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Accepted manuscript

PREVENTIVE MEASURES FOR FOREST BIOMASS EXTRACTION

BEYOND INCREMENT IN THE WESTERN GHATS, INDIA

SEEMA S. HEGDE

GREENSPIRIT, No 40, 18 Cross, Sampige road, Malleswaram, Bangalore- 560003 E-mail address: seemahegde78@gmail.com

ABSTRACT

The study was carried out in four selected villages of Uttara Kannada district in the Western

Ghats with an aim to present the annual change in biomass using estimated stock and

extraction, and to estimate the reduced extraction due to conservation practices. The data

collected from a vegetation survey of eight one-hectare sites in the forests, and a biomass

extraction survey involving 247 households were subjected to a sensitivity analysis of

community’s pressure on the forests using the estimates of mean annual increment (MAI) in

biomass quoted by various studies. The results show that at an MAI rate of 2.1 t/ha, on an

average, the annual extraction by the community is 62% of the increment in biomass,

however the values range from 143% to 39% between the villages. A shift to fuel-efficient

stoves and live fences by a little more than a quarter of the surveyed households shows a

reduction in annual biomass extraction to 56% of its MAI, and a potential reduction to 17%

in case all the households adopt conservation practices.

Keywords: Biomass extraction; biomass conservation; mean annual increment; Uttara

Kannada; Western Ghats

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One liner: Shifting to conservation techniques has a huge potential to prevent the biomass

extraction going beyond mean annual increment in the Western Ghats.

Introduction

In the Western Ghats, especially in Uttara Kannada district, agriculture is interwoven

with the forest resources because ‘forest biomass’ (referred to as ‘biomass’ henceforth) is an

integral part of the agricultural inputs. People extract a variety of biomass products on a daily

basis without realising that their every activity of biomass extraction results in meddling with

the forest ecosystem and ultimately reduces the tangible and intangible benefits enjoyed by

them (Mehta et al., 2008). The important biomass products associated with agriculture in the

district are firewood, green and dry leaves, and fencing materials- extraction of which creates

disturbance in forests during the time of extraction and beyond.

Uttara Kannada has undergone degradation of forests over the years, for which

biomass based agriculture (Bhat and Gadgil, 1987) and unlimited free access to forest

resources (Nadkarni et al., 1989) are among the most quoted reasons. A satellite imagery data

of the district between 1995 and 2001 show that the dense forest with the canopy cover of

>40% has declined significantly and the open forest with canopy cover of 10 to <40% has

increased substantially which indicates the degradation of the good forests (Ninan, 2007) and

hence, there is a need for conservation in order to retain the ecological balance. A few studies

have estimated the biomass stock (Bhat et al., 2003; Bhat and Ravindranath, 2011; Prasad et

al., 1987), and a few have concluded that in many villages of the district the annual extraction

of biomass exceeds its annual increment and the community is eating away the stock of

biomass (Bhat et al., 2003; Lele, 1993), but none of the studies has estimated the biomass

conservation potential and hence, the present study aims to bridge this research gap.

Therefore, the study was carried out with an objective to elucidate the annual change in

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biomass by estimating its stock and extraction, and to present the reduction in biomass

extraction due to adoption of biomass conserving techniques.

Materials and Methods

Uttara Kannada district (130.55 to 150.31 N Lat; 740.9 to 750.10 E Long) has 80%

of its total geographical area under forests (Government of Karnataka, 2010) which are

legally classified on the basis of access rights to the community as Reserve Forests (RF) with

restricted access, Minor Forests (MF) with limited access, Village Forests with unquestioned

open access, and betta the privileged forests with only user rights to arecanut (betel nut-

Areca catechu) cultivators (Buchy, 1996; Nadkarni et al., 1989). In the light of this

classification, the present study was undertaken in the four selected villages of Uttara

Kannada district namely Bilur, Kabbe, Manjguni, and Nidgod (Figure 1) which have 75%,

52%, 80%, and 77% of their total geographical area under forests respectively. In order to

estimate the biomass stock and extraction solely from the natural forests, the villages were

selected such that they have only natural forest (RF and/or MF), but not village forest and/or

betta as the presence of latter two forests would reduce the pressure on natural forests.

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Fig. 1: Location of the study villages.

Estimation of biomass stock

As RF and MF stretch to a fairly vast area around the study villages it was impossible

to study the entire vegetation. Hence, following Ravindranath and Premnath (1997), one

hectare area in both RF and MF were surveyed in all the selected villages by marking the tree

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quadrats of size 50 x 50 m in four places. All trees1 in the quadrats were measured for their

girth at breast height (GBH) and data were recorded. Height of the trees was estimated using

the method of eye-estimation with the assistance of fieldwork professionals of Centre for

Ecological Sciences, Indian Institute of Science, Bangalore, India. The total forest area

surveyed was eight hectare comprising of four hectare of RF and MF each. A tree forked into

multiple branches below breast height was considered to have branches A, B, C and so on

from the greatest to the lowest girth respectively, and GBH of each branch was measured

separately, but the tree was treated as a single individual and the longest branch was

considered for measuring height of the tree. Measured GBH of the tree is converted into basal

area (the cross-sectional area occupied by the base of a tree) using the formula GBH2/4π, and

the basal areas of individual trees were added to obtain the basal area of one hectare forest.

Biomass in this study (unless specified otherwise) means above ground tree biomass and is

the product of basal area, height, and wood density of 0.6 g cm3 which is an average oven-dry

mass common to all species in tropical rain forests (Condit, 2008; Whitmore, 1984). Biomass

of the one hectare forest is the sum of biomasses of individual trees in that area. Thus

estimated biomass was extrapolated to the total forest area to arrive at the biomass stock of

the whole village. This procedure was replicated in all the four selected villages.

Estimation of biomass extraction

In each village 50% of the households were selected for study through stratified

random sampling that includes large farmers, small farmers and landless in order to get a

representative data of biomass extraction by the community. The total number of households

surveyed was 247 comprising of 63 large farmers, 93 small farmers, and 91 landless. The

survey was conducted through direct personal interview. The head of the household was

1 A tree is an individual with girth greater than or equal to 10 cm at breast height i.e. 132 cm from the ground

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approached with a pre-tested questionnaire and was interviewed in detail about quantity of

firewood, green and dry leaves, and fencing materials collected annually. The quantities of

these products extracted were added to arrive at the total biomass and was extrapolated to the

total number of households in the village arrive at the biomass extraction by the whole village.

Mean annual increment (MAI)

Since only one-time measurement of the GBH and height of the trees was carried out

under the present study, the MAI estimates quoted by various studies are used in the analysis.

An extensive literature review showed that the MAI estimates for tropical forests of the

Western Ghats range from 0.6 t/ha to 3.1 t/ha. For instance, estimates by Lele (1993) range

from 1.1 t/ha to 3.1 t/ha, estimate by Reddy et al. (1986) is 0.6 t/ha, and by Rai (1984) is 2.0

t/ha. In addition, an estimate by Ravindranath et al. (2006) is 2.0 t/ha on an average for

naturally regenerating species for Karnataka state. Since there are no estimated figures of

MAI available precisely for the locations chosen under present study, a sensitivity analysis of

community’s pressure on forests is conducted using all the above mentioned estimates. Also,

for further analyses, an average of MAI estimate of Lele (1993) (i.e. 2.1 t/ha) is considered as

it is the closest estimate to the estimates given by other studies.

The annual net biomass stock of the forest can be calculated using the estimated biomass

stock, extraction, and MAI values as given below.

[(Existing biomass stock + MAI @ 2.1 t/ha) – Annual biomass extraction] Equation (1)

Estimation of biomass conserved

There were instances of farmers’ switchover to biogas and/or fuel-efficient stoves,

popularly known as ASTRA stoves which are developed by ASTRA (Application of Science

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and Technology for Rural Areas) department of Indian Institute of Science, Bangalore. Also

there were instances of farmers’ shift from traditional fences to live fences by planting

Gliricidia species along the hedges of agricultural land. Among the surveyed farmers, the

farmers who had shifted to biomass conserving practices were interviewed for their biomass

dependency before and after the shift in order to estimate the reduction in biomass extraction

after the adoption of conservation techniques.

The annual net biomass stock after shifting to conservation techniques is estimated using the

below given equation.

[(Existing biomass stock + MAI @ 2.1 t/ha) – (Annual biomass extraction – Annual biomass

saved)] Equation (2)

Results and Discussion

Biomass based agriculture and low adaptability to biomass conservation techniques

are among the major reasons for forest degradation in Uttara Kannada. Since biomass

extraction for agricultural purposes is happening continuously over the years, the gradual

change it is bringing in its stock is mostly unnoticed. The stock and extraction of biomass,

annual change in biomass, and the impact of conservation practices on biomass extraction are

presented in the following sections.

Biomass stock

Analysis of the data collected from the vegetation shows that RF has greater biomass

compared to that of MF (Table 1). On an average the estimated biomass of RF is 2.74 times

greater than that of MF, and ranges from 1.20 times in Kabbe to 6.25 times in Manjguni. This

shows a huge variation in the degree of exploitation of RF and MF; only MF is severely

degraded in Manjguni, but both RF and MF are degraded in Kabbe (Table 1).

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Table 1: Biomass stock in the study villages.

Village Forest areaa

(ha) Estimated biomass (t/ha) Extrapolated biomass (t)

RF MF Total RF MF Total RF MF Total Bilur 303.54 82.02 385.56 374.81 151.32 526.13 113770 12411 126181Kabbe 172.38 5.00 177.38 55.95 46.44 102.39 9645 232 9877 Manjguni 323.32 142.78 466.10 250.90 40.16 291.06 81121 5734 86855 Nidgod 472.95 151.55 624.50 91.05 44.58 135.63 43062 6756 49818 Total 1272.19 381.35 1653.54 772.71 282.50 1055.21 247598 25133 272731Note: a Source- Office of the Deputy Conservator of Forests, Sirsi Division, Uttara Kannada district

Biomass extraction

Dependency of villagers on various biomass products is presented in Table 2. It is

clear that firewood is the most extracted biomass followed by green leaves, dry leaves, and

fencing material. On an average, firewood constitutes 56% of the total biomass extracted per

household, and total biomass extraction per household is highest in Kabbe and lowest in

Manjguni (Table 2).

Table 2: Biomass extraction in the study villages.

Village Total No. of

HH

No. of HH

surveyed

Annual biomass extraction (t)

Firewood Green leaves

Dry leaves

Fencing material

Total biomass

Extrapolated total biomass

Bilur 98 52 195 (3.7)

59 (1.1)

25 (0.5)

6 (0.11)

284 (5.5)

535 (5.5)

Kabbe 94 50 161 (3.2)

64 (1.3)

51 (1.0)

6 (0.12)

283 (5.7)

532 (5.7)

Manjguni 123 65 67

(1.0) 98

(1.5) 33

(0.5) 5

(0.08) 202 (3.1)

382 (3.1)

Nidgod 150 80 220 (2.7)

104 (1.3)

50 (0.6)

9 (0.11)

382 (4.8)

716 (4.8)

Total 465 247 643 (2.6)

324 (1.3)

158 (0.6)

26 (0.10)

1151 (4.7)

2165 (4.7)

Note: HH- Households Figures in parentheses indicate annual biomass extracted per household (t)

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Mean annual increment and biomass extraction

The sensitivity analysis of percentage of biomass extraction from the annual

increment to different MAI estimates (in other words, the sensitivity of community’s pressure

on forests to various MAI estimates) is presented in Table 3. With the lowest estimate of

MAI by Reddy et al. (1986) as 0.6 t/ha, on the whole the annual biomass extraction is 218%

of the MAI. Even if we assume the rate of increment in biomass stock to be as high as 3.1

t/ha as given by Lele (1993), on an average, the villagers are eating away 42% of it every

year. On the other hand, if the average of estimates provided by Lele (1993) (i.e. 2.1 t/ha) is

considered, on the whole, 62% of the MAI in biomass is extracted in a year and Kabbe is the

worst exploiter with 143% (Table 3) which is because the total forest area in Kabbe is less as

compared to other villages and hence, its MAI in absolute terms turns out to be low. But

unfortunately even with the low MAI, the annual biomass extraction per household is the

highest in Kabbe (Table 2) which is leading to further forest degradation.

Table 3: Sensitivity of biomass increment and extraction in the study villages to

different MAI estimates.

Village

Estimated mean annual increment in biomass (t) and extraction from it (%)

Reddy et al. (1986)

0.6 t/ha

Lele (1993)

1.1 t/ha

Lele (1993)

3.1 t/ha

Lele (1993)a 2.1 t/ha

Rai (1984), R’nath et al. (2006)b

2.0 t/ha

Bilur 231

(231) 424

(126) 1195 (45)

810 (66)

771 (69)

Kabbe 106

(500) 195

(273) 550 (97)

372 (143)

355 (150)

Manjguni 280

(137) 513 (75)

1445 (26)

979 (39)

932 (41)

Nidgod 375

(191) 687

(104) 1936 (37)

1311 (55)

1249 (57)

Total 992

(218) 1819 (119)

5126 (42)

3472 (62)

3307 (65)

Note: Figures in parentheses indicate percentage of annual biomass extracted from the increment. These values are calculated using extrapolated total biomass figures from Table 2. a Average of Lele (1993) i.e. MAI estimates 1.1 t/ha and 3.1 t/ha b R’nath et al. (2006) represents Ravindranath et al. (2006)

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Impact of conservation practices on biomass extraction

With the advent of Joint Forest Management programme in Uttara Kannada in the

early 1990s, awareness creation about biomass conservation started with the distribution of

ASTRA stoves and subsidising biogas plants. There are also instances of villagers shifting to

long lasting live fences from yearly construction and maintenance demanding traditional

fences. Table 4 presents the details of biomass saved in terms of firewood and fencing

material. Out of the 247 surveyed households, 27% of the households have adopted ASTRA

stoves and/or biogas, and 38% of the households have shifted to live fences. These

households which have adopted either one or all of these conservation techniques together

have demonstrated a reduction in biomass consumption by 60%, Nidgod being the largest

biomass conserver followed by Kabbe (Table 4).

Table 4: Biomass saving in the study villages.

Village Total firewood

collected (t/year)

Total fencing material

collected (t/year)

Total biomassa collected (t/year)

Total biomass

saved (t/year)d

Net biomass stock (t/year)

Before Afterb Before Afterc Before After Beforee Afterf

Bilur 81 47

(25) 3

0.00 (38)

84 47 37

(44) 126456 126493

Kabbe 172 66

(40) 7

0.00 (40)

179 66 113 (63)

9717 9830

Manjguni 74 29

(32) 3

0.00 (37)

77 29 47

(62) 87452 87499

Nidgod 35 12

(16) 10

0.00 (39)

45 12 34

(74) 50413 50447

Total 362 154 (27)

23 0.00 (38)

385 154 231 (60)

274038 274269

Note: a Sum of firewood and fencing material b Figures in parentheses indicate percentage of households using fuel-efficient devices to total number of surveyed households c Figures in parentheses indicate percentage of households using live fences to total number of surveyed households d Figures in parentheses indicate percentage savings in biomass due to biomass conserving practices e Values calculated using equation (1)

f Values calculated using equation (2)

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The common notion that RF in Uttara Kannada are in better state of health than MF

on an average (Gadgil 1987; Nadkarni et al., 1989) is although true, may not hold good when

the individual villages are considered. Even though RF is a closed access to the community,

there are evidences of community extracting biomass from it (Mani, 1985; Murali et al.,

2004) because restrictions on access to it exist only on the paper, but in reality are not strictly

enforced (Shrinidhi and Lele, 2001). Moreover, unequal allocation of area under RF and MF

makes villagers to exert pressure on RF despite of legal restriction as in the case of Kabbe

where the area under MF is merely 2.82% of the total forest area of the village. In addition,

location of the habitation in the village can also be a factor determining from where the

biomass is extracted. This is because villagers often do not distinguish between the legal

classifications, but collect biomass products from the forests nearer to their habitation. For

instance, MF in Manjguni and RF in Nidgod are located closer to habitation, and it was found

that most of the biomass needs are met from those forests and thereby leading to low biomass

in those areas. Therefore, present study is in line with the findings of Bhat and Ravindranath

(2011), Karanth et al. (2006) and Parthasarathy (1999) who argue that human interference

would have negative impact on biomass, tree and species density. Furthermore, proximity of

a village to a town also has an impact on the biomass of that village. For instance, in Kabbe

both RF and MF are degraded because of the pressure by the neighbouring town Sirsi. A

conversation with the villagers in Kabbe brought forth the fact that people from Sirsi town

extract biomass from Kabbe forests.

On the contrary, biomass conservation techniques like installation of ASTRA stoves

and biogas, and shifting to live fences have shown a reduction in the biomass consumption in

Uttara Kannada. Live fences are universally known for not only reducing the fencing material

extraction, but also for providing fodder, firewood and foliage (Falvey, 1982; Simons and

Stewart, 1994). Studies by Hegde (1986) and Ramachandra et al. (2000) about the use of

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ASTRA stoves in Uttara Kannada have provided evidences of reduction in the firewood use

by 55% and 27.45% respectively. Supporting these findings, in the present study the analysis

has shown that, assuming MAI rate of 2.1 t/ha, with a little more than one-fourth of the

surveyed households adopting either any one or all of the conservation techniques, there is a

biomass saving of 231 t/year (Table 4), and thereby the annual extraction of biomass from its

increment has been brought down from 62% (Table 3) to 56% (using Table 2 and 3).

Furthermore, an extrapolation of biomass saving by sampled households to all households in

the study villages shows a potential saving of 1,559 t/year which could further bring down the

extraction from the annual increment to 17% at an MAI rate of 2.1 t/ha.

Conclusion

In conclusion, when only a little over a quarter of the households shifting to

fuel-efficient stoves and live fences can bring down the extraction of biomass from its MAI

by 6%, there could be a huge potential to save biomass if all the households in the villages

shift to conservation practices. At present, on an average, extraction has not exceeded the

MAI in biomass at the rate of 2.1 t/ha, but cannot be expected to remain the same in the

future due to expansion of agriculture and increase in population. Since biomass is an

absolute necessity of the villagers, they cannot be deprived of its use completely and hence,

shifting to conservation techniques is strongly suggested to save forests.

Acknowledgements

The author thanks Dr. D.M. Bhat and Dr. R.V. Dadibhavi for their valuable suggestions

during the research period, and an unknown reviewer for his/her comments that helped

improve the manuscript.

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