ROOTING OF Inga edulis Mart. (LEGUMINOSAE-MIMOSOIDEAE) MINI-CUTTINGS

Seeds of the species Inga edulis are recalcitrant and lose viability quickly, which restricts seedling production at only a certain time of the year. Thus, this study aimed to analyze the potential of mini-cutting and the influence of different indole-3-butyric acid (IBA) concentrations on the vegetative propagation of Inga edulis. The vegetative material was collected from juvenile plants from a clonal mini-garden. The experiment was carried out in a completely randomized design, with five replications and each experimental unit with eight cuttings. Treatments consisted of different IBA concentrations (0, 1000, 2000, 4000, and 8000 mg kg−1). The percentage of live and rooted mini-cuttings, number of roots emitted from the base, longest root length, total number of roots, fine root length, total root length, root surface area, weighted average root diameter, root volume, shoot dry matter, root dry matter, total dry matter, specific root length, specific root surface area, and root density were analyzed after 45 days in a greenhouse. All Inga edulis mini-cuttings survived, and rooting was over 85%. IBA concentrations had no significant effect on most of the analyzed variables. However, exogenous auxin concentration between 2000 and 4636.96 mg kg−1 provided mini-cuttings with a higher number of roots, surface area, and root volume. Rooting of juvenile Inga edulis mini-cuttings may occur without the use of IBA

CONTROLLED-RELEASE FERTILIZER IN THE GROWTH OF Dalbergia nigra SEEDLINGS

For the realization of forest restoration projects, it is essential to produce native seedlings in quantity, also necessary that they present greater vegetative vigor and good nutritional status. In this context, the objective of this work was to analyze the growth and nutrition of phosphorus of Dalbergia nigra seedlings from two sources cultivated with doses of controlled-release fertilizer (CRF). The experimental design was in randomized blocks, arranged in a factorial scheme 2 x 4, referring to lots of two seed sources of D. nigra (Viçosa, MG and Linhares, ES) and four doses of CRF (0, 2, 4 and 8 kg m-3), with four replications and 126 seedlings per plot. At 60, 90 and 120 days after sowing, the seedlings were collected to measure the variables related to growth and nutrition. D. nigra seedlings from Linhares (ES) show better growth and dry matter production. It is recommended to dose 7.46 kg m-3 of controlled-release fertilizer for seedlings from Linhares (ES) and the dose 5.99 kg m-3 for those coming from Viçosa (MG), aiming to maximize the growth of production of seedlings of D. nigra. Increasing doses of controlled-release fertilizer allow greater accumulation of P in shoot shoots of D. nigra

GROWTH AND NUTRITION OF Paratecoma peroba SEEDLINGS IN DIFFERENT TUBE VOLUMES AND CONTROLLED-RELEASE FERTILIZERS

Paratecoma peroba is a native forest species of great economic and ecological interest, currently at risk of extinction from selective and illegal exploitation; however, there are no established parameters for the production of seedlings of this species. The objective of this study was to analyze the growth and nutritional balance of P. peroba seedlings grown in polypropylene tubes of different sizes with variable doses of controlled-release fertilizer (CRF). Three volumes of tubes (120, 180, and 280 cm3), four CRF doses (0, 2.5, 5, and 7.5 kg m-3), and a conventional mineral fertilizer (CF) were tested as indicated in the literature for native forest species: arranged in a completely randomized design in a 3 × 5 factorial scheme, with four replicates composed of 16 seedlings. After 180 days, the percentage of survival, growth variables, indices of the diagnosis and recommendation integrated system, and the average nutrient balance index of the seedlings were analyzed. Based on the total dry matter and the mean nutritional balance index, the combination of a 280 cm³ tube with a 7.5 kg m-3 CRF dose was the most effective in the production of P. peroba seedlings

ESTIMATIVA DA ALTURA DE ESPÉCIES FLORESTAIS EM REGENERAÇÃO NATURAL UTILIZANDO REDES NEURAIS ARTIFICIAIS

The use of neural networks has been used in various branches of science. In vegetation studies, neural networks have been used mainly to estimate tree biomass, height and diameter of tree individuals, but there are few studies with natural regeneration. In this context, the objective was to estimate, through artificial neural networks, the height (H) of regenerating species in an area of a Semideciduous Ombrophilous Forest fragment. The database came from individuals of tree species from regeneration of 20 plots of 10 m2 (2 x 5 m), in São Cristóvão, SE. To estimate total H by artificial neural networks, Multilayer Perceptron networks were tested. RNA was efficient in the estimation of H of the regenerative stratum in an area of a Semideciduous Ombrophilous Forest fragment. RNA 12 with 14 neurons was more efficient to estimate the height of the most abundant species in the area. The greater number of individuals with lower heights promoted an overestimation of the height.O uso de redes neurais vem sendo utilizado em vários ramos da ciência. Em estudos de vegetação as redes neurais têm sido utilizadas principalmente para estimativa de biomassa aérea, altura e diâmetro de indivíduos arbóreos, porém, existem poucos estudos com a regeneração natural. Neste contexto, objetivou-se estimar, por meio de redes neurais artificiais, a altura (H) das espécies regenerantes em uma área de um fragmento de Floresta Ombrófila Semidecidual. A base de dados foi proveniente de indivíduos de espécies arbóreas da regeneração de 20 parcelas de 10 m2 (2 x 5 m), no município de São Cristóvão, SE. Para estimativa da H total por redes neurais artificiais foram testadas redes do tipo Multilayer Perceptron. A RNA foi eficiente na estimativa da H do estrato regenerativo em uma área de um fragmento de Floresta Ombrófila Semidecidual. A RNA 12, com 14 neurônios foi mais eficiente para estimar a altura das espécies mais abundantes na área

Redes Neurais Artificiais na estimação de variáveis biométricas de mudas de espécies florestais produzidas em diferentes substratos

The aim of this study was to evaluate the stem growth in diameter and height as well as the production of total dry matter from seedlings of Myracrodruon urundeuva, Jacaranda brasiliana and Mimosa caesalpiniaefolia. Concurrently, an Artificial Neural Network (RNA) of Multilayer Perceptron type that would be able to estimate the H and the MST of the seedlings of the studied species was developed. The seedlings were cultivated in a protected environment with 50% shade. Thus, the treatments were considered with five proportions of the organic material (0, 20, 40, 60 and 80% v/v) in the final substrate composition (desertified area soil). At 120 days after sowing, the seedlings were collected to determine the biometric variables. The MLP network was used with help of the Levenberg-Marquardat training algorithm. The variables used as input of the MLP for height and dry mass estimation of the seedlings were: stem diameter, minimum, medium and maximum diameter of stem; and species and sources of organic residues (cattle manure, goat manure and rice straw), totaling ten entries. The hyperbolic tangent activation function was conducted. As a result, a 80:20% ratio (bovine manure and/or goat manure: soil from the degraded area) is recommended to be used in the growing substrate for seedling growth. The addition of bovine manure and goat manure doses influenced the Jacaranda brasiliana DC, with the linear effect increasing with the estimated value of 2.66 mm plant-1. For H, the addition of bovine and goat manure influenced the growth of Myracrodruon urundeuva seedlings. The MST production of seedlings from the three species was also distributed as a function of the increasing proportions of organic residues incorporated into the culture substrate. The use of the Artificial Neural Network of Multilayer Perceptron type was efficient for the estimation of the height and total dry mass of the species studied.O objetivo do trabalho foi avaliar o crescimento em diâmetro do coleto e altura, e a produção de matéria seca total de mudas de Myracrodruon urundeuva, Jacaranda brasiliana e Mimosa caesalpiniaefolia. Concomitantemente, desenvolveu-se uma Rede Neural Artificial (RNA) do tipo Multilayer Perceptron que seria capaz de estimar a H e a MST das mudas das espécies estudadas. As mudas foram cultivadas em ambiente protegido com 50% de sombra. Assim, os tratamentos foram considerados com cinco proporções do material orgânico (0, 20, 40, 60 e 80% v/v) na composição do substrato final (solo da área desertificada). Aos 120 dias após a semeadura, as mudas foram coletadas para determinação das variáveis biométricas. A rede MLP foi utilizada empregando-se o algoritmo de treinamento Levenberg-Marquardat. As variáveis utilizadas como entrada da MLP para a estimação da altura e massa seca das mudas foram: diâmetro do coleto, diâmetro mínimo, médio e máximo do coleto, as espécies e fontes de resíduos orgânicos (esterco bovino, esterco caprino e palha de arroz), totalizando dez entradas. Foi utilizada a função de ativação tangente hiperbólica. Como resultados, recomenda-se a proporção 80:20% (esterco bovino e/ou esterco caprino:solo da área degradada) ao substrato de cultivo para o crescimento das mudas das espécies. A adição de doses de esterco bovino e esterco caprino influenciaram o DC do Jacaranda brasiliana, sendo constatado o efeito linear crescente com valor estimado de 2,66 mm planta-1. Para a H a adição de esterco bovino e caprino influenciou no crescimento das mudas de Myracrodruon urundeuva. A produção de MST das mudas das três espécies foi igualmente distribuída em função das proporções crescentes de resíduo orgânico incorporado ao substrato de cultivo. O uso da Rede Neural Artificial do tipo Multilayer Perceptron mostrou-se eficiente para a estimação da altura e da massa total seca das mudas das espécies estudadas

Wastewater from swine farming in the growth and nutrition of Khaya senegalensis (DESR.) A Juss seedlings

This study evaluated the use of wastewater from swine farming in the growth and nutritional balance of Khaya senegalensis (Desr.) A. Juss. (African mahogany) seedlings. The experiment was setup in a shade house on the Professor Cinobelina Elvas Campus of the Federal University of Piauí, in Bom Jesus, in the State of Piauí, Brazil. The experimental design was completely randomised, with five concentrations of swine farm wastewater (SFW) (0, 25, 50, 75 and 100%) added to the irrigation water. The growth and nutritional balance of the seedlings were evaluated 100 days after sowing, by measuring shoot height (H), stem diameter (SD), number of leaves (NL), total chlorophyll (TC), leaf area (LA), shoot dry weight (SDW) and root dry weight (RDW), and by calculating the total dry weight (TDW), leaf (LBA), stem (SBA), and root (RBA) biomass allocation, Dickson Quality Index (DQI) and average Nutritional Balance Index (NBIm). It was found that K. senegalensis seedlings responded to the SFW, showing the best results for growth and nutritional balance at concentrations of around 50%

Cannabis sativa: DA TOXICIDADE AO POTENCIAL FARMACOLÓGICO

O objetivo deste estudo é realizar uma revisão sistemática sobre as manifestações clínicas pelo uso da Cannabis sativa, e o potencial terapêutico do Canabidiol. Trata-se de uma revisão sistemática, realizado no período de março a junho de 2022, utilizando as bases de dados SCIELO e PUBMED. As palavras chaves utilizadas: Cannabis sativa, Tetrahidrocanabinol e Canabidiol. Incluídos artigos publicados de 2017 a 2022, em português e inglês e excluídos artigos repetidos, preprint e sem correlação. Foram incluídos 18 artigos que demonstram potenciais tóxicos e farmacológicos do Tetrahidrocanabinol e Canabidiol respectivamente. O Tetrahidrocanabinol possui uma ação maior nos receptores CB1 e CB2, gerando efeitos psicotrópicos. O Canabidiol apresenta menor atividade nesses receptores, sendo assim, anticonvulsivante e neuroprotetor. Evidencia-se que o Canabidiol pode ser utilizado no tratamento de patologias

The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability

Chromobacterium violaceum is one of millions of species of free-living microorganisms that populate the soil and water in the extant areas of tropical biodiversity around the world. Its complete genome sequence reveals (i) extensive alternative pathways for energy generation, (ii) ≈500 ORFs for transport-related proteins, (iii) complex and extensive systems for stress adaptation and motility, and (iv) wide-spread utilization of quorum sensing for control of inducible systems, all of which underpin the versatility and adaptability of the organism. The genome also contains extensive but incomplete arrays of ORFs coding for proteins associated with mammalian pathogenicity, possibly involved in the occasional but often fatal cases of human C. violaceum infection. There is, in addition, a series of previously unknown but important enzymes and secondary metabolites including paraquat-inducible proteins, drug and heavy-metal-resistance proteins, multiple chitinases, and proteins for the detoxification of xenobiotics that may have biotechnological applications

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

Tropical forests are the most diverse and productive ecosystems on Earth. While better understanding of these forests is critical for our collective future, until quite recently efforts to measure and monitor them have been largely disconnected. Networking is essential to discover the answers to questions that transcend borders and the horizons of funding agencies. Here we show how a global community is responding to the challenges of tropical ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots. We review the major scientific discoveries of this work and show how this process is changing tropical forest science. Our core approach involves linking long-term grassroots initiatives with standardized protocols and data management to generate robust scaled-up results. By connecting tropical researchers and elevating their status, our Social Research Network model recognises the key role of the data originator in scientific discovery. Conceived in 1999 with RAINFOR (South America), our permanent plot networks have been adapted to Africa (AfriTRON) and Southeast Asia (T-FORCES) and widely emulated worldwide. Now these multiple initiatives are integrated via ForestPlots.net cyber-infrastructure, linking colleagues from 54 countries across 24 plot networks. Collectively these are transforming understanding of tropical forests and their biospheric role. Together we have discovered how, where and why forest carbon and biodiversity are responding to climate change, and how they feedback on it. This long-term pan-tropical collaboration has revealed a large long-term carbon sink and its trends, as well as making clear which drivers are most important, which forest processes are affected, where they are changing, what the lags are, and the likely future responses of tropical forests as the climate continues to change. By leveraging a remarkably old technology, plot networks are sparking a very modern revolution in tropical forest science. In the future, humanity can benefit greatly by nurturing the grassroots communities now collectively capable of generating unique, long-term understanding of Earth's most precious forests.Additional co-authors: Susan Laurance, William Laurance, Francoise Yoko Ishida, Andrew Marshall, Catherine Waite, Hannsjoerg Woell, Jean-Francois Bastin, Marijn Bauters, Hans Beeckman, Pfascal Boeckx, Jan Bogaert, Charles De Canniere, Thales de Haulleville, Jean-Louis Doucet, Olivier Hardy, Wannes Hubau, Elizabeth Kearsley, Hans Verbeeck, Jason Vleminckx, Steven W. Brewer, Alfredo Alarcón, Alejandro Araujo-Murakami, Eric Arets, Luzmila Arroyo, Ezequiel Chavez, Todd Fredericksen, René Guillén Villaroel, Gloria Gutierrez Sibauty, Timothy Killeen, Juan Carlos Licona, John Lleigue, Casimiro Mendoza, Samaria Murakami, Alexander Parada Gutierrez, Guido Pardo, Marielos Peña-Claros, Lourens Poorter, Marisol Toledo, Jeanneth Villalobos Cayo, Laura Jessica Viscarra, Vincent Vos, Jorge Ahumada, Everton Almeida, Jarcilene Almeida, Edmar Almeida de Oliveira, Wesley Alves da Cruz, Atila Alves de Oliveira, Fabrício Alvim Carvalho, Flávio Amorim Obermuller, Ana Andrade, Fernanda Antunes Carvalho, Simone Aparecida Vieira, Ana Carla Aquino, Luiz Aragão, Ana Claudia Araújo, Marco Antonio Assis, Jose Ataliba Mantelli Aboin Gomes, Fabrício Baccaro, Plínio Barbosa de Camargo, Paulo Barni, Jorcely Barroso, Luis Carlos Bernacci, Kauane Bordin, Marcelo Brilhante de Medeiros, Igor Broggio, José Luís Camargo, Domingos Cardoso, Maria Antonia Carniello, Andre Luis Casarin Rochelle, Carolina Castilho, Antonio Alberto Jorge Farias Castro, Wendeson Castro, Sabina Cerruto Ribeiro, Flávia Costa, Rodrigo Costa de Oliveira, Italo Coutinho, John Cunha, Lola da Costa, Lucia da Costa Ferreira, Richarlly da Costa Silva, Marta da Graça Zacarias Simbine, Vitor de Andrade Kamimura, Haroldo Cavalcante de Lima, Lia de Oliveira Melo, Luciano de Queiroz, José Romualdo de Sousa Lima, Mário do Espírito Santo, Tomas Domingues, Nayane Cristina dos Santos Prestes, Steffan Eduardo Silva Carneiro, Fernando Elias, Gabriel Eliseu, Thaise Emilio, Camila Laís Farrapo, Letícia Fernandes, Gustavo Ferreira, Joice Ferreira, Leandro Ferreira, Socorro Ferreira, Marcelo Fragomeni Simon, Maria Aparecida Freitas, Queila S. García, Angelo Gilberto Manzatto, Paulo Graça, Frederico Guilherme, Eduardo Hase, Niro Higuchi, Mariana Iguatemy, Reinaldo Imbrozio Barbosa, Margarita Jaramillo, Carlos Joly, Joice Klipel, Iêda Leão do Amaral, Carolina Levis, Antonio S. Lima, Maurício Lima Dan, Aline Lopes, Herison Madeiros, William E. Magnusson, Rubens Manoel dos Santos, Beatriz Marimon, Ben Hur Marimon Junior, Roberta Marotti Martelletti Grillo, Luiz Martinelli, Simone Matias Reis, Salomão Medeiros, Milton Meira-Junior, Thiago Metzker, Paulo Morandi, Natanael Moreira do Nascimento, Magna Moura, Sandra Cristina Müller, Laszlo Nagy, Henrique Nascimento, Marcelo Nascimento, Adriano Nogueira Lima, Raimunda Oliveira de Araújo, Jhonathan Oliveira Silva, Marcelo Pansonato, Gabriel Pavan Sabino, Karla Maria Pedra de Abreu, Pablo José Francisco Pena Rodrigues, Maria Piedade, Domingos Rodrigues, José Roberto Rodrigues Pinto, Carlos Quesada, Eliana Ramos, Rafael Ramos, Priscyla Rodrigues, Thaiane Rodrigues de Sousa, Rafael Salomão, Flávia Santana, Marcos Scaranello, Rodrigo Scarton Bergamin, Juliana Schietti, Jochen Schöngart, Gustavo Schwartz, Natalino Silva, Marcos Silveira, Cristiana Simão Seixas, Marta Simbine, Ana Claudia Souza, Priscila Souza, Rodolfo Souza, Tereza Sposito, Edson Stefani Junior, Julio Daniel do Vale, Ima Célia Guimarães Vieira, Dora Villela, Marcos Vital, Haron Xaud, Katia Zanini, Charles Eugene Zartman, Nur Khalish Hafizhah Ideris, Faizah binti Hj Metali, Kamariah Abu Salim, Muhd Shahruney Saparudin, Rafizah Mat Serudin, Rahayu Sukmaria Sukri, Serge Begne, George Chuyong, Marie Noel Djuikouo, Christelle Gonmadje, Murielle Simo-Droissart, Bonaventure Sonké, Hermann Taedoumg, Lise Zemagho, Sean Thomas, Fidèle Baya, Gustavo Saiz, Javier Silva Espejo, Dexiang Chen, Alan Hamilton, Yide Li, Tushou Luo, Shukui Niu, Han Xu, Zhang Zhou, Esteban Álvarez-Dávila, Juan Carlos Andrés Escobar, Henry Arellano-Peña, Jaime Cabezas Duarte, Jhon Calderón, Lina Maria Corrales Bravo, Borish Cuadrado, Hermes Cuadros, Alvaro Duque, Luisa Fernanda Duque, Sandra Milena Espinosa, Rebeca Franke-Ante, Hernando García, Alejandro Gómez, Roy González-M., Álvaro Idárraga-Piedrahíta, Eliana Jimenez, Rubén Jurado, Wilmar López Oviedo, René López-Camacho, Omar Aurelio Melo Cruz, Irina Mendoza Polo, Edwin Paky, Karen Pérez, Angel Pijachi, Camila Pizano, Adriana Prieto, Laura Ramos, Zorayda Restrepo Correa, James Richardson, Elkin Rodríguez, Gina M. Rodriguez M., Agustín Rudas, Pablo Stevenson, Markéta Chudomelová, Martin Dancak, Radim Hédl, Stanislav Lhota, Martin Svatek, Jacques Mukinzi, Corneille Ewango, Terese Hart, Emmanuel Kasongo Yakusu, Janvier Lisingo, Jean-Remy Makana, Faustin Mbayu, Benjamin Toirambe, John Tshibamba Mukendi, Lars Kvist, Gustav Nebel, Selene Báez, Carlos Céron, Daniel M. Griffith, Juan Ernesto Guevara Andino, David Neill, Walter Palacios, Maria Cristina Peñuela-Mora, Gonzalo Rivas-Torres, Gorky Villa, Sheleme Demissie, Tadesse Gole, Techane Gonfa, Kalle Ruokolainen, Michel Baisie, Fabrice Bénédet, Wemo Betian, Vincent Bezard, Damien Bonal, Jerôme Chave, Vincent Droissart, Sylvie Gourlet-Fleury, Annette Hladik, Nicolas Labrière, Pétrus Naisso, Maxime Réjou-Méchain, Plinio Sist, Lilian Blanc, Benoit Burban, Géraldine Derroire, Aurélie Dourdain, Clement Stahl, Natacha Nssi Bengone, Eric Chezeaux, Fidèle Evouna Ondo, Vincent Medjibe, Vianet Mihindou, Lee White, Heike Culmsee, Cristabel Durán Rangel, Viviana Horna, Florian Wittmann, Stephen Adu-Bredu, Kofi Affum-Baffoe, Ernest Foli, Michael Balinga, Anand Roopsind, James Singh, Raquel Thomas, Roderick Zagt, Indu K. Murthy, Kuswata Kartawinata, Edi Mirmanto, Hari Priyadi, Ismayadi Samsoedin, Terry Sunderland, Ishak Yassir, Francesco Rovero, Barbara Vinceti, Bruno Hérault, Shin-Ichiro Aiba, Kanehiro Kitayama, Armandu Daniels, Darlington Tuagben, John T. Woods, Muhammad Fitriadi, Alexander Karolus, Kho Lip Khoon, Noreen Majalap, Colin Maycock, Reuben Nilus, Sylvester Tan, Almeida Sitoe, Indiana Coronado G., Lucas Ojo, Rafael de Assis, Axel Dalberg Poulsen, Douglas Sheil, Karen Arévalo Pezo, Hans Buttgenbach Verde, Victor Chama Moscoso, Jimmy Cesar Cordova Oroche, Fernando Cornejo Valverde, Massiel Corrales Medina, Nallaret Davila Cardozo, Jano de Rutte Corzo, Jhon del Aguila Pasquel, Gerardo Flores Llampazo, Luis Freitas, Darcy Galiano Cabrera, Roosevelt García Villacorta, Karina Garcia Cabrera, Diego García Soria, Leticia Gatica Saboya, Julio Miguel Grandez Rios, Gabriel Hidalgo Pizango, Eurídice Honorio Coronado, Isau Huamantupa-Chuquimaco, Walter Huaraca Huasco, Yuri Tomas Huillca Aedo, Jose Luis Marcelo Peña, Abel Monteagudo Mendoza, Vanesa Moreano Rodriguez, Percy Núñez Vargas, Sonia Cesarina Palacios Ramos, Nadir Pallqui Camacho, Antonio Peña Cruz, Freddy Ramirez Arevalo, José Reyna Huaymacari, Carlos Reynel Rodriguez, Marcos Antonio Ríos Paredes, Lily Rodriguez Bayona, Rocio del Pilar Rojas Gonzales, Maria Elena Rojas Peña, Norma Salinas Revilla, Yahn Carlos Soto Shareva, Raul Tupayachi Trujillo, Luis Valenzuela Gamarra, Rodolfo Vasquez Martinez, Jim Vega Arenas, Christian Amani, Suspense Averti Ifo, Yannick Bocko, Patrick Boundja, Romeo Ekoungoulou, Mireille Hockemba, Donatien Nzala, Alusine Fofanah, David Taylor, Guillermo Bañares-de Dios, Luis Cayuela, Íñigo Granzow-de la Cerda, Manuel Macía, Juliana Stropp, Maureen Playfair, Verginia Wortel, Toby Gardner, Robert Muscarella, Hari Priyadi, Ervan Rutishauser, Kuo-Jung Chao, Pantaleo Munishi, Olaf Bánki, Frans Bongers, Rene Boot, Gabriella Fredriksson, Jan Reitsma, Hans ter Steege, Tinde van Andel, Peter van de Meer, Peter van der Hout, Mark van Nieuwstadt, Bert van Ulft, Elmar Veenendaal, Ronald Vernimmen, Pieter Zuidema, Joeri Zwerts, Perpetra Akite, Robert Bitariho, Colin Chapman, Eilu Gerald, Miguel Leal, Patrick Mucunguzi, Miguel Alexiades, Timothy R. Baker, Karina Banda, Lindsay Banin, Jos Barlow, Amy Bennett, Erika Berenguer, Nicholas Berry, Neil M. Bird, George A. Blackburn, Francis Brearley, Roel Brienen, David Burslem, Lidiany Carvalho, Percival Cho, Fernanda Coelho, Murray Collins, David Coomes, Aida Cuni-Sanchez, Greta Dargie, Kyle Dexter, Mat Disney, Freddie Draper, Muying Duan, Adriane Esquivel-Muelbert, Robert Ewers, Belen Fadrique, Sophie Fauset, Ted R. Feldpausch, Filipe França, David Galbraith, Martin Gilpin, Emanuel Gloor, John Grace, Keith Hamer, David Harris, Tommaso Jucker, Michelle Kalamandeen, Bente Klitgaard, Aurora Levesley, Simon L. Lewis, Jeremy Lindsell, Gabriela Lopez-Gonzalez, Jon Lovett, Yadvinder Malhi, Toby Marthews, Emma McIntosh, Karina Melgaço, William Milliken, Edward Mitchard, Peter Moonlight, Sam Moore, Alexandra Morel, Julie Peacock, Kelvin Peh, Colin Pendry, R. Toby Pennington, Luciana de Oliveira Pereira, Carlos Peres, Oliver L. Phillips, Georgia Pickavance, Thomas Pugh, Lan Qie, Terhi Riutta, Katherine Roucoux, Casey Ryan, Tiina Sarkinen, Camila Silva Valeria, Dominick Spracklen, Suzanne Stas, Martin Sullivan, Michael Swaine, Joey Talbot, James Taplin, Geertje van der Heijden, Laura Vedovato, Simon Willcock, Mathew Williams, Luciana Alves, Patricia Alvarez Loayza, Gabriel Arellano, Cheryl Asa, Peter Ashton, Gregory Asner, Terry Brncic, Foster Brown, Robyn Burnham, Connie Clark, James Comiskey, Gabriel Damasco, Stuart Davies, Tony Di Fiore, Terry Erwin, William Farfan-Rios, Jefferson Hall, David Kenfack, Thomas Lovejoy, Roberta Martin, Olga Martha Montiel, John Pipoly, Nigel Pitman, John Poulsen, Richard Primack, Miles Silman, Marc Steininger, Varun Swamy, John Terborgh, Duncan Thomas, Peter Umunay, Maria Uriarte, Emilio Vilanova Torre, Ophelia Wang, Kenneth Young, Gerardo A. Aymard C., Lionel Hernández, Rafael Herrera Fernández, Hirma Ramírez-Angulo, Pedro Salcedo, Elio Sanoja, Julio Serrano, Armando Torres-Lezama, Tinh Cong Le, Trai Trong Le, Hieu Dang Tra

RENTABILIDADE DE PLANTIOS DE ACÁCIA-AUSTRALIANA E DE SISTEMA DE INTEGRAÇÃO LAVOURA-PECUARIA-FLORESTA NO SUDOESTE DO PIAUÍ

Objetivou-se com este trabalho realizar análise comparativa dos rendimentos de sistemas agroflorestais e monocultivo com Acacia mangium Willd, em uma área de 10 hectares no município de Bom Jesus no Sudoeste do Estado do Piauí. Foram realizadas análises comparativas das simulações de receitas da venda do carvão vegetal para o sistema de monocultivo, sistema Taungya e integração Lavoura-Pecuária-Floresta (iLPF) aos sete anos. Foram coletadas informações levantadas pelos autores, artigos científicos e de plantios experimentais da cultura em outras regiões do país. As informações foram transformadas em tabelas e planilhas por proporcionar uma visão mais clara e direta da conclusão dos dados. A viabilidade econômica foi determinada por meio da aplicação dos métodos de avaliação de projetos: Valor Presente Líquido (VPL), Valor Anual Equivalente (VAE) e Razão Benefício/Custo (B/C). Os resultados demostraram que ambos os sistemas de manejo são viáveis economicamente. Verificou-se que o sistema Taungya apresentou os melhores resultados dos indicadores avaliados, demostrando ser o mais rentável financeiramente. Palavras-Chaves: Acacia mangium Willd, Economia florestal, Planejamento Agroflorestal, carvão vegetal.   PLANTATIONS OF PROFITABILITY OF Acacia mangium AND SYSTEM INTEGRATION CROP-LIVESTOCK-FOREST, PIAUÍ, BRAZIL   ABSTRACT The objective of this work conduct comparative analysis of income from agroforestry and monoculture systems with Acacia mangium Willd in an area of ​​10 hectares in the municipality of Bom Jesus in the State of Piauí Southwest, Brazil. Comparative analyzes were carried out of sales revenues simulations charcoal for the monoculture system, Taungya system and integration Crop-Livestock-Forest (iLPF) to seven years. Information was collected raised by the authors, scientific articles and experimental plantings of the crop in other parts of the country. Information was transformed into tables and spreadsheets by providing a clearer and more direct view of the completion of the data. Economic viability was determined by the application of project evaluation methods: Net Present Value (NPV), Equivalent Annual Value (EAV) and Benefit / Cost Ratio (B / C). The results showed that both management systems are economically viable. It was found that the Taungya system showed the best results of the indicators assessed, showing to be the most profitable financially. Keywords: Acacia mangium Willd, Forest Economics, Agroforestry Planning, charcoal. DOI: http://dx.doi.org/10.14583/2318-7670.v03n04a0