Mapping forest biomass in India through aerial photographs and nondestructive field sampling

A~~fied Geography (1984), 4, 151-155

Mapping forest biomass in India through aerial photographs and nondestructive field sampling A. K. Tiwari and J. S. Singh department of Botany, Kumaun ~~i~~~r~~t~, ~a~~~ Tal263 002, India

Abstract A method for mapping of forest biomass using black-and-white aerial photographs and nondestructive field sampling is described through a case study of Ladhiya subcatchment in Kumaun Himalaya, India. Forest types were mapped using aerial photographs and field checks. Each forest type was divided into five crown cover classes. Mean crown cover for each class was determined in the field. Density and basal cover were measured on reference sites. Stand biomass was estimated by using biomass estimation equations, mean girth and mean density on the reference sites. Regression equations were developed between crown cover and basal cover, and between crown cover and stand biomass. Mean basal cover and mean stand biomass for each photo-interpreted crown cover class were estimated through these equations. Forest biomass values were substituted for crown cover classes on the interpreted map.

Introduction Vegetation inventories are required for many decisions in wildland and natural resource management. Estimations of forest biomass are needed especially for the determination of site productivity, nutrient cycling and energy potential (Schmitt and Grigal 1981). Regional biomass maps also constitute a valuable resource inventory. The massive inputs of time and money required in traditional field methods involving plot harvest make them impractical for developing biomass maps for large areas. Interpretation of aerial photographs combined with appropriately restricted field sampling could be a viable alternative. The objectives of this study were (a) to describe a method for forest biomass mapping that has been used for a large tract of Kumaun Himalaya; (b) to generate discussion on the method; and (c) to initiate collection of data on forest species for generalized species and interspecies biomass estimation equations. The method is illustrated through a case study of a subcatchment, Ladhiya (29%’ to 29”27’ N latitude and 79”44’ to 79”50’ E longitude), located in the Naini Tal district and involving a total area of 8218.75 ha.

Methods The tota study involved a large area of rugged terrain, nearly O-2 x 10’ ha, lying between 29% and 29”35’ N latitude and between 79”7’ and 79”50’ E longitude in the northwestern part of the Central Himalaya. The sequence of steps involved in the method is outlined in Fig. 1. The area was mapped through the interpretation of 0143-6228/8~/02#iSl-15$03.00 0 1984 Butterworth & Co (Publishers) Ltd

1.52

~ap~~#g forest biomass in India

black-and-white aerial photographs (1:40~0) taken in 1973, following the method of Tewari and Singh (1983). In brief, by using a double scanning mirror stereoscope and a photo-interpretation key (developed on the basis of reconnaissance of the area with survey maps and aerial photographs), different forest types were delineated on the aerial photographs on the basis of crown characteristics (Tomar I

AERIAL

CALIBRATION

OF

PHOTOINTERPRETATION

INTERPRETED

CROWN

COVER

BY

FIELD

CHECK I

_--

-I MAPPING

OF FORESTS

SELECTION EACH

OF SITES CROWN

ACCORDING

FOR EACH COVER

TO

FOREST

CLASS

CROWN

TYPE

FOR FIELD

COVER

AND

I-____-____-_;

FOR

SAMPLING

I FIELD

_-

ESTIMATION

0~

CBH. DENSITY.

CROWN

BASAL

COVER

AND -----

COVER

, ,

I

t FIELD

__

OF MEAN

INrERPRETED

i

BASAL

ESTIMATION

CROWN

-7

r

CROWN

COVER

COVER

CLASS

FOR EACH

I

t

-_---

.J!i, / i

COVER

REGRESSION BASAL CROWN

OF MEASURED

COVER

ON

MEASURED

COVER @-_-----___-_I

L__-_---__a

Figure 1. Flow diagram of the method. arrows indicate information flow.

Solid arrows

indicate

sequence

of steps and broken

A. K. Tiwari and J.S. Singh

153

and Maslekar 1974). Each forest type was further subdivided on the basis of crown cover into five classes: s 20 per cent, 21-40 per cent, 41-60 per cent, 61-80 per cent and > 80 per cent. Crown cover interpreted from the aerial photographs was calibrated by intensive field checks for all forest types. Interpreted details of the aerial photographs were transferred to a base map (1:50000) prepared from a topographic sheet, using an Aerosketchmaster, and the area of different forest types under each crown cover class was estimated using a dot grid overlay. Test sites for each crown class for each forest type were selected from the entire study area and marked randomly on the interpreted map. These sites were also marked on the topographic sheet. The sites were then located in the field and sampled for density and basal cover using 8 to 12 quadrats, each 10 x 10 m in size. The size of quadrat was determined by reference to species area curves (Braun-Blanquet 1932; Oosting 19.53) and the number of quadrats by the running mean method (Kershaw 1973). Within each quadrat each individual tree of circumference at breast height (cbh) >31.5 cm was measured for cbh. On each site, crown cover was estimated by the line intercept method (Misra 1968). A 50-m long measuring tape was laid randomly at 10 places on each site. The length of the tape which was covered by the tree crown was measured. By averaging all 10 replicates, per cent crown cover for that site was computed. The average across sites yielded the mean crown cover for each photo-interpreted crown cover class of a forest type (Table 1). Tree density and total basal cover were computed following Misra (1968). The ground-measured crown cover and basal cover values for each forest type were related through regression equations of the form bkl

y

=

Pl

+

B2

@ho

x

(1)

where

Y = basal cover (cm* 100 m-*) X = crown cover (%) Intercept (Jr), slope (‘J2), 2 and SE,,, values are given in Table 2. equations, and values of mean crown cover determined earlier, mean for each crown cover class (photo-interpreted) was computed for each (Table 3). The values of basal cover were then divided into five classes: 18.1-27, 27-l-36, 36-l-45 m* ha-‘, and mapped.

Using these basal cover forest type ~9,9.1-18,

Table 1. Per cent mean ground-measured

photo-interpreted

crown cover corresponding to different crown cover classes for the forest types present in the Ladhiya subcatchmenV Photo-interpreted

crown cover class (per cent)

S20

2140

41-60

61-80

14

37

47

67

8.5

Pine-mixed broadleaf Quercus leucotrichophora

16

35 35

46 54

61 74

$

Mixed high-altitude Mixed broadleaf

$ 17

24 35

51 53

64 77

Forest type Pinus roxburghii

oak

HO

a The values are derived from a much larger sampling area of which Ladhiya subcatchment was a part b Not present

154

Mapping forest biomass in India

Table 2. Allometric relationships

Forest types

between the crown cover, X (per cent) and basal cover, Y (cm2 100 m-*)’ Intercept (/3,)

Slope

c/32)

Pinus roxburghii

1.7132

Pine-mixed

2.6509

1.0715 0.5767

Quercus leucotrichophora

1.9371

Mixed high-altitude Mixed broadleaf

2.2038 I .6627

broadleaf oak

?J

SE,

x

0.974 0.860

0.049 0.057

0.9605

0.968

0.066

0.8617 1.0721

0.903 0.810

0.082 0.147

” According to log,,, Y = /J, + /& log,,, X On each site, mean basal cover per tree and mean cbh per tree were calculated for the dominant and the subordinate species. All the subordinate species were categorized into one group because they were not recognizable as different species on aerial photographs (Tiwari et al. 1983). Mean tree biomass (bole and total above-ground) was estimated by allometric biomass estimation equations. Relevant equations used for the area chosen to illustrate the method are given in Table 4. Generalized species biomass estimation equations for the dominant species and generalized interspecies biomass estimation equations for the subordinate species were developed by pooling data from which site-specific biomass estimation equations were reported by Negi et al. (1983), and Rawat (1983). Mean tree biomass was multiplied by density and summed across the dominant and subordinate species to yield stand biomass for each site. The biomass of each site was related to the ground-measured crown cover, according to log10

y

=

01 + Pz log10x

(2)

Where

Y = biomass (kg 100 m-*) X = crown cover (%) Intercept VI), slope &), 3 and SE,, values are given in Table 5. The mean biomass for each crown class for each forest type was estimated by using the corresponding mean crown cover values in the above equations (Table 3). The mean biomass values were divided into five classes for bole (~40, 41-80, 81-120, 121-160, 161-200 t ha-‘) and for total above-ground biomass (~80, 81-160, 161-240, 241-320, and 321-400 t ha-‘) and mapped. Results The result of such an exercise is the map itself. Forest crown cover, basal cover, bole biomass and total above-ground biomass are mapped in Figs 2, 3, 4 and 5, respectively, for the Ladhiya subcatchment. A total of 612.5 ha (i.e. 74.5 per cent of the subcatchment) was under forest use. However, forest with >40 per cent crown cover was present only in 11.4 per cent of the total subcatchment area and in 15.3 per cent of the forested land (see Table 3). Of the five forest types present in this subcatchment none had a crown cover >60 per cent. Pinus roxburghii Sarg. forest occupied a maximum area (27.7 per cent of forested land) and was distributed in all crown cover classes of ~60 per cent. Mixed broadleaf forest occupying 26.4 per cent of the forested land was next to P. roxburghii in extent and was distributed in crown cover classes of ~40 per cent. Quercus leucotrichophora A. Camus forest

A. K. Tiwari and J.S. Singh Table 3. Area,

basal cover,

bole biomass and total above-ground different crown cover classes

biomass

155

in forests

of

Crown cover class (per cent) Forest

types

Pinus roxburghii Area (ha) Area (% of total forest) Basal cover (m2 ha-‘) Bole biomass (t ha-‘) Total above-ground biomass Pine-mixed broadleaf Area (ha) Area (% of total forest) Basal cover (m” ha-‘) Bole biomass (t ha-‘) Total above-ground biomass Quercus leucotrichophora Area (ha) Area (% of total forest) Basal cover (m2 ha-‘) Bole biomass (t ha-‘) Total above-ground biomass Mixed-high altitude oak Area (ha) Area (% of total forest) Basal cover (m’ ha-‘) Bole biomass (t ha-‘) Total above-ground biomass Mixed broadleaf Area (ha) Area (% of total forest) Basal cover (m2 ha-‘) Bole biomass (t ha-‘) Total above-ground biomass

620

21-40

41-60

Total

(t ha-‘)

500.0 8.2 8.7 33.0 40.0

1143.75 18.7 24.7 78.0 107.0

50.0 0.8 32.0 97.0 135.0

1693.75 27.7 -

(t ha-‘)

231.25 3.8 22.1 94.0 142.0

87.5 1.4 34.8 122.0 207.0

(t ha-‘)

-

512.5 8.4 26.3 97.7 213.8

(t ha-‘)

-

287.5 4.6 24.7 108.0 222.0

(t ha-‘)

531.25 8.7 9.6 41.0 83.0

1087.5 17.7 20.8 78.0 154.0

-

887.5 14.5 39.9 142.8 308.7

-

-

Total Area (ha) Area (% of total forest)

1262.5 20.5

3118.75 50.8

Scrub vegetation Area (ha) Area (% of total forest)

-

-

-

Total forest

-

-

-

(ha)

937.5 15.3

318.75 5.2 -

1400.0 22.9 -

287.5 4.6 -

1618.75 26.4 -

5318.75 86.8

806.25 13.2 6125.0

156

Mopping forest biomass in India

0 I

29’ ‘25’

. * Crown cover <20 21-40

1

Pinus roxburghii Pine mixed broadleaf ITIE Quercus

leucotrichophora •~

Mixed

high altitude

Mixed

broadleaf

Scrub vegetation Non-forested land

q J

cl 79”45’

I

Figure

262c

Oak

2. Map

subcatchment.

showing different forest types and their crown cover classes Altitudes of selected points are given in metres.

in the Ladhiya

A. K. Tiwari and J.S. Singh

Basal c:over m2 ha’

<, 9.0 9.1-18.0 18.1-27.0 27.1-

36.0

36.1-45.0

2k .m

Figure

represent

3. Map of tree

non-forest

basal cover for the Ladhiya use and scrub vegetation.

subcatchment.

Open

spaces

Mapping forest biomass in India

158

Table 4. Allometric

P. roxburghii

relationships

between biomass, Y (kg tree-‘)

Intercept

Slope

VA)

v32)

Bole Total

-6,418 -6.398

Bole Total Boleh Tota?’ Bole Total

Bole Total Bole’ Totalh Bole Total

and cbh, X (cm)’

r?

SE,,,

Source

2.598 2.655

0.985 0.990

0.053 O-053

Chaturvedi and Singh ( 1983)

-0.523 -0.685 0.574 0,851 -0.321 0.984

1.367 1.254 1.064 0‘807 1.316 1.192

0.994 0.988 O-992 0.991 0.988 0.978

0.032 0.041 NR NR 0.032 0.037

Rawat (1983)

-0.861 0.349 I.882 2,178 -0-347 0.971

1.425 1.316 0.002 0.879 1.279 1.138

O.Y15

O-058 0.055 NR NR O-038 0.041

Q. lel~cotrichophora

Naini Tal area Pithoragarh

area

Generalized

Negi el al. ( 1983)

Interspecies Naini Tal area Pithoragarh

area

Generalized

0.904 0.892 o-937 0,826 0.784

Rawat (1983) Negi et al. (1983)

NR = Not reported * According to In Y = fll + & In X ’ According to log,,, Y = /3, + j& log,,, X

Table 5. Allomctric

relationships

between biomass, Y (kg 100 m-‘) and crown cover, X (per cent) Intercept (13,)

Slope C./U

$

SE, r

1.4836 1.4159

0.8988 1.0274

0,958 0.953

0.058

2.5610 2.5959

0.3422 0.4637

0.723 0.792

om1 0.058

Q. leucotrichophora Bole Total

16564 2.0368

0.8660

0.8397

0.950 O-980

0.075 0.043

Mixed broadleaf Bole Total

1.5215 1.8592

0.8893 0.8631

0.931 O-965

0.102 0.052

1.2443 1.6139

0.5790 0.5384

0.876 0.810

0.066 0.082

Forest types P. roxburghii Bole

Total Pine-mixed Bole Total

0.072

broadleaf

Mixed high-aititude Bole Total

oak

* According to loglo Y = j3, + jfz log,,, X

A. K. Tiwari and J.S. Singh

159

had crown cover between 21 and 60 per cent. It had comparatively more mean basal cover as well as mean biomass in all crown cover classes than P,roxburghii and mixed broadleaf forests, due to which it accounted for the maximum proportion of total basal cover (38.8 per cent) and biomass (bole = 34.9 per cent, total above-ground = 44.6 per cent) in the subcatchment (Table 6). P. roxburghii followed Q. leucotrichophora in the contribution of basal cover but it accounted for a lower proportion of total above-ground biomass than mixed broadleaf forest. Pine-mixed broadleaf forest had maximum mean basal cover as well as mean biomass among all forest types in respective crown cover classes but recorded minimum total above-ground biomass (5.1 x lo4 tons; i.e. 5.9 per cent of the subcatchment total biomass). Mixed high-altitude oak forest had mean basal cover as well as mean biomass comparable to that of Q. feucotrichophoru but due to a very small area (806.25 ha) under its cover, it contributed only 7.2 per cent of the bole biomass and 7.5 per cent of the total subcatchment above-ground biomass. The patchiness in the biomass density (Figs 4 and 5) reflects the variations in site quality, species composition and intensity of biotic stress. Discussion

The present method is based on four major assumptions. The first assumption was that the major quantitative parameters of vegetation expression are interrelated, and one can be used to predict the other. The ? and SE,,, values for the relationship between crown cover and basal cover (see Table 2) and between crown cover and biomass (see Table 5) for individual forest types obtained in this study supported the above assumption. It was, therefore, possible to estimate the basal cover from the mean crown cover after due standardization from random field sampling, and to assess biomass and basal cover values for photo-interpreted crown cover classes. The second assumption was that, by using allometric biomass estimation

equations, mean tree basal cover and density, it is possible to estimate the stand biomass. The use of dimensional analysis (Whittaker and Woodwell 1968) or allometry (Kira and Shidei 1967) to relate biomass to various tree dimensions has been commonly employed for estimating stand biomass in recent years (Baskerville 1955; Attiwill and Ovington 1968; Kira and Shidei 1967; Satoo 1968, 1970; Crow 1971, 1978). A review and cross-section of results from dimensional analysis are Table 6. Basal cover, bole biomass and total above-ground biomass in different forest types of the Ladhiya subcatchment. Calculations are based on values in Table 3

Forest types

Basal cover (10” m2)

%

P. roxburghii

34-3

27.2

8.2

65

48.9

38-8

7.1 27-7

5.6 21.9

Pine-mixed broadleaf Q. ~eucotr~chophora Mixed high-altitude oak Mixed broadleaf Total

126-2

Total above-ground biomass (104 t)

Bole biomass (lo4 t) 11.1 3.2 15-1 3.1 10.7 43.2

25.7 7.4 34.9 7.2 24.8

14.9 5.1 38.3 6.4 21.2 85.9

% 17-3 5.9 44-6 7.5 24.7

160

Mapping forest biomass in lndia

Bole biomass tons per ha

w= f-4

/

5 40

---- --

41-80 81-120 121-160 161- 200

0

2km

I

Figure 4. Map of bole biomass for the Ladhiya represent non-forest use and scrub vegetation.

subcatchment.

Open

spaces

A. K. Tiwari and J.S. Singh

--------------

Total abwe-ground biomass tons per ha

81- 160 161- 240

\:

: : :

24% 320 321- 400

0

I

2km

I

Figure 5. Map showing total above-ground tree biomass for the Ladhiya subcatchment. Open spaces represent non-forest use and scrub vegetation.

161

162

Mupping forest biomuss in India

given in Whittaker and Marks (1975). In this method the more common procedure is to divide the tree population of each species on a site into several girth classes, to determine the mean girth for each class, to estimate the biomass of the mean tree for each girth class, to estimate the girth class biomass by multiplying the mean tree biomass with the density of the girth class and to sum the biomass values across girth classes. The division of the population into girth classes is arbitrary and depends upon convenience and the judgement of the investigator. Girth class distribution will also vary from site to site; hence the approach becomes impracticable when a large area which may contain numerous ‘sites’ is concerned. Furthermore, density in forest stands decreases with increasing tree diameter (and hence mean basal cover) as competition between individuals eliminates some trees (O’Neill and De Angelis 1980). Self-thinning is apparent also in the similar relation between mean biomass and density in natural forests. It may be assumed that this relationship represents a stabilizing mechanism. Therefore, applying biomass estimation equations for mean tree basal cover and multiplying the resultant value with mean density should provide acceptable estimates of stand biomass. The third assumption was that the generalized species and interspecies biomass estimation equations can be used for dominant and subordinate species, respectively. Crow (1978), Green and Grigal(1978), and Schmitt and Grigal(l981) have argued that the geographically generalized biomass estimation equations are generally applicable over the geographic range of aggregate data sources and provide a viable alternative when site-specific equations are unavailable and costly to equations develop. A comparison of 2 and ScL., values for the generalized presented here with those of site-specific equations provides further means for confidence (see Table 4). A similar question may be raised on the use of interspecies biomass estimation equations for subordinate species. Ogawa er al. (1961, 1965) and Yoda (1968) have shown that in tropical forests the tree species may be so similar in form as to fit a single regression line and there is no marked gain in accuracy by the use of regressions for the individual species. Whittaker and Woodwell (1968), in their Brookhaven study, dealt with species more widely different in form and stature, yet these were related by interspecies trends. Recently Negi et al. (1983) have used interspecies equations for estimating the stand biomass of those species for which individual equations were not available. A majority of biomass is accounted for in any case by the dominants. The use of interspecies equations is also a function of the degree of resolution required for the study. From the aerial photographs used it was not possible to identify individual subordinate species (Tewari and Singh 1983; Tiwari et ul. 19X3). Differences in composition and proportions of subordinate species within the same forest type occur in response to various factors such as aspect and slope position (Saxena and Singh 1982). Therefore, when generalized biomass maps for forest types are needed, it is not possible to use individual biomass equations for all species, even if such equations were available. Further, the gain in ‘precision’ may be counterbalanced by the additive error of equations. Precision can be increased, and should be increased, by expanding the sample size and geographical range in developing such equations. Independent estimates of stand biomass are available for 15 sites, 5 from pine forests, 1 from pine-mixed broadleaf forest and 9 from oak forests from the Kumaun Himalaya (Table 7). Biomass estimates in the present study from corresponding crown cover classes of the same forest types are plotted against the independent estimates in Fig. 6. The corresponding crown cover classes were determined with the help of the reported basal cover from the independent sites.

A. K. Tiwari and J.S.

Table 7. Reported

Forest

total above-ground Basal cover (m* ha-‘)

type

Pine forest

Pine-mixed

biomass

broadleaf

forest

I

163

types

Source

83 161 225 193 163

Chaturvedi (1983) Chaturvedi (1983) Chaturvedi (1983) Chaturvedi (1983) B. S. Rana (unpublished)

24.3

158

B. S. Rana (unpublished)

45.0 50.8 37.0 42.3 86.7 40.5 59.7 9.4 7.4

238 290 198 269 323 362 457 89 70

Rawat (1983) Rawat (1983) Negi et al. (1983) Negi et al. (1983) Negi et al. (1983) B. S. Rana (unpublished) B. S. Rana (unpublished) Pandey and Singh (1984) Pandey and Singh (1984)

200 Reported

400

300 biomass

I

1

I

I

I

100

forest

Total aboveground biomass (tons ha-‘)

25.0 40.2 47.2 45.4 39.9

Oak forest

of certain

Singh

(t

ha-’

500

I 600

x2

)

Figure 6. Relationship between total stand biomass estimated in the present study and biomass reported independently for certain forest types. For those basal covers (and hence crown classes) which were not present in the Ladhiya subcatchment, values from other parts of the larger study area were used. The line represents the equation X1 = 23.9097 + 1.0967 X2.

The interreiat~onship between the two sets of estimates indicates a fair amount of agreement (3 = 0.824, p
The research on which this paper is based was funded by the Indian Space Research Organisation, Bangalore. References Attiwill. P. M. and Ovington, J. D. (1968) Determination of forest biomass. Forest Science 14, 13-15. Baskerville, G. L. (1965) Estimation of dry weight of tree components and total standing crop in conifer stands. Ecology 46, 867-869. Braun-Blanquet, 3. (1932) Plant sociology: the study of plant ~ornrnui~~iies.Translated, revised and edited by G. D. Fuller and H. S. Conard. New York: M~G~dw-~i~i. Chaturvedi. 0. P. (19X3) ~i0mas.s structure, ~rodl~~t~~~~~ and fflftrjent cycling in Pinus roxburghii forest. Unpublished PhD thesis, University of Kumaun, Naini Tal. Chaturvedi, 0. P. and Singh, J. S. (19X3) Total biomass and biomass production of Pinu roxburghii trees growing in all aged natural forests. Cunadian Journal of Forest Research 12(3), 6325640. Crow, T. R. (1971) Estimation of biomass in an even-aged stand regression and ‘mean tree’ technique. In Forest biomass studies (H.E. Young, ed.) pp. 3548. Orono, Maine. Crow, T. R. (1976) Biomass and productivity regressions for trees and woody shrubs common to the enterprise forests. In The enterprise radiation forest: radioecological studies (J. Zavitkowski, ed.), pp. 63-67. United States Energy Resource Development Administration Report, TID-26113-p2. Crow, T. R. (1978) Common regressions to estimate tree biomass in tropical stands. Forest Scirmx 24, 1l&114. Green, D. C. and Grigal, D. F. (197X) Generalized biomass estimation equations for Jack pine. .~~~zrzes~)ta Forest Research Notes> NO. 268.

A. K. Tiwari and J.S. Singh

165

Kershaw, K. A. (1973) Quantitative and dynamic plant ecology. London: Edward Arnold. Kira, T. and Shidei, T. (1967) Primary production and turnover of organic matter in different forest ecosystems of the western Pacific. Japanese Journal of Ecology 17, 70-87. MacLean, D. (1981) Timber volume stratification on small-scale aerial photos. Journal of Forestry 79, 739-740. Misra, R. (1968) Ecolog_y work book. New Delhi: Oxford and IBH Publishing Company. Negi. K. S., Rawat. Y. S. and Singh. J. S. (1983) Estimation of biomass and nutrient storage in Himalayan moist temperate forest. Canadian Journal of Forest Research (in press). Ogawa, H., Yoda, K. and Kira, T. (1961) A preliminary survey on the vegetation of Thailand. Nature and Life in South East Asia I, 21-157. Ogawa. H., Yoda, K., Ogino, K. and Kira, T. (1965) Comparative ecological studies on three main types of forest vegetation in Thailand. II. Plant biomass. Nature and Life in South East Asia 4, 49-80. O’Neill and De Angelis. D. L. (19X0) Comparative productivity and biomass relations of forest ecosystems. In Dynamic properties of forest ecosystems (D. E. Reichle, ed.) pp. 41 l-449. Cambridge: Cambridge University Press. Oosting, H. J. (1953) The study of plant communities: an introduction to plant ecology. San Francisco, California: W. H. Freeman and Co. Pandey, A. N. and Singh, J. S. (1984) Mechanism of ecosystem recovery: a case study. Journal of Ecology (in press). Rawat, Y. S. (1983) Plant biomass, net primary production and nutrient cycling in oak forests. Unpublished PhD thesis, University of Kumaun, Naini Tal. Satoo, T. (1968) Materials for the study of growth in stands, 7. Primary production and distribution of produced matter in a plantation of Cinnamomum camphora. Bulletin of Tokyo University Forest 64, 241-275. Satoo, T. (1970) A synthesis of studies by the harvest method. Primary production relations in temperate deciduous forests of Japan. Analysis of temperate forest ecosystems (D. Reichle, ed.), pp. 55-72. New York: Springer-Verlag. Saxena, A. K. and Singh, J. S. (1982) A phytosociological analysis of woody species in forest communities of a part of Kumaun Himalaya. Vegetatio 50, 3-22. Schmitt, M.D.C. and Grigal, D. F. (1981) Generalized biomass estimation equations for Betula papyrifera Marsh. Canadian Journal of Forest Research 11, 837-840. Shute, D. A. and West, N. E. (1982) Two basic methodological choices in wildland vegetation inventories: their consequences and implications. Journal of Applied Ecology 19, 249-262. Tewari, J. C. and Singh, J. S. (1983) Application of aerial photoanalysis for assessment of vegetation in Kumaun Himalaya. I. Ranibag to Naina peak - Kilbari. Proceedings of Indian National Science Academy (in press). Tiwari, A.K. Tewari, J. C. and Singh, J. S. (1983) Application of aerial photoanalysis for assessment of vegetation in Kumaun Himalaya. II. Kathgodam to Okhalkanda. Proceedings of Indian National Science Academy (in press). Tomar. M. S. and Maslekar, A. R. (1974) Aerial photographs in landuse and forest surveys. Dehra Dun: Jugal Kishore and Co. Whittaker, R. H. and Marks, P. L. (1975) Methods for assessing terrestrial productivity. In Primary productivity of biosphere (H. Lieth and H. Whittaker, eds). New York: Springer-Verlag. Whittaker. R. H. and Woodwell, G. M. (1968) Dimensional and production relations of trees and shrubs in the Brookhaven forest, New York. Journal of Ecology 56, l-25. Yoda, K. (1968) A preliminary survey of the forest vegetation of eastern Nepal. III. Plant biomass in the sample plots chosen from different vegetation zones. Journal of College of Arts and Science, Chiba University, Natural Science Series 5, 277-302. (Revised manuscript received I September 1983)