Arsalan · Muhammad Faheem Siddiqui · Moinuddin Ahmed · Syed Shahid Shaukat ·Alamdar Hussain

Abstract This study focuses on age, growth rate and diameter distribution of pine forests in the Malam Jabba area, Swat District, Pakistan. Wood core samples were taken from twenty stands. Picea smithiana was the oldest at 234 years with a 112-cm diameter. Abies pindrow was 125 years with an 80-cm diameter while the oldest Pinus wallichiana was 122 years with 75-cm diameter. The fastest overall growth rate of 1.5 ± 0.1 year/cm was for P.wallichiana on a west-facing aspect, while the slowest 5.8 ± 2.6 year/cm growth was P. smithiana on an eastfacing exposure. P. wallichiana and A. pindrow exhibited marked differences in growth rates over a 5-year period.The highest growth was by P. wallichiana from 1966 to 2006. A. pindrow showed less growth over the same years,such pattern simultaneously reverse from 1911 to 1965.The relationship between diameter and age, diameter and growth rate and age and growth rate were correlated. P.wallichiana and A. pindrow ages were correlated with diameter and growth rates. P. smithiana age was positive correlated with diameter. Generally, topographic and edaphic factors did not show significant correlations with growth rates, although some appreciable correlations were recorded. The growth of P. wallichiana was correlated with elevation while A. pindrow was correlated with maximum water retaining capacity. Diameter and age produced uneven size classes and many size gaps, which could be the result of anthropogenic disturbances.

Keywords Dendrochronology · Environmental variables ·Conifer species · Forest structure · Age classes

Introduction

Dendrochronological parameters are employed in forestry and ecological research on population dynamics. Tree rings are used to date the exact year of population formation and to analyze temporal and spatial patterns of processes in the physical and cultural sciences (Fritts 1976). Pakistan has potential for tree-ring studies due to its diverse topography,various climatic regions and long-lived trees (Ahmed 2014). Tree growth is affected by climatic and seasonal cycles (Speer et al. 2010). Initially, ages of some tree species from different mountainous areas of Pakistan were estimated (Swathi 1953; Khan 1968; Sheikh 1985), but their estimates were imprecise due to a lack of modern dendrochronological techniques. These studies were based on simple ring counts, small increment cores, small sample sizes, or only qualitative or observational estimates, hence there were considerable errors associated. Despite the importance of age and growth rate estimates in studies of population dynamics of forest trees, there are only a few published data on Pakistani tree species (Ahmed 1988;Ahmed et al. 1990a, b; Ahmed and Sarangezai 1991, 1992). They employed dendrochronological techniques to estimate age and growth rates of conifers to determine relations with climatic variables. Population dynamics and dendrochronological data of pine species from District Dir were evaluated by Wahab (2011), while vegetation ecology and dendrochronology of Chitral Gol National Park was studied by Khan (2011). Akber (2013)and Hussain (2013) estimated the age and growth rates of pine species from Gilgit and Baltistan respectively. Age and growth rates were estimated for conifers from different areas of moist temperate regions of Pakistan at elevations of 1430 m to 3145 m (Siddiqui 2011; Siddiqui et al.2013b). These estimates described the structure and population dynamics of selected moist temperate forests. The dendroseismological potential of pine species of the Azad Jammu and Kashmir province of Pakistan was estimated using age and growth rate data (Bokhari et al. 2013). They disclosed the past episodes of earthquakes that occurred in the area. Growth rate patterns on 5-year intervals would be helpful to evaluate past climatic variations.

No tree-ring studies have been conducted in Malam Jabba, Swat District in detail. The area had been under the jurisdiction of the military during the cleanup operation since last 15 years and the present condition of these forests is of interest. It is hoped that this study will contribute to the management of the Malam Jabba forests since they play vital roles in local climate, water shed management,soil protection and biodiversity conservation (De Sherbinin et al. 2007).

Materials and methods

Study area

Locations of the sampling stands are presented in Fig. 1,and edaphic and site characteristics in Table 1.

Environmental variables

The elevation of each stand was recorded with a Garmine Trex Legend HCx global positioning system, while slope was estimated with a PM-5/1520 PC slope meter, and site exposure using a compass. Four to five soil samples were randomly collected from each stand to evaluate edaphic properties, and pooled to make one composite soil sample.A 10-gm soil paste was prepared in 50 ml distilled water;the filtrate was used to determine pH, electrical conductivity (EC) and total dissolved solids (TDS) of each soil sample by Multiparameter (Model Adwa 1000, Hungary).Maximum water retaining capacity of the soil was determined according to Shaukat (1976) and soil organic matter following Jackson (1958).

Dendrochronology

Conifer forests in Pakistan are exposed to anthropogenic disturbances; therefore, stands that were least disturbed were selected for dendrochronological analysis. Other selection criteria were homogeneity of habitat conditions,adequate size (4 acres or more) and low grazing intensity.Core samples from dominant individuals of P. wallichiana A. B. Jacks., A. pindrow (Royle ex D. Don) Royle, P.smithiana (Wall.) Boiss. and C. deodara (Roxb.) G. Donf were sampled for the estimation of age and growth rates.A Swedish increment borer was used, often not passing through the centre or pith. These increment cores were cross-dated according to Stokes and Smiley (1968) and measured by the Velmex measuring system attached with computer, microscope and digital camera. A quality control program COFECHA (Holmes 1983) was used to check the accuracy of cross-dating and to produce growth curves of two pine species. The actual ages of the trees could be only obtained from the root collar which is not possible without cutting the tree. Therefore, two sections were obtained from the root collars as small samplings of each species at each location. The rings of the root collars of these seedlings were counted in these cores, which was the approximate number of years required for the tree to reach the height at which the cores were taken. Missing years and number of rings in the seedlings were added to the number of rings obtained from the increment samples to provide a good estimate of the total age of the trees (Ogden 1980, 1981; Ahmed 1984, 2014).

Statistical analysis

Data were subjected to statistical analysis according to Zar(2009). Correlation and regression analyses were performed between diameter and age, diameter and growth rate, age and growth rate and growth rates and environmental factors.

Results

Environmental variables

Topographic and edaphic characteristics showed little variability among the different sites (Table 1). These forests were distributed over all aspects with 25-50 slopes,and from 2100 to 2898 m elevation. Soil pH ranges from 5.4 to 6.7 with 728-1495 mm hos/cm electrical conductivity (EC). Organic matter content was 7.6-11.9% while the maximum water retaining capacity (MWRC) was 25.3-63.3%. Total dissolved solids were from 36.4 to 74.7 mg/L. The highest amount of soil organic matter(11.4-11.9%) was found in stands 2, 3, 4, 12 and 13 while the highest MWRC i.e., 66.5% was recorded in stand 13.

Fig. 1 The study area after Siddiqui (2011) and Siddiqui et al. (2013a)

Diameter distribution

Overall diameter size class structure of pooled data for each pine species is presented in Fig. 2. P. smithiana, P.wallichiana, and C. deodara are represented up to the 8, 9 and 6 diameter size classes respectively, while A. pindrow was present only in a small range of classes. Overall mean diameter shows a maximum for P. smithiana of 79.4 ± 5.2 cm, and a minimum for A. pindrow of 57.2 ± 1.6 cm. The relative variability as expressed by the coefficient of variation (CV %) was highest for P. smithiana i.e., CV = 25.3%, and lowest for A. pindrow, CV =16.4%. With the exception of C. deodara, all species showed gaps in size class distribution. P. wallichiana had few individuals in class 1, while A. pindrow was unrepresented in class 1, and P. smithiana was missing in classes 1 and 2. Large-diameter P. wallichiana, A. pindrow and C.deodara were absent from the study area. The maximum number of P. wallichiana were in medium size classes with a gradual decrease in number in larger size classes, while the maximum number of A. pindrow were distributed in small and medium size classes. P. smithiana was not found in small size classes while small numbers occurred in other size classes.

Age structure

Minimum and maximum diameters and ages are shown in Table 2. The average age for P. smithiana was highest at 109.1 years ± 13.9, with a CV of 49.3%, while P. wallichiana was the lowest at 75.4 years ± 3.0 with a CV of 24.6%. The oldest P. wallichiana (122 years) had a dbh of 69.5 cm recorded from Malikabad (stand 9), while a 120-year-old tree had a dbh of 76 cm in Mangerkot (stand 2). Fast-growing species such as P. wallichiana may reach 70 cm dbh in 64 years at Mangerkot, while the same species in Pechao may take 71 years to reach 70 cm dbh. An age of 65 years was calculated for A. pindrow at 53 cm dbh, while the oldest tree of the same species in Miandam had a dbh of 80 cm at 125 years. Another A. pindrow was 111 years old with a 67.0 cm dbh in Sur Glu. The oldest P.smithiana was 230 years with 112 cm dbh from Kuo. A 225-year-old P. smithiana with a 115-cm dbh was growing at Bela. The oldest C. deodara was 112 years with a 72.5 cm dbh at Kuza, while the same species was larger at81.9-cm dbh and 108-years-old at the Spin Oba site of Malam Jabba.

Table 1 Topographic and edaphic variables of sampling sites

The largest number of P. wallichiana occurred in the 51-70 year age class, followed by the 71-90 year age class, and then the 91-110 year age class. Class 1(31-50 years) and class 5 (111-130 years) had a minimum number of trees; no trees were recorded in older age classes(Fig. 3). A. pindrow was more numerous in the 71-90 year age class followed by 91-110 year age class, and occurred in class 2 and 5 in minimum numbers. The minimum and maximum age of P. wallichiana was 54 and 122 years,while A. pindrow was similar with a minimum age of 65 and maximum of 125. The presence of young trees of both species indicates better recruitment in the future. P.smithiana had a wide range of ages (36-230 years) with many gaps and this may be due to harvesting of trees over several decades.

Growth rates

Growth rates (year/cm and cm/year) of four pine species from different stands are presented in Table 2. P. wallichiana showed the highest growth rate (1.4 years/cm)from Pechao, while its lowest growth rate (3.9 years/cm)was recorded from Manglaur. Slow and fast growth rates were estimated and compared with earlier studies. A. pindrow from Sur Glu produced narrow rings (4.7 years/cm)while it had wider rings (2.2 years/cm) at Miandam, Swat valley. In the present study A. pindrow had the slowest growth rate (4.9 years/cm). Maximum growth (2.7 years/cm) was recorded Pendy while a minimum growth rate(8.4 years/cm) was recorded at Dur Sher. C. deodara exhibited the fastest growth rate of 1.9 years/cm from Benimanza Sar while its slowest growth rate 4.1 years/cm was recorded at Dando.

Fig. 2 Size class distribution of pine species. The Y-axis shows the average density ha-1 for each class. Note DBH classes were: 1 = 10-20 cm,2 = 21-30 cm, 3 = 31-40 cm dbh, … 10 = 91 100 cm, each class has a 10-cm width. Small size class = 10-40 cm, medium size class = 41-70 cm, large size class = 71-90 cm

Growth rate pattern on 5-year interval

Growth rate of P. wallichiana and A. pindrow on a 5-year interval was determined in order to evaluate the pattern of growth and development (Fig. 4). C. deodara and P.smithiana were not considered due to small sampled sized.P. wallichiana showed a greater rate of growth from 2010 to 1970 compared to A. pindrow, and slower growth initially (1911-1970). On the other hand, A. pindrow exhibited an opposite pattern to that of P. wallichiana. If the growth periods were examined in 20-year segments, in only seven of these periods were the growth rates of both species similar. Significant differences in the growth rates of the two species were in 1921-1926, 1941-1951,1971-2005.

Correlation between diameter/age, diameter/growth rate and age/growth rates

Diameters of P. wallichiana were positively correlated with age (p ＜0.01), and the relationship between age/-growth rate was also highly significant but negative; there was no relation between diameter and growth rate(Table 3). A highly significant positive correlation(p ＜0.001) was observed between age/growth rate and diameter/growth rate for A. pindrow and P. smithiana had a positive relationship with all three parameters, while there was an insignificant relationship between age and diameter for C. deodara. This species showed a significant correlation between diameter and growth rate (p ＜0.05) and a highly significant correlation between age and growth rate(p ＜0.001).

Correlation between growth rates with edaphic and topographic factors

Regression analysis evaluated the significance of topographic and edaphic factors on the growth rates of P.wallichiana and A. pindrow. P. smithiana and C. deodara were not included in this analysis due to small sample size.Correlations between growth rates and topographic factors(Table 4) were generally poor. The growth rate of P.wallichiana did not show any significant correlation with physiographic variables except for elevation, while A.pindrow growth rates correlated with maximum water retaining capacity.

Discussion

Environmental variables

Plants depend on soil characteristics, topography and climatic factors for growth and development but low amounts of organic matter are a characteristic of arid zone soils(Aubert 1960). Singh (1986) observed that in plant communities which had a higher percentage of soil organic matter, water-retaining capacity was better owing to greater colloidal nature of the organic matter.

Growth rate cm/year Growth rate year/cm Mean ± SE 2.15 ± 0.32 2.6 ± 0.53 2.55 ± 0.34 2.21 ± 0.68 2.45 ± 0.34 2.75 ± 0.38 1.5 ± 0.11 2.2 ± 0.43 3.1 ± 0.73 2.0 ± 0.26 2.1 ± 0.39 1.7 ± 0.05 3.06 ± 0.39 2.44 ± 0.36 3.46 ± 0.23 2.05 ± 0.09 3.70 ± 0.38 2.78 ± 0.26 3.13 ± 0.46 3.64 ± 0.41 2.70 ± 0.20 2.79 ± 0.22 3.89 ± 0.27 4.10 ± 0.40 2.98 ± 0.06 4.31 ± 0.49 3.53 ± 0.49 4.05 ± 0.87 4.16 ± 1.08 Mean ± SE 0.48 ± .07 0.385 ± .08 0.395 ± 0.06 0.495 ± 0.16 0.41 ± 0.06 0.365 ± 0.06 0.633 ± 0.05 0.45 ± 0.09 0.33 ± 0.08 0.496 ± 0.07 0.49 ± 0.11 0.58 ± 0.02 0.33 ± 0.043 0.429 ± 0.07 0.290 ± 0.02 0.489 ± 0.03 0.272 ± 0.03 0.363 ± 0.03 0.33 ± 0.04 0.276 ± 0.03 0.372 ± 0.03 0.36 ± 0.03 0.258 ± 0.02 0.245 ± 0.02 0.335 ± 0.01 0.234 ± 0.03 0.288 ± 0.04 0.258 ± 0.06 0.493 ± 0.09 Growth rate Max 2.77 3.22 2.89 2.9 2.79 3.14 1.79 2.71 3.86 2.39 2.59 1.75 3.46 3.05 3.70 2.21 4.74 3.31 4.51 4.37 3.11 3.15 4.17 3.71 3.10 4.82 4.04 4.93 6.3 year/cm Min 1.66 2.15 2.21 1.53 2.11 2.37 1.39 1.84 2.39 1.55 1.40 1.65 2.67 1.78 3.22 1.87 2.88 2.3 2.44 2.94 2.24 2.16 3.62 4.51 2.88 3.82 3.04 3.18 2.8 CV% Growth rate cm/Max 0.6 0.46 0.45 0.65 0.47 0.42 0.71 0.54 0.41 0.44 0.71 0.6 0.38 0.56 0.31 0.54 0.34 0.41 0.4 0.34 0.44 0.46 0.28 0.27 0.35 0.26 0.33 0.31 0.65 year 13.87 Min 43.03 0.36 28.66 0.31 3.82 0.34 16.89 0.34 13.83 0.35 16.46 0.31 29.42 0.55 18.32 0.36 16.87 0.25 22.31 0.41 5.34 0.57 23.05 0.29 12.62 0.27 13.86 0.45 24.64 15.43 0.21 15.29 0.3 13.39 0.22 4.56 0.22 18.39 0.32 22.92 0.31 14.52 0.24 18.02 0.22 14.31 0.32 0.75 0.21 10.75 0.25 18.32 0.20 15.85 18.23 0.37 73.66 ± 5.8 Age range Age 108 ± 14 92 ± 28 76.5 ± 15.5 83 ± 10.69 11.98 0.38 79.5 ± 9.5 59 ± 5 55.5 ± 1.5 59.6 ± 5.6 76 ± 10.11 12.46 0.33 92 ± 9 93 ± 7.1 Table 2 Age and growth of four pine species in 20 stands of Malam Jabba, Swat 74.5 ± 15.5 10.9589 Min Max Mean ± SE 63.33 ± 6.1 65.5 ± 2.5 96.5 ± 8.5 67.33 ± 4.9 75.44 ± 3.01 74.33 ± 6.56 90.25 ± 6.04 91.33 ± 2.40 85.75 ± 7.88 98.75 ± 1.31 92.5 ± 9.5 102 ± 13 77.33 ± 6.38 93.5 ± 0.5 85.5 ± 6.5 96.5 ± 12.5 89.71 ± 2.40 89.33 ± 9.40 81 64 120 67 112 57 89 71 90 75 97 64 68 94 77 87 96 89 94 92 62 54 70 83 101 54 59 94 122 54 90 54 63 59 88 105 61 80 111 65 75 103 88 69 107 77 125 83 102 89 115 67 93 79 84 109 78 225 CV%7.57 26.07 20.96 7.53 42.74 5.44 5.87 7.74 9.08 13.23 12.81 8.75 8.01 39.56 4.71 21.75 5.66 18.28 2.85 5.83 17.41 DBH Mean ± SE 65 ± 4.1 73 ± 3 56 ± 9 48.8 ± 10.2 68.5 ± 4.5 84.5 ± 20.5 67.83 ± 1.9 61 ± 3 72.25 ± 2.75 50.16 ± 3.8 72.66 ± 4.9 64.25 ± 4.25 46.9 ± 4.3 69.53 ± 4.1 89.4 ± 20.2 72.2 ± 1.98 10.96 66.35 ± 2.27 21.14 50.75 ± 5.5 53 ± 1.73 54.12 ± 3.99 14.76 52.83 ± 5.6 59.25 ± 3.75 12.66 69.25 ± 4.78 13.81 60.35 ± 0.85 25.42 54.4 ± 1.1 58.66 ± 1.97 59.3 ± 7.3 61.2 ± 11.1 27.27 53.25 ± 7.95 21.11 57.2 ± 1.58 24.64 81.5 ± 6.72 14.29 Sampling Dbh Max 73 76 67.8 59 73 105 70 64 75 46 81 68.5 51.2 77.2 109.6 74.8 67 56 62.5 64 67 80 71.2 54.5 62.5 66.6 72.3 61.2 115 range Min 57 70 56.6 38.6 64 64 64 58 69.5 43 64 60 42.6 63 69.2 68.3 43 50 44.5 48 55 57 49.5 52.3 55.9 52 50.1 45.3 72 Stand no.1 Pinus wallichiana 1 2 3 4 5 6 7 8 9 10 12 13 14 16 19 20 Overall mean ± SE 2 Abies pindrow 1 3 7 11 12 13 14 15 17 18 19 20 Overall mean ± SE 3 Picea simthana 3

Growth rate cm/year Growth rate year/cm Mean ± SE 4.8 ± 1.6 5.8 ± 2.6 3.65 ± 1.55 3.35 ± 0.15 2.73 ± 0.39 3.92 ± 0.08 2.724 ± 0.14 3.323 ± 0.54 2.796 ± 081 2.909 ± 0.47 2.844 ± 0.95 Mean ± SE 0.385 ± 0.07 0.385 ± 0.06 0.465 ± 0.16 0.395 ± 0.06 0.3 ± 0.02 0.255 ± 0.01 0.368 ± 0.02 0.320 ± 0.06 0.389 ± 0.11 0.371 ± 0.06 0.395 ± 0.13 Growth rate Max 6.4 8.4 5.2 3.5 3.12 4.00 2.87 4.05 3.60 4.00 3.80 year/cm Min 3.2 3.2 2.1 3.2 2.34 3.84 2.58 2.27 1.99 2.04 1.89 CV% Growth rate cm/Max 0.45 0.44 0.62 0.45 0.32 0.26 0.39 0.44 0.56 0.49 0.53 year 13.87 Min 46.24 0.32 22.95 0.33 75.03 0.31 61.35 0.34 0.58 0.28 9.42 0.25 4.81 0.35 27.28 0.25 37.21 0.28 23.59 0.25 47.13 0.26 26.53 Age range Age 53.5 ± 17.5 10.9589 Min Max Mean ± SE 95.5 ± 15.5 147 ± 78 163 ± 71 120.5 ± 0.5 105 ± 7 109.13 ± 13.91 49.30 73.5 ± 2.5 77.66 ± 2.23 85.5 ± 22.5 67.25 ± 7.93 84 ± 28 76 ± 5.59 82 234 92 98 76 97 90 36 71 120 111 121 80 69 112 71 55 63 108 55 56 112 CV%12.58 4.13 29.61 11.95 7.82 DBH Mean ± SE 57.3 ± 5.1 66.55 ± 1.95 84.85 ± 0.15 50.24 98.2 ± 13.8 19.87 76.4 ± 16 89.95 ± 2.05 18.94 79.4 ± 5.19 25.31 61.5 ± 5.2 59.53 ± 7.43 21.62 74.45 ± 7.45 14.14 53.9 ± 6.33 23.51 68.7 ± 3.8 61.80 ± 3.28 19.17 Sampling Dbh Max 112 84.4 60.4 92.4 102 77.9 66.7 69.5 81.9 68.5 72.5 range Min 78 62.4 52.2 68.5 64.6 54.7 56.3 45 67 40.6 64.9 Table 2 continued Stand no.4 5 6 7 11 17 Overall mean ± SE 4 Cedrus deodara 14 15 17 18 20 Overall mean ± SE Details of 20 stands are given in Table 1 SE standard error, dbh diameter at breast height, CV coefficient of variation

Fig. 3 Age structure of pine species based on size class. The Y-axis is the number of trees in different age classes. Note age classes i.e.,1 = 30-50 years, 2 = 51-70 years, 3 = 71-90 years,… 10 = 211-230 years

Fig. 4 Growth rates of Pinus wallichiana and Abies pindrow by 5-year intervals

Records of edaphic variables and topographic characteristics of other pine forests of Pakistan are available for comparison. The pH of the forests in this study ranged from 5.4 to 6.7 in agreement with previous findings. Malik et al.(1973) suggested 6.0-6.5 as an ideal pH for the growth and development of pines. According to Siddiqui (2011), pH values from 5.2 to 7.0 were recorded from different pine forests of the moist temperate areas of the Himalayan and Hindukush ranges of Pakistan, while a pH range of 4.9-6.5 was recorded from the forests of Dir, KPK, Pakistan, a dry temperate area (Wahab 2011). Malam Jabba in the Swat District of Pakistan is a moist temperate area that showed some variations of edaphic variables with the other climatic regions. Total dissolved solids (TDS) ranged from 0.03 to 0.16% estimated at different elevations of the forest communities of northern Pakistan (Hussain and Badshah 1998),while up to 0.04% TDS was recorded from the moist temperate areas (Siddiqui 2011). Our results show slightly higher values of TDS and conductivity, possibly due to anthropogenic disturbances.

Organic matter is an important soil component which improves water-holding capacity (Karim et al. (2009).Malik et al. (1973) reported 2.6-10.2% organic matter from northern area soils, while Khan (2012) found 5.3-7.0%organic matter from different forests of Chitral, KPK,Pakistan (Khan 2012). Maximum water retaining capacity(MWRC) improves the growth and development of vegetation by providing adequate water supplies. The MWRCranges from 32.5 to 65.4% in moist temperate forests(Siddiqui et al. 2013a), while Tareen and Qadir (2000)observed 24.1-56.0% MWRC from Quetta district,Baluchistan.

Table 3 Linear regression equations and correlation coefficients between diameter/age, diameter/growth rate, and age/growth rates

Table 4 Correlation between growth rates (cm/year) with edaphic and topographic factors

Topographic and edaphic factors govern the growth rates of trees (Currie 1991). By contrast, a weak relationship has been observed between the growth rates of pine species in this study with environmental factors. A possible explanation may be that there is a long history of disturbance in these forests. As result, many soil factors are altered over time; although P. wallichiana was a dominant species in this study area and flourished successfully, it did not exhibit any significant relationship with edaphic and topographic factors. A. pindrow showed a weak correlation with water-retaining capacity. Strong correlations between tree distributions and soil factors cannot be expected in an area with a long history of disturbances, such as military actions, stock grazing, illegal cutting of trees, and burning of vegetation to clear land. Limited research has been carried out along these lines in Pakistan. No significant relationships of soil variables with phytosociological attributes from forests of Baluchistan were observed by Ahmed et al. (1990a, b). In another study, Ahmed et al.(2011) did not find significant relationships between elevation and growth rates for five conifer species in other forests of Pakistan that showed the effect of anthropogenic disturbances.

However, contrary to this study, several researchers have reported significant relationships between physiographic factors and growth rates of conifers from different forests (Siddiqui et al. 2013b; Wahab 2011). There were significant relationships with topographic and edaphic factors and the distribution of vegetation (Hussain and Qadir 1970). There was a highly significant correlation(p ＜0.001) between basal areas of Juniperus excelsa M.Bieb. and P. wallichiana with elevation and slope in Gilgit,Pakistan (Hussain 2013). There was a significant negative correlation between altitude and growth rate when all growth rate values were considered (Ahmed and Sarangezai 1991). Tree-ring studies have contributed significantly to the understanding of environmental changes and forest stand dynamics (Pederson et al. 2007). On the limit of distribution of a tree species, e.g., a timberline on a mountain, environmental factors often restrict further expansion of the population (Block and Treter 2001). In the present study, the weak or poor relationships that were observed could be due to anthropogenic disturbances, and not environmental factors.

Diameter distribution

Studies of the diameter distribution of various forests of Pakistan are available (Khan 2011, 2017; Wahab 2011;Hussain 2013; Akbar 2013; Iqbal 2017). These studies also reported gaps in an unbalanced diameter distribution. With the exception of C. deodara, the other species had gaps in size classes. A large number of individuals in small size classes, gradually increasing in middle size classes, and then decreasing in larger size classes represent an ideal size class structure of a stable forest (Ahmed 1984). The forests of Pakistan have a long history of disturbance, i.e., legal and illegal logging, tree clearing for agriculture, and animal grazing. The present diameter distribution of four pine species is unstable when large size class trees are absent.Small numbers of trees in early classes indicates poor regeneration; their absence means no regeneration. Gaps in diameter distribution are not due to regeneration loss but to removal of large trees (Ahmed et al. 1990a). If regeneration is not promoted and disturbances do not cease, these forests may vanished eventually.

Age structure

Ages of conifer trees were recorded from different climatic conditions in Pakistan by several researchers (Wahab et al.2008; Bokhari 2011; Khan 2011; Hussain 2013; Siddiqui et al. 2013b). Age distribution varied between species,within species and between stands, and from site to site(Ahmed et al. 2011). Diameter is evidently not a good predictor of age. The ages of pines reported in this study are similar to those found by other researchers in Pakistan(Ahmed et al. 2011). A fast growth rate of P. wallichiana was recorded from Ayubia and Khanspur moist temperate conifer forests (Ahmed and Sarangezai 1991). A 277 yearold A. pindrow with a 89-cm dbh was recorded in Ayubia(Ahmed et al. 2009), while the oldest A. pindrow at 325 years was a considerably smaller tree (77.5 cm dbh)reported by (Siddiqui et al. 2013b) from Malam Jabba.

All four pines showed different age structures. P. wallichiana and A. pindrow stands did not show any recruitment over the last 35-50 years due to the absence of early regeneration. It is also evident that mature trees are being removed as indicated in P. smithiana stands because trees more than 130 years old were absent. There was a significant relationship between age and dbh in P. wallichiana from Zhob district of Baluchistan, and a tree 230 years-old with a 60-cm dbh was reported by Ahmed and Sarangezai(1991). Ahmed et al. (2009) found the largest. P. smithiana with a 148 cm dbh and 177 years, and the oldest tree at 347 years with only a 91 cm dbh from Naltar. Slowgrowing species have good vigor to face pathogenic and environmental pressures and these species attain high ages(Larson 2001). The age structure of trees plays a vital role in population dynamics. Knowledge of the age distribution is helpful for the management of forests and for increasing regeneration and recruitment (Agren and Zackrisson 1990).C. deodara showed almost the same pattern as P. wallichiana. The maximum number of trees occurred in lower age-classes (51-70 years), followed by the periods of 71-90 years, 91-110 years, and finally class 5(111-130 years) had a minimum number of trees.

Growth rate

Growth rate data of various conifer species from different areas are also available for comparison (Wahab et al. 2008;Ahmed et al. 2009; Akbar 2013; Hussain 2013; Siddiqui et al.2013b). The highest growth rate of P. wallichiana from Patriata, Murree hills (Siddiqui et al. 2013b) was 1.1 years/cm, while the lowest was 8.8 years/cm from the Shinu, Kaghan valley. There was a substantial difference in the lowest growth rate of P. wallichiana at two different locations of Malam Jabba; this could be due to nutrient availability, slope angle, aspect and/or anthropogenic factors. In another study, Siddiqui (2011) recorded the slowest growth rate for A. pindrow of 11.8 years/cm at Kuzah Gali(Abbottabad) and the fastest of 1.4 year/cm from Malam Jabba, Swat valley. This wide variation of growth rates by the same or similar species could be due to differences in environmental conditions. In the present study, A. pindrow exhibited slowest growth rate of 4.9 years/cm which is similar to the results obtained by Ahmed and Sarangezai(1991) and Ahmed et al. (2009). It was suggested that A.pindrow is a slow-growing species of moist temperate areas. This is corroborated by the present study. P.smithiana did not show a wide variance in growth rates.Growth rates of 3.1-14.3 years/cm by P. gerardiana Wall.ex D. Don from the Zhob District of Balochistan were recorded by Ahmed and Sarangezai (1991). Both these species prefer dry temperate climates. Khan et al. (2018)examined the age and growth rate of A. pindrow from Indus Kohistan, KPK, and reported significant correlation with environment variables that are comparable with the present study.

Growth rate patterns on 5-year intervals

Growth rates of both species varied greatly, although they occupied the same site but showed opposite patterns of growth. A reason for this contrast could be the adaptability and vigor to prevailing environmental conditions. Fast growth rates are seen as a fitness criterion because of competition, attainment of reproductive ability earlier,reduction of generation time, and increased short-term survival probability (Bigler and Veblen 2009). It has been observed that particularly old and slow-growing trees may be often associated with unfavorable environmental conditions (e.g., low temperatures, drought, or intense winds).Growth depends on the availability of adequate nutrients,suitable environments, prevention from natural disasters,and/or anthropogenic disturbances (Siddiqui 2011). Significant growth years were observed over the life span of both species except during 1956-1960 and 1961-1965.Growth in these two periods was insignificant. On a longterm basis, both species (A. pindrow and P. wallichiana)showed significantly different growth patterns. Each species has their own requirements and show different growth rates in similar environments.

From 1936 to 1955 there was significant growth while from 1956 to 1965 growth was insignificant, and then significantly different until 2005. For the 10-year period(1911-1920) there were not significant growth patterns.That both species show similar and significantly different growth at 5-year periods may be due to the history of disturbances at different times such as the cutting of trees.A. pindrow was dominant at 25-30 years and this may be due to its vigor or its aggressive behavior that suppressed P. wallichiana seedlings. At 30-35 years, P. wallichiana was initially suppressed by Abies pindrow since it became a superior competitor and presumably ecologically dominated the specific area. These two species showed both significant and insignificant differences in growth, although the mean extrinsic environmental factors appear to be the same for both. The two species may respond differently under similar environments as suggested by Ahmed (1984).Growth patterns of C. deodara, A. pindrow and P. wallichiana on 10-year intervals were determined by Iqbal(2017) from the forest of Shangla, KPK and the patterns were similar as in this study.

Correlation between diameter and age, diameter and growth rates, and age and growth rate

Contradictory results may be attributed to different degrees of anthropogenic disturbance. Ahmed and Ogden (1987)found a significant, negative correlation between age diameter and growth rate for Agathis australis in New Zealand. There was a significant relationship between age and diameter of Pinus gerardiana in the Baluchistan forest(Ahmed and Sarangezai 1991).

Siddiqui (2011) reported highly significant relations between age and growth of P. wallichiana, A. pindrow and C. deodara. Several researchers have shown correlations between diameter/age, diameter/growth rates, and age/-growth rates of pine species in different areas of Pakistan(Wahab et al. 2008; Ahmed et al. 2009; Siddiqui et al.2013b; Khan 2017; Khan et al. 2018). Similar results were found for the same species by Ahmed and Sarangezai(1991) in the Zhob district of Balochistan. In another study,Ahmed et al. (1990a) did not find significant relationships between diameter and growth rates of Juniperus excelsa in Balochistan.

Evidence of disturbance

Gaps in diameter and age structure usually show disturbances in the forests. The age distribution of P. wallichiana and A. pindrow showed no trees between 30 and 50 years.In early size classes, there was no recruitment, due to either no regeneration or to disturbances (Ahmed 1984). There were no trees in the 50-70 year and 301-320 year age classes of Picea smithiana. Gaps were evident in size class distribution due to disturbances (cutting, over grazing).Small, medium and mature trees were logged, while seedlings could not survive or were crushed during logging operations. This situation has been recorded for many forests in Pakistan (Ahmed et al. 2009; Siddiqui 2011).Disturbances in different forests of Afghanistan could very likely be due to civil war (Wahab et al. 2008). The area in this study consisted of small trees, indicating large-scale logging practices and/or disturbances such as fire, illegal cutting or over-grazing. Another important factor is both intra- and inter-specific competition that influences species survival and can result in the thinning of tree populations.Tree diseases are also a major cause of decline in density;vegetation may be deteriorating with the passage of time.Therefore, a proper management and conservation plan is needed to save these forests.

The overall situation of the forests in this study was not satisfactory, and their future is questionable due to the high degree of anthropogenic disturbances, and perhaps the efforts against militants by the Pakistan military. Local population pressure has increased demand for fuel wood,so tree density is on the decline, and stands are being heavily depleted. There is no quick change to this pattern of forest decline, and the opportunity for extensive collections should be considered sooner than later (Ahmed 1984). If there are no changes to current pressures and practices, these forest resources are likely to be exhausted within the next 20-30 years.

AcknowledgementsWe gratefully acknowledge the direction, input and valuable suggestions of Dr. Qiang Li, Associate Professor,Institute of Earth Environment, Chinese Academy of Sciences (No.97, Yanxiang Road, Yanta District, Xi’an 710061, China) during the preparation of this manuscript. We also remain grateful to Dr. Javed Iqbal and Dr. Abdul Wahab for their immense support during field sampling.