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Published (Version of record)CC BY V4.0, Open Access
Published (Version of record)CC BY V4.0, Open
Journal article
Predicting the dynamics of a native Araucaria forest using a distance-independent individual tree-growth model
Forest ecosystems, Vol.3(1), pp.1-11
12/2016
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Abstract
In recent decades, native Araucaria forests in Brazil have become fragmented due to the conversion of forest to agricultural lands and commercial tree plantations. Consequently, the forest dynamics in this forest type have been poorly investigated, as most fragments are poorly structured in terms of tree size and diversity.We developed a distance-independent individual tree-growth model to simulate the forest dynamics in a native Araucaria forest located predominantly in southern Brazil. The data were derived from 25 contiguous plots (1 ha) established in a protected area left undisturbed for the past 70 years. The plots were measured at 3-year intervals from their establishment in 2002. All trees above a 10-cm diameter at breast height were tagged, identified as to species, and measured. Because this forest type comprises hundreds of tree species, we clustered them into six ecological groups: understory, subcanopy, upper canopy shade-tolerant, upper canopy light-demanding, pioneer, and emergent. The diameter increment, survival, and recruitment sub-models were fitted for each species group, and parameters were implemented in a simulation software to project the forest dynamics. The growth model was validated using independent data collected from another research area of the same forest type. To simulate the forest dynamics, we projected the species group and stand basal areas for 50 years under three different stand-density conditions: low, average, and high.Emergent species tended to grow in basal area, irrespective of the forest density conditions. Conversely, shade-tolerant species tended to decline over the years. Under low-density conditions, the model showed a growth tendency for the stand basal area, while under average-density conditions, forest growth tended to stabilize within 30 years. Under high-density conditions, the model indicated a decline in the stand basal area from the onset of the simulation, suggesting that under these conditions, the forest has already reached its maximum-stock capacity.The model validation using independent data indicated close agreement between the observed and estimated values, suggesting the model is consistent in projecting species-group and stand growth. The methodology used in this study for developing the growth model should be tested in other species-rich forests.
Details
- Title
- Predicting the dynamics of a native Araucaria forest using a distance-independent individual tree-growth model
- Creators
- Enrique Orellana - Midwest State University-UNICENTRO-PR PR 153, Km 7, Riozinho Irati Paraná 84500-000 BrazilAfonso Figueiredo Filho - Federal University of Paraná UFPR. Av. Pref. Lothário Meissner, 900, Jardim Botânico Curitiba Paraná 80210-170 BrazilSylvio Péllico Netto - Federal University of Paraná UFPR. Av. Pref. Lothário Meissner, 900, Jardim Botânico Curitiba Paraná 80210-170 BrazilJerome Vanclay - Southern Cross University (SCU) PO Box 157 Lismore NSW Australia
- Publication Details
- Forest ecosystems, Vol.3(1), pp.1-11
- Publisher
- Beijing Forestry University; Beijing
- Grant note
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (http://dx.doi.org/10.13039/501100003593)
- Identifiers
- 991012927062902368
- Copyright
- This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Academic Unit
- Office of Deputy Vice Chancellor, Research; School of Environment, Science and Engineering; Science; Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article