Search

Taper functions have been widely used for various purposes. Several functions were developed and successfully applied; however, most of these functions fail to account for the influence of stand-level and individual-tree effects of variation on the stem profile. Hence, we aimed in this study to assess how these factors influence the stem profile of black wattle (Acacia mearnsii De Wild.) trees in southern Brazil. There is a notable necessity for developing a domestic market for black wattle solid wood. The database was composed of 218 black wattle trees at age 10 years distributed across the state of Rio Grande do Sul, Brazil. A dimensionally compatible taper equation combined with the mixed-effect modeling approach was used. Additionally, auxiliary variables were included to build a generalized taper function that explains stem form variations. In general, all variables showed a significant influence on the stem profile, except the crown ratio. The inclusion of relative spacing and tree hierarchical position in the taper function resulted in higher accuracy when estimating stem diameters and total tree volume. This study indicates that accounting for attributes at the stand and individual-tree levels may improve stem profile predictions, as well as the biological soundness of the taper function.

Full waveform (FW) LiDAR systems have gained momentum to map forest biophysical variables in the last two decades, owing to their ability to accurately estimate canopy heights and aboveground biomass. Currently, the Global Ecosystem Dynamics Investigation (GEDI) system on board of the International Space Station (ISS) is the most recent FW spaceborne LiDAR instrument for the continuous observation of earth's forests. Here, we assess the accuracy of GEDI FW data for the estimation of stand-scale dominant heights ( $H_{dom}$ ), and stand volume (V) using linear and nonlinear regression models based on several GEDI metrics. The models were calibrated and validated using in-situ data from Eucalyptus plantations in Brazil. Overall, the most accurate estimates of $H_{dom}$ and V were obtained using the stepwise regression, with an RMSE of 1.44 m (R2 of 0.92) and 24.39 m3.ha−1 (R2 of 0.90) respectively. The principal metric explaining more than 87% and 84% of the variability (R2) of $H_{dom}$ and V was the metric representing the height above the ground at which 90% of the waveform energy occurs.

Understanding the interaction between the hydrological cycle and native forests is essential to improve watershed management and support ecological services. The objectives of this study were to analyse and evaluate rainfall interception models applied to an ecosystem from the Brazilian Atlantic Forest Biome (BAFB), classified as “Montane Semi-Deciduous Forest.” The variables Gross Rainfall (P) (rainfall that reaches the canopy), Throughfall (Tf), Stemflow (Sf), and Interception Loss (I) were measured from September 2012 to March 2015. Weather variables were quantified above the canopy by a weather station and then used for canopy evaporation estimation. This estimation was based on two approaches: the slope of the linear regression of gross rainfall against interception, or the Gash procedure (Ev1), and the Penman–Monteith equation (Ev2). Two rainfall interception models (Liu and Gash) were employed, using both Ev1 and Ev2. Thirty-two fixed rain gauges were used for Tf measurements and 32 trees were selected across species and diameter at breast height ranges for Sf observations. The revised version of the analytical Gash model underestimated I by -17.5% and -11.1% for Ev1 and Ev2, respectively, resulting in less accurate estimates. Based on these relative errors, the performance of the Gash model was classified as “fair.” The Liu model overestimated I by 5.3% and 11.3% for Ev1 and Ev2, resulting in assessments of “good” and “fair” respectively, and thus indicating improved performance compared to the Gash model. Therefore, the Liu model coupled with Ev1 is preferable for simulation of rainfall interception in semi-deciduous forests of the BAFB. However, slight overestimation bias was observed, and the model requires tweaking with respect to the estimation of forest storage capacity for this ecosystem. Interception loss modelling is a strategic tool for assessing the influence of different weather patterns and forest vegetative features on water balance in semi-deciduous forest ecosystems.

Made available in DSpace on 2020-12-10T19:36:21Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-09-15 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) University of Sao Paulo Sao Paulo State University Federal University of Lavras Federal University of Rio Grande do Norte Colorado State University North Carolina State University USDA Forest Service Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Anglo American Arauco Arborgen ArcelorMittal Cenibra CMPC Comigo Copener Duratex Eldorado Fazenda Campo Bom Fibria Florestal Itaquari Forestal Oriental Gerdau GMR International Paper Jari Klabin Lwarcel Montes del Plata Plantar Rigesa Suzano Vallourec Veracel Growth and yield (G &Y) model systems aim at forecasting forest productivity. The lack of environmental variables to account for how water availability constrains eucalyptus production in Brazil, however, is argued to be a major drawback of these model systems. Thus, this study aimed to develop a stand-level G & Y model system that accounts for water availability (G & Y with SWD), highlighting its usefulness when applied for clonal eucalypt stands under drier climatic conditions. The dataset is composed of remeasurement information of sixteen research sites that span all climatic regions in Brazil. A total of eleven eucalypt clones were planted in single block plots at each site, and extra replications under the rainfall exclusion system were also installed for these eleven clones in fourteen sites. Linear algebra techniques were used to simultaneously fit a compatible set of prediction and projection basal area equations. A stand-level volume equation was also developed. These equations were validated through the use of an independent dataset composed of the rainfall exclusion plots. Finally, the accuracy and usefulness of a conventional G & Y model system applied to clonal eucalypt stands in Brazil was compared to the new proposed G & Y model system, which accounts for the impact of water availability in eucalyptus productivity. The prediction and projection basal area equations accounting for water availability displayed estimates in the order of 5% more accurate compared to the conventional basal area modeling. Stand-level volume estimates were 40% and 74% less biased through the use of the new G & Y model system. This result highlighted how useful and powerful the newly developed approach is, since the model system was capable to provide accurate estimates through the use of the rainfall exclusion plots. The new G & Y model system is a powerful alternative to estimate forest afforestation yield and is fully capable to accurately update forest inventories. The model system can also be used for projecting how forest growth may be impacted by short-term climate variation. North Carolina State Univ, Dept Forestry & Environm Resources, 2820 Faucette Dr,Campus Box 8001, Raleigh, NC 27695 USA Virginia Polytech Inst & State Univ, Dept Forest Resources & Environm Conservat, 310 W Campus Dr,Campus Box 169, Blacksburg, VA 24061 USA Forestry Sci & Res Inst, Via Comendador Pedro Morganti 3500, BR-13415000 Piracicaba, SP, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ 3780, BR-18610034 Botucatu, SP, Brazil Univ Sao Paulo, Dept Forest Sci, Ave Padua Dias 11, BR-13418900 Piracicaba, SP, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ 3780, BR-18610034 Botucatu, SP, Brazil CNPq: 249979/2013-6

Made available in DSpace on 2019-10-04T12:13:44Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-05-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Anglo American Arauco Arborgen Arcelor-Mittal Cenibra CMPC Comigo Copener Duratex Eldorado Fazenda Campo Bom Fibria Florestal Itaquari Forestal Oriental Gerdau GMR International Paper Jari Klabin Lwarcel Montes del Plata Plantar Rigesa Suzano Vallourec Veracel University of Sao Paulo Sao Paulo State University Federal University of Lavras Federal University of Rio Grande do Norte Colorado State University North Carolina State University USDA Forest Service Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Lack of generalized equations has prevailed in Brazil, because it is assumed that localized or climate-specific equations are needed. This study aimed to develop generalized stem taper and volume equations applicable to 11 eucalyptus clones and evaluate if climate variation impacts the accuracy of the estimates. A total of 693 trees evenly distributed across 11 clones at 21 sites were used for model fittings and predictive validation. The penalized mixed spline (PMS) approach was developed for predicting stem taper and volume along the stem profile. The Schumacher and Hall (1933) equation was used to predict total tree volume, while volume ratio equations were applied to predict merchantable volume. For every fitted equation, an annual climatic variable was included to assess the improvement in model performance. The overall results highlighted that climatic variation does not need to be accounted for in stem taper and volume modeling. All of the equations displayed desirable accuracy, but the generalized PMS equation may be preferred when the forestry enterprise looks to furnish a range of multiple forest products. The generalized total tree volume equation, combined with the ratio equations, is highly recommended when the forestry enterprise produces a single product. North Carolina State Univ, Dept Forestry & Environm Resources, Raleigh, NC 27695 USA Virginia Polytech Inst & State Univ, Dept Forest Resources & Environm Conservat, Blacksburg, VA 24061 USA Forestry Sci & Res Inst, BR-13415000 Sao Paulo, Brazil State Univ Sao Paulo, Dept Forest Sci, BR-18610034 Sao Paulo, Brazil State Univ Sao Paulo, Dept Forest Sci, BR-18610034 Sao Paulo, Brazil CNPq: 249979/2013-6

Made available in DSpace on 2019-10-04T12:34:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-15 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Anglo American Arauco Arborgen ArcelorMittal Cenibra CMPC Comigo Copener Duratex Eldorado Fazenda Campo Bom Fibria Florestal Itaquari Forestal Oriental Gerdau GMR International Paper Jari Klabin Lwarcel Montes del Plata Plantar Rigesa Suzano Vallourec Veracel University of Sao Paulo Sao Paulo State University Federal University of Lavras Federal University of Rio Grande do Norte Colorado State University North Carolina State University USDA Forest Service Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Linking individual-tree and stand-level growth models is required for estimating future forest stand structure, while maintaining the desired accuracy for forest management decision making. There is a scarcity of studies addressing this issue for clonal Eucalypt stands in Brazil. Thus, this paper aims to develop a compatible individual-tree and stand-level growth and yield system for clonal Eucalypt stands in Brazil. The dataset used in this study is derived from remeasurement information of sixteen TECHS sites. At every site, eleven Eucalypt clones were planted in single block plots, while extra plots under a rainfall exclusion regime were also installed in fourteen sites. Prediction and projection diameter percentile equations were developed, as well as an individual-tree mortality equation and a generalized height-diameter equation. In addition, a detailed explanation of the structural architecture of the developed compatible growth and yield system is provided. Differences when forecasting forest afforestation and updating forest inventories were highlighted in order to provide the proper use of the developed growth and yield system. Finally, the individual-tree equations were validated through the use of the rainfall exclusion regime plots as was the growth and yield system when applied for prediction and projection purposes. The individual-tree level equations provided accurate estimates. The newly developed compatible growth and yield system also displayed unbiased and accurate estimates. The system achieved full compatibility between individual-tree and stand-level estimates and produced accurate stand table estimates. The growth and yield system presented is a powerful analytical tool that can serve to update inventory data in tropical Brazil and also to provide estimates for expected forest afforestation. The system has the capability of providing detailed outputs, which allows forest managers to consider merchandizing the clonal Eucalypt stands into multiple products. North Carolina State Univ, Dept Forestry & Environm Resources, 2820 Faucette Dr,Campus Box 8001, Raleigh, NC 27695 USA Virginia Polytech Inst & State Univ, Dept Forest Resources & Environm Conservat, 310 W Campus Dr,Campus Box 169, Blacksburg, VA 24061 USA Univ Fed Santa Catarina, Dept Forestry Agr & Biodivers, Campus Box 101,Rod Ulysses Gaboardi,Km 3, BR-89520000 Curitibanos, SC, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ,3780, BR-18610034 Botucatu, SP, Brazil Univ Sao Paulo, Dept Forest Sci, Ave Padua Dias,11, BR-13418900 Piracicaba, SP, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ,3780, BR-18610034 Botucatu, SP, Brazil CNPq: 249979/2013-6

Made available in DSpace on 2019-10-04T12:34:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-15 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Anglo American Arauco Arborgen ArcelorMittal Cenibra CMPC Comigo Copener Duratex Eldorado Fazenda Campo Born Fibria Florestal Itaquari Forestal Oriental Gerdau GMR International Paper Jani Klabin Lwarcel Montes del Plata Plantar Rigesa Suzano Vallourec Veracel University of Sao Paulo Sao Paulo State University Federal University of Lavras Federal University of Rio Grande do Norte Colorado State University North Carolina State University USDA Forest Service Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Several approaches for modeling whole-stand survival or mortality have been reported in the literature, although this component is often times neglected for clonal eucalypt stands in Brazil. In addition, the traditional form for projecting whole-stand survival appears incomplete for clonal eucalypt stands, since this tree species is highly sensitive to lack of water in the environment. Consequently, this study aimed to define the best approach to estimate whole-stand survival in clonal eucalypt stands and to develop a new approach for modeling whole-stand survival as a function of cumulative soil water deficit. Remeasurement of sixteen research sites composed the database used in this study. At each research site, the same eleven eucalypt clones were planted in single block plots, which results in a total of 176 plots distributed across Brazil. Two traditional approaches (two-step approach and direct estimation) were tested for modeling whole-stand survival. Additionally a new approach that replaces the age term by cumulative soil water deficit (cumulative SWD) was compared to the best selected traditional approach to estimate whole-stand survival in clonal eucalypt stands. The direct projection approach of whole-stand survival displayed better results when compared to the two-step approach. In addition, the replacement of age by cumulative SWD in the direct estimation approach allowed for an increase in the explanatory ability of the developed difference model. The newly developed difference model employing the direct estimation approach constrained by cumulative SWD ensures that the environmental stress effect is reflected on the survival of clonal eucalypt stands over time, and it is more biologically sound for extrapolation purposes. North Carolina State Univ, Dept Forestry & Environm Resources, 2820 Faucette Dr,Campus Box 8001, Raleigh, NC 27695 USA Virginia Polytech Inst & State Univ, Dept Forest Resources & Environm Conservat, 310 W Campus Dr,Campus Box 169, Blacksburg, VA 24061 USA Forestry Sci & Res Inst, Via Comendador Pedro Morganti, BR-13415000 Sao Paulo, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ,3780, BR-18610034 Botucatu, SP, Brazil Univ Sao Paulo, Dept Forest Sci, Ave Padua Dias,11, BR-13418900 Sao Paulo, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ,3780, BR-18610034 Botucatu, SP, Brazil CNPq: 249979/2013-6

Made available in DSpace on 2022-04-28T17:20:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 French Space Study Center (CNES, TOSCA 2020 project) National Research Institute for Agriculture, Food, and the Environment (INRAE) Over the past two decades spaceborne LiDARsystems have gainedmomentumin the remote sensing community with their ability to accurately estimate canopy heights and aboveground biomass. This article aims at using the most recent global ecosystem dynamics investigation (GEDI) LiDAR system data to estimate the stand-scale dominant heights (H-dom), and stand volume (V) of Eucalyptus plantations in Brazil. These plantations provide a valuable case study due to the homogenous canopy cover and the availability of precise field measurements. Several linear and nonlinear regression models were used for the estimation of H-dom and V based on several GEDI metrics. H-dom and V estimation results showed that over low-slopped terrain the most accurate estimates of H-dom and V were obtained using the stepwise regression, with an root-mean-square error (RMSE) of 1.33m(R-2 of 0.93) and 24.39 m(3).ha(-1) (R-2 of 0.90) respectively. The principal metric explaining more than 87% and 84% of the variability (R-2) of H-dom and V was the metric representing the height above the ground at which 90% of the waveform energy occurs. Testing the postprocessed GEDI metric values issued from six available different processing algorithms showed that the accuracy on H-dom and V estimates is algorithm dependent, with a 16% observed increase in RMSE on both variables using algorithm a5 vs. a1. Finally, the choice to select the ground return from the last detected mode or the stronger of the last two modes could also affect the H-dom estimation accuracy with 12 cm RMSE decrease using the latter. Univ Montpellier, French Natl Res Inst Agr Food & Environm INRAE, AgroParisTech, CIRAD,CNRS,TETIS, F-34093 Montpellier, France UNESP, Fac Ciencias Agron, BR-18610034 Botucatu, SP, Brazil Suzano SA, BR-13465970 Limeira, Brazil Univ Montpellier, LISAH, Inst Agro, INRAE,IRD, F-34060 Montpellier, France IRD, CNRS, UPS, Ctr Study Biosphere Space,CNES,INRAE, F-31401 Toulouse, France CIRAD, UMR Eco & Sols, F-34398 Montpellier, France IRD, INRA, CIRAD, Eco & Sols, Montpellier, France Univ Montpellier, SupAgro, F-34060 Montpellier, France UNESP, Fac Ciencias Agron, BR-18610034 Botucatu, SP, Brazil

Brazil nut (Bertholletia excelsa) is one of the most important non-timber forest product (NTFP) species in the world. Better management and conservation practices will only be possible with an in-depth knowledge of tree species ecology. This study aimed to assess the spatial association of fruit yield of Bertholletia excelsa (B. excelsa) trees in two forest types (old growth terra firme forest and Amazon-cerrado transitional forest) in the Brazilian Amazon. Fruit yield was measured in both forest types during 2010. At each forest type, fruit yield was divided into different yield classes (number of fruits) for subsequent spatial modeling. The bivariate Ripley?s K-function was applied to quantify the spatial association of fruit yield of B. excelsa trees over different fruit yield classes. The results revealed that the forest type influences the spatial association of B. excelsa fruit yield. The old growth terra firme forest presented random spatial association for fruit yield, which implies that fruit yield of B. excelsa trees in this forest type is not limited by tree location and site resources. On the other hand, the Amazon-cerrado transitional forest presented significant negative spatial association for fruit yield across different yield classes, which means that under some conditions fruit yield of a given tree influences the fruit yield of the neighboring tree in this forest type. Site resources in the Amazon-cerrado transitional forest is limited and naturally favors inter- and intra-specific competition. Finally, the results imply the need for adoption of different management and conservation strategies for B. excelsa in different forest types in the Brazilian Amazon. Made available in DSpace on 2019-11-18T18:05:43Z (GMT). No. of bitstreams: 1 CPAFAP2019SpatialassociationoffruityielofBertholletia.pdf: 1446611 bytes, checksum: 0663c4cbe619dc9907b50f02093ce2cf (MD5) Previous issue date: 2019

Modeling the growth of Bertholletia excelsa Bonpl. (B. excelsa) trees in natural forests is important for understanding the species’ ecology and for better defining site-specific management. In this sense, this study aimed to model the diameter growth rate of B. excelsa trees in contrasting forest environments in the Brazilian Amazon. This study was conducted in the Extractive Reserve Rio Cajari (RESEX Cajari). Growth models were fitted at species level to predict diameter growth rate in the two Amazonian forest environments. Subsequently, the age at which the B. excelsa tree in each forest environment reaches the minimum diameter for seed production was calculated by integrating the growth models. In each forest environment, the negative exponential behavior of the diametric growth rate of the tree species was fitted by an appropriate model. The time required for B. excelsa trees to reach the minimum diameter was shorter in the secondary forest environment when compared with that of the old growth terra firme forest (47 and 78 years to reach the diameter of 25 cm in the secondary and old growth terra firme forest, respectively). While the average growth pattern indicated higher diameter growth rates of B. excelsa in the secondary forest environment, the high level of uncertainty in the model’s estimation makes this inference complex. In conclusion, the secondary forest seems a favorable forest environment for the growth of B. excelsa trees, which may be an indicator of the potential for secondary forest environments to produce B. excelsa seeds in the future.

Fast-growing Eucalyptus spp. forest plantations and their resultant wood products are economically important and may provide a low-cost means to sequester carbon for greenhouse gas reduction. The development of advanced and optimized frameworks for estimating forest plantation attributes from lidar remote sensing data combined with statistical modeling approaches is a step towards forest inventory operationalization and might improve industry e ciency in monitoring and managing forest resources. In this study, we first developed and tested a framework for modeling individual tree attributes in fast-growing Eucalyptus forest plantation using airborne lidar data and linear mixed-e ect models (LME) and assessed the gain in accuracy compared to a conventional linear fixed-e ects model (LFE). Second, we evaluated the potential of using the tree-level estimates for determining tree attribute uniformity across di erent stand ages. In the field, tree measurements, such as tree geolocation, species, genotype, age, height (Ht), and diameter at breast height (dbh) were collected through conventional forest inventory practices, and tree-level aboveground carbon (AGC) was estimated using allometric equations. Individual trees were detected and delineated from lidar-derived canopy height models (CHM), and crown-level metrics (e.g., crown volume and crown projected area) were computed from the lidar 3-D point cloud. Field and lidar-derived crown metrics were combined for ht, dbh, and AGC modeling using an LME. We fitted a varying intercept and slope model, setting species, genotype, and stand (alone and nested) as random e ects. For comparison, we also modeled the same attributes using a conventional LFE model. The tree attribute estimates derived from the best LME model were used for assessing forest uniformity at the tree level using the Lorenz curves and Gini coe cient (GC).We successfully detected 96.6% of the trees from the lidar-derived CHM. The best LME model for estimating the tree attributes was composed of the stand as a random e ect variable, and canopy height, crown volume, and crown projected area as fixed e ects. The %RMSE values for tree-level height, dbh, and AGC were 8.9%, 12.1%, and 23.7% for the LFE model and improved to 7.3%, 7.1%, and 13.6%, respectively, for the LME model. Tree attributes uniformity was assessed with the Lorenz curves and tree-level estimations, especially for the older stands. All stands showed a high level of tree uniformity with GC values approximately 0.2. This study demonstrates that accurate detection of individual trees and their associated crown metrics can be used to estimate Ht, dbh, and AGC stocks as well as forest uniformity in fast-growing Eucalyptus plantations forests using lidar data as inputs to LME models. This further underscores the high potential of our proposed approach to monitor standing stock and growth in Eucalyptus—and similar forest plantations for carbon dynamics and forest product planning info:eu-repo/semantics/publishedVersion

Taper functions have been widely used with an existing array of model forms and methods; however, comparisons of contrasting statistical methods have been more limited. This study aimed to assess c...

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.

The Atlantic forest biome in Brazil possesses many suitable tree species for cultivation and restoration purposes. This biome was the most rapidly and extensively exploited forest type in Brazil and it displays areas ill-suited for eucalyptus cultivation. Since tropical tree species usually do not form growth rings and long-term growth data are still not available in Brazil, this study addressed a new approach to diameter growth rate estimation. The approach was developed in order to alleviate the shortage of species-specific growth information for the Atlantic forest biome. The two reasons for developing the approach were: (1) the possibility of increased ecological and economic diversification of plantation forests beyond eucalyptus, and (2) the potential to identify suitable tree species for restoration programs in the biome. Either reason requires growth models with sound biological properties. The data used in this study came from 20 native forest fragments and included six tropical tree species. Forest inventory to assess forest growth was first conducted in 2003, while the re-measurement was conducted in 2008. A non-linear exponential model, containing an asymptote parameter as a function of stand density, was fit to estimate tree species diameter growth rate for each of the six tree species in the study. Additionally, based on the exponential model, a formulation of the time required for each tree species to reach a given diameter was developed. The fitted models exhibited high variability among the six tree species, but they performed well with respect to tree growth behavior. Since the model accounted for stand density, it was possible to predict how different stand densities would affect each tree species growth over time. Finally, the tree species Triplaris gardneriana Weddell, Inga vera Willd. and Xylopia brasiliensis Spreng are recommended as potentially fast-growing tree species in the Atlantic forest biome. These tree species exhibited good growth rates regardless the stand density simulated (1600/ha, 2000/ha, and 2400/ha) to reach a dbh of 10 cm (Xylopia brasiliensis Spreng - 16 years, 17 years, and 18 years; Triplaris gardneriana Weddell - 15 years, 17 years, and 21 years; Inga vera Willd. - 25 years, 25.5 years, and 26 years) and showed promising potential for both restoration and production programs. The developed approach reveals a unique diameter growth rate prediction method.

The goals of this study were to identify and group three eucalyptus clones, each under coppice and clear-cut management regimes, into two or more groups based on similar growth rates; and fit a site index equation as a function of rainfall variables for each group to evaluate how different groups were impacted by climatic variation. The database came from the Continuous Forest Inventory (CFI) and weather stations. The CFI was conducted between 1994 and 2012, with climatic data also being gathered for the same period. The study area was managed by clear-cut and coppice regimes, with 126 and 72 CFI plots, respectively. The relationship between clones, management regimes and stand age with annual dominant height growth was assessed by linear mixed effects modeling. Ridge regression was applied for fitting each group as a function of the rainfall variables. Finally, ordinary Kriging was applied for each of the rainfall variables in the study area. Then, site index equations were applied to the generated maps enabling the observation of their pattern throughout the study area as well as their evaluation under a pessimistic climatic scenario. Three groups were defined, since each clone exhibited similar growth behavior under either management regimes; however, the 3 clones differ among each other. A significant reduction in the annual dominant height growth over time was observed for all 3 clones. Ridge regressions afforded good accuracy and equations with sound biological behavior. Applying the fitted site index equations to the maps of precipitation and rainy days enabled the definition of the most appropriate clone to be planted throughout the area. Site quality as a function of rainfall variables could be an important tool to better enable silvicultural planning, since it provides estimates of the site index and also enables the incorporation of short-term climate change.

In recent Eucalyptus cold-tolerance trials, E. benthamii has shown good growth rates as well as cold tolerance for USDA Plant Hardiness Zones 8 and 9. This study developed growth and yield models for E. benthamii in the southeastern United States. A network of 182 temporary sample plots of E. benthamii ranging in age from 1.5 to 13.3 years was established, and inventory data were collected. Site quality was determined by fitting a polymorphic site index curve, whereas a function for stand basal area based on age, dominant height, and site occupancy was fitted. Stand-level volume and dry-weight biomass prediction equations were fitted as a function of dominant height and basal area. Based on the growth and yield model results, mean annual increments ranged from 26.4 m3 ha–1 year–1 at rotation age 6 years on the best sites to 13.7 m3 ha–1 year–1 at rotation age 10 years on the poorest sites. This is the first published set of management-oriented models for land managers considering planting E. benthamii in the southeastern United States.

Made available in DSpace on 2019-10-04T12:34:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-15 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Anglo American Arauco Arborgen ArcelorMittal Cenibra CMPC Comigo Copener Duratex Eldorado Fazenda Campo Bom Fibria Florestal Itaquari Forestal Oriental Gerdau GMR International Paper Jari Klabin Lwarcel Montes del Plata Plantar Rigesa Suzano Vallourec Veracel University of Sao Paulo Sao Paulo State University Federal University of Lavras Federal University of Rio Grande do Norte Colorado State University North Carolina State University USDA Forest Service Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The research objective of this paper was to group eleven widely planted eucalypt clones based on their volume yield pattern by assessing how climatic variation impacts their productivity in tropical Brazil. A total of 187 plots evenly distributed across eleven clones and 17 sites (from Parana to Para State) were used. Plot measurements were carried out every six months (from 2013 to 2017) to evaluate eucalyptus growth. Since the year of plot establishment differs across the sites, volumes of all the plots and sites were standardized at a common age of 5 years. Clonal grouping analysis was performed based on the common age for volume yields using a new approach, which consisted of three steps: (1) create general groups based on testing of the slope coefficient, which was applied to every clonal-specific regression with volume yield as a function of annual water deficit index (WDI); (2) split each general group using volume yield deviation computations into subgroups of high and low productivity; (3) apply linear mixed effects models for every subgroup in order to confirm the non-existence of statistical difference among the volume yield of the clones. Statistical tests showed satisfactory yield estimates at the common age of 5 years. Clonal grouping revealed the identification of four groups (A: high productivity and non-sensitive to climate variation, B: high productivity and sensitive to climate variation, C: low productivity and sensitive to climate variation, D: low productivity and non-sensitive to climate variation). The volume yield of the Clonal group B was detected to be the most impacted by annual water deficit index variation, followed by clonal groups C, A and D. The findings of the study highlighted the utility of the proposed approach for grouping clones. Group identification and detection of the climatic impact on yield patterns was evaluated as a measure to increase site-specific productivity. North Carolina State Univ, Dept Forestry & Environm Resources, 2820 Faucette Dr,Campus Box 8001, Raleigh, NC 27695 USA Virginia Polytech Inst & State Univ, Dept Forest Resources & Environm Conservat, 310 W Campus Dr,Campus Box 169, Blacksburg, VA 24061 USA Univ Fed Santa Catarina, Dept Forestry Agr & Biodivers, Campus Box 101,Rod Ulysses Gaboardi,Km 3, BR-89520000 Curitibanos, SC, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ,3780, BR-18610034 Botucatu, SP, Brazil Univ Sao Paulo, Dept Forest Sci, Ave Padua Dias,11, BR-13418900 Sao Paulo, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ,3780, BR-18610034 Botucatu, SP, Brazil CNPq: 249979/2013-6

Dominant height growth equations, which given at some base age is defined as site index, is usually used to assess site quality. A flexible and accurate way to represent the potential productive capacity of forest stands of Eucalyptus spp. was developed. The generalized algebraic difference method was used, in which 15 dynamic equations were tested for modeling dominant height growth. The models were fitted to a data set derived from permanent plots located in the states of Bahia (BA) and Espirito Santo (ES), Brazil, with clonal eucalyptus plantations. The database was analyzed separately for the clear-cut and coppice regimes. The selection of the best-fitting model for each management regime was based on statistical fitting, predictive validation, and graphical analysis. After selection of the best model, one of its parameters were expanded with the addition of climatic variables that allowed for the creation of scenarios. The polymorphic modified Von Bertalanffy-Richards model with a single asymptote performed the best for the two management regimes. For clear-cut management, conditioning the slope parameter by the mean monthly precipitation obtained the best performance. For coppice management, the asymptote parameter conditioned by the mean monthly precipitation and its distribution throughout the year provided the best performance. The inclusion of the climate modifiers added flexibility for the models, which was represented by the interannual variations of precipitation. Expansions of the parameters did not mischaracterize the behavior of the modified Von Bertalanffy-Richards model for the management regimes studied. Climatic conditioning of the parameters of the slope and asymptote for the two management regimes led to accuracy gains in the estimates. Additionally, this enabled the generation of productivity scenarios based on the amount and distribution of the total precipitation for the areas under study.

The aim of this study was to map aboveground carbon stock of arboreal vegetation in the Savanna and Atlantic forest biomes in Minas Gerais State, Brazil, in order to assess the best spatial technique for mapping. The dataset was obtained from 148 forest fragments of these biomes. The best form of mapping was based on statistical criteria and mapping quality. The exponential semivariogram model was selected for conducting the study. The geographical model developed in this study for regression-kriging application was fitted having as input longitude and biome variables, and, globally, has presented good spatial behavior of the carbon stock distributed along the Minas Gerais State. From mapping carbon stock by different techniques, it was found that regression-kriging mapping was the most efficient. In addition, as the semivariograms were fitted for each biome using kriging and co-kriging, it is possible to stand out the flexibility for using regression-kriging, including biome as a categorical variable in the geographical model. Another result was the high correlation found between different forms of mapping, which adds reliability for this study. Thus, it was concluded that the carbon stock distribution in the arboreal vegetation of these two biomes is spatially structured. Ordinary kriging and co-kriging have presented satisfactory results, however, regression-kriging has been more reliable for mapping and estimating carbon stock distribution, in the Minas Gerais State.

This study analyzes the trade-off between net present value (NPV) of timber resources, and carbon sequestration and storage for a working forest, the Hofmann Forest in North Carolina, USA. Multi-objective optimization is used to determine the production possibility curves showing the relationship between NPV and carbon. We then perform a sensitivity analysis to explore alternative management strategies. For carbon yields we used aboveground pools: branches, leaves, tops and bole as estimated by the Forest Vegetation Simulator (FVS) and LOBDSS using the California Carbon Market Protocols, including product carbon. Timber yields of sawtimber, chip-n-saw and pulpwood were estimated by LOBDSS for planted stands less than 49 years of age, and FVS was used for all natural stands and planted stands 49 years and over. Our results reveal that NPV opportunity costs associated with increasing carbon sequestration at Hofmann Forest are less than the current California carbon market price.

This article returns to the Hossfeldt and Pressler volume formulas that were developed in the 19th century and uses them as predictor variables for total volume equations of species in North and South America. Both the Hossfeldt and Pressler formulas require an upper-stem measurement and are exact equations for the geometric shapes of a cone or paraboloid. Rarely is a direct measurement of the Hossfeldt diameter or Pressler height made on a stem, and a taper function is employed to indirectly obtain these values. A Kozak-type taper function is expanded to include routine auxiliary information of an inventory, such as age, dominant height, relative spacing, and a ranking variable that indicates position of the subject tree to a tree of average size. Using the Hossfeldt diameter and Pressler height, it is demonstrated how a merchantable volume ratio equation is indirectly derived. With the aid of one lower-stem measurement of diameter and height, such as the height at 5 m, vastly enhanced estimates of total stem volume are possible. These new volume equations imply that form factor is dependent upon the ratio of Pressler height to total tree height, and Hossfeldt diameter to diameter breast height (dbh). Therefore, the costly method of destructive tree sampling for making new volume equations can be obviated, since changes in form can be detected easily and less expensively by monitoring changes to the ratios of Pressler height to total tree height, and Hossfeldt diameter to dbh.

Tree biomass equations are important yet difficult, time-intensive, and expensive to develop. However, the calibration of previously developed, species-specific models could be a viable alternative, particularly for highly diverse and protected forests like the Atlantic Forest of Brazil. Consequently, the primary research goal of this study was to conduct a comprehensive evaluation of the potential to calibrate an existing individual tree aboveground biomass model for a new species and/or site by using linear mixed-effects. Specific research objectives were to determine the optimal approach for effective calibration by allowing sample selection method, sample size, and range of tree sizes sampled to vary. In particular, a certain set of species was used as a primary dataset to fit both generalized and species-specific biomass models, that were then calibrated for a secondary dataset at a different site and location. Both similar and divergent species at the secondary site were used to calibrate and evaluate the previous models. Our results suggested that species-level calibration was efficient for the majority of the species or individuals examined that can greatly improve the performance at much lower sample sizes required to develop a new equation, especially for the larger trees in the stand. In general, one to three randomly selected trees were sufficient to effectively calibrate a biomass model for a new species. We expect the combination of model calibration for abundant species associated with the use of the previous developed generalized model for less abundant species can drastically reduce the need for destructive sampling and improve predictions, which is important for highly threatened forests like the Atlantic Forest in Brazil. Overall, the results highlight the potential of model calibration to significantly improve both biomass and carbon estimates in species-rich forests like those in the tropics.

The wood production potential that a site presents is largely represented by its climatic condition and by the affinity of its genetic material. An issue which concerns all wood producers is climate change and how it will influence wood production and wood characteristics, as they can be decisive in industrial applications. Therefore, this study aimed to: (i) verify the wood volume (WV), stem biomass (SB) and the basic wood density (BWD) behavior against different climatic scenarios; and (ii) verify the potential of estimating the BWD through meteorological variables. The WV, BWD and SB of four different Eucalyptus spp. clones as to their climate of origin and species were analyzed. The cultivation was from 2012 to 2015 (four years) with planting in 11 locations in Brazil, representing a wide range of climatic characteristics with average precipitation from 649 mm y−1 to 1618 mm y−1. Precipitation, maximum vapor-pressure deficit, water deficit in the soil, temperature and precipitation seasonality were used to characterize the regions during the growth period. Hierarchical grouping was carried out for the sites, and the WV, BWD and SB behavior within the groups were analyzed. Thus, a linear regression equation between the most influential meteorological variables in the BWD were adjusted in order to identify the potential of the estimative BWD. Four groups were formed between the sites, and the variation in WV, BWD and SB for each clone between the wet and dry groups were respectively: C3: −68.3%, +8.7% and −65.0%; K2: −77.5%, +8.3% and −74.3%, A1: −40.3%, −9.21% and −39.9%; and Q8 – −31.6%, +8.4% and −34.1%. The drier locations generally showed lower WV and SB, and higher BWD associated to a decrease in the growth rate. This behavior is intrinsic to each clone and does not establish a defined proportion. Humid locations did not show clear patterns in changing density. The maximum vapor-pressure deficit and the water deficit in the soil were the most significant variables and had the best potential to estimate the basic wood density of the wood. Basic wood density is a resource which can be strongly influenced by genetics, and above all there is a significant influence of climate on the sites.

Stand structure can have a considerable influence on forest growth and productivity. A stand’s response to factors like temperature, precipitation, vapor pressure deficit and different soil characteristics may result not only from the mean change in tree responses (e.g. growth decrease or increase), but may also depend on how individual tree responses vary in relation to their size and how they cope with competition. There may be a large growth imbalance among trees as a function of their size, which is referred to as growth dominance. That is, a change in a factor may have different impacts on stand growth depending on stand structure and how growth is distributed. Thus, using an experimental platform spanning tropical Brazil, we explored the relationship between growth dominance and stand growth, and whether this relationship changes across a wide climatic gradient, represented by soil water deficit. We found a predominance of negative growth dominance during the early phase of stand development which increased until dominance became positive, after about 30 months, and kept increasing afterwards. Increasing soil water deficit slowed the increase in growth dominance throughout time. The intensification of growth dominance (either positive or negative) was associated with decreasing stand growth. Increasing soil water deficit decreased the negative effect of growth dominance on increment in absolute terms, but we showed that, at the end of a 5-year rotation, increasing growth dominance at a site with more intense water deficit led to a greater growth loss in relative terms than at a site with milder water deficit. For example, the estimated difference in increment between a stand with a low growth dominance of 0.05 and a stand with a high growth dominance of 0.20 at the end of a 60–month rotation at a site with an accumulated water deficit of −200 mm was about 28 m3 ha−1 year−1, which is equivalent to a 39% decrease in relative terms. This same GDC difference under a water stress of −4000 mm resulted in a decrease in increment of approximately 18 m3 ha−1 year−1, or 48% in relative terms.

Mid-rotation fertilization presents an opportunity to increase the economic return of plantation forests in the southeastern United States (SEUS). For this reason, the Forest Productivity Cooperative established a series of mid-rotation fertilization trials in Pinus taeda L. plantations across the SEUS between 1984 and 1987. These trials identified site-specific responses to nitrogen (N) and phosphorus (P) fertilizers, resulting in increased stand production for 6&ndash, 10 years after fertilization. There are successful volume response models that allow users to quantify the gain in stand productivity resulting from fertilization. However, all the current models depend on empirical relationships that are not bounded by biological response, meaning that greater fertilizer additions continue to create more volume gains, regardless of physiological limits. To address this shortcoming, we developed a bounded response model that evaluates relative volume response gain to fertilizer addition. Site index and relative spacing are included as model parameters to help provide realistic estimates. The model is useful for evaluating productivity gain in Pinus taeda stands that are fertilized with N and P in mid-rotation.

Made available in DSpace on 2020-12-10T19:58:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-06-15 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Anglo American Arauco Arborgen ArcelorMittal Cenibra CMPC Comigo Copener Duratex Eldorado Fazenda Campo Bom Fibria Florestal Itaquari Forestal Oriental Gerdau GMR International Paper Jari Klabin Lwarcel Montes del Plata Plantar Rigesa Suzano Vallourec Veracel University of Sao Paulo Sao Paulo State University Federal University of Lavras Federal University of Rio Grande do Norte Colorado State University North Carolina State University USDA Forest Service Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Growth models have been applied to assess the growth potential for areas without previous forest plantation records and to update forest inventory when commercial stands have been planted. However, there is a lack of growth models capable of incorporating environmental variables for updating forest inventories and recomputing site quality throughout Brazil. Consequently, this research aimed to deliver a compatible set of prediction and projection growth equations with parameters refined by environmental variables. The dataset used through this study is composed of remeasurement information of 16 research sites in Brazil. At each site, the same eleven eucalypt clones were planted in single block plots. Extra block plots were also installed in 14 sites to evaluate eucalyptus growth under drier climate scenarios. Four different competing model forms were tested. A common parameter of the best compatible set of growth equations was refined to test the magnitude of the environment effect on the prediction and projections of dominant height/site index in clonal eucalypt stands in Brazil. The compatible set of Chapman-Richards growth equations displayed the most accurate estimates of dominant height for clonal eucalypt plantations in Brazil. The common asymptote parameters between the growth models were refined as a function of annual soil water deficit (SWD), and a gain in accuracy of the projected and predicted dominant height estimates was observed. It is relevant to highlight that the developed set of growth equations possesses the ability to make short-, medium- and long-term predictions and projections with more assuredness about the biological behavior and its soundness. This feature ensures accurate estimation of site-specific growth curves. North Carolina State Univ, Dept Forestry & Environm Resources, 2820 Faucette Dr,Campus Box 8001, Raleigh, NC 27695 USA Univ Fed Lavras, LEMAF, Dept Forest Sci, Campus Univ,Campus Box 3037, BR-37200000 Lavras, MG, Brazil Virginia Polytech Inst & State Univ, Dept Forest Resources & Environm Conservat, 310 W Campus Dr,Campus Box 169, Blacksburg, VA 24061 USA Forestry Sci & Res Inst, Via Comendador Pedro Morganti 3500, BR-13415000 Piracicab, SP, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ 3780, BR-18610034 Botucatu, SP, Brazil Univ Sao Paulo, Dept Forest Sci, Ave Padua Dias 11, BR-13418900 Piracicaba, SP, Brazil State Univ Sao Paulo, Dept Forest Sci, Ave Univ 3780, BR-18610034 Botucatu, SP, Brazil CNPq: 249979/2013-6

The objectives of this study were to apply statistical techniques to discriminate fertilization treat- ments of Eremanthus erythropappus (DC.) MacLeish. through autoregressive modeling, and to develop individual tree models for diameter and crown area (CA) projection to define management strategies for candeia plantations sub- jected to different fertilization treatments. This is an important tree species originating from the Brazilian Atlantic Rain forest and Savannah biomes, intensively used in the cosmetic industry. Nonetheless, to date, research has not addressed the management of natural stands or plan- tations of the species. Our experiment was located in Baependi, Minas Gerais, Brazil, and comprised of four randomized blocks and 13 treatments. The treatments consisted of 12 different regimes of fertilization plus a control. Each sample plot was composed of 50 plants plus two border plants in a planting spacing of 2.5 9 2.0 m and undergoing pruning at 5 and 6 years of age. Starting in the second year, total tree height (H) and circumference (at 1.30 m from the ground or breast height, CBH) were measured every 6 months. Starting in the fifth year CA was measured. Tree growth varied by fertilization strategy. Differences were detected by using an autoregressive approach, considering that standard statistical methods were not powerful enough to detect significant differences. Three growth groups were formed, and maximum growth was obtained for treatment 10 (NPK, 8-28-16). Manage- ment guidelines are provided based on individual tree models for different fertilization levels.

The objective of this study was to determine the best method to estimate tree height by different hypsometric approaches. This study is a provenance trial with Eucalyptus spp. in a 35-year-old pioneering plantation in the municipality of Lavras, Brazil. The census was taken by measuring the diameter at 1.30 m above ground and total height. All x and y coordinates of the individual trees were obtained and these trees were classified according to their stem quality. The ordinary kriging, co-kriging and ordinary kriging of the residuals generated from the regression models were fitted by an exponential model. The Curtis model was selected for calculating the regression. The best method to estimate the height-diameter relationship was based on the statistical and graphical criteria. The spatial prediction model did not adequately represent the height–diameter relationship. The regression technique was more precise and accurate by inserting variables that helped capture different development standards of the trees. The regression-kriging produced more accurate total height estimates. Inclusion of the stochastic effect in the general spatial behavior of the total height variable helped to capture specific details about the stand. Therefore, this method is recommended for experimental areas. Key words: Kriging, regression, covariable.

The objective of this work was to analyze the spatial distribution and the behavior of species richness and diversity in a shrub savanna fragment, in 2003 and 2014, using ordinary kriging, in the state of Minas Gerais, Brazil. In both evaluation years, the measurements were performed in a fragment with 236.85 hectares, in which individual trees were measured and identified across 40 plots (1,000 m2). Species richness was determined by the total number of species in each plot, and diversity by the Shannon diversity index. For the variogram study, spatial models were fitted and selected. Then, ordinary kriging was applied and the spatial distribution of the assessed variables was described. A strong spatial dependence was observed between species richness and diversity by the Shannon diversity index (

The objective of this study was to map the spatial distribution of aboveground carbon stock (using Regression-kriging) of arboreal plants in the Atlantic Forest, Semi-arid woodland, and Savanna Biomes in Minas Gerais State, southeastern Brazil. The database used in this study was obtained from 163 forest fragments, totaling 4,146 plots of 1,000 m2 distributed in these Biomes. A geographical model for carbon stock estimation was parameterized as a function of Biome, latitude and altitude. This model was applied over the samples and the residuals generated were mapped based on geostatistical procedures, selecting the exponential semivariogram theoretical model for conducting ordinary Kriging. The aboveground carbon stock was found to have a greater concentration in the north of the State, where the largest contingent of native vegetation is located, mainly the Savanna Biome, with Wooded Savanna and Shrub Savanna phytophysiognomes. The largest weighted averages of carbon stock per hectare were found in the south-center region (48.6 Mg/ha) and in the southern part of the eastern region (48.4 Mg/ha) of Minas Gerais State, due to the greatest predominance of Atlantic Forest Biome forest fragments. The smallest weighted averages per hectare were found in the central (21.2 Mg/ha), northern (20.4 Mg/ha), and northwestern (20.7 Mg/ha) regions of Minas Gerais State, where Savanna Biome fragments are predominant, in the phytophysiognomes Wooded Savanna and Shrub Savanna.