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## Agrociencia

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*On-line version* ISSN 2521-9766*Print version* ISSN 1405-3195

### Agrociencia vol.51 n.5 México Jul./Aug. 2017

Natural Renewable Resources

*Eucalyptus urophylla* merchantable volume estimation with total volume and ratio models

^{1}Postgrado en Ciencias Forestales, Colegio de Postgraduados. 56230. Carretera México-Texcoco, km. 36.5. Montecillo, Texcoco, Estado de México.

^{2}Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP). 74060. Campo experimental San Martinito, Tlahuapan, Puebla, México. (tamarit.juan@inifap.gob.mx).

^{3}Woods Hole Research Center. Gilman Ordway Campus. 149 Woods Hole Road. Falmouth, MA 02540. apeduzzi@whrc.org

The functional relationships between diameter at breast height (*dn*) and height (*A*) with the total volume (*Vt*) of a tree is essential for the technical management and exploitation of commercial forest plantations (PFC), along with the rate of different commercial heights (*Ai*) or minimum diameters (*di*) along the bole with the merchantable volume (*Vc*). Based on the hypothesis that with such mathematically-expressed relationships it is possible to accurately estimate *Vt* and *Vc*, the objective was to propose a tool to quantify the *Vt* and *Vc* in *Eucalyptus urophylla* PFCs from seed and clones in southeastern Mexico, by means of volume-ratio functions (*r*). Six *Vt* models -fitted and corrected for heteroscedasticity taking variance into consideration- and ten ratio models -correcting autocorrelation with an autoregressive structure- were evaluated using dasometric information from 175 clone trees measured in 2007 (P1), 93 in 2014 (P2), and 459 in 2007 (P3); the third group was grown from seeds. The Schumacher-Hall model -which includes dichotomous variables- showed that populations are statistically different. The best *Vt* models were: Schumacher-Hall for P1 and P3, and Spurr for P2. The best *r* models -which consider the diameter at different heights- were: Burkhart for P1 and P2, and Cao for P3. When bole height models are used, Zepeda’s was the most appropriate for the three populations. With these *Vt* and *r* models, each population’s *Vc* was determined at any given *di* or *Ai*, which accounted for more than 94 % of the variability. The slenderness ratio was 114, 122, and 118 cm cm^{-1} and the form factor was 0.45, 0.34, and 0.34 for P1, P2 and P3, respectively.

**Key words: **stem profile; taper; forest plantations; product distribution; Eucalyptus urophylla

Introduction

Commercial forest plantations (PFC) are an option to achieve the reduction of the pressure over natural forests in Mexico (^{CONAFOR-COLPOS, 2012}). In the last decade, PFC establishment has increased significantly (^{CONAFOR, 2014}) and it has supplied timber to the industry (^{Rodríguez-Juárez et al., 2014}). The *Eucalyptus* genus is one of the most frequently used sources of germplasm in PFC (^{Juárez-Palacios et al., 2013}, ^{CONAFOR, 2014}) and it’s ranked in second place among the species established in Mexico between 2000 and 2014, with a surface of 32 452 ha (18.31 %) (^{CONAFOR, 2015}).

*Eucalyptus urophylla* is the most frequently used species in tropical climates (^{CONAFOR, 2012}) and it is planted worldwide due to its rapid growth (^{Rosa et al., 2011}), its wide altitudinal range (0 to 1200 m), and its minimum edaphic establishment requirements (^{Nieto and Rodríguez, 2003}). In addition, it can adapt to places with mean annual precipitation between 2000 and 3000 mm and mean annual temperature between 24 and 28 °C (^{Vieira and Bucsan, 1980}).

The timber volume of the plantations is an indicator of the stand productive potential (^{Moret et al., 1998}) and it
can be divided in total volume (*Vt*) and merchantable volume
(*Vc*) (^{Chauchard and
Sbrancia, 2005}). According to ^{Prodan
et al. (1997)}, there are three
*Vc* estimation methodologies for individual trees: 1) to
implement *Vt* functions with the restriction of a limit diameter
or height, in which the portion of the remaining tree is omitted in the
prediction (^{Gilabert and Paci, 2010}), for
example the free bole volume equations (*Vtfl*); 2) to adjust
functions that describe the tree profile and, afterwards, to estimate the
*Vc* at a defined diameter or a given height (^{Chauchard and Sbrancia, 2005}), based on a
taper function; 3) to implement the proportional ratio between a predetermined
volume and the *Vt* for different tree types (^{Pece, 1994}), using volume-ratio functions
(*frv*).

The *frv* concept was introduced by ^{Honner
(1967)}, and developed by ^{Burkhart
(1977)}, ^{Alder (1980)}, ^{Cao et al. (1980)}, ^{Van Deusen et al. (1981)},
and ^{Parresol et al.
(1987)} provided some complementary variants. Their efficiency was
discussed by ^{Prodan et al.
(1997)} who pointed out that using this type of function enables the
accurate calculation of the volume at any dimension of diameter or height
defined in a simpler way, than fitting or using a taper model. In addition,
^{Gilabert and Paci (2010)} compared the
results of this type of systems in two species, in Chile, with those of a taper
function and pointed out the precision of the results and the simplicity to
obtain them.

These percentage functions are a system of equations made up of a *Vt* equation and a volume ratio equation (*r*), which operate together in order to estimate the volume by product type per tree (*Vc*) (^{Chauchard and Sbrancia, 2005}; ^{Gilabert and Paci, 2010}); *r* matches the volume ratio up to a utilization percentage or a non-merchantable diameter (*Vi*) and the *Vt* of the bole (*Vi*/*Vt*) (^{Trincado et al., 1997}; ^{Barrio et al., 2007}; ^{Barrios et al., 2014}).

The models that include a *frv* are conceptually and mathematically simple, generate consistent results, can be used to estimate *Vc* in different diameter and height ranges without implementing complex numerical integration methods, and can be coupled with any type of *Vt* function (^{Chauchard and Sbrancia, 2005}). In addition, based on independent variables, using a ratio function (*r*), the minimum diameter (*di*) or merchantable height (*Ai*) can be estimated by product type (^{Chauchard and Sbrancia, 2005}).

The increasing demand for high-quality timber products and the changing standards of the sawmill industry have replaced the concept of total timber volume (*Vt*), as an indicator of PFC performance, with the concepts of product volume (*Vp*) or merchantable volume (*Vc*), which are important for the planning, management, and estimation of this type of forest masses. Therefore, based on the hypothesis that it is possible to carry out precise estimates of *Vt* and *Vc*, by means of the mathematical representation of the functional relations between the variables of a tree, the objective of this study was to propose a tool made up of a total volume model and a volume ratio model, in order to quantify total and merchantable volumes in commercial plantations in southeastern Mexico; these plantations use seed and two clonal sources of *E. urophylla*.

Materials and Methods

Study Area

The *E. urophylla* PFCs evaluated are located in the municipality of Huimanguillo, Tabasco, Mexico. The climate is hot and humid (Am): the mean annual temperature is 26 °C and the mean annual precipitation is 2500 mm. The soils belong to the Phaeozem group and the terrain is made up of low hills (^{INEGI, 2005}).

Description of the sample and estimation of the total volume

The sample was taken from 727 *E. urophylla* trees, out of which: 175 belonged to clones measured in 2007 (P1), 93 to clones measured in 2014 (P2), and 459 to trees grown from seeds measured in 2007 (P3). The clones’ age (P1 and P2) fluctuated from one to seven years, while trees grown from seeds (P3) ranged from two to eleven years.

The sample trees were chosen according to: their morphological condition (to cover the
greatest possible phenotypic variability within the plantations); the
variability between their *dn* and *A*
dimensions; and their age distribution. In each tree, the diameter at breast
height (*dn*) and total height (*A*) were
measured, and then they were felled and cut at different sections
(*di* and *Ai*) along the bole, in order
to measure their diameter and height; measures were taken 1 m distance from
each other, starting with the diameter and height of the tree stump
(*dt* and *ht*, respectively). The Newton
and the cone formulas were used to find out the volume of each log
(*V*_{troza}) and each tip
(*V*_{punta}), respectively. The
total volume (*Vt*) was calculated using ^{Bailey’s overlapping bolts method
(1995)}.

Interpopulation comparison of trees

In order to determine differences between clones’ populations (P1 and P2) with regard to trees grown from seeds (P3), the following hypotheses were tested on the *dn* and *A* variables. The analysis was performed contrasting P1 *vs.* P2, P1 *vs*. P3, and P2 *vs*. P3.

Null hypothesis (Ho): populations are the same.

Alternative hypothesis (Ha): populations are different.

In order to verify if trees of the three populations have differences in *Vt* -and on the assumption that two trees can have the same volume without necessarily presenting the same *dn* and *A* dimensions-, the *Vt* of the two types of clones and plantations grown from seed was fitted. In addition, to quantify the effect of each type of tree (either clone or grown from seeds), an indicator variable was inserted into the Schumacher-Hall (^{Draper and Smith, 1966}) volume model (Table 1). Analyzes were carried out with SAS 9.2. (^{Institute Inc. Statistical Analysis System, 2008}).

The indicator variables (*W*_{n}) were programmed in the Schumacher-Hall volume model (1), according to the contrast performed for each population.

The model is expressed as follows:

where *a*_{0}, *a*_{1}, and *a*_{2} are the regression parameters, whereas *a*_{ 0c} and *a*_{1c} are the addition parameters for the different populations.

Estimation of slenderness ratio and form factor

The slenderness ratio (*IE*) was calculated to verify the trees’ degree of
mechanical stability against winds or hurricanes, dividing the
*A* average by the *dn* average, as
reported by ^{Arias (2004} and ^{2005)} and ^{Nájera and Hernández (2008)}. In order to verify if
these are statistically different from each other, a one-factor ANOVA was
carried out for the average *IE* between the populations at a
p=0.05 level.

The form factor (*ff*) was calculated with the slope (*p*) of the bole volume and the combined variable (*dn*^{2} *A*), and, then, the factor was calculated with regard to a theoretical cylinder, using the following formula:

The adjusted total volume models are those of ^{Da Cunhaa y
Guimaraes (2009)}, ^{Corral-Rivas
and Návar-Cháidez (2009)}, ^{Tschieder et al. (2011)}, and ^{Casnati et al. (2014)}.
Meanwhile, the standard type or double-entry types (^{Prodan et al., 1997)} only differ in
the form and number of parameters to be estimated (Table 1).

The best model was selected on the basis of the highest value of the determination coefficient, adjusted by the number of parameters (*R ^{2}_{aj}*) and the lower values in the sum of squares error (

*SCE*) and the root mean square error (

*RCME*), as well as the best graphic distribution of residuals. With a model that complied with the above-described conditions, and, in order to avoid increasing the variance as the diameter increases (heteroscedasticity), weighted regression was used (

^{Cailliez, 1980};

^{Tschieder et al., 2011}), with the following weight variables: 1/

*dn*, 1/

*dn*

^{2}, 1/

*dnA*y 1/

*d*

^{2}

*A*. The bole volume estimates for the three populations were made with the corrected models.

Volumetric ratio models

The volumetric ratio (*r*) was calculated as the volume (at different heights and diameters) and the total volume (*Vi*/*Vt*) quotient. With this purpose, volume ratio models using *dn*, *di*, *A*, and *Ai* as independent variables were successfully utilized in other studies (^{Pece, 1994}; ^{Chauchard and Sbrancia, 2005}; ^{Barrio et al., 2007}; ^{Gilabert and Paci, 2010}; ^{Barrios et al., 2014}) (Table 2).

*R*_{d} is the volume ratio that uses the following as independent variables: the diameter at breast height (*dn*) and the diameter at different heights (*di*); *R*_{h}, which includes in the model the total height (*A*) and height at different sections along the bole (*Ai*); *b*_{0}, *b*_{1}, *b*_{2}, *b*_{3}, *b*_{5}, and *b* _{6} are the parameters to be estimated.

To fit these models, 1958, 2113 and 6060 pairs of *di*-*Ai*
data were used for the P1, P2 and P3 populations, respectively. As a first
step, the volume ratio models were adjusted without including the error term
with the purpose of verifying the residuals trends and the value of the
Durbin-Watson (*DW*) autocorrelation statistic, as ^{Barrios et al. (2014)}
indicate.

In order to fit this type of models, the volume is calculated at different heights and diameters to obtain a volumetric ratio. Therefore, the longitudinal structure of the information used is inevitable; its measures are different along the bole and they have a close correlation, because they belong to the same tree. As a result of this, a continuous-time autoregressive (CAR) model was used to correct the error structure (^{Zimmerman and Nuñez-Antón, 2001}), and the model is expressed as follows:

Where *Y*_{ij} is the vector of the dependent
variable. *X*_{ij} is the matrix of
independent variables. *B* is the vector of the parameters to
be estimated. *e*_{ij} is the
*j*-th residual of *i* tree.
*I*_{k} =1 for
*j*>*k* and *I*_{
k} =0 for *j*≤*k*.
ρ_{k} is the autoregressive parameter of
the *k* order to be estimated.
*h*_{ij} -*h*_{
ij-k} is the distance that separates the
*j*-th measurement height from the
*j*-th-*k* measurement height in each tree
(*h*_{ij} >*h*
_{
ij-k}). ε_{ij} is the
random error (^{Barrios et
al., 2014}). The number of lags applied in the CAR(X)
model was established at the moment that the *DW* statistic
was evaluated, which should have been close to 2 as mentioned by ^{Verbeek (2004)}.

Model adjustment and evaluation criteria

The statistical fit of *Vt* and *r* models was carried out using the MODEL procedure in SAS 9.2 and the full information maximum likelihood (FIML) technique (^{Institute Inc. Statistical Analysis System, 2008}).

The evaluation and selection of the best model was performed with the highest value of *R ^{2}_{aj}* and the lowest values in the SCE and RCME, along with the tests of independence (

*DW*) and normality of the frequency of the residuals (

^{Da Cunha and Guimaraes, 2009}). The homogeneity of variance was subject to a graphical evaluation (

^{Tschieder et al., 2011}), while the predictive capacity of the best models was evaluated estimating the absolute bias (Ē) and the aggregate deviation (

*DA*%) for each population.

**Determination of merchantable volume ( Vc)**

In order to estimate the merchantable volume at any point along the bole, a scale system consisting of the best *Vt* and *r* model was formed for each of the populations. With the tree’s *Vt* and applying the volumetric ratio model, the merchantable volume is the result of multiplying the two equations results (^{Chauchard and Sbrancia, 2005}). The evaluation of the estimation accuracy was carried out with a linear trend chart of predicted against observed values (^{Pece, 1994}).

Results and Discussion

**Interpopulation comparison of Vt, dn and A in trees**

The fitting of the Schumacher-Hall model was acceptable (Table 3) and the values of the parameters in the *W*_{ n} indicator variable were significant (p≤0.05), which confirms that the three populations have different *dn* and *A* averages, as well as different *Vt* averages, and that their growth rates are different. This difference between the 2007 and 2014 clones is the result of the reproduction selection of the latter, because it was made on the basis of their larger *dn* or *A* dimensions, without taking into account the *Vt* or the form factor.

Estimation of slenderness index, form factor, and total volume

Once it was identified that the three populations should be analyzed separately, *IE* was calculated. The mean values by population were 114, 122, and 118 cm cm^{-1}, for P1, P2 and P3, respectively. The lower average *IE* value suggests that the clones measured in 2007 were selected for their growth in diameter, rather than for their growth in height, because it is more practical and simple to take only the diameter at breast height as a production indicator. In the ANOVA test, the minimum significant *IE* difference was 4.77; in addition, the means of the slenderness ratio between the populations were statistically different (P1=122.571, P2=112.168, and P3=93.804), because the error probability value was low (Pr>F=<0.0001).

These indexes are similar to those for fast-growing tropical species such as *E.
Nitens* (*IE*=124) (^{Díaz et al., 2012}), *Hieronyma
alchorneoides* (*IE*=111), and *Terminalia
amazonia* (*IE*=106) (^{Arias, 2005}). However, because *IE* is
higher than the 1:1 growth ratio between *dn* and
*A*, the trees are assumed to be thin and strong thinning
intensities must be applied with care (^{Arias,
2005}; ^{Díaz et al., 2012}),
due to the PFC’s susceptibility to the mechanical damages caused by winds
(^{Wilson and Oliver, 2000}).

With regard to *ff*, the shape of trees in the P2 and P3 populations was the same (conical type with a value of 0.34), while it was different in the P1 population (*ff*=0.45), which indicates that the shape of trees is more similar to a paraboloid.

As a result of the fit statistics of the best *Vt* models -determined by the higher *R ^{2}_{aj}* values, the lower SCE and RCME values and the significance of the parameter value (p<t)-, the Schumacher-Hall model was best fitted to P1 and P3 data, and the Spurr model for P2 (Table 4).

*SCE*: sum of squared errors; *RCME*: Root mean square error; *R ^{2}_{aj}*: Adjusted coefficient of determination;

*Eea*: Approximate standard error;

*b*: Parameters to be estimated.

_{n}In the three fittings, all the resulting parameters were significant (95 % confidence), and the Shapiro-Wilk normality test showed values higher than *W*=0.92 and a level of Pr<*W*=0.0001, whereas the residual plots showed a tendency towards a straight line in the form of a Gaussian bell curve, which indicates that the data are normal. However, in the variance homogeneity test, very marked trends were observed; therefore, heteroscedasticity problems were assumed, and the weighted variable with best corrective results was 1/*dn ^{2}A*, with which a homogenous distribution of residuals was obtained (Figure 1). The estimation of the parameters and the goodness of fit indicators of the bole volume equations for the P1, P2, and P3 populations are shown in Table 5.

*SCE*: sum of squared errors; *RCME*: Root mean square
error; *R ^{2}_{aj}*: Adjusted
coefficient of determination;

*Eea*: Approximate standard error;

*b*: Parameters to be estimated.

_{n}In the estimates made with the corrected models, as well as their projections, the average
*IE* was considered when calculating the height of each
population. As it is observed, the selection of the vegetative material to
produce the clones measured in 2014 was carried out taking the samples of
highest *dn* and *A*, without considering the
*Vt*, because the line that corresponds to this
population is the lowest of the three and makes reference to the more
slender trees (conical form) and have less volume than the 2007 clones and
the trees grown from seeds (Figure
2).

Taking as reference the 2007 clone plantations -which have more *Vt* than the rest-, it was observed that, up to the 0.30 diameter range -which on average is the maximum in the three populations-, the 2014 plantations have 3.60 % less *Vt* than those grown in 2007, and 1.47 % less than trees grown from seeds (Figure 2). Projections outside the sample up to 45 cm diameter indicate that the differences increase to 11.35 % and 4.72 % in the P2 and P3 populations, respectively, with regard to P1’s projected *Vt*.

Volumetric ratio models

When the first fitting was made, the values of the parameters and the statistics obtained
were relevant, but the residuals showed a trend towards heteroscedasticity,
and the value of *DW* for P1 varied from 0.59 to 1.03, for P2
from 0.13 to 0.82, and for P3 from 0.44 to 1.09, which shows that the data
are correlated. Therefore -after a graphical analysis of the autocorrelation
function (ACF) was carried out in the three populations-, a auto-regressive
structure of first, second, and third order was used to correct the
autocorrelation of the errors (CAR (*X*)) and the one that
had best results was selected (Table
5).

After the autocorrelation was corrected for the *R _{d}* model (11) of
P2, we decided that this was the best one, based on

^{Fuentes et al. proposal (2001a}and

^{2001b)}about the absence of correlation for values in this statistic that are higher and equal to 1 and the greater precision that this model generated with regard to the rest. The

*DW*values demonstrate an autoregressive type CAR(1) serial correlation, due to the existence of logs with bole diameters at a given height, related to a similar or equal diameter to a different

*Ac*(

^{Pérez, 1996};

^{1998}), and that -when another delay was applied to the errors and the

*DW*value was improved- we observed that quality was lost in the fit, because no significant parameters were evident (i.e.,

*R*lower or biased estimations with regard to the observed data).

^{2}_{aj}In the three populations analyzed, one *R*_{d} -type
and one *R*_{h} -type volume ratio
models were selected in order to use either of these two variants to
estimate *Vc*. This selection was based on the highest
*R ^{2}_{aj}* values, and the lowest

*SCE*and

*RCME*values, as reported by

^{Trincado et al. (1997)}and

^{Barrio et al. (2007)}. The fit of best models had satisfactory results and all the parameter values were different than zero (p≤0.05) (Table 6).

*SCE*: Sum of squared errors; *RCME*: Root mean square
error; *R ^{2}_{aj}*: Adjusted
coefficient of determination;

*Eea*: Approximate standard error;

*b*: Parameters to be estimated;

_{n}*p*1

*r*,

*p*2

*r*and

*p*3

*r*indicate the order and number of delays applied in the CAR (

*X*) type model applied.

When the residuals’ distribution was verified (Figure
3) for the *R*_{d} models in
the P1 and P3 populations, the results matched those mentioned by ^{Barrios et al. (2014)}
for *E. grandis*, which has an homoscedastic distribution (a
and c). However, there is a slight presence of heteroscedasticity in P2; but
it does not affect the estimations made with this model, because when the
volume ratio was calculated with better distribution models, the absolute
error was lower in the selected model (b). In no case, the
*R*_{
h} models show a trend (d, e, and f), which
matches what ^{Pece (1994)} described
when he used this type of model for *E. pellita*.

When the absolute bias (Ē) and the aggregate deviation (*DA* %) for each population were estimated -and with the purpose of verifying the precision of the estimations with the *R*_{d} y *R*_{h} models- we observed that their values were low for the three populations, and in no situation did *DA* without exceed 1.29 % (Table 7).

Estimation of the merchantable volume of trees

The fitted models allow us to find the volumetric accumulation ratio, as the total height is reached, starting from the tree stump height, as well as the relation between the total volume and the volume of a limited diameter or height. The expressions used to obtain the *Vc* of individual trees in each population consist of a *Vt* and *r* model; when multiplied, they will result in the *Vc* of any diameter or height of defined exploitation. The resulting equations are the following:

*Vc* equations for the P1 population.

*Vc* equations for the P2 population.

*Vc* equations for the P3 population.

When the *Vc* predictions obtained with the volume ratio method are subject
to a graphic comparison with the accumulated volume, the result is close to
a straight line (Figure 4); and, when a
linear regression is applied to these data the use of the *R*_{
d} -type models shows -by the value of
*R*^{2}- that the sample estimation is higher
than 94 %, while the use of *R*_{h}
-type models has 96 % results. When the accuracy and absolute bias are
verified, taking as reference the *R*
^{2} value and the difference in its approximation to the unit, the
difference for the *R*_{d} models is
3.0, 5.4 and 5.5 % in the P1, P2 and P3 populations, respectively; while it
is 1.1, 3.1, and 2.6 % in *R*_{h}
models (Figure 4). The trend observed
and the values of the fittings between the predicted and the observed values
match those indicated in the studies carried out by ^{Pece (1994)} in *Eucalyptus pellita*, by
^{Chauchard and Sbrancia, (2005)} in
*P. radiata*, and by ^{Barrios et al. (2014)} in *E.
grandis*.

In order to estimate a merchantable diameter at a given commercial height for P1 and P2
populations, we solve for di from equation (11) and *R*_{
d} is replaced by
*R*_{h} (equation 30),
according to the procedure set forth by ^{Trincado et al. (1997)}, using the parameters
estimated for each model and replacing them in the resulting equation. If
the inverse calculation was necessary (*i.e*., to estimate
*Ac* for a specific diameter in the three populations),
*Ai* would be solved from equation (21), and
*R*_{h} would be replaced by
*R*_{d} (equation 31).

For P3, in model 15 of *R*_{d}, *di* at any height is calculated by a numerical approximation with the Excel tool SOLVER, because when this variable is solved from the equation, the roots can be mathematically reduced until they disappear.

The models selected show consistency in the total and merchantable volume determination, their values do not crossover, and they enable a direct estimation of the bole diameter at an established height, or the bole height at a limit diameter. As a whole, these models are highly trustworthy and allow to carry out estimations of product distribution, to create tables of merchantable volumes for any useful diameter or height established by the sawmill industry or to calculate the economic valuation of plantations. Stock and operational harvest data are required to validate the models generated.

Conclusions

The functional relations between the tree’s *dn* and *A* variables are reliable in the estimation of total and merchantable volume. In addition, the adjustment of their mathematical expressions suggests that -if the owners or investors intend to maximize the volume to be obtained in *Eucalyptus urophylla* clone plantations- the selection of trees for clonal reproduction purposes should consider an analysis of the tree’s total volume (rather than the diameter at breast height and total height). Likewise, we observed statistically significant changes in the populations in a relatively short period (7 years); the reliability of the models used to estimate the potential timber harvest and the value of the forestry investment also underwent changes. Therefore, in this type of fast-growing plantations, these models must be updated at the same rate that the vegetative material used and the applied cultural practices are replaced

Literatura Citada

Alder, D., 1980. Estimación del volumen forestal y predicción del rendimiento con referencia especial a los trópicos. Vol. 22/2. Predicción del Rendimiento. Ed. FAO, Montes, 189 p. [ Links ]

Arias, D. 2004. Estudio de las relaciones altura-diámetro para seis especies maderables utilizadas en programas de reforestación en la zona sur de Costa Rica. Rev. For. Kurú 1: 1-11. [ Links ]

Arias, D . 2005. Morfometría del árbol en plantaciones forestales tropicales. Rev. For. Kurú 2: 2-11. [ Links ]

Barrio, M., H. Sixto, I. Cañellas, y F. González. 2007. Sistema de cubicación con clasificación de productos para plantaciones de *Populus*×*euramericana* (Dode) Guinier cv. ‘I-214’ en la meseta norte y centro de España. Inv. Agraria: Sistemas Recursos For. 16: 65-75.
[ Links ]

Barrios, A., A. M. López, y V. Nieto. 2014. Predicción de volúmenes comerciales de *Eucalyptus grandis* a través de modelos de volumen total y de razón. Colombia For. 17: 137-149.
[ Links ]

Bailey, R. L. 1995. Upper-stem volumes from stem-analysis data: An overlapping bolt method. Can. J. For. Res. 25: 170-173. [ Links ]

Burkhart, H. E. 1977. Cubic-foot volume of loblolly pine to any merchantable top limit. Southern J. App. For. 1: 7-9. [ Links ]

Cailliez, F. 1980. Estimación del volumen forestal y predicción del rendimiento con referencia especial a los trópicos: estimación del volumen. Vol. 22/1. Estudio FAO: Montes, Roma, Italia. 92 p. [ Links ]

Cao, Q., H. Burkhart, and T. Max. 1980. Evaluation of two methods for cubic volume prediction of loblolly pine to any merchantable limit. For. Sci. 26: 71-80. [ Links ]

Casnati, C., G. Mason E., R. Woollons, and F. Resquin. 2014. Volume and taper equations for *P. tadea* (L.) and *E. grandis* (Hill ex. Maiden). Agrociencia 18: 47-60.
[ Links ]

Chauchard, L., y R. Sbrancia. 2005. Funciones de razón para la estimación de los volúmenes maderables de *Pino radiata* en el País Vasco. Inv. Agraria: Sistemas Recursos For . 14: 185-194.
[ Links ]

CONAFOR (Comisión Nacional Forestal). 2012. Logros y perspectivas del desarrollo forestal en México 2007-2012. http://www.conafor.gob.mx/biblioteca/documentos/LOGROS_Y_PERSPECTIVAS_DEL_DESARROLLO_FORESTAL_EN_MEXICO.PDF (Consulta: diciembre, 2015). [ Links ]

CONAFOR (Comisión Nacional Forestal). 2014. México cuenta con 270 mil hectáreas de Plantaciones Forestales Comerciales. Boletín 77. http://www.conafor.gob.mx:8080/documentos/docs/7/5752M%C3%A9xico%20cuenta%20con%20270%20mil%20hect%C3%A1reas%20de%20%20Plantaciones%20Forestales%20Comerciales.pdf . (Consulta: diciembre 2015). [ Links ]

CONAFOR (Comisión Nacional Forestal). 2015. Principales especies maderables establecidas en PFC por año (2000 - 2014) y Principales especies maderables establecidas en PFC por Entidad Federativa (2000 - 2014). http://www.conafor.gob.mx/web/temas-forestales/plantaciones-forestales / (Consulta: diciembre 2015). [ Links ]

CONAFOR-COLPOS (Comisión Nacional Forestal-Colegio de Posgraduados). 2012. Situación Actual y Perspectivas de las Plantaciones Forestales Comerciales en México. http://www.conafor.gob.mx/web/temas-forestales/plantaciones-forestales/ (Consulta: enero 2017). [ Links ]

Corral-Rivas, S., y J. de J. Návar-Cháidez. 2009. Comparación de técnicas de estimación de volumen fustal total para cinco especies de pino de Durango, México. Rev. Chapingo Serie Ciencias For. Ambiente 15: 5-13. [ Links ]

Da Cunha, T., y C. A. Guimaraes F. 2009. Modelo de regresión para estimar el volumen total con corteza de árboles de *Pinus tadea* L. en el sur de Brasil. Rev. For. Kurú : 2-15.
[ Links ]

Díaz B., S. M. Espinosa. L. Valenzuela, J. Cancino, y J. P. Lasserre. 2012. Efecto del raleo en el crecimiento y algunas propiedades de la madera de *Eucalyptus nitens* en una plantación de 15 años. Madera, Ciencia Tecnol. 14: 373-388.
[ Links ]

Draper, N., R., and H. Smith. 1966. Applied Regression Analysis. John Wiley & Sons, New York. USA. 407 p. [ Links ]

Fuentes E., D., J. J. Troncoso, y C. A. Bonilla. 2001a. Operaciones forestales y concentración de sedimentos en cauces naturales I: Formulación de un modelo matemático. Bosque 22: 15-24. [ Links ]

Fuentes E., D., J. J. Troncoso, y C. A. Bonilla. 2001b. Operaciones forestales y concentración de sedimentos en cauces naturales II: Análisis de sensibilidad y comparación con otros modelos. Bosque 22: 25-27. [ Links ]

Gilabert, H., and C. Paci. 2010. An assessment of volume-ratio functions for *Eucalyptus globulus* and *E. nitens* in Chile. Ciencia Inv. Agraria 37: 5-15.
[ Links ]

Honner, T. G. 1967. Standard volume tables and merchantable conversion factors for the commercial tree species of central and eastern Canada. Information Report FMR-X-5. Forest Management Research and Service Institute. 162 p. [ Links ]

INEGI (Instituto Nacional de Estadística y Geografía). 2005. Marco Geoestadístico Municipal 2005, v. 3.1. http://www3.inegi.org.mx/contenidos/app/mexicocifras/datos_geograficos/27/27008.pdf (Consulta: diciembre 2015). [ Links ]

Institute Inc. Statistical Analysis System. 2008. SAS/STAT 9.2 User’s Guide Second Edition. SAS Institute Inc. Raleigh, NC USA. (Consulta: diciembre, 2015). [ Links ]

Juárez-Palacios, J. C., J. A. Honorato-Salazar, L. Vázquez-Silva, y J. F. C. Parraguirre-Lezama. 2013. Patogenicidad de *Crysoporthe cubensis* en clones de *Eucalyptus grandis* y *E. urophylla* en el sureste de México. Madera y Bosques 19: 17-36.
[ Links ]

Matney, T. G., and D. Sullivan A. 1982. Variable top volume and height predictors for slash pine trees. For. Sci . 22: 283-289 [ Links ]

Moret, A. Y., M. Jerez, y A. Mora. 1998. Determinación de ecuaciones de volumen para plantaciones de teca (*Tectona grandis* L.) en la unidad experimental de la reserva forestal Caparo, estado de Barinas-Venezuela. Rev. For. Venez. 42: 41-50
[ Links ]

Nájera, L., J. A., y E. Hernández H. 2008. Relaciones morfométricas de un boque coetáneo de la región del Salto, Durango. Ra-Ximhai 4: 69.81. [ Links ]

Nieto, V. M., y J. Rodríguez. 2003. *Eucalyptus urophylla* Dehnh. *In*: Vozzo, J.A. Manual de Semillas JA Árbol Tropical. Parte II. Especies descripciones. Washington, DC: USDA Forest Service. 473 p.
[ Links ]

Parresol, B. R., J. E. Hotvedt, and Q. V. Cao. 1987. A volume and taper prediction system for bald cypress. Can. J. Forest Res. 17: 250-259. [ Links ]

Pece, R., M. 1994. Tabla de volumen comercial para *Eucalyptus pellita* utilizando el método de la razón volumétrica. Quebracho 2: 54-63.
[ Links ]

Pérez, C. 1996. Econometría y Análisis Estadístico Multivariable con Statgraphics. Técnicas Avanzadas. Ed. Rama. Madrid, España, 745 p. [ Links ]

Pérez, C. 1998. Métodos Estadísticos con Statgraphics para Windows. Técnicas Básicas. Ed. Rama. Madrid, España, 705 p. [ Links ]

Prodan, M., R. Peters, F. Cox, y P. Real. 1997. Mensura Forestal. Serie Investigación y Educación de Desarrollo Sostenible. Instituto Interamericano de Cooperación para la Agricultura (IICA)/BMZ/GTZ. San José, Costa Rica. 561 p. [ Links ]

Trincado, G., K.Von Gadow, y V. Sandoval. 1997. Estimación de volumen comercial en latifoliadas. Bosque 18: 39-44. [ Links ]

Tschieder E. F., E. Fassola H., y M. García C. 2011. Ecuaciones de volumen total para *Populus deltoides* de plantaciones del Bajo Delta del Paraná. Rev. Inv. Agropec. 37: 172-179.
[ Links ]

Rodríguez-Juárez M., I., A. Velázquez-Martínez, A. Gómez-Guerrero, A. Aldrete, y M. Domínguez-Domínguez. 2014. Fertilización con boro en plantaciones de Eucalyptus urophylla S. T. Blake en Tabasco. Rev. Chapingo : Serie Ciencias For. 20: 204-213. [ Links ]

Rosa, F.G., C. Morel P., R. Montanari., J.Motta S., G.Machado S., y E.Casarin Z. 2011. Variabilidade espacial de propriedades dendrométricas do eucalipto e de atributos físicos de um Latossolo Vermelho. Bragantia, Campinas 70: 439-446. [ Links ]

Van Deusen, P., A. Sullivan, and T. Matney. 1981. A prediction system for cubic foot volume of loblolly pine applicable through much of its range. Southern J. Appl. For. 5: 186-189. [ Links ]

Verbeek, M. 2004. A Guide to Modern Econometrics. Second edition. West Sussex: John Wiley & Sons. 429 p. [ Links ]

Vieira, F. S. y Bucsan, B. 1980. Ocurrencia natural de *Eucalyptus urophylla* en Indonesia. Silvicultura 3: 359-361.
[ Links ]

Wilson, J. S., and C. Oliver. 2000. Stability and density management in Douglas-fir plantations. Can. J. Forrest Res. 30: 910-920. [ Links ]

Zimmerman, D., L., and V. Núñez-Antón. 2001. Parametric modelling of growth curve data: An overview (with discussion). Test 10: 1-73. [ Links ]

Received: February 2016; Accepted: February 2017