INTRODUCTION
Zagros forests have 5.05 million ha-1 area
covering northwest to south of Iran. These forests area in above 650-2200
m sea level with mean precipitation of 350-1000 mm. The dominant species
are Quercus persica, Pistacia atlantica, Acer monspessulanum
and Amygdalus lycioides (Anonymous, 2002). Pay attention to disturbing
of this forests in last years, its structures are disturbed and as coppice
forests. Forest settlers and native peoples in these forests are components
of this ecosystem. For achievement to forest structure, quantity and quality
characteristics and other parameters using different methods of sampling
are common.
In zagros forests using of sampling methods as sample
plots (fix or variable, regarding to forest conditions) and linear (transect)
for inventory of canopy cover. Richness (especially, for woody plant)
is one of the important factors in disturbed forests (as zagros forests).
Plant biological richness includes richness, diversity, population`s structure,
plant distribution algorithm (Parthasarathy, 1997). Biological richness
is adaptative capacity of forest ecosystems with their environments (Burianek,
1996).
In central zagros forests were used of plots with different
area in operation works. Plots with 100 ARE area and square form are being
used in Kakareza, Shol Abad and Ghleh Gol regions in Lorestan, west of
Iran (Anonymous, 2004a). Forestry group of Lorestan university used circle
plots of 10, 12, 15 ARE area in forest management plan of Chekriz in Lorestan
Kakareza region (Anonymous, 2004b). The other research in north of Fars
province (South of Iran) used square plots of 100, 200, 400 ARE area for
vegetation mapping (Anonymous, 2004a).
Salehpoor (1990) had introduced use of satellite images,
aerial photographs and field sampling as the best inventory method in
Iran. Porhashemi (2003) used plots with 12 ARE, 10, 1 m areas to study
forest structure, generation and vegetation in Doveiseh forests in Kurdistan
province (west of Iran).
Zobeiry (2000) proposed plots with 10-15 ARE area for
coppice forests of Iran west and 10-20 ARE area for high forests of
Quercus persica as the best area. Saber (1993) used circle plots of
10 ARE area and inventory network of 150x400 m area with random-systematic
method for calculation of canopy cover area, canopy cover volume (for
produce of seed), browse volume (for feed of livestock) in protective
forests of zagros south (Taheri, 1994).
Fallah (2000) in his study used square plots under selective
method. He used plots of 50 ARE area for investigating forest structure
(with number and volume ha-1 characteristics) and 100 ARE area
with adding other factors. Kerpel (1982), used plots of 0.5-1 ha-1
area for study of growth and stand structure changes in Slovaki natural
forest. Sample size was 3-6 plots regarding to stand conditions, species
combination and their structure characteristics.
For study of forest structure and stand tree combination
in national park of Harbey Kentin in Vietnam had used of plots 1 ha-1
area. Also, plots with 50x20 m area with rectangular form were used for
design of vertical and horizontal structure of forest (Kerkhove et
al., 1993). Many researches were performed to determine the best inventory
network dimensions for Iranian forests. Taheri (1994), selected 200x100
m inventory network and plots of 50 m areas. Navroodi (1992) had proposed
plots of 12 ARE area for forest management plans for the North of Iran.
Many researches were performed in relation to species
richness. Parthasarathy (1997) had investigated richness of woody plant
with diameter more than 10 cm in plots of 1 ha-1 area in tropical
forests. They found that these forests have high richness. Porbabayee
(2000), in his study used plots of 0.5 ha-1 areas with lozenge
shape for woody plant richness in fagetum type in the north of Iran. Hosseini
(2001) in investigating the richness of native needle leave forests in
the north of Iran using plots of 2500 m area found that richness of these
forests in common and new formulas have reduced with increase of elevation
above sea level. But, the changes of biological richness in relation to
the changes of plots area performed no researches, up to now. In order
to, has investigated tree richness instead bio richness and has analyzed
with using of graphs, in this study.
In Zagros forest can not use of complete inventory method
(due to expanded areas) and pay attention to performed plans in these
forests, using of sampling method with fixed plots is logical. Cost and
time are the other important factors in forest inventory and with selection
of the best inventory network and appropriate area of plots; it is possible
to reduce costs. By reason of, determination the appropriate plot area
for investigation of canopy cover, richness, species frequency in Zagros
forests are the purpose of this study.
MATERIALS AND METHODS
Study area: Study area is located on northern part of Khuzestan
province (that is component of Zagros forests ecosystem) between 3628000
to 3654000 longitude and 232000 to 294000 latitude (UTM unit) and 832-1845
m above sea level. Mean annual precipitation is 540 m (Anonymous, 2004c).
The dominant forest species in region are Quercus persica, Pistacia
atlantica, Acer monspessulanum and Amygdalus lycioides. Forest
vegetation is variable between 1-83% and in expended areas these forests
are degraded. Study area includes Bidrobeh, Shahzadeh Ahmad, Kabotaran
and Koh Chavani local usages. This study was performed in the summer of
2006.
Data collections: In mountainous regions using of single-stage
sampling method isn`t useful. In this conditions, using of stratification
sampling method (Zobeiry, 2002; Namiranian, 2007). In order to, was used
of stratification sampling and random-systematically methods, concurrently,
in this study. Firstly, on the basis of canopy cover, canopy cover classes
include 1-5, 5-10, 10-25 and 25-50%, more than 50% were selected. Number
of 5 plots separated for sampling of one stage (stratification) (with
slope < 50%) with using of forest walking and aerial photos and in
two stage have selected 2x2 km inventory network with plots 4 ha-1
area for the first four classes and plots 1 ha-1 area for five
class (Anonymous, 2004a).
Circle plots was used (that has the least circumference factor), as it
has recommended for inventory of forests in the west of Iran (Zobeiry,
2000). species name, canopy cover area, distance tree to center, height
of region, slope, aspect, effective factors on degradation, forest type
were recorded in every plots. For achievement to tree richness changes
and appropriate plot area the releve method was used. Radius of every
plots was calculated and then distance of each tree from plot center (using
GPS), number of trees and canopy cover area were recorded in plots 10,
20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300 and 400 ARE areas, separately
(Fig. 1, 2) and was calculated, extremely.
For determination
 |
| Fig 1:
|
Uniform plots and permissible radius
for trees inventory (112.86 m in plot 400 ARE area) in 1-5, 5-10,
10-25 and 25-50% canopy cover classes |
 |
| Fig
2: |
Uniform
plots and permissible radius for trees inventory (56.43
m in plot 100 ARE area) in >50% canopy cover classes |
|
of the appropriate plot area in west forests and to show
graphs of tree richness changes, was used of canopy cover 400 ARE on the
ground of basis canopy cover and was compared with this area the other
areas. Extremely, 48 plots of 4 ha-1 area and 7 plots of 1
ha-1 were recorded (18 plot in 1-5% class, 11 plot in 5-10
class, 10 plot in 10-25 class, 9 plot in 25-50 class, 7 plots in >50%
class). Statistical analysis was done in SAS software program in a simple
variance design and SNK test was performed for means comparison.
RESULTS
The least plots area for type map, canopy cover classes
and investigation zagros forests structure was calculated with analysis
collection of data. In 1-5% canopy cover class were insignificant differences
between plots 300 ARE area with plots 400 ARE area (Fig.
3). Thus, canopy cover (%) in this area has show actual area of forest
in 1-5% class. For 5-10, 10-25, 25-50 and >50% canopy cover classes
were calculated 125, 150, 100 and 75 ARE areas, respectively (in 95% confidence
level) (Table 1, Fig. 4-7).
Analysis of tree species richness relation with increase of area has
showed that in 1-5% class, 150 ARE area to after, increase trend of tree
richness is fixing, almost (Fig. 8). Trend of frequency
increase after to 125 ARE area is fixing, also (Fig. 9).
In 5-10% class, increase trend of tree richness is extensive to 50 ARE
and the other areas increase trend is monotonous, almost (Fig.
8). Total frequency of existent species in this class to 50 ARE area
is climbing and the other areas has similar
 |
| Fig 3: |
Significant correlation between
different areas of plots in 1-5% canopy covers class |
|
 |
| Fig 4: |
Significant correlation between
different areas of plots in 5-10% canopy covers class |
|
 |
| Fig 5: |
Significant correlation between
different areas of plots in 10-25% canopy covers class |
|
trend, also (Fig. 9). In 10-25% class, tree richness
has increase trend to 30 ARE area and thereafter is following of similar
trend (Fig. 8). Total frequency of trees in this class
to 40 ARE area is increase trend and thereafter has irregular trend (Fig.
9).
In 25-50% class, tree richness changes is following of irregular trend
and the most of this increase is visible in 30, 40 and 200 ARE areas (Fig.
8), Changes of species frequency are following of regular trend and
number 41 in hectare is fixing, mostly (Fig. 7). In more
than 50% class, increase of tree richness is climbing and tree richness
is increasing with increase of area (Fig. 8). Frequency
of
| Table 1: |
The most appropriate area of
plots for canopy cover inventory in Zagros forests |
|
 |
| * = Significant at the 0.05 F-probability level,
** = Significant at the 0.01 F-probability level, ns = no significant |
 |
| Fig 6: |
Significant correlation between
different areas of plots in 25-50% canopy covers class |
|
 |
| Fig 7: |
Significant correlation between
different areas of plots in more than 50% canopy cover clas |
|
 |
| Fig 9: |
Trend changes
of species frequency in five canopy cover classes |
|
species in this class is increasing trend that the most of it, is visible
in 50 ARE area (Fig. 9).
DISCUSSION
Pay attention to disturbed conditions of Zagros forests
and spot form of trees distribution in low classes of canopy cover and
on the basis obtained results, using of plots with more than 100 ARE area
is appropriate and it is similar to plots that is using by forests and
rangelands organization in Lorestan (Anonymous, 2004b) and Fars (Saber,
1993) provinces. But it is unlike with plots that were used by Zobeiry
(2000), Porhashemi (2003), Saber (2003) and Anonymous (2004b). In according
to obtained results for 1-5, 5-10, 10-25 and 25-50% canopy cover classes,
plots 300, 125, 150 and 100 ARE areas is appropriate, respectively. In
order to harmony with inventory of forest total, plots 200 ARE area for
canopy cover (<50%) is recommend, extremely.
Results of this study showed that for canopy cover class
more than 50% plots of 75 ARE areas are appropriate, this result confirm
Kerkhove et al. (1993), Fallah (2000) and Kerpel (1982) researches
in forests with condensed canopy cover. Tree richness in 1-5 canopy cover
class has extensive climbing trend to 50 ARE area. This climbing trend
is visible in 5-10, 10-25 and 25-50 canopy cover classes to 50 ARE, 30
ARE, 30 and 40 ARE areas, respectively.
Therefore, tree species richness is increasing with increase
of cover in central Zagros forests. This subject is trust in relation
with species frequency and with increase of canopy cover, species frequency
in area unit is increasing. Climbing trend is visible in canopy cover
class more than 50% similar to the other classes, also. Therefore, with
increase of canopy cover, mentioned information is available in small
areas. Pay attention to obtained results of this study is proposed plots
75 ARE and 40 ARE, for determination of tree richness and frequency in
<50% and >50% cover classes, respectively. This result is similar
to researches result of Parthasarathy (1997), Porbabayee (2000) and Hosseini
(2001). Consequently, using 100 ARE area sampling plots is suggested for
all density classes in central Zagros forests, pay attention to results
of determination plots area for tree species richness and canopy cover
in different classes of canopy cover in central zagros forests and in
order to saving of time, also
ACKNOWLEDGMENTS
The authors would like to acknowledge Mr. Amir Ahmadi,
Mr. Hasanvand, Mr. Kamari and Mr. Ziar for technical supports and throughout
the course of this project.
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