Does post-fire forest management increase tree growth and cone production in Pinus halepensis?

Forest Ecology and Management 188 (2004) 235–247

Does post-fire forest management increase tree growth and cone production in Pinus halepensis? Ana I. Gonza´lez-Ochoa, Francisco R. Lo´pez-Serrano*, Jorge de las Heras Departamento de Produccio´n Vegetal y Tecnologı´a Agraria, Escuela Te´cnica Superior de Ingenieros Agro´nomos, Universidad de Castilla-La Mancha, Campus Universitario s/n, 02071 Albacete, Spain Received 21 October 2002; received in revised form 5 June 2003; accepted 14 July 2003

Abstract Sapling densities may greatly increase in Pinus halepensis forest stands after fire. This study examines the effects of different post-fire silvicultural treatments on Aleppo pine forests at sites of different quality in Spain: dry (good) (Yeste, Albacete) and semiarid (worse) (Calasparra, Murcia) by monitoring permanent plots from 1999 to 2001. Changes occurring as a consequence of thinning (to a constant density of 1600 trees/ha), full scrubbing and pruning (to one-half to total height) practices were examined measuring diameter and total height of the trees in a 2-year interval. The growth (except on relative diameter increment) of Aleppo pine from Yeste was greater than from Calasparra, probably as a result of its better site quality. Thinning in the good quality site, and thinning plus scrubbing, in the worse quality one, were the treatments that most improved pine growth. Pruning, in contrast should not be carried out in any site, at least under the conditions of this study. The different response in total growth between plots for the same treatment was caused by differences in initial characteristics of the plots: micro-site quality (dominant height by plot) was important in the good quality site, whereas initial density (saplings/ha) was important in the worse quality one. Regarding fructification, treatments that included thinning plus scrubbing improved, 22 months later, the probability of cone production by a factor of 2.07 in relation to control. # 2003 Elsevier B.V. All rights reserved. Keywords: Aleppo pine; After fire; Silvicultural treatments; Growth; Thinning; Scrubbing; Pruning; Spain

1. Introduction The Aleppo pine (Pinus halepensis Mill.) is a compulsory seeder (Trabaud et al., 1985). The postfire regeneration of Aleppo pine forest stands depends almost exclusively upon the canopy seed bank. * Corresponding author. Present address: Departamento de Ciencia y Tecnologı´a Agroforestal, Escuela Te´cnica Superior de Ingenieros Agro´nomos, Universidad de Castilla-La Mancha, Campus Universitario s/n, 02071 Albacete, Spain. Tel.: þ34-967599200; fax: þ34-967599238. E-mail address: [email protected] (F.R. Lo´pez-Serrano).

This results from the short life span of seed, which never extends beyond 2 years (Nahal, 1962; Ceballos and Ruiz de la Torre, 1979). In addition, the long seed life is sharply reduced as a result of intense predation (Costas and Daskalakou, 2000; Saracino and Leone, 1993). When fire affects mature P. halepensis forests, rupture of the cones and a massive liberation of seeds is registered (Gaussen, 1970; Le Houerou, 1974). In post-fire stands of P. halepensis, most of the cones are serotinous (Tapias et al., 2001). Released seeds do not usually reach distances longer than 20 m (Ache´rar et al., 1984). Mature trees are usually killed by wildfire

0378-1127/$ – see front matter # 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2003.07.015

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(Agge, 1998) and regeneration relies exclusively on the dispersed seeds (Trabaud, 1987) originating from the canopy seed bank. After seed dispersal, germination is restricted to late autumn–early winter, resulting in recruitment early in the rainy season of the Mediterranean climate (Schiller, 1978) with no dormancy period (Abbas et al., 1984; Costas et al., 1996). For example, a study in Israel showed that germination took place in autumn and was completed within 19 days (Saracino and Leone, 1993). Nevertheless, natural post-fire regeneration is not always guaranteed as it depends on several factors such as the age of the forest (Trabaud et al., 1985), the environmental conditions of the particular year of regeneration (Daskalakou and Costas, 1996), the available cones per tree (Saracino and Leone, 1994), the slope (Herranz, personal communication), and the intensity of the predation that seeds are subjected to (Nathan and Ne’eman, 2000). Thus, post-fire recruitment of P. halepensis shows very variable densities in Southeast Spain, ranging, 6 months later, from 0 saplings/ha (Martı´nez-Sa´ nchez et al., 1997) to 6666 saplings/ha (Herranz et al., 1997) or 86,600 saplings/ha (Martı´nez-Sa´ nchez et al., 1999). If factors affecting natural regeneration are favourable, very high density of saplings (Martı´nez-Sa´ nchez et al., 1999; Gonza´ lez-Ochoa and De las Heras, 2002) and density control (thinning) is needed. The principal aim of thinning is primarily to redistribute growth potential or to benefit the quality of the residual stand (Daniel et al., 1979). Another pine species associated with relatively dry, nutrient poor sites as Pinus contorta Dougl. Var. latifolia Engelm., also regenerates densely following natural disturbance, and is subjected to density control via early spacing (Yang, 1998). In this way, a reduction of pine density in semiarid quality sites implies an increment of the water availability for the remaining trees, and as a consequence, this speeds their growth (Yang, 1998). From a biological point of view, stands should be thinned prior to the onset of serious between-tree competition if timber production is a high priority. From a cost benefit perspective, thinning in regeneration post-fire of P. halepensis should be conducted from 4 to 6 years after fire (Lorente, personal communication, expert forest manager). The reason is that, due to the low saplings size at this time, thinning can be performed with clearing saw (portable swinging

arm scythe) and it is still not needed the more expensive use of the chain-saw. Furthermore, the volume of non-commercial residues is much more reduced and it is easier to destroy them. Nevertheless, although it is usual practice in forest stands in Spain, no scientific studies have been carried out on this subject. On the other hand, besides intraspecific competition, interspecific competition could also influence the development of the saplings. Several studies in the Mediterranean forest have shown that P. halepensis saplings at an early age increase growth if intra- and interspecific competition is reduced: thus, if P. halepensis saplings (by thinning) and Cistus sp. shrubs (by scrubbing) are reduced, pine mortality diminished and growth enhanced in Israel (Ne’eman et al., 1995; Mendel et al., 1997). Scrubbing also increased the survival of P. halepensis sapling in Spain (De las Heras et al., 2002). However, these studies have been carried out in early stages of the saplings (no more than 2 years old) and were focused on the survival of the saplings. Therefore, there is a lack of knowledge of the effects of this treatment in growth variables such as diameter or height. Other usual silvicultural practice in Southeast Spain in P. halepensis trees is pruning. This practice is usually carried out in P. halepensis forest stands when they are around 15 years old (J.D. Cabezas, personal communication, expert forest manager) and the principal aim of this practice is to reduce vertical continuity of the canopy biomass to avoid fire propagation (Ve´ lez, 2000). Although this seems to be adequate to avoid forest fire propagation, conclusive studies do not exist about its effects on productivity (Hubert and Courraud, 1988). As a result of the high recurrence of forest fires in Southeast Spain, the ultimate aim of thinning (and also scrubbing and pruning) would be to advance the production of viable cones. This, in turn, would advance several years the forest self-regeneration. In forest stand of Pinus pinaster Ait. in Spain, thinning resulted in earlier post-fire fructification (Tapias, 1998). The objectives of this study were, thus to: (i) find management techniques that improved growth of the residual stand in P. halepensis natural post-fire forests in Southeast Spain and, (ii) examine if any silvicultural practice may advance cone production, and thus, in turn, self-regeneration of the forest stand.

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2. Methods data 2.1. Study sites In August 1994 two great forest fires affected a total of 14,000 and 30,000 ha in Yeste (Albacete province) and Calasparra (Murcia province), respectively. In Yeste (28200 W, 388220 S), mature forests of P. halepensis and P. pinaster were burnt, whereas the main species in Calasparra (18380 W, 388160 S) was P. halepensis. At both sites the understorey (scrub) consisted of bushes of the species: Quercus coccifera L., Rosmarinus officinalis L., Juniperus oxycedrus L., Rhamnus lycioides L., Thymus sp. and Cistus sp.). Average annual rainfall and temperature (standard deviation) for the last 30 years were, respectively, 530  148 mm and 13:01  1:1 8C in Yeste, compared to 290  59 mm and 16:5  0:7 8C in Calasparra. The soil texture class was Sandy in Yeste and Sandy Loam in Calasparra, while the pH values were 8.6 and 8.7, respectively. N, P, K values in Yeste were 0.45%, 3.6 and 200.1 mg/l, respectively; in Calasparra they were 0.19%, 3.43 and 215.24 mg/l. Natural regeneration occurring after fire produced a very high density of Aleppo pine saplings at both sites. After 5 years, an experimental area was selected at each site and subjected to several silvicultural treatments. The average density and height of pine saplings in Yeste were (mean  S:E:), 5116  2134 trees/ha and 105:3  12:4 cm, compared to 46,000  20,400 trees/ha and 51:1  8:5 cm in Calasparra. In April 2000 both two sites suffered a Pachyrhinus squamosus outbreak and severe defoliation. Shortly after the outbreak, the forest recovered most of their vitality (Gonza´ lez-Ochoa and De las Heras, 2002). 2.2. Experimental design A factorial design with two factors (site and treatment) was carried out. The study sites (Yeste, Y and Calasparra, C) were the two levels for site, while the treatment had seven levels: Tt (thinning to a final density of 1600 trees/ha), Ts (total scrubbing), Tt,s (thinning plus scrubbing), Tt,p (thinning plus pruning to half of the total height), Ts,p (scrubbing plus pruning), Tt,s,p (thinning, scrubbing plus pruning) and Tc (control, i.e., without treatment). There were three

237

replicates for each treatment at each site, except the control at Yeste which had six plots. The experimental block for the treatments was located in an apparently homogenous and flat area at each site what was dominated by P. halepensis. Twenty-four and 21 rectangular plots (10 m  15 m) were fixed in Yeste and Calasparra, respectively. To avoid a border effect, a 6 m distance was kept between plots. Silvicultural treatments were randomly assigned to plots. For all plots with thinning treatment, the criterion used was to leave growing 26 of the highest trees per plot (1600 trees/ha), which, in addition, are placed in a spatial distribution random near systematic within the plot. All other trees were felled. Thinning and scrubbing were carried out with a clearing saw, and pruning was performed with shears. A meteorological station was installed on each site. The stations recorded temperature (T) and rainfall (P) every 2 h. Average T values for Yeste and Calasparra were, respectively, 16.3 and 17.1 8C, whereas mean annual rainfall was 844.9 and 225.8 mm, from the study period, i.e., from July 1999 to April 2001. 2.3. Observations Total height (cm) and diameter (mm, 30 and 20 cm above ground, in Yeste and Calaparra, respectively) of all saplings per plot were measured before treatments were imposed. Silvicultural treatments were carried out on the 15 July 1999 in Yeste and on the 1 August 1999 in Calasparra. Once silvicultural treatments had been carried out, selected trees were marked with plastic tags in a way that their individual growth could be assessed. A total of 26 trees per plot (i.e., 1600 trees/ha, the usual density in artificial regeneration) were selected in each plot. For plots where thinning was not performed, a sample of 26 trees was selected using the same criteria as in the thinning treatment. All trees selected at both sites (1170 saplings) were measured in August 1999. This included measuring the total height of the tree (cm) using a height stick, and their diameter (mm) at 30 cm above ground (in Yeste) or at 20 cm (in Calasparra) using a calliper, as well as the number of cones (male and female). These measures were recorded 2 years later (July 2001) on the same trees. For these measurements, the following were calculated: (i) total increment in diameter

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considered in the statistical analysis. Thus, the following variables were computed to assess the initial heterogeneity per plot: (i) initial density of the plots (D, trees/ha), as an index of the intraspecific competition, because the initial density varied as a consequence of the irregularity of natural regeneration after fire and (ii) dominant height (Hd, cm) of the plot, that could be an index of ‘‘micro-quality site’’ because soil depth and root development was expected to be greater where trees were higher (as trees were even aged). The dominant height by plot was modified from Parde and Bouchon (1994) as the average height of trees by plot plus two times the standard deviation. The values for these variables are presented in Table 2.

(Da, mm), as the difference between diameters at the two dates (August 1999 and July 2001); (ii) relative increment in diameter (Dr), as the ratio Da to diameter on August 1999; (iii) total increment of tree height (Ha, cm) as the difference between total heights at the two dates; and (iv) relative increment of height (Hr) as the ratio between Ha and the total height of the tree in August 1999. The effect of the treatments on cone occurrence was tested by assessing the presence or lack of cones in each tree on the following dates: 1 October 1999, 29 March 2000, 2 June 2000, 6 October 2000, 12 February 2001 and 9 July 2001. The reason for this procedure was that: (i) not all plots had a similar number of trees with cones at the start of the study, nor was here a similar number of cones per tree (Table 1); and (ii) to avoid the high complexity of cone dynamics (individual occurrence and disappearance). Thus, the analysis consisted of a simple logistic regression (see statistical section below). In order to examine the effect of treatments on the mean growth of diameter and height of the trees, all plots within a site should share the same starting conditions. This was not the case (see Table 2), so that it is very important that starting conditions are

2.4. Statistical analysis To test whether continuous variables fitted a normal distribution, data was examined using normal probability plot, standardised skewness and kurtosis, and the Kolmogorov–Smirnov test. Subsequently, missing data (due to lost identification number in the plastic tags in the field) were discarded from further analysis. The effect of each particular treatment and site on variables such as total height or diameter, was tested

Table 1 Characteristics of conea (female) production (mean  standard error) at two sites and two dates (1999, 5 years old and 2001, 7 years old) and for different treatmentsb (before and after treatments); n ¼ 3 plots for all treatments and sites (except for Tc treatment at Yeste, where n ¼ 6) Sitec

T

Before treatments (1999)d Tco

Y Y Y Y Y Y Y C C C C C C C

Tt Ts Tt,s Tt,p Ts,p Tt,s,p Tc Tt Ts Tt,s Tt,p Ts,p Tt,s,p Tc a

6.41 11.54 5.13 0 2.57 3.85 5.77 10.26 20.51 2.56 17.95 12.82 2.57 16.67

             

4.62 0 1.28 0 1.28 2.22 2.38 5.59 15.12 2.56 7.14 10.95 1.28 14.78

After treatments (2001)d

Ctree

Cha

0.06  0.04 0.17  0.03 0.05  0.01 00 0.03  0.01 0.05  0.04 0.06  0.02 0.10  0.06 0.27  0.20 0.03  0.03 0.19  0.08 0.17  0.15 0.03  0.01 0.17  0.15

213 711 258 0 148 411 253 3687 22190 1826 8339 10010 1369 7061

Tco              

154 110 64 0 74 271 114 1897 18223 1826 4678 8605 690 6448

Male cones (male flowers) were not detected along the period of study. Acronyms as in Table 2. c Site: Yeste (Y) and Calasparra (C). d Tco: trees with cones (%); Ctree: Cones by tree; Cha: cones by ha. b

19.23 32.05 16.67 8.97 14.10 15.38 14.10 12.82 21.80 5.13 20.51 16.67 2.57 16.67

Ctree              

9.68 8.97 9.25 5.59 3.39 5.87 2.15 2.56 14.28 2.56 8.41 13.01 1.28 14.78

0.40 0.60 0.63 0.10 0.40 0.53 0.23 0.21 0.29 0.05 0.35 0.28 0.03 0.19

Cha              

0.15 0.14 0.36 0.07 0.10 0.20 0.07 0.06 0.20 0.03 0.17 0.24 0.01 0.17

636 2588 1005 164 2290 841 1020 328 23692 82 554 17005 41 8169

             

237 528 570 108 594 310 324 89 19143 41 268 14211 21 7555

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Table 2 Forest mensuration characteristics of plots (mean  standard error) by site and treatment in 1999, before and just after conducting silvicultural treatmentsa Treatmentb

n

Before treatments D (trees/ha)

After treatments  (cm) H

Hd (cm)

D (trees/ha)

 (cm) H

Yeste Tt Ts Tt,s Tt,p Ts,p Tt,s,p Tc

3 3 3 3 3 3 6

3156 4356 5044 5022 5755 7333 5189

      

146 235 44 619 22 700 1358

111 110 91 105 107 107 97

      

20 8 7 16 8 4 5

170 185 144 165 173 171 153

      

14 15 14 16 14 14 10

1600 4356  235 1600 1600 5755  22 1600 5189  1358

133 110 116 131 107 137 97

      

23 8 7 16 8 6 5

Calasparra Tt Ts Tt,s Tt,p Ts,p Tt,s,p Tc

3 3 3 3 3 3 3

29222 56933 37867 41867 54400 51333 49994

      

8147 17745 16745 8801 13460 3014 12592

56 56 55 51 48 42 49

      

5 4 5 4 4 2 8

91 83 89 81 75 69 80

      

7 7 6 7 6 6 7

1600 56933  17745 1600 1600 54400  13460 1600 49994  12592

83 56 67 82 48 76 49

      

5 4 4 7 4 4 8

 average height; Hd: dominant height (the average height of trees by plot plus two times the D: number of trees by ha (density); H: standard deviation); n: number of sampled plots. b t: thinning to a final density of 1600 trees/ha; s: total scrubbing; p: pruning to half of the total height; c: control. a

using indicator variables (or dummy variables) in multiple regression analysis (Neter et al., 1996; Manugistics, 1998). These indicator variables (predictor variables) were the different treatments (k  1 indicator or dummy variables, k ¼ 7 levels of treatments), and the sites (two sites, one dummy variable), and the interaction of both. Additional dummy variables were the nested effect of plot within treatments. Thus, the model (the response variable is on a tree basis) included a total of 44 dummy variables: a dummy variable for site, six dummy variables for treatment, six for interaction of site by treatment and 31 dummies for plot effect nested within treatment. The models were simplified using the general linear test statistic (F-test, Neter et al., 1996) to test some hypotheses about regression coefficients. In addition, a multiple regression analysis was carried out to discern whether the nested effect of plot within treatment (i.e., the last dummy variables mentioned above) might be explained by intraspecific competition o by micro-site quality. The predictor variables were the dummy variables of site and treatment (no plot effects were considered here) and the dominant height and density, which

substituted the dummy variables for plots nested within treatments. The best model was chosen selecting the highest R2, lowest S.E.E., lack of colineality of the predicting variables (low variance inflation factor), and based on an analysis of the residuals both examining graphs of residuals and the Durbin–Watson statistic. In all cases, the model chosen was the one that explained the behaviour of the variable of interest with a clear physical basis. The final models were validated using predicted values in both, the models that use only dummy variables (including plot effect) and those that included only quantitative variables for plot effect. A simple regression analysis between both predicted values allowed testing of whether the intercept was different from 0 and the slope differed from 1. A simple logistic regression model (maximum likelihood method, Neter et al., 1996) was used to test if the treatments carried out in both sites increased cone production in addition to speeding growth of height and diameter. Individual trees were assigned a 1 or 0 depending on whether they had cones or not, respectively. This variable (the response variable) is a binary

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random variable that follows a Bernoulli distribution taking on the values 1 and 0 with probabilities p and (1  p), respectively. Since p (even probability) did not differ between sites (P > 0:1, values of 0.145 for Yeste, and 1.167 for Calasparra), and in order to get a large sample size, a logistic regression was applied for each treatment by pooling both sites. The predictor variable (Xi) was the date (interval time, in months), from October 1999 up to each record. The odds ratio (OR) interpretation of the estimated regression coefficient (bi, as slope in simple regression analysis) allowed to obtain the change in probability of occurring event 1 versus 0 after a particular period of time:   odd1 logðORÞ ¼ log ¼ nbi odd2 where odd1 ¼ p=ð1  pÞ for Xi, and odd2 is the same equation for Xiþn, whilst n is the interval of time (from 1 to 22 months). To check the appropriateness of the fitted logistic regression model we will use the w2 goodness of fit test (Neter et al., 1996). If the logistic regression is appropriate, the statistic of goodness follows approximately a w2 distribution with c  2 d.f. if n is large (c is the number of classes of grouping the cases, n is the number of cases).

3. Results 3.1. Diameter and height increments Multiple regression analysis (Table 3) showed that site was a significant factor for the following variables: height (Ha), diameter (Da) and relative height increments (Hr). Ha at Yeste was 17.34 cm and Da 6.18 mm, while at Calasparra the values were 7.76 cm (17:34  9:58) and 1.75 mm (6:18  4:43), respectively, for control plots. Relative height increment (Hr) was significantly lower (0.05) in Calasparra than in Yeste (Table 3). In contrast, relative diameter increment (Dr) did not show a site effect (Table 3). In general, silvicultural treatments had a significant effect on all variables. However, treatments had a different effect at each site, i.e., there exists an interaction between site and treatment.

Table 3 Regression coefficients for predictor variables of the absolute and relative increment of trees and statistics for goodness of fita Ha

Hr

Da

Constant C Tt Ts Tt,s Tt,p Ts,p Tt,s,p

17.34 9.58 9.26

0.13 0.05 0.08

2.83

0.03

     

9.78

(C) (C) (C) (C) (C) (C)

(Tt) (Ts) (Tt,s) (Tt,p) (Ts,p) (Tt,s,p)

(Tt)  (P ¼ 9) (Tt)  (P ¼ 2) (Tt)  (P ¼ 14) (Ts)  (P ¼ 16) (Ts)  (P ¼ 29) (Tt,s)  (P ¼ 7) (Tt,s)  (P ¼ 38) (Tt,s)  (P ¼ 43) (Tt,p)  (P ¼ 23) (Tt,p)  (P ¼ 42) (Ts,p)  (P ¼ 20) (Ts,p)  (P ¼ 39) (Ts,p)  (P ¼ 40) (Tt,s,p)  (P ¼ 44) (Tc)  (P ¼ 1) (Tc)  (P ¼ 19) (Tc)  (P ¼ 41) n F P R2 S.E.E. DW

Dr

6.18 4.43 2.99 2.74 5.39 3.35 3.95 4.14

0.31

2.34

0.09 0.17

3.35

0.10

4.05

0.25 0.27

0.27 0.24 0.14 0.16

0.07

0.03 3.49

0.07 0.05

6.85 2.51 0.16 0.07 0.08 3.63 3.02

3.11 2.27 2.68

0.21 0.14

3.88 0.09

0.15 0.14 0.14

0.07

1.85 1.66

892 23.79 <0.001 24.51 0.07 1.87

895 43.40 <0.001 45.70 3.44 1.92

3.20 895 63.70 <0.001 41.88 6.77 1.71

899 21.49 <0.001 22.08 0.17 1.83

a The response variables are the diameter periodic (2 years) increments of trees (recorded at 30 and 20 cm above ground, respectively for Yeste and Calasparra; including total Da in mm, and relative Dr increments) and height periodic increments (total Ha in cm, and relative Hr). Predictive variables were dummy (44 variables): treatments (six dummy variables), site (one dummy variable), treatment by site interaction (six dummy variables) and nested effect of plots within treatments (31 dummy variables). All coefficients shown are significant at P < 0:05. T: treatments, acronyms as Table 2; C: Calasparra site; P: number of plots from 1 to 45 (Yeste, plots 1–24; Calasparra, plots 25–45). Empty cells means that the coefficients are not significant (P > 0:05); n: number of the complete data (trees).

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241

Fig. 1. Means and standard errors for periodic (2 years) increment variables at two sites (Yeste and Calasparra) and seven treatments (acronyms as in Table 2): (a) total diameter increment (Da, mm); (b) relative diameter increment (Dr, ratio); (c) total height increment (Ha, cm) and (d) relative height increment (Hr ratio).

At Yeste, Tt and Tt,s treatments were those that produced a positive and significant effect with respect to the control for Ha and Hr variables (Table 3; Ha and Hr for Tt and Tt,s, respectively, 9.26 cm and 0.08, and 2.83 cm and 0.03). For Da, all treatments produced a significant increment with respect to the control, but Tt,s (5.39 mm) and Tt,s,p (4.14 mm) produced the biggest increment. In relation with Dr, Tt, Tt,s, Tt,p and Tt,s,p treatments had a positive and significant effect (Table 3 and Fig. 1b). At Calasparra, Tt,s and Tt,s,p produced significant effect on Ha and Hr with respect to the control (2.83 cm and 0.03, and 3.49 cm and 0.07, respectively, Table 3). For Da and Dr, all treatments including thinning originated a significant increment (Table 3). For both localities, all variables showed a nested effect of plot within treatment. Thus, the different plots within a treatment did not achieve the same mean increment (Table 3). Initial heterogeneity of the plots (Table 2, see Section 2) was quantified by the initial density (D) and the dominant height (Hd, micro-site quality). To test if differences in these variables between plots could explain differences in response to treatment

within site (Table 4) a multiple regression analysis was performed using both, these and the dummy (treatment) variables, for each site. Table 4 shows a different behaviour of these quantitative variables depending on site. At Yeste, Ha depends on initial dominant height of the plot (Hd). In addition, treatments Tt and Tt,s produced a significant increment with respect to the control, the same result obtained by the model that included only dummy variables. Da depended on plot dominant height and Tt,s produced the best significant increment compared to the control. In addition, Tt and Tt,s,p produced a significant effect with positive dependence on initial density. For Hr, Tt and Tt,s produced again a significant increment, but Hd was not significant. At Calasparra, the initial density of the plot (D) had a negative relationship on both, Ha and Hr, and all treatments except Tt produced a significant increment compared to the control. However, for Hr, the effect of initial density was more intense in treatments that did not include thinning (Ts and Ts,p, Table 4). Da depended also on initial density (the higher the density, the lower the increase in diameter) and Tt, Tt,s,

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Table 4 Regression coefficients for predictor variables and statistics for goodness of fit for both sites Yeste (Y) and Calasparra (C)a Ha Y Constant Tt Ts Tt,s Tt,p Ts,p Tt,s,p Tt  (D) Ts  (D) Tt,s  (D) Tt,p  (D) Ts,p  (D) Tt,s,p  (D) Tt,p  (Hd) Tt,s,p  (Hd) D Hd n F P R2 S.E.E. DW

Hr C

9.64 7.25 4.65

Y 8.94 3.83 4.18 2.82 2.72 5.66

Dr (both sitesb)

Da C

Y

0.13 0.06 0.06

C

0.11

3.891

0.16 0.08

4.26

3.888

0.12 0.08 7.93  104

6.04  105

1.6  106 4.4  105 7

8.32  10 1.4  106

3.7  104

6.5  105 0.04 456 15.91 <0.001 9.00 8.54 1.72

439 17.26 <0.001 18.31 4.15 1.69

437 19.75 <0.001 25.59 0.07 1.73

0.243 0.078 0.088 0.138 3.1  1.1  1.9  2.1  2.6  2.8 

106 106 106 106 106 106

0.026 0.047 2.8  105

8.53  107 455 21.50 <0.001 8.28 0.06 1.78

0.302 0.154

0.023 451 14.30 <0.001 10.56 4.59 1.77

444 43.19 <0.001 32.26 2.05 1.75

899 22.85 <0.001 21.11 0.24 1.84

a The response variables are the diameter increment (in the last 2 years) of trees (recorded at 30 and 20 cm above ground, respectively, for Yeste and Calasparra; including total Da in mm, and relative Dr increments) and height increment (total Ha in cm, and relative Hr). Predictive variables are dummy (treatments, six dummy variables, acronyms as Table 2), quantitative variables: stand density (D, number of trees/ha) and dominant height (Hd, m) both before treatments, and the interactions. All coefficients shown were significant at P < 0:05. Da: total diameter growth; Dr: relative diameter growth; Ha: total height growth; Hr: relative height growth. b Relative diameter growth does not show significant differences between sites. Empty cells means that the coefficients are not significant (P > 0:05).

Tt,p and Tt,s,p (treatments that include thinning) showed a significant and positive effect. However, this effect was related to initial density for treatments Tt and Tt,s, and was related to dominant height for treatments Tt,s,p and Tt,p (Table 4). For both localities, initial density (nested within treatments) was significant for relative diameter increment (Dr). Moreover, the former variable had a positive effect for treatments with thinning (Tt, Tt,s, Tt,p, Tt,s,p; the greater the initial density, the greater the increment), whereas the effect was negative for treatments without thinning (Ts and Ts,p; Table 4, see Section 4). Results obtained with the two regression models (using either dummy or quantitative variables for plot effect), were validated by comparing the

predicted values for Ha, Da, Hr and Dr, obtained by both models. Table 5 shows that both predicted values for each variable, did not differ significantly (intercept 0; slope 1). Thus the initial plot density (mainly in Calasparra) or dominant height (in Yeste), may explain differences in the growth (both total and relative) between plots for the same treatment. 3.2. Cone production Tables 1 and 2 show that in the ANOVA before treatments (1999), site was significant in the number of cones per hectare (and also in number of total trees, P < 0:01). Calasparra showed a greater number of trees/ha (D) and cones/ha (Cha) than Yeste (45,946 and

A.I. Gonza´ lez-Ochoa et al. / Forest Ecology and Management 188 (2004) 235–247 Table 5 Intercepts (a) and slopes (b) for simple regression analysis between predicted values for increment variables (Da, Dr, Ha, Hr) using both models, those using dummy for plot effect (Table 3) and those using quantitative variables for this effect (Table 4) Variablesa

ab

bc

R2

S.E.E.

n

Da Dr Ha Hr

0.026 0.01 0.365 0.004

1.001 0.976 0.975 0.965

90.0 82.8 86.5 75.3

0.99 0.06 2.07 0.02

895 899 895 892

a Da: total diameter increment; Dr: relative diameter increment; Ha: total height increment; Hr: relative height increment. b All intercepts do not differ significantly from 0 (at 95% confidence interval). c Slopes did not differ significantly to 1 (at 95% confidence interval).

5122 trees/ha, and 7783 and 285 cones/ha, respectively). However, the percentage of trees with cones (Tco, 4.85 and 11.90%, respectively, for Yeste and Calasparra) and the number of cones per tree (Ctree, 0.06 and 0.13 cones per tree, respectively, for Yeste and Calasparra), did not show any significant site difference (P ¼ 0:06 and P ¼ 0:08, respectively), although there was a marginally significant difference. After treatments (2001), Tco and Cha did not show significant site differences (P ¼ 0:42), ranging between 17.21 and 13.74% of trees with cones and 1220 and 7125 cones/ha, respectively, for Yeste and Calasparra. However, for Ctree, did exist significant

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Table 6 Regression coefficients (ai, bi) and statistics for goodness of fit (for each treatment) obtained by simple logistic regression model (maximum likelihood)a Treatment ai Tt Ts Tt,s Tt,p Ts,p Tt,s,p Tc

2.174 1.186 3.144 2.260 2.020 2.970 1.786

bi

Odds ratio w2

d.f. P

0.035 0.031 0.059 0.023 0.032 0.042 0.021

1.035 1.031 1.061 1.024 1.033 1.043 1.022

4 4 4 4 4 4 4

3.86 7.55 3.71 1.38 3.32 4.15 2.39

n

0.425 942 0.109 942 0.447 936 0.847 948 0.505 942 0.385 935 0.664 1375

a The response variable was the probability for cone production in a tree for a specific date and treatment and the predictor variable was the interval time elapsed between the application of the treatment and the date of the measures. Acronyms as in Table 2. All models were significant (P < 0:05); n ¼ 7020 (1170 trees  six dates).

differences due to the site (P ¼ 0:02) ranging between 0.41 and 0.20 cones by tree, respectively, for Yeste and Calasparra. Treatment Tt,s best stimulates the probability of production of cones for both sites, followed by Tt,s,p (Table 6). The probability of having cones in a tree is increased 3.66 times after 22 months with treatment Tt,s (Fig. 2). In contrast, the control treatment has the lowest probability of cone production as time goes by (the increase in probability is only 1.59 times after 22 months). This means that the net gain in

Fig. 2. Odds ratio (increase in the probability cones occurring in a pine versus not occurring) for each treatment (acronyms as Table 2) versus time interval after treatments. Statistics as in Tables 5 and 6 (pooled data for both sites).

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probability of having cones 22 months after treatment is 2.07 times.

4. Discussion Growth in height and diameter at Yeste was higher than at Calasparra, which is indicative of a better site quality at Yeste. Thus, average pine heights at the beginning of the study were 105.3 cm in Yeste and 51.1 cm in Calasparra. It is well established that forest height depends primarily on site quality (Daniel et al., 1979). In addition, initial density in Calasparra (46,000 trees/ha) was far higher than in Yeste (5116 trees/ha) and thus, intraspecific competition might be more influential in Calasparra. The interaction between site and treatment, as well as the nested effect of some plots within treatments, might result from the initial heterogeneity of the plots. Thus, initial density in Calasparra and dominant height in Yeste, appear to be the reason for the growth differences towards the same treatment between plots. This could be due to the fact that at Yeste there was little variability on plot density within each treatment in the majority of the treatments (relative standard error ranged from 0.87% for Tt,s to 12.33% for Tt,p, data calculated from Table 2). However, for Hd a bigger variability for all treatments existed (relative standard error ranged from 8.09% for Ts,p to 9.72% for Tt,s). In contrast, for Calasparra the contrary was true (relative standard error for D ranged between 5.87% for Tt,s,p and 44.22% for Tt,s, and for Hd ranged between 6.74% for Tt,s and 8.7% for Tt,s,p). At Yeste, all treatments that included thinning led to increased diameter growth. However, only thinning and thinning plus scrubbing treatments led to a significant increase in height growth. This could be explained if the plot effect is considered in the interpretations. Thus, for Da model (Table 3) some plots of treatments Ts, Tt,p and Ts,p (plots numbers 16, 23 and 20, respectively) have negative coefficients. In contrast, a plot with Tt treatment has a positive coefficient (plot number 9). The latter means that Tt and Tt,s are the best treatments for both variables. Thus, on good sites, reducing intraspecific plus interspecific competition may increase pine development. For Calasparra (the worse quality site), again all treatments with thinning improved the growth in

diameter (Da and Dr), but the best treatment was Tt,s (thinning plus scrubbing). However, for height increment (Ha and Hr) all treatments with thinning, except Tt, improved these variables, and the best treatments were Tt,s and Tt,s,p (Table 3). This anomalous result for Tt could be explained (see below) taking into account that plots with Tt treatment had the smallest density, i.e., 29,222 trees/ha (Table 2). Thinning may have improved diameter and height growth at both sites because it increases levels of available light and moisture to trees (Brix, 1983). Diameter growth is one of the factors in which foresters can exert a considerable control. Thus, according to Reineke (1933, cited in Zeide, 1995), in even-aged stands (full density) the relationship between the quadratic mean diameter (Dg) of trees and their number per hectare (D), is a linear: logðDÞ ¼ a0  a1 logðDg Þ. Thus, if a thinning is carried out, there is no longer full density and this causes an unbalance in this relationship, which speeds up the process to reach the equilibrium stated by Reineke’s law (as a result of the greater resource availability). In agreement with this, the diameter of lodgepole pine increased significantly in response to thinning after 5 years, reaching an increment similar to that presented in un-thinned forest for a 10-year period (Yang, 1998). However, it should be noted that Tt treatment (only thinning) did not result in a height increment in Calasparra (in contrast to Yeste, Figs. 1c and 2d). This might be attributed to the differences in initial characteristics of the plots: they showed a dominant height similar to plots with Tc treatment (control), but had the lowest density (see Table 2). Thus, micro-site quality of plots in Calasparra were similar, but thinning was much more lightly in Tt plots than in the remaining plots subjected to other treatments with thinning. Moreover, as a consequence of an initial density lower than in the other plots, these had a greater amount of shrubs (data not shown). Thus, plots with Tt treatment did not improved substantially compared to the control. Fig. 3 shows plots with Tt are below the equilibrium line of Reineke’s (1933) law. This means that for this site and age these plots might stand a greater density. As a consequence and before treatment, the trees in these plots were growing at the maximum they could grow in this site under the existing hydric restrictions. Thus, a slight thinning will not increase substantially the availability of resources

A.I. Gonza´ lez-Ochoa et al. / Forest Ecology and Management 188 (2004) 235–247

Fig. 3. Reineke’s (1933) law for Calasparra site before treatments: logðDÞ ¼ 13:02  1:17 logðDg Þ where D is density (trees/ha) and Dg is mean quadratic diameter (mm) for each treatment (acronyms as in Table 2); log is natural logarithm. The model was significant (P < 0:01), Tt data were dropped in the analysis.

because the limiting factor is water, and the presence of shrubs makes the conditions worse for pines. On the other hand, it should be noted that the treatment involving only scrubbing (Ts) did not improve growth significantly at both sites. This could be because, as has been suggested before, the interspecific competition is the most important factor that affect growth but, in addition, the Mediterranean shrub species have shown to improve soil chemical properties in a typical P. halepensis forests in Spain (Gimeno-Garcı´a et al., 2001). Thus, it is not surprising that no additional growth in diameter is found if scrubbing is added to thinning. Scrubbing plus pruning treatment (Ts,p) achieved results similar to scrubbing alone (Ts, Fig. 1, Table 3). Moreover, for relative increment in diameter (Dr), pruning added to thinning or to thinning plus scrubbing, resulted in a decrease of the growth (only 0.14 and 0.16, respectively) compared to the results obtained when only thinning or thinning plus scrubbing was applied (0.27 and 0.24, respectively, Table 3), particularly in sites of worse quality (Tables 3 and 4; Fig. 1). This might suggest that pruning had a negative effect in growth of diameter, according to the interpretation of the pipe model theory (Shinozaki et al., 1964). In general, pruning counterbalanced the improving effect of thinning in treatments including both (Tt,p and Tt,s,p) by delaying growth. Previous studies showed that early pruning might cause a delay in the bole growth and a slower injury cicatrisation (Hubert and Courraud, 1988).

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At the start of the study (trees aged 5 years), some fructification cones (female) were detected both in Yeste and in Calasparra. The fruiting process also started at 5 years in other P. halepensis post-fire forests in Spain (Tapias et al., 2001; Papio, 1994). This young fructification age has also been detected in some Aleppo pine post-fire forests in Israel (Ne’eman, 1997). In general, flowering in crowded trees occurs later than in isolated ones and, so, the better the sun exposure a tree has, the earlier the flower initiation and seed maturity (Meso´ n and Montoya, 1993). Site had a significant effect in variables such as Tco, Ctree, and Cha in 1999 (before the silvicultural treatments) due to the fact that Calasparra had a higher number of trees with cones, and a higher number of cones per tree. On the other hand, seed bank per hectare was higher, due to the higher individual production besides the higher density of pines at Calasparra. In 2001 (2 years after silvicultural treatments), the logistic analysis showed that thinning caused an increment in the probability of fructification for both sites. Cone production of a particular genotype is influenced by crown development and tree class or canopy position (Daniel et al., 1979). In this way, welldeveloped and well exposed trees are notoriously heavy seed producers. Thinning is a treatment enhanced to get a more vigorous trees and it has been used to increase seed production in trees (Brender and McNab, 1972). Initiation and periodicity in flowering are known to be associated primarily with genetic, carbohydrate, and nitrogen relationships, all of which can be influenced by silvicultural treatments (Daniel et al., 1979). In the study site, it has been proved that thinning origins a significant effects on the foliar nitrogen concentration in Yeste as well as in Calasparra (Gonza´ lez-Ochoa, unpublished). According to Schmidtling (1971), the increased availability of nitrogen could explain the improvement in flowering when some treatments have taken place. This author proposes that nitrogen fertilisation increases flowering in conifers due to physiological or biochemical effects. These effects could possibly be associate with amino acid production and especially free arginine, comparable to those induced by stress. Thus, whether silvicultural treatments can induce mobilisation of the nitrogenous compounds (White, 1984; Daniel et al., 1979), this could explain the goodness of thinning at Yeste and

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Calasparra by increasing foliar nitrogen involving a positive influence in flowering. P. halepensis trees usually begin reproduction as females (Panetsos, 1981; Tapias, 1998), and male cones appear several years later. A study in Israel showed that small trees start as females (the majority between 4 and 9 years old P. halepensis trees in two different climatic conditions) and later become monoecious (at the age of 13 years, Smidha et al., 2000). These findings coincide with the results obtained in our study where, between the ages of 5–7 years old, all cones presented were females. Due to the short period, which lapsed after the treatments, it is not possible to know whether these treatments stimulate the probability of male cone production in the same way as the female cones. On the other hand, the segregation of male and young female cones within the canopy of P. halepensis trees has a typical pattern (Gil and Ara´ nzazu, 1993): the majority of female cones are located in the higher part, a few in the middle and very few in the lower part of the trees. However, the male cones are located mainly in the middle and lower parts. In this sense, if pruning is carried out by eliminating the lower branches, it could influence the moment and or quantity of male cone production. In the same way, male cone production is lower in mature trees growing in the middle of dense forests due to the lack of live lower branches (Smidha et al., 2000). Thus, treatments including thinning (plus scrubbing) produced an increase in the probability of cone production in both localities. This has both biological and economical implications: if the trees have a greater number of cones which are viable, then there will be a higher probability that an adequate seed bank will ensure the start of a natural regeneration after a new fire, which in turn, will guarantee the future of the forest.

Acknowledgements We wish to thank the Regional Forestry Service of Castilla-La Mancha and Murcia Region for providing the research site. We are grateful to the following people for field data collection: E. Simarro, A. Atienza, P. Artime, C. Pe´ rez, J.J. Soler, A. Tu´ nez, J.A. Caro. We also thank Dr. Landete-Castillejos for

help in translation and improvement of style. This research was supported through funds provided by the FEDER Programme (EU): 1FD97-0441.

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