Partitioning of net primary production in Eucalyptus and Acacia stands and in mixed-species plantations: Two case-studies in contrasting tropical environments

Epron, Daniel; Nouvellon, Yann; Mareschal, Louis; Moreira, Rildo Moreira e; Koutika, Lydie‐Stella; Geneste, Blandine; Delgado-Rojas, Juan Sinforiano; Laclau, Jean‐Paul; Sola, Gaël; Gonçalves, José Leonardo de Moraes; Bouillet, Jean‐Pierre

doi:10.1016/j.foreco.2012.10.034

Cited by 103 publications

(102 citation statements)

References 60 publications

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“…[ 31,32] Stand density S -Increases in stand density can increase, decrease, or have no effect on complementarity. The direction is likely to depend on the resources that are influenced by the species interactions and how the change in density influences those resources.…”

Section: Possibly Crmentioning

confidence: 99%

“…For example, a mass balance approach was used to determine whether greater above-ground productivity of mixtures was associated with greater total productivity or a shift in biomass partitioning between below-ground and above-ground biomass pools, or both. In some cases, the increase in above-ground production resulted only from a shift in partitioning, while in other cases, it was also associated with increased total productivity [31,32].…”

Section: Processes Influencing Diversity-productivity Relationshipsmentioning

confidence: 99%

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A Review of Processes Behind Diversity—Productivity Relationships in Forests

2016

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Through complementarity interactions, mixedspecies forests can be more productive than monocultures, and this effect can increase with tree-species richness. However, this is not always the case. This review examines the processes and stand structural attributes that can influence diversity-productivity relationships (DPRs); how they influence resource availability, resource uptake, and resource-use efficiency; and also describes some important differences between tree-diversity versus grassland-diversity experiments. The size of the complementarity effects caused by these processes and stand structures varies along spatial and temporal gradients in resource availability and climate. These spatial and temporal dynamics have now been examined in many studies, and the general patterns are summarized using a simple framework; complementarity is predicted to increase as the availability of resource BX^declines (or climatic condition X becomes harsher) if the species interactions improve the availability, uptake, or use efficiency of resource X (or interactions improve climatic condition X). Importantly, this framework differs from the stress-gradient hypothesis to account for a wider range of inter-specific plant interactions (not only facilitation) by considering contrasting methods used to quantify species interactions while accounting for stand structure. In addition, complementarity (as opposed to facilitation) for a given species combination can increase as growing conditions improve in forests, contrary to predictions of the stressgradient hypothesis with regards to facilitation. This review indicates that while the effects of tree-species diversity on growth and other forest functions are now receiving a lot of attention, far less is known about the effects of structural diversity on growth or forest functioning. Direct measurements of the processes, as opposed to focusing mainly on growth responses, could greatly contribute to our understanding of structural diversity effects.

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Section: Possibly Crmentioning

confidence: 99%

Section: Processes Influencing Diversity-productivity Relationshipsmentioning

confidence: 99%

A Review of Processes Behind Diversity—Productivity Relationships in Forests

2016

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“…Eucalyptus is the most planted tree in the tropics (Epron et al, 2013), in addition of being the main genus *Corresponding author. miguelederpereira@gmail.com.…”

Section: Introductionmentioning

confidence: 99%

Artificial neural networks in whole-stand level modeling of Eucalyptus plants

Lima¹,

Lustosa²,

Oliveira³

et al. 2017

Afr. J. Agric. Res.

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Forestry production is traditionally predicted using mathematical modelling, where whole-stand models are prominent for providing estimates of growth and production per unit area. However, there is a need to perform research that adopts innovative tools, such as artificial Intelligence techniques. The objective of this study was to train and evaluate the efficiency of Artificial Neural Networks (ANN) in the modeling process of growth and production of Whole-Stand Level, in "equineanean" forests of the Eucalyptus genus clones. For the training of the networks, the supervised method was adopted. There were 100 networks trained, of which, for each output variable, 5 networks were selected. The criteria used to verify the quality of the training and validation of the networks were: Student's test "T", graphical analysis of the dispersion of residues, standard error of the relative estimate (Syx%), Pearson's correlation coefficient (r) between the observed and estimated values, and aggregate difference (AD). The ANN selected in the training process, which estimated the volume variables, site index and future production, when validated did not differ statistically by the Test "T" and presented adequate statistical accuracy values to the modeling process, with satisfactory correlation values (r) between the observed and estimated values, low values of standard error of the relative estimate (Syx%) and aggregate difference (AD). Artificial neural networks of the multilayer perceptron type are precise and efficient in the entire modeling process for whole-stand level of Eucalyptus plantations, therefore its use is recommended.

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“…Due to this great contribution, the forest industry has dedicated time and funds in the pursuit of solutions to meet one of the biggest challenges of the 21 st century: the growing demand for wood, energy and fibers, without neglecting the maintenance of natural resources and social inclusion (Ibá, 2016). Eucalyptus is the main genus cultivated in the tropics (Epron et al, 2013), due to its fast growth, productivity, great adaptability, diversity of species, and wide use possibility. Two countries have the largest planted areas of Eucalyptus genus: India with nearly 22% and Brazil with nearly 21% (Miguel et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Morphometric indexes and dendrometric measures for classification of forest sites of Eucalyptus urophylla stands

Carrijo¹,

Miguel²,

Rezende³

et al. 2017

Aust J Crop Sci

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The main goal of this study was to verify the applicability of morphometric indexes and dendrometric measures to assess production capacity and volumetric prognosis of forest sites under E. urophylla stands/plantation. During forest measurement inventory, 21 randomized permanent sample plots were monitored from the third to the sixth year of cultivation, registering individuals with standard minimum features, collecting the variables diameter at breast height (DBH), crown diameter (CD), total height (TH), and crown height (CH). A volume estimation equation was adjusted using the software Statistica 7, which were used for estimation the wood volume of each sample in each year of cultivation. Furthermore, other three stand variables were collected: arithmetic mean diameter (MD), quadratic mean diameter (QMD), and dominant height (DH); along with three morphometric indexes: slenderness degree (SD), salience index (SI), and crown formal (CF). Amongst five sigmoidal models adjusted for site classification three of them were considered best choice for different variables: Richards (MD, QMD, and CF); Gompertz (DH); Weibull (SD and SI). All variables presented satisfying adjustment precision for the Clutter prognosis model. Despite a small advantage found in some indexes on statistical tests, there was no significant difference between the six variables on an Analysis of Variance (ANOVA) for volume prediction, which brought us the conclusion that all variables are efficient for site quality classification.

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Partitioning of net primary production in Eucalyptus and Acacia stands and in mixed-species plantations: Two case-studies in contrasting tropical environments

Cited by 103 publications

References 60 publications

A Review of Processes Behind Diversity—Productivity Relationships in Forests

A Review of Processes Behind Diversity—Productivity Relationships in Forests

Artificial neural networks in whole-stand level modeling of Eucalyptus plants

Morphometric indexes and dendrometric measures for classification of forest sites of Eucalyptus urophylla stands

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