Robust volumetric models for supporting the management of secondary forest stands in the Southern Brazilian Atlantic Forest

Oliveira, Laio Zimermann; Klitzke, Aline Renata; Fantini, Alfredo Celso; Uller, Heitor Felippe; Correia, Jean; Vibrans, Alexander Christian

doi:10.1590/0001-3765201820180111

Cited by 9 publications

(16 citation statements)

References 22 publications

(14 reference statements)

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“…2) were fitted in their linear form by logarithmic transformation to predict stem and total volumes. These models were fitted for generic and specific datasets, corresponding to the three main forest types (SSF, DOF, and RES) and four timber species with management potential in the Atlantic Forest, according to Nascimento et al (2017) and Oliveira et al (2018): Apuleia leiocarpa (Vogel) J. F. Macbr., Astronium graveolens Jacq., Miconia cinnamomifolia (DC.)…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, total volume models that consider crown volume are rare for Atlantic Forests (Oliveira et al 2018), in which this study is also a pioneer. These models can provide estimates of forest growth in the National Forest Inventory (Gschwantner et al 2019) to support the management of secondary forests (Oliveira et al 2018, Fantini et al 2019. Environmental heterogeneity may explain the variation in allometric relationships between forest types (Fig.…”

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

“…On the other hand, the high variability of tropical tree crown pat-terns can affect the fit of total volume models (Mauya et al 2014). In general, the stem volume is more homogeneous than total volume, and its allometric attributes are more easily described by tree diameter and height (Oliveira et al 2018).…”

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

“…In this study, tree crown represented, on average, 30.1% of the total volume, varying according to forest type (DOF = 30.7%; RES = 34.2%; SSF = 28.0%). Crown volume in subtropical regions of the Atlantic Forest can represent up to 34.5% of total tree volume (Oliveira et al 2018). However, most allometric models developed in tropical forests only estimate the stem volume and do not consider the volume of thick branches (Segura & Kanninen 2005).…”

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

“…However, most allometric models developed in tropical forests only estimate the stem volume and do not consider the volume of thick branches (Segura & Kanninen 2005). Crown volume is an important component of timber stocks in natural forests, so it should not be ignored in management systems (Oliveira et al 2018) or in forest biomass and carbon predictions (Nogueira et al 2008).…”

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

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Tree volume modeling for forest types in the Atlantic Forest: generic and specific models

Cysneiros¹,

Gaui²,

Filho³

et al. 2020

iForest

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National Forest Inventories are important primary data sources for large-scale forest resource surveys, in which volume estimates of sampled trees are essential for quantitative analysis. Volume prediction models in natural forests are scarce in Brazil due to legal restrictions for cutting trees, especially in the Atlantic Forest. This study aimed to fit volume models for the main forest types and timber species of the Atlantic Forest in Rio de Janeiro state, considering two hypotheses: (I) generic volume models provide greater generalizability of estimates; however, (II) they may reduce the accuracy of forest typeand species-specific predictions. Four linear models with logarithmic transformation of variables were evaluated to fit volume models for generic and specific datasets, which correspond to the main forest types and timber species. Goodness-of-fit statistics were calculated to compare the accuracy and efficiency of the models, and selected models were validated through leave-oneout cross-validation procedures. The estimates obtained by generic and specific models were compared by non-parametric hypothesis tests. Generic models showed similar predictions to the specific models for forest types and timber species, with similar potential for stem and total volume predictions. Therefore, generic models can be used for Atlantic Forests in Rio de Janeiro state, while specific models are recommended to obtain more detailed local estimates.

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Section: Discussionmentioning

confidence: 99%

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

See 3 more Smart Citations

Tree volume modeling for forest types in the Atlantic Forest: generic and specific models

Cysneiros¹,

Gaui²,

Filho³

et al. 2020

iForest

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Multi-year, post-harvesting impact assessment in a neotropical secondary Atlantic Forest

et al. 2022

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Subject to overexploitation in the past centuries, the Atlantic Forest is subject to very rigorous protection rules. However, the law is a controversial issue since landowners are not compensated for the limited choice of land use possibilities. We believe that, alternatively to a general timber harvest ban, sustainable forest management of the Atlantic Forest has the potential to generate income for the landowners while sustaining important ecological functions of the forest. Such choice would require better understanding of the potential effects of timber harvesting on the forest ecosystem and on species composition and succession over time. In this context, we assessed the harvesting impact of a conventional harvesting method (CM) and compared it to an alternative harvesting method (AM) in three different stands (stands A, B and C) of a secondary forest fragment in southern Brazil. Results from three comprehensive forest inventories over a period of two years were used to assess the timber harvesting impact. Measurements of species composition (i.e., number of species, life form, ecological group), forest structure (i.e., density, basal area, DBH, volume) and saplings density formed the basis of the impact assessment. The inventories were carried out before, immediately after and two years after harvesting. Intensities of damage on remnant trees immediately after harvesting and two years after harvesting were also measured. Before harvesting, a total of 114 tree species (trees, tree fern and palm tree) belonging to 49 families were identified in the study site’s three research stands. Palm trees and secondary species, such as Euterpe edulis, represented the majority of recruited individuals (DBH ≥ 5 cm) two years after harvesting. However, new saplings (DBH ≤ 5 cm) after two years were mainly pioneer woody tree species, such as Cecropia glaziovii and Schizolobium parahyba. On average, AM reduced damage to saplings by 5%. Most of the damages caused by CM were moderate to severe, while AM caused light to moderate damages. Binary logistic regression indicated dependency of the mortality rates on the independent variables “stand, stem and leaning damages.” On the other hand, the recovery rates of damaged trees were dependent on crown, stem and leaning damages. Therefore, two years after harvesting a higher mortality rate of low-dimensional trees was observed in stands with high density of smaller trees and high density of improvement felling. Although crown damages were not related to mortality rates, high intensity of crown damages reduced recovery rates over time.

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Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

et al. 2020

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The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R 2 adj ), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.

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Robust volumetric models for supporting the management of secondary forest stands in the Southern Brazilian Atlantic Forest

Cited by 9 publications

References 22 publications

Tree volume modeling for forest types in the Atlantic Forest: generic and specific models

Tree volume modeling for forest types in the Atlantic Forest: generic and specific models

Multi-year, post-harvesting impact assessment in a neotropical secondary Atlantic Forest

Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

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