michael, Blonder, B., Bond, W., Bond-Lamberty, B., Brown, K., Burrascano, S., Byun, C., Campetella, G., Cavender-Bares, J., Stuart Chapin III, F., Choat, B., Coomes, D.A., Cornwell, W.K., Craine, J., Craven, D., Dainese, M., de Araujo, A.C., de Vries, F.T., Ferreira Domingues, T., Enquist, B.J., Fagúndez, J., Fang, J., Fernández-Méndez, F., Fernandez-Piedade, M.T., Ford, H., Forey, E., Freschet, G.T., Gachet, S., Gallagher, R., Green, W., Guerin, G.R., Gutiérrez, A.G., Harrison, S.P., Hattingh, W.N., He, T., Hickler, T., Higgins, S.I., Higuchi, P., Ilic, J., Jackson, R.B., Jalili, A., Jansen, S., Koike, F., König, C., Kraft, N., Kramer, K., Kreft, H., Kühn, Ingolf, Kurokawa, H., Lamb, E.G., Laughlin, D.C., Leishman, M., Lewis, S., Louault, F., Malhado, A.C.M., Manning, P., Meir, P., Mencuccini, M., Messier, J., Miller, R., Minden, V., Molofsky, J., Montgomery, R., Montserrat-Martí, G., Díaz, S., Kattge, J., Cornelissen, J.H.C., Wright, I.J., Lavorel, S., Dray, S., Reu, B., Kleyer, M., Wirth, C., Prentice, I.C., Garnier, E., Bönisch, G., Westoby, M., Poorter, H., Reich, P.B., Moles, A.T., Dickie, J., Zanne, A.E., Chave, J., Wright, S.J., Sheremetiev, S.N., Jactel, H., Baraloto, C., Cerabolini, B.E.L., Pierce, S., Shipley, B., Casanoves, F., Joswig, J.S., Günther, A., Falczuk, V., Mahecha, M.D., Gorné, L.D., Amiaud, B., Atkin, O.K., Bahn, M., Baldocchi, D., Beckmann, Michael, Blonder, B., Bond, W., Bond-Lamberty, B., Brown, K., Burrascano, S., Byun, C., Campetella, G., Cavender-Bares, J., Stuart Chapin III, F., Choat, B., Coomes, D.A., Cornwell, W.K., Craine, J., Craven, D., Dainese, M., de Araujo, A.C., de Vries, F.T., Ferreira Domingues, T., Enquist, B.J., Fagúndez, J., Fang, J., Fernández-Méndez, F., Fernandez-Piedade, M.T., Ford, H., Forey, E., Freschet, G.T., Gachet, S., Gallagher, R., Green, W., Guerin, G.R., Gutiérrez, A.G., Harrison, S.P., Hattingh, W.N., He, T., Hickler, T., Higgins, S.I., Higuchi, P., Ilic, J., Jackson, R.B., Jalili, A., Jansen, S., Koike, F., König, C., Kraft, N., Kramer, K., Kreft, H., Kühn, Ingolf, Kurokawa, H., Lamb, E.G., Laughlin, D.C., Leishman, M., Lewis, S., Louault, F., Malhado, A.C.M., Manning, P., Meir, P., Mencuccini, M., Messier, J., Miller, R., Minden, V., Molofsky, J., Montgomery, R., and Montserrat-Martí, G.
Abstract: Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date. Measurement(s) plant trait Technology Type(s) various Factor Type(s) none Sample Characteristic - Organism Tracheophyta Sample Characteristic - Environment natural environment Sample Characteristic - Location global
Published: 2022

9. The number of tree species on Earth

Author: Cazzolla Gatti, R., Reich, P., Gamarra, J., Crowther, T., Hui, C., Morera, A., Bastin, J.-F., de-Miguel, S., Nabuurs, G.-J., Svenning, J.-C., Serra-Diaz, J., Merow, C., Enquist, B., Kamenetsky, M., Lee, J., Zhu, J., Fang, J., Jacobs, D., Pijanowski, B., Banerjee, A., Giaquinto, R., Alberti, G., Almeyda Zambrano, A., Alvarez-Davila, E., Araujo-Murakami, A., Avitabile, V., Aymard, G., Balazy, R., Baraloto, C., Barroso, J., Bastian, M., Birnbaum, P., Bitariho, R., Bogaert, J., Bongers, F., Bouriaud, O., Brancalion, P., Brearley, F., Broadbent, E., Bussotti, F., Castro da Silva, W., César, R., Češljar, G., Chama Moscoso, V., Chen, H., Cienciala, E., Clark, C., Coomes, D., Dayanandan, S., Decuyper, M., Dee, L., Del Aguila Pasquel, J., Derroire, G., Djuikouo, M., Van Do, T., Dolezal, J., Đorđević, I., Engel, J., Fayle, T., Feldpausch, T., Fridman, J., Harris, D., Hemp, A., Hengeveld, G., Herault, B., Herold, M., Ibanez, T., Jagodzinski, A., Jaroszewicz, B., Jeffery, K., Johannsen, V., Jucker, T., Kangur, A., Karminov, V., Kartawinata, K., Kennard, D., Kepfer-Rojas, S., Keppel, G., Khan, M., Khare, P., Kileen, T., Kim, H., Korjus, H., Kumar, A., Laarmann, D., Labrière, N., Lang, M., Lewis, S., Lukina, N., Maitner, B., Malhi, Y., Marshall, A., Martynenko, O., Monteagudo Mendoza, A., Ontikov, P., Ortiz-Malavasi, E., Pallqui Camacho, N., Paquette, A., Park, M., Parthasarathy, N., Peri, P., Petronelli, P., Pfautsch, S., Phillips, O., Picard, N., Piotto, D., Poorter, L., Poulsen, J., Pretzsch, H., Ramírez-Angulo, H., Restrepo Correa, Z., Rodeghiero, M., Rojas Gonzáles, R., Rolim, S., Rovero, F., Rutishauser, E., Saikia, P., Salas-Eljatib, C., Shchepashchenko, D., Scherer-Lorenzen, M., Šebeň, V., Silveira, M., Slik, F., Sonké, B., Souza, A., Stereńczak, K., Svoboda, M., Taedoumg, H., Tchebakova, N., Terborgh, J., Tikhonova, E., Torres-Lezama, A., van der Plas, F., Vásquez, R., Viana, H., Vibrans, A., Vilanova, E., Vos, V., Wang, H.-F., Westerlund, B., White, L., Wiser, S., Zawiła-Niedźwiecki, T., Zemagho, L., Zhu, Z., Zo-Bi, I., Liang, J., Cazzolla Gatti, R., Reich, P., Gamarra, J., Crowther, T., Hui, C., Morera, A., Bastin, J.-F., de-Miguel, S., Nabuurs, G.-J., Svenning, J.-C., Serra-Diaz, J., Merow, C., Enquist, B., Kamenetsky, M., Lee, J., Zhu, J., Fang, J., Jacobs, D., Pijanowski, B., Banerjee, A., Giaquinto, R., Alberti, G., Almeyda Zambrano, A., Alvarez-Davila, E., Araujo-Murakami, A., Avitabile, V., Aymard, G., Balazy, R., Baraloto, C., Barroso, J., Bastian, M., Birnbaum, P., Bitariho, R., Bogaert, J., Bongers, F., Bouriaud, O., Brancalion, P., Brearley, F., Broadbent, E., Bussotti, F., Castro da Silva, W., César, R., Češljar, G., Chama Moscoso, V., Chen, H., Cienciala, E., Clark, C., Coomes, D., Dayanandan, S., Decuyper, M., Dee, L., Del Aguila Pasquel, J., Derroire, G., Djuikouo, M., Van Do, T., Dolezal, J., Đorđević, I., Engel, J., Fayle, T., Feldpausch, T., Fridman, J., Harris, D., Hemp, A., Hengeveld, G., Herault, B., Herold, M., Ibanez, T., Jagodzinski, A., Jaroszewicz, B., Jeffery, K., Johannsen, V., Jucker, T., Kangur, A., Karminov, V., Kartawinata, K., Kennard, D., Kepfer-Rojas, S., Keppel, G., Khan, M., Khare, P., Kileen, T., Kim, H., Korjus, H., Kumar, A., Laarmann, D., Labrière, N., Lang, M., Lewis, S., Lukina, N., Maitner, B., Malhi, Y., Marshall, A., Martynenko, O., Monteagudo Mendoza, A., Ontikov, P., Ortiz-Malavasi, E., Pallqui Camacho, N., Paquette, A., Park, M., Parthasarathy, N., Peri, P., Petronelli, P., Pfautsch, S., Phillips, O., Picard, N., Piotto, D., Poorter, L., Poulsen, J., Pretzsch, H., Ramírez-Angulo, H., Restrepo Correa, Z., Rodeghiero, M., Rojas Gonzáles, R., Rolim, S., Rovero, F., Rutishauser, E., Saikia, P., Salas-Eljatib, C., Shchepashchenko, D., Scherer-Lorenzen, M., Šebeň, V., Silveira, M., Slik, F., Sonké, B., Souza, A., Stereńczak, K., Svoboda, M., Taedoumg, H., Tchebakova, N., Terborgh, J., Tikhonova, E., Torres-Lezama, A., van der Plas, F., Vásquez, R., Viana, H., Vibrans, A., Vilanova, E., Vos, V., Wang, H.-F., Westerlund, B., White, L., Wiser, S., Zawiła-Niedźwiecki, T., Zemagho, L., Zhu, Z., Zo-Bi, I., and Liang, J.
Abstract: One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.
Published: 2022

10. Long-term decline of the Amazon carbon sink

Author: Brienen, R. J. W., Phillips, O. L., Feldpausch, T. R., Gloor, E., Baker, T. R., Lloyd, J., Lopez-Gonzalez, G., Monteagudo-Mendoza, A., Malhi, Y., Lewis, S. L., Vásquez Martinez, R., Alexiades, M., Álvarez Dávila, E., Alvarez-Loayza, P., Andrade, A., Aragão, L. E. O. C., Araujo-Murakami, A., Arets, E. J. M. M., Arroyo, L., Aymard, G. A. C., Bánki, O. S., Baraloto, C., Barroso, J., Bonal, D., Boot, R. G. A., Camargo, J. L. C., Castilho, C. V., Chama, V., Chao, K. J., Chave, J., Comiskey, J. A., Cornejo Valverde, F., da Costa, L., de Oliveira, E. A., Di Fiore, A., Erwin, T. L., Fauset, S., Forsthofer, M., Galbraith, D. R., Grahame, E. S., Groot, N., Hérault, B., Higuchi, N., Honorio Coronado, E. N., Keeling, H., Killeen, T. J., Laurance, W. F., Laurance, S., Licona, J., Magnussen, W. E., Marimon, B. S., Marimon-Junior, B. H., Mendoza, C., Neill, D. A., Nogueira, E. M., Núñez, P., Pallqui Camacho, N. C., Parada, A., Pardo-Molina, G., Peacock, J., Peña-Claros, M., Pickavance, G. C., Pitman, N. C. A., Poorter, L., Prieto, A., Quesada, C. A., Ramírez, F., Ramírez-Angulo, H., Restrepo, Z., Roopsind, A., Rudas, A., Salomão, R. P., Schwarz, M., Silva, N., Silva-Espejo, J. E., Silveira, M., Stropp, J., Talbot, J., ter Steege, H., Teran-Aguilar, J., Terborgh, J., Thomas-Caesar, R., Toledo, M., Torello-Raventos, M., Umetsu, R. K., van der Heijden, G. M. F., van der Hout, P., Guimarães Vieira, I. C., Vieira, S. A., Vilanova, E., Vos, V. A., and Zagt, R. J.
Published: 2015
Full Text: View/download PDF

11. Author Correction: Tree mode of death and mortality risk factors across Amazon forests (Nature Communications, (2020), 11, 1, (5515), 10.1038/s41467-020-18996-3)

Author: Esquivel-Muelbert, A, Phillips, OL, Brienen, RJW, Fauset, S, Sullivan, MJP, Baker, TR, Chao, KJ, Feldpausch, TR, Gloor, E, Higuchi, N, Houwing-Duistermaat, J, Lloyd, J, Liu, H, Malhi, Y, Marimon, B, Marimon Junior, BH, Monteagudo-Mendoza, A, Poorter, L, Silveira, M, Torre, EV, Dávila, EA, del Aguila Pasquel, J, Almeida, E, Loayza, PA, Andrade, A, Aragão, LEOC, Araujo-Murakami, A, Arets, E, Arroyo, L, Aymard C, GA, Baisie, M, Baraloto, C, Camargo, PB, Barroso, J, Blanc, L, Bonal, D, Bongers, F, Boot, R, Brown, F, Burban, B, Camargo, JL, Castro, W, Moscoso, VC, Chave, J, Comiskey, J, Valverde, FC, da Costa, AL, Cardozo, ND, Di Fiore, A, Dourdain, A, Erwin, T, Llampazo, GF, Vieira, ICG, Herrera, R, Honorio Coronado, E, Huamantupa-Chuquimaco, I, Jimenez-Rojas, E, Killeen, T, Laurance, S, Laurance, W, Levesley, A, Lewis, SL, Ladvocat, KLLM, Lopez-Gonzalez, G, Lovejoy, T, Meir, P, Mendoza, C, Morandi, P, Neill, D, Nogueira Lima, AJ, Vargas, PN, de Oliveira, EA, Camacho, NP, Pardo, G, Peacock, J, Peña-Claros, M, Peñuela-Mora, MC, Pickavance, G, Pipoly, J, Pitman, N, Prieto, A, Pugh, TAM, Quesada, C, Ramirez-Angulo, H, de Almeida Reis, SM, Rejou-Machain, M, Correa, ZR, Bayona, LR, Rudas, A, Salomão, R, Serrano, J, Espejo, JS, Silva, N, Singh, J, Stahl, C, Stropp, J, Swamy, V, Talbot, J, ter Steege, H, and Terborgh, J
Abstract: The original version of this Article contained an error in Table 2, where the number of individuals in the “All Amazonia” row was reported as 11,6431 instead of 116,431. Also, the original version of this Article contained an error in the Methods, where the R2 for the proportion of broken/uprooted dead trees increase per year was reported as 0.12, the correct value being 0.06. The original version of this Article contained errors in the author affiliations. The affiliation of Gerardo A. Aymard C. with UNELLEZGuanare, Herbario Universitario (PORT), Portuguesa, Venezuela Compensation International Progress S.A. Ciprogress–Greenlife.
Published: 2021

12. 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

13. A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data

Author: Moreno-Martinez, A., Camps-Valls, G., Kattge, J., Robinson, N., Reichstein, M., Bodegom, P.M. van, Kramer, K., Cornelissen, J., Hans, C., Reich, P., Bahn, M., Niinemets, U., Penuelas, J., Craine, J.M., Cerabolini, B.E.L., Minden, V., Laughlin, D.C., Sack, L., Allred, B., Baraloto, C., Byun, C., Soudzilovskaia, N.A., Running, S.W., Biology, and Systems Ecology
Subjects: 0106 biological sciences, FOS: Computer and information sciences, 010504 meteorology & atmospheric sciences, Specific leaf area, Climate, Bos- en Landschapsecologie, Soil Science, FOS: Physical sciences, Applied Physics (physics.app-ph), 010603 evolutionary biology, 01 natural sciences, Statistics - Applications, Goodness of fit, Abundance (ecology), Machine learning, Forest and Landscape Ecology, Applications (stat.AP), Computers in Earth Sciences, Plant ecology, Vegetatie, 0105 earth and related environmental sciences, Remote sensing, Mathematics, 2. Zero hunger, Plant traits, Vegetation, Data stream mining, Landsat, MODIS, Random forests, Geology, Global Map, Regression analysis, Physics - Applied Physics, 15. Life on land, PE&RC, Random forest, Trait, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology
Abstract: This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then aggregated to Plant Functional Types (PFTs). Next, the spatial abundance of PFTs at MODIS resolution (500 m) is calculated using Landsat data (30 m). Based on these PFT abundances, representative trait values are calculated for MODIS pixels with nearby trait data. Finally, different regression algorithms are applied to globally predict trait estimates from these MODIS pixels using remote sensing and climate data. The methods were compared in terms of precision, robustness and efficiency. The best model (random forests regression) shows good precision (normalized RMSE≤ 20%) and goodness of fit (averaged Pearson's correlation R = 0.78) in any considered trait. Along with the estimated global maps of leaf traits, we provide associated uncertainty estimates derived from the regression models. The process chain is modular, and can easily accommodate new traits, data streams (traits databases and remote sensing data), and methods. The machine learning techniques applied allow attribution of information gain to data input and thus provide the opportunity to understand trait-environment relationships at the plant and ecosystem scales. The new data products – the gap-filled trait matrix, a global map of PFT abundance per MODIS gridcells and the high-resolution global leaf trait maps – are complementary to existing large-scale observations of the land surface and we therefore anticipate substantial contributions to advances in quantifying, understanding and prediction of the Earth system.
Published: 2020
Full Text: View/download PDF

14. Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities

Author: Draper, FC, Baraloto, C, Brodrick, PG, Phillips, OL, Vasquez Martinez, R, Honorio Coronado, EN, Baker, TR, Zárate Gómez, R, Amasifuen Guerra, CA, Flores, M, García Villacorta, R, Fine, PVA, Freitas, L, Monteagudo-Mendoza, A, Brienen, RJW, and Asner, GP
Abstract: 1. The forests of Amazonia are among the most biodiverse on Earth, yet accurately quantifying how species composition varies through space (i.e., beta‐diversity) remains a significant challenge. Here, we use high‐fidelity airborne imaging spectroscopy from the Carnegie Airborne Observatory to quantify a key component of beta‐diversity, the distance decay in species similarity through space, across three landscapes in Northern Peru. We then compared our derived distance decay relationships to theoretical expectations obtained from a Poisson Cluster Process, known to match well with empirical distance decay relationships at local scales. 2. We used an unsupervised machine learning approach to estimate spatial turnover in species composition from the imaging spectroscopy data. We first validated this approach across two landscapes using an independent dataset of forest composition in 49 forest census plots (0.1–1.5 ha). We then applied our approach to three landscapes, which together represented terra firme clay forest, seasonally flooded forest and white‐sand forest. We finally used our approach to quantify landscape‐scale distance decay relationships and compared these with theoretical distance decay relationships derived from a Poisson Cluster Process. 3. We found a significant correlation of similarity metrics between spectral data and forest plot data, suggesting that beta‐diversity within and among forest types can be accurately estimated from airborne spectroscopic data using our unsupervised approach. We also found that estimated distance decay in species similarity varied among forest types, with seasonally flooded forests showing stronger distance decay than white‐sand and terra firme forests. Finally, we demonstrated that distance decay relationships derived from the theoretical Poisson Cluster Process compare poorly with our empirical relationships. 4. Synthesis. Our results demonstrate the efficacy of using high‐fidelity imaging spectroscopy to estimate beta‐diversity and continuous distance decay in lowland tropical forests. Furthermore, our findings suggest that distance decay relationships vary substantially among forest types, which has important implications for conserving these valuable ecosystems. Finally, we demonstrate that a theoretical Poisson Cluster Process poorly predicts distance decay in species similarity as conspecific aggregation occurs across a range of nested scales within larger landscapes.
Published: 2019

15. Biased-corrected richness estimates for the Amazonian tree flora

Author: ter Steege, H., Prado, P.I., Lima, R.A.F., Pos, E., de Souza Coelho, L., de Andrade Lima Filho, D., Salomão, R.P., Amaral, I.L., de Almeida Matos, F.D., Castilho, C.V., Phillips, O.L., Guevara, J.E., de Jesus Veiga Carim, M., Cárdenas López, D., Magnusson, W.E., Wittmann, F., Martins, M.P., Sabatier, D., Irume, M.V., da Silva Guimarães, J.R., Molino, J.-F., Bánki, O.S., Piedade, M.T.F., Pitman, N.C.A., Ramos, J.F., Monteagudo Mendoza, A., Venticinque, E.M., Luize, B.G., Núñez Vargas, P., Silva, T.S.F., de Leão Novo, E.M.M., Reis, N.F.C., Terborgh, J., Manzatto, A.G., Casula, K.R., Honorio Coronado, E.N., Montero, J.C., Duque, A., Costa, F.R.C., Castaño Arboleda, N., Schöngart, J., Zartman, C.E., Killeen, T.J., Marimon, B.S., Marimon-Junior, B.H., Vasquez, R., Mostacedo, B., Demarchi, L.O., Feldpausch, T.R., Engel, J., Petronelli, P., Baraloto, C., Assis, R.L., Castellanos, H., Simon, M.F., de Medeiros, M.B., Quaresma, A., Laurance, S.G.W., Rincón, L.M., Andrade, A., Sousa, T.R., Camargo, J.L., Schietti, J., Laurance, W.F., de Queiroz, H.L., Nascimento, H.E.M., Lopes, M.A., de Sousa Farias, E., Magalhães, J.L.L., Brienen, R., Aymard C, G.A., Revilla, J.D.C., Vieira, I.C.G., Cintra, B.B.L., Stevenson, P.R., Feitosa, Y.O., Duivenvoorden, J.F., Mogollón, H.F., Araujo-Murakami, A., Ferreira, L.V., Lozada, J.R., Comiskey, J.A., de Toledo, J.J., Damasco, G., Dávila, N., Lopes, A., García-Villacorta, R., Draper, F., Vicentini, A., Cornejo Valverde, F., Lloyd, J., Gomes, V.H.F., Neill, D., Alonso, A., Dallmeier, F., de Souza, F.C., Gribel, R., Arroyo, L., Carvalho, F.A., de Aguiar, D.P.P., do Amaral, D.D., Pansonato, M.P., Feeley, K.J., Berenguer, E., Fine, P.V.A., Guedes, M.C., Barlow, J., Ferreira, J., Villa, B., Peñuela Mora, M.C., Jimenez, E.M., Licona, J.C., Cerón, C., Thomas, R., Maas, P., Silveira, M., Henkel, T.W., Stropp, J., Paredes, M.R., Dexter, K.G., Daly, D., Baker, T.R., Huamantupa-Chuquimaco, I., Milliken, W., Pennington, T., Tello, J.S., Pena, J.L.M., Peres, C.A., Klitgaard, B., Fuentes, A., Silman, M.R., Di Fiore, A., von Hildebrand, P., Chave, J., van Andel, T.R., Hilário, R.R., Phillips, J.F., Rivas-Torres, G., Noronha, J.C., Prieto, A., Gonzales, T., de Sá Carpanedo, R., Gonzales, G.P.G., Gómez, R.Z., de Jesus Rodrigues, D., Zent, E.L., Ruschel, A.R., Vos, V.A., Fonty, É., Junqueira, A.B., Doza, H.P.D., Hoffman, B., Zent, S., Barbosa, E.M., Malhi, Y., de Matos Bonates, L.C., de Andrade Miranda, I.P., Silva, N., Barbosa, F.R., Vela, C.I.A., Pinto, L.F.M., Rudas, A., Albuquerque, B.W., Umaña, M.N., Carrero Márquez, Y.A., van der Heijden, G., Young, K.R., Tirado, M., Correa, D.F., Sierra, R., Costa, J.B.P., Rocha, M., Vilanova Torre, E., Wang, O., Oliveira, A.A., Kalamandeen, M., Vriesendorp, C., Ramirez-Angulo, H., Holmgren, M., Nascimento, M.T., Galbraith, D., Flores, B.M., Scudeller, V.V., Cano, A., Ahuite Reategui, M.A., Mesones, I., Baider, C., Mendoza, C., Zagt, R., Urrego Giraldo, L.E., Ferreira, C., Villarroel, D., Linares-Palomino, R., Farfan-Rios, W., Casas, L.F., Cárdenas, S., Balslev, H., Torres-Lezama, A., Alexiades, M.N., Garcia-Cabrera, K., Valenzuela Gamarra, L., Valderrama Sandoval, E.H., Ramirez Arevalo, F., Hernandez, L., Sampaio, A.F., Pansini, S., Palacios Cuenca, W., de Oliveira, E.A., Pauletto, D., Levesley, A., Melgaço, K., Pickavance, G., ter Steege, H., Prado, P.I., Lima, R.A.F., Pos, E., de Souza Coelho, L., de Andrade Lima Filho, D., Salomão, R.P., Amaral, I.L., de Almeida Matos, F.D., Castilho, C.V., Phillips, O.L., Guevara, J.E., de Jesus Veiga Carim, M., Cárdenas López, D., Magnusson, W.E., Wittmann, F., Martins, M.P., Sabatier, D., Irume, M.V., da Silva Guimarães, J.R., Molino, J.-F., Bánki, O.S., Piedade, M.T.F., Pitman, N.C.A., Ramos, J.F., Monteagudo Mendoza, A., Venticinque, E.M., Luize, B.G., Núñez Vargas, P., Silva, T.S.F., de Leão Novo, E.M.M., Reis, N.F.C., Terborgh, J., Manzatto, A.G., Casula, K.R., Honorio Coronado, E.N., Montero, J.C., Duque, A., Costa, F.R.C., Castaño Arboleda, N., Schöngart, J., Zartman, C.E., Killeen, T.J., Marimon, B.S., Marimon-Junior, B.H., Vasquez, R., Mostacedo, B., Demarchi, L.O., Feldpausch, T.R., Engel, J., Petronelli, P., Baraloto, C., Assis, R.L., Castellanos, H., Simon, M.F., de Medeiros, M.B., Quaresma, A., Laurance, S.G.W., Rincón, L.M., Andrade, A., Sousa, T.R., Camargo, J.L., Schietti, J., Laurance, W.F., de Queiroz, H.L., Nascimento, H.E.M., Lopes, M.A., de Sousa Farias, E., Magalhães, J.L.L., Brienen, R., Aymard C, G.A., Revilla, J.D.C., Vieira, I.C.G., Cintra, B.B.L., Stevenson, P.R., Feitosa, Y.O., Duivenvoorden, J.F., Mogollón, H.F., Araujo-Murakami, A., Ferreira, L.V., Lozada, J.R., Comiskey, J.A., de Toledo, J.J., Damasco, G., Dávila, N., Lopes, A., García-Villacorta, R., Draper, F., Vicentini, A., Cornejo Valverde, F., Lloyd, J., Gomes, V.H.F., Neill, D., Alonso, A., Dallmeier, F., de Souza, F.C., Gribel, R., Arroyo, L., Carvalho, F.A., de Aguiar, D.P.P., do Amaral, D.D., Pansonato, M.P., Feeley, K.J., Berenguer, E., Fine, P.V.A., Guedes, M.C., Barlow, J., Ferreira, J., Villa, B., Peñuela Mora, M.C., Jimenez, E.M., Licona, J.C., Cerón, C., Thomas, R., Maas, P., Silveira, M., Henkel, T.W., Stropp, J., Paredes, M.R., Dexter, K.G., Daly, D., Baker, T.R., Huamantupa-Chuquimaco, I., Milliken, W., Pennington, T., Tello, J.S., Pena, J.L.M., Peres, C.A., Klitgaard, B., Fuentes, A., Silman, M.R., Di Fiore, A., von Hildebrand, P., Chave, J., van Andel, T.R., Hilário, R.R., Phillips, J.F., Rivas-Torres, G., Noronha, J.C., Prieto, A., Gonzales, T., de Sá Carpanedo, R., Gonzales, G.P.G., Gómez, R.Z., de Jesus Rodrigues, D., Zent, E.L., Ruschel, A.R., Vos, V.A., Fonty, É., Junqueira, A.B., Doza, H.P.D., Hoffman, B., Zent, S., Barbosa, E.M., Malhi, Y., de Matos Bonates, L.C., de Andrade Miranda, I.P., Silva, N., Barbosa, F.R., Vela, C.I.A., Pinto, L.F.M., Rudas, A., Albuquerque, B.W., Umaña, M.N., Carrero Márquez, Y.A., van der Heijden, G., Young, K.R., Tirado, M., Correa, D.F., Sierra, R., Costa, J.B.P., Rocha, M., Vilanova Torre, E., Wang, O., Oliveira, A.A., Kalamandeen, M., Vriesendorp, C., Ramirez-Angulo, H., Holmgren, M., Nascimento, M.T., Galbraith, D., Flores, B.M., Scudeller, V.V., Cano, A., Ahuite Reategui, M.A., Mesones, I., Baider, C., Mendoza, C., Zagt, R., Urrego Giraldo, L.E., Ferreira, C., Villarroel, D., Linares-Palomino, R., Farfan-Rios, W., Casas, L.F., Cárdenas, S., Balslev, H., Torres-Lezama, A., Alexiades, M.N., Garcia-Cabrera, K., Valenzuela Gamarra, L., Valderrama Sandoval, E.H., Ramirez Arevalo, F., Hernandez, L., Sampaio, A.F., Pansini, S., Palacios Cuenca, W., de Oliveira, E.A., Pauletto, D., Levesley, A., Melgaço, K., and Pickavance, G.
Abstract: Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come. © 2020, The Author(s).
Published: 2020

16. 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

17. Compositional response of Amazon forests to climate change

Author: Esquivel-Muelbert, A, Baker, TR, Dexter, KG, Lewis, SL, Brienen, RJW, Feldpausch, TR, Lloyd, J, Monteagudo-Mendoza, A, Arroyo, L, Álvarez-Dávila, E, Higuchi, N, Marimon, BS, Marimon-Junior, BH, Silveira, M, Vilanova, E, Gloor, E, Malhi, Y, Chave, J, Barlow, J, Bonal, D, Davila Cardozo, N, Erwin, T, Fauset, S, Hérault, B, Laurance, S, Poorter, L, Qie, L, Stahl, C, Sullivan, MJP, ter Steege, H, Vos, VA, Zuidema, PA, Almeida, E, Almeida de Oliveira, E, Andrade, A, Vieira, SA, Aragão, L, Araujo-Murakami, A, Arets, E, Aymard C, GA, Baraloto, C, Camargo, PB, Barroso, JG, Bongers, F, Boot, R, Camargo, JL, Castro, W, Chama Moscoso, V, Comiskey, J, Cornejo Valverde, F, Lola da Costa, AC, del Aguila Pasquel, J, Di Fiore, A, Fernanda Duque, L, Elias, F, Engel, J, Flores Llampazo, G, Galbraith, D, Herrera Fernández, R, Honorio Coronado, E, Hubau, W, Jimenez-Rojas, E, Lima, AJN, Umetsu, RK, Laurance, W, Lopez-Gonzalez, G, Lovejoy, T, Aurelio Melo Cruz, O, Morandi, PS, Neill, D, Núñez Vargas, P, Pallqui Camacho, NC, Parada Gutierrez, A, Pardo, G, Peacock, J, Peña-Claros, M, Peñuela-Mora, MC, Petronelli, P, Pickavance, GC, Pitman, N, Prieto, A, Quesada, C, Ramírez-Angulo, H, Réjou-Méchain, M, Restrepo Correa, Z, Roopsind, A, Rudas, A, Salomão, R, Silva, N, Silva Espejo, J, Singh, J, Stropp, J, Terborgh, J, Thomas, R, Toledo, M, Torres-Lezama, A, Valenzuela Gamarra, L, van de Meer, PJ, van der Heijden, G, van der Hout, P, Esquivel-Muelbert, A, Baker, TR, Dexter, KG, Lewis, SL, Brienen, RJW, Feldpausch, TR, Lloyd, J, Monteagudo-Mendoza, A, Arroyo, L, Álvarez-Dávila, E, Higuchi, N, Marimon, BS, Marimon-Junior, BH, Silveira, M, Vilanova, E, Gloor, E, Malhi, Y, Chave, J, Barlow, J, Bonal, D, Davila Cardozo, N, Erwin, T, Fauset, S, Hérault, B, Laurance, S, Poorter, L, Qie, L, Stahl, C, Sullivan, MJP, ter Steege, H, Vos, VA, Zuidema, PA, Almeida, E, Almeida de Oliveira, E, Andrade, A, Vieira, SA, Aragão, L, Araujo-Murakami, A, Arets, E, Aymard C, GA, Baraloto, C, Camargo, PB, Barroso, JG, Bongers, F, Boot, R, Camargo, JL, Castro, W, Chama Moscoso, V, Comiskey, J, Cornejo Valverde, F, Lola da Costa, AC, del Aguila Pasquel, J, Di Fiore, A, Fernanda Duque, L, Elias, F, Engel, J, Flores Llampazo, G, Galbraith, D, Herrera Fernández, R, Honorio Coronado, E, Hubau, W, Jimenez-Rojas, E, Lima, AJN, Umetsu, RK, Laurance, W, Lopez-Gonzalez, G, Lovejoy, T, Aurelio Melo Cruz, O, Morandi, PS, Neill, D, Núñez Vargas, P, Pallqui Camacho, NC, Parada Gutierrez, A, Pardo, G, Peacock, J, Peña-Claros, M, Peñuela-Mora, MC, Petronelli, P, Pickavance, GC, Pitman, N, Prieto, A, Quesada, C, Ramírez-Angulo, H, Réjou-Méchain, M, Restrepo Correa, Z, Roopsind, A, Rudas, A, Salomão, R, Silva, N, Silva Espejo, J, Singh, J, Stropp, J, Terborgh, J, Thomas, R, Toledo, M, Torres-Lezama, A, Valenzuela Gamarra, L, van de Meer, PJ, van der Heijden, G, and van der Hout, P
Abstract: © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO 2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO 2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.
Published: 2019

18. Rarity of monodominance in hyperdiverse Amazonian forests

Author: Ter Steege, H., Henkel, T.W., Helal, N., Marimon, B.S., Marimon-Junior, B.H., Huth, A., Groeneveld, J., Sabatier, D., Coelho, L.S., Filho, D.A.L., Salomão, R.P., Amaral, I.L., Matos, F.D.A., Castilho, C.V., Phillips, O.L., Guevara, J.E., Carim, M.J.V., Cárdenas López, D., Magnusson, W.E., Wittmann, F., Irume, M.V., Martins, M.P., Guimarães, J.R.D.S., Molino, J.-F., Bánki, O.S., Piedade, M.T.F., Pitman, N.C.A., Mendoza, A.M., Ramos, J.F., Luize, B.G., Moraes de Leão Novo, E.M., Núñez Vargas, P., Silva, T.S.F., Venticinque, E.M., Manzatto, A.G., Reis, N.F.C., Terborgh, J., Casula, K.R., Honorio Coronado, E.N., Montero, J.C., Feldpausch, T.R., Duque, A., Costa, F.R.C., Arboleda, N.C., Schöngart, J., Killeen, T.J., Vasquez, R., Mostacedo, B., Demarchi, L.O., Assis, R.L., Baraloto, C., Engel, J., Petronelli, P., Castellanos, H., de Medeiros, M.B., Quaresma, A., Simon, M.F., Andrade, A., Camargo, J.L., Laurance, S.G.W., Laurance, W.F., Rincón, L.M., Schietti, J., Sousa, T.R., de Sousa Farias, E., Lopes, M.A., Magalhães, J.L.L., Mendonça Nascimento, H.E., Lima de Queiroz, H., Aymard C, G.A., Brienen, R., Revilla, J.D.C., Vieira, I.C.G., Cintra, B.B.L., Stevenson, P.R., Feitosa, Y.O., Duivenvoorden, J.F., Mogollón, H.F., Araujo-Murakami, A., Ferreira, L.V., Lozada, J.R., Comiskey, J.A., de Toledo, J.J., Damasco, G., Dávila, N., Draper, F., García-Villacorta, R., Lopes, A., Vicentini, A., Alonso, A., Dallmeier, F., Gomes, V.H.F., Lloyd, J., Neill, D., de Aguiar, D.P.P., Arroyo, L., Carvalho, F.A., de Souza, F.C., do Amaral, D.D., Feeley, K.J., Gribel, R., Pansonato, M.P., Barlow, J., Berenguer, E., Ferreira, J., Fine, P.V.A., Guedes, M.C., Jimenez, E.M., Licona, J.C., Peñuela Mora, M.C., Villa, B., Cerón, C., Maas, P., Silveira, M., Stropp, J., Thomas, R., Baker, T.R., Daly, D., Dexter, K.G., Huamantupa-Chuquimaco, I., Milliken, W., Pennington, T., Ríos Paredes, M., Fuentes, A., Klitgaard, B., Pena, J.L.M., Peres, C.A., Silman, M.R., Tello, J.S., Chave, J., Cornejo Valverde, F., Di Fiore, A., Hilário, R.R., Phillips, J.F., Rivas-Torres, G., van Andel, T.R., von Hildebrand, P., Noronha, J.C., Barbosa, E.M., Barbosa, F.R., de Matos Bonates, L.C., Carpanedo, R.S., Dávila Doza, H.P., Fonty, É., GómeZárate Z, R., Gonzales, T., Gallardo Gonzales, G.P., Hoffman, B., Junqueira, A.B., Malhi, Y., Miranda, I.P.A., Pinto, L.F.M., Prieto, A., Rodrigues, D.J., Rudas, A., Ruschel, A.R., Silva, N., Vela, C.I.A., Vos, V.A., Zent, E.L., Zent, S., Weiss Albuquerque, B., Cano, A., Carrero Márquez, Y.A., Correa, D.F., Costa, J.B.P., Flores, B.M., Galbraith, D., Holmgren, M., Kalamandeen, M., Nascimento, M.T., Oliveira, A.A., Ramirez-Angulo, H., Rocha, M., Scudeller, V.V., Sierra, R., Tirado, M., Umaña Medina, M.N., van der Heijden, G., Vilanova Torre, E., Vriesendorp, C., Wang, O., Young, K.R., Ahuite Reategui, M.A., Baider, C., Balslev, H., Cárdenas, S., Casas, L.F., Farfan-Rios, W., Ferreira, C., Linares-Palomino, R., Mendoza, C., Mesones, I., Torres-Lezama, A., Giraldo, L.E.U., Villarroel, D., Zagt, R., Alexiades, M.N., de Oliveira, E.A., Garcia-Cabrera, K., Hernandez, L., Palacios Cuenca, W., Pansini, S., Pauletto, D., Ramirez Arevalo, F., Sampaio, A.F., Sandoval, E.H.V., Valenzuela Gamarra, L., Levesley, A., Pickavance, G., Melgaço, K., Ter Steege, H., Henkel, T.W., Helal, N., Marimon, B.S., Marimon-Junior, B.H., Huth, A., Groeneveld, J., Sabatier, D., Coelho, L.S., Filho, D.A.L., Salomão, R.P., Amaral, I.L., Matos, F.D.A., Castilho, C.V., Phillips, O.L., Guevara, J.E., Carim, M.J.V., Cárdenas López, D., Magnusson, W.E., Wittmann, F., Irume, M.V., Martins, M.P., Guimarães, J.R.D.S., Molino, J.-F., Bánki, O.S., Piedade, M.T.F., Pitman, N.C.A., Mendoza, A.M., Ramos, J.F., Luize, B.G., Moraes de Leão Novo, E.M., Núñez Vargas, P., Silva, T.S.F., Venticinque, E.M., Manzatto, A.G., Reis, N.F.C., Terborgh, J., Casula, K.R., Honorio Coronado, E.N., Montero, J.C., Feldpausch, T.R., Duque, A., Costa, F.R.C., Arboleda, N.C., Schöngart, J., Killeen, T.J., Vasquez, R., Mostacedo, B., Demarchi, L.O., Assis, R.L., Baraloto, C., Engel, J., Petronelli, P., Castellanos, H., de Medeiros, M.B., Quaresma, A., Simon, M.F., Andrade, A., Camargo, J.L., Laurance, S.G.W., Laurance, W.F., Rincón, L.M., Schietti, J., Sousa, T.R., de Sousa Farias, E., Lopes, M.A., Magalhães, J.L.L., Mendonça Nascimento, H.E., Lima de Queiroz, H., Aymard C, G.A., Brienen, R., Revilla, J.D.C., Vieira, I.C.G., Cintra, B.B.L., Stevenson, P.R., Feitosa, Y.O., Duivenvoorden, J.F., Mogollón, H.F., Araujo-Murakami, A., Ferreira, L.V., Lozada, J.R., Comiskey, J.A., de Toledo, J.J., Damasco, G., Dávila, N., Draper, F., García-Villacorta, R., Lopes, A., Vicentini, A., Alonso, A., Dallmeier, F., Gomes, V.H.F., Lloyd, J., Neill, D., de Aguiar, D.P.P., Arroyo, L., Carvalho, F.A., de Souza, F.C., do Amaral, D.D., Feeley, K.J., Gribel, R., Pansonato, M.P., Barlow, J., Berenguer, E., Ferreira, J., Fine, P.V.A., Guedes, M.C., Jimenez, E.M., Licona, J.C., Peñuela Mora, M.C., Villa, B., Cerón, C., Maas, P., Silveira, M., Stropp, J., Thomas, R., Baker, T.R., Daly, D., Dexter, K.G., Huamantupa-Chuquimaco, I., Milliken, W., Pennington, T., Ríos Paredes, M., Fuentes, A., Klitgaard, B., Pena, J.L.M., Peres, C.A., Silman, M.R., Tello, J.S., Chave, J., Cornejo Valverde, F., Di Fiore, A., Hilário, R.R., Phillips, J.F., Rivas-Torres, G., van Andel, T.R., von Hildebrand, P., Noronha, J.C., Barbosa, E.M., Barbosa, F.R., de Matos Bonates, L.C., Carpanedo, R.S., Dávila Doza, H.P., Fonty, É., GómeZárate Z, R., Gonzales, T., Gallardo Gonzales, G.P., Hoffman, B., Junqueira, A.B., Malhi, Y., Miranda, I.P.A., Pinto, L.F.M., Prieto, A., Rodrigues, D.J., Rudas, A., Ruschel, A.R., Silva, N., Vela, C.I.A., Vos, V.A., Zent, E.L., Zent, S., Weiss Albuquerque, B., Cano, A., Carrero Márquez, Y.A., Correa, D.F., Costa, J.B.P., Flores, B.M., Galbraith, D., Holmgren, M., Kalamandeen, M., Nascimento, M.T., Oliveira, A.A., Ramirez-Angulo, H., Rocha, M., Scudeller, V.V., Sierra, R., Tirado, M., Umaña Medina, M.N., van der Heijden, G., Vilanova Torre, E., Vriesendorp, C., Wang, O., Young, K.R., Ahuite Reategui, M.A., Baider, C., Balslev, H., Cárdenas, S., Casas, L.F., Farfan-Rios, W., Ferreira, C., Linares-Palomino, R., Mendoza, C., Mesones, I., Torres-Lezama, A., Giraldo, L.E.U., Villarroel, D., Zagt, R., Alexiades, M.N., de Oliveira, E.A., Garcia-Cabrera, K., Hernandez, L., Palacios Cuenca, W., Pansini, S., Pauletto, D., Ramirez Arevalo, F., Sampaio, A.F., Sandoval, E.H.V., Valenzuela Gamarra, L., Levesley, A., Pickavance, G., and Melgaço, K.
Abstract: Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such “monodominant” forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors.
Published: 2019

19. Compositional response of Amazon forests to climate change

Author: Esquivel-Muelbert, A., Baker, T.R., Dexter, K.G., Lewis, S.L., Brienen, R.J.W., Feldpausch, T.R., Lloyd, J., Monteagudo-Mendoza, A., Arroyo, L., Álvarez-Dávila, E., Higuchi, N., Marimon, B.S., Marimon-Junior, B.H., Silveira, M., Vilanova, E., Gloor, E., Malhi, Y., Chave, J., Barlow, J., Bonal, D., Davila Cardozo, N., Erwin, T., Fauset, S., Hérault, B., Laurance, S., Poorter, L., Qie, L., Stahl, C., Sullivan, M.J.P., ter Steege, H., Vos, V.A., Zuidema, P.A., Almeida, E., Almeida de Oliveira, E., Andrade, A., Vieira, S.A., Aragão, L., Araujo-Murakami, A., Arets, E., Aymard C, G.A., Baraloto, C., Camargo, P.B., Barroso, J.G., Bongers, F., Boot, R., Camargo, J.L., Castro, W., Chama Moscoso, V., Comiskey, J., Cornejo Valverde, F., Lola da Costa, A.C., del Aguila Pasquel, J., Di Fiore, A., Fernanda Duque, L., Elias, F., Engel, J., Flores Llampazo, G., Galbraith, D., Herrera Fernández, R., Honorio Coronado, E., Hubau, W., Jimenez-Rojas, E., Lima, A.J.N., Umetsu, R.K., Laurance, W., Lopez-Gonzalez, G., Lovejoy, T., Aurelio Melo Cruz, O., Morandi, P.S., Neill, D., Núñez Vargas, P., Pallqui Camacho, N.C., Parada Gutierrez, A., Pardo, G., Peacock, J., Peña-Claros, M., Peñuela-Mora, M.C., Petronelli, P., Pickavance, G.C., Pitman, N., Prieto, A., Quesada, C., Ramírez-Angulo, H., Réjou-Méchain, M., Restrepo Correa, Z., Roopsind, A., Rudas, A., Salomão, R., Silva, N., Silva Espejo, J., Singh, J., Stropp, J., Terborgh, J., Thomas, R., Toledo, M., Torres-Lezama, A., Valenzuela Gamarra, L., van de Meer, P.J., van der Heijden, G., van der Hout, P., Vasquez Martinez, R., Vela, C., Vieira, I.C.G., Phillips, O.L., Esquivel-Muelbert, A., Baker, T.R., Dexter, K.G., Lewis, S.L., Brienen, R.J.W., Feldpausch, T.R., Lloyd, J., Monteagudo-Mendoza, A., Arroyo, L., Álvarez-Dávila, E., Higuchi, N., Marimon, B.S., Marimon-Junior, B.H., Silveira, M., Vilanova, E., Gloor, E., Malhi, Y., Chave, J., Barlow, J., Bonal, D., Davila Cardozo, N., Erwin, T., Fauset, S., Hérault, B., Laurance, S., Poorter, L., Qie, L., Stahl, C., Sullivan, M.J.P., ter Steege, H., Vos, V.A., Zuidema, P.A., Almeida, E., Almeida de Oliveira, E., Andrade, A., Vieira, S.A., Aragão, L., Araujo-Murakami, A., Arets, E., Aymard C, G.A., Baraloto, C., Camargo, P.B., Barroso, J.G., Bongers, F., Boot, R., Camargo, J.L., Castro, W., Chama Moscoso, V., Comiskey, J., Cornejo Valverde, F., Lola da Costa, A.C., del Aguila Pasquel, J., Di Fiore, A., Fernanda Duque, L., Elias, F., Engel, J., Flores Llampazo, G., Galbraith, D., Herrera Fernández, R., Honorio Coronado, E., Hubau, W., Jimenez-Rojas, E., Lima, A.J.N., Umetsu, R.K., Laurance, W., Lopez-Gonzalez, G., Lovejoy, T., Aurelio Melo Cruz, O., Morandi, P.S., Neill, D., Núñez Vargas, P., Pallqui Camacho, N.C., Parada Gutierrez, A., Pardo, G., Peacock, J., Peña-Claros, M., Peñuela-Mora, M.C., Petronelli, P., Pickavance, G.C., Pitman, N., Prieto, A., Quesada, C., Ramírez-Angulo, H., Réjou-Méchain, M., Restrepo Correa, Z., Roopsind, A., Rudas, A., Salomão, R., Silva, N., Silva Espejo, J., Singh, J., Stropp, J., Terborgh, J., Thomas, R., Toledo, M., Torres-Lezama, A., Valenzuela Gamarra, L., van de Meer, P.J., van der Heijden, G., van der Hout, P., Vasquez Martinez, R., Vela, C., Vieira, I.C.G., and Phillips, O.L.
Abstract: Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO 2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO 2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.
Published: 2019

20. sPlot:a new tool for global vegetation analyses

Author: Bruelheide, H. (Helge), Dengler, J. (Juergen), Jimenez-Alfaro, B. (Borja), Purschke, O. (Oliver), Hennekens, S. M. (Stephan M.), Chytry, M. (Milan), Pillar, V. D. (Valerio D.), Jansen, F. (Florian), Kattge, J. (Jens), Sandel, B. (Brody), Aubin, I. (Isabelle), Biurrun, I. (Idoia), Field, R. (Richard), Haider, S. (Sylvia), Jandt, U. (Ute), Lenoir, J. (Jonathan), Peet, R. K. (Robert K.), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Schmidt, M. (Marco), Schrodt, F. (Franziska), Winter, M. (Marten), Acic, S. (Svetlana), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Ambarli, D. (Didem), Angelini, P. (Pierangela), Apostolova, I. (Iva), Khan, M. A. (Mohammed A. S. Arfin), Arnst, E. (Elise), Attorre, F. (Fabio), Baraloto, C. (Christopher), Beckmann, M. (Michael), Berg, C. (Christian), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Bjorkman, A. D. (Anne D.), Bondareva, V. (Viktoria), Borchardt, P. (Peter), Botta-Dukat, Z. (Zoltan), Boyle, B. (Brad), Breen, A. (Amy), Brisse, H. (Henry), Byun, C. (Chaeho), Cabido, M. R. (Marcelo R.), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Curran, M. (Michael), Custerevska, R. (Renata), Stevanovic, Z. D. (Zora Dajic), De Bie, E. (Els), de Ruffray, P. (Patrice), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dressler, S. (Stefan), Ejrnaes, R. (Rasmus), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fagundez, J. (Jaime), Finckh, M. (Manfred), Font, X. (Xavier), Forey, E. (Estelle), Fotiadis, G. (Georgios), Garcia-Mijangos, I. (Itziar), de Gasper, A. L. (Andre Luis), Golub, V. (Valentin), Gutierrez, A. G. (Alvaro G.), Hatim, M. Z. (Mohamed Z.), He, T. (Tianhua), Higuchi, P. (Pedro), Holubova, D. (Dana), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Indreica, A. (Adrian), Gursoy, D. I. (Deniz Isik), Jansen, S. (Steven), Janssen, J. (John), Jedrzejek, B. (Birgit), Jirousek, M. (Martin), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Knollova, I. (Ilona), Kolomiychuk, V. (Vitaliy), Korolyuk, A. (Andrey), Kozhevnikova, M. (Maria), Kozub, L. (Lukasz), Krstonosic, D. (Daniel), Kuehl, H. (Hjalmar), Kuehn, I. (Ingolf), Kuzemko, A. (Anna), Kuzmic, F. (Filip), Landucci, F. (Flavia), Lee, M. T. (Michael T.), Levesley, A. (Aurora), Li, C.-F. (Ching-Feng), Liu, H. (Hongyan), Lopez-Gonzalez, G. (Gabriela), Lysenko, T. (Tatiana), Macanovic, A. (Armin), Mahdavi, P. (Parastoo), Manning, P. (Peter), Marceno, C. (Corrado), Martynenko, V. (Vassiliy), Mencuccini, M. (Maurizio), Minden, V. (Vanessa), Moeslund, J. E. (Jesper Erenskjold), Moretti, M. (Marco), Mueller, J. V. (Jonas V.), Munzinger, J. (Jerome), Niinemets, U. (Ulo), Nobis, M. (Marcin), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Ozinga, W. A. (Wim A.), Pauchard, A. (Anibal), Pedashenko, H. (Hristo), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rodwell, J. (John), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schaminee, J. H. (Joop H. J.), Schmiedel, U. (Ute), Sibik, J. (Jozef), Silc, U. (Urban), Skvorc, Z. (Zeljko), Smyth, A. (Anita), Sop, T. (Tenekwetche), Sopotlieva, D. (Desislava), Sparrow, B. (Ben), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Swacha, G. (Grzegorz), Tang, Z. (Zhiyao), Tsiripidis, I. (Ioannis), Turtureanu, P. D. (Pavel Dan), Ugurlu, E. (Emin), Uogintas, D. (Domas), Valachovic, M. (Milan), Vanselow, K. A. (Kim Andre), Vashenyak, Y. (Yulia), Vassilev, K. (Kiril), Velez-Martin, E. (Eduardo), Venanzoni, R. (Roberto), Vibrans, A. C. (Alexander Christian), Violle, C. (Cyrille), Virtanen, R. (Risto), von Wehrden, H. (Henrik), Wagner, V. (Viktoria), Walker, D. A. (Donald A.), Wana, D. (Desalegn), Weiher, E. (Evan), Wesche, K. (Karsten), Whitfeld, T. (Timothy), Willner, W. (Wolfgang), Wiser, S. (Susan), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zizka, G. (Georg), Zverev, A. (Andrei), Bruelheide, H. (Helge), Dengler, J. (Juergen), Jimenez-Alfaro, B. (Borja), Purschke, O. (Oliver), Hennekens, S. M. (Stephan M.), Chytry, M. (Milan), Pillar, V. D. (Valerio D.), Jansen, F. (Florian), Kattge, J. (Jens), Sandel, B. (Brody), Aubin, I. (Isabelle), Biurrun, I. (Idoia), Field, R. (Richard), Haider, S. (Sylvia), Jandt, U. (Ute), Lenoir, J. (Jonathan), Peet, R. K. (Robert K.), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Schmidt, M. (Marco), Schrodt, F. (Franziska), Winter, M. (Marten), Acic, S. (Svetlana), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Ambarli, D. (Didem), Angelini, P. (Pierangela), Apostolova, I. (Iva), Khan, M. A. (Mohammed A. S. Arfin), Arnst, E. (Elise), Attorre, F. (Fabio), Baraloto, C. (Christopher), Beckmann, M. (Michael), Berg, C. (Christian), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Bjorkman, A. D. (Anne D.), Bondareva, V. (Viktoria), Borchardt, P. (Peter), Botta-Dukat, Z. (Zoltan), Boyle, B. (Brad), Breen, A. (Amy), Brisse, H. (Henry), Byun, C. (Chaeho), Cabido, M. R. (Marcelo R.), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Curran, M. (Michael), Custerevska, R. (Renata), Stevanovic, Z. D. (Zora Dajic), De Bie, E. (Els), de Ruffray, P. (Patrice), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dressler, S. (Stefan), Ejrnaes, R. (Rasmus), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fagundez, J. (Jaime), Finckh, M. (Manfred), Font, X. (Xavier), Forey, E. (Estelle), Fotiadis, G. (Georgios), Garcia-Mijangos, I. (Itziar), de Gasper, A. L. (Andre Luis), Golub, V. (Valentin), Gutierrez, A. G. (Alvaro G.), Hatim, M. Z. (Mohamed Z.), He, T. (Tianhua), Higuchi, P. (Pedro), Holubova, D. (Dana), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Indreica, A. (Adrian), Gursoy, D. I. (Deniz Isik), Jansen, S. (Steven), Janssen, J. (John), Jedrzejek, B. (Birgit), Jirousek, M. (Martin), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Knollova, I. (Ilona), Kolomiychuk, V. (Vitaliy), Korolyuk, A. (Andrey), Kozhevnikova, M. (Maria), Kozub, L. (Lukasz), Krstonosic, D. (Daniel), Kuehl, H. (Hjalmar), Kuehn, I. (Ingolf), Kuzemko, A. (Anna), Kuzmic, F. (Filip), Landucci, F. (Flavia), Lee, M. T. (Michael T.), Levesley, A. (Aurora), Li, C.-F. (Ching-Feng), Liu, H. (Hongyan), Lopez-Gonzalez, G. (Gabriela), Lysenko, T. (Tatiana), Macanovic, A. (Armin), Mahdavi, P. (Parastoo), Manning, P. (Peter), Marceno, C. (Corrado), Martynenko, V. (Vassiliy), Mencuccini, M. (Maurizio), Minden, V. (Vanessa), Moeslund, J. E. (Jesper Erenskjold), Moretti, M. (Marco), Mueller, J. V. (Jonas V.), Munzinger, J. (Jerome), Niinemets, U. (Ulo), Nobis, M. (Marcin), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Ozinga, W. A. (Wim A.), Pauchard, A. (Anibal), Pedashenko, H. (Hristo), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rodwell, J. (John), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schaminee, J. H. (Joop H. J.), Schmiedel, U. (Ute), Sibik, J. (Jozef), Silc, U. (Urban), Skvorc, Z. (Zeljko), Smyth, A. (Anita), Sop, T. (Tenekwetche), Sopotlieva, D. (Desislava), Sparrow, B. (Ben), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Swacha, G. (Grzegorz), Tang, Z. (Zhiyao), Tsiripidis, I. (Ioannis), Turtureanu, P. D. (Pavel Dan), Ugurlu, E. (Emin), Uogintas, D. (Domas), Valachovic, M. (Milan), Vanselow, K. A. (Kim Andre), Vashenyak, Y. (Yulia), Vassilev, K. (Kiril), Velez-Martin, E. (Eduardo), Venanzoni, R. (Roberto), Vibrans, A. C. (Alexander Christian), Violle, C. (Cyrille), Virtanen, R. (Risto), von Wehrden, H. (Henrik), Wagner, V. (Viktoria), Walker, D. A. (Donald A.), Wana, D. (Desalegn), Weiher, E. (Evan), Wesche, K. (Karsten), Whitfeld, T. (Timothy), Willner, W. (Wolfgang), Wiser, S. (Susan), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zizka, G. (Georg), and Zverev, A. (Andrei)
Abstract: Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.
Published: 2019

21. sPlot – a new tool for global vegetation analyses

Author: Bruelheide, H., Dengler, J., Jiménez‐Alfaro, B., Purschke, O., Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R.K., Peyre, G., Sabatini, F.M., Schmidt, M., Schrodt, F., Winter, M., Aćić, S., Agrillo, E., Alvarez, M., Ambarlı, D., Angelini, P., Apostolova, I., Khan, M.A.S.A., Arnst, E., Attorre, F., Baraloto, C., Beckmann, Michael, Kühn, Ingolf, Virtanen, Risto, Berg, C., et al., Bruelheide, H., Dengler, J., Jiménez‐Alfaro, B., Purschke, O., Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R.K., Peyre, G., Sabatini, F.M., Schmidt, M., Schrodt, F., Winter, M., Aćić, S., Agrillo, E., Alvarez, M., Ambarlı, D., Angelini, P., Apostolova, I., Khan, M.A.S.A., Arnst, E., Attorre, F., Baraloto, C., Beckmann, Michael, Kühn, Ingolf, Virtanen, Risto, and Berg, C., et al.
Abstract: QuestionsVegetation‐plot records provide information on presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. LocationsPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected between 1885 and 2015. MethodsWe complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g. biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. ResultsWe present the first maps of global patterns of community richness and community‐weighted means of key traits. ConclusionsThe availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.
Published: 2019

22. Global trait:environment relationships of plant communities

Author: Bruelheide, H. (Helge), Dengler, J. (Juergen), Purschke, O. (Oliver), Lenoir, J. (Jonathan), Jimenez-Alfaro, B. (Borja), Hennekens, S. M. (Stephan M.), Botta-Dukat, Z. (Zoltan), Chytry, M. (Milan), Field, R. (Richard), Jansen, F. (Florian), Kattge, J. (Jens), Pillar, V. D. (Valerio D.), Schrodt, F. (Franziska), Mahecha, M. D. (Miguel D.), Peet, R. K. (Robert K.), Sandel, B. (Brody), van Bodegom, P. (Peter), Altman, J. (Jan), Alvarez-Davila, E. (Esteban), Khan, M. A. (Mohammed A. S. Arfin), Attorre, F. (Fabio), Aubin, I. (Isabelle), Baraloto, C. (Christopher), Barroso, J. G. (Jorcely G.), Bauters, M. (Marijn), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Blonder, B. (Benjamin), Carni, A. (Andraz), Cayuela, L. (Luis), Cerny, T. (Tomas), Cornelissen, J. H. (J. Hans C.), Craven, D. (Dylan), Dainese, M. (Matteo), Derroire, G. (Geraldine), De Sanctis, M. (Michele), Diaz, S. (Sandra), Dolezal, J. (Jiri), Farfan-Rios, W. (William), Feldpausch, T. R. (Ted R.), Fenton, N. J. (Nicole J.), Garnier, E. (Eric), Guerin, G. R. (Greg R.), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hattab, T. (Tarek), Henry, G. (Greg), Herault, B. (Bruno), Higuchi, P. (Pedro), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Karger, D. N. (Dirk N.), Kessler, M. (Michael), Kleyer, M. (Michael), Knollova, I. (Ilona), Korolyuk, A. Y. (Andrey Y.), Kuehn, I. (Ingolf), Laughlin, D. C. (Daniel C.), Lens, F. (Frederic), Loos, J. (Jacqueline), Louault, F. (Frederique), Lyubenova, M. I. (Mariyana, I), Malhi, Y. (Yadvinder), Marceno, C. (Corrado), Mencuccini, M. (Maurizio), Mueller, J. V. (Jonas, V), Munzinger, J. (Jerome), Myers-Smith, I. H. (Isla H.), Neill, D. A. (David A.), Niinemets, U. (Ulo), Orwin, K. H. (Kate H.), Ozinga, W. A. (Wim A.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Partel, M. (Meelis), Reich, P. B. (Peter B.), Roemermann, C. (Christine), Rodrigues, A. V. (Arthur, V), Sabatini, F. M. (Francesco Maria), Sardans, J. (Jordi), Schmidt, M. (Marco), Seidler, G. (Gunnar), Silva Espejo, J. E. (Javier Eduardo), Silveira, M. (Marcos), Smyth, A. (Anita), Sporbert, M. (Maria), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Thomas, R. (Raquel), Tsiripidis, I. (Ioannis), Vassilev, K. (Kiril), Violle, C. (Cyrille), Virtanen, R. (Risto), Weiher, E. (Evan), Welk, E. (Erik), Wesche, K. (Karsten), Winter, M. (Marten), Wirth, C. (Christian), Jandt, U. (Ute), Bruelheide, H. (Helge), Dengler, J. (Juergen), Purschke, O. (Oliver), Lenoir, J. (Jonathan), Jimenez-Alfaro, B. (Borja), Hennekens, S. M. (Stephan M.), Botta-Dukat, Z. (Zoltan), Chytry, M. (Milan), Field, R. (Richard), Jansen, F. (Florian), Kattge, J. (Jens), Pillar, V. D. (Valerio D.), Schrodt, F. (Franziska), Mahecha, M. D. (Miguel D.), Peet, R. K. (Robert K.), Sandel, B. (Brody), van Bodegom, P. (Peter), Altman, J. (Jan), Alvarez-Davila, E. (Esteban), Khan, M. A. (Mohammed A. S. Arfin), Attorre, F. (Fabio), Aubin, I. (Isabelle), Baraloto, C. (Christopher), Barroso, J. G. (Jorcely G.), Bauters, M. (Marijn), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Blonder, B. (Benjamin), Carni, A. (Andraz), Cayuela, L. (Luis), Cerny, T. (Tomas), Cornelissen, J. H. (J. Hans C.), Craven, D. (Dylan), Dainese, M. (Matteo), Derroire, G. (Geraldine), De Sanctis, M. (Michele), Diaz, S. (Sandra), Dolezal, J. (Jiri), Farfan-Rios, W. (William), Feldpausch, T. R. (Ted R.), Fenton, N. J. (Nicole J.), Garnier, E. (Eric), Guerin, G. R. (Greg R.), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hattab, T. (Tarek), Henry, G. (Greg), Herault, B. (Bruno), Higuchi, P. (Pedro), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Karger, D. N. (Dirk N.), Kessler, M. (Michael), Kleyer, M. (Michael), Knollova, I. (Ilona), Korolyuk, A. Y. (Andrey Y.), Kuehn, I. (Ingolf), Laughlin, D. C. (Daniel C.), Lens, F. (Frederic), Loos, J. (Jacqueline), Louault, F. (Frederique), Lyubenova, M. I. (Mariyana, I), Malhi, Y. (Yadvinder), Marceno, C. (Corrado), Mencuccini, M. (Maurizio), Mueller, J. V. (Jonas, V), Munzinger, J. (Jerome), Myers-Smith, I. H. (Isla H.), Neill, D. A. (David A.), Niinemets, U. (Ulo), Orwin, K. H. (Kate H.), Ozinga, W. A. (Wim A.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Partel, M. (Meelis), Reich, P. B. (Peter B.), Roemermann, C. (Christine), Rodrigues, A. V. (Arthur, V), Sabatini, F. M. (Francesco Maria), Sardans, J. (Jordi), Schmidt, M. (Marco), Seidler, G. (Gunnar), Silva Espejo, J. E. (Javier Eduardo), Silveira, M. (Marcos), Smyth, A. (Anita), Sporbert, M. (Maria), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Thomas, R. (Raquel), Tsiripidis, I. (Ioannis), Vassilev, K. (Kiril), Violle, C. (Cyrille), Virtanen, R. (Risto), Weiher, E. (Evan), Welk, E. (Erik), Wesche, K. (Karsten), Winter, M. (Marten), Wirth, C. (Christian), and Jandt, U. (Ute)
Abstract: Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
Published: 2018

23. Global trait–environment relationships of plant communities

Author: Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez‐Alfaro, B., Hennekens, S.M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V.D., Schrodt, F., Mahecha, M.D., Peet, R.K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Khan, M.A.S.A., Attorre, F., Aubin, I., Baraloto, C., Barroso, J.G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J.H.C., Craven, Dylan, Dainese, M., Derroire, G., De Sanctis, M., Díaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T.R., Fenton, N.J., Garnier, E., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Kącki, Z., Karger, D.N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A.Y., Kühn, Ingolf, Laughlin, D.C., Lens, F., Loos, J., Louault, F., Lyubenova, M.I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J.V., Munzinger, J., Myers-Smith, I.H., Neill, D.A., Niinemets, Ü., Orwin, K.H., Ozinga, W.A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O.L., Pärtel, M., Reich, P.B., Römermann, C., Rodrigues, A.V., Sabatini, F.M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J.E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, Risto, Weiher, E., Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez‐Alfaro, B., Hennekens, S.M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V.D., Schrodt, F., Mahecha, M.D., Peet, R.K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Khan, M.A.S.A., Attorre, F., Aubin, I., Baraloto, C., Barroso, J.G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J.H.C., Craven, Dylan, Dainese, M., Derroire, G., De Sanctis, M., Díaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T.R., Fenton, N.J., Garnier, E., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Kącki, Z., Karger, D.N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A.Y., Kühn, Ingolf, Laughlin, D.C., Lens, F., Loos, J., Louault, F., Lyubenova, M.I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J.V., Munzinger, J., Myers-Smith, I.H., Neill, D.A., Niinemets, Ü., Orwin, K.H., Ozinga, W.A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O.L., Pärtel, M., Reich, P.B., Römermann, C., Rodrigues, A.V., Sabatini, F.M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J.E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, Risto, and Weiher, E.
Abstract: Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
Published: 2018

24. Maximising Synergy among Tropical Plant Systematists, Ecologists, and Evolutionary Biologists

Author: Baker, TR, Pennington, RT, Dexter, KG, Fine, PVA, Fortune-Hopkins, H, Honorio, EN, Huamantupa-Chuquimaco, I, Klitgård, BB, Lewis, GP, De Lima, HC, Ashton, P, Baraloto, C, Davies, S, Donoghue, MJ, Kaye, M, Kress, WJ, Lehmann, CER, Monteagudo, A, Phillips, OL, and Vasquez, R
Subjects: Ecology, Evolution, Behavior and Systematics
Abstract: Closer collaboration among ecologists, systematists, and evolutionary biologists working in tropical forests, centred on studies within long-term permanent plots, would be highly beneficial for their respective fields. With a key unifying theme of the importance of vouchered collection and precise identification of species, especially rare ones, we identify four priority areas where improving links between these communities could achieve significant progress in biodiversity and conservation science: (i) increasing the pace of species discovery; (ii) documenting species turnover across space and time; (iii) improving models of ecosystem change; and (iv) understanding the evolutionary assembly of communities and biomes.
Published: 2017
Full Text: View/download PDF

25. Amazon forest response to repeated droughts

Author: Feldpausch, T. R., Phillips, O. L., Brienen, R. J. W., Gloor, E., Lloyd, J., Lopez-Gonzalez, G., Monteagudo-Mendoza, A., Malhi, Y., Alarcón, A., Dávila, E. Álvarez, Alvarez-Loayza, P., Andrade, A., Aragao, L. E. O. C., Arroyo, L., Aymard C, G. A., Baker, T. R., Baraloto, C., Barroso, J., Bonal, D., Castro, W., Chama, V., Chave, J., Domingues, T. F., Fauset, S., Groot, N., Honorio Coronado, E., Laurance, S., Laurance, W. F., Lewis, S. L., Licona, J. C., Marimon, B. S., Marimon-Junior, B. H., Mendoza Bautista, C., Neill, D. A., Oliveira, E. A., Santos, C. Oliveira Dos, Pallqui Camacho, N. C., Pardo-Molina, G., Prieto, A., Quesada, C. A., Ramírez, F., Ramírez-Angulo, H., Réjou-Méchain, M., Rudas, A., Saiz, G., Salomão, R. P., Silva-Espejo, J. E., Silveira, M., Steege, H. Ter, Stropp, J., Terborgh, J., Thomas-Caesar, R., Heijden, G. M. F., Vásquez Martinez, R., Vilanova, E., Vincent Antoine Vos, Chercheur indépendant, Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), Evolution et Diversité Biologique (EDB), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Natural Environment Research Council (NERC) Urgency, Standard, and Consortium NE/I02982X/1, Niche Evolution of South American Trees NE/I028122/1, AMAZONICA NE/F005806/1, TROBIT NE/D005590/1, European Union 282664, CNPq/PELD 403725/2012-7, Gordon and Betty Moore Foundation, ERC, Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES), Brazil, 177/2012 European Research Council, Royal Society Wolfson Research Merit Award, Investissement d'Avenir grants of the ANR CEBA: ANR-10-LABX-25-01 TULIP: ANR-10-LABX-0041, CNES funds (TOSCA), Biological Dynamics of Forest Fragments project 694, and The Royal Society
Subjects: [SDV]Life Sciences [q-bio], TROPICAL FORESTS, Environmental Sciences & Ecology, precipitation, INDUCED TREE MORTALITY, LIANAS, MECHANISMS, BIOMASS, PLOTS, Meteorology & Atmospheric Sciences, 0402 Geochemistry, Geosciences, Multidisciplinary, water deficit, forest productivity, Science & Technology, CLIMATE-CHANGE, vegetation dynamics, carbon, fungi, food and beverages, Geology, RAIN-FOREST, SOILS, Physical Sciences, tree mortality, GROWTH, 0401 Atmospheric Sciences, Life Sciences & Biomedicine, Environmental Sciences
Abstract: The Amazon Basin has experienced more variable climate over the last decade, with a severe and widespread drought in 2005 causing large basin-wide losses of biomass. A drought of similar climatological magnitude occurred again in 2010; however, there has been no basin-wide ground-based evaluation of effects on vegetation. We examine to what extent the 2010 drought affected forest dynamics using ground-based observations of mortality and growth from an extensive forest plot network. We find that during the 2010 drought interval, forests did not gain biomass (net change: −0.43 Mg ha−1, confidence interval (CI): −1.11, 0.19, n = 97), regardless of whether forests experienced precipitation deficit anomalies. This contrasted with a long-term biomass sink during the baseline pre-2010 drought period (1998 to pre-2010) of 1.33 Mg ha−1 yr−1 (CI: 0.90, 1.74, p
Published: 2016
Full Text: View/download PDF

26. Estimating the global conservation status of over 15,000 Amazonian tree species

Author: Steege, HT, Pitman, NCA, Killeen, TJ, Laurance, WF, Peres, CA, Guevara, JE, Salomão, RP, Castilho, CV, Amaral, IL, Dionízia de Almeida Matos, F, de Souza Coelho, L, Magnusson, WE, Phillips, OLB, de Andrade Lima Filho, D, de Jesus Veiga Carim, M, Victória Irume, M, Martins, MP, Molino, J-F, Sabatier, D, Wittmann, F, Lopez, DC, da Silva Guimarães, JR, Monteagudo Mendoza, A, Vargas, PN, Manzatto, AG, Farias Costa Reis, N, Terborgh, J, Casula, KR, Montero, JC, Feldpausch, TR, Honorio Coronado, EN, Duque Montoya, AJ, Zartman, ZE, Mostacedo, B, Vasquez, R, Assis, RL, Brilhante Medeiros, M, Fragomeni Simon, M, Andrade, A, Camargo, JL, Laurance, SGW, Mendonça Nascimento, HE, Marimon, BS, Marimon Jr, B-H, Costa F, Targhetta, N, Guimarães Vieira, IC, Brienen, R, Castellanos, H, Duivenvoorden, JF, Mogollón, HF, Fernandez Piedade, MT, Aymard, GA, Comiskey, JA, Damasco, G, Dávila, N, García-Villacorta, R, Stevenson Diaz, PR, Vincentini, A, Emilio, T, Levis, C, Schietti, J, Souza, P, Alonso, A, Dallmeier, F, Valle Ferreira, L, Neill, D, Araujo-Murakami, A, Arroyo, L, Antunes Carvalho, F, Coelho Souza, F, Dantas do Amaral, D, Gribel, R, Garcia Luize, B, Petrati Pansonato, M, Venticinque, E, Fine, P, Toldeo, M, Baraloto, C, Cerón, C, Engel, J, Henkel, TW, Jimenez, EM, Maas, P, Peñuela Mora, MC, Petronelli, P, Cardenas Revilla, JD, Silveira, M, Stropp, J, Thomas-Caesar, R, Baker, TR, Daly, D, Ríos Paredes, M, Ferreira da Silva, N, Fuentes, A, Møller Jørgensen, P, Schöngart, J, Silman, MR, Castaño Arboleda, N, Ladvocat Cintra, B, Cornejo Valverde, F, Di Fiore, A, Fernando Phillips, J, van Andel, TR, von Hildebrand, P, Marques Barbosa, E, de Matos Bonates, LC, de Castro, D, de Sousa Farias, E, Gonzales, T, Guillaumet, J-L, Hoffman, B, Malhi, Y, de Andrade Miranda, IP, Prieto, M, Rudas, A, Ruschell, AR, Silva, N, Vela, CIA, Vos, VA, Zent, EL, Zent, S, Cano, A, Trindade Nascimento, M, Oliveira, AA, Ramirez-Angulo, H, Ferreira Ramos, J, Sierra, R, Tirado, M, Umaña Medina, MN, van der Heijden, G, Vilanova Torre, E, Vriesendorp, C, Wang, O, Young, KR, Baider, C, Balslev, H, de Castro, N, Farfan-Rios, W, Ferreira, C, Mendoza, C, Mesonos, I, Torres-Lezama, A, Urrego Giraldo, LE, Villarroel, D, Zagt, R, Alexiades, MN, Garcia-Cabrera, K, Hernandez, L, Huamantupa-Chuquimaco, I, Milliken, W, Palacios Cuenca, W, Pansini, S, Pauletto, D, Ramirez Arevalo, F, Sampaio, AF, and Valderrama Sandoval, EH
Abstract: Estimates of extinction risk for Amazonian plant and animal species are rare, and not often incorporated into land-use policy and conservation planning. Here we overlay spatial distribution models with historical and projected deforestation to show that at least 40% and up to 64% of all Amazonian tree species are likely to qualify as globally threatened under IUCN Red List criteria. If confirmed, these results would increase the number of threatened plant species on Earth by 22%. We further show that the trends observed in Amazonia apply to trees throughout the tropics, and predict that most of the world's >40,000 tropical tree species currently qualify as globally threatened. A gap analysis suggests that existing Amazonian protected areas and indigenous territories will protect viable populations of most threatened species if those areas suffer no further degradation, highlighting the key roles that protected areas, indigenous peoples, and improved governance can play in preventing large-scale extinctions in the tropics in this century.
Published: 2015

27. Intraspecific leaf trait variability along a boreal-to-tropical community diversity gradient

Author: Bastias, CC, Fortunel, C, Valladares, F, Baraloto, C, Benavides, R, Cornwell, W, Markesteijn, L, De Oliveira, AA, Sansevero, JBB, Vaz, MC, Kraft, NJB, Bastias, CC, Fortunel, C, Valladares, F, Baraloto, C, Benavides, R, Cornwell, W, Markesteijn, L, De Oliveira, AA, Sansevero, JBB, Vaz, MC, and Kraft, NJB
Abstract: © This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Disentangling the mechanisms that shape community assembly across diversity gradients is a central matter in ecology. While many studies have explored community assembly through species average trait values, there is a growing understanding that intraspecific trait variation (ITV) can also play a critical role in species coexistence. Classic biodiversity theory hypothesizes that higher diversity at species-rich sites can arise from narrower niches relative to species-poor sites, which would be reflected in reduced ITV as species richness increases. To explore how ITV in woody plant communities changes with species richness, we compiled leaf trait data (leaf size and specific leaf area) in a total of 521 woody plant species from 21 forest communities that differed dramatically in species richness, ranging from boreal to tropical rainforests. At each forest, we assessed ITV as an estimate of species niche breadth and we quantified the degree of trait overlap among co-occurring species as a measure of species functional similarity. We found ITV was relatively invariant across the species richness gradient. In addition, we found that species functional similarity increased with diversity. Contrary to the expectation from classic biodiversity theory, our results rather suggest that neutral processes or equalizing mechanisms can be acting as potential drivers shaping community assembly in hyperdiverse forests.
Published: 2017

28. Diversity and carbon storage across the tropical forest biome

Author: Sullivan, MJP, Talbot, J, Lewis, SL, Phillips, OL, Qie, L, Begne, SK, Chave, J, Cuni-Sanchez, A, Hubau, W, Lopez-Gonzalez, G, Miles, L, Monteagudo-Mendoza, A, Sonké, B, Sunderland, T, Ter Steege, H, White, LJT, Affum-Baffoe, K, Aiba, SI, De Almeida, EC, De Oliveira, EA, Alvarez-Loayza, P, Dávila, EÁ, Andrade, A, Aragão, LEOC, Ashton, P, Aymard, GA, Baker, TR, Balinga, M, Banin, LF, Baraloto, C, Bastin, JF, Berry, N, Bogaert, J, Bonal, D, Bongers, F, Brienen, R, Camargo, JLC, Cerón, C, Moscoso, VC, Chezeaux, E, Clark, CJ, Pacheco, ÁC, Comiskey, JA, Valverde, FC, Coronado, ENH, Dargie, G, Davies, SJ, De Canniere, C, Djuikouo, MN, Doucet, JL, Erwin, TL, Espejo, JS, Ewango, CEN, Fauset, S, Feldpausch, TR, Herrera, R, Gilpin, M, Gloor, E, Hall, JS, Harris, DJ, Hart, TB, Kartawinata, K, Kho, LK, Kitayama, K, Laurance, SGW, Laurance, WF, Leal, ME, Lovejoy, T, Lovett, JC, Lukasu, FM, Makana, JR, Malhi, Y, Maracahipes, L, Marimon, BS, Junior, BHM, Marshall, AR, Morandi, PS, Mukendi, JT, Mukinzi, J, Nilus, R, Vargas, PN, Camacho, NCP, Pardo, G, Peña-Claros, M, Pétronelli, P, Pickavance, GC, Poulsen, AD, Poulsen, JR, Primack, RB, Priyadi, H, Quesada, CA, Reitsma, J, Réjou-Méchain, M, Restrepo, Z, Rutishauser, E, Salim, KA, Salomão, RP, Samsoedin, I, Sheil, D, Sierra, R, Sullivan, MJP, Talbot, J, Lewis, SL, Phillips, OL, Qie, L, Begne, SK, Chave, J, Cuni-Sanchez, A, Hubau, W, Lopez-Gonzalez, G, Miles, L, Monteagudo-Mendoza, A, Sonké, B, Sunderland, T, Ter Steege, H, White, LJT, Affum-Baffoe, K, Aiba, SI, De Almeida, EC, De Oliveira, EA, Alvarez-Loayza, P, Dávila, EÁ, Andrade, A, Aragão, LEOC, Ashton, P, Aymard, GA, Baker, TR, Balinga, M, Banin, LF, Baraloto, C, Bastin, JF, Berry, N, Bogaert, J, Bonal, D, Bongers, F, Brienen, R, Camargo, JLC, Cerón, C, Moscoso, VC, Chezeaux, E, Clark, CJ, Pacheco, ÁC, Comiskey, JA, Valverde, FC, Coronado, ENH, Dargie, G, Davies, SJ, De Canniere, C, Djuikouo, MN, Doucet, JL, Erwin, TL, Espejo, JS, Ewango, CEN, Fauset, S, Feldpausch, TR, Herrera, R, Gilpin, M, Gloor, E, Hall, JS, Harris, DJ, Hart, TB, Kartawinata, K, Kho, LK, Kitayama, K, Laurance, SGW, Laurance, WF, Leal, ME, Lovejoy, T, Lovett, JC, Lukasu, FM, Makana, JR, Malhi, Y, Maracahipes, L, Marimon, BS, Junior, BHM, Marshall, AR, Morandi, PS, Mukendi, JT, Mukinzi, J, Nilus, R, Vargas, PN, Camacho, NCP, Pardo, G, Peña-Claros, M, Pétronelli, P, Pickavance, GC, Poulsen, AD, Poulsen, JR, Primack, RB, Priyadi, H, Quesada, CA, Reitsma, J, Réjou-Méchain, M, Restrepo, Z, Rutishauser, E, Salim, KA, Salomão, RP, Samsoedin, I, Sheil, D, and Sierra, R
Abstract: © The Author(s) 2017. Tropical forests are global centres of biodiversity and carbon storage. Many tropical countries aspire to protect forest to fulfil biodiversity and climate mitigation policy targets, but the conservation strategies needed to achieve these two functions depend critically on the tropical forest tree diversity-carbon storage relationship. Assessing this relationship is challenging due to the scarcity of inventories where carbon stocks in aboveground biomass and species identifications have been simultaneously and robustly quantified. Here, we compile a unique pan-Tropical dataset of 360 plots located in structurally intact old-growth closed-canopy forest, surveyed using standardised methods, allowing a multi-scale evaluation of diversity-carbon relationships in tropical forests. Diversity-carbon relationships among all plots at 1 ha scale across the tropics are absent, and within continents are either weak (Asia) or absent (Amazonia, Africa). A weak positive relationship is detectable within 1 ha plots, indicating that diversity effects in tropical forests may be scale dependent. The absence of clear diversity-carbon relationships at scales relevant to conservation planning means that carbon-centred conservation strategies will inevitably miss many high diversity ecosystems. As tropical forests can have any combination of tree diversity and carbon stocks both require explicit consideration when optimising policies to manage tropical carbon and biodiversity.
Published: 2017

29. Intraspecific leaf trait variability along a boreal-to-tropical community diversity gradient

Author: Ministerio de Economía y Competitividad (España), Comunidad de Madrid, European Commission, Bastias, Cristina C., Fortunel, C., Valladares Ros, Fernando, Baraloto, C., Benavides, Raquel, Cornwell, W., Markesteijn, L., De Oliveira, A.A., Sansevero, J.B.B., Vaz, M.C., Kraft, N.J.B., Ministerio de Economía y Competitividad (España), Comunidad de Madrid, European Commission, Bastias, Cristina C., Fortunel, C., Valladares Ros, Fernando, Baraloto, C., Benavides, Raquel, Cornwell, W., Markesteijn, L., De Oliveira, A.A., Sansevero, J.B.B., Vaz, M.C., and Kraft, N.J.B.
Abstract: Disentangling the mechanisms that shape community assembly across diversity gradients is a central matter in ecology. While many studies have explored community assembly through species average trait values, there is a growing understanding that intraspecific trait variation (ITV) can also play a critical role in species coexistence. Classic biodiversity theory hypothesizes that higher diversity at species-rich sites can arise from narrower niches relative to species-poor sites, which would be reflected in reduced ITV as species richness increases. To explore how ITV in woody plant communities changes with species richness, we compiled leaf trait data (leaf size and specific leaf area) in a total of 521 woody plant species from 21 forest communities that differed dramatically in species richness, ranging from boreal to tropical rainforests. At each forest, we assessed ITV as an estimate of species niche breadth and we quantified the degree of trait overlap among co-occurring species as a measure of species functional similarity. We found ITV was relatively invariant across the species richness gradient. In addition, we found that species functional similarity increased with diversity. Contrary to the expectation from classic biodiversity theory, our results rather suggest that neutral processes or equalizing mechanisms can be acting as potential drivers shaping community assembly in hyperdiverse forests.
Published: 2017

30. Correspondence: Rapid tree carbon stock recovery in managed Amazonian forests

Author: Rutishauser, E., Hérault, B., Baraloto, C., Blanc, L., Descroix, L., Sotta, E., Ferreira, J., Kanashiro, M., Mazzei, L., and Pena Claros, M.
Subjects: Life Science, Bosecologie en Bosbeheer, PE&RC, Forest Ecology and Forest Management
Abstract: While around 20% of the Amazonian forest has been cleared for pastures and agriculture, one fourth of the remaining forest is dedicated to wood production [1]. Most of these production forests have been or will be selectively harvested for commercial timber, but recent studies show that even soon after logging, harvested stands retain much of their tree-biomass carbon and biodiversity 2 and 3. Comparing species richness of various animal taxa among logged and unlogged forests across the tropics, Burivalova et al. [4] found that despite some variability among taxa, biodiversity loss was generally explained by logging intensity (the number of trees extracted). Here, we use a network of 79 permanent sample plots (376 ha total) located at 10 sites across the Amazon Basin [5] to assess the main drivers of time-to-recovery of post-logging tree carbon ( Table S1). Recovery time is of direct relevance to policies governing management practices (i.e., allowable volumes cut and cutting cycle lengths), and indirectly to forest-based climate change mitigation interventions
Published: 2015

31. The global spectrum of plant form and function

Author: Díaz, S, Kattge, J, Cornelissen, JHC, Wright, IJ, Lavorel, S, Dray, S, Reu, B, Kleyer, M, Wirth, C, Colin Prentice, I, Garnier, E, Bönisch, G, Westoby, M, Poorter, H, Reich, PB, Moles, AT, Dickie, J, Gillison, AN, Zanne, AE, Chave, J, Joseph Wright, S, Sheremet Ev, SN, Jactel, H, Baraloto, C, Cerabolini, B, Pierce, S, Shipley, B, Kirkup, D, Casanoves, F, Joswig, JS, Günther, A, Falczuk, V, Rüger, N, Mahecha, MD, Gorné, LD, Díaz, S, Kattge, J, Cornelissen, JHC, Wright, IJ, Lavorel, S, Dray, S, Reu, B, Kleyer, M, Wirth, C, Colin Prentice, I, Garnier, E, Bönisch, G, Westoby, M, Poorter, H, Reich, PB, Moles, AT, Dickie, J, Gillison, AN, Zanne, AE, Chave, J, Joseph Wright, S, Sheremet Ev, SN, Jactel, H, Baraloto, C, Cerabolini, B, Pierce, S, Shipley, B, Kirkup, D, Casanoves, F, Joswig, JS, Günther, A, Falczuk, V, Rüger, N, Mahecha, MD, and Gorné, LD
Abstract: Earth is home to a remarkable diversity of plant forms and life histories, yet comparatively few essential trait combinations have proved evolutionarily viable in today € s terrestrial biosphere. By analysing worldwide variation in six major traits critical to growth, survival and reproduction within the largest sample of vascular plant species ever compiled, we found that occupancy of six-dimensional trait space is strongly concentrated, indicating coordination and trade-offs. Three-quarters of trait variation is captured in a two-dimensional global spectrum of plant form and function. One major dimension within this plane reflects the size of whole plants and their parts; the other represents the leaf economics spectrum, which balances leaf construction costs against growth potential. The global plant trait spectrum provides a backdrop for elucidating constraints on evolution, for functionally qualifying species and ecosystems, and for improving models that predict future vegetation based on continuous variation in plant form and function.
Published: 2016

32. Variation in stem mortality rates determines patterns of aboveground biomass in Amazonian forests: implications for dynamic global vegetation models

Author: Johnson, M O, Galbraith, D, Gloor, E, De Deurwaerder, H, Guimberteau, M, Rammig, A, Thonicke, K, Verbeeck, H, von Randow, C, Monteagudo, A, Phillips, O L, Brienen, R J W, Feldpausch, T R, Lopez Gonzalez, G, Fauset, S, Quesada, C A, Christoffersen, B, Ciais, P, Gilvan, S, Kruijt, B, Meir, P, Moorcroft, P, Zhang, K, Alvarez, E A, Alves de Oliveira, A, Amaral, I, Andrade, A, Aragao, L E O C, Araujo-Murakami, A, Arets, E J M M, Arroyo, L, Aymard, G A, Baraloto, C, Barroso, J, Bonal, D, Boot, R, Camargo, J, Chave, J, Cogollo, A, Cornejo, F Valverde, Costa, L da, di Fiore, A, Ferreira, L, Higuchi, N, Honorio, E, Killeen, T J, Laurance, S G, Laurance, W F, Licona, J, Lovejoy, T, Malhi, Y, Marimon, B, Marimon, B H Junior, Matos, D C L, Mendoza, C, Neill, D A, Pardo, G, Peña-Claros, M, Pitman, N C A, Poorter, L, Prieto, A, Ramirez-Angulo, H, Roopsind, A, Rudas, A, Salomao, R P, Silveira, M, Stropp, J, Ter Steege, H, Terborgh, J, Thomas, R, Toledo, M, Torres-Lezama, A, van der Heijden, Geertje, Vasquez, R, Vieira, I, Vilanova, E, Vos, V A, Baker, T R, Johnson, M O, Galbraith, D, Gloor, E, De Deurwaerder, H, Guimberteau, M, Rammig, A, Thonicke, K, Verbeeck, H, von Randow, C, Monteagudo, A, Phillips, O L, Brienen, R J W, Feldpausch, T R, Lopez Gonzalez, G, Fauset, S, Quesada, C A, Christoffersen, B, Ciais, P, Gilvan, S, Kruijt, B, Meir, P, Moorcroft, P, Zhang, K, Alvarez, E A, Alves de Oliveira, A, Amaral, I, Andrade, A, Aragao, L E O C, Araujo-Murakami, A, Arets, E J M M, Arroyo, L, Aymard, G A, Baraloto, C, Barroso, J, Bonal, D, Boot, R, Camargo, J, Chave, J, Cogollo, A, Cornejo, F Valverde, Costa, L da, di Fiore, A, Ferreira, L, Higuchi, N, Honorio, E, Killeen, T J, Laurance, S G, Laurance, W F, Licona, J, Lovejoy, T, Malhi, Y, Marimon, B, Marimon, B H Junior, Matos, D C L, Mendoza, C, Neill, D A, Pardo, G, Peña-Claros, M, Pitman, N C A, Poorter, L, Prieto, A, Ramirez-Angulo, H, Roopsind, A, Rudas, A, Salomao, R P, Silveira, M, Stropp, J, Ter Steege, H, Terborgh, J, Thomas, R, Toledo, M, Torres-Lezama, A, van der Heijden, Geertje, Vasquez, R, Vieira, I, Vilanova, E, Vos, V A, and Baker, T R
Abstract: Understanding the processes that determine aboveground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity (woody NPP) and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size-structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influence AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates, and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP, and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. This article is protected by copyright. All rights reserved.
Published: 2016

33. The water relations of two tropical rainforest species (Virola surinamensis and Eperua falcata): Is Virola unusual as previously reported?

Author: Têtè Sévérien Barigah, Aussenac, G., Baraloto, C., Bonal, D., Hervé Cochard, Agnès Granier, Jm Guehl, Huc, R., Ma Sobrado, Mt Tyree, Laboratoire de Physique et Physiologie Intégratives de l'Arbre Fruitier et Forestier (PIAF), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), Ecologie des forêts de Guyane (ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université des Antilles et de la Guyane (UAG)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Unité de Recherches Forestières Méditerranéennes (URFM), Institut National de la Recherche Agronomique (INRA), and Hervé Cochard
Subjects: Vegetal Biology, potentiel hydrique foliaire, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Conductivity apparatus, Hydraulic architecture, HPFM, Leaf water potential, Pressure chamber, Psychrometer, chambre à pression, Biologie végétale, Conductivity apparatus, Hydraulic architecture, HPFM, Leaf water potential, Pressure chamber, Psychrometer, architecture hydraulique
Abstract: HYDRO; International audience; The objective of this study was to examine the water relations and hydraulic architecture and vulnerability to cavitation in Virola surinamensis and V. michelii and to compare to similar measurements in Eperua falcata. In several previous reports Virola was seen to have a rather narrow range of xylem pressure potentials (Ψx) near zero in the course of a wet-season day while having water fluxes quite close to Eperua. We tested the hypothesis that the narrow range of Ψx might be consistent with very high hydraulic conductivities of stems, roots and shoots and high vulnerability to cavitation in Virola compared to Eperua. When this hypothesis proved false we concluded that the previous determinations of Ψx might be wrong in Virola due to latex. We re-examined the determination of Ψx in Virola by the pressure chamber technique and compared results to determination of Ψleaf by the thermocouple psychrometer technique and found that the likely range of Ψx are more negative than previously reported. Problems concerning the determination of Ψx in species with latex are discussed.
Published: 2014

34. Current knowledge on overall post-logging biomass dynamics in Northern Amazonian forests

Author: Sist, P., Lilian Blanc, Mazzei, L., Baraloto, C., Aussenac, R., Biens et services des écosystèmes forestiers tropicaux : l'enjeu du changement global (Cirad-Es-UPR 105 BSEF), Département Environnements et Sociétés (Cirad-ES), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Biens et services des écosystèmes forestiers tropicaux (UPR105 BSef), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Belem, Embrapa, Ecologie des forêts de Guyane (ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université des Antilles et de la Guyane (UAG)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Ecole Nationale du Génie Rural, des Eaux et des Forêts (ENGREF)-Institut National de la Recherche Agronomique (INRA)-Université des Antilles et de la Guyane (UAG)-Centre National de la Recherche Scientifique (CNRS), FFEM (Fonds frangais pour l'environnement mondial) through the project Floresta em Pe, CIRAD, Ministry of Overseas Departments (CORDET), National Forestry Fund (FFN), State Region Plan, European Structural Funds, Biens et services des écosystèmes forestiers tropicaux : l'enjeu du changement global (UPR BSEF), and Biens et services des écosystèmes forestiers tropicaux (UPR BSef)
Subjects: [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, F40 - Écologie végétale, WOOD DENSITY, Production forestière, TROPICAL FORESTS, above ground-biomass, logging impact, silviculture, Amazonian rainforests, SILVICULTURAL TREATMENTS, CARBON STOCKS, GROWTH-RATES, RAIN-FOREST, PATTERNS, BALANCE, TREES, F62 - Physiologie végétale - Croissance et développement, forêt tropicale, Abattage d'arbres, Biomasse, Dynamique des populations, Croissance, Impact sur l'environnement, Exploitation forestière, Régénération naturelle, K10 - Production forestière, séquestration du carbone, Forêt, P01 - Conservation de la nature et ressources foncières, Biodiversité
Abstract: This article presents the effects of logging on the dynamics of above-ground biomass from the results of the post-logging study within two forests: Cikel in Eastern Para, Brazil and Paracou in French Guiana. The main objective is to compare the impact of commercial logging on the regeneration of the above-ground biomass in these forests whose characteristics differ in terms of structure and growth. In both sites, the intensity of exploitation is a key factor in determining the loss of biomass and the time required for its regeneration. In Paracou, the regeneration of biomass lost during conventional logging of 10 trees per hectare takes 45 years and more than 100 years when operating with higher intensity (21 trees/ha). In Cikei the forest biomass regenerates after 49 years harvesting 6 trees/ha and that takes 87 years after removal of 8 trees/ha. This regeneration needs similar time on both sites but with lower logging intensity at Cikel, in which felled trees are larger with a greater biomass than those of Paracou. This post-logging study has established a direct correlation of the dynamics of the biomass with the initial structure of the forest, as well as with the parameters of forest dynamics: mortality, growth and recruitment. The accumulation of biomass by the tree growth of the two remaining stands is a key parameter for the net carbon storage, while the contribution of recruitment in Paracou becomes significant only after 10 years after felling. Therefore in view to improve the growth of residual trees, it is compulsory to apply adequate silvicultural treatments such as selective thinning or removal of vines. While the two forests are geographically close enough, their regenerative abilities differ and because of the significant difference in size of the trees, the forest could tolerate more intensive harvesting in French Guiana, This article presents the effects of log- ging on the dynamics of above-ground biomass from the results of the post-log- ging study within two forests: Cikel in Eastern Pará, Brazil and Paracou in French Guiana. The main objective is to compare the impact of commercial log- ging on the regeneration of the above- ground biomass in these forests whose characteristics differ in terms of structure and growth. In both sites, the intensity of exploitation is a key factor in deter- mining the loss of biomass and the time required for its regeneration. In Paracou, the regeneration of biomass lost during conventional logging of 10 trees per hectare takes 45 years and more than 100 years when operating with higher intensity (21 trees/ha ). In Cikel the for- est biomass regenerates after 49 years harvesting 6 trees/ha and that takes 87 years after removal of 8 trees/ha. This regeneration needs similar time on both sites but with lower logging intensity at Cikel, in which felled trees are larger with a greater biomass than those of Paracou. This post-logging study has established a direct correlation of the dynamics of the biomass with the initial structure of the forest, as well as with the parameters of forest dynamics: mortality, growth and recruitment. The accumulation of bio- mass by the tree growth of the two remaining stands is a key parameter for the net carbon storage, while the contri- bution of recruitment in Paracou becomes significant only after 10 years after felling. Therefore in view to improve the growth of residual trees, it is compul- sory to apply adequate silvicultural treat- ments such as selective thinning or removal of vines. While the two forests are geographically close enough, their regenerative abilities differ and because of the significant difference in size of the trees, the forest could tolerate more intensive harvesting in French Guiana, En este artículo se presentan los efectos de la explotación maderera sobre la diná- mica de la biomasa aérea gracias a los resultados del estudio de post-tala y aca- rreo en dos bosques: Cikel en el este de Pará en Brasil y Paracou en Guayana Francesa. El objetivo principal consistió en comparar el impacto de la tala comercial en la regeneración de la biomasa aérea en estos bosques cuyas características difie- ren en cuanto a la estructura y el creci- miento. En ambos lugares, la intensidad de la explotación resulta ser un factor clave para determinar la pérdida de bio- masa y el tiempo necesario para su rege- neración. En Paracou, la regeneración de la biomasa perdida durante la extracción de 10 árboles por hectárea tomará 45 años, así como100 años operando con mayor intensidad (21 árboles/ha). En Cikel la biomasa se regenera al cabo de 49 años al talar 6 árboles/ha y unos 87 años cose- chando 8 árboles/ha. Esta regeneración se alcanza al mismo plazo en ambos sitios, pero con intensidad de tala menor en Cikel, cuyos árboles comerciales son de mayor tamaño y con más biomasa que los de Paracou. Este estudio de post-tala esta- blece una correlación directa de la diná- mica de la biomasa con la estructura inicial de los bosques, así como con los parámetros de la dinámica forestal: morta- lidad, crecimiento y reclutamiento. La acu- mulación de biomasa que proporciona el crecimiento de los árboles residuales resulta ser un parámetro clave para la cap- tura y estoc de carbono, sin embargo la contribución del reclutamiento en Paracou solo llega a ser significativo al cabo de 10 años después de la tala. Por lo tanto, para mejorar el crecimiento post-tala de los árboles residuales se requiere una silvícul- tura en su favor consistiendo en raleos selectivos o eliminación de lianas. A pesar de la relativa proximidad geográfica de los dos bosques, el potencial regenerativo no es idéntico y debido a la obvia diferencia del tamaño de los árboles, el bosque de Guayana Francesa podría tolerar una valo- rización mas intensa.
Published: 2012

35. Using functional traits and phylogenetic trees to examine the assembly of tropical tree communities

Author: Baraloto, C., Hardy, O. J., Paine, C. E. T., Dexter, K. G., Cruaud, C., Dunning, L. T., Gonzalez, M. A., Molino, Jean-François, Sabatier, Daniel, Savolainen, V., and Chave, J.
Subjects: tropical forests, niche, phylogenetic signal, limiting similarity, environmental filtering, functional traits, determinants of plant community diversity and structure, competition, French Guiana
Abstract: 1. Niche theory proposes that species differences underlie both coexistence within communities and the differentiation in species composition among communities via limiting similarity and environmental filtering. However, it has been difficult to extend niche theory to species-rich communities because of the empirical challenge of quantifying niches for many species. This has motivated the development of functional and phylogeny-based approaches in community ecology, which represent two different means of approximating niche attributes. 2. Here, we assess the utility of plant functional traits and phylogenetic relationships in predicting community assembly processes using the largest trait and phylogenetic data base to date for any set of species-rich communities. 3. We measured 17 functional traits for all 4672 individuals of 668 tree species co-occurring in nine tropical rain forest plots in French Guiana. Trait variation was summarized into two ordination axes that reflect species niche overlap. 4. We also generated a dated molecular phylogenetic tree based on DNA sequencing of two plastid loci (rbcL and matK) comprising 97% of the individuals and 91% of the species in the plots. 5. We found that, on average, co-occurring species had greater functional and, to a lesser extent, phylogenetic similarity than expected by chance. 6. We also found that functional traits and their ordination loadings showed significant, albeit weak, phylogenetic signal, suggesting that phylogenetic distance provides pertinent information on niche overlap in tropical tree communities. 7. Synthesis. We provide the most comprehensive examination to date of the relative importance of environmental filtering and limiting similarity in structuring tropical tree communities. Our results confirm that environmental filtering is the overriding influence on community assembly in these species-rich systems.
Published: 2012

36. Contrasting taxonomic and functional responses of a tropical tree community to selective logging

Author: Baraloto, C., Hérault, B., Paine, C. E. T., Massot, H., Blanc, L., Bonal, D., Molino, Jean-François, Nicolini, E. A., Sabatier, Daniel, University of Zurich, Baraloto, Christopher, Ecologie des forêts de Guyane (ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université des Antilles et de la Guyane (UAG)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Forêts et Sociétés (Cirad-Es-UPR 105 Forêts et Sociétés), Département Environnements et Sociétés (Cirad-ES), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), French Ecology Ministry (MEDDAM) Biodiversite et Gestion Forestiere section, Biodiversite call of the Agence Nationale de la Recherche, France, INRA Package grant, Forêts et Sociétés (UPR Forêts et Sociétés), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud])
Subjects: [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, F40 - Écologie végétale, Aménagement forestier, forêt tropicale, Abattage d'arbres, tropical rain forest, 10127 Institute of Evolutionary Biology and Environmental Studies, K01 - Foresterie - Considérations générales, Densité, functional traits, species richness, Croissance, disturbance, Xylème, Morphologie végétale, Composition botanique, functional evenness, Impact sur l'environnement, Exploitation forestière, F70 - Taxonomie végétale et phytogéographie, Taxonomie, Régénération naturelle, functional diversity, light partitioning, K10 - Production forestière, French Guiana, Forêt, 570 Life sciences, biology, 590 Animals (Zoology), P01 - Conservation de la nature et ressources foncières, Biodiversité, canopy gap dynamics, 2303 Ecology
Abstract: 1. Considerable debate surrounds the extent to which tropical forests can be managed for resource extraction while conserving biodiversity and ecosystem properties, which depend on functional composition. Here we evaluate the compatibility of these aims by examining the effects of logging on taxonomic and functional diversity and composition in a tropical forest. 2. Twenty years after selective logging, we inventoried 4140 stems regenerating in logging gaps and adjacent undisturbed areas, and we integrated a database of 13 functional traits describing leaf and wood economics of tropical trees. 3. We found no differences in taxonomic and functional richness among habitats, but logging gaps had significantly higher taxonomic and functional evenness. 4. Logging also effected striking, long-term changes in both species and functional composition. In particular, the xylem density of recruits in logging gaps was 6% less than in unlogged forests, leaves were 11% less tough and had 613% greater mineral nutrient concentrations. 5. Synthesis and applications. Our results suggest that managers of tropical forests should limit overall surface area converted to logging gaps by creating fewer, larger gaps during selective logging, to reduce impacts on the taxonomic and functional composition of the regenerating stand.
Published: 2012
Full Text: View/download PDF

37. Functional traits predict ontogenetic growth trajectories among neotropical trees

Author: Hérault, B., Bachelot, B., Poorter, L., Bongers, F., Chave, J., Paine, C.E.T., Rossi, V., and Baraloto, C.
Subjects: life-history, wood density, PE&RC, Forest Ecology and Forest Management, economics spectrum, shade tolerance, trade-offs, photosynthetic traits, good predictors, mixed dipterocarp forest, tropical trees, Bosecologie en Bosbeheer, relative importance
Abstract: 1. Functional traits are posited to explain interspecific differences in performance, but these relationships are difficult to describe for long-lived organisms such as trees, which exhibit strong ontogenetic changes in demographic rates. Here, we use a size-dependent model of tree growth to test the extent to which of 17 functional traits related to leaf and stem economics, adult stature and seed size predict the ontogenetic trajectory of tree growth. 2. We used a Bayesian modelling framework to parameterize and contrast three size-dependent diameter growth models using 16 years of census data from 5524 individuals of 50 rain forest tree species: a size-dependent model, a size-dependent model with species-specific parameters and a size-dependent model based on functional traits. 3. Most species showed clear hump-shaped ontogenetic growth trajectories and, across species, maximum growth rate varied nearly tenfold, from 0.58 to 5.51 mm year-1. Most species attained their maximum growth at 60% of their maximum size, whereas the magnitude of ontogenetic changes in growth rate varied widely among species. 4. The Trait-Model provided the best compromise between explained variance and model parsimony and needed considerably fewer parameters than the model with species terms. 5. Stem economics and adult stature largely explained interspecific differences in growth strategy. Maximum absolute diameter growth rates increased with increasing adult stature and leaf d13C and decreased with increasing wood density. Species with light wood had the greatest potential to modulate their growth, resulting in hump-shaped ontogenetic growth curves. Seed size and leaf economics, generally thought to be of paramount importance for plant performance, had no significant relationships with the growth parameters. 6. Synthesis. Our modelling approach offers a promising way to link demographic parameters to their functional determinants and hence to predict growth trajectories in species-rich communities with little parameter inflation, bridging the gap between functional ecology and population demography.
Published: 2011

38. Contributions of a global network of tree diversity experiments to sustainable forest plantations

Author: Verheyen, K., Vanhellemont, M., Auge, Harald, Baeten, L., Baraloto, C., Barsoum, N., Bilodeau-Gauthier, S., Bruelheide, H., Castagneyrol, B., Godbold, D., Haase, J., Hector, A., Jactel, H., Koricheva, J., Loreau, M., Mereu, S., Messier, C., Muys, B., Nolet, P., Paquette, A., Parker, J., Perring, M., Ponette, Q., Potvin, C., Reich, P., Smith, A., Weih, M., Scherer-Lorenzen, M., Verheyen, K., Vanhellemont, M., Auge, Harald, Baeten, L., Baraloto, C., Barsoum, N., Bilodeau-Gauthier, S., Bruelheide, H., Castagneyrol, B., Godbold, D., Haase, J., Hector, A., Jactel, H., Koricheva, J., Loreau, M., Mereu, S., Messier, C., Muys, B., Nolet, P., Paquette, A., Parker, J., Perring, M., Ponette, Q., Potvin, C., Reich, P., Smith, A., Weih, M., and Scherer-Lorenzen, M.
Abstract: The area of forest plantations is increasing worldwide helping to meet timber demand and protect natural forests. However, with global change, monospecific plantations are increasingly vulnerable to abiotic and biotic disturbances. As an adaption measure we need to move to plantations that are more diverse in genotypes, species, and structure, with a design underpinned by science. TreeDivNet, a global network of tree diversity experiments, responds to this need by assessing the advantages and disadvantages of mixed species plantations. The network currently consists of 18 experiments, distributed over 36 sites and five ecoregions. With plantations 1–15 years old, TreeDivNet can already provide relevant data for forest policy and management. In this paper, we highlight some early results on the carbon sequestration and pest resistance potential of more diverse plantations. Finally, suggestions are made for new, innovative experiments in understudied regions to complement the existing network.
Published: 2015

39. Globally, functional traits are weak predictors of juvenile tree growth, and we do not know why

Author: Paine, C.E.T., Amissah, L., Auge, Harald, Baraloto, C., Baruffol, M., Bourland, N., Bruelheide, H., Dainou, K., de Gouvenain, R.C., Doucet, J.-L., Doust, S., Fine, P.V.A., Fortunel, C., Haase, J., Holl, K.D., Jactel, H., Li, X., Kitajima, K., Koricheva, J., Martínez-Garza, C., Messier, C., Paquette, A., Philipson, C., Piotto, D., Poorter, L., Posada, J.M., Potvin, C., Rainio, K., Russo, S.E., Ruiz-Jaen, M., Scherer-Lorenzen, M., Webb, C.O., Wright, S.J., Zahawi, R.A., Hector, A., Paine, C.E.T., Amissah, L., Auge, Harald, Baraloto, C., Baruffol, M., Bourland, N., Bruelheide, H., Dainou, K., de Gouvenain, R.C., Doucet, J.-L., Doust, S., Fine, P.V.A., Fortunel, C., Haase, J., Holl, K.D., Jactel, H., Li, X., Kitajima, K., Koricheva, J., Martínez-Garza, C., Messier, C., Paquette, A., Philipson, C., Piotto, D., Poorter, L., Posada, J.M., Potvin, C., Rainio, K., Russo, S.E., Ruiz-Jaen, M., Scherer-Lorenzen, M., Webb, C.O., Wright, S.J., Zahawi, R.A., and Hector, A.
Abstract: Plant functional traits, in particular specific leaf area (SLA), wood density and seed mass, are often good predictors of individual tree growth rates within communities. Individuals and species with high SLA, low wood density and small seeds tend to have faster growth rates.If community-level relationships between traits and growth have general predictive value, then similar relationships should also be observed in analyses that integrate across taxa, biogeographic regions and environments. Such global consistency would imply that traits could serve as valuable proxies for the complex suite of factors that determine growth rate, and, therefore, could underpin a new generation of robust dynamic vegetation models. Alternatively, growth rates may depend more strongly on the local environment or growth–trait relationships may vary along environmental gradients.We tested these alternative hypotheses using data on 27 352 juvenile trees, representing 278 species from 27 sites on all forested continents, and extensive functional trait data, 38% of which were obtained at the same sites at which growth was assessed. Data on potential evapotranspiration (PET), which summarizes the joint ecological effects of temperature and precipitation, were obtained from a global data base.We estimated size-standardized relative height growth rates (SGR) for all species, then related them to functional traits and PET using mixed-effect models for the fastest growing species and for all species together.Both the mean and 95th percentile SGR were more strongly associated with functional traits than with PET. PET was unrelated to SGR at the global scale. SGR increased with increasing SLA and decreased with increasing wood density and seed mass, but these traits explained only 3.1% of the variation in SGR. SGR–trait relationships were consistently weak across families and biogeographic zones, and over a range of tree statures. Thus, the most widely studied functional traits in plant e
Published: 2015

40. Data from: Globally, functional traits are weak predictors of juvenile tree growth, and we do not know why

Author: Paine, C.E.T., Amissah, Lucy, Auge, H., Baraloto, C., Poorter, Lourens, Paine, C.E.T., Amissah, Lucy, Auge, H., Baraloto, C., and Poorter, Lourens
Abstract: 1. Plant functional traits, in particular specific leaf area (SLA), wood density and seed mass, are often good predictors of individual tree growth rates within communities. Individuals and species with high SLA, low wood density and small seeds tend to have faster growth rates. 2. If community-level relationships between traits and growth have general predictive value, then similar relationships should also be observed in analyses that integrate across taxa, biogeographic regions and environments. Such global consistency would imply that traits could serve as valuable proxies for the complex suite of factors that determine growth rate, and, therefore, could underpin a new generation of robust dynamic vegetation models. Alternatively, growth rates may depend more strongly on the local environment or growth–trait relationships may vary along environmental gradients. 3. We tested these alternative hypotheses using data on 27 352 juvenile trees, representing 278 species from 27 sites on all forested continents, and extensive functional trait data, 38% of which were obtained at the same sites at which growth was assessed. Data on potential evapotranspiration (PET), which summarizes the joint ecological effects of temperature and precipitation, were obtained from a global data base. 4. We estimated size-standardized relative height growth rates (SGR) for all species, then related them to functional traits and PET using mixed-effect models for the fastest growing species and for all species together. 5. Both the mean and 95th percentile SGR were more strongly associated with functional traits than with PET. PET was unrelated to SGR at the global scale. SGR increased with increasing SLA and decreased with increasing wood density and seed mass, but these traits explained only 3.1% of the variation in SGR. SGR–trait relationships were consistently weak across families and biogeographic zones, and over a range of tree statures. Thus, the most widely studied functional traits
Published: 2015

41. Shifts in species and phylogenetic diversity between sapling and tree communities indicate negative density-dependence in a lowland rainforest

Author: Gonzalez, M.A., Roger, A., Courtois, E., Jabot, F., Norden, N., Paine, C.E.T., Baraloto, C., Thébaud, C., Chave, J., Evolution et Diversité Biologique (EDB), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées
Subjects: ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2010

42. Decoupled leaf and stem economics in rain forest trees

Author: Baraloto, C., Paine, C.E.T., Poorter, L., Beauchene, J., Bonal, D., Domenach, A.M., Herault, B., Patiño, S., Roggy, J.C., Chave, J., Department of Biology, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Ecologie des forêts de Guyane (ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université des Antilles et de la Guyane (UAG)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Commissariat général du Plan (CGP), Premier ministre, Instituto de Investigación de Recursos Biológicos Alexander von Humboldt. Diagonal 27 No. 15-09, Earth and Biosphere Institute, School of Geography, Evolution et Diversité Biologique (EDB), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)
Subjects: architecture, Écologie, F40 - Écologie végétale, Tige, [SDV]Life Sciences [q-bio], Méthode d'optimisation, F62 - Physiologie végétale - Croissance et développement, size, F50 - Anatomie et morphologie des plantes, diversity, spectrum, K01 - Foresterie - Considérations générales, Bosecologie en Bosbeheer, functional traits, Forêt tropicale humide, Adaptation, Densité du peuplement, U10 - Informatique, mathématiques et statistiques, Analyse multivariée, Feuille, wood density, PE&RC, Forest Ecology and Forest Management, Physiologie végétale, phylogenetics, neotropical forests, Anatomie végétale, Wildlife Ecology and Conservation, strategies, conductivity, Modèle végétal, functional diversity, leaf economics, multiple factor analysis, plant strategies, plant traits, tropical forest, wood density, trait physiologique
Abstract: International audience; Cross-species analyses of plant functional traits have shed light on factors contributing to differences in performance and distribution, but to date most studies have focused on either leaves or stems. We extend these tissue-specific analyses of functional strategy towards a whole-plant approach by integrating data on functional traits for 13 448 leaves and wood tissues from 4672 trees representing 668 species of Neotropical trees. Strong correlations amongst traits previously defined as the leaf economics spectrum reflect a tradeoff between investments in productive leaves with rapid turnover vs. costly physical leaf structure with a long revenue stream. A second axis of variation, the 'stem economics spectrum', defines a similar tradeoff at the stem level: dense wood vs. high wood water content and thick bark. Most importantly, these two axes are orthogonal, suggesting that tradeoffs operate independently at the leaf and at the stem levels. By simplifying the multivariate ecological strategies of tropical trees into positions along these two spectra, our results provide a basis to improve global vegetation models predicting responses of tropical forests to global change.
Published: 2010
Full Text: View/download PDF

43. Hyperdominance in the Amazonian tree flora

Author: Steege, H. ter, Pitman, C.A., Sabatier, D., Baraloto, C., Salomão, R.P., Guevara, J.E., Phillips, O.L., Castilho, C.V., Magnusson, W.E., Mollino, J.-F., Stevenson Diaz, P.R., Costa , F., Emilio, T., Levis, C., Schietti, J., Souza, P., Alonso, A., Dallmeier, F., Duque Montoya, A.J., Fernandez Piedade, M.T., Maas, P., Araujo-Murakami, A., Arroyo, L., Gribel, R., Fine, P.V.A., Peres, C.A., Toledo, M., Aymard C., G.A., Baker, T.R., Cerón, C., Engel, J., Petronelli, P., Henkel, T.W., Stropp, J., Zartman, C.E., Daly, D., Neill, D., Silveira, M., Ríos Paredes, M., Chave, J., de Andrade Lima Filho, D., Hoffman, B., Møller Jørgensen, P., Fuentes, A., Schöngart, J., Cornejo Valverde, F., Di Fiore, A., Jimenez, E.M., Peñuela Mora, M.C., Phillips, J.F., Rivas, G., Andel, T.R. (Tinde) van, Zent, E.L., Hildebrand, P. von, Malhi, Y., Prieto, A., Rudas, A., Ruschell, A., Silva, N., Vos, V., Zent, S., Oliveira, A.A., Wang, O., Cano Schutz, A., Gonzales, T., Trindade Nascimento, M., Ramirez-Angulo, H., Sierra, R., Tirado , M., Umaña Medina, M.N., Heijden, G. van der, Vela, C.I.A., Vilanova Torre, E., Young, K.R., Vriesendorp, C., Baider, C., Balslev, H., Ferreira, C., Mesones, I., Torres-Lezama, A., Urrego Giraldo, L.E., Zagt, R., Alexiades, M.N., Monteagudo, A., Hernandez, L., Huamantupa-Chuquimaco, I., Millikes, W., Palacios Cuenca, W., Pauletto, D., Valderrama Sandoval, E., Valenzuela Gamarra, L., Dexter, K.G., Feeley, K., Lopez-Gonzalez, G., Núñez Vargas, P., Silman, M.R., Montero, J.C., Feldpausch, T.R., Honorio Coronado, E.N., Killeen, T.J., Mostacedo, B., Vasquez, R., Assis, R.L., Terborgh, J., Wittmann, F., Andrade, A., Laurance, W.F., Laurance, S.G.W., Marimon, B.S., Marimon , (B.-H. Jr.), Célia Guimarães Vieira, I., Leão Amaral, I., Brienen, R., Castellanos, H., Cárdenas López, D., Duivenvoorden, J.F., Mogollón, H.F., Dionízia de Almeida Matos, F., Dávila, N., García-Villacorta, R., Steege, H. ter, Pitman, C.A., Sabatier, D., Baraloto, C., Salomão, R.P., Guevara, J.E., Phillips, O.L., Castilho, C.V., Magnusson, W.E., Mollino, J.-F., Stevenson Diaz, P.R., Costa , F., Emilio, T., Levis, C., Schietti, J., Souza, P., Alonso, A., Dallmeier, F., Duque Montoya, A.J., Fernandez Piedade, M.T., Maas, P., Araujo-Murakami, A., Arroyo, L., Gribel, R., Fine, P.V.A., Peres, C.A., Toledo, M., Aymard C., G.A., Baker, T.R., Cerón, C., Engel, J., Petronelli, P., Henkel, T.W., Stropp, J., Zartman, C.E., Daly, D., Neill, D., Silveira, M., Ríos Paredes, M., Chave, J., de Andrade Lima Filho, D., Hoffman, B., Møller Jørgensen, P., Fuentes, A., Schöngart, J., Cornejo Valverde, F., Di Fiore, A., Jimenez, E.M., Peñuela Mora, M.C., Phillips, J.F., Rivas, G., Andel, T.R. (Tinde) van, Zent, E.L., Hildebrand, P. von, Malhi, Y., Prieto, A., Rudas, A., Ruschell, A., Silva, N., Vos, V., Zent, S., Oliveira, A.A., Wang, O., Cano Schutz, A., Gonzales, T., Trindade Nascimento, M., Ramirez-Angulo, H., Sierra, R., Tirado , M., Umaña Medina, M.N., Heijden, G. van der, Vela, C.I.A., Vilanova Torre, E., Young, K.R., Vriesendorp, C., Baider, C., Balslev, H., Ferreira, C., Mesones, I., Torres-Lezama, A., Urrego Giraldo, L.E., Zagt, R., Alexiades, M.N., Monteagudo, A., Hernandez, L., Huamantupa-Chuquimaco, I., Millikes, W., Palacios Cuenca, W., Pauletto, D., Valderrama Sandoval, E., Valenzuela Gamarra, L., Dexter, K.G., Feeley, K., Lopez-Gonzalez, G., Núñez Vargas, P., Silman, M.R., Montero, J.C., Feldpausch, T.R., Honorio Coronado, E.N., Killeen, T.J., Mostacedo, B., Vasquez, R., Assis, R.L., Terborgh, J., Wittmann, F., Andrade, A., Laurance, W.F., Laurance, S.G.W., Marimon, B.S., Marimon , (B.-H. Jr.), Célia Guimarães Vieira, I., Leão Amaral, I., Brienen, R., Castellanos, H., Cárdenas López, D., Duivenvoorden, J.F., Mogollón, H.F., Dionízia de Almeida Matos, F., Dávila, N., and García-Villacorta, R.
Abstract: The vast extent of the Amazon Basin has historically restricted the study of its tree communities to the local and regional scales. Here, we provide empirical data on the commonness, rarity, and richness of lowland tree species across the entire Amazon Basin and Guiana Shield (Amazonia), collected in 1170 tree plots in all major forest types. Extrapolations suggest that Amazonia harbors roughly 16,000 tree species, of which just 227 (1.4%) account for half of all trees. Most of these are habitat specialists and only dominant in one or two regions of the basin. We discuss some implications of the finding that a small group of species—less diverse than the North American tree flora—accounts for half of the world’s most diverse tree community.
Published: 2013
Full Text: View/download PDF

44. Within-individual variation of trunk and branch xylem density in tropical trees

Author: Sarmiento, C., primary, Patino, S., additional, Paine, C. E. T., additional, Beauchene, J., additional, Thibaut, A., additional, and Baraloto, C., additional
Published: 2010
Full Text: View/download PDF

45. Positive biodiversity-productivity relationship predominant in global forests

Author: Fischer, Markus, Ba Azy, R., Neldner, V. J., Lei, X., Picard, N., Crowther, T. W., Vayreda, J., OBrien, T., Valladares, F., Herault, B., Vibrans, A. C., Bitariho, R., Jucker, T., Piotto, D., Rovero, F., Pretzsch, H., Hengeveld, G. M., Alvarez-Loayza, P., Odeke, D. E., Lu, H., Ngugi, M. R., Watson, J. V., Schall, P., Vasquez, R. M., Paquette, A., Valencia, R., Peri, P. L., Tchebakova, N., Marshall, A. R., Schulze, E.-D., Zhu, J., Finer, L., Nabuurs, G.-J., Reich, P. B., Martin, E. H., Bruelheide, H., Viana, H., Oleksyn, J., Chamuya, N., Salas, C., Wiser, S., Liang, J., Schmid, B., Tavani, R., Ammer, C., Bozzato, F., Lee, E., Glick, H. B., Kim, H. S., Engone-Obiang, N. L., Pfautsch, S., Jagodzinski, A. M., Lewis, S. L., McGuire, A. D., Wortel, V., Zhou, M., Schelhaas, M.-J., De-Miguel, S., Brandl, S., Scherer-Lorenzen, M., Sunderland, T., Sonke, B., Bouriaud, O., Jaroszewicz, B., Alberti, G., Lee, B., Coomes, D. A., Verbyla, D., Gianelle, D., Gonmadje, C., Niklaus, P. A., Searle, E. B., Ferreira, L. V., Gourlet-Fleury, S., Marthy, W., Zawiła-Niedźwiecki, T., Mortier, F., Kitahara, F., Parfenova, E. I., Baraloto, C., Frizzera, L., Barrett, C. B., Bussotti, F., and Chen, H. Y. H.
Subjects: 13. Climate action, 15. Life on land, 580 Plants (Botany)

46. Long-term decline of the Amazon carbon sink

Author: Brienen, Roel J.W., Phillips, Oliver L., Feldpausch, Ted R., Gloor, E., Baker, Tim R., Lloyd, J., Monteagudo-Mendoza, A., Malhi, Y., Lewis, S.L., Alexiades, M., Alvarez-Loayza, P., Andrade, A., Araujo-Murakami, A., Arets, Eric J.M.M., Arroyo, L., Aymard C., G. A., Baraloto, C., Barroso, J., Bonal, D., Boot, R.G.A., Castilho, Carolina V., Chama, V., Chao, K.J., Chave, J., Comiskey, James A., Cornejo Valverde, F., da Costa, L., de Oliveira, E.A., Di Fiore, A., Erwin, Terry L., Fauset, S., Forsthofer, M., Galbraith, David R., Grahame, E.S., Groot, N., Higuchi, N., Keeling, H., Killeen, T. J., Laurance, William F., Laurance, S., Licona, J., Magnussen, W.E., Marimon, Beatriz S., Marimon-Junior, Ben H., Mendoza, C., Neill, D.A., Nogueira, E,M., Pallqui Camacho, N.C., Parada, A., Pardo-Molina, G., Peacock, J., Pickavance, G.C., Pitman, Nigel C.A., Poorter, L., Prieto, A., Quesada, Carlos A., Restrepo, Z., Roopsind, A., Rudas, A., Schwarz, M., Silva, N., Silva-Espejo, J.E., Silveira, M., Stropp, J., Talbot, J., ter Steege, H., Teran-Aguilar, J., Terborgh, J., Thomas-Caesar, R., Toledo, M., Torello-Raventos, M., Umetsu, R.K.., van der Heijden, Geertje M.F., van der Hout, Peter, Vieira, Simone A., Vilanova, Emilio, Vos, Vincent A., and Zagt, Roderick J.
Subjects: Forest ecology, Climate-change ecology, Population dynamics

47. Evolutionary heritage influences Amazon tree ecology

Author: Coelho De Souza, F, Dexter, KG, Phillips, OL, Brienen, RJW, Chave, J, Galbraith, DR, Lopez Gonzalez, G, Monteagudo Mendoza, A, Pennington, TR, Poorter, L, Alexiades, M, Álvarez-Dávila, E, Andrade, A, Aragão, LEOC, Araujo-Murakami, A, Arets, E, Aymard, GA, Baraloto, C, Barroso, JG, Bonal, D, Boot, RGA, Camargo, JLC, Comiskey, JA, Cornejo Valverde, F, de Camargo, PB, Di Fiore, A, Elias, F, Erwin, TL, Feldpausch, TR, Ferreira, L, Fyllas, NM, Gloor, E, Herault, B, Herrera, R, Higuchi, N, Honorio Coronado, EN, Killeen, T, Laurance, WF, Laurance, S, Lloyd, J, Lovejoy, TE, Malhi, Y, Maracahipes, L, Marimon, BS, Marimon-Junior, BH, Mendoza, C, Morandi, P, Neill, DA, Núñez Vargas, P, Oliveira, EA, Lenza, E, Palacios, WA, Peñuela-Mora, M, Pipoly III, JJ, Pitman, NCA, Prieto, A, Quesada, CA, Ramirez-Angulo, H, Rudas, A, Ruokolainen, K, Salomão, RP, Silveira, M, Stropp, J, ter Steege, H, Thomas-Caesar, R, van der Hout, P, van der Heijden, GMF, van der Meer, PJ, Vasquez, RV, Vieira, SA, Vilanova, E, Vos, VA, Wang, O, Young, KR, Zagt, RJ, Baker, TR, Chercheur indépendant, Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), and The Royal Society
Subjects: Life Sciences & Biomedicine - Other Topics, Convergent Evolution, WOOD DENSITY, [SDV]Life Sciences [q-bio], Trait, Forests, Trees, BIOMASS, Angiosperm, Divergence, Divergent selection, Natural Selection, tropical tree, Phylogeny, Research Articles, Ecology, PRODUCTIVITY, trait, phylogenetic signal, RAIN-FOREST, 11 Medical And Health Sciences, Biological Evolution, Phylogenetics, GROWTH, divergent selection, Life Sciences & Biomedicine, Environmental Sciences & Ecology, Life History Trait, Forest Inventory, Magnoliophyta, Amazonia, Tropical Forest, Tropical tree, convergent evolution, Mortality, Biology, Tropical Climate, Evolutionary Biology, Science & Technology, South America, PHYLOGENETIC NICHE CONSERVATISM, 06 Biological Sciences, SIGNAL, SIZE, FUNCTIONAL TRAITS, Ecosystem Function, 07 Agricultural And Veterinary Sciences, COMMUNITY ECOLOGY
Abstract: Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant lifehistory strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change. © 2016 The Authors.
Full Text: View/download PDF

48. Long-term decline of the Amazon carbon sink

Author: Brienen, Roel J.W., Phillips, Oliver L., Feldpausch, Ted R., Gloor, E., Baker, Tim R., Lloyd, J., López-González, Gabriela, Monteagudo-Mendoza, A., Malhi, Y., Lewis, S.L., Vásquez Martinez, R., Alexiades, M., Álvarez Dávila, E., Alvarez-Loayza, P., Andrade, A., Aragão, Luis E.O.C., Araujo-Murakami, A., Arets, Eric J.M.M., Arroyo, L., Aymard C., G. A., Bánki, O.S., Baraloto, C., Barroso, J., Bonal, D., Boot, R.G.A., Camargo, José L.C., Castilho, Carolina V., Chama, V., Chao, K.J., Chave, J., Comiskey, James A., Cornejo Valverde, F., da Costa, L., de Oliveira, E.A., Di Fiore, A., Erwin, Terry L., Fauset, S., Forsthofer, M., Galbraith, David R., Grahame, E.S., Groot, N., Hérault, B., Higuchi, N., Honorio Coronado, Eurídice N., Keeling, H., Killeen, T. J., Laurance, William F., Laurance, S., Licona, J., Magnussen, W.E., Marimon, Beatriz S., Marimon-Junior, Ben H., Mendoza, C., Neill, D.A., Nogueira, E,M., Núñez, P., Pallqui Camacho, N.C., Parada, A., Pardo-Molina, G., Peacock, J., Peña-Claros, M., Pickavance, G.C., Pitman, Nigel C.A., Poorter, L., Prieto, A., Quesada, Carlos A., Ramírez, F., Ramírez-Angulo, H., Restrepo, Z., Roopsind, A., Rudas, A., Salomão, Rafael P., Schwarz, M., Silva, N., Silva-Espejo, J.E., Silveira, M., Stropp, J., Talbot, J., ter Steege, H., Teran-Aguilar, J., Terborgh, J., Thomas-Caesar, R., Toledo, M., Torello-Raventos, M., Umetsu, R.K.., van der Heijden, Geertje M.F., van der Hout, Peter, Guimarães Vieira, Ima Célia, Vieira, Simone A., Vilanova, Emilio, Vos, Vincent A., Zagt, Roderick J., Brienen, Roel J.W., Phillips, Oliver L., Feldpausch, Ted R., Gloor, E., Baker, Tim R., Lloyd, J., López-González, Gabriela, Monteagudo-Mendoza, A., Malhi, Y., Lewis, S.L., Vásquez Martinez, R., Alexiades, M., Álvarez Dávila, E., Alvarez-Loayza, P., Andrade, A., Aragão, Luis E.O.C., Araujo-Murakami, A., Arets, Eric J.M.M., Arroyo, L., Aymard C., G. A., Bánki, O.S., Baraloto, C., Barroso, J., Bonal, D., Boot, R.G.A., Camargo, José L.C., Castilho, Carolina V., Chama, V., Chao, K.J., Chave, J., Comiskey, James A., Cornejo Valverde, F., da Costa, L., de Oliveira, E.A., Di Fiore, A., Erwin, Terry L., Fauset, S., Forsthofer, M., Galbraith, David R., Grahame, E.S., Groot, N., Hérault, B., Higuchi, N., Honorio Coronado, Eurídice N., Keeling, H., Killeen, T. J., Laurance, William F., Laurance, S., Licona, J., Magnussen, W.E., Marimon, Beatriz S., Marimon-Junior, Ben H., Mendoza, C., Neill, D.A., Nogueira, E,M., Núñez, P., Pallqui Camacho, N.C., Parada, A., Pardo-Molina, G., Peacock, J., Peña-Claros, M., Pickavance, G.C., Pitman, Nigel C.A., Poorter, L., Prieto, A., Quesada, Carlos A., Ramírez, F., Ramírez-Angulo, H., Restrepo, Z., Roopsind, A., Rudas, A., Salomão, Rafael P., Schwarz, M., Silva, N., Silva-Espejo, J.E., Silveira, M., Stropp, J., Talbot, J., ter Steege, H., Teran-Aguilar, J., Terborgh, J., Thomas-Caesar, R., Toledo, M., Torello-Raventos, M., Umetsu, R.K.., van der Heijden, Geertje M.F., van der Hout, Peter, Guimarães Vieira, Ima Célia, Vieira, Simone A., Vilanova, Emilio, Vos, Vincent A., and Zagt, Roderick J.
Full Text: View/download PDF

49. sPlot – A new tool for global vegetation analyses

Author: Bruelheide H., Dengler J., Jiménez-Alfaro B., Purschke O., Hennekens S., Chytrý M., Pillar V., Jansen F., Kattge J., Sandel B., Aubin I., Biurrun I., Field R., Haider S., Jandt U., Lenoir J., Peet R., Peyre G., Sabatini F., Schmidt M., Schrodt F., Winter M., Aćić S., Agrillo E., Alvarez M., Ambarlı D., Angelini P., Apostolova I., Arfin Khan M., Arnst E., Attorre F., Baraloto C., Beckmann M., Berg C., Bergeron Y., Bergmeier E., Bjorkman A., Bondareva V., Borchardt P., Botta-Dukát Z., Boyle B., Breen A., Brisse H., Byun C., Cabido M., Casella L., Cayuela L., Černý T., Chepinoga V., Csiky J., Curran M., Ćušterevska R., Dajić Stevanović Z., De Bie E., de Ruffray P., De Sanctis M., Dimopoulos P., Dressler S., Ejrnæs R., El-Sheikh M., Enquist B., Ewald J., Fagúndez J., Finckh M., Font X., Forey E., Fotiadis G., García-Mijangos I., de Gasper A., Golub V., Gutierrez A., Hatim M., He T., Higuchi P., Holubová D., Hölzel N., Homeier J., Indreica A., Işık Gürsoy D., Jansen S., Janssen J., Jedrzejek B., Jiroušek M., Jürgens N., Kącki Z., Kavgacı A., Kearsley E., Kessler M., Knollová I., Kolomiychuk V., Korolyuk A., Kozhevnikova M., Kozub Ł., Krstonošić D., Kühl H., Kühn I., Kuzemko A., Küzmič F., Landucci F., Lee M., Bruelheide H., Dengler J., Jiménez-Alfaro B., Purschke O., Hennekens S., Chytrý M., Pillar V., Jansen F., Kattge J., Sandel B., Aubin I., Biurrun I., Field R., Haider S., Jandt U., Lenoir J., Peet R., Peyre G., Sabatini F., Schmidt M., Schrodt F., Winter M., Aćić S., Agrillo E., Alvarez M., Ambarlı D., Angelini P., Apostolova I., Arfin Khan M., Arnst E., Attorre F., Baraloto C., Beckmann M., Berg C., Bergeron Y., Bergmeier E., Bjorkman A., Bondareva V., Borchardt P., Botta-Dukát Z., Boyle B., Breen A., Brisse H., Byun C., Cabido M., Casella L., Cayuela L., Černý T., Chepinoga V., Csiky J., Curran M., Ćušterevska R., Dajić Stevanović Z., De Bie E., de Ruffray P., De Sanctis M., Dimopoulos P., Dressler S., Ejrnæs R., El-Sheikh M., Enquist B., Ewald J., Fagúndez J., Finckh M., Font X., Forey E., Fotiadis G., García-Mijangos I., de Gasper A., Golub V., Gutierrez A., Hatim M., He T., Higuchi P., Holubová D., Hölzel N., Homeier J., Indreica A., Işık Gürsoy D., Jansen S., Janssen J., Jedrzejek B., Jiroušek M., Jürgens N., Kącki Z., Kavgacı A., Kearsley E., Kessler M., Knollová I., Kolomiychuk V., Korolyuk A., Kozhevnikova M., Kozub Ł., Krstonošić D., Kühl H., Kühn I., Kuzemko A., Küzmič F., Landucci F., and Lee M.
Abstract: © 2019 International Association for Vegetation Science Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

50. The global spectrum of plant form and function: enhanced species-level trait dataset

Author: Sandra Díaz, Jens Kattge, Johannes H. C. Cornelissen, Ian J. Wright, Sandra Lavorel, Stéphane Dray, Björn Reu, Michael Kleyer, Christian Wirth, I. Colin Prentice, Eric Garnier, Gerhard Bönisch, Mark Westoby, Hendrik Poorter, Peter B. Reich, Angela T. Moles, John Dickie, Amy E. Zanne, Jérôme Chave, S. Joseph Wright, Serge N. Sheremetiev, Hervé Jactel, Christopher Baraloto, Bruno E. L. Cerabolini, Simon Pierce, Bill Shipley, Fernando Casanoves, Julia S. Joswig, Angela Günther, Valeria Falczuk, Nadja Rüger, Miguel D. Mahecha, Lucas D. Gorné, Bernard Amiaud, Owen K. Atkin, Michael Bahn, Dennis Baldocchi, Michael Beckmann, Benjamin Blonder, William Bond, Ben Bond-Lamberty, Kerry Brown, Sabina Burrascano, Chaeho Byun, Giandiego Campetella, Jeannine Cavender-Bares, F. Stuart Chapin, Brendan Choat, David Anthony Coomes, William K. Cornwell, Joseph Craine, Dylan Craven, Matteo Dainese, Alessandro Carioca de Araujo, Franciska T. de Vries, Tomas Ferreira Domingues, Brian J. Enquist, Jaime Fagúndez, Jingyun Fang, Fernando Fernández-Méndez, Maria T. Fernandez-Piedade, Henry Ford, Estelle Forey, Gregoire T. Freschet, Sophie Gachet, Rachael Gallagher, Walton Green, Greg R. Guerin, Alvaro G. Gutiérrez, Sandy P. Harrison, Wesley Neil Hattingh, Tianhua He, Thomas Hickler, Steven I. Higgins, Pedro Higuchi, Jugo Ilic, Robert B. Jackson, Adel Jalili, Steven Jansen, Fumito Koike, Christian König, Nathan Kraft, Koen Kramer, Holger Kreft, Ingolf Kühn, Hiroko Kurokawa, Eric G. Lamb, Daniel C. Laughlin, Michelle Leishman, Simon Lewis, Frédérique Louault, Ana C. M. Malhado, Peter Manning, Patrick Meir, Maurizio Mencuccini, Julie Messier, Regis Miller, Vanessa Minden, Jane Molofsky, Rebecca Montgomery, Gabriel Montserrat-Martí, Marco Moretti, Sandra Müller, Ülo Niinemets, Romà Ogaya, Kinga Öllerer, Vladimir Onipchenko, Yusuke Onoda, Wim A. Ozinga, Juli G. Pausas, Begoña Peco, Josep Penuelas, Valério D. Pillar, Clara Pladevall, Christine Römermann, Lawren Sack, Norma Salinas, Brody Sandel, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Ernst-Detlef Schulze, Fritz Schweingruber, Satomi Shiodera, Ênio Sosinski, Nadejda Soudzilovskaia, Marko J. Spasojevic, Emily Swaine, Nathan Swenson, Susanne Tautenhahn, Ken Thompson, Alexia Totte, Rocío Urrutia-Jalabert, Fernando Valladares, Peter van Bodegom, François Vasseur, Kris Verheyen, Denis Vile, Cyrille Violle, Betsy von Holle, Patrick Weigelt, Evan Weiher, Michael C. Wiemann, Mathew Williams, Justin Wright, Gerhard Zotz, Biology, General Botany and Nature Management, Instituto Multidisciplinario de Biología Vegetal [Córdoba] (IMBIV), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Facultad de Ciencias Exactas, Físicas y Naturales [Córdoba], Universidad Nacional de Córdoba [Argentina]-Universidad Nacional de Córdoba [Argentina], Universidad Nacional de Córdoba [Argentina], Ecologie quantitative et évolutive des communautés, Département écologie évolutive [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-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)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Etude et Compréhension de la biodiversité (ECODIV), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), TRY initiative on plant traits (https://www.try-db.org).TRY is an initiative of the Max Planck Institute for Biogeochemistry, bioDISCOVERY/Future Earth (ICSU), the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and Nucleo DiverSus (CONICET-Universidad Nacional de Cordoba, Argentina)., The Global Spectrum of Plant Form and Function study has been supported by the European BACI project (Towards a Biosphere Atmosphere change Index, EU grant ID 640176), FONCyT, CONICET, Universidad Nacional de Cordoba, the Inter-American Institute for Global Change Research, and The Newton Fund (NERC UK -CONICET ARG), Díaz, Sandra [0000-0003-0012-4612], Kattge, Jens [0000-0002-1022-8469], Wright, Ian J [0000-0001-8338-9143], Lavorel, Sandra [0000-0002-7300-2811], Dray, Stéphane [0000-0003-0153-1105], Wirth, Christian [0000-0003-2604-8056], Garnier, Eric [0000-0002-9392-5154], Westoby, Mark [0000-0001-7690-4530], Reich, Peter B [0000-0003-4424-662X], Moles, Angela T [0000-0003-2041-7762], Zanne, Amy E [0000-0001-6379-9452], Chave, Jérôme [0000-0002-7766-1347], Wright, S Joseph [0000-0003-4260-5676], Sheremetiev, Serge N [0000-0002-0318-6766], Baraloto, Christopher [0000-0001-7322-8581], Cerabolini, Bruno EL [0000-0002-3793-0733], Casanoves, Fernando [0000-0001-8765-9382], Joswig, Julia S [0000-0002-7786-1728], Mahecha, Miguel D [0000-0003-3031-613X], Atkin, Owen K [0000-0003-1041-5202], Bahn, Michael [0000-0001-7482-9776], Bond, William [0000-0002-3441-2084], Bond-Lamberty, Ben [0000-0001-9525-4633], Byun, Chaeho [0000-0003-3209-3275], Campetella, Giandiego [0000-0001-6126-522X], Cavender-Bares, Jeannine [0000-0003-3375-9630], Chapin, F Stuart [0000-0002-2558-9910], Choat, Brendan [0000-0002-9105-640X], Coomes, David Anthony [0000-0002-8261-2582], Cornwell, William K [0000-0003-4080-4073], Craine, Joseph [0000-0001-6561-3244], Craven, Dylan [0000-0003-3940-833X], Dainese, Matteo [0000-0001-7052-5572], Domingues, Tomas Ferreira [0000-0003-2857-9838], Enquist, Brian J [0000-0002-6124-7096], Gallagher, Rachael [0000-0002-4680-8115], Harrison, Sandy P [0000-0001-5687-1903], Hattingh, Wesley Neil [0000-0002-3626-5137], He, Tianhua [0000-0002-0924-3637], Higuchi, Pedro [0000-0002-3855-555X], Jackson, Robert B [0000-0001-8846-7147], Jansen, Steven [0000-0002-4476-5334], Kreft, Holger [0000-0003-4471-8236], Kühn, Ingolf [0000-0003-1691-8249], Kurokawa, Hiroko [0000-0001-8778-8045], Laughlin, Daniel C [0000-0002-9651-5732], Manning, Peter [0000-0002-7940-2023], Mencuccini, Maurizio [0000-0003-0840-1477], Müller, Sandra [0000-0003-4289-755X], Pausas, Juli G [0000-0003-3533-5786], Penuelas, Josep [0000-0002-7215-0150], Pillar, Valério D [0000-0001-6408-2891], Sack, Lawren [0000-0002-7009-7202], Salinas, Norma [0000-0001-9941-2109], Sardans, Jordi [0000-0003-2478-0219], Scherer-Lorenzen, Michael [0000-0001-9566-590X], Sosinski, Ênio [0000-0001-6310-9474], Spasojevic, Marko J [0000-0003-1808-0048], Weigelt, Patrick [0000-0002-2485-3708], Williams, Mathew [0000-0001-6117-5208], Zotz, Gerhard [0000-0002-6823-2268], Apollo - University of Cambridge Repository, Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS), Diaz, S, Kattge, J, Cornelissen, JHC, Wright, IJ, Lavorel, S, Dray, S, Reu, B, Kleyer, M, Wirth, C, Prentice, IC, Garnier, E, Bonisch, G, Westoby, M, Poorter, H, Reich, PB, Moles, AT, Dickie, J, Zanne, AE, Chave, J, Wright, SJ, Sheremetiev, SN, Jactel, H, Baraloto, C, Cerabolini, BEL, Pierce, S, Shipley, B, Casanoves, F, Joswig, JS, Gunther, A, Falczuk, V, Ruger, N, Mahecha, MD, Gorne, LD, Amiaud, B, Atkin, OK, Bahn, M, Baldocchi, D, Beckmann, M, Blonder, B, Bond, W, Bond-Lamberty, B, Brown, K, Burrascano, S, Byun, C, Campetella, G, Cavender-Bares, J, Chapin, FS, Choat, B, Coomes, DA, Cornwell, WK, Craine, J, Craven, D, Dainese, M, de Araujo, AC, de Vries, FT, Domingues, TF, Enquist, BJ, Fagundez, J, Fang, J, Fernandez-Mendez, F, Fernandez-Piedade, MT, Ford, H, Forey, E, Freschet, GT, Gachet, S, Gallagher, R, Green, W, Guerin, GR, Gutierrez, AG, Harrison, SP, Hattingh, WN, He, T, Hickler, T, Higgins, SI, Higuchi, P, Ilic, J, Jackson, RB, Jalili, A, Jansen, S, Koike, F, Konig, C, Kraft, N, Kramer, K, Kreft, H, Kuhn, I, Kurokawa, H, Lamb, EG, Laughlin, DC, Leishman, M, Lewis, S, Louault, F, Malhado, ACM, Manning, P, Meir, P, Mencuccini, M, Messier, J, Miller, R, Minden, V, Molofsky, J, Montgomery, R, Montserrat-Marti, G, Moretti, M., Muller, S, Niinemets, U, Ogaya, R, Ollerer, K, Onipchenko, V, Onoda, Y, Ozinga, WA, Pausas, JG, Peco, B, Penuelas, J, Pillar, VD, Pladevall, C, Romermann, C, Sack, L, Salinas, N, Sandel, B, Sardans, J, Schamp, B, Scherer-Lorenzen, M, Schulze, ED, Schweingruber, F, Shiodera, S, Sosinski, E, SOUDZILOVSKAIA, Nadia, Spasojevic, MJ, Swaine, E, Swenson, N, Tautenhahn, S, Thompson, K, Totte, A, Urrutia-Jalabert, R, Valladares, F, van Bodegom, P, Vasseur, F, Verheyen, K, Vile, D, Violle, C, von Holle, B, Weigelt, P, Weiher, E, Wiemann, MC, Williams, M, Wright, J, Zotz, G, and Systems Ecology
Subjects: Statistics and Probability, Data Descriptor, [SDV]Life Sciences [q-bio], Bos- en Landschapsecologie, Library and Information Sciences, Education, SIZE-REDUCTION, QUERCUS-ILEX, WIDE-RANGE, Life Science, Forest and Landscape Ecology, Macroecology, Vegetatie, Vegetation, ENVIRONMENT RELATIONSHIPS, 3103 Ecology, Biology and Life Sciences, Biodiversity, 3108 Plant Biology, Computer Science Applications, Biogeography, 631/158/852, FOLIAR NITROGEN ISOTOPES, 631/158/851, [SDE]Environmental Sciences, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, LEAF ECONOMICS SPECTRUM, Statistics, Probability and Uncertainty, data-descriptor, ELEVATED CO2, WOODY-PLANTS, PHOTOSYNTHETIC CAPACITY, 631/158/670, RELATIVE GROWTH-RATE, Information Systems, 31 Biological Sciences
Abstract: [Abstract] Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date. The study has been supported by the TRY initiative on plant traits (https://www.try-db.org). TRY is an initiative of the Max Planck Institute for Biogeochemistry, bioDISCOVERY/Future Earth (ICSU), the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and Núcleo DiverSus (CONICET- Universidad Nacional de Córdoba, Argentina). The Global Spectrum of Plant Form and Function study has been supported by the European BACI project (Towards a Biosphere Atmosphere change Index, EU grant ID 640176), and grants to SD by FONCyT, CONICET, Universidad Nacional de Córdoba, the Inter-American Institute for Global Change Research, and The Newton Fund (NERC UK – CONICET ARG). VO thanks RSF (#19-14-00038p). Open Access funding enabled and organized by Projekt DEAL
Published: 2022
Full Text: View/download PDF

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Region

Database

Publisher

165 results on '"Baraloto C."'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources