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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. 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

4. Offset integrity reduces environmental risk: Using lessons from biodiversity and carbon offsetting to inform water quality offsetting in the catchments of the Great Barrier Reef.

Author: McMahon JM, Turner RDR, Smart JCR, Shortle JS, Ramsay I, Correa DF, Chamberlain D, Mao Y, and Warne MSJ
Subjects: Environmental Monitoring, Australia, Carbon analysis, Conservation of Natural Resources methods, Water Pollution prevention & control, Nitrogen analysis, Water Quality, Biodiversity, Coral Reefs
Abstract: Environmental offsetting has been developed as a mechanism to facilitate the benefits from economic development while avoiding or minimizing environmental harm. This is achieved by compensating for environmental impacts at one location by generating equivalent environmental improvements elsewhere. However, experience with biodiversity and carbon offsetting indicates it can be difficult to ensure the integrity of offsets. Under recent legislation in the catchments of the Great Barrier Reef (GBR), Australia, it is mandatory for water quality emissions from new or expanded point source development to be offset by reducing pollution elsewhere, frequently through reducing non-point source pollution (NPSP). Therefore, informed by experience with biodiversity and carbon offsetting, we summarised sources of uncertainty in NPSP reduction that would influence water quality offset integrity; estimated the maximum potential demand for water quality offsets from sewage treatment plants, the largest point source emitter of total nitrogen (TN) in the GBR catchments, between 2018 and 2050; and discussed the implications of both on the ability of offsetting to counterbalance the impact of economic development in catchments where nitrogen loads have a large influence on the health of important GBR ecosystems. The catchments surrounding the population centres of Cairns and Mackay had both a potentially high future demand for nitrogen water quality offsets and nitrogen loads with a strong influence on the health of the GBR. Consequently, any low integrity water quality offsets in these catchments could jeopardise progress toward the water quality improvements needed to ensure the continued health of the GBR. Water quality offsetting has numerous strengths as a policy instrument however substantial uncertainties remain related to environmental outcomes. Until further research can reduce these uncertainties, water quality offsets that are implemented near increased point source emissions and have a high certainty of effectiveness may provide a balance between scientific rigour and policy workability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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5. The biogeography of the Amazonian tree flora.

Author: Luize BG, Tuomisto H, Ekelschot R, Dexter KG, Amaral ILD, Coelho LS, Matos FDA, Lima Filho DA, Salomão RP, Wittmann F, Castilho CV, Carim MJV, Guevara JE, Phillips OL, Magnusson WE, Sabatier D, Cardenas Revilla JD, Molino JF, Irume MV, Martins MP, Guimarães JRDS, Ramos JF, Bánki OS, Piedade MTF, Cárdenas López D, Pitman NCA, Demarchi LO, Schöngart J, de Leão Novo EMM, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Honorio Coronado EN, Mendoza AM, Montero JC, Costa FRC, Feldpausch TR, Quaresma AC, Castaño Arboleda N, Zartman CE, Killeen TJ, Marimon BS, Marimon BH, Vasquez R, Mostacedo B, Assis RL, Baraloto C, do Amaral DD, Engel J, Petronelli P, Castellanos H, de Medeiros MB, Simon MF, Andrade A, Camargo JL, Laurance WF, Laurance SGW, Rincón LM, Schietti J, Sousa TR, Mori GB, Farias ES, Lopes MA, Magalhães JLL, Nascimento HEM, de Queiroz HL, Vasconcelos CC, Aymard C GA, Brienen R, Stevenson PR, Araujo-Murakami A, Cintra BBL, Baker TR, Feitosa YO, Mogollón HF, Duivenvoorden JF, Peres CA, Silman MR, Ferreira LV, Lozada JR, Comiskey JA, de Toledo JJ, Damasco G, Dávila N, Draper FC, García-Villacorta R, Lopes A, Vicentini A, Valverde FC, Alonso A, Arroyo L, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, Noronha JC, de Aguiar DPP, Barbosa FR, Bredin YK, Carpanedo RS, Carvalho FA, Souza FC, Feeley KJ, Gribel R, Haugaasen T, Hawes JE, Pansonato MP, Pipoly JJ 3rd, Paredes MR, Rodrigues DJ, Barlow J, Berenguer E, da Silva IB, Ferreira MJ, Ferreira J, Fine PVA, Guedes MC, Levis C, Licona JC, Villa Zegarra BE, Vos VA, Cerón C, Durgante FM, Fonty É, Henkel TW, Householder JE, Huamantupa-Chuquimaco I, Silveira M, Stropp J, Thomas R, Daly D, Milliken W, Molina GP, Pennington T, Vieira ICG, Albuquerque BW, Campelo W, Fuentes A, Klitgaard B, Pena JLM, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, Pereira LO, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Balee W, Barbosa EM, Bonates LCM, Dávila Doza HP, Zárate Gómez R, Gonzales T, Gallardo Gonzales GP, Hoffman B, Junqueira AB, Malhi Y, Miranda IPA, Pinto LFM, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent S, Zent EL, Endara MJ, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Monteiro Flores B, Galbraith D, Holmgren M, Kalamandeen M, Lobo G, Torres Montenegro L, Nascimento MT, Oliveira AA, Pombo MM, Ramirez-Angulo H, Rocha M, Scudeller VV, Umaña MN, van der Heijden G, Vilanova Torre E, Vargas TM, Ahuite Reategui MA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Parada GA, Torres-Lezama A, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Fortier RP, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valderrama Sandoval EH, Valenzuela Gamarra L, Hirota M, Palma-Silva C, and Ter Steege H
Subjects: Brazil, Biodiversity, Forests, Soil chemistry, Geography, Phylogeography, Trees
Abstract: We describe the geographical variation in tree species composition across Amazonian forests and show how environmental conditions are associated with species turnover. Our analyses are based on 2023 forest inventory plots (1 ha) that provide abundance data for a total of 5188 tree species. Within-plot species composition reflected both local environmental conditions (especially soil nutrients and hydrology) and geographical regions. A broader-scale view of species turnover was obtained by interpolating the relative tree species abundances over Amazonia into 47,441 0.1-degree grid cells. Two main dimensions of spatial change in tree species composition were identified. The first was a gradient between western Amazonia at the Andean forelands (with young geology and relatively nutrient-rich soils) and central-eastern Amazonia associated with the Guiana and Brazilian Shields (with more ancient geology and poor soils). The second gradient was between the wet forests of the northwest and the drier forests in southern Amazonia. Isolines linking cells of similar composition crossed major Amazonian rivers, suggesting that tree species distributions are not limited by rivers. Even though some areas of relatively sharp species turnover were identified, mostly the tree species composition changed gradually over large extents, which does not support delimiting clear discrete biogeographic regions within Amazonia., (© 2024. The Author(s).)
Published: 2024
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6. One sixth of Amazonian tree diversity is dependent on river floodplains.

Author: Householder JE, Wittmann F, Schöngart J, Piedade MTF, Junk WJ, Latrubesse EM, Quaresma AC, Demarchi LO, de S Lobo G, Aguiar DPP, Assis RL, Lopes A, Parolin P, Leão do Amaral I, Coelho LS, de Almeida Matos FD, Lima Filho DA, Salomão RP, Castilho CV, Guevara-Andino JE, Carim MJV, Phillips OL, Cárdenas López D, Magnusson WE, Sabatier D, Revilla JDC, Molino JF, Irume MV, Martins MP, Guimarães JRDS, Ramos JF, Rodrigues DJ, Bánki OS, Peres CA, Pitman NCA, Hawes JE, Almeida EJ, Barbosa LF, Cavalheiro L, Dos Santos MCV, Luize BG, Novo EMML, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Costa FRC, Honorio Coronado EN, Monteagudo Mendoza A, Montero JC, Feldpausch TR, Aymard C GA, Baraloto C, Castaño Arboleda N, Engel J, Petronelli P, Zartman CE, Killeen TJ, Rincón LM, Marimon BS, Marimon-Junior BH, Schietti J, Sousa TR, Vasquez R, Mostacedo B, Dantas do Amaral D, Castellanos H, Medeiros MB, Simon MF, Andrade A, Camargo JL, Laurance WF, Laurance SGW, Farias ES, Lopes MA, Magalhães JLL, Mendonça Nascimento HE, Queiroz HL, Brienen R, Stevenson PR, Araujo-Murakami A, Baker TR, Cintra BBL, Feitosa YO, Mogollón HF, Noronha JC, Barbosa FR, de Sá Carpanedo R, Duivenvoorden JF, Silman MR, Ferreira LV, Levis C, Lozada JR, Comiskey JA, Draper FC, Toledo JJ, Damasco G, Dávila N, García-Villacorta R, Vicentini A, Cornejo Valverde F, Alonso A, Arroyo L, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, Carvalho FA, Coelho de Souza F, Feeley KJ, Gribel R, Pansonato MP, Ríos Paredes M, Barlow J, Berenguer E, Dexter KG, Ferreira J, Fine PVA, Guedes MC, Huamantupa-Chuquimaco I, Licona JC, Pennington T, Villa Zegarra BE, Vos VA, Cerón C, Fonty É, Henkel TW, Maas P, Pos E, Silveira M, Stropp J, Thomas R, Daly D, Milliken W, Pardo Molina G, Vieira ICG, Albuquerque BW, Campelo W, Emilio T, Fuentes A, Klitgaard B, Marcelo Pena JL, Souza PF, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, Pereira LO, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Balee W, Barbosa EM, Bonates LCM, Doza HPD, Gómez RZ, Gonzales T, Gonzales GPG, Hoffman B, Junqueira AB, Malhi Y, Miranda IPA, Mozombite-Pinto LF, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent S, Zent EL, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Flores BM, Galbraith D, Holmgren M, Kalamandeen M, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña MN, van der Heijden G, Vilanova Torre E, Ahuite Reategui MA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Parada GA, Torres-Lezama A, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valderrama Sandoval EH, Valenzuela Gamarra L, and Ter Steege H
Subjects: Brazil, Forests, Biodiversity, Trees, Rivers, Floods
Abstract: Amazonia's floodplain system is the largest and most biodiverse on Earth. Although forests are crucial to the ecological integrity of floodplains, our understanding of their species composition and how this may differ from surrounding forest types is still far too limited, particularly as changing inundation regimes begin to reshape floodplain tree communities and the critical ecosystem functions they underpin. Here we address this gap by taking a spatially explicit look at Amazonia-wide patterns of tree-species turnover and ecological specialization of the region's floodplain forests. We show that the majority of Amazonian tree species can inhabit floodplains, and about a sixth of Amazonian tree diversity is ecologically specialized on floodplains. The degree of specialization in floodplain communities is driven by regional flood patterns, with the most compositionally differentiated floodplain forests located centrally within the fluvial network and contingent on the most extraordinary flood magnitudes regionally. Our results provide a spatially explicit view of ecological specialization of floodplain forest communities and expose the need for whole-basin hydrological integrity to protect the Amazon's tree diversity and its function., (© 2024. The Author(s).)
Published: 2024
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7. Author Correction: One sixth of Amazonian tree diversity is dependent on river floodplains.

Author: Householder JE, Wittmann F, Schöngart J, Piedade MTF, Junk WJ, Latrubesse EM, Quaresma AC, Demarchi LO, de S Lobo G, Aguiar DPP, Assis RL, Lopes A, Parolin P, Leão do Amaral I, Coelho LS, de Almeida Matos FD, Lima Filho DA, Salomão RP, Castilho CV, Guevara-Andino JE, Carim MJV, Phillips OL, Cárdenas López D, Magnusson WE, Sabatier D, Revilla JDC, Molino JF, Irume MV, Martins MP, Guimarães JRDS, Ramos JF, Rodrigues DJ, Bánki OS, Peres CA, Pitman NCA, Hawes JE, Almeida EJ, Barbosa LF, Cavalheiro L, Dos Santos MCV, Luize BG, Novo EMML, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Costa FRC, Honorio Coronado EN, Monteagudo Mendoza A, Montero JC, Feldpausch TR, Aymard C GA, Baraloto C, Castaño Arboleda N, Engel J, Petronelli P, Zartman CE, Killeen TJ, Rincón LM, Marimon BS, Marimon-Junior BH, Schietti J, Sousa TR, Vasquez R, Mostacedo B, Dantas do Amaral D, Castellanos H, Medeiros MB, Simon MF, Andrade A, Camargo JL, Laurance WF, Laurance SGW, Farias ES, Lopes MA, Magalhães JLL, Mendonça Nascimento HE, Queiroz HL, Brienen R, Stevenson PR, Araujo-Murakami A, Baker TR, Cintra BBL, Feitosa YO, Mogollón HF, Noronha JC, Barbosa FR, de Sá Carpanedo R, Duivenvoorden JF, Silman MR, Ferreira LV, Levis C, Lozada JR, Comiskey JA, Draper FC, Toledo JJ, Damasco G, Dávila N, García-Villacorta R, Vicentini A, Cornejo Valverde F, Alonso A, Arroyo L, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, Carvalho FA, Coelho de Souza F, Feeley KJ, Gribel R, Pansonato MP, Ríos Paredes M, Barlow J, Berenguer E, Dexter KG, Ferreira J, Fine PVA, Guedes MC, Huamantupa-Chuquimaco I, Licona JC, Pennington T, Villa Zegarra BE, Vos VA, Cerón C, Fonty É, Henkel TW, Maas P, Pos E, Silveira M, Stropp J, Thomas R, Daly D, Milliken W, Pardo Molina G, Vieira ICG, Albuquerque BW, Campelo W, Emilio T, Fuentes A, Klitgaard B, Marcelo Pena JL, Souza PF, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, Pereira LO, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Balee W, Barbosa EM, Bonates LCM, Doza HPD, Gómez RZ, Gonzales T, Gonzales GPG, Hoffman B, Junqueira AB, Malhi Y, Miranda IPA, Mozombite-Pinto LF, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent S, Zent EL, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Flores BM, Galbraith D, Holmgren M, Kalamandeen M, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña MN, van der Heijden G, Vilanova Torre E, Ahuite Reategui MA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Parada GA, Torres-Lezama A, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valderrama Sandoval EH, Valenzuela Gamarra L, and Ter Steege H
Published: 2024
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8. Consistent patterns of common species across tropical tree communities.

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

Author: Lopera Valle JS, Puello Correa DF, and Sanín E
Abstract: Objective: This study aimed to evaluate the overall survival of hepatocellular carcinoma patients who qualify for transarterial chemoembolization (TACE) using the "six-and-twelve" prognostic score. The research was conducted on a patient cohort between 2009 and 2019., Materials and Methods: A retrospective cohort study was conducted, involving patients diagnosed with unresectable hepatocarcinoma, Barcelona Clinic Liver Cancer (BCLC) staging A or B, and Child-Pugh staging A or B. Exclusion criteria included patients with spontaneous tumor rupture, other neoplasms, decompensated liver cirrhosis, and a lack of reference images. The study assessed the size of the largest nodule and the number of tumors based on imaging studies. Overall survival was defined as the time from initial TACE to death from any cause, with telephonic follow-up conducted. Patients were categorized into three groups based on tumor burden: ≤6, >6-≤12, and >12. Mortality rates at 12, 24, and 36 months were compared using the chi-square test for categorical variables and the ANOVA and Kruskal-Wallis tests for continuous variables, depending on their distribution., Results: A total of 90 patients were included in the study, with a median age of 69 years (interquartile range (IQR): 62-77). Among the patients, 61.1% had a tumor burden of six or less. The overall survival rate was found to have a median of 28.4 months (IQR: 26.3-30.5), with survival rates at one, two, and three years being 84.7%, 55.2%, and 29.4%, respectively. It was observed that mortality increased in proportion to tumor burden, and this difference was statistically significant., Conclusion: The use of tumor burden, with cut-off points of six and 12, as a prognostic score proved to be a valuable tool for predicting mortality in the studied cohort., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Lopera Valle et al.)
Published: 2023
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10. Mapping density, diversity and species-richness of the Amazon tree flora.

Author: Ter Steege H, Pitman NCA, do Amaral IL, de Souza Coelho L, de Almeida Matos FD, de Andrade Lima Filho D, Salomão RP, Wittmann F, Castilho CV, Guevara JE, Veiga Carim MJ, Phillips OL, Magnusson WE, Sabatier D, Revilla JDC, Molino JF, Irume MV, Martins MP, da Silva Guimarães JR, Ramos JF, Bánki OS, Piedade MTF, Cárdenas López D, Rodrigues DJ, Demarchi LO, Schöngart J, Almeida EJ, Barbosa LF, Cavalheiro L, Dos Santos MCV, Luize BG, de Leão Novo EMM, Vargas PN, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Honorio Coronado EN, Monteagudo Mendoza A, Montero JC, Costa FRC, Feldpausch TR, Quaresma AC, Castaño Arboleda N, Zartman CE, Killeen TJ, Marimon BS, Marimon-Junior BH, Vasquez R, Mostacedo B, Assis RL, Baraloto C, do Amaral DD, Engel J, Petronelli P, Castellanos H, de Medeiros MB, Simon MF, Andrade A, Camargo JL, Laurance WF, Laurance SGW, Maniguaje Rincón L, Schietti J, Sousa TR, de Sousa Farias E, Lopes MA, Magalhães JLL, Nascimento HEM, de Queiroz HL, Aymard C GA, Brienen R, Stevenson PR, Araujo-Murakami A, Baker TR, Cintra BBL, Feitosa YO, Mogollón HF, Duivenvoorden JF, Peres CA, Silman MR, Ferreira LV, Lozada JR, Comiskey JA, Draper FC, de Toledo JJ, Damasco G, García-Villacorta R, Lopes A, Vicentini A, Cornejo Valverde F, Alonso A, Arroyo L, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, Noronha JC, de Aguiar DPP, Barbosa FR, Bredin YK, de Sá Carpanedo R, Carvalho FA, de Souza FC, Feeley KJ, Gribel R, Haugaasen T, Hawes JE, Pansonato MP, Ríos Paredes M, Barlow J, Berenguer E, da Silva IB, Ferreira MJ, Ferreira J, Fine PVA, Guedes MC, Levis C, Licona JC, Villa Zegarra BE, Vos VA, Cerón C, Durgante FM, Fonty É, Henkel TW, Householder JE, Huamantupa-Chuquimaco I, Pos E, Silveira M, Stropp J, Thomas R, Daly D, Dexter KG, Milliken W, Molina GP, Pennington T, Vieira ICG, Weiss Albuquerque B, Campelo W, Fuentes A, Klitgaard B, Pena JLM, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, de Oliveira Pereira L, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Balee W, Barbosa EM, de Matos Bonates LC, Dávila Doza HP, Zárate Gómez R, Gonzales T, Gallardo Gonzales GP, Hoffman B, Junqueira AB, Malhi Y, de Andrade Miranda IP, Pinto LFM, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent EL, Zent S, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Flores BM, Galbraith D, Holmgren M, Kalamandeen M, Lobo G, Torres Montenegro L, Nascimento MT, Oliveira AA, Pombo MM, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña MN, van der Heijden G, Vilanova Torre E, Reategui MAA, Baider C, Balslev H, Cárdenas S, Casas LF, Endara MJ, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Parada GA, Torres-Lezama A, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Cuenca WP, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valderrama Sandoval EH, Gamarra LV, Levesley A, Pickavance G, and Melgaço K
Subjects: Forests, Soil, Temperature, Trees, RNA, Long Noncoding
Abstract: Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution., (© 2023. The Author(s).)
Published: 2023
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11. More than 10,000 pre-Columbian earthworks are still hidden throughout Amazonia.

Author: Peripato V, Levis C, Moreira GA, Gamerman D, Ter Steege H, Pitman NCA, de Souza JG, Iriarte J, Robinson M, Junqueira AB, Trindade TB, de Almeida FO, Moraes CP, Lombardo U, Tamanaha EK, Maezumi SY, Ometto JPHB, Braga JRG, Campanharo WA, Cassol HLG, Leal PR, de Assis MLR, da Silva AM, Phillips OL, Costa FRC, Flores BM, Hoffman B, Henkel TW, Umaña MN, Magnusson WE, Valderrama Sandoval EH, Barlow J, Milliken W, Lopes MA, Simon MF, van Andel TR, Laurance SGW, Laurance WF, Torres-Lezama A, Assis RL, Molino JF, Mestre M, Hamblin M, Coelho LS, Lima Filho DA, Wittmann F, Salomão RP, Amaral IL, Guevara JE, de Almeida Matos FD, Castilho CV, Carim MJV, Cárdenas López D, Sabatier D, Irume MV, Martins MP, Guimarães JRDS, Bánki OS, Piedade MTF, Ramos JF, Luize BG, Novo EMML, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Demarchi LO, Honorio Coronado EN, Monteagudo Mendoza A, Montero JC, Schöngart J, Feldpausch TR, Quaresma AC, Aymard C GA, Baraloto C, Castaño Arboleda N, Engel J, Petronelli P, Zartman CE, Killeen TJ, Marimon BS, Marimon-Junior BH, Schietti J, Sousa TR, Vasquez R, Rincón LM, Berenguer E, Ferreira J, Mostacedo B, do Amaral DD, Castellanos H, de Medeiros MB, Andrade A, Camargo JL, Farias ES, Magalhães JLL, Mendonça Nascimento HE, de Queiroz HL, Brienen R, Cardenas Revilla JD, Stevenson PR, Araujo-Murakami A, Barçante Ladvocat Cintra B, Feitosa YO, Barbosa FR, Carpanedo RS, Duivenvoorden JF, de Noronha JDC, Rodrigues DJ, Mogollón HF, Ferreira LV, Householder JE, Lozada JR, Comiskey JA, Draper FC, de Toledo JJ, Damasco G, Dávila N, García-Villacorta R, Lopes A, Cornejo Valverde F, Alonso A, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, de Aguiar DPP, Arroyo L, Antunes Carvalho F, Coelho de Souza F, Feeley KJ, Gribel R, Pansonato MP, Ríos Paredes M, Brasil da Silva I, Ferreira MJ, Fine PVA, Fonty É, Guedes MC, Licona JC, Pennington T, Peres CA, Villa Zegarra BE, Parada GA, Pardo Molina G, Vos VA, Cerón C, Maas P, Silveira M, Stropp J, Thomas R, Baker TR, Daly D, Huamantupa-Chuquimaco I, Vieira ICG, Weiss Albuquerque B, Fuentes A, Klitgaard B, Marcelo-Peña JL, Silman MR, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, Phillips JF, Rivas-Torres G, von Hildebrand P, Pereira LO, Barbosa EM, de Matos Bonates LC, Doza HPD, Zárate Gómez R, Gallardo Gonzales GP, Gonzales T, Malhi Y, de Andrade Miranda IP, Mozombite Pinto LF, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent EL, Zent S, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Galbraith D, Holmgren M, Kalamandeen M, Lobo G, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, van der Heijden G, Vilanova Torre E, Ahuite Reategui MA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valenzuela Gamarra L, and Aragão LEOC
Subjects: Humans, Brazil, Forests, Archaeology
Abstract: Indigenous societies are known to have occupied the Amazon basin for more than 12,000 years, but the scale of their influence on Amazonian forests remains uncertain. We report the discovery, using LIDAR (light detection and ranging) information from across the basin, of 24 previously undetected pre-Columbian earthworks beneath the forest canopy. Modeled distribution and abundance of large-scale archaeological sites across Amazonia suggest that between 10,272 and 23,648 sites remain to be discovered and that most will be found in the southwest. We also identified 53 domesticated tree species significantly associated with earthwork occurrence probability, likely suggesting past management practices. Closed-canopy forests across Amazonia are likely to contain thousands of undiscovered archaeological sites around which pre-Columbian societies actively modified forests, a discovery that opens opportunities for better understanding the magnitude of ancient human influence on Amazonia and its current state.
Published: 2023
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12. Beyond ecology: ecosystem restoration as a process for social-ecological transformation.

Author: Tedesco AM, López-Cubillos S, Chazdon R, Rhodes JR, Archibald CL, Pérez-Hämmerle KV, Brancalion PHS, Wilson KA, Oliveira M, Correa DF, Ota L, Morrison TH, Possingham HP, Mills M, Santos FC, and Dean AJ
Subjects: Humans, Ecology, Ecosystem, Conservation of Natural Resources methods
Abstract: Ecosystem restoration conventionally focuses on ecological targets. However, while ecological targets are crucial to mobilizing political, social, and financial capital, they do not encapsulate the need to: integrate social, economic, and ecological dimensions and systems approaches; reconcile global targets and local objectives; and measure the rate of progress toward multiple and synergistic goals. Restoration is better conceived as an inclusive social-ecological process that integrates diverse values, practices, knowledge, and restoration objectives across temporal and spatial scales and stakeholder groups. Taking a more process-based approach will ultimately enable greater social-ecological transformation, greater restoration effectiveness, and more long-lasting benefits to people and nature across time and place., Competing Interests: Declaration of interests None declared by authors., (Copyright © 2023 Elsevier Ltd. All rights reserved.)
Published: 2023
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13. Hepatitis A seroprevalence among special populations in the Rio de Janeiro Metropolitan Area, Brazil.

Author: Carvalho F, Brandão LGP, Varela MC, Tuyama M, Correa DF, Santos ATDS, Lemos ADS, Costa MDD, Cerbino-Neto J, and Brasil PEAAD
Subjects: Pregnancy, Female, Humans, Seroepidemiologic Studies, Brazil epidemiology, Retrospective Studies, Parturition, Acquired Immunodeficiency Syndrome
Abstract: The objectives were to estimate hepatitis A virus seroprevalence in subjects attending to a travel medicine and immunization clinic in Rio de Janeiro, Brazil, and to develop a prediction model for hepatitis A virus seroprevalence. This retrospective research included individuals sequentially from April 2011 to June 2019 at a travel medicine and special population immunization clinic with an anti-hepatitis A virus IgG chemiluminescence result. Participants' data were verified via electronic medical records. Data were split into development and validation set taking 2018 as the date break. A cross-validated elastic generalized linear model with binomial distribution was performed. In total, 2,944 subjects were analyzed. Hepatitis A virus overall seroprevalence was 67.8%. Health professionals, travelers, and those who had contact with immunocompromised subjects had lower seroprevalence (40%-55%), whereas subjects with chronic conditions (heart, lung, and liver) ranged from 89% to 94%. The retained predictors in the final model were sex, age, year of birth, travelers, HIV/AIDS, spleen dysfunction, transplant candidates, household communicators, cancer-related immunosuppression, health care professionals. Area under the curve was 0.836 and maximum error was 0.051. Users can make predictions with the following calculator: https://pedrobrasil.shinyapps.io/INDWELL/. The groups with lower seroprevalence should be evaluated more carefully regarding need for hepatitis A virus vaccination even when they seek immunization clinics for other purposes.
Published: 2023
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14. Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology.

Author: Pos E, de Souza Coelho L, de Andrade Lima Filho D, Salomão RP, Amaral IL, de Almeida Matos FD, Castilho CV, Phillips OL, Guevara JE, de Jesus Veiga Carim M, López DC, Magnusson WE, Wittmann F, Irume MV, Martins MP, Sabatier D, da Silva Guimarães JR, Molino JF, Bánki OS, Piedade MTF, Pitman NCA, Mendoza AM, Ramos JF, Hawes JE, Almeida EJ, Barbosa LF, Cavalheiro L, Dos Santos MCV, Luize BG, de Leão Novo EMM, Vargas PN, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Coronado ENH, Montero JC, Marimon BS, Marimon-Junior BH, Feldpausch TR, Duque A, Baraloto C, Arboleda NC, Engel J, Petronelli P, Zartman CE, Killeen TJ, Vasquez R, Mostacedo B, Assis RL, Schöngart J, Castellanos H, de Medeiros MB, Simon MF, Andrade A, Camargo JL, Demarchi LO, Laurance WF, Laurance SGW, de Sousa Farias E, Lopes MA, Magalhães JLL, Nascimento HEM, de Queiroz HL, Aymard GAC, Brienen R, Revilla JDC, Costa FRC, Quaresma A, Vieira ICG, Cintra BBL, Stevenson PR, Feitosa YO, Duivenvoorden JF, Mogollón HF, Ferreira LV, Comiskey JA, Draper F, de Toledo JJ, Damasco G, Dávila N, García-Villacorta R, Lopes A, Vicentini A, Noronha JC, Barbosa FR, de Sá Carpanedo R, Emilio T, Levis C, de Jesus Rodrigues D, Schietti J, Souza P, Alonso A, Dallmeier F, Gomes VHF, Lloyd J, Neill D, de Aguiar DPP, Araujo-Murakami A, Arroyo L, Carvalho FA, de Souza FC, do Amaral DD, Feeley KJ, Gribel R, Pansonato MP, Barlow J, Berenguer E, Ferreira J, Fine PVA, Guedes MC, Jimenez EM, Licona JC, Mora MCP, Peres CA, Zegarra BEV, Cerón C, Henkel TW, Maas P, Silveira M, Stropp J, Thomas-Caesar R, Baker TR, Daly D, Dexter KG, Householder JE, Huamantupa-Chuquimaco I, Pennington T, Paredes MR, Fuentes A, Pena JLM, Silman MR, Tello JS, Chave J, Valverde FC, Di Fiore A, Hilário RR, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Barbosa EM, de Matos Bonates LC, Doza HPD, Fonty É, Gómez RZ, Gonzales T, Gonzales GPG, Guillaumet JL, Hoffman B, Junqueira AB, Malhi Y, de Andrade Miranda IP, Pinto LFM, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Vos VA, Zent EL, Zent S, Albuquerque BW, Cano A, Correa DF, Costa JBP, Flores BM, Holmgren M, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña MN, van der Heijden G, Torre EV, Vriesendorp C, Wang O, Young KR, Reategui MAA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Torres-Lezama A, Giraldo LEU, Villarroel D, Zagt R, Alexiades MN, Garcia-Cabrera K, Hernandez L, Milliken W, Cuenca WP, Pansini S, Pauletto D, Arevalo FR, Sampaio AF, Sandoval EHV, Gamarra LV, Boenisch G, Kattge J, Kraft N, Levesley A, Melgaço K, Pickavance G, Poorter L, and Ter Steege H
Subjects: Entropy, Forests, Plants, Ecology, Tropical Climate, Ecosystem, Biodiversity
Abstract: In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics., (© 2023. The Author(s).)
Published: 2023
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15. Generalized Edema and Pseudothrombocytopenia After ChAdOx1 nCoV-19 COVID-19 Vaccination: A Case Report.

Author: Bokel J, Mendes-de-Almeida DP, Martins-Gonçalves R, Palhinha L, Vizzoni AG, Correa DF, Brandão LGP, Bozza PT, and Grinsztejn B
Subjects: COVID-19 Vaccines adverse effects, ChAdOx1 nCoV-19, Edema, Humans, SARS-CoV-2, Vaccination adverse effects, COVID-19 prevention & control, Thrombocytopenia chemically induced, Thrombocytopenia diagnosis
Abstract: Reports of side effects of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are increasing worldwide. Capillary leak syndrome and vaccine-induced immune thrombotic thrombocytopenia are very rare but life-threatening adverse events that should be identified early and treated. However, isolated thrombocytopenia can indicate pseudothrombocytopenia. In certain people, ethylenediaminetetraacetic acid (EDTA) induces an in vitro platelet aggregation, resulting in misleading underestimation of platelet counts. It is essential to recognize pseudothrombocytopenia to prevent diagnostic errors, overtreatment, anxiety, and unnecessary invasive procedures. We present a case who developed generalized edema and persistent pseudothrombocytopenia after the first dose of the ChAdOx1 nCoV-19 vaccine (AstraZeneca)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bokel, Mendes-de-Almeida, Martins-Gonçalves, Palhinha, Vizzoni, Correa, Brandão, Bozza and Grinsztejn.)
Published: 2022
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16. Biased-corrected richness estimates for the Amazonian tree flora.

Author: Ter Steege H, Prado PI, Lima RAF, Pos E, de Souza Coelho L, de Andrade Lima Filho D, Salomão RP, Amaral IL, de Almeida Matos FD, Castilho CV, Phillips OL, Guevara JE, de Jesus Veiga Carim M, Cárdenas López D, Magnusson WE, Wittmann F, Martins MP, Sabatier D, Irume MV, da Silva Guimarães JR, Molino JF, Bánki OS, Piedade MTF, Pitman NCA, Ramos JF, Monteagudo Mendoza A, Venticinque EM, Luize BG, Núñez Vargas P, Silva TSF, de Leão Novo EMM, Reis NFC, Terborgh J, Manzatto AG, Casula KR, Honorio Coronado EN, Montero JC, Duque A, Costa FRC, Castaño Arboleda N, Schöngart J, Zartman CE, Killeen TJ, Marimon BS, Marimon-Junior BH, Vasquez R, Mostacedo B, Demarchi LO, Feldpausch TR, Engel J, Petronelli P, Baraloto C, Assis RL, Castellanos H, Simon MF, de Medeiros MB, Quaresma A, Laurance SGW, Rincón LM, Andrade A, Sousa TR, Camargo JL, Schietti J, Laurance WF, de Queiroz HL, Nascimento HEM, Lopes MA, de Sousa Farias E, Magalhães JLL, Brienen R, Aymard C GA, Revilla JDC, Vieira ICG, Cintra BBL, Stevenson PR, Feitosa YO, Duivenvoorden JF, Mogollón HF, Araujo-Murakami A, Ferreira LV, Lozada JR, Comiskey JA, de Toledo JJ, Damasco G, Dávila N, Lopes A, García-Villacorta R, Draper F, Vicentini A, Cornejo Valverde F, Lloyd J, Gomes VHF, Neill D, Alonso A, Dallmeier F, de Souza FC, Gribel R, Arroyo L, Carvalho FA, de Aguiar DPP, do Amaral DD, Pansonato MP, Feeley KJ, Berenguer E, Fine PVA, Guedes MC, Barlow J, Ferreira J, Villa B, Peñuela Mora MC, Jimenez EM, Licona JC, Cerón C, Thomas R, Maas P, Silveira M, Henkel TW, Stropp J, Paredes MR, Dexter KG, Daly D, Baker TR, Huamantupa-Chuquimaco I, Milliken W, Pennington T, Tello JS, Pena JLM, Peres CA, Klitgaard B, Fuentes A, Silman MR, Di Fiore A, von Hildebrand P, Chave J, van Andel TR, Hilário RR, Phillips JF, Rivas-Torres G, Noronha JC, Prieto A, Gonzales T, de Sá Carpanedo R, Gonzales GPG, Gómez RZ, de Jesus Rodrigues D, Zent EL, Ruschel AR, Vos VA, Fonty É, Junqueira AB, Doza HPD, Hoffman B, Zent S, Barbosa EM, Malhi Y, de Matos Bonates LC, de Andrade Miranda IP, Silva N, Barbosa FR, Vela CIA, Pinto LFM, Rudas A, Albuquerque BW, Umaña MN, Carrero Márquez YA, van der Heijden G, Young KR, Tirado M, Correa DF, Sierra R, Costa JBP, Rocha M, Vilanova Torre E, Wang O, Oliveira AA, Kalamandeen M, Vriesendorp C, Ramirez-Angulo H, Holmgren M, Nascimento MT, Galbraith D, Flores BM, Scudeller VV, Cano A, Ahuite Reategui MA, Mesones I, Baider C, Mendoza C, Zagt R, Urrego Giraldo LE, Ferreira C, Villarroel D, Linares-Palomino R, Farfan-Rios W, Farfan-Rios W, Casas LF, Cárdenas S, Balslev H, Torres-Lezama A, Alexiades MN, Garcia-Cabrera K, Valenzuela Gamarra L, Valderrama Sandoval EH, Ramirez Arevalo F, Hernandez L, Sampaio AF, Pansini S, Palacios Cuenca W, de Oliveira EA, Pauletto D, Levesley A, Melgaço K, and Pickavance G
Subjects: Brazil, Biodiversity, Classification methods, Forests, Rivers, Trees classification
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.
Published: 2020
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17. Species distribution of the main aetiologic agents causing skin dermatophytosis in Colombian patients: A 23-year experience at a Mycological Reference Center.

Author: Carrascal-Correa DF, Zuluaga A, and González A
Subjects: Adolescent, Adult, Aged, Aged, 80 and over, Arthrodermataceae classification, Arthrodermataceae isolation & purification, Child, Child, Preschool, Colombia epidemiology, Dermatomycoses microbiology, Epidermophyton classification, Epidermophyton isolation & purification, Fungi classification, Humans, Infant, Male, Microsporum classification, Microsporum isolation & purification, Middle Aged, Retrospective Studies, Skin microbiology, Skin pathology, Tinea epidemiology, Trichophyton classification, Trichophyton isolation & purification, Young Adult, Dermatomycoses epidemiology, Fungi isolation & purification, Tinea microbiology
Abstract: Background: Dermatophytosis is one of the most frequent superficial mycoses in the world., Main Aim: To describe the cases of skin dermatophytosis and its main aetiologic agents in patients referred to a Mycological Reference Laboratory in Medellín, Colombia., Methods: A retrospective study was carried out with records of patients referred between 1994 and 2016 to the Corporación para Investigaciones Biológicas (CIB), Medellín-Colombia, because of clinical suspicion of skin dermatophytosis., Results: Of a total of 5628 clinical records of patients with suspicion of skin dermatophytosis analysed, 2780 (49.4%) had a proven or probable dermatophytosis diagnosis, 2774 cultures were performed, and aetiologic agents were isolated in 2576 samples (92.9%). The most frequently isolated aetiologic agents were Trichophyton rubrum (44.3%), followed by Trichophyton mentagrophytes complex (33.3%), Epidermophyton floccosum (12.4%), Nannizzia gypseum complex (5.7%, formerly Microsporum gypseum), Microsporum canis (3.5%) and Trichophyton tonsurans (0.8%). The most frequent clinical forms were tinea pedis (72.7%) and tinea corporis (12.7%). In addition, a group of patients (0.9%) developed mixed infections by two dermatophyte agents and another (4.1%) developed infections in more than one anatomical site., Conclusions: The results of the present study are coherent with previous reports where T rubrum and T mentagrophytes complex were the main causative agents of dermatophytosis. However, the increased incidence of N gypsea complex over M canis is worth highlighting., (© 2020 Blackwell Verlag GmbH.)
Published: 2020
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18. Seroprevalence of varicella antibodies in adults without clinical history of disease.

Author: Büchele KS, Correa DF, Tuyama M, Lemos ADS, Costa MDD, Mesquita EC, Costa DMD, Cerbino-Neto J, Varela MC, Brasil PEAAD, and Brandão LGP
Subjects: Adult, Antibodies, Viral blood, Brazil epidemiology, Chickenpox blood, Chickenpox prevention & control, Chickenpox Vaccine, Cross-Sectional Studies, Humans, Luminescent Measurements, Prevalence, Seroepidemiologic Studies, Chickenpox epidemiology, Herpesvirus 3, Human immunology, Immunoglobulin G blood
Abstract: Varicella in adults and immunocompromised patients can be severe. The clinical diagnosis of varicella has high accuracy and the history of disease has a high positive predictive value for protection. A significant portion of adults, however, cannot remember if they have had varicella, especially older individuals. We conducted a cross-sectional study to determine the seroprevalence of varicella protective antibodies titers in adults with no clinical history of disease, attended at a Reference Center for Special Immunobiologicals and Travel Medicine in Rio de Janeiro (Brazil). Titration of immunoglobulin G (IgG) antibodies to varicella-zoster was determined by chemiluminescence immunoassay. Among 140 adults without history of varicella, 92% had protective antibody titers. We concluded that seroprevalence of varicella-zoster protection was very high in adults with negative history of disease and the use of serology before vaccination reduced significantly unnecessary vaccine and immunoglobulin use.
Published: 2020
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19. Rarity of monodominance in hyperdiverse Amazonian forests.

Author: Ter Steege H, Henkel TW, Helal N, Marimon BS, Marimon-Junior BH, Huth A, Groeneveld J, Sabatier D, Coelho LS, Filho DAL, Salomão RP, Amaral IL, Matos FDA, Castilho CV, Phillips OL, Guevara JE, Carim MJV, Cárdenas López D, Magnusson WE, Wittmann F, Irume MV, Martins MP, Guimarães JRDS, Molino JF, Bánki OS, Piedade MTF, Pitman NCA, Mendoza AM, Ramos JF, Luize BG, Moraes de Leão Novo EM, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Honorio Coronado EN, Montero JC, Feldpausch TR, Duque A, Costa FRC, Arboleda NC, Schöngart J, Killeen TJ, Vasquez R, Mostacedo B, Demarchi LO, Assis RL, Baraloto C, Engel J, Petronelli P, Castellanos H, de Medeiros MB, Quaresma A, Simon MF, Andrade A, Camargo JL, Laurance SGW, Laurance WF, Rincón LM, Schietti J, Sousa TR, de Sousa Farias E, Lopes MA, Magalhães JLL, Mendonça Nascimento HE, Lima de Queiroz H, Aymard C GA, Brienen R, Revilla JDC, Vieira ICG, Cintra BBL, Stevenson PR, Feitosa YO, Duivenvoorden JF, Mogollón HF, Araujo-Murakami A, Ferreira LV, Lozada JR, Comiskey JA, de Toledo JJ, Damasco G, Dávila N, Draper F, García-Villacorta R, Lopes A, Vicentini A, Alonso A, Dallmeier F, Gomes VHF, Lloyd J, Neill D, de Aguiar DPP, Arroyo L, Carvalho FA, de Souza FC, do Amaral DD, Feeley KJ, Gribel R, Pansonato MP, Barlow J, Berenguer E, Ferreira J, Fine PVA, Guedes MC, Jimenez EM, Licona JC, Peñuela Mora MC, Villa B, Cerón C, Maas P, Silveira M, Stropp J, Thomas R, Baker TR, Daly D, Dexter KG, Huamantupa-Chuquimaco I, Milliken W, Pennington T, Ríos Paredes M, Fuentes A, Klitgaard B, Pena JLM, Peres CA, Silman MR, Tello JS, Chave J, Cornejo Valverde F, Di Fiore A, Hilário RR, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Noronha JC, Barbosa EM, Barbosa FR, de Matos Bonates LC, Carpanedo RS, Dávila Doza HP, Fonty É, GómeZárate Z R, Gonzales T, Gallardo Gonzales GP, Hoffman B, Junqueira AB, Malhi Y, Miranda IPA, Pinto LFM, Prieto A, Rodrigues DJ, Rudas A, Ruschel AR, Silva N, Vela CIA, Vos VA, Zent EL, Zent S, Weiss Albuquerque B, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Flores BM, Galbraith D, Holmgren M, Kalamandeen M, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña Medina MN, van der Heijden G, Vilanova Torre E, Vriesendorp C, Wang O, Young KR, Ahuite Reategui MA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Torres-Lezama A, Giraldo LEU, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Sandoval EHV, 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
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20. Addressing travelers' perception of risk in pre-travel care: Reports from a travel clinic in Rio de Janeiro, Brazil.

Author: Mesquita EC, Varela MC, Brasil PEAAD, Correa DF, Tuyama M, Carvalho F, Neves ES, Cerbino-Neto J, Lemos ADS, and Costa MDD
Subjects: Adult, Brazil, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Risk Assessment, Socioeconomic Factors, Vaccines administration & dosage, Health Knowledge, Attitudes, Practice, Travel statistics & numerical data, Travel-Related Illness
Abstract: Introduction: Travel medicine is aimed at promoting health risk reduction. However, travelers' perception of risk is subjective and may influence implementation of recommendations. This study reports on travelers' perception of risk, pre-travel characteristics, and recommended interventions., Methods: This is a descriptive cross-sectional study., Results: This study included 111 individuals. Most travelers (74%) perceived their risk as low. Significant differences in travel-related risk perception between practitioners and travelers were observed (Gwet's agreement coefficient [AC1] 0.23; standard error 0.10; 95% confidence interval 0.02-0.44)., Conclusions: Future studies should investigate the relationship between travelers' perception of risk and implementation of recommendations.
Published: 2019
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21. Species Distribution Modelling: Contrasting presence-only models with plot abundance data.

Author: Gomes VHF, IJff SD, Raes N, Amaral IL, Salomão RP, de Souza Coelho L, de Almeida Matos FD, Castilho CV, de Andrade Lima Filho D, López DC, Guevara JE, Magnusson WE, Phillips OL, Wittmann F, de Jesus Veiga Carim M, Martins MP, Irume MV, Sabatier D, Molino JF, Bánki OS, da Silva Guimarães JR, Pitman NCA, Piedade MTF, Mendoza AM, Luize BG, Venticinque EM, de Leão Novo EMM, Vargas PN, Silva TSF, Manzatto AG, Terborgh J, Reis NFC, Montero JC, Casula KR, Marimon BS, Marimon BH, Coronado ENH, Feldpausch TR, Duque A, Zartman CE, Arboleda NC, Killeen TJ, Mostacedo B, Vasquez R, Schöngart J, Assis RL, Medeiros MB, Simon MF, Andrade A, Laurance WF, Camargo JL, Demarchi LO, Laurance SGW, de Sousa Farias E, Nascimento HEM, Revilla JDC, Quaresma A, Costa FRC, Vieira ICG, Cintra BBL, Castellanos H, Brienen R, Stevenson PR, Feitosa Y, Duivenvoorden JF, Aymard C GA, Mogollón HF, Targhetta N, Comiskey JA, Vicentini A, Lopes A, Damasco G, Dávila N, García-Villacorta R, Levis C, Schietti J, Souza P, Emilio T, Alonso A, Neill D, Dallmeier F, Ferreira LV, Araujo-Murakami A, Praia D, do Amaral DD, Carvalho FA, de Souza FC, Feeley K, Arroyo L, Pansonato MP, Gribel R, Villa B, Licona JC, Fine PVA, Cerón C, Baraloto C, Jimenez EM, Stropp J, Engel J, Silveira M, Mora MCP, Petronelli P, Maas P, Thomas-Caesar R, Henkel TW, Daly D, Paredes MR, Baker TR, Fuentes A, Peres CA, Chave J, Pena JLM, Dexter KG, Silman MR, Jørgensen PM, Pennington T, Di Fiore A, Valverde FC, Phillips JF, Rivas-Torres G, von Hildebrand P, van Andel TR, Ruschel AR, Prieto A, Rudas A, Hoffman B, Vela CIA, Barbosa EM, Zent EL, Gonzales GPG, Doza HPD, de Andrade Miranda IP, Guillaumet JL, Pinto LFM, de Matos Bonates LC, Silva N, Gómez RZ, Zent S, Gonzales T, Vos VA, Malhi Y, Oliveira AA, Cano A, Albuquerque BW, Vriesendorp C, Correa DF, Torre EV, van der Heijden G, Ramirez-Angulo H, Ramos JF, Young KR, Rocha M, Nascimento MT, Medina MNU, Tirado M, Wang O, Sierra R, Torres-Lezama A, Mendoza C, Ferreira C, Baider C, Villarroel D, Balslev H, Mesones I, Giraldo LEU, Casas LF, Reategui MAA, Linares-Palomino R, Zagt R, Cárdenas S, Farfan-Rios W, Sampaio AF, Pauletto D, Sandoval EHV, Arevalo FR, Huamantupa-Chuquimaco I, Garcia-Cabrera K, Hernandez L, Gamarra LV, Alexiades MN, Pansini S, Cuenca WP, Milliken W, Ricardo J, Lopez-Gonzalez G, Pos E, and Ter Steege H
Subjects: Brazil, Chrysobalanaceae physiology, Fabaceae physiology, Humans, Polygonaceae physiology, Conservation of Natural Resources statistics & numerical data, Models, Statistical, Plant Dispersal physiology, Trees physiology
Abstract: Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.
Published: 2018
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22. CMV and HSV-2 myeloradiculitis in an HIV infected patient.

Author: Pinto A, Santos E, Correa DF, Escada R, Vorsatz Cde M, Cardoso SW, and Lima MA
Subjects: Cytomegalovirus isolation & purification, DNA, Viral cerebrospinal fluid, Fatal Outcome, Herpesvirus 2, Human isolation & purification, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Radiculopathy virology, AIDS-Related Opportunistic Infections complications, Cytomegalovirus Infections complications, Herpes Simplex complications, Radiculopathy complications
Abstract: While CMV myeloradiculitis is a known complication in AIDS patients with severe immunosuppression, HSV-2 necrotizing myeloradiculitis is rare and often associated with disabling a fatal outcome. We hereby describe a 46 year-old HIV infected patient with profound and sustained immunosuppression who presented with an acute ascending paraparesis and urinary retention. Lumbar spine MRI showed contrast enhancement at the conus medullaris and cauda equine, and both CMV and HSV-2 CSF PCR were positive. Despite treatment, the patient died 20 days later. We review the main diagnostic and therapeutic aspects of herpes virus associated myeloradiculitis and discuss the approach in similar cases.
Published: 2011
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23. [Blackwater fever: a case report].

Author: Olga PS and Correa DF
Subjects: Cuba, Humans, Male, Middle Aged, Blackwater Fever diagnosis
Abstract: The first case of blackwater fever was reported in Cuban medical literature. It is an uncommon complication of paludism due to Plasmodium falciparum, characterized by fever, hemoglobinuria, and kidney failure, with dramatic development and high mortality. The patient came from the People's Republic of Angola, where he stayed 7 years, with history of various episodes of malaria. He was admitted with fever, icterus and thick film test positive for P. falciparum. Treatment with quinine was started, but dark red urine and an increase of icterus were observed 12 hours later. Treatment with quinine was suspended. Red blood cells and platelets were transfused and hemodialysis and plasmapheresis were performed. The patient was discharged 2 weeks later asymptomatic and with negative thick film test. The pathogeny of this disease was discussed, specially kidney failure, making emphasis on the importance of the symptomatic and maintenance treatment in the patient's evolution.
Published: 2003

24. Protein kinases selectively modulate apoptosis in the developing retina in vitro.

Author: Varella MH, Correa DF, Campos CB, Chiarini LB, and Linden R
Subjects: 2-Aminopurine pharmacology, Animals, Animals, Newborn physiology, Antimetabolites pharmacology, Cyclic AMP metabolism, Cyclic AMP-Dependent Protein Kinases physiology, Embryo, Mammalian physiology, Enzyme Inhibitors pharmacology, In Vitro Techniques, Phosphodiesterase Inhibitors pharmacology, Protein Kinase Inhibitors, Rats, Retina cytology, Aging physiology, Apoptosis physiology, Protein Kinases physiology, Retina physiology
Abstract: In the retina of newborn rats there is evidence for two mechanisms of programmed cell death. Apoptosis of ganglion cells (RGCs) following axotomy depends on protein synthesis. In contrast, inhibition of protein synthesis leads to apoptosis in the neuroblastic layer (NBL). The induction of apoptosis following translational arrest suggests that post-translational modifications of apoptosis-associated proteins may be crucial to the cell death programs in the developing retina. We investigated the possible role of protein kinases upon apoptosis in retinal explants in vitro. An increase in the intracellular concentration of cAMP produced either by the adenylyl-cyclase activator forskolin (10 microM) or by 8-Br-cAMP (1 mM), prevented apoptosis induced in the NBL by inhibition of protein synthesis, but had no statistically significant effect upon RGC death. In contrast, neither 8-Br-cGMP (1 mM) nor the specific cGMP-phosphodiesterase inhibitor zaprinast (10-100 microM) had significant effects on apoptosis in the retina. The cAMP-phosphodiesterase inhibitors isobutylmethylxantine (IBMX, 0.1-1 mM) and Ro-201724 (50-200 microM) also prevented apoptosis in the NBL. The isoquinolinesulfonamide H89 (20 microM), a specific cAMP-dependent protein kinase inhibitor, partially reverted the protective effect of either forskolin or IBMX within the NBL. Neither 12-O-tetradecanoyl phorbol-13-acetate (TPA, 10 nM) nor bisindolylmaleimide (0.2-0.5 microM), respectively an activator and an inhibitor of protein kinase C had significant effects upon the retinal explants. The protein kinase inhibitor 2-aminopurine (2-AP, 10 mM) prevented apoptosis of axotomized ganglion cells and induced apoptosis in the NBL. Forskolin prevented the apoptosis induced by 2-AP in the NBL, whereas TPA had no effect. The effects of 2-AP were, however, not dependent on inhibition of protein synthesis. The data indicate that modulation of the activity of both cAMP-dependent protein kinase and several protein kinases sensitive to 2-aminopurine selectively affect apoptosis in distinct cell layers of the developing retina.
Published: 1997
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25. Death in a dish: controls of apoptosis within the developing retinal tissue.

Author: Linden R, Rehen SK, Chiarini LB, Nakatani M, Rocha M, Campos CB, Borges HL, Varella MH, Freitas FG, Correa DF, and Guimarães CA
Subjects: Animals, Mice, Rats, Apoptosis physiology, Brain-Derived Neurotrophic Factor physiology, Culture Techniques, Retinal Degeneration metabolism, Signal Transduction physiology
Abstract: Studies of programmed cell death in the developing retina in vitro are currently reviewed. The results of inhibiting protein synthesis in retinal explants indicate two mechanisms of apoptosis. One mechanism depends on the synthesis of positive modulators ('killer proteins'), while a distinct, latent mechanism appears to be continuously blocked by negative modulators. Extracellular modulators of apoptosis include the neurotrophic factors NT-4 and BDNF, while glutamate may have either a positive or a negative modulatory action on apoptosis. Several protein kinases selectively modulate apoptosis in distinct retinal layers. Calcium and nitric oxide were also shown to affect apoptosis in the developing retinal tissue. The protein c-Jun was found associated with apoptosis in various circumstances, while p53 seems to be selectively expressed in some instances of apoptosis. The results indicate that the sensitivity of each retinal cell to apoptosis is controlled by multiple, interactive, cell type- and context-specific mechanisms. Apoptosis in the retina depends on a critical interplay of extracellular signals delivered through neurotrophic factors, neurotransmitters and neuromodulators, several signal transduction pathways, and the expression of a variety of genes.
Published: 1996

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25 results on '"Correa DF"'

1. Consistent patterns of common species across tropical tree communities

2. Consistent patterns of common species across tropical tree communities

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

4. Offset integrity reduces environmental risk: Using lessons from biodiversity and carbon offsetting to inform water quality offsetting in the catchments of the Great Barrier Reef.

5. The biogeography of the Amazonian tree flora.

6. One sixth of Amazonian tree diversity is dependent on river floodplains.

7. Author Correction: One sixth of Amazonian tree diversity is dependent on river floodplains.

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

9. "Six-and-Twelve" Prognostic Score in Transarterial Chemoembolization-Treated Hepatocellular Carcinoma Patients.

10. Mapping density, diversity and species-richness of the Amazon tree flora.

11. More than 10,000 pre-Columbian earthworks are still hidden throughout Amazonia.

12. Beyond ecology: ecosystem restoration as a process for social-ecological transformation.

13. Hepatitis A seroprevalence among special populations in the Rio de Janeiro Metropolitan Area, Brazil.

14. Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology.

15. Generalized Edema and Pseudothrombocytopenia After ChAdOx1 nCoV-19 COVID-19 Vaccination: A Case Report.

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

17. Species distribution of the main aetiologic agents causing skin dermatophytosis in Colombian patients: A 23-year experience at a Mycological Reference Center.

18. Seroprevalence of varicella antibodies in adults without clinical history of disease.

19. Rarity of monodominance in hyperdiverse Amazonian forests.

20. Addressing travelers' perception of risk in pre-travel care: Reports from a travel clinic in Rio de Janeiro, Brazil.

21. Species Distribution Modelling: Contrasting presence-only models with plot abundance data.

22. CMV and HSV-2 myeloradiculitis in an HIV infected patient.

23. [Blackwater fever: a case report].

24. Protein kinases selectively modulate apoptosis in the developing retina in vitro.

25. Death in a dish: controls of apoptosis within the developing retinal tissue.

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