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1.
Combining ALS and UAV to derive the height of Araucaria angustifolia in the Brazilian Atlantic Rain Forest
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CUNHA NETO, ERNANDES M. DA
; VERAS, HUDSON F.P.
; MOURA, MARKS M.
; BERTI, ANDRÉ L.
; SANQUETTA, CARLOS R.
; PELISSARI, ALLAN L.
; CORTE, ANA PAULA D.
.
Abstract Quantitative data obtained from native forests is costly and time-consuming. Thus, alternative measurement methods need to be developed to provide reliable information, especially in Atlantic Rain Forests. In this study we evaluated the hypothesis that the combination of an Airborne Laser Scanner (ALS) and an Unmanned Aerial Vehicle (UAV) can provide accurate quantitative information on tree height, volume, and aboveground biomass of the Araucaria angustifolia species. The study was carried out in Atlantic Rain forest fragments in southern Brazil. We tested and evaluated 3 digital canopy height model (CHM) scenarios: 1) CHM derived from ALS models; 2) CHM derived from UAV models; and 3) CHM from a combined ALS digital terrain model and UAV digital surface model. The height value at each tree coordinate was extracted from the pixel in the three evaluated scenarios and compared with the field measured values. ALS and UAV+ALS obtained RMSE% of 6.38 and 12.82 for height estimates, while UAV was 49.91%. Volume and aboveground biomass predictions are more accurate by ALS and UAV+ALS, while the UAV produced biased estimates. Since the ALS is currently used, periodic monitoring can be carried out by a combination of active (ALS) and passive (UAV) sensors. timeconsuming. timeconsuming time consuming. consuming time-consuming Thus Forests (ALS (UAV volume species Brazil (CHM 1 models 2 values UAVALS RMSE 638 6 38 6.3 1282 12 82 12.8 estimates 4991 49 91 49.91% used sensors 63 6. 128 8 12. 499 4 9 49.91 49.9 49.
2.
Geostatistical modeling and remotely sensed data to improve dendrometric variables prediction in Tectona grandis L. f. stand
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Pfutz, Iasmin Fernanda Portela
; Pelissari, Allan Libanio
; Corte, Ana Paula Dalla
; Caldeira, Sidney Fernando
; Rodrigues, Carla Krulikowski
; Ebling, Angelo Augusto
.
Resumen El conocimiento detallado de la estructura de las plantaciones de teca es necesario para los planes de gestión sostenible. La integración de variables de teledetección con la modelización geoestadística en plantaciones de teca ha sido poco estudiada y, por tanto, el objetivo consistía en modelizar la distribución espacial de las variables del rodal de teca, incorporando covariables. El estudio se realizó en plantaciones de teca de 19 años en Brasil con 213 hectáreas en el espacio inicial de 3 m x 3 m. Se asignaron parcelas georreferenciadas de 900 m² y se obtuvieron las variables forestales después del clareo. Los índices de vegetación se calcularon a partir de operaciones aritméticas ejecutadas entre las bandas de imágenes Landsat. La interpolación de las variables forestales se procedió por el método geoestadístico univariante de kriging ordinario, así como por el método multivariante de kriging con deriva externa, considerando las variables de teledetección como covariables. El análisis estadístico de las variables de teledetección muestra una discreta correlación lineal con las variables de la teca, lo que tiende a hacer inviable su uso como covariables en la modelización geoestadística. Sin embargo, el kriging con deriva externa predice los patrones espaciales de las variables forestales con mayor detalle, lo que da como resultado a posibles errores de suavización menores que los obtenidos por el kriging ordinario, y proporciona recomendaciones más precisas para la gestión localizada en plantaciones de teca. La integración de variables de teledetección en el inventario forestal mediante geoestadística es ventajosa para cartografiar la distribución espacial de las variables de los rodales de teca.
Abstract Detailed knowledge of teak stand structure is necessary for sustainable management plans. The integration of remote sensing variables with geostatistical modeling in teak forest stands has not been sufficiently studied and, therefore, the aim was to model the spatial distribution of teak stand variables, adding covariables. The study was carried out on 19-year-old teak stand in Brazil with 213 hectares in the initial spatial of 3 m x 3 m. Geo-referenced plots of 900 m² were allocated, and forest variables were obtained after thinning. Vegetation indices were calculated from arithmetic operations conducted between the Landsat image bands. The interpolation of forest variables was performed by the geostatistical univariate method of ordinary kriging, as well as by the multivariate method of kriging with external drift, considering the remote sensing variables as covariables. Statistical analysis of remote sensing variables shows a weak linear correlation with teak variables, which tends to make them unviable to use as covariables in geostatistical modeling. However, kriging with external drift predicts spatial patterns of forest variables with greater detail, which results in lower possible smoothing errors than those obtained by ordinary kriging and provides more accurate recommendations for localized management in teak stand. The integration of remote sensing variables in forest inventory through geostatistics is advantageous for mapping the spatial distribution of teak stand variables.
3.
Configuração de algoritmos de aprendizado de máquina na modelagem florestal: um estudo de caso na modelagem da relação hipsométrica
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Costa-Filho, Sérgio Vinícius Serejo da
; Arce, Julio Eduardo
; Montaño, Razer Nizer Rojas
; Pelissari, Allan Libanio
.
Resumo No presente estudo foram aplicados quatro algoritmos de aprendizado de máquina na tarefa de modelagem da relação hipsométrica de povoamentos de Pinus taeda L. em diferentes idades. Centenas de combinações de parâmetros foram testadas para os algoritmos k-vizinhos mais próximos, florestas aleatórias, máquinas de vetores de suporte e redes neurais artificiais. Para seleção do melhor modelo para cada algoritmo, utilizou-se o método de busca em grade combinada ao método de validação cruzada k-fold. Os modelos selecionados foram utilizados para predição da altura total de indivíduos pertencentes a um conjunto de dados independente, e os resultados foram comparados aos obtidos por modelos de regressão linear. Os modelos de aprendizado de máquina apresentaram indicadores estatísticos similares aos modelos de regressão linear, no entanto, tiveram dispersão de resíduos menos tendenciosa, principalmente na análise estratificada por povoamento. A máquina de vetores de suporte e a rede neural artificial foram os modelos mais satisfatórios em precisão e dispersão dos resíduos.
Abstract In the present study, four machine learning algorithms were applied in the task of modeling the height-diameter relationship of Pinus taeda L. stands at different ages. Hundreds of parameter combinations were tested for the k-nearest neighbors, random forests, support vector machines, and artificial neural networks algorithms. In order to select the best model for each algorithm, the grid search and the k-fold cross validation methods were applied. The selected models were used to predict the total height of individuals in an independent data set, and the results were compared to those obtained by linear regression models. The machine learning models presented similar statistical indicators to the linear regression models. However, they had less biased dispersion of residues, especially in the stratified analysis by age. The support vector machine and the artificial neural network were the most satisfactory models in precision and dispersion of residues.
https://doi.org/10.5902/1980509828392
1248 downloads
4.
Modeling residual biomass from mechanized wood harvesting with data measured by forest harvester
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RODRIGUES, CARLA K.
; LOPES, EDUARDO S.
; FIGUEIREDO FILHO, AFONSO
; PELISSARI, ALLAN L.
; SILVA, MATHEUS K.C.
.
Abstract: The lack of accurate models for estimating residual biomass in wood harvesting operations results in underutilization of this co-product by forestry companies. Due to the lack of this information, forestry operations planning, such as chipping and transport logistics, are influenced, with a consequent increase in costs. Thereby, the aim of this study was to propose and evaluate statistical models to estimate residual biomass of Eucalyptus sp. in wood harvesting operations by means of tree variables measured from harvester processing head. Generalized linear models were composed through stepwise procedure for estimating residual biomass by tree covariates: diameter at breast height, commercial height, commercial limit diameter, and stem commercial volume, considering also their transformations and combinations. Residual biomass distributions with positive skew support the application of generalized linear model and Gamma distribution in random component, since normality assumption in traditional linear regression was a requirement not satisfied in this study. By stepwise procedure, tree variables associated to forest biomass were selected, whose linear combinations resulted in models with high statistical efficiency and accuracy. Thus, models developed in this study are innovative tools to estimate residual biomass in mechanized wood harvesting, in which can be inserted into harvester’s hardware to provide real-time information.
https://doi.org/10.1590/0001-3765201920190194
549 downloads
5.
Energy balance and CO2 emission in mechanized biomass harvesting in pine stands under thinning
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RODRIGUES, CARLA K.
; LOPES, EDUARDO S.
; SILVA, DIMAS A.
; FIGUEIREDO FILHO, AFONSO
; PELISSARI, ALLAN L.
.
Abstract: Biomass is an important component of the Brazilian energy matrix, with a potential contribution of co-products from thinned forests. The aim of this work was to evaluate the energy balance and CO2 potential emission in mechanized biomass harvesting operations in Pinus taeda stands at 9 and 10 years-old and under thinning, searching to support the use of co-product biomass from thinning as a renewable energy source. Thinning was carried out through cut-to-length harvesting method, in which large logs for sawmill and small logs for energy were produced. In addition, tops, needles, barks, and branches were considered as co-products. The balance between consumed energy and emitted CO2 by machines for thinning in relationship to the energy and CO2 in thinned biomass was estimated. Thus, dry matter, energy potential, and CO2 potential emission were evaluated and compared considering thinning stand ages as treatments. Mechanized thinning consumes a large energy and produces CO2, however, the energy consumed by machines is lower than 1% of the estimated energy potential in thinned biomass, while the CO2 emission is lower than 0.5% of the biomass. Therefore, the use of co-product biomass of thinning is an important way to mitigate greenhouse gas emission.
https://doi.org/10.1590/0001-3765201920180839
650 downloads
6.
Sampling system for estimating woody debris in an urban mixed tropical forest
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PÉLLICO NETTO, SYLVIO
; PELISSARI, ALLAN L.
; BRIBEIRO, ANDRESSA
; MACHADO, SEBASTIÃO A.
; NASCIMENTO, RODRIGO G.M.
.
Abstract Woody debris, defined as standing and downed deadwood, consists in an essential component of the forest carbon stock. However, few studies have been carried out to get an efficient and accurate sampling procedure for estimating it. This work proposes two methodologies to estimate the woody debris volume in a Brazilian mixed tropical forest: 1) two-stage systematic sampling, using a mixed methodology, in which the Strand’s method is applied to standing dead trees and stumps, and line intercept sampling is used to fallen trees and branches; and 2) ratio estimate of the sum of cross-sectional areas of deadwood pieces and forest basal area, aiming to obtain the total woody debris volume indirectly in the natural forest. Conversions for biomass and carbon stocks were made applying the mean basic density on the estimates of deadwood volumes. Both methodologies are accurate for woody debris volume estimates, with a sampling error equal to 16.1% (methodology 1) and 5.7% (methodology 2), at a 95% probability level. Thus, the methodology 2 has potential to be used in strategic forest inventories of woody debris, such as in National Forest Inventories, due to increasing importance of its quantification in all forest ecosystems.
https://doi.org/10.1590/0001-3765201820180100
830 downloads
7.
Spatial variability of tree species diversity in a mixed tropical forest in Southern Brazil
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PELISSARI, ALLAN L.
; F FILHO, AFONSO
; EBLING, ANGELO A.
; SANQUETTA, CARLOS R.
; CYSNEIROS, VINICIUS C.
; CORTE, ANA PAULA D.
.
Abstract Floristic surveys and diversity indices are often applied to measure tree species diversity in mixed tropical forest remnants. However, these analyses are frequently limited to the overall results and do not allow to evaluate the spatial variability distributions of tree diversity, leading to develop additional tools. This study aimed to estimate the spatial variability of tree diversity and map their spatial patterns in a Brazilian mixed tropical forest conservation area. We used indices to measure the tree species diversity (dbh ≥ 10 cm) in 400 sampling units (25 m x 25 m) from a continuous forest inventory. Semivariograms were fitted to estimate spatial dependences and punctual kriging was applied to compose maps. Mean diversity values were constant in the continuous inventories, indicating a forest remnant in an advanced stage of ecological succession. On the other hand, tree diversity presented spatial patterns identified by geostatistics, in which the dynamics were composed of heterogeneous mosaics spatially influenced by tree species with different ecological features and densities, gap dynamics, advancement of forest succession, mortality, and Araucaria angustilofia’s cohorts.
https://doi.org/10.1590/0001-3765201820170826
1025 downloads
8.
Sampling procedures for inventory of commercial volume tree species in Amazon Forest
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NETTO, SYLVIO P.
; PELISSARI, ALLAN L.
; CYSNEIROS, VINICIUS C.
; BONAZZA, MARCELO
; SANQUETTA, CARLOS R.
.
ABSTRACT The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.
https://doi.org/10.1590/0001-3765201720160760
2487 downloads
9.
GEOSTATISTICAL MODELING OF TIMBER VOLUME SPATIAL VARIABILITY FOR Tectona grandis L. F. PRECISION FORESTRY
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Pelissari, Allan Libanio
; Roveda, Marcelo
; Caldeira, Sidney Fernando
; Sanquetta, Carlos Roberto
; Corte, Ana Paula Dalla
; Rodrigues, Carla Krulikowski
.
RESUMO Considerando a hipótese de que os volumes de madeira apresentam dependência espacial, cujo conhecimento contribui para o manejo de precisão, o objetivo deste trabalho foi estimar a variabilidade espacial do volume de sortimentos de madeira e identificar seus padrões espaciais em povoamentos de Tectona grandis. Utilizou-se um conjunto de dados de 1.038 árvores para ajustar funções de afilamento e estimar os volumes para fuste total, serraria e lenha em 273 parcelas alocadas em povoamentos de T. grandis ao oitavo ano de idade, o qual representa o segundo desbaste que possibilita volumes comerciais. Modelos de semivariogramas foram aplicados para ajustar a dependência espacial e a krigagem pontual foi utilizada para compor mapas de volume. A modelagem geoestatística permitiu estimar a variabilidade espacial de T. grandis e desenvolver mapas de volume de madeira. Assim, tratamentos silviculturais, como desbaste e poda, bem como planejamento de intervenções espaciais, podem ser recomendados para produtos de madeira almejados.
ABSTRACT Considering the hypothesis that the wood volumes present spatial dependence, whose knowledge contributes for the precision forestry, the aim of this work was to estimate the volume spatial variability for timber assortments and identify their spatial patterns on Tectona grandis stands. A dataset of 1,038 trees was used to fit taper models and estimate the total stem, sawlog, and firewood volumes in 273 plots allocated on T. grandis stands at eight years old, which represents the second thinning that enables commercial volumes. Semivariograms models was applied to fit the spatial dependence, and punctual kriging was used to compose volume maps. Geostatistical modeling allowed us to estimate the T. grandis spatial variability and develop timber volume maps. Thus, silvicultural treatments, such as thinning and pruning, as well as for planning spatial interventions, are possible to be recommended for aimed wood products.
https://doi.org/10.1590/01047760201723012291
1408 downloads
10.
Growing knowledge: an overview of Seed Plant diversity in Brazil
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Zappi, Daniela C.
; Filardi, Fabiana L. Ranzato
; Leitman, Paula
; Souza, Vinícius C.
; Walter, Bruno M.T.
; Pirani, José R.
; Morim, Marli P.
; Queiroz, Luciano P.
; Cavalcanti, Taciana B.
; Mansano, Vidal F.
; Forzza, Rafaela C.
; Abreu, Maria C.
; Acevedo-Rodríguez, Pedro
; Agra, Maria F.
; Almeida Jr., Eduardo B.
; Almeida, Gracineide S.S.
; Almeida, Rafael F.
; Alves, Flávio M.
; Alves, Marccus
; Alves-Araujo, Anderson
; Amaral, Maria C.E.
; Amorim, André M.
; Amorim, Bruno
; Andrade, Ivanilza M.
; Andreata, Regina H.P.
; Andrino, Caroline O.
; Anunciação, Elisete A.
; Aona, Lidyanne Y.S.
; Aranguren, Yani
; Aranha Filho, João L.M.
; Araújo, Andrea O.
; Araújo, Ariclenes A.M.
; Araújo, Diogo
; Arbo, María M.
; Assis, Leandro
; Assis, Marta C.
; Assunção, Vivian A.
; Athiê-Souza, Sarah M.
; Azevedo, Cecilia O.
; Baitello, João B.
; Barberena, Felipe F.V.A.
; Barbosa, Maria R.V.
; Barros, Fábio
; Barros, Lucas A.V.
; Barros, Michel J.F.
; Baumgratz, José F.A.
; Bernacci, Luis C.
; Berry, Paul E.
; Bigio, Narcísio C.
; Biral, Leonardo
; Bittrich, Volker
; Borges, Rafael A.X.
; Bortoluzzi, Roseli L.C.
; Bove, Cláudia P.
; Bovini, Massimo G.
; Braga, João M.A.
; Braz, Denise M.
; Bringel Jr., João B.A.
; Bruniera, Carla P.
; Buturi, Camila V.
; Cabral, Elza
; Cabral, Fernanda N.
; Caddah, Mayara K.
; Caires, Claudenir S.
; Calazans, Luana S.B.
; Calió, Maria F.
; Camargo, Rodrigo A.
; Campbell, Lisa
; Canto-Dorow, Thais S.
; Carauta, Jorge P.P.
; Cardiel, José M.
; Cardoso, Domingos B.O.S.
; Cardoso, Leandro J.T.
; Carneiro, Camila R.
; Carneiro, Cláudia E.
; Carneiro-Torres, Daniela S.
; Carrijo, Tatiana T.
; Caruzo, Maria B.R.
; Carvalho, Maria L.S.
; Carvalho-Silva, Micheline
; Castello, Ana C.D.
; Cavalheiro, Larissa
; Cervi, Armando C.
; Chacon, Roberta G.
; Chautems, Alain
; Chiavegatto, Berenice
; Chukr, Nádia S.
; Coelho, Alexa A.O.P.
; Coelho, Marcus A.N.
; Coelho, Rubens L.G.
; Cordeiro, Inês
; Cordula, Elizabeth
; Cornejo, Xavier
; Côrtes, Ana L.A.
; Costa, Andrea F.
; Costa, Fabiane N.
; Costa, Jorge A.S.
; Costa, Leila C.
; Costa-e-Silva, Maria B.
; Costa-Lima, James L.
; Cota, Maria R.C.
; Couto, Ricardo S.
; Daly, Douglas C.
; De Stefano, Rodrigo D.
; De Toni, Karen
; Dematteis, Massimiliano
; Dettke, Greta A.
; Di Maio, Fernando R.
; Dórea, Marcos C.
; Duarte, Marília C.
; Dutilh, Julie H.A.
; Dutra, Valquíria F.
; Echternacht, Lívia
; Eggers, Lilian
; Esteves, Gerleni
; Ezcurra, Cecilia
; Falcão Junior, Marcus J.A.
; Feres, Fabíola
; Fernandes, José M.
; Ferreira, D.M.C.
; Ferreira, Fabrício M.
; Ferreira, Gabriel E.
; Ferreira, Priscila P.A.
; Ferreira, Silvana C.
; Ferrucci, Maria S.
; Fiaschi, Pedro
; Filgueiras, Tarciso S.
; Firens, Marcela
; Flores, Andreia S.
; Forero, Enrique
; Forster, Wellington
; Fortuna-Perez, Ana P.
; Fortunato, Reneé H.
; Fraga, Cléudio N.
; França, Flávio
; Francener, Augusto
; Freitas, Joelcio
; Freitas, Maria F.
; Fritsch, Peter W.
; Furtado, Samyra G.
; Gaglioti, André L.
; Garcia, Flávia C.P.
; Germano Filho, Pedro
; Giacomin, Leandro
; Gil, André S.B.
; Giulietti, Ana M.
; A.P.Godoy, Silvana
; Goldenberg, Renato
; Gomes da Costa, Géssica A.
; Gomes, Mário
; Gomes-Klein, Vera L.
; Gonçalves, Eduardo Gomes
; Graham, Shirley
; Groppo, Milton
; Guedes, Juliana S.
; Guimarães, Leonardo R.S.
; Guimarães, Paulo J.F.
; Guimarães, Elsie F.
; Gutierrez, Raul
; Harley, Raymond
; Hassemer, Gustavo
; Hattori, Eric K.O.
; Hefler, Sonia M.
; Heiden, Gustavo
; Henderson, Andrew
; Hensold, Nancy
; Hiepko, Paul
; Holanda, Ana S.S.
; Iganci, João R.V.
; Imig, Daniela C.
; Indriunas, Alexandre
; Jacques, Eliane L.
; Jardim, Jomar G.
; Kamer, Hiltje M.
; Kameyama, Cíntia
; Kinoshita, Luiza S.
; Kirizawa, Mizué
; Klitgaard, Bente B.
; Koch, Ingrid
; Koschnitzke, Cristiana
; Krauss, Nathália P.
; Kriebel, Ricardo
; Kuntz, Juliana
; Larocca, João
; Leal, Eduardo S.
; Lewis, Gwilym P.
; Lima, Carla T.
; Lima, Haroldo C.
; Lima, Itamar B.
; Lima, Laíce F.G.
; Lima, Laura C.P.
; Lima, Leticia R.
; Lima, Luís F.P.
; Lima, Rita B.
; Lírio, Elton J.
; Liro, Renata M.
; Lleras, Eduardo
; Lobão, Adriana
; Loeuille, Benoit
; Lohmann, Lúcia G.
; Loiola, Maria I.B.
; Lombardi, Julio A.
; Longhi-Wagner, Hilda M.
; Lopes, Rosana C.
; Lorencini, Tiago S.
; Louzada, Rafael B.
; Lovo, Juliana
; Lozano, Eduardo D.
; Lucas, Eve
; Ludtke, Raquel
; Luz, Christian L.
; Maas, Paul
; Machado, Anderson F.P.
; Macias, Leila
; Maciel, Jefferson R.
; Magenta, Mara A.G.
; Mamede, Maria C.H.
; Manoel, Evelin A.
; Marchioretto, Maria S.
; Marques, Juliana S.
; Marquete, Nilda
; Marquete, Ronaldo
; Martinelli, Gustavo
; Martins da Silva, Regina C.V.
; Martins, Ângela B.
; Martins, Erika R.
; Martins, Márcio L.L.
; Martins, Milena V.
; Martins, Renata C.
; Matias, Ligia Q.
; Maya-L., Carlos A.
; Mayo, Simon
; Mazine, Fiorella
; Medeiros, Debora
; Medeiros, Erika S.
; Medeiros, Herison
; Medeiros, João D.
; Meireles, José E.
; Mello-Silva, Renato
; Melo, Aline
; Melo, André L.
; Melo, Efigênia
; Melo, José I.M.
; Menezes, Cristine G.
; Menini Neto, Luiz
; Mentz, Lilian A.
; Mezzonato, A.C.
; Michelangeli, Fabián A.
; Milward-de-Azevedo, Michaele A.
; Miotto, Silvia T.S.
; Miranda, Vitor F.O.
; Mondin, Cláudio A.
; Monge, Marcelo
; Monteiro, Daniele
; Monteiro, Raquel F.
; Moraes, Marta D.
; Moraes, Pedro L.R.
; Mori, Scott A.
; Mota, Aline C.
; Mota, Nara F.O.
; Moura, Tania M.
; Mulgura, Maria
; Nakajima, Jimi N.
; Nardy, Camila
; Nascimento Júnior, José E.
; Noblick, Larry
; Nunes, Teonildes S.
; O'Leary, Nataly
; Oliveira, Arline S.
; Oliveira, Caetano T.
; Oliveira, Juliana A.
; Oliveira, Luciana S.D.
; Oliveira, Maria L.A.A.
; Oliveira, Regina C.
; Oliveira, Renata S.
; Oliveira, Reyjane P.
; Paixão-Souza, Bruno
; Parra, Lara R.
; Pasini, Eduardo
; Pastore, José F.B.
; Pastore, Mayara
; Paula-Souza, Juliana
; Pederneiras, Leandro C.
; Peixoto, Ariane L.
; Pelissari, Gisela
; Pellegrini, Marco O.O.
; Pennington, Toby
; Perdiz, Ricardo O.
; Pereira, Anna C.M.
; Pereira, Maria S.
; Pereira, Rodrigo A.S.
; Pessoa, Clenia
; Pessoa, Edlley M.
; Pessoa, Maria C.R.
; Pinto, Luiz J.S.
; Pinto, Rafael B.
; Pontes, Tiago A.
; Prance, Ghillean T.
; Proença, Carolyn
; Profice, Sheila R.
; Pscheidt, Allan C.
; Queiroz, George A.
; Queiroz, Rubens T.
; Quinet, Alexandre
; Rainer, Heimo
; Ramos, Eliana
; Rando, Juliana G.
; Rapini, Alessandro
; Reginato, Marcelo
; Reis, Ilka P.
; Reis, Priscila A.
; Ribeiro, André R.O.
; Ribeiro, José E.L.S.
; Riina, Ricarda
; Ritter, Mara R.
; Rivadavia, Fernando
; Rocha, Antônio E.S.
; Rocha, Maria J.R.
; Rodrigues, Izabella M.C.
; Rodrigues, Karina F.
; Rodrigues, Rodrigo S.
; Rodrigues, Rodrigo S.
; Rodrigues, Vinícius T.
; Rodrigues, William
; Romaniuc Neto, Sérgio
; Romão, Gerson O.
; Romero, Rosana
; Roque, Nádia
; Rosa, Patrícia
; Rossi, Lúcia
; Sá, Cyl F.C.
; Saavedra, Mariana M.
; Saka, Mariana
; Sakuragui, Cássia M.
; Salas, Roberto M.
; Sales, Margareth F.
; Salimena, Fatima R.G.
; Sampaio, Daniela
; Sancho, Gisela
; Sano, Paulo T.
; Santos, Alessandra
; Santos, Élide P.
; Santos, Juliana S.
; Santos, Marianna R.
; Santos-Gonçalves, Ana P.
; Santos-Silva, Fernanda
; São-Mateus, Wallace
; Saraiva, Deisy P.
; Saridakis, Dennis P.
; Sartori, Ângela L.B.
; Scalon, Viviane R.
; Schneider, Ângelo
; Sebastiani, Renata
; Secco, Ricardo S.
; Senna, Luisa
; Senna-Valle, Luci
; Shirasuna, Regina T.
; Silva Filho, Pedro J.S.
; Silva, Anádria S.
; Silva, Christian
; Silva, Genilson A.R.
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; Silva, Márcia C.R.
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; Simão-Bianchini, Rosângela
; Simões, André O.
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; Siniscalchi, Carolina M.
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; Sobral, Marcos
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; Souza, Elnatan B.
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; Souza, Maria L.D.R.
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; Stapf, María N.S.
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; Takeuchi, Cátia
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; Temponi, Lívia G.
; Terra-Araujo, Mário H.
; Thode, Veronica
; Thomas, W.Wayt
; Tissot-Squalli, Mara L.
; Torke, Benjamin M.
; Torres, Roseli B.
; Tozzi, Ana M.G.A.
; Trad, Rafaela J.
; Trevisan, Rafael
; Trovó, Marcelo
; Valls, José F.M.
; Vaz, Angela M.S.F.
; Versieux, Leonardo
; Viana, Pedro L.
; Vianna Filho, Marcelo D.M.
; Vieira, Ana O.S.
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; Vignoli-Silva, Márcia
; Vilar, Thaisa
; Vinhos, Franklin
; Wallnöfer, Bruno
; Wanderley, Maria G.L.
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; Watanabe, Maurício T.C.
; Weigend, Maximilian
; Welker, Cassiano A.D.
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Resumo Um levantamento atualizado das plantas com sementes e análises relevantes acerca desta biodiversidade são apresentados. Este trabalho se iniciou em 2010 com a publicação do Catálogo de Plantas e Fungos e, desde então vem sendo atualizado por mais de 430 especialistas trabalhando online. O Brasil abriga atualmente 32.086 espécies nativas de Angiospermas e 23 espécies nativas de Gimnospermas e estes novos dados mostram um aumento de 3% da riqueza em relação a 2010. A Amazônia é o Domínio Fitogeográfico com o maior número de espécies de Gimnospermas, enquanto que a Floresta Atlântica possui a maior riqueza de Angiospermas. Houve um crescimento considerável no número de espécies e nas taxas de endemismo para a maioria dos Domínios (Caatinga, Cerrado, Floresta Atlântica, Pampa e Pantanal), com exceção da Amazônia que apresentou uma diminuição de 2,5% de endemicidade. Entretanto, a maior parte das plantas com sementes que ocorrem no Brasil (57,4%) é endêmica deste território. A proporção de formas de vida varia de acordo com os diferentes Domínios: árvores são mais expressivas na Amazônia e Floresta Atlântica do que nos outros biomas, ervas são dominantes no Pampa e as lianas apresentam riqueza expressiva na Amazônia, Floresta Atlântica e Pantanal. Este trabalho não só quantifica a biodiversidade brasileira, mas também indica as lacunas de conhecimento e o desafio a ser enfrentado para a conservação desta flora.
Abstract An updated inventory of Brazilian seed plants is presented and offers important insights into the country's biodiversity. This work started in 2010, with the publication of the Plants and Fungi Catalogue, and has been updated since by more than 430 specialists working online. Brazil is home to 32,086 native Angiosperms and 23 native Gymnosperms, showing an increase of 3% in its species richness in relation to 2010. The Amazon Rainforest is the richest Brazilian biome for Gymnosperms, while the Atlantic Rainforest is the richest one for Angiosperms. There was a considerable increment in the number of species and endemism rates for biomes, except for the Amazon that showed a decrease of 2.5% of recorded endemics. However, well over half of Brazillian seed plant species (57.4%) is endemic to this territory. The proportion of life-forms varies among different biomes: trees are more expressive in the Amazon and Atlantic Rainforest biomes while herbs predominate in the Pampa, and lianas are more expressive in the Amazon, Atlantic Rainforest, and Pantanal. This compilation serves not only to quantify Brazilian biodiversity, but also to highlight areas where there information is lacking and to provide a framework for the challenge faced in conserving Brazil's unique and diverse flora.
https://doi.org/10.1590/2175-7860201566411
33340 downloads
11.
Mapping of sites in forest stands
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Geralmente as empresas florestais usam a área total de um ano de plantio como estrato mínimo do total da população e, consequentemente, o processamento do inventário florestal tem sido realizado pela aplicação da amostragem aleatória estratificada. Este estudo foi realizado na Floresta Nacional de Três Barras, Brasil, e teve como objetivo classificar e mapear os locais onde Pinus elliottii se destaca. A amostragem sistemática foi estruturada em grupos e aplicada de forma independente por compartimentos. Os conglomerados em cruz maltesa, foram compostos por quatro subunidades de amostragem, utilizando o método de amostragem Prodan com um número fixo de seis árvores. Pela análise da metodologia, foi possível confirmar as hipóteses: a) o afinamento seletivo causa expressivo aumento de variabilidade volumétrica dentro dos compartimentos; b) a variação de locais no interior dos compartimentos provoca a expansão volumétrica de variância e esta cresce proporcionalmente à qualidade dos sítios; c) a estratificação em locais resulta em menor variância dentro deles; d) a estratificação em locais resultou em redução de até 91% das variâncias dentro deles.
Generally, the forest companies use the total one year planting area as a minimum stratum of the total population and, consequently, the forest inventory processing has been conducted by applying the stratified random sampling to it. This study was carried out in the National Forest of Tres Barras, Brazil, and it aimed to classify and map the sites of Pinus elliottii stands. A systematic sampling was structured into clusters and applied independently by compartments. The clusters, in maltese cross, were composed of four sampling subunits, using Prodan sampling method with a fixed number of six trees. By analysis of the methodology it was possible to confirm the hypothesis: a) the selective thinning cause expressive increase of volumetric variability within compartments; b) the variation of sites within the compartments causes volumetric expansion of variance and this grows proportionally to the quality of the sites; c) the stratification in sites results in minimum variance within them; d) the stratification in sites resulted in until to 91% reduction of variances within them.
https://doi.org/10.1590/0001-3765201420130480
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