ABSTRACT Background: The insertion of stand variables allows for generalized mixed-effects height-diameter model, and the inclusion of random effects aids in model flexibility and application to new databases through calibration. This study aimed to develop a generalized mixed-effects model capable of accurately predicting the total height of Pinus taeda trees, subjected to different management regimes and at different ages. Results: Experimental data between 4 and 27 years of age collected from stands of Pinus taeda located in the State of Santa Catarina were used. The experiment covers a combination of different planting densities and thinning intensities. The Lasso method was used to select the model’s independent variables, and mixed modeling was implemented, with calibration using BLUP (best linear unbiased predictor). Dominant height and quadratic mean diameter were selected in different formulations by the Lasso method to compose the predictor variables of the model, along with diameter at 1.3 m (dbh). Random effects were entered into the intercept and inverse of dbh terms of the model. Conclusion: The results show that the generalized model developed presents flexibility and can be applied to Pinus taeda stands in southern Brazil using the calibration of random effects, when necessary, by collecting a small sample of plot data. Background mixedeffects heightdiameter trees ages Results 2 intensities models s implemented best predictor. . predictor) 13 1 3 1. dbh. (dbh) Conclusion necessary (dbh

RESUMO A dominância, tamanho e posição sociológica das espécies arbóreas são aspectos cruciais para os padrões naturais das florestas, fornecendo informações de grande relevância. Esses padrões podem ser influenciados por uma série de fatores. Assim, o objetivo deste estudo foi avaliar o uso de variáveis espectrais, hidrológicas e geográficas para estimar o estoque de carbono acima do solo (AGC) em quatro estratos de dossel definidos por percentis diamétricos em um remanescente de Mata Atlântica brasileira. Utilizamos técnicas de aprendizado de máquina (Random Forest - RF + Algoritmo Genético - GA) e Regressão Linear Múltipla (MLR) para modelar o AGC. Nossos resultados indicam uma alta variação nos valores de AGC nas parcelas, variando de 0,37 a 467,71 MgC.ha-1, com média de 77,4 MgC.ha-1. Os conjuntos formados por árvores nos percentis 30, 60 e 90 contribuíram, respectivamente, com 97,32%, 87,74% e 52,02% do AGC total. As variáveis espectrais e hidrológicas se associam à área basal para explicar o estoque de AGC. Nossas descobertas comprovam a eficácia de ambos os métodos na obtenção de estimativas precisas de carbono e na geração de um conjunto de dados otimizado. Árvores no percentil 30 representam uma parte menor do AGC total, e a remoção dessas árvores não interfere na relação entre AGC e variáveis espectrais. dominância florestas relevância fatores Assim (AGC brasileira Random GA MLR (MLR parcelas 037 0 37 0,3 46771 467 71 467,7 MgC.ha1, MgCha1 MgCha MgC.ha 1, MgC ha 1 MgC.ha-1 774 77 4 77, MgC.ha1. 1. 6 9 contribuíram respectivamente 9732 97 32 97,32% 8774 87 74 87,74 5202 52 02 52,02 total otimizado 3 03 0, 4677 46 7 467, ha1 MgC.ha1 MgC.ha- 973 97,32 877 8 87,7 520 5 52,0 97,3 87, 52, 97,

ABSTRACT The dominance, size, and sociological position of tree species are essential components of natural forest patterns, providing critical information for understandinh forest dynamics. These patterns can be influenced by a variety of factors. This study aimed to evaluate the effectiveness of using spectral, hydrological, and geographical variables to estimate aboveground carbon stock (AGC) across four canopy strata, defined by diametric percentiles, in a Brazilian Atlantic Forest remnant. Our methodology, which employed machine learning techniques (Random Forest - RF + Genetic Algorithm - GA) and Multiple Linear Regression (MLR) to model AGC, proved to be highly efficient, as evidenced by our results. We observed a wide range of AGC values, from 0.37 to 467.71 MgC.ha-1, with an average of 77.4 MgC.ha-1. Trees in the 30th, 60th, and 90th percentiles contributed, respectively, 97.32%, 87.74%, and 52.02% of the total AGC. Spectral and hydrological variables combined with basal area explain AGC stock. Our findings demonstrate the robustness of machine learning techniques and MLR methods in obtaining accurate carbon estimates and generating an optimized dataset. Trees within the 30th percentile represent a smaller portion of the total AGC, and their removal does not interfere with the relationship between AGC and spectral variables. dominance size dynamics factors (AGC strata remnant methodology Random GA (MLR efficient results values 037 0 37 0.3 46771 467 71 467.7 MgC.ha1, MgCha1 MgCha MgC.ha 1, MgC ha 1 MgC.ha-1 774 77 4 77. MgC.ha1. 1. th 60th contributed respectively 9732 97 32 97.32% 8774 87 74 87.74% 5202 52 02 52.02 dataset 03 3 0. 4677 46 7 467. ha1 MgC.ha1 MgC.ha- 973 9 97.32 877 8 87.74 520 5 52.0 97.3 87.7 52. 97. 87.

Resumo O objetivo deste trabalho foi aplicar o algoritmo “random forest” (RF) à modelagem do estoque de carbono acima do solo (CAS) de uma floresta tropical, por meio da testagem de três procedimentos de seleção de variáveis: remoção recursiva e algoritmos genéticos (AGs) uniobjetivo e multiobjetivo. Os dados utilizados abrangeram 1.007 parcelas amostradas na bacia hidrográfica do Rio Grande, no estado de Minas Gerais, Brasil, e 114 variáveis ambientais (climáticas, edáficas, geográficas, de terreno e espectrais). A melhor estratégia de seleção de variáveis – a RF com AG multiobjetivo – chega ao menor erro quadrático de 17,75 Mg ha-1 com apenas quatro variáveis espectrais – índice de umidade por diferença normalizada, textura de correlação do índice de queimada por razão normalizada 2, cobertura arbórea e fluxo de calor latente –, o que representa redução de 96,5% no tamanho do banco de dados. As estratégias de seleção de variáveis ajudam a obter melhor desempenho da RF, ao melhorar a acurácia e reduzir o volume dos dados. Embora a remoção recursiva e o AG multiobjetivo mostrem desempenho semelhante como estratégias de seleção de variáveis, esta último apresenta menor subconjunto de variáveis, com maior precisão. As descobertas deste trabalho destacam a importância do uso de infravermelho próximo, comprimentos de onda curtos e índices de vegetação derivados para a estimativa de CAS baseada em sensoriamento remoto. Os produtos MODIS mostram relação significativa com o estoque de CAS e precisam ser melhor explorados pela comunidade científica para a modelagem deste estoque.

Abstract The objective of this work was to apply the random forest (RF) algorithm to the modelling of the aboveground carbon (AGC) stock of a tropical forest by testing three feature selection procedures – recursive removal and the uniobjective and multiobjective genetic algorithms (GAs). The used database covered 1,007 plots sampled in the Rio Grande watershed, in the state of Minas Gerais state, Brazil, and 114 environmental variables (climatic, edaphic, geographic, terrain, and spectral). The best feature selection strategy – RF with multiobjective GA – reaches the minor root-square error of 17.75 Mg ha-1 with only four spectral variables – normalized difference moisture index, normalized burnratio 2 correlation text ure, treecover, and latent heat flux –, which represents a reduction of 96.5% in the size of the database. Feature selection strategies assist in obtaining a better RF performance, by improving the accuracy and reducing the volume of the data. Although the recursive removal and multiobjective GA showed a similar performance as feature selection strategies, the latter presents the smallest subset of variables, with the highest accuracy. The findings of this study highlight the importance of using near infrared, short wavelengths, and derived vegetation indices for the remote-sense-based estimation of AGC. The MODIS products show a significant relationship with the AGC stock and should be further explored by the scientific community for the modelling of this stock.

ABSTRACT Background: Process-based modeling is made to simulate the interactions of the soil-plant-atmosphere system providing information and estimates for forest management and services. Through bibliometric evaluation we identify the quantitative state of the art on the use of Process-Based Models (PBMs) applied in forestry studies, contextualizing research fronts, and analyzing the main topics and emerging themes. Data from the Web of Science and Scopus were used for the bibliometric survey of 533 scientific records. Results: We verified that (i) the number of publications related to the PBMs was boosted in the year 2000, and is growing; (ii) Forest Ecology and Management (74 publications) is the journal that most publishes on the subject; (iii) Annikki Mäkelä is the most productive researcher (20 publications) and most cited (h-index: 12); (iv) The USA (131 records) is the country with the highest number of research; (v) there are eight collaborative networks between the authors, three workings together, and five producing in isolation; (vi) the keywords are grouped into five clusters: (a) the effect of climate change on forests; (b) carbon studies; (c) physiology of trees; (d) silvicultural practices and; (e) analysis of model uncertainties. The separation of themes showed that the new search hotspots are the PBMs using of remote detection tools. Conclusion: The results presented can be a fundamental theoretical tool for understanding the trends and development perspectives of this research line in future studies.

ABSTRACT The objective of this study was to evaluate the use of the MSI Sentinel-2 and SRTM data to estimate the volume of wood in a Semidecidual Seasonal Forest. Regression equations were fitted based on the remote sensing data, taking into consideration the individual bands and vegetation index of the MSI, elevation values and their derivatives obtained from the SRTM mission and the combination of the data drawn from the MSI and SRTM. RMSE and graphic analysis of residues were used to assess the accuracy of the fitted equations. The best model revealed values of 0.6508 and RMSE of 20.41% in the fit, and of 0.5680 and RMSE of 26.61% in the validation, using the combined MSI and SRTM data as predictors. The volume estimation using spectral data showed satisfactory results, highlighting the importance of topography in the prediction of the volume of wood for the area under investigation.

ABSTRACT This study aimed to evaluate the growth of Eremanthus erythropappus (DC.) MacLeish submitted to different planting spacing and growth modelling based on the diameter and crown area projection, as well as to identify the best management strategy to be applied to control the competition, period and intensity of thinning. The evaluated planting spacings were: 1.5 × 1.5 m; 1.5 × 2.0 m; 1.5 × 2.5 m and 1.5 × 3.0 m. Diametric growth modelling in function of the age and crown area projection according to the mixed models methodology was efficient and the individual tree modelling allowed for defining a correct thinning prescription for tree plantations in relation to the percentage of removal needed at each spacing, thus permitting the trees to grow free from competition and produce trees with larger diameters.

ABSTRACT The state of Minas Gerais has a high ecological relevance mainly due to its forest species diversity. Understanding the spatialization of that diversity is of importance to develop environmental public policies. The hypothesis of this study is that the tree species diversity from different forest types, in the state of Minas Gerais, presents distribution with spatial dependence. Thus, the objective of this work was to prove that spatial dependence and to relate it between the forest types. Data from the project called “Forest Inventory of Minas Gerais” were used to calculate indices of Shannon, Simpson and Pielou. We used geostatistical and kriging tools to create spatial maps. As results, the mappings indicated that the state presents well-defined gradients of diversity and richness of forest species, increasing in North-South and from West-East directions. The spatial dependence and the spatialization of the tree species diversity show that the geostatistical modeling is a tool that supports the forest resource management. The maps of diversity can be used as indicators of potential areas for creating Conservation Units, establishing ecological corridors, besides supporting environmental policy development.

RESUMO O objetivo deste trabalho foi determinar o número adequado de discos de madeira, as melhores posições de amostragem, ao longo do fuste e propor equações que permitam estimar a densidade básica da madeira de árvores, a partir de um número reduzido de discos, em diversas fisionomias florestais, para subsidiar estimativas de biomassa. Os dados de cubagem rigorosa das árvores foram obtidos no Inventário Florestal de Minas Gerais, advindas de 1.325 árvores, distribuídas em regiões, classes de diâmetro e altura e em diversas fisionomias florestais. De cada árvore foram retirados cinco discos de madeira nas posições 0 (A), 25 (B), 50 (C), 75 (D) e 100% (E) da altura comercial. A densidade básica da madeira de cada disco foi determinada, conforme a ABNT NBR 11.941 (2003), e a densidade geral do fuste, a partir da média aritmética entre as densidades dos discos. Os dados foram analisados, com base na análise de regressão, critério de informação de Akaike, erro padrão da estimativa e análise gráfica de resíduos. Os resultados indicaram que, em geral, a melhor posição de amostragem, para estimativa da densidade básica da madeira do fuste com apenas um disco, deve ser efetuada na metade do fuste principal, com dois discos nas posições 25 e 75% da altura e com três discos nas posições 0, 50 e 100% da altura do fuste. Observou-se, também, que a melhor estimativa da densidade básica do fuste sempre será dada por aquela com maior número de discos, entretanto, é possível estimar com alta precisão a densidade do fuste com menor número de discos, desde que amostrados em posições específicas do fuste e inseridos nas equações propostas de acordo com cada fitofisionomia.

ABSTRACT The objective of this study was to determine the most suitable number of discs, the best sampling positions along the stem and to propose equations to estimate the basic density of trees using a reduced number of discs in various phytophysiognomies, in order to subsidize biomass estimates. The detailed scaling data of the trees were obtained from the Forest Inventory of Minas Gerais state, and is composed by 1,325 trees distributed in regions, diameters and height classes and various forest formations. We took five discs from each at positions 0 (A), 25 (B), 50 (C) 75 (D) and 100% (E) of commercial height. The density of each disk was determined according to ABNT NBR 11.941 (2003) and the overall stem density from the arithmetic mean of the disc densities. Analyses were performed by regression analysis, the Akaike Information Criterion, Standard Error of the Estimate and graphical analysis of residuals. The results indicated that, in general, the best sampling position for estimating the basic density of stem wood with only one disc should be performed in the middle of the main stem, with two discs in positions 25 and 75% in height and with three discs at positions 0, 50 and 100% of the stem height. We also observed that the best estimate of stem density will always be given by the largest number of discs. However, it is possible to estimate the density of the trees with high precision, with a smaller number of discs provided that they are sampled at specific positions of the stem and inserted in the Equations according to each phytophysiology.

ABSTRACT The use of height-diameter models have important applications in the management of eucalyptus plantations. The aim of this paper is to provide adequate height models based on the diameter and stand variables that could be easily used and applied to plantation’s management. The data was based on tests located in Espírito Santo and Bahia. A total of 312 plots, including 35 different treatments (different initial planting densities, number and severity of thinning operations, fertilization regimes, among others), and four different clones. This resulted in 2,407 conditions for 85,608 tree measurements. The constructed equations were based on mixed-effect models, in order to accommodate possible autocorrelations, to address variations between sites and to obtain locally calibrated estimates. Among the different model structures and combination of variables tested and presented, the best model showed a coefficient of determination of 0.953 and 0.988, for the fixed and fixed+random parts, respectively. The model included a random factor for measurements-within-tree and tree-within-plot. The bias of the fixed part was 0.208 cm (0.0659%). We believe the models in this study can have broad applications in management and inventory methods applied to plantations.

RESUMO O crescimento da demanda por madeira se dá em qualidade e quantidade, sendo os estudos econômicos fundamentais na análise da viabilidade de projetos florestais. Tais estudos estão alinhados aos estudos de manejo e silvicultura, destacando a modelagem do crescimento e produção. Este trabalho propõe a avaliação econômica da implantação do mogno africano no Brasil sob diferentes perspectivas de manejo florestal. Os dados são provenientes de plantios com idades variando de 1,1 a 15 anos localizados em diferentes regiões do Brasil. Uma análise financeira foi realizada utilizando o Valor Presente Líquido (VPL), Taxa Interna de Retorno (TIR) e Valor Anual Equivalente (VAE) para uma rotação de 20 anos de idade considerando diferentes regimes de desbaste (A - não desbastado, B - um desbaste aos 10 anos de idade com 150 árvores por hectare remanescentes e C - dois desbastes, primeiro na idade de 8 anos remanescendo 150 árvores por hectare e segundo aos 15 anos com 75 árvores por hectare remanescentes) considerando uma densidade inicial de 278 árvores por hectare. Uma simulação de Monte Carlo foi realizada levando em consideração diferentes variáveis de risco. Os resultados mostraram que a taxa de desconto foi a variável que mais influenciou a viabilidade do investimento. Todas as classes de sítio nos diferentes regimes de manejo apresentaram valores de VPL positivos, variando de 25.053 a 125.780 reais por hectare, sendo os regimes B e C os melhores. A simulação de Monte Carlo mostrou que a probabilidade de insucesso do investimento é praticamente zero, destacando o mogno africano como uma boa opção para investimento florestal, uma vez que possui altos valores de taxa interna de retorno (14% a 25%), superiores à maioria das taxas de investimento disponíveis no mercado.

ABSTRACT Wood demand is increasing in quality and quantity, and economic studies are fundamental to analyze the feasibility of forest projects. These researches are in line with management and silvicultural studies, highlighting growth and yield modeling. This paper proposes an economic evaluation of implementation of African mahogany stands in Brazil under different perspectives of forest management. Data are from plantations ranging from 1.1 to 15 years old in different Brazilian regions. Financial analysis was undertaken using Net Present Value (NPV), Internal Rate of Return (IRR) and Equal Annual Equivalent (EAE) for a 20-year period considering three thinning management regimes (A - unthinned, B - one thinning at age 10 years remaining 150 trees ha-1 and C - two thinnings, first at age 8 remaining 150 trees ha-1 and second at age 15 years remaining 75 trees ha-1) considering an initial density of 278 trees ha-1. A Monte Carlo simulation was performed considering six risk variables. Results showed that the discount rate is the variable that most influences the viability of the project. All site indexes in all management regimes lead to a feasible financial return, with NPV values ranging from 25,053 to 125,780 Brazilian reais per hectare, being regimes B and C the best ones. The probability for an unfeasible investment is almost zero, highlighting African mahogany as a great forest investment opportunity, providing high interest rates values (14% to 25%), superior to most available market rates of return.

ABSTRACT We reviewed key studies published so far regarding Eremanthus erythropappus (DC.) MacLeish (Candeia), in order to approach the sustainable management of this species. The objective of this study was to discuss what is already known by the scientific community, presenting the current scenario and outlining the main challenges that still need to be addressed. Candeia is a tree species found in some Brazilian states, being used in the production of fence posts, and essential oils. It aids in the preservation and restoration of natural areas when properly managed, promoting social development through the creation of jobs and economic growth, due to the current high demand and market value for its products. Due to the high value of its timber, there is a strong anthropic pressure on this species, and it has consequently been exploited in an unsustainable manner. However, already published research suggests that well-managed stands of Eremanthus erythropappus can be economically feasible.

RESUMO A serrapilheira corresponde à camada de matéria morta em decomposição presente sobre o solo. Esta camada é de grande importância na ciclagem de nutrientes e aporte de matéria orgânica sobre o solo, além de estocar carbono. Objetivou-se quantificar a biomassa, teor e estoque de carbono e espacializar o estoque de C da serrapilheira do Cerrado de Minas Gerais. Os dados foram coletados em 26 fragmentos de Cerrado no Estado de MG, totalizando 335 pontos amostrados em todo estado. Foi realizado o estudo variográfico e, para o mapeamento, utilizou-se a Krigagem, para delimitação de zonas homogêneas. Foi possível detectar alta variabilidade nas características avaliadas, biomassa, teor e estoque de carbono na serrapilheira do Cerrado em Minas Gerais, Brasil. O teor de C foi a característica que apresentou menor variabilidade, com intervalo de 40-44%, de modo que não é um atributo crítico para explicar o estoque de C na serrapilheira. O Campo Cerrado tem o mais baixo estoque de C, e o Cerradão o mais alto. O estoque de C apresenta considerável dependência da estrutura espacial, permitindo o uso de procedimentos geoestatísticos para mapeá-lo no bioma Cerrado do estado de Minas Gerais. O mapa de krigagem de estoque de C mostrou boa precisão e com base nele, foi possível verificar que os estoques de menor teor de carbono na serrapulheira são encontrados do centro para o norte do estado de Minas Gerais, onde tem-se as maiores temperaturas médias anuais.

ABSTRACT Litter corresponds to the layer of decomposing dead organic matter present on the soil surface. This layer is very important for nutrient cycling and contributes with organic matter accumulation in the soil, besides the carbon stock. The objective herein was to quantify the carbon biomass, both content and stock, and map the litter C-stock in the Cerrado biome, which is formed by Savanna Grassland (SG), Cerrado Stricto Sensu (CE) and Forest Savanna (FS), in Minas Gerais state, southeastern Brazil. The data were collected in 26 fragments in Minas Gerais state, totaling 210 sampling locations. A variographic study was conducted and, for mapping, the ordinary kriging method was used for delimitation of homogeneous zones. It was possible to detect high variability in the carbon biomass, carbon content and C-stock in the Cerrado biome litter in Minas Gerais state. The carbon content presented lower variability, ranging from 40 to 44%, so that it is not responsible for explaining the variability of the litter C-stock. Savanna Grassland and Savanna Forest present, respectively, the lowest and highest C-stocks. C-stock presented a considerable spatial structure dependence, allowing to use the geostatistical procedures for mapping it in the Cerrado biome of the Minas Gerais state. The C-stock kriging map showed good accuracy, allowing to verify that the lowest C-stocks in the litter are found from the center to the northern of the Minas Gerais since the highest air temperatures are also verified in this direction.

RESUMO Ecossistemas florestais contribuem significativamente para estocar gases do efeito estufa. Objetivou-se investigar a distribuição espacial e vertical do carbono em serapilheira, raízes e solo. Foram obtidos biomassa e carbono de compartimentos (serapilheira, raiz e solo) em vegetação do bioma Cerrado, Minas Gerais, Brasil. O material foi coletado em 7 sub-parcelas de 0,5 m² aleatoriamente alocadas na vegetação. As amostras de raízes e solo foram tiradas de cinco camadas do solo na profundidade de 0-100 cm. Raízes foram classificadas em três classes: raízes finas (<5 mm), médias (5-10 mm) e grossas (>10 mm). Estoques de carbono foram mapeados usando análise geoestatística. Resultados indicaram médias do estoque de carbono no solo de 208,5 Mg.ha-1 (94,6% do carbono total), carbono nas raízes de 6,8 Mg.ha-1 (3,1%), e na serapilheira de 5 Mg.ha-1 (2,3%). Carbono de raízes foi majoritariamente estocado nas raízes grossas (83%), seguido das finas (10%) e médias (7%). A maior porção das raízes finas se concentrou na camada de 0-10 cm, enquanto que raízes médias e grossas majoritariamente entre 10-20 cm. A maior porção do carbono em solo (53%) e raízes (85%) estiveram estocados nas camadas superficiais do solo (acima de 40 cm). Como conclusão, a distribuição espacial do carbono segue razoável tendência entre os compartimentos. Há uma relação vertical de que quanto mais profunda a camada de solo, menor o estoque de carbono de solo e raízes. Com exceção da camada de solo mais superficial, raízes grossas estocaram a maior porção de carbono nas profundidades avaliadas.

ABSTRACT Forest ecosystems contribute significantly to store greenhouse gases. This paper aimed to investigate the spatial and vertical distribution of litter, roots, and soil carbon. We obtained biomass and carbon of compartments (litter, roots, and soil) in a vegetation from Cerrado biome, state of Minas Gerais, Brazil. The materials were collected in 7 0.5 m² sub-plots randomly allocated in the vegetation. Root and soil samples were taken from five soil layers across the 0-100 cm depth. Roots were classified into three diameter classes: fine (<5 mm), medium (5-10 mm), and coarse (>10 mm) roots. The carbon stock was mapped through geostatistical analysis. The results indicated averages of soil carbon stock of 208.5 Mg.ha-1 (94.6% of the total carbon), root carbon of 6.8 Mg.ha-1 (3.1%), and litter of 5 Mg.ha-1 (2.3%). The root carbon was majority stored in coarse roots (83%), followed by fine (10%), and medium roots (7%). The largest portion of fine roots concentrated in the 0-10 cm soil depth, whereas medium and coarse roots were majority in the 10-20 cm depth. The largest portion of soil (53%) and root (85%) carbon were stored in superficial soil layers (above 40 cm). As conclusion, the carbon spatial distribution follows a reasonable trend among the compartments. There is a vertical relation of which the deeper the soil layer, the lower the soil and root carbon stock. Excepting the shallowest layer, coarse roots held the largest portion of carbon across the evaluated soil layers.

RESUMO O setor florestal brasileiro está em plena expansão e com um aumento gradativo de investidores florestais optando pelo cultivo de espécies de madeira nobre. O mogno africano (Khaya spp.) é uma espécie que vêm se destacando na preferência dos empresários como opção no investimento florestal. Porém, estudos e pesquisas sobre a espécie, principalmente no Brasil, são escassos. Assim, a presente revisão procurou reunir diversas fontes de publicação, nacionais e internacionais, abordando aspectos históricos do mogno, buscando aclarar as características da espécie e a experiência de outros países no manejo dessa cultura.

ABSTRACT The Brazilian forest sector is fast growing with a gradual increase of forest investors choosing valuable hardwood species for tree crops. African mahogany (Khaya spp.) is a species that has been preferred by many entrepreneurs as a forestry investment. However, there are few studies and research on the species, especially in Brazil. Therefore, this review aimed to bring together diverse sources of national and international publications, discussing the history of the mahogany and characteristics of the species as well as the experience of other countries on the management of this crop.

RESUMO A estimativa da qualidade de sítio é uma importante ferramenta para o manejo florestal, uma vez que auxilia na modelagem do crescimento e produção de florestas equiâneas. Dados de plantios brasileiros de mogno africano (Khaya ivorensis A. Chev.) foram utilizados para avaliar modelos de crescimento em altura dominante comparando modelos dinâmicos invariantes com a idade padrão e modelos estáticos (método da curva guia). Para a avaliação dos modelos foram utilizados critérios quantitativos e qualitativos. Também foi verificada a estabilidade dos modelos candidatos, sendo preferido o modelo que resultou em menos mudanças de classes na predição da mesma parcela em diferentes idades. O modelo de Lundqvist-Korf com o método da curva guia se mostrou eficiente, sendo recomendado para a classificação de sítios e para a predição de altura dominante em povoamentos de mogno africano. A amplitude dos índices de sítio, na idade de referência de 15 anos, foi de 17 a 33 metros.

ABSTRACT Site quality estimation is an important tool in forest management since it is useful for modeling growth and yield for even-aged stands. Data from African mahogany (Khaya ivorensis A. Chev.) Brazilian plantations were used to develop a model to predict dominant height growth, comparing dynamic base-age invariant site index models with the guide curve method (static models). For the evaluation of the candidate models qualitative and quantitative criteria were used. We also verified the stability of the candidate models, preferring a model providing fewer site class changes when predicting site index from different ages. The Lundqvist-Korf function fitted with the guide curve method proved to be effective and accurate for site classification and dominant height predictions of African mahogany stands. The range of observed site index, at a reference age of 15, was between 17 and 33 meters.