*
 

iForest - Biogeosciences and Forestry

iForest - Biogeosciences and Forestry
*

Allometric relationships for predicting the stem volume in a Dalbergia sissoo Roxb. plantation in Bangladesh

iForest - Biogeosciences and Forestry, Volume 3, Issue 6, Pages 153-158 (2010)
doi: https://doi.org/10.3832/ifor0554-003
Published: Nov 15, 2010 - Copyright © 2010 SISEF

Research Articles

Allometric relationships for estimating stem volumes of Dalbergia sissoo Roxb. (Sissoo) trees were investigated in monoculture plantations in Bangladesh. The various allometric relationships between stem volume and different dimensions were tested and the coefficient of determination R2 values were used to compare the strength of the relationships. Although the allometric equations were highly significant (P<0.01) there was considerable variation among them as indicated by the R2 values. Our results suggested that tree volume is more correlated with basal area than with simple D (stem diameter at 1.3 m height above the ground). The allometric relationships of stem volume to the tree diameter at 10% of tree height (D0.1) did not improve the allometric strength in comparison with simple D as reported in case of some other tree species. The multiplication of tree height H with D in the allometric equation gives a little improvement in the degree of fitness of the allometric equations. However, for the Sissoo plantations studied the stem dbh alone showed a very strong accuracy of estimation (R2 = 0.997) especially when used as D2. It is concluded that the use of tree height in the allometric equation can be neglected for the species, as far as the present study area is concerned. Therefore, for estimating the stem volume of Sissoo, the use of D2 as an independent variable in the allometric equation with a linear or quadratic equation is recommended. The paper describes details of tree volume allometry, which is important in silviculture and forest management.

Allometry, Monoculture plantation, Regression, Rosewood, Sissoo, Stem volume

  Introduction 

Sissoo is known as a premier timber species of the rosewood genus with the common name sissoo in Bangladesh. It is native to Sub-Himalayan zone including India, Pakistan and Afghanistan ([35], [20]). It is also recognized as an important species for fuel wood, shade tree, agroforestry and fodder in the region ([35], [34], [13]). Foresters traditionally derive timber volumes by employing allometric techniques. Allometric relationship for estimating stand volume as well as forest biomass is very important for managing any natural and artificial forest resources ([5], [10], [22], [24]). In the estimation of stand volume, the uncertainties appear due to the measurements of basal area and the use of a mean form factor, which is related to mean tapering ([24]). Thus, allometric relationships offer better estimates of the forest standing volume, which is also an important parameter in further research such as biomass and carbon-emission estimates avoiding the uncertainties in the bole-volume estimates ([16], [24]). Therefore, choosing a suitable functional variable in the allometric equation is very important for allometric techniques in forest science ([16], [17]).

There are various independent variables in the allometric relationships to estimate biomass. In most studies, D (dbh, stem diameter at 1.3 m height above the ground) was taken as the only independent variable in the allometric equation (e.g., [23], [29], [12], [1], [11], [26]). However, incorporation of the variable H (tree height - i.e., the use of D2H) ensures higher accuracy of allometric estimation in some tree species ([32], [33], [18], [28]). Moreover, the use of the new variable D0.12H (D0.1, diameter at one-tenth of H) instead of D2H has been suggested to improve the accuracy of estimation ([25], [14], [17]). Attiwill ([3]) found a strong allometric relationship between the girth (at the point immediately before branching) of main branches of a tree and branch dry weight in a stand of Eucalyptus obliqua L’ Herit. The use of DB (stem diameter at a height of clear bole length) provides better results in estimating the weight of branch and leaf, and leaf area per tree, as described by the pipe model theory of Shinozaki et al. ([30]). Various allometric equations have been developed from different tropical species ([7], [27], [6], [2], [9], [16], [10]). It is evident that mainly species of dicotyledonous trees differ in allometry because of distinctive bole shape. The allometric equations developed from various species yield useful estimates for large-scale inventories.

In this paper, we seek to establish the allometric relationships of the stem volume of individual trees to different dimensions, such as D, D2, D2H, D0.1, D0.12 and D0.12H and to propose a standard method for predicting the stem volume of Sissoo.

  Materials and methods 

Study site and species description

The study was carried out in block plantations at Khulna located in the southern part of Bangladesh (Fig. 1). The area belongs to subtropical region. Dalbergia sissoo is one of the important plantation species in the region.

Fig. 1 - Location map of the study site.

  Enlarge/Shrink   Download   Full Width  Open in Viewer

The species is a strong-light demander and shows good coppicing ability ([35]). The development of seedling is better in full overhead light than under partial shade. It is capable of growing under adverse soil and moisture conditions ([34]). Though, D. sissoo is a frost hardy species, its young leaves are adversely affected by severe frost and even the poles get completely defoliated ([31]). It has a complex root system that consists of a deep tap root and long lateral roots. Root suckers are produced from the lateral roots. Root suckers develop towards the end of the rainy season and may attain a height of more than 2 m on good soil ([15]). The species can grow naturally up to 1500 m elevation. The temperature in its native range averages 12-22 °C, but varies from just below freezing to nearly 50 °C with an average annual rainfall of 500 to 2000 mm with a monsoonal pattern and drought period of 3-4 months ([35]). The growth of the bole is crooked and straight logs of any great length are difficult to obtain. The heartwood is brown with darker streaks and because of its strength and durability, the wood is highly valued for furniture, constructional and general utility purposes.

Sampling, data collection and analysis

All the studies were carried out in May 2006 in a monoculture plantation of D. sissoo where the canopy was completely closed. A destructive sampling of 30 individual trees with a wide range of diameter and height were used for this study (Tab. 1). The following measurements were carried out: tree height H, stem diameter at a height of H/10 (D0.1 - [17]), stem dbh D and stem diameter at 1.0 m interval thereafter up to the merchantable height (stem height at 10 cm diameter). For measuring the diameter, girth values were converted to diameter after divided with π. Stem volume was calculated using the Smalian’s formula ([4]).

Tab. 1 - Description of sissoo sample trees used for this study. H: Tree height; D0.1: stem diameter at a height of H/10; D: stem diameter at 1.3 m height (dbh); V: stem volume.

Tree No. D (cm) D0.1 (cm) H (m) V (cm3)
1 9.549 10.027 9.01 10403.4
2 9.708 10.504 8.01 17653.9
3 10.134 11.141 8.02 25678.3
4 10.663 10.982 9.01 20521.2
5 10.759 11.459 8.07 27829.2
6 11.141 11.937 9.03 14610.4
7 11.513 12.414 7.50 36859.9
8 11.678 13.051 8.02 37520.3
9 11.937 11.937 9.75 38089.3
10 12.321 12.573 8.50 41628.1
11 12.614 12.892 8.50 46894.1
12 12.984 12.796 12.01 51629.2
13 13.210 13.528 11.03 62953.1
14 13.242 13.210 11.02 56349.9
15 13.687 13.433 10.25 57361.4
16 13.866 14.006 10.25 36131.8
17 14.006 14.324 8.50 60054.8
18 14.961 14.801 14.01 89369.7
19 15.597 15.756 14.04 101757.4
20 16.470 16.870 14.02 128149.9
21 16.999 17.666 11.01 139271.9
22 17.189 17.507 10.75 122993.6
23 21.963 22.282 12.50 206910.6
24 26.897 26.420 15.10 411254.8
25 27.056 26.420 15.00 390567.9
26 27.693 27.693 14.75 437078.1
27 29.155 28.254 20.05 569421.1
28 31.210 29.155 20.02 665874.1
29 32.675 30.152 20.50 759421.1
30 33.423 31.831 21.75 819421.1

  Enlarge/Reduce  Open in Viewer

The simple allometric equation is generally written using the power curve ([17]) in the form (eqn. 1):

\begin{equation} y=ax^b \end{equation}

where y is the dependent variable and x is the independent variable, and a the coefficient and b the allometric constant. The equation is linearized by taking logarithms, as follows (eqn. 2):

\begin{equation} ln(y)=ln(a)+b \cdot ln(x) \end{equation}

where ln a and b are the intercept and slope of the regression line, respectively. The ln a and b are obtained by the method of least squares. In this study, the allometric relationships of the volume and different dimensions such as D, D2, D2H, D0.1, D0.12 and D0.12H were also established using following equations (eqn. 3, eqn. 4, eqn. 5, eqn. 6, eqn. 7):

\begin{equation} Linear:\;y=a+bx \end{equation}
\begin{equation} Exponential:\;y = a \cdot e^{bx} \end{equation}
\begin{equation} Logarithmic:\;y = a + b \cdot log(x) \end{equation}
\begin{equation} Quadratic:\;y=a+bx+cx^2 \end{equation}
\begin{equation} Cubic:\;y=a+bx+cx^2+dx^3 \end{equation}

The coefficient of determination R2 was calculated using the following equation (based on the real data before logarithmic transformation - eqn. 8):

\begin{equation} R^2=1- {{\sum_{i=1}^n (y_i - \hat{y}_i)^2} \over {\sum_{i=1}^n (y_i - \bar{y}_i)^2}} \end{equation}

where yi is the observed value, yei is the corresponding values calculated from the regression line, and ymi is the mean of the observed values ([19]). The R2 value (coefficient of determination) is a measure of the goodness-of-fit between the observed and calculated values ([17]).

  Results 

Various allometric equations were developed for data fitting. The allometric relationships of stem volume of sissoo trees to D and D2 are illustrated in Fig. 2. The scatter plot shows a non-linear trend when D is used as independent variable. This trend is changed to linear distribution if D2 is used (Fig. 2). This is also illustrated by the coefficient of determination using D, where the power equation (R2 = 0.970) shows better fitting than linear equation (R2 = 0.944). When D values are squared, the linear equation shows stronger relationship (R2 = 0.983) than power equation (R2 = 0.970 - Tab. 2). In this case, the polynomial cubic equation showed the best fit for both D (R2 = 0.997) and D2 (R2 = 0.996) with a very close estimate by the quadratic equation for D (R2 = 0.993) and D2 (R2 = 0.996).

Fig. 2 - Relationships of stem volume to D and D2 in Dalbergia sissoo Roxb. trees.

  Enlarge/Shrink   Download   Full Width  Open in Viewer

Tab. 2 - Summarized coefficients of the relationships between individual tree volumes of Sissoo to different independent variables. H: Tree height; D0.1: stem diameter at a height of H/10; D: stem diameter at 1.3 m height (dbh). The units: D = [cm], D0.1 = [cm], H]= [m]. LIN = Linear, LOG = Logarithmic, QUA = Quadratic, CUB = Cubic, POW = Power, EXP = Exponential.

Variable Equation a b c d R2 F Sign.
D LIN -342298 30629.2 - - 0.944 474.4 < 0.01
LOG -1E+06 561873 - - 0.869 186.3 < 0.01
QUA 145717 -24827 1322.63 - 0.993 1925.9 < 0.01
CUB -203182 34316.7 -1754.7 49.327 0.997 2588.8 < 0.01
POW 15.91 3.108 - - 0.97 902.6 < 0.01
EXP 5528 0.159 - - 0.928 361.7 < 0.01
D2 LIN -75972 739.7 - - 0.983 1660.3 < 0.01
LOG -1E+06 280937 - - 0.869 186.3 < 0.01
QUA -13315 317.6 0.3825 - 0.996 3517 < 0.01
CUB -31764 487.7 0.0288 0.0002 0.996 2462.9 < 0.01
POW 15.91 1.554 - - 0.97 902.6 < 0.01
EXP 23664 0.0036 - - 0.867 182.3 < 0.01
D0.1 LIN -390344 33385.1 - - 0.925 343 < 0.01
LOG -2E+06 611406 - - 0.86 172.4 < 0.01
QUA 275457 -42005 1844.01 - 0.981 696.3 < 0.01
CUB -445256 80012.7 -4601.5 106.354 0.989 782.3 < 0.01
POW 7.04 3.385 - - 0.961 695.9 < 0.01
EXP 4172 0.1752 - - 0.928 362.9 < 0.01
D0.12 LIN -99651 828.7 - - 0.964 742.6 < 0.01
LOG -2E+06 305703 - - 0.86 172.4 < 0.01
QUA 7859 104.7 0.7173 - 0.987 1043.7 < 0.01
CUB -30223 453.3 -0.0564 0.0005 0.988 721.3 < 0.01
POW 7.04 1.693 - - 0.961 695.9 < 0.01
EXP 20529 0.0042 - - 0.881 207.6 < 0.01
D2H LIN -5209 34.9 - - 0.995 5738.1 < 0.01
LOG -1E+06 205386 - - 0.877 199 < 0.01
QUA -15721 40.2 -0.0002 - 0.997 4000.6 < 0.01
CUB -17734 41.7 -0.0004 4.90E-09 0.997 2584.4 < 0.01
POW 11 1.125 - - 0.959 656.2 < 0.01
EXP 35224 0.0002 - - 0.785 102.3 < 0.01
D0.12 H LIN -18747 39.3 - - 0.995 5791.8 < 0.01
LOG -2E+06 219854 - - 0.877 199.2 < 0.01
QUA -20488 40.2 -5.00E-05 - 0.995 2811.9 < 0.01
CUB -10661 33 0.0008 -3.00E-08 0.996 1959.7 < 0.01
POW 5.65 1.204 - - 0.959 654.2 < 0.01
EXP 32624 0.0002 - - 0.808 118.1 < 0.01

  Enlarge/Reduce  Open in Viewer

Fig. 3 illustrates the allometric relationships of stem volume to D0.1 and D0.12. As observed with the variable D, the use of D0.1 alsoshowed strong data fitting (R2 = 0.925) in the allometry (Tab. 2). This relationship is further improved (R2 = 0.964) when the D0.1 value is squared. The power equation for both the variables D0.1 and D0.12 showed the same coefficient of determination (R2 = 0.961). For both the variables D0.1 and D0.12 the polynomial cubic and quadratic equations showed a slight stronger fitting (Tab. 2) in comparison with other equations.

Fig. 3 - Relationships of stem volume to D0.1 and D0.12 in Dalbergia sissoo Roxb. trees.

  Enlarge/Shrink   Download   Full Width  Open in Viewer

As illustrated in Fig. 4, the incorporation of tree height H in the allometric equation gives a better fitting in the linear equation, specially for both D2H (R2 = 0.995) and D0.12H (R2 = 0.995). The polynomial cubic along with the quadratic equation showed a very close fit in comparison with the linear equation for both variables D2H and D0.12H (Tab. 2).

Fig. 4 - Relationships of stem volume to D2H and D0.12H in Dalbergia sissoo Roxb. trees.

  Enlarge/Shrink   Download   Full Width  Open in Viewer

  Discussion 

Although the allometric equations were highly significant (P < 0.01) there was considerable variation among them as indicated by the coefficient of determination R2 values (Tab. 2). The scatter plotting (Fig. 2) shows a non-linear trend for D as independent variable, which becomes linear when plotted against D2. This indicates that tree volume is more correlated with basal area than with simple dbh ([8]). Using the simple D as independent variable in the allometric equation, the cubic equation showed the best fit (R2 = 0.997) with a very close estimate by the quadratic equation (R2 = 0.993). However, there were low differences in the goodness-of-fit among the polynomial, power and linear equations. As the quadratic and cubic equations consist of several coefficients, for practical applications in stand volume estimation, because of simplicity, the linear or power equations the use of D2 as an independent variable should be preferred ([17]).

Like the commonly known variable D, the use of D0.1 also showed strong linear data fitting (R2 = 0.925) in the allometry (Tab. 2). This degree of linearity was further improved (R2 = 0.964) when D0.12 value is used instead of D0.1 ([14], [17]). Here, the cubic equation showed the best fit for both D0.1 (R2 = 0.989) and D0.12 (R2 = 0.988). The next strong fit is also from the quadratic equation for D0.1 (R2 = 0.981) and D0.12 (R2 = 0.987). Overall, it may be remarked that the allometric relationships of stem volume to the tree diameter at 10% of tree height (D0.1) did not improve the allometric strength in D. sissoo in comparison with simple D, as reported in case of some tree species ([14], [17]).

The multiplication of tree height H with diameter or basal area in the allometric equation gives high degree of linearity for both the variables D2 H (R2 = 0.995) and D0.12H (R2 = 0.995) in the allometric estimation. This suggests that biologically tree diameter and height change proportionality with the change of tree size ([17]). Hence, H is incorporated in the allometric equations, the polynomial cubic and quadratic equations showed a similar degree of fitting in comparison with linear equation for both the variables D2H and D0.12H, because of simplicity, the linear equation would be preferred for indirect estimation in the field with a good level of accuracy (R2 = 0.995).

For predicting timber yield ([21]) foresters often combine trunk diameter and height measurements ([21], [4]) as the independent variables in allometric relationships. However, for the D. sissoo plantations studied the stem dbh alone showed a very strong accuracy of estimation (R2 = 0.983 to 0.997) especially when used as D2. Thus, it is concluded that the use of tree height in the allometric equation ([32], [18], [28], [17]) can be neglected for D. sissoo, as far as the present study area is concerned. Therefore, for estimating the stem volume of sissoo, the use of D2 as an independent variable in the allometric equation with a linear or quadratic equation is recommended.

The findings of this study indicate that there is a variation in the use of independent variables in allometric equations for estimating the stem volume of the species. The allometric relationships described in this paper may not be appropriate in mixed or open forest stands, because the present study was carried out under monospecific and closed canopy conditions. For estimation stem volume of trees outside the size range of this investigation, care should be taken in extrapolating the present allometric relationships. Therefore, users of these allometric equations are recommended to check some individual trees outside the present size class.

  Acknowledgements 

We are grateful to Forestry and Wood Technology Discipline, Khulna University, Bangladesh for providing logistic support for the field data collection. The data analysis and manuscript preparation were performed in the Institute of Forest Growth and Forest Computer Sciences, Technische Universität Dresden, Germany, which was supported by the Alexander von Humboldt Stiftung / Foundation, Germany.

  References

(1)
Amarasinghe MD, Balasubrananiam S (1992). Net primary productivity of two mangrove forests stands on the northwest coast of Sri Lanka. Hydrobiologia 247: 37-47.
CrossRef | Gscholar
(2)
Araújo TM, Higuchi N, Andrade de Carvalho J (1999). Comparison of formulae for biomass content determination in a tropical rain forest site in the state of Pará, Brazil. Forest Ecology and Management 117: 43-52.
CrossRef | Gscholar
(3)
Attiwill PM (1962). Estimating branch dry weight and leaf area from measurement of branch girth in Eucalyptus. Forest Science 8: 132-141.
Gscholar
(4)
Avery TE, Burkhart HE (1994). Forest Measurements. McGraw- Hill, New York, pp. 408.
Gscholar
(5)
Baker TR, Phillips OL, Malhi Y, Almeida S, Arroyo L, Di Fiore A, Killeen TJ, Laurance SG, Laurance WF, Lewis SL, Lloyd J, Monteagudo A, Neill DA, Patiño S, Pitman NCA, Silva N, Martínez RV (2004). Variation in wood density determines spatial patterns in Amazonian forest biomass. Global Change Biology 10: 45-562.
CrossRef | Gscholar
(6)
Brown S (1997). Estimating biomass and biomass change of tropical forests: a primer. FAO Forestry Paper 134, Rome, Italy.
Gscholar
(7)
Brown S, Gillespie AJR, Lugo AE (1989). Biomass estimation methods for tropical forests with applications to forest inventory data. Forest Science 35: 881-902.
Gscholar
(8)
Burrows WH, Hoffmann MB, Compton JF, Back PV, Tait LJ (2000). Allometric relationships and community biomass estimates for some dominant eucalypts in Central Queensland woodlands. Australian Journal of Botany 48: 707-714.
CrossRef | Gscholar
(9)
Chambers JQ, dos Santos J, Ribeiro RJ, Higuchi N (2001). Tree damage, allometric relationships, and above-ground net primary production in central Amazon forest. Forest Ecology and Management 152: 73-84.
CrossRef | Gscholar
(10)
Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Fölster H, Fromard F, Higuchi N, Kira T, Lescure JP, Nelson BW, Ogawa H, Puig H, Riéra B, Yamakura T (2005). Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145: 87-99.
CrossRef | Gscholar
(11)
Clough BF, Dixon P, Dalhaus O (1997). Allometric relationships for estimating biomass in multistemed mangrove trees. Australian Journal of Botany 45: 1023-1031.
CrossRef | Gscholar
(12)
Clough BF, Scott K (1989). Allometric relationships for estimating above ground biomass in six mangrove species. Forest Ecology and Management 27: 117-127.
CrossRef | Gscholar
(13)
French JH, Blicher-Mathiesen U (1995). Introduction to the field sites. In: “International workshop on agroforestry investment, production and marketing”. Dehra Dun (India), 17-26 Sept. 1995. APAN Report no. 20, FAO/APAN.
Gscholar
(14)
Hagihara A, Yoyota T, Ogawa K (1993). Allometric relations in hinoki (Chamaecyparis obtusa (Sieb. et Zucc.) Endl.) trees. Bulletin of Nagoya University Forestry 12: 11-29.
Gscholar
(15)
Joshi KD (1945). Unirrigated canal plantation in the United Provinces. Indian Journal of Forestry 71: 331-335.
Gscholar
(16)
Ketterings MQ, Coe R, Noordwijk MV, Amagau Y, Palm AC (2001). Reducing uncertainty in the use of allometric biomass equations for predicting above ground tree biomass in mixed secondary forest. Forest Ecology and Management 146: 199-209.
CrossRef | Gscholar
(17)
Khan MNI, Suwa R, Hagihara A (2005). Allometric relationships for estimating the aboveground phytomass and leaf area of mangrove Kandelia candal (L.) Druce trees in the Manko Wetland, Okinawa Island, Japan. Trees 19: 266-272.
CrossRef | Gscholar
(18)
Kusmana C, Sabiham S, Abe K, Watanable H (1992). An estimation of above ground tree biomass of the mangrove forest in East Sumatra, Indonesia. Tropics 1: 243-257.
CrossRef | Gscholar
(19)
Kvålseth TO (1985). Cautionary note about R 2. American Statistics 39: 279-285.
CrossRef | Gscholar
(20)
Lodhiyal N, Lodhiyal SL (2003). Biomass and net primary productivity of Bhabar Shisham forests in central Himalaya, India. Forest Ecology and Management 176: 217-235.
CrossRef | Gscholar
(21)
Madgwick HAI, Frederick DJ, Tew DT (1991). Biomass relationships in stands of Eucalyptus species. Bioresource Technology 37: 85-91.
CrossRef | Gscholar
(22)
Malhi Y, Wood D, Baker TR, Wright J, Phillips OL, Cochrane T, Meir P, Chave J, Almeida S, Arroyo L, Higuchi N, Killeen T, Laurance SG, Laurance WF, Lewis SL, Monteagudo A, Neill DA, Vargas PN, Pitman NCA, Quesada CA, Salomão R, Silva JNM, Lezama AT, Terborgh J, Martínez RV, Vinceti B (2006). The regional variation of aboveground live biomass in old-growth Amazonian forests. Global Change Biology 12: 1107-1138.
CrossRef | Gscholar
(23)
Nakasuga T (1979). Analysis of mangrove stands. Japanese Journal of Ecology 24: 237-246 (in Japanese with English summary).
Gscholar
(24)
Nogueira EM, Fearnside PM, Nelson BW, Barbosa RI, Keizer EWH (2008). Estimates of forest biomass in the Brazilian Amazon: new allometric equations and adjustments to biomass from wood-volume inventories. Forest Ecology and Management 256: 1853-1867.
CrossRef | Gscholar
(25)
Ogawa H, Kira T (1977). Methods of estimating forest biomass. In: “Primary productivity of Japanese forests” (Shidei T, Kira T eds). Productivity of terrestrial communites, University of Tokyo Press, Tokyo, pp. 15-36.
Gscholar
(26)
Ong JE, Gong WK, Wong CH (2004). Allometry and partitioning of the mangrove, Rhizophora apiculata. Forest Ecology and Management 188: 395-408.
CrossRef | Gscholar
(27)
Overman JPM, Witte HJL, Saldarriaga JG (1994). Evaluation of regression models for above-ground biomass determination in Amazon rainforest. Journal of Tropical Ecology 10: 207-218.
CrossRef | Gscholar
(28)
Poungparn S, Komiyama A, Patanaponpaipoon P, Jintana V, Sangatiean T, Tanapermpool P, Piriyayota S, Maknual C, Kato S (2002). Site independent allometric relationships for estimating above-ground weights of mangroves. Tropics 12: 147-158.
CrossRef | Gscholar
(29)
Putz FE, Chan HT (1986). Tree growth, dynamic, and productivity in a mature mangrove forest in Malaysia. Forest Ecology and Management 17: 211-230.
CrossRef | Gscholar
(30)
Shinozaki K, Yoda K, Hozumi K, Khira T (1964). A quantitative analysis of plant form-the species model theory. II. Further evidence of the theory and its application in forest ecology. Japanese Journal of Ecology 14: 133-139.
Gscholar
(31)
Singh B (1963). First irrigated plantation of Rajasthan. Indian Journal of Forestry 89: 690-700.
Gscholar
(32)
Suzuki E, Tagawa H (1983). Biomass of mangrove forest and a sedge marsh on Ishigaki island, south Japan. Japanese Journal of Ecology 33: 231-234.
Gscholar
(33)
Tamai S, Nakasuga T, Tabuchi R, Ogino K (1986). Standing biomass of mangrove forests in southern Thailand. Journal of Japanese Forestry Society 68: 384-388.
Gscholar
(34)
Tewari DN (1994). A monograph on Dalbergia sissoo Roxb. Indian Council on Forestry Resource and Education, International Books Distributors, Deharadun, India.
Gscholar
(35)
Troup RS (1921). The silviculture of Indian trees 1. Oxford University Press, Oxford, United Kingdom.
Gscholar

Authors’ Affiliation

(1)
NI Khan
Department Forest Biometry and Systems Analysis, Institute of Forest Growth and Forest Computer Sciences, TU Dresden, P.O. Box 1117, D-01735 Tharandt (Germany)
(2)
NI Khan
O Faruque
Forestry and Wood Technology Discipline, Khulna University, 9208 Khulna (Bangladesh)

Corresponding author

Citation

Khan NI, Faruque O (2010). Allometric relationships for predicting the stem volume in a Dalbergia sissoo Roxb. plantation in Bangladesh. iForest 3: 153-158. - doi: 10.3832/ifor0554-003

Paper history

Received: Mar 04, 2010
Accepted: Oct 01, 2010

First online: Nov 15, 2010
Publication Date: Nov 15, 2010
Publication Time: 1.50 months

© SISEF - The Italian Society of Silviculture and Forest Ecology 2010

  Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Creative Commons Licence

Breakdown by View Type

(Waiting for server response...)

Article Usage

Total Article Views: 29862
(from publication date up to now)

Breakdown by View Type
HTML Page Views: 22588
Abstract Page Views: 1417
PDF Downloads: 4636
Citation/Reference Downloads: 32
XML Downloads: 1189

Web Metrics
Days since publication: 5113
Overall contacts: 29862
Avg. contacts per week: 40.88

Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Nov 2020)

Total number of cites (since 2010): 9
Average cites per year: 0.82

 
 

Publication Metrics

by Dimensions ©

List of the papers citing this article based on CrossRef Cited-by.

 

iForest Similar Articles

iForest Database Search

Google Scholar Search

PubMed Search

 

This website uses cookies to ensure you get the best experience on our website. More info