FINAL PROGRESS REPORT OF THE PROJECT PRODUCTIVITY …€¦ · FINAL PROGRESS REPORT OF THE PROJECT...

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FINAL PROGRESS REPORT OF THE PROJECT

PRODUCTIVITY AND BIOMETRICS STUDIES ON SOME

IMPORTANT SPECIES IN ARID & SEMI-ARID REGIONS

OF RAJASTHAN FOR THEIR SUSTAINABLE

MANAGEMENT

(2008-09- 2013-14)

Submitted to

STATE FOREST DEPARTMENT

RAJASTHAN

by

Dr. Sunil Kumar Principal Investigator & Scientist-E

Arid Forest Research Institute Indian Council of Forestry Research & Education

(An Autonomous Council of Ministry of Environment and Forests, GOI)

New Pali Road, Jodhpur – 342005

PHONE: 91-291-2729145: Fax: 91-291-2722764

Email: [email protected]

2014

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Final Progress Report

1. Title: Productivity and biometrics studies on some important species in arid &

semi-arid regions of Rajasthan for their sustainable management

2. Project Number: AFRI-95/Silvi./SFD/2009-2012

3. a Name of the Principal Investigator:

Dr. Sunil Kumar, Scientist-E

3. b Name of Associate :

(i) Dr. Bilas Singh, R.O.

(ii) Sh. J. P. Dadhich, RA-II

3. c Duration: Six years

4. Year of Start: 2008-09

5. Date of completion: 2013-14

6. Name and Address of Contact person to whom correspondence is to be made,

along with telephone number (with STD code), Fax No/E-mail Address:

Director, Arid Forest Research Institute, PO: Krishi Upaj Mandi, New Pali Road,

Jodhpur. (Rajasthan) - 342005.

Telephone No. 0291-2722549(O), Fax No.: 021-2722764, Telegraphic address:

‘Vaniki Jodhpur’ and E-mail: [email protected]

7. Area of Activity:

Forest Management and volume tables of Ailenthus excelsa and Prosopis cineraria for

arid and semi-arid regions of Rajasthan.

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8. Total Amount of Sanction along with period (Years):

The total budget sanctioned for this project was Rs 5.47 Lakhs with period from

January 2009 to March 2012 as per project document and up to March 2014 for the

extension of the project period.

9. Amount of Ist Installation & date received:

For the year 2009-10 -Rs. 1.90 Lakhs

(Received on dated 19-12-2008).

10. Amount of IInd Installation & date received:

0.92 Lakhs Received on dated 22-03-2011).

11. Amount of IIIrd and forth Installation:

0.81 Lakhs on dated 20-11-12 for year 2012-13

0.81 Lakhs received for 2013-14 (Total amount Released 4.44 lakhs)

12. Financial Achievements: Please see on next page.

13. Objectives of the study:

Short Term objectives:

(i) Construction of tree volume equations for the species Prosopis cineraria (Khejri)

and Ailanthus excelsa (Ardu)

(ii) For extended period:

To estimate average yearly foliage production of Prosopis cineraria on the

farmers’ field.

Long Term objective of the Project:

(iii) To develop growth & yield functions for sustainable management of plantations

of selected species in semi-arid areas of Rajasthan.

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Financial Achievements:

14. Details of the work done:

14.1 Introduction

The forests of India are under immense pressure and their management is

becoming increasingly complex. Rapidly growing population, dwindling forest resources,

and environment degradation have posed a perplexing problem. The Indian arid land

suffers from low productivity, slow growth rate of tree species, less precipitation, but it

has to support a large density of cattle and human population. The lives of the large

chunk of people residing in the vicinity of forests depending wholly or partially on it are

uncertain. For conceptualization, forest management essentially needs accurate

predictions of output of socio-economic benefits in terms of yield for all relevant

combination of measurable forest characterizes viz. age, site, density and growth. These

estimates are crucial for intelligent management decisions on optimum rotation, planting

density, thinning schedule and treatment regime. Too much removal from forest may lead

to liquidation of growing stock and too little would be inefficient use because available

growth potential is not fully harnessed and society would be deprived of immediate

SN Activities 2008-

2009

2009-10 2010-11 2011-12 2012-13 2013-14 Total

1 Field Assistant -1 14032 60000 36333 - - - 110365

2 Wages 0 0 2718 6472 - 19901 29091

3 Material &

Supplies

0 0 0 0 4480 0 4480

4 Travel Expenses

(POL+ TA/DA)

12467 15056 12876 29182 46431 42474 158486

5 O.E. 10593 0 90 0 2500 18380 31563

6 Others 0 0 1250 1390 - - 2640

Sub Total 37092 75056 53,267 37044 53411 80755 336625

7 Intuitional charges 25000 0 0 0 0 82375 107375

Grand Total 62092 75056 53267 37044 53411 163130 444000

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benefits. Also, such information is required for silvicultural and environment

management.

Heights and diameters of growing stock are two most important elements of any

forest stand. Observations on height and diameter of plantations is an indispensable

element of any individual tree based volume functions and its projection. Estimation of

stand volume with greater accuracy has always been a matter of interest for forest manger

as it is directly related with the production estimates.

Unfortunately, information on the volume and yield of Ailanthus excelsa and

Prosopis cineraria are meager raised in semi-arid area of Rajasthan is. The forest

managers are very much interested in proper management of its productive resources.

Elaborate systematic and scientific studies on the volume and yields aspects of Ailanthus

excelsa and Prosopis cineraria are still lacking. It is in this context the present study was

taken.

Considering the importance of total volume and merchantable volume functions,

this project was taken up with the short term objectives: construction of tree volume

equations for the species Prosopis cineraria (Khejri), and Ailanthus excelsa (Ardu) and

long term objective was to develop growth and yield functions for sustainable

management of plantations of selected species in semi arid areas of Rajasthan.

The data required for conducting this study were collected from the plantations

raised by State Forest Department, Rajasthan. Survey of the plantation areas of Prosopis

cineraria and Ailanthus excelsa was carried out in IGNP (Indira Gandhi Nahar

Pariyojana) areas with the aim to laying out permanent sample plots and felling of trees

of representative DBH classes from the surrounding. Required observations were

collected from the fourteen permanent sample plots distributed over in study area for the

year 2011-12 to 2013-14. Eight numbers of models were used for deriving the total

volume, merchantable volume over bark and under bark for both of species viz. Prosopis

cineraria and Ailanthus excelsa. Our goal was to estimate the total volume of wood over

bark and under bark up to 5 cm diameter and merchantable wood up to 10 cm diameter

on the basis of single tree. Thus, it will comprise a total of sixty four equations, 8 each in

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four cases. The results obtained are discussed as follows. The best volume equations out

of set of eight equations were screened for Prosopis cineraria and Ailanthus excels on the

basis of coefficient of correlation (R2) and standard error (SE).

14.1 Technical details of the study:

14.2 Study Area:

The data required for conducting this study were collected from the plantations

raised by State Forest Department, Rajasthan. Survey of the plantation areas of Prosopis

cineraria and Ailanthus excelsa plantations was carried out in IGNP areas with the aim to

laying out permanent sample plots, recording of standard observations and felling of trees

of representative DBH classes from the surrounding. Eight plantations for Prosopis

cineraria (03 RD, 08 RD, 1447 RD , 1340 RD, 1387 RD, 1355 RD, 740 RD, 704 RD )

and 6 for Ailanthus excelsa (19 KJD ,CSP-KCSP-KJD 0-17 RD, 802 RD, 9MD,0-2 RD)

were selected in IGNP areas.

14.3 Laying out of Permanent sample plots:

Sample plots were laid out at various locations at IGNP areas in Rajasthan. Eight

sample plots of Prosopis cineraria and six sample plots of A. excelsa were laid down at

various locations in IGNP area. Total number of fourteen sample plots was laid down at

represented sites of IGNP as shown in Table 2 and Table 4.

14.4 Collection of Field Observations:

Required observations were collected from the fourteen permanent sample plots

distributed over Bikaner, Jaisalmer, Ganganagar and Pali Divisions of study area in the

year 2011-12 to 2013-14. For identification of the permanent sample plots for recording

observations in the subsequent years, the sample plots were demarcated with rigs of red

paint. The trees lying within the selected area were numbered and marked plus with black

paints at 1.37 meter height (DBH). L-shaped trench were dug in corners of each

permanent sample plots. The standard observations such as DBH over bark and total

heights of all trees lying inside of sample plots were recorded for Ailanthus excelsa and

Prosopis cineraria from 2011-12 to 2013-14. Trees from the surrounding of sample plots

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were felled. A site map of the sample plot was drawn for future use and deriving of its

exact area.

After felling of trees, its total height was measured with the help of tape and

marked at each section of 3 m log and its mid points with chalk and over and under bark

observations of DBH were taken. Total volume is considered as the volume of main trunk

and volume of branches up to last tip at 5 cm. Hubers’ formula was applied to estimate

the total volume of individual tree. The observation of the felled trees such as crown

diameter, height at first branching, merchantable height etc. were also recorded.

Table 2: Summarized Field observations for P. cineraria

S.

No Locations

No. of

Trees in

sample

plot

2010-11 2011-12 2012-13 2013-14

Dbh

(cm)

Height

(m)

Dbh

(cm)

Heig

ht

(m)

Dbh

(cm)

Height

(m)

Dbh

(cm)

Height

(m)

1 03 RD, IGNP

area 45 14.19 7.05 14.35 7.35 14.82 7.77 15.4 8.18

2 08 RD, IGNP

area 40 13.82 7.75 14.18 8.08 14.69 8.55 15.21 8.68

3 1447 RD,

IGNP area 41 9.30 5.61 10.3 6.08 10.69 6.58 11.18 6.78

4 1340 RD,

IGNP area 55 16.56 9.43 17.07 11.1 17.38 11.8 17.58 12.2

5 1387 RD,

IGNP area 38 15.87 11.70 16.31 12.11 17.13 12.93 17.45 13.28

6 1355 RD,

IGNP area 50 16.78 8.52 17.31 8.98 18.19 9.42 18.51 9.73

7 740 RD, IGNP

area 34 - - 12.22 7.03 13.40 7.69 15.66 9.04

8 704 RD, IGNP

area 17 - - 16.66 7.62 17.96 8.14 18.53 8.70

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Table 3: Summarized table of attributes of Prosopis cineraria for year 2011-12 to

2013-14

Plot

Location

Avg.

DBH

Max

(DBH)

Min

(DBH)

Avg.

DBH

Max

(DBH)

Min

(DBH)

Avg.

DBH

Max

(DBH)

Min

(DBH)

2011-12 2011-12 2011-12 2012-13 2012-13 2012-13 2013-14 2013-14 2013-14

704 RD 16.7 24.9 4.3 18.0 25.4 8.7 18.5 25.6 9.0

740 RD 12.2 22.1 4.7 13.4 23.4 8.4 15.7 24.5 9.6

1335

RD 17.3 29.4 5.75 18.2 29.5 6.1 18.6 29.9 6.5

1340 Rd 17.1 35.1 6.2 17.4 35.4 6.3 17.6 36.6 6.3

03 RD 14.4 24.4 4.7 14.8 24.9 4.8 15.4 25.1 8.1

08 RD 14.2 21.2 6.2 14.7 22.6 6.5 15.2 22.8 6.6

1447

RD 10.4 17.2 3.15 14.6 17.6 3.3 11.2 18.2 3.5

1387

RD 16.2 27.9 4.7 15.6 28.2 7.75 17.5 29.2 8.0

Table 4: Summarized Field observations for A. excelsa

S. N. Location

2011-12 2012-13 2013-14

No. of

Trees in

sample

plot

Dbh (cm) Height

(m) Dbh (cm)

Height

(m) Dbh (cm)

Height

(m)

1 19 KJD 63 13.33 9.08 14.55 11.42 15.82 12.92

2

CSP-

KJD,0-

17RD

26 22.93 8.18 24.70 12.44 26.55 13.76

3 802RD 41 17.85 11.20 18.94 11.88 19.98 12.78

4 9MD 34 16.84 8.77 17.60 8.79 18.01 9.74

5 0-2RD 30 25.78 12.58 26.54 15.48 27.37 16.12

6 Dadia

(Sojat) 61 13.25 5.60 - - - -

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Table 5: Summarized table of attributes of A. excelsa for year 2011-12 to 2013-14

14.5 Volume per hectare:

14.5.1: Prosopis cineraria:

Volume of Prosopis cineraria was measured from the direct measurement of the trees by

felling. The volume per hectare can be measured by the formula

𝑉 = 𝑣𝑖𝑗

𝑛𝑎

Where

V= average volume per hectare, m3

per hectare, estimated from n samples each of a

hectares

𝑣𝑖𝑗 = Volume of i-th individual tree measured on j-th plot after felling

i= 1, 2, 3-------n

Plot

location

DBH

(Av.)

Maximum

(DBH)

Minimum

(DBH)

DBH

(Av.)

Maximum

(DBH)

Minimum

(DBH)

DBH

(Av.)

Maximum

(DBH)

Minimu

m (DBH)

Year

2011-12 2011-12 2011-12 2012-13 2012-13 2012-13 2013-14 2013-14 2013-14

19 KBD 13.3 26.2 4.6 14.55 27.65 6.60 15.82 29.0 8.55

9 MD 16.9 28.7 11.2 17.6 29.9 11.6 18.01 30.2 11.8

0-2 RD

Rawala 25.8 38.6 13.9 26.5 39.0 14.2 27.37 40.1 14.05

CSP-KJD

0-17 RD

(61 rd )

22.9 29.9 7.4 24.7 32.35 7.7 26.55 39.6 8.05

802 RD,

Mohangarh 17.9 36.6 9.5 18.9 37.5 10.1 19.98 38.6 10.25

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j = 1, 2, 3 ----- m

m i = total number of trees in the ith plot

n= number of plots

The table no. 6 shows the total volume of felled trees of Prosopis cineraria from the

various locations of IGNP area. The maximum volume was observed at 1387 RD and 03

RD and minimum volume was at 1447 RD.

Table 6: Volume of Khejri (Prosopis cineraria) felled trees in various locations of IGNP

areas.

14.5.2 : Ailanthus excelsa:

The table no 7 shows the volume of felled trees of Ardu (Ailanthus excelsa) from

the various locations of IGNP area. The maximum volume was observed at 02 RD and

minimum volume was at 19 KJD.

Locations Tree1 Tree2 Tree3 Tree4 Tree5

Average

Volume

(m3/tree)

Area of

plot

(ha)

704 RD 0.196325 0.02464 0.054987 0.041562 0.102991 0.084101 0.039694

740 RD 0.06117 0.07704 0.04668 0.027893 0.192627 0.081082 0.040114

1387 RD 0.058365 0.039039 0.321539 0.047054 0.111351 0.11547 0.027891

1340 RD 0.434918 0.037191 0.037191 - - 0.169767 0.060695

03 RD 0.074797 0.133821 0.133821 0.068196 0.154275 0.112982 0.045655

1447 RD 0.035455 0.075577 0.009401 0.015839 0.047673 0.036789 0.055201

1335 RD 0.05819 0.035164 0.047673 0.052256 - 0.048321 0.054648

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Table 7: Volume of single felled trees of Ardu (Ailanthus excelsa) in various locations of

IGNP areas and per hectare volume

Locations tree 1 tree 2 tree 3 tree 4 tree 5 Average

Volume

(m3/tree)

Area of

plot (ha)

19 KJD 0.0560 0.0319 0.1021 0.0099 0.0610 0.05218 0.05037

CSP-KJD,

0-17 RD

0.2653 0.1362 0.0797 0.0000 0.0000

0.1604 0.03612

802 RD 0.0488 0.1118 0.1387 0.0864 0.0345 0.08404 0.03640

9 MD 0.0799 0.0473 0.0418 0.1407 - 0.07743 0.03215

02 RD 0.1469 0.0994 0.4321 0.1918 - 0.21755 0.02997

14.6 Basal area per hectare:

The cross sectional area of a tree estimated at breast height is called the tree basal

area and is denoted by g. It is normally expressed in sq meter and usually measured

overbark. The sum of basal areas of all trees standing on a piece of land is denoted by G

m 2

per ha. It ranges from 12.38 to 49.11 m 2

per ha. The basal area of a plot can be

estimated by the following formula.

𝐺 = 𝑔 𝑖𝑗 𝑚𝑖

𝑗𝑛𝑖

𝑎

Unit is sq. meter per hectare.

Where,

G= Average basal area per hectare

g ij = basal area in j th diameter class of I th plot

m i = Number of diameter class in ith plot

n= number of plots in stand or no of plantation in region

a = Area of sample plot

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14.6.1 Prosopis cineraria:

The table no 8 shows the Basal area of Prosopis cinerarias of permanent sample

plots located in various locations of IGNP area. The maximum basal area was observed at

1340 RD and minimum basal area was at 1447 RD. The overall basal area of sum of all

plots were 18.079 sq. meters per hectare in the case of Prosopis cineraria.

Table 8: Basal area of Prosopis cinerarias in different years.

Locations

Site wise Basal Area trend Average

BA (m2

per plot)

Area of

plot (ha) 2011-12 2012-13 2013-14

704RD 0.41052 0.434248 0.465501 0.43676 0.039694

740RD 0.414502 0.450714 0.833453 0.56622 0.040114

1322RD 0.497183 0.519542 0.552243 0.52299 0.027891

1335RD 1.261876 1.292455 1.334492 1.29627 0.060695

1340RD 1.391359 1.444777 1.47171 1.43595 0.045655

03RD 0.78157 0.817608 0.853651 0.81761 0.055201

08RD 0.676022 0.730959 0.781244 0.72941 0.054648

1447RD 0.367335 0.387637 0.423498 0.39282 0.029669

1387RD 0.881792 0.921548 0.95547 0.9196 0.040114

BA (m3/ha ) 16.97354 17.77959 19.48598 18.0798

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Table 9 shows the trend of Basal area per ha. of Ardu (Ailanthus excelsa) over in various

locations of IGNP areas

Table 9: Basal area (m2

per plot) of Ailanthus excelsa in various locations of IGNP areas.

14.7 Modeling Strategies:

Tree crops being a very long gestation period to mature, methods for its yield

predictions are required at early stage. Volume equations or functions play an important

role in forest management. Usually estimates of volume per hectare is based on the

volume of single tree, so an accurate estimate of its required for this purpose. The

estimate of merchantable wood volume is crucial for economical point of view. The

objective of this study is to develop volume functions of total volume as well as to the

merchantable volume for both of the species viz. Prosopis cinerarias and Ailanthus

excels. The tree volume models are mainly classified into linear and nonlinear models.

Linear models are based on linear regression techniques, which describe the change in

size of volume in response variable with respect to change in the set of explanatory

variables. In our case the response variable was trees volume and explanatory variables

were diameter at breast height, total height or combination of both D and H i.e D2H. The

Locations

Site wise basal area (m3) trend Area of

plot (ha)

2011-12 2012-13 2013-14

Average

BA (m2

per plot)

19 KJD 0.91295 1.087421 1.171674 1.05735 0.05037

CSP-KJD, 0-17 RD 0.790636 0.862571 0.901078 0.85143 0.03612

802 RD 1.594317 1.681684 1.787309 1.68777 0.03640

9 MD 1.025184 1.195181 1.425398 1.21525 0.03215

0-2 RD 1.128799 1.199693 1.302456 1.21032 0.02997

BA (m2/ha) 29.4679 32.574 35.6082 32.55

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use of linear equations is very much common in forestry and the following models were

used by various workers i.e. Spurr (1952), Loetsch et al. (1973) and Clutter et al. (1983).

Some of the standard volume equations used in present study is mentioned below:

Table 9: The Equations for the volume tested in the study:

Equation Type Modal No

V= a+bD2H (Combined variable) 1

V= a+bD2 2

V= a+b D + c D2

3

V= a+b D + c D2 + d D

2H 4

V= a+ b D 5

Log D = a + b log D 6

Log V = a + b log D+ c D2H 7

Log V = a+ b DH + c D2 H 8

(Where a, b, c and are parameters in above equations D is the DBH and H is the height)

Eight numbers of models, as described above were used for deriving the total


cineraria and Ailanthus excelsa. Out of eight equations four (2, 3, 5 and 6) are based on

only DBH only, others are based on either DBH (denoted by D) and total height (denoted

by D) or combination of D & H i.e. D2H. Our goal is to estimate the total volume of

wood over bark and under bark and merchantable wood up to 10 com diameter on the

basis of single tree. Thus merits of set of eight equations in each of four cases are

discussed below, thus comprising a total of sixty four equations. The statistical analysis

was done with the help of Microsoft office excel 1997 and IBM SPSS Statistics 20.

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14.7.1: Total Volume of Ailanthus excelsa over Bark:

Height of felled trees of Ailanthus excelsa ranged between 9.74 m to 16.12 m and DBH

ranged between 11 cm to 18 cm which were used for volume validation of Ailanthus

excelsa trees in arid region of Rajasthan. The above mentioned models were used to

predict total volume over bark. Regression statistics such as multiple R, R2,

adjusted R2

and standard error were calculated. Analysis of variance was carried out to know the

contribution due to regression and to know the value of F and its significance. All sets of

equations have given creditable level of coefficient of determination about more than 80

% and low value of Root Mean Square Error. Regression parameters was estimated and

shown in table 10 along with standard error. Model no 7 gave highest R2 (0.9430), Adj.

R2

(0.9360) with RMSE 0.3818.

14.7.2: Total Volume of Ailanthus excelsa under Bark:

The set of all equations were used to predict the total volume of Ailanthus excelsa

under Bark. The observations of predicator variables of volume equations under bark

were regressed with the explanatory variables such as either combination of D &H i.e.

D2H or DH. Regression parameters was estimated and shown in table 11. Different

models have different values of RMSE, but are and high R2

values. Model no. 4 gave

highest R2 (0.8485), Adj. R

2 (0.8218) with RMSE 0.1353.

14.7.3: Merchantable Volume of Ailanthus excelsa over Bark:

The set of all equations was utililized to observe the relationship among the

merchantable volume of wood over bark with the merchantable height up to 10 cm.

diameters and DBH over bark of Ailanthus excelsa or their combinations. The results

were shown in table no.12. Model no. 4 gave highest R2 (0.9726), Adj. R

2 (0.9677) with

RMSE 0.0552.

14.7.4: Merchantable Volume of Ailanthus excelsa under Bark:

The set of all equations was utilized to observe the relationship between the

merchantable volume of wood under bark with the merchantable height up to 10 cm.

diameters and DBH under bark of Ailanthus excelsa or their combinations. The results

16

were shown in table no. 13. Model no. 4 gave highest R2 (0.9597), Adj. R

2 (0.9526) with

RMSE 0.0533.

14.7.5: Total Volume of Prosopis cineraria overBark:

Height of felled trees of Prosopis cineraria ranged between 6.0 m to 13.28 m and DBH

ranged between 11 cm to 18 cm which were used for volume validation of Prosopis

cineraria trees in dry region of Rajasthan.

The set of all equations were used to predict the total volume of Prosopis cineraria over

Bark. The observations of predicator variables of volume equations under bark were

regressed with the explanatory variables such as either combination of D & H i.e. D2H or

DH. Regression parameters was estimated and shown in table 9. Different models have

different values of RMSE, but are and high R2

values. Model no. 14 gave highest R2

(0.8578), Adj. R2

(0.8425) with RMSE 0.1899.

14.7.6: Total Volume of Prosopis cineraria under Bark:

The set of all equations were used to predict the total volume of Prosopis

cineraria under Bark. The observations of predicator variables of volume equations under

bark were regressed with the explanatory variables such as either combination of D & H

i.e. D2H or DH. Regression parameters was estimated and shown in table 15. Different

models have different values of RMSE, but are and high R2 values. Model no. 4 gave

highest R2 (0.7356), Adj. R

2 (0.7073) with RMSE 0.2417.

14.7.7: Merchantable Volume of Prosopis cineraria over Bark:



diameters and DBH overbark of Prosopis cineraria or their combinations. The results

were shown in table no. 16. Model no 4 gave highest R2 as 0.96 followed by model 1.

Model no. 4 gave highest R2 (0.9368), Adj. R

2 (0.9300) with RMSE 0.06083.

17

14.7.8: Merchantable Volume of Prosopis cineraria under Bark:



diameter and DBH underbark of Prosopis cineraria or their combinations. The results

were shown in table no. 17. Model no 4 gave highest R2 as 0.96 followed by model 1.

Model no. 4 gave highest R2 (0.9170), Adj. R

2 (0.90815) with RMSE 0.04572.

Table 10 : Total Volume Over Bark of Ailanthus excelsa

Model

No.

a b c d R2 Adj. R

2 RMSE

1 0.033992712

(0.0103322)

3.08152E-05

(2.743e-06)

0.8691 0.8622 0.1535

2 -0.018479571

(0.0164005)

0.000467742

(4.954e-05)

0.8243 0.8150 0.1779

3 0.0331535094

(0.0729982)

-0.006202032

(0.0085384)

0.000636759

(0.000238)

0.8293 0.8103 0.1754

4 -0.092591517

(0.0710822)

0.0152252

(0.0096298)

-0.000443478

(0.0003884)

3.39036E-

05

(1.057e-05)

0.8936 0.8749 0.1384

5 -0.144870884

(0.0345191)

0.016125987

(0.0020705)

0.7614 0.7489 0.2073

6 -3.833635549

(0.2144377)

2.333656885

(0.1805431)

0.8978 0.8925 0.5114

7 -3.711549041

(0.1676204)

1.61864646222

(0.2343982)

0.841367416

(0.2225376)

0.9430 0.9367 0.3818

8 -1.773869953

(0.1183574)

0.008876415

(0.0020691)

-0.000191979

(6.791e-05)

0.7834 0.7593 0.7448

18

Table 11 : Total Volume Under Bark of Ailanthus excelsa

Model

No.

a b c d R2 Adj. R

2 RMSE

1 0.019272

(0.009391)

3.25E-05

(3.34E-06)

0.833454 0824688 0.141931

2 -0.02332

(0.013555)

0.000511

(5.62E-05)

0.813042 0.803202 0.150377

3 0.034055

(0.05637)

-0.00807

(0.007693)

0.000766

(0.00025)

0.823802 0.804225 0.145985

4 -0.03868

(0.069266)

0.0069843

(0.011619)

-0.00014

(0.000595)

2.86E-05

(1.72E-05)

0.848537 0.821809 0.135351

5 -0.12153

(0.029273)

0.014888

(0.002066)

0.732063 0.717961 0.180022

6 -3.84952

(0.316895)

2.334388

(0.283994)

0.780514 0.768962 0.824348

7 -3.74505

(0.276485)

1.330437

(0.44221)

1.174102

(0.430223)

0.844751 0.827501 0.693302

8 -1.99638

(0.134933)

0.010819

(0.002718)

-0.00027

(0.000103)

0.75977 0.733078 0.862423

Values in parentheses are standard error in all such tables.

19

Table 12: Merchantable Volume Over Bark of Ailanthus excelsa

Model

No.

a b c d R2 Adj. R

2 RMSE

1 0.024816

(0.004079)

2.82E-05

(1.3e-06)

0.96144 0.95941 0.065427

2 -0.0257

(0.01198)

0.000372

(3.62e-05)

0.84774 0.83972 0.130013

3 0.088161

(0.046552)

-0.01368

(0.005445)

0.000745

(0.000152)

0.88727 0.87473 0.111876

4 -0.03452

(0.029033)

0.006587

(0.003925)

-0.00016

(0.000146)

2.78E-

05

(3.83e-

06)

0.97257 0.96773 0.055182

5 -0.12009

(0.028471)

0.012443

(0.001708)

0.73643 0.72256 0.171056

6 -4.02582

(0.362532)

2.345044

(0.30523)

0.75649 0.74367 0.172626

7 (-3.33007)

(0.304472)

1.134795

(0.352821)

1.073767

(0.245795)

0.88180 0.86867 0.602357

8 -1.92112

(0.118291)

0.013343

(0.003032)

-0.00033

(0.0001)

0.75813 0.73126 0.861673

20

Table 13: Merchantable Volume Under Bark of Ailanthus excelsa

Model

No.

a b c d R2 Adj. R

2 RMSE

1 0.015518

(0.003736)

2.93E-05

(1.57E-06)

0.94798 0.94798

0.06060

2 -0.02578

(0.007988)

0.000408

(3.31E-05)

0.88880 0.88295 0.08861

3 0.065633

(0.026041)

-0.01285

(0.003554)

0.00081

(0.00011

6)

0.93559 0.92843 0.06744

4 0.001581

(0.029154)

6.95E-06

(0.004953)

0.00012

(0.00023

6)

2.13E-

05

(6.66E-

06)

0.95977 0.95267 0.05329

5 -0.09991

(0.021271)

0.011573

(0.001501)

0.75768 0.74493 0.13080

6 -4.07379

(0.3506)

2.393157

(0.314199)

0.75329 0.74030 0.91202

7 -3.53665

(0.362247)

1.34715

(0.472668)

0.91593

(0.33743

6)

0.82494 0.80549 0.76824

8 -2.07399

(0.131745)

0.014807

(0.003893)

-0.00041

(0.00014

8)

0.72398 0.69331 0.96467

21

Table 14 : Total Volume Over Bark of Prosopis cineraria

Model

No.

a b c d R2 Adj. R

2 RMSE

1 -0.00327

(0.013708)

5.7E-05

(6.55e-06)

0.71621 0.71675 0.26821

2 -0.02035

(0.020092)

0.000536

(8.36e-05)

0.57791 0.56384 0.32710

3 0.199834

(0.11478)

-0.03189

(0.016387)

0.001589

(0.001589)

0.62665 0.60091 0.30764

4 0.104971

(0.073449)

-0.00544

(0.01101013)

-0.00117

(0.000534)

0.0001

83

(2.71e-

05)

0.85780 0.84256 0.18986

5 -0.11826

(0.038231)

0.015182

(0.002673)

0.51813 0.50207 0.34950

6 -3.38291

(0.357211)

1.958132

(0.318043)

0.55821 0.54348 1.31136

7 -3.49971

(0.321623)

0.586715

(0.547585)

1.965508

(0.670864)

0.65911 0.63560 1.15192

8 -1.90907

(0.16894)

0.009849

(0.004114)

-0.00019

(0.000166)

0.66485 0.64173 1.14218

22

Table 15 : Total Volume Under Bark of Prosopis cineraria

Model

No.

a b c d R2 Adj. R

2 RMSE

1 -0.0092

(0.015446)

6.73E-05

(1.08e-05)

0.56551 0.55103 0.30984

2 -0.07153

(0.02057)

0.000598

(0.000125)

0.43300 0.41410 0.35395

3 0.103701

(0.114442)

-0.02153

(0.019993)

0.001458

(0.000808)

0.4548 0.4172 0.34708

4 0.088393

(0.081156)

-0.00686

(0.014423)

-0.0016

(0.000802)

0.00024

(4.56e-05)

0.73559 0.70727 0.24170

5 -0.09219

(0.037388)

0.014101

(0.003195)

0.39364 0.37343 0.36603

6 -3.44791

(0.301589)

2.031266

(0.292303)

0.61681 0.60404 1.29564

7 -3.79639

(0.289239)

0.674513

(0.51025)

2.071239

(0.672017)

0.71136 0.69145 1.12449

8 -2.15561

(0.154206)

0.013775

(0.004492)

-0.00034

(0.000217)

0.71464 0.69496 1.11807

23

Table 16 : Merchantable Volume Over Bark of Prosopis cineraria

Model

No.

a b c d R2 Adj. R

2 RMSE

1 0.009175

(0.003824)

4.89E-05

(3.12e-06)

0.890863 0.887225 0.079953

2 -0.00549

(0.007852)

0.000288

(3.27e-05)

0.72101 0.71171 0.127833

3 -0.01003

(0.047686)

0.000657

(0.006808)

0.000266

(0.000227)

0.721099 0.701865 0.127812

4 0.025657

(0.023384)

-0.00393

(0.00331)

0.000234

(0.00011)

3.7E-05

(3.8e-06)

0.936827 0.930058 0.06083

5 -0.06324

(0.014306)

0.00853

(0.001)

0.707956 0.698211 0.130789

6 -3.81204

(0.357148)

2.152117

(0.317988)

0.604247 0.591055 1.311138

7 -3.93781

(0.291141)

1.837889

(0.269015)

0.828925

(0.203105)

0.748628 0.731292 1.044948

8 -1.79808

(0.115168)

0.003863

(0.005285)

0.000178

(0.000239)

0.62007 0.593868 1.284659

24

Table 17: Merchantable Volume UnderBark of Prosopis cineraria

Model

No.

a b c d R2 Adj. R

2 RMSE

1 0.01005

(0.003434)

4.28E-05

(4.1e-05)

0.78388 0.77668 0.07379162

2 -0.00221

(0.003908)

0.000278

(2.37e-05)

0.82053 0.81455 0.067244

3 -0.00272

(0.022172)

9.14E-05

(0.003873)

0.000274

(0.000157)

0.82053 0.80816 0.067244

4 0.008831

(0.015474)

-0.00175

(0.002699)

0.000238

(0.000109)

2.3E-05

(4.03e-06)

0.91704 0.90815 0.045718

5 -0.03958

(0.007223)

0.006795

(0.000617)

0.80155 0.79493 17.52142

6 -3.75993

(0.303932)

2.122476

(0.294573)

0.63377 0.62156 1.305705

7 -3.93845

(0.267469)

1.893262

(0.263055)

0.718444

(0.213503)

0.73661 0.71844 1.107299

8 -1.95903

(0.124965)

0.004818

(0.006631)

0.000232

(0.000357)

0.55106 0.52010 1.445634

On the basis of best equation screened the volume tables were prepared and given in the

annexure in the end.

References:

1. Clutter J.L., Fortson J.C., Pienaar L.V., Brisster G.H. and Bailey R.L. 1983.

Timber management: A quantitative approach. John Wiley and sons, Chichester,

411p.

2. Loetsch F., Zohrer F. and Haller K.E. 1973. Forest Inventory Vol. II. BLV

Verlagsgesellschaft, Munchen, Germany, 469p.

3. Spurr S.H. 1952. Forest Inventory. John Wiley and sons, New York, 476p.

25

14.8: Work Report for extended period:

14.8.1: Objective: To estimate average yearly foliage production of Prosopis cineraria

on the farmers’ field.

14.8.2: Introduction:

Farmers of arid region are maintaining a few naturally growing trees such as Prosopis

cineraria (Khejri), Tecomella undulata (Rohida), Zizyphus nummularia (Ber) etc. in their

fields with the aim to obtain fodder, fuel and timber. Prosopis cineraria (L) Druce, commonly

known as Khejri is a deep-rooted tree. It is suitable for areas of low water tables. It is the

general practice that Khejri trees have been lopped from the time immemorial in order to meet

fodder and fuel requirement. The wood is useful for house construction and making

agricultural implements. Besides fuel wood and fodder, the boiled-dried pods of Khejri are

the important constituents of the panchkuta, a famous Marwari vegetable. This species

provide economic and social security in the event of drought and famine through multi-facets

products.

Khejri the state tree of Rajasthan is regarded the lifeline of desert dwellers owing to

multiple products and services it renders to society. Besides providing food (fresh and dried

pods), Fodder (fresh and dry leaves), fuel (wood) and fencing material (lopped branches), it

enriches the soil and serves as a shelter for the animals during hot summers. It is also known

to increase soil fertility and underneath productivity. P. cineraria is under stressed due to

continuous and complete lopping, decrease in ground water table, changes in land use pattern

and infestation of diseases. The present study was conducted to know the average foliage

production per year in Jodhpur and Nagour districts of farmers.

The objective of the study is to estimate average yearly foliage production of

Prosopis cineraria of different diameter classes (Big size: above 35 cm. and above,

Medium size Diameter: 20 to 35 cm, Small Size Diameter: less than 20 cm) on the

farmers’ field.

26

Sixty trees of Prosopis cineraria were selected, thirty each of two sites - 15 at

Goth in Nagour district and 15 at Kharia Midhapur and 30 at Bhavi in Jodhpur district for

estimating foliage yield.

Selected 60 trees were lopped and observations such as DBH, total height, height

at first branch, crown length, crown width, crown volume fuel wood and fodder and only

fodder yield were measured.

14.8.3: Data Analysis and Brief Result

Step Up Multiple Regression Technique was applied for above mentioned

collected data assuming height as dependent variable and taking Diameter at Breast

Height (DBH), Ist

branch (IstBr), Fuel wood and Fodder quantity (FF), Fodder (F), crown

volume (CrVol) and crown area (CrA) as a set of independent variables. All possible

combination of the independent variables was worked out. For example, in the case of

height considering as dependent variable with set of six independent variables (DBH, Ist

branch, Fuel wood and Fodder quantity, Fodder, crown volume and crown area) total

number of 63 equations were ( One variable-6, Two Variable-15, Three-20 Four

Variable-15, Five Variable-6 and Six Variable -1) developed.

All the combination of the equations was worked out with the help of SPSS IBM

statistics version 20 along with Multiple regression coefficient R and standard error at

5%. Out of these best of two equations were reported.

Out of all possible combination of regression equations among height and set of

six variables as independent variables 63 equations ( One variable-6, Two Variable-15,

Three-20 Four Variable-15, Five Variable-6 and Six Variable -1) were developed and

two best equation were screened on the basis of Multiple regression coefficient R and

standard Error at 5%. Following are the best equations between heights as dependent

variable with the set of six independent variables. Two equations in each case, one

variable to the six variables were reported as follows:

27

14.9: Regression equation with height as dependent variable:

One Variable

H=6.158+0.012 CrVol

R=0.688 SE=1.18047

H=6.079+0.079CrA

R=0.557 SE=1.35200

Two variables

H=4.882+0.045D+0.009 CrVol

R=0.814 SE=0.095465

H=3.377+1.026IstBr+0.014CrVol

R=0.792 SE=1.00257

Three variables

H=3.906-0.182CrA+0.038CrVol +1.190Istbr

R=0.891 SE=0.75353

H=5.665+0.039D-0.115CrA+0.025CrVol

R=0.852 SE=0.86764

Four variables

H=3.973-0.184CrA+0.026F + 60.038CrVol +0.0991Istbr

R=0.898 SE=0.73462

H=4.856+0.009 CrVol +0.018FF-0.077F+0.048D

R=0.826 SE=0.94298

28

Five variables

H=4.004+0.035CrVol-0.167CrA+0.011D+0.898IstBr+0.004 FF

R=0.901 SE=0.73149

Six variables

H=4.002-0.164CrA+0.005FF-0.008F+0.898Istbr+0.012D+0.34 CrVol

R=0.901 SE=0.73810

14.10: Dependent variable - DBH


collected data assuming DBH as dependent variable and taking Height, Ist branch, Fuel

wood and Fodder quantity , Fodder, crown volume and crown area as a set of

independent variables. Multiple regression coefficient R and standard Error at 5% was

worked out in each case. Out of all possible combination of regression equations between

DBH and set of six variables as independent variables 63 equations (One variable-6, Two

Variable-15, Three-20 Four Variable-15, Five Variable-6 and Six Variable -1) two best

equation were screened on the basis of Multiple regression coefficient R and standard

Error at 5%. Following are the best equations between DBH as dependent variable with

the set of six independent variables. Two equations in each case of one variable to the six

variables were reported as follows:

One Variable

D= -15.413+6.867H

R=0.657 SE=12.82189

D=12.467+1.216F

R=0.631 SE=13.18821

29

Two variables

D= -19.753+5.170H+0.876F

R=0.782 SE=10.68365

D= -17.766+0.146FF+5.626H

R=0.733 SE=11.67884

Three variables

D= -21.165+5.223H-0.275FF+2.057F

R=0.811 SE=10.12823

D= -24.357+5.072H+2.817Istbr+0.778F

R=0.787 SE=1066860

Four variables

D= -22.556+5.747H+2.087F-0.286FF-0.115CrA

R=0.814 SE=10.14790

D= -22.628+5.583H+2.055F-0.278FF-0.009CrVol

R=0.812 SE=10.20457

D= -3.443+0.908F+8.386IstBr-1.424CrA+0.260CrVol

R=0.801 SE=10.46083

Five variables

D= -2.700-1.572CrA+0.277CrVol+2.159F-0.284FF+7.871IstBr

R=0.830 SE=9.84228

D= -11.729+4.109H-0.766CrA+0.110CrVol+2.275F-0.302FF

R=0.822 SE=10.02622

30

Six variables

D= -11.238-1.178CrA+0.196CrVol+2.120F-0.288FF+5.732IstBr+2.151H

R=0.835 SE=9.80351

14.11: Dependent Variable - Fuel wood and Fodder


collected data assuming as Fuel wood and Fodder dependent variable and taking DBH,

Height, Ist

branch, Fodder, crown volume and crown area as a set of independent

variables. Multiple regression coefficient R and standard Error at 5% was worked out in

each case. Out of all possible combination of regression equations between Fuel wood &

Fodder and set of six variables as independent variables 63 equations (One variable-6,

Two Variable-15, Three-20 Four Variable-15, Five Variable-6 and Six Variable -1) two

best equation were screened on the basis of Multiple regression coefficient R and

standard Error at 5%. Following are the best equations between Fuel wood and Fodder as

dependent variable with the set of six independent variables. Two equations in each case

of one variable to the six variables were reported as follows:

One Variable

FF= -3.928+4.305F

R=0.945 SE=13.17786

FF=34.679+1.254D

R=0.530 SE=34.11457

Two variables

FF= -0.671-0.261D+4.623F

R=0.949 SE=12.83077

FF= -5.131+0.193H+4.292F

R=0.945 SE=13.28966

31

FF= -2.395+4.320F-0.092CrA

R=0.945 SE=13.28044

Three variables

FF= -0.877-0.552CrA+4.337F+0.066CrVol

R=0.946 SE=13.24044

FF= -0.484-0.257D-0.014CrA+4.620F

R=0.949 SE=12.94370

Four Variables

FF= -32.471+1.113D+9.825H+3.186CrA-0.590CrVol

R=0.615 SE=32.59597

FF= -15.913-0.438D+4.651F+3.290H-0.184CrA

R=0.953 SE=12.56409

Five variables

FF=1.027-0.461D+2.050IstBr+0.179CrVol-1.180CrA+4.824F

R=0.954 SE=12.53757

FF= -12.741-0.217CrA+3.449H-0.426D-2.36Istbr+4.706F

R=0.953 SE=12.63576

Six variables

FF= -5.072+1.522H-0.476D+0.667IstBr+4.798F+0.126CrVol-0.920CrA

R=0.954 SE=12.60492

32

14.12 Dependent variable fodder:


collected data assuming as Fodder dependent variable and taking DBH, Height, Ist

branch, Fuel wood and Fodder quantity , crown volume and crown area as a set of



Fodder and set of six variables as independent variables 63 equations (One variable-6,

Two Variable-15, Three-20 Four Variable-15, Five Variable-6 and Six Variable -1) two

best equation were screened on the basis of Multiple regression coefficient R and

standard Error at 5%. Following are the best equations between Fodder as dependent

variable with the set of six independent variables. Two equations in each case of one

variable to the six variables were reported as follows:

One variable:

F=2.908+0.207FF

R=0.945 SE=2.292323

F=7.647+0.328D

R=0.631 SE=6.84788

Two variables:

F=1.188+0.094D+0.186FF

R=0.957 SE=2.57554

F=0.221+1.355IstBr+0.197FF

R=0.949 SE=2.81684

Three variables

F= -0.274+0.129D+0.284CrA-0.043CrVol+0.178FF

R=0.965 SE=2.38506

33

F=3.908-0.518H+0.127D+0.188FF

R=0.960 SE=2.51660

F= -0.280+0.284CrA+0.129D+0.004IstBr-0.043CrVol+0.178FF

R=0.965 SE=2.40705

Five variables

F= -0.280+0.284CrA+0.129D+0.004IstBr-0.043CrVol+0.178FF

R=0.965 SE=2.40705

F=0.076+0.276CrA+0.131D-0.042CrVol+0.178FF-0.063H

R=0.965 SE=2.40644

Six variables

F=0.073+0.270CrA-0.040CrVol+0.178FF-0.088H+0.083IstBr+0.130D

R=0.965 SE=2.42878

14.13 Dependent variable Crown Volume:


collected data assuming as Crown Volume dependent variable and taking DBH, Height,

Ist branch, Fuel wood and Fodder quantity, fodder and crown area as a set of



Crown Volume and set of six variables as independent variables 63 equations (One

variable-6, Two Variable-15, Three-20 Four Variable-15, Five Variable-6 and Six

Variable -1) two best equation were screened on the basis of Multiple regression

coefficient R and standard Error at 5%. Following are the best equations between Crown

Volume as dependent variable with the set of six independent variables. Two equations in

each case of one variable to the six variables were reported as follows:

34

One Variable:

CrVol= -27.488+6.928CrA

R=0.956 SE=26.66179

CrVol= -177.818+38.245H

R=0.688 SE=65.58783

Two variables

CrVol= -104.072+12.598H+6.013CrA

R=0.974 SE=20.69076

CrVol= -42.412+0.527D+6.719CrA

R=0.960 SE=25.46770

Three variables

CrVol= -102.088+14.787H-0.204FF+5.906CrA

R=0.978 SE=19.38055

CrVol= -67.860+16.930H-23.154Istbr+5.553CrA

R=0.985 SE=15.92683

Four variables

CrVol= -70.592-0.416+17.368H-20.372Istbr+5.572CrA

R=0.985 SE=15.77021

CrVol= -70.155+17.361H-21.227Istbr+5.552CrA-0.074FF

R=0.985 SE=15.85989

CrVol= -62.322+15.800H+0.188D+5.551CrA-24.630Istbr

R=0.985 SE=15.90639

CrVol= -71.24+42.456H+0.269D-0.159F-56.224Istbr

R=0.783 SE=57.79544

35

Five variables

CrVol=0.280+1.314D-15.807Istbr+0.525FF-3.443F+6.450CrA

R=0.973 SE=21.44614

CrVol= -70.467-20.205Istbr+0.053FF-0.648F+5.583CrA+17.303H

R=0.986 SE=15.89956

CrVol=-90.278+0.257FF-2.507F+5.986CrA+12.778H+0.380D

R=0.980 SE=18.66525

Six variables

CrVol= -58.542+14.664H+0.476D-21.049Istbr+0.185FF-

1.597F+5.623CrA

R=0.987 SE=15.28194

14.14 Distribution of fodder, Fuel wood & Fodder and Crown volume with

Diameter Classes:

The collected data pertaining to lopping study were classified into three diameter

classes (Small: Diameter with less than 20cm, medium: Diameter with 20 to 35cm and

Large: Diameter with more than 35cm). To explore the variation of fodder, Fuel wood

&Fodder and Crown volume with Diameter Classes the histogram were drawn between

diameter and other variables mentioned above. The diameter classes were taken on the x-

axis and other variables were taken on y-axis. These charts are shown in next pages.

38

Fig. 5: Change of growth pattern (D.B.H.) of Prosopis cineraria in successive years

Fig 6: Change of growth pattern (Height) of Prosopis cineraria in successive years

5

6

7

8

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03 RD 08 RD 1447 RD 1340 RD 1387 RD 1355 RD 740 RD 704 RD

He

igh

t (m

)

2010-11

2011-12

2012-13

2013-14

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03 RD 08 RD 1447 RD 1340 RD 1387 RD 1355 RD 740 RD 704 RD

D.B

.H. (

cm.)

2010-11

2011-12

2012-13

2013-14

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Fig 7: Change of growth pattern (D.B.H.) of A. excelsa in successive years.

Fig 8: Change of growth pattern (Height) of A. excelsa in successive years

5

10

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25

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19 KJD 0-17RD 802RD 9MD 0-2RD

D.B

.H. (

cm)

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2012-13

2013-14

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19 KJD 0-17RD 802RD 9MD 0-2RD

He

igh

t (m

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Photographs: Collection of data and interaction with farmers

Photo 1: Lopping of Prosopis cineraria in Farmer’s field.

Photo 2: Collection of fuelwood and fodder of Prosopis cineraria.

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Photo 3: Weighing total fresh weight of fuelwood and fodder of Prosopis

cineraria.

Photo4: Fodder collected from one khejri tree.

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Photo 5: Fuel wood collected from one khejri tree.

Photo 6: Fresh fodder collected on farmer’s field ready for

transportation.

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Summary of the Project

1. Title: "Productivity and biometrics studies on some important species in arid &

semi-arid regions of Rajasthan for their sustainable management"

2. Project Number: AFRI-95/Silvi./SFD/2009-2012

3. Name of the Principal Investigator: Dr. Sunil Kumar, Scientist-E

4. Total Amount of Sanction along with period (Years):

The total budget sanctioned for this project was Rs 5.47 Lakhs with period from

January 2009 to March 2012 as per project document. The project was further

extended for the period of two years from 2012-13 and 2013-14. Total budget

released was Rs. 4.44 lakhs and was spent for carrying out activities related to the

project as per project plan.

Summary: This project taken up with the objectives was to construction of tree volume

equations for the species Prosopis cineraria (Khejri) and Ailanthus excelsa (Ardu) and to

develop growth and yield models (height, basal area) for sustainable management of

plantations in semi arid areas of Rajasthan. The data required for conducting this study

were collected from the plantations raised by State Forest Department, Rajasthan. Survey

of the plantation areas of Prosopis cineraria and Ailanthus excelsa was carried out in

IGNP areas with the aim to laying out permanent sample plots and felling of trees of

representative DBH classes from the surrounding. Eight plantations for Prosopis

cineraria (03 RD, 08 RD, 1447 RD , 1340 RD, 1387 RD, 1355 RD, 740 RD, 704 RD )

and 6 for Ailanthus excels (19 KJD ,CSP-KCSP-KJD 0-17 RD, 802 RD, 9MD,0-2 RD &

Dadia) were selected in IGNP and Pali divisions and sample plots were laid out at these

locations in Rajasthan. Thirty two trees of Prosopis cineraria and 22 numbers of trees of

Ailanthus excelsa were felled for validation of tree volume. Required observations were

collected from the fourteen permanent sample plots distributed over in study area for the

year 2011-12 to 2012-13. Eight numbers of models were used for deriving the total


cineraria and Ailanthus excelsa. Out of eight equations four are based on only DBH only,

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others are based on either DBH and H or combination of D & H i.e. D2H. Our goal is to

estimate the total volume of wood over bark and under bark and merchantable wood up

to 10 cm diameter on the basis of single tree. Thus, it will comprise a total of sixty four

equations, 8 each in four cases. The following results were obtained.

Total Volume of Ailanthus excelsa over Bark: Log V = a + b log D+ c D2H

(Model no 7 with a=-3.71155 b=1.61865 c=0.84136) gave highest R2 (0.9430),

Adj. R2 (

0.9360) with RMSE 0.3818.

Log V = -3.71155 + 1.61865 log D+ 0.84136 D2H

R2= 0.9430, Adj. R

2 =

0.936, RMSE = 0.3818.

Total Volume of Ailanthus excelsa under Bark: V= a+b D + c D2 + d D

2H

(Model no. 4 a=-0.03868 b=0.00698 c=-0.00014 d=.0000286) gave highest R2

(0.8485), Adj. R2 (

0.8218) with RMSE 0.1353.

V = -0.03868 + 0.00698 D - 0.00014 D2

+ 0.0000286 D2H

R2 =0.8485, Adj. R

2 =0.8218 with RMSE= 0.1353.

Merchantable Volume of Ailanthus excelsa over Bark: V= a+ b D + c D2 + d

D2H

(Model no. 4 a=-0.03452 b=0.006587 c=-0.00016 d= .000027) gave highest R2

(0.9726), Adj. R 2

(0.9677) with RMSE 0.0552.

V= -0.03452 + 0.006587 D - 0.00016 D2 + .000027 D

2H

(Model no. 4 a=-0.03452 b=0.006587 c=-0.00016 d= .000027) gave highest

R2= 0.9726, Adj. R

2=0.967 RMSE= 0.0552.

Merchantable Volume of Ailanthus excelsa under Bark: V= a+ b D + c D2 + d

D2H

(Model no. 4 a=0.00159 b=0.000007 c=0.000124 d=0.00002) gave highest R2

(0.9597), Adj. R 2

(0.9526) with RMSE 0.0533.

V= 0.00159 +0.000007 D + 0.000124 D2 + 0.00002 D

2H

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a=0.00159 b=0.000007 c=0.000124 d=0.00002 R2=0.9597, Adj. R

2 =

0.9526 with

RMSE 0.0533.

Total Volume of Prosopis cineraria over Bark: V= a+ b D + c D2 + d D

2H

(Model no. 4 a=0.10497 b=-0.00544 c=-0.00117 d=0.000183) gave highest R2

(0.8578), Adj. R 2

(0.8425) with RMSE 0.1899.

V= 0.10497 - 0.00544 D - 0.00117 D2 + 0.000183 D

2H

(Model no. 4 a=0.10497 b=-0.00544 c=-0.00117 d=0.000183) gave highest

R2 =0.8578, Adj. R

2 = 0.8425 with RMSE= 0.1899.

Total Volume of Prosopis cineraria under Bark: V= a+ b D + c D2 + d D

2H

(Model no. 4 a=0.08839 b= -0.00686 c=-0.0016 d=0.000249) gave highest R2

(0.7356), Adj. R 2

(0.7073) with RMSE 0.2417.

V= 0.08839 - 0.00686 D - 0.0016 D2 + 0.000249 D

2H

(Model no. 4 a=0.08839 b= -0.00686 c=-0.0016 d=0.000249) gave highest

R2 =0.7356, Adj. R

2 =0.7073 with RMSE =0.2417.

Merchantable Volume of Prosopis cineraria over Bark: V= a+ b D + c D2 + d

D2H

(Model no. 4 a=0.02565 b=-0.00393 c=0.000234 d=0.000038) gave highest R2

(0.9368), Adj. R 2

(0.9300) with RMSE 0.06083.

V= 0.02565 - 0.00393 D + 0.000234 D2 + 0.000038 D

2H

(Model no. 4 a=0.02565 b=-0.00393 c=0.000266 d= 0.000038) gave highest

R2 =0.9368, Adj. R

2 = 0.9300 with RMSE 0.06083.

Merchantable Volume of Prosopis cineraria under Bark: V= a+ b D + c D2 + d

D2H

(Model no. 4 a=0.008831 b=-0.00175 c=0.000238 d=0.00002) gave highest R2

(0.9170), Adj. R 2

(0.90815) with RMSE 0.04572.

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V= 0.008831 - 0.00175 D + 0.000238 D2 + 0.00002 D

2H

R2 = 0.9170, Adj. R

2 = 0.90815 with RMSE 0.04572.

Summary of the Project (for extended Period)

The objective of the study is to estimate average yearly foliage production of Prosopis

cineraria of different diameter classes (Big size: above 35 cm. and above, Medium size

diameter: 20 to 35 cm, Small size diameter: less than 20cm) on the farmers’ field.

Thirty trees of P. cineraria were selected at each of two sites one at Goth in Nagour

district and Kharia Midhapur and Bhavi in Jodhpur district for estimating foliage yield.

Total numbers of 60 trees was lopped and measurements such as DBH, total height,

height at first branch, crown length, crown width, crown volume fuel wood and fodder

and only fodder yield were measured.

Step up Multiple Regression Technique was applied for above mentioned collected data

assuming height as dependent variable and taking Diameter at Breast Height(DBH), Ist

branch, Fuel wood and Fodder quantity , Fodder, crown volume and crown area as a set

of independent variables. All possible combination of the independent variables was

worked out. For example, in the case of height considering as dependent variable with set

of six independent variables (DBH, Ist branch, Fuel wood and Fodder quantity , Fodder,

crown volume and crown area) total number of 63 equations were ( One variable-6, Two

Variable-15, Three-20 Four Variable-15, Five Variable-6 and Six Variable -1) developed.

Regression equation with height as dependent variable:

Five variables

H=4.004+0.035CrVol-0.167CrA+0.011D+0.898IstBr+0.004 FF

R=0.901 SE=0.73149

Dependent variable: DBH

Four variables

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D= - 22.556 + 5.747H + 2.087F - 0.286FF - 0.115CrA

R=0.814 SE=10.14790

Dependent Variable: Fuel wood and Fodder:

FF= - 5.131 + 0.193H + 4.292F

R=0.945 SE=13.28966

FF= - 2.395 + 4.320F - 0.092CrA

R=0.945 SE=13.28044

Dependent variable fodder:

Three variables

F= - 0.274 + 0.129D + 0.284CrA - 0.043CrVol + 0.178FF

R=0.965 SE=2.38506

Dependent variable Crown Volume:

Four variables

CrVol= - 70.592 - 0.416 + 17.368H - 20.372Istbr + 5.572CrA

R=0.985 SE=15.77021

(Dr. Sunil Kumar) Head, Silviculture GC(R) Director

Scientist –E AFRI, Jodhpur AFRI, Jodhpur AFRI, Jodhpur

Place: Jodhpur

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