Research articleCompetition indices after reduced impact logging in the Brazilian Amazon
Introduction
Forest competition consists of a direct relationship between the increased demand for the resources necessary for plant growth and the decrease in their availability (Weber et al., 2018). Water, light and nutrients are some of the natural resources that plants compete with each other for (Vatraz et al., 2018).
In recent decades, one of the greatest challenges for studies related to tropical rainforests has been to evaluate how competition for environmental resources affects tree growth and production. This competitive relationship among trees can be evaluated through competition indices (CIs) (Peltoniemi and Mäkipää, 2011; Pedersen et al., 2013). Therefore, the use of CIs has become an important part of forest management worldwide (Vatraz et al., 2018).
Various studies in the fields of ecology and forestry have been performed to develop or improve different indices to quantify competition at the individual tree level (Maleki et al., 2015). Based on such studies, some statistical models have already been developed to include competition as a variable to estimate mortality (Peltoniemi and Mäkipää, 2011; Das et al., 2011), recruitment (Duchesne and Prévost, 2013; Mugasha et al., 2016), and diameter, height and basal area growth (Contreras et al., 2011; Bérubé-Deschênes et al., 2017; Lhotka, 2017).
The CIs described in the literature can be grouped into three categories: distance-independent indices (DII), distance-dependent indices (DDI) (Burkhart and Tomé, 2012), and distance-semi-independent indices (DSII) (Stage and Ledermann, 2008; Contreras et al., 2011). The categories are distinguished according to the criteria used to express the relationships between trees (Castro et al., 2014).
In the distance-independent or non-spatially explicit indices, competition is estimated through the relationship between the object-tree dimensions and the stand variables, such as number of trees per hectare, basal area per hectare, and mean tree height (Kahriman et al., 2018; Burkhart and Tomé, 2012). In addition to including tree dimensions, DDI also incorporates the locations of neighboring or competing trees to the object-tree (Kahriman et al., 2018; Contreras et al., 2011). Therefore, such indices are more complex in terms of data collection (Sun et al., 2018). The variables included in distance-semi-independent indices are similar to those of distance-independent indices; however, they are spatially restricted to a smaller set of neighboring trees (competition radius) rather than all trees in the plot (Stage and Ledermann, 2008; Lederman, 2010).
The literature does not clearly indicate the universal superiority of one category of index over the others (Weiskittel et al., 2011) nor indicate the best index within each category (Fox et al., 2007).
Several studies have evaluated the performance of competition indexes to estimate changes in tree growth in monospecific forests or those with few species (Martins et al., 2011; Duchesne and Prévost, 2013; Amiri and Naghd, 2016; Bérubé-Deschênes et al., 2017). However, the number of studies on forests with high species richness is still very small (Castro et al., 2014; Vatraz et al., 2018; Lustosa Júnior et al., 2019).
There are also no studies which have evaluated or compared the three categories of competition indexes in the specific case of the Amazon Forest and particularly in areas subjected to some management intensity such as the forest management areas in the Amazon which have different growth dynamics than unmanaged natural areas (Reis et al., 2016). In addition, competition is an important quantitative variable in the growth and forest production models (Martins et al., 2011; Castro et al., 2014) which can increase the efficiency of these models in estimating growth and mortality at the individual tree level (Castro et al., 2014). Modeling, especially of individual trees, is one of the tools which can guide long-term planning, technically subsidizing the decisions regarding the best-suited cutting intensity and cutting cycle for the sustainability of the forest (Phillips et al., 2004).
In view of the above, this study aimed to estimate, evaluate and select the best CI for individual trees after reduced impact logging in a forest management area of the eastern Amazon.
Section snippets
Study area
The study was conducted in the forest management area (FMA) of the Rio Capim Farm (Fig. 1) belonging to the company CKBV Florestal Ltda., located in the municipality of Paragominas, in the state of Pará, Brazil (03°39′28.16"S and 48°49′59.73"W) (Maciel et al., 2009). Rio Capim Farm has a total area of 140,000 ha, from which 121,000 ha are under forest management certified by the Forest Stewardship Council (FSC) since 2001 (Dionisio et al., 2017).
The climate of the region is classified as “Awi”
Basal area growth and probability of mortality after RIL
The means of ΔG showed significant difference (t-test; p < 0.05), between the three classes of tree size, for the six periods analyzed. Large treesshowed the highest growth increments in every period (Fig. 2a). The largest means of ΔG occurred in period 1 (2005–2006), about one year after RIL: large = 0.0049 m2 year−1; medium = 0.0029 m2 year−1 and small = 0.0018 m2 year−1. In period 2 (2006–2008), the growth of the three size classes reduced: large = 0.0024 m2 year−1;
Competition versus ΔG and P (m) after RIL
In tropical rainforests, where light is one of the most limiting resources (Rüger et al., 2009), larger trees are submitted to less competition (Weiskittel et al., 2011) and tend to show higher growth rates (Reis et al., 2015) as they are located in upper strata, where there are better lighting conditions of their treetop (Vatraz et al., 2018). A similar finding was obtained by Dionisio et al. (2018) in the management area of the Rio Capim Farm, who observed higher growth rates for larger
Conclusions
Despite the advances obtained by Forest Science in recent years with the development of several competition indexes with varying levels of complexity, it is observed that the ability to express competition is strongly influenced by characteristics of the studied forest, with no guarantees that a greater number of variables or complex mathematical relationships will imply in a significant gain in precision to express the competition. In this study, the BAL index (distance-independent) which is
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
We would like to thank the Graduate program in Forest Sciences of the University of Brasília (UnB) and the Embrapa Eastern Amazon. This study was partly financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
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