Does debarking intensity during the first cork extraction affect future cork thickness?
The use of increasing debarking during the first harvest of cork oak trees (Quercus suberL.) had no effect on the secondary cork calliper (thickness) in one of the trials and had a small negative effect in a second trial. Little evidence was found that debarking coefficient is a useful index for the management of cork oak stands.
The Portuguese national legislation defines, without the support of scientific data or knowledge, maximum values of debarking coefficients (ratio of debarking height and perimeter at breast height measured over cork). For the first debarking, this value is limited to 2.0.
The aim of this study was to determine the impact of increasing cork debarking coefficient on the calliper of the secondary cork extraction.
Trees were located in two sites, in distinct regions characterized by low or high productivity classes. Three debarking coefficients were considered: 1.5, 2.0 and 2.5. The debarking coefficient for the first cork extraction was randomly selected for each tree. During the second debarking, a cork sample was taken from each tree. The samples were used for assessing secondary cork calliper. Differences in cork calliper were analysed using both correlation analysis and modelling approaches.
Debarking intensity increase had a small negative effect on secondary cork thickness in the most inland site, while no effect was detected in the more coastal site.
In our experiment, debarking intensity had a significant but small effect in one site and no effect in other sites. Debarking coefficients not only should be defined according to legal constraints but also instead should be adapted considering tree and site characteristics.
KeywordsQuercus suber L. Montado Debarking coefficient Debarking height Secondary cork Cork thickness Cork calliper
Cork oak forests, also designated as montados, are one of the most extended high natural and cultural value ecosystems in the Mediterranean region (den Herder et al. 2017; Plieninger et al. 2015). These systems have been managed for centuries to engender the compatibility of cork production with agriculture and/or extensive grazing, but cork is frequently one of the most important sources of revenue for the landowners. Therefore, tree debarking is one of the most important management operations, not only because it results in the collection of the cork but also because the way the operation is carried out may affect the tree and cork growth in the following growth period (Costa et al. 2004; Costa et al. 2015; Natividade 1950; Pereira 2007).
The immediate physiological response of the tree to the debarking operation has been researched at tree level by Correia et al. (1992), Hakam et al. (2012) and Werner and Correia (1996) and at stand level by Silva et al. (2015). Apart from for Hakam et al. (2012), no author found any relation between the tree response and the debarking intensity evaluated by debarking coefficient and by total debarked surface. Regarding a medium (annual) to long-term (period between two cork extractions) tree response, Costa et al. (2015), Fialho et al. (2001), Leal et al. (2008) and Oliveira et al. (2002) researched the effect of the debarking on radial growth and tree phenology, but none of the authors investigated the tree response to different debarking intensities.
One of the main concerns of landowners, managers and researchers regarding the management of the cork oak tree is the impact of the debarking intensity at a debarking event at tree age t, on tree and cork growth during the next cork growth period that will terminate in the debarking event at tree age (t + 9) (e.g. Oliveira and Costa 2012; Paulo et al. 2016). Debarking intensity may be measured by debarking height or number of debarked branches variables or computed as debarking coefficient or debarking surface values. The Portuguese national legislation defines maximum values for the debarking coefficients, defined as the ratio between debarking height measured along the tree stem and the debarked branches and the perimeter at breast height measured over cork. It restricts to a maximum of 2.0 for the first debarking, 2.5 for the second and 3.0 for the third and following debarking operations. The established values were suggested by Natividade (1950) based on expert judgement. These limits are clearly defined as upper limits, with the objective of protecting trees from overexploitation, but questions related to the most appropriate value for particular stands or trees remain open (Paulo et al. 2016). It is expected that several variables may be related to the tree response to the debarking, for example, stand growing conditions (site productivity), management operations (e.g. understory composition and management operations for its control) or tree characteristics (e.g. sanitary conditions, cork thickness). Natividade (1950) suggested a reduction of the proposed 3.0 debarking coefficient to 2.5 for trees with more than three debarked branches, highlighting the importance of tree structure and tree debarking surface on the definition of the debarking intensity. More recent research, based on representative data sets, is scarce in the literature. The need for long-term experiments and data collection in controlled trials largely explains the current state of the art regarding this subject. Paulo et al. (2016) and Pizzurro et al. (2010) indirectly discuss the effect of the debarking intensity on cork thickness, the first suggesting that other variables such as annual precipitation and site characteristics are more influential for cork thickness, and the second supporting the conclusions of Natividade (1950) that increasing debarking heights will result in a decrease in cork calliper. Both authors base their research on data collected from adult trees, of unknown age, and with an ‘unknown management history’, particularly in what concerns the debarking intensities that were applied in previous debarking operations. These characteristics of the data sets do not exclude a possible influence of the past debarking operations on the results.
The objective of the present research is to evaluate the effect of the debarking intensity, at the first cork extraction, on cork thickness extracted during the second debarking operation. This was carried out by the analysis of the cork thickness values, measured at tree level, in two distinct trials characterized by distinct soil and climate conditions. The trees in both sites had not been debarked prior to the treatments application, and for this reason, no co-effect of previous debarking disturbs the results.
2 Materials and methods
The research was developed on two distinct sites. The first site is located in a privately owned property called Machuqueira do Grou, located in the Ribatejo province, in the Coruche county (WGS84 coordinates: 39.132 N, − 8.343 W). The second site is located at the Perímetro Florestal of Contenda, currently a municipal property under the joint management of the Municipality of Moura and the National Forest Authority. It is located in the Baixo Alentejo province, near the city of Barrancos in Moura county (WGS84 coordinates: 38.058 N, − 7.040 W). The two sites are, from now on, referred to as MG (Machuqueira do Grou) and PFC (Perímetro Florestal of Contenda).
The stand of the MG site is characterized by an uneven-aged structure, including a considerable percentage of young undebarked trees. It is managed as a traditional silvopastoral system: reduced number of animals per hectare (sheep) feeding on natural pasture and reduced implementation of mechanical understory control methods (one or two per cork growth rotation period made with mounted knifes or chains). The average number of trees per hectare is 145, with a basal area under cork of 7.6 m2 ha−1 and a crown cover percentage of 45%. The stand includes older and adult trees, mixed with young non-debarked trees. The trees considered for the trial had similar diameter and were therefore considered to have approximately uniform age. The productivity of the site, assessed by the site index model from Paulo et al. (2015), was estimated at 16 m for the total height of the dominant trees at a base age of 80 years, corresponding to a high productivity class (Paulo et al. 2015).
The stand of the PFC site is characterized by an even-aged structure stand, installed between 1958 and 1964, and managed primarily for game production (Pinheiro 1997). Forest management in PFC was limited to understory control operations with mounted knifes or chains, carried out with a reduced frequency and in order to reduce fire risk. The average number of trees per hectare was 143, with a basal area under cork of 3.1 m2 ha−1 and a crown cover percentage of 24.2%. The productivity of the site, assessed by the site index model from Paulo et al. (2015), was estimated at 13 m, corresponding to a low productivity class.
Soil and climate characterization of the two sites were the trials were installed
Predominant soil typea
Soil depth (cm)b
79 to 173 m
235 to 583 m
0 to 5%
15 to 30%
Annual minimum temperaturec
Mean annual temperaturec
Annual maximum temperaturec
Years of debarking
The selected trees were completely enclosed by virgin cork (undebarked trees) at the year of the trial installation. Due to legal constraints imposed by national legislation, only trees presenting a minimum value of 70 cm of perimeter at breast height over virgin cork were considered. All debarking operations took place in June. In the MG site, a total of 90 trees were randomly selected. These trees were debarked for the first time in 1995. The second debarking took place in 2005, on 72 trees. The remaining 18 trees were not found and presumed dead. In the PFC site, a total of 144 trees were selected among 8 existing permanent plots in the stand. These trees were debarked for the first time in 2003. The second debarking took place in 2012, on 134 trees. The ten remaining trees were dead and randomly distributed across four plots.
On both sites and during each measurement, the following tree measurements were carried out: diameter at breast height before (di where i = 1,2 for representing the first and second cork debarking operations, respectively) and after debarking (dui where i = 1,2 for representing the first and second cork debarking operations respectively) and total height (hi where i = 1,2 for representing total height at the time of the first and second cork debarking operations). Virgin cork thickness (ctv) was computed as (d1 − du1)/2. In the year of the first debarking stem height (hs), vertical debarking height (hdv), debarked length in the branches (lb) and perimeter at the middle section of the debarked branches (pb) were also measured. The two last measurements were only carried out when the debarking height was higher than the stem height. These measurements allowed the computation of two additional variables that characterize debarking intensity: total debarking height (hdtot) and total debarked surface (sd). hdtot is defined as the sum of the debarking length on the stem and on the branches. Total debarked surface is computed as the sum of the surface area of cylinders associated to the stem (characterized by hs and du) and the branches (characterized by lb and pb).
Summary statistics of tree variables at the establishment of the trials
MG (n = 90)
PFC (n = 144)
The analysis of the effect of the debarking intensity was carried out at two levels: individual tree and stand level. Distinct statistical approaches were considered for each level.
Graphical and correlation analysis of the relationship between the response variable secondary cork thickness (ct) and the following independent variables: diameter before and after debarking (d1, du1, du2), virgin cork thickness (ctv), vertical debarking height (hdv), total debarking height (hdtot), debarked surface (sd) and debarking coefficient (dcoef). Graphical analysis was made by means of scatter and box plots observation. Correlation analysis was carried out by the computation of the Pearson r and Spearman ρ correlation coefficients, for assessing linear and monotonic relationships respectively (McDonald 2014). This analysis was carried out with the PROC CORR procedure of the SAS 9.4 software.
Linear modelling of the secondary cork thickness (ct) value as a function of tree variables (d1, du1, du2, ctv) and variables related to debarking height and intensity (hdv, hdtot, sd and dcoef). Due to the categorical feature of the debarking coefficient variable (dcoef), dummy variables associated to each category were created as suggested by Myers (1990): dcoef1.5 (assumes a value of 1 for trees debarked for a 1.5 dcoef and 0 for other trees) and dcoef2.5 (assumes a value of 1 for trees debarked for a 2.5 dcoef and 0 for other trees). Trees debarked for a 2.0 dcoef present values of dcoef1.5 and dcoef2.5 equal to zero. While for the MG site a fixed effect model was suitable due to the non-existence of any grouping structure of the tree data, for the PFC site, a mixed model approach was considered due to the nested structure of the data that presents trees inside plots (Pinheiro and Bates 2000). The modelling procedure was carried out with the PROC MODEL and PROC MIXED procedures of the SAS 9.4 software.
All variables were tested separately for significance (α = 0.05) and biological meaning of the associated parameter. Models including more than one single variable were then tested considering the inclusion of the variables selected in the previous step. The final models were characterized and discussed in terms of mean square error (the smaller the better) and adjusted r2 (the larger the better) for the case of linear fixed effect models and AIC (the smaller the better) for the case of linear mixed models. If the plot random effect (uj) was not significant in the final model defined for the PFC site, it was removed and the model was refitted as a linear fixed effect model.
Comparison of the median cork thickness value by the median test (McDonald 2014)
Comparison of the cork thickness empirical distributions values by the Kruskal-Wallis test (McDonald 2014), for each site and for each debarking coefficient value (1.5, 2.0 and 2.5). When the Kruskal-Wallis test rejected the null hypothesis of equal empirical distributions, these were again compared using the Kolmogorov-Smirnov tests for a two-sample comparison, therefore resulting in three tests: dcoef1.5 versus dcoef2.0, dcoef1.5 versus dcoef2.5 and dcoef2.0 versus dcoef2.5. This analysis was carried out with the PROC NPAR1WAY procedure of the SAS 9.4 software, by the inclusion of the EDF, median and Wilcoxon options.
Pearson (r) and Spearman (ρ) correlation coefficients between secondary cork thickness (ct) and explanatory variables (d1, du1, du2, ctv, hdv, hdtot and sd)
− 0.0414 (0.7357)
− 0.0185 (0.8804)
− 0.0642 (0.6005)
− 0.0746 0.5422
− 0.0115 (0.9252)
− 0.0841 (0.3377)
− 0.0385 (0.6615)
− 0.0439 (0.6174)
− 0.0267 (0.7617)
Parameter estimates in the models for cork thickness estimation
Pr > |t|
Pr > |t|
Pr > |t|
cti = α0 + α1 ctvi
cti = α0 + α1d1,i
cti = α0 + α1 ctvi
cti = α0 + α1d1,i + α2 dcoef(1.5)i
cti = α0 + α1 ctvi + α2 dcoef(1.5)i
For the models developed for the PFC site, variables d1, du1, du2 and ctv were significant (α = 0.05) and associated with positive values. Variables hdv, hdtot and sd were not significant in the model (not shown). Dummy variables dcoef1.5 and dcoef2.5 confirmed the differences in ct average values already suggested by the box plots of Fig. 2. The variance estimates associated with the plot random effect (uj) in the mixed model were not significant, allowing the rejection of the hypothesis that different plot conditions had significant effect on the secondary cork thickness (ct). For the following modelling process, the fixed effect model approach was considered for the PFC site. The models presenting the lower mean square error and higher adjusted r2 values were the ones including variables d1 or ctv (Table 4). When combining d1 or ctv variables with the dummy variables dcoef1.5 and dcoef2.5, two final models were obtained (Table 4). These models did not include the dcoef2.5 dummy variable, indicating that no significant differences exist between trees debarked with dcoef of 2.0 and 2.5. Parameter estimates indicated that larger trees or trees with higher virgin cork thickness were associated with larger ct values and that the application of a dcoef equal to 1.5 would result in a 2.125-mm increase of the ct value.
Chi-square statistics of the median and Kruskal-Wallis tests, performed for the comparison of median value and empirical distribution comparison of ct from the three debarking coefficient: 1.5, 2.0 and 2.5
Chi-square statistics of two samples Kolmogorov-Smirnov test for the PFC site (average low productivity)
H0: f1.5(ct) = f2.0(ct)
H0: f1.5(ct) = f2.5(ct)
H0: f2.0(ct) = f2.5(ct)
For the PFC site, the cork thickness empirical distribution from trees debarked with a lower debarking coefficient (dcoef = 1.5) was significantly different from the ones debarked with a debarking coefficient of 2.0 or 2.5. The average value of cork thickness decreased from 19.9 mm (median 19.0 mm) to 16.9 mm (median 17.1) going from dcoef of 1.5 to 2.5. Instead, no significant differences were found between the empirical distributions resulting from trees debarked with debarking coefficient of 2.0 and 2.5 (Table 6).
The relationship between mature cork thickness and tree diameter after debarking has been researched by Pizzurro et al. (2010) and Sánchez-González et al. (2007) considering cork thickness before boiling and by Paulo et al. (2016) considering cork thickness after boiling. Despite this difference of the cork response variable, results suggest a positive (Paulo et al. 2016 and Sánchez-González et al. 2007) or null relationship (Pizzurro et al. 2010) between the two variables. Our results agree in suggesting a small and positive relationship between these variables, but only at the site located in an inland region, characterized by Leptosols and drier climate. Since none of the available and published data sets addressed the relationship of cork thickness and tree diameter for different site conditions (Paulo et al. 2015), open questions remain to be addressed regarding the different patterns of relationship of between these variables.
An additional and relevant characteristic of the data sets, used by Paulo et al. (2016), Pizzurro et al. (2010) and Sánchez-González et al. (2007), is the lack of information about the management of the sampled trees or stands (number of previous debarkings, previous debarking intensities, etc.), since this could help to understand the differences in the results when researching the relationship between cork thickness and debarking intensity. Pizzurro et al. (2010) reported a negative effect of the debarking intensity (assessed by total debarking height, debarking coefficient and debarking surface) while Paulo et al. (2016) concluded on a null relationship (assessed by vertical and total debarking heights and debarking coefficient). Our results suggest that the effect of distinct debarking intensity may be different according to the soil and climate conditions of the site, with limiting sites being associated with a significant and negative effect of increasing debarking intensities on secondary cork thickness.
Considering the impact of debarking coefficients in the revenue resulting from the debarking operation, one may observe that, for average values, the differences encountered in the two sites varied from 0 to 2 mm. The largest differences were encountered in the PFC site, with Podzols and dry climate conditions, between the trees debarked with a debarking coefficient of 1.5 and others debarked with 2.0 or 2.5 coefficients. Looking at current cork price structures, it may be expected that these differences, although significant from a statistical point of view, will not have a large impact in the price of the resulting cork (Paulo and Tomé 2017).
Present results are restricted to the impact of the debarking intensity from the first cork extraction on secondary cork thickness, and no extrapolation should be made for cork extracted in following debarking operations and/or in adult trees. Research on the effect of long-term under- or over-exploitation of cork requires the maintenance of the trials presented in this manuscript, the replication of the trials, and the inclusion of additional independent variables in the analysis, such as microsite soil chemical and physical properties (Corona et al. 2005). Meanwhile, the present results are key for the management of new cork oak plantations in Portugal and for other species able to be considered for bark extraction (Leite and Pereira 2017) such as the Quercus variabilis, a species relatively abundant across temperate and subtropical areas in East Asia and presently under increase interest (e.g. Du et al. 2015; Zhou et al. 2010). Portuguese plantations began to be established at the end of the 1980s with the support of the common agricultural policy measures, and now they represent an important area in the country and a potential plus for national cork production (Coelho et al. 2012) and carbon sequestration (Palma et al. 2014). Average trees from these plantations have now achieved, or are close to achieving, the minimum perimeter value of 70 cm defined in national legislation that allows the first debarking to be carried out. National legislation also defines the maximum value of 2.0 for the debarking coefficient to apply during this operation. The established values, suggested by Natividade (1950) based on expert judgement and with a clear objective of protecting trees from overexploitation, should be considered as maximum values for good to average growth conditions that are associated with high and average Portuguese productivity classes proposed by Paulo et al. (2015). Meanwhile, in sites characterized by lower productivity classes, values under 2.0 are also considered, as they may contribute to an increase in the average cork thickness produced by the tree in the growth period immediately following.
Our results suggest that the impact of the increasing debarking intensity from the first debarking on cork thickness is small albeit different between sites. The debarking coefficient was significantly related to secondary cork thickness in the site characterized by Podzols, drier conditions and associated to average to a low productivity class but was not significant in the site characterized by Podzols and associated to a high productivity class. It is suggested that during the first debarking operation, the debarking coefficient values should be defined considering tree and site characteristics. The follow-up monitoring and sampling of the trials are needed in order to clarify the long-term tree response to increasing debarking intensities in consecutive cork debarking operations.
The authors acknowledge Cristina Gonçalves, Sónia Pacheco Faias, Susana Barreiro, Sofia Leal and Sofia Knapic for their collaboration during measurements and sample collection.
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