“VALUATION STUDY OF MANGROVE PLANTATIONS … · · 2016-05-19International Union for Conservation of Nature, Pakistan . Table of Contents ... non-timber forest products from mangroves

“VALUATION STUDY OF MANGROVE

PLANTATIONS ESTABLISHED Under Sindh Coastal Community Development Project (SCCDP)”

Akhtar A. Hai (Consultant-IUCN)

June 2013

International Union for Conservation of Nature, Pakistan

Table of Contents

EXECUTIVE SUMMARY

1. INTRODUCTION

2. LITERATURE REVIEW

2.1 International Evidences

2.2 Evidence from Indus Delta

2.3 Focus Group Discussion

3. BACKGROUND OF THE INDUS DELTA

4. SOCIO-ECONOMIC PROFILE OF THE RESPONDENTS

5. ECONOMIC VALUATION OF MANGROVES – METHODOLOGY

5.1 Estimating the Willingness to Pay

5.2 Economic Valuation of Mangroves - Empirical Valuation

5.2.1 Estimating Direct Values

5.2.2 Indirect Value

5.2.3 Non Use Value

5.3 Derivation of Total Value of Mangroves Forest

5.4 Comparative Estimates on Valuation of Mangroves

5.5 Distribution of Total Economic Benefits of Mangroves Annually

5.6 Derivation of Benefit Cost Ratio and IRR

CONCLUSIONS AND RECOMMENDATIONS

REFERENCES

ANNEXURE

Research Team

1. Mr. Akhtar A. Hai Development Economist & Team Leader

2. Dr. Ambreen Fatima Econometrician

3. Mr. Arsalan Ahmed Research Officer

4. Mr. Ali Rashad Research Officer

5. Mr. S. Qaisar Ali Anjum Project Secretary

(i)

EXECUTIVE SUMMARY

- The on-site (i.e. coastal environment) is interrelated with off-site (open sea

environment) and jointly appear as a great natural resource on which the

coastal communities depend heavily for their livelihood.

- The current state of economic and social development in coastal areas of

Sindh, is extremely poor. These communities remain isolated in receiving their

share in the economic development taking place in the country.

- The current situation in the Indus delta amply demonstrates the level of

dependence of coastal population on mangroves for their livelihood (directly

and indirectly).

- However, if such an exclusive dependence continues in the long run, it may be

productive or unproductive for mangroves based on how this great natural

resource is valued by the coastal communities. Such an understanding (or lack

of it) would be pivotal to the long run sustainability of mangroves in the

region.

- Internationally, awareness about the mangrove has been promoted through

number of studies, but a small number of studies estimated and identified the

economic value of mangrove ecosystems. Sathirathai (2000) studied for the

area of SuratThani, South of Thailand.

- Emerton, L., and Kekulandala (2003) found out the total economic value of

mangroves, in the region of Muthurajawela wetland in Sri Lanka,

asUS$ 7,567,604 per year.

- IUCN (2003) for Kala Oya in Sri Lanka shows the economic benefits of

mangrove ecosystems by adding up the direct and indirect benefits. The direct

use value of mangrove work out to be US$ 8,956/ha/year.

- For Pakistan, FAO, WWF, Forest Department and IUCN have conducted

studies for the assessment of mangroves area especially for the region of Indus

delta. These studies highlight that mangroves are serving as breeding grounds

for shrimp and fish species. Sindh Coastal Development Authority and other

organization had replanted about 80,000 ha of mangroves along the Sindh

coast since 1985.

- According to the IUCN (2003) in Sindh coastal area around 1,06,588 hectares

of land have been lost to sea intrusion since 1963, and this will increase

to1,33,235 in next ten year due to this sea intrusion. The estimated agriculture

losses for five years 1995-2000 due to sea intrusion was estimated around

Rs.265.7 million.

- A number of Focused Group Discussions (FGD’s) were conducted to

understand the community relationship with mangroves. According to the

participants the reasons behind the reduction are: reduced supply of sweet

water and sediments, over cutting of mangroves for sale of timber, fuel wood

and poles for housing. Participants also criticized decision of the government

about restriction on the Indus water flows at Kotri barrage in 1960 and held

that responsible for the reduction in mangroves cover.

(ii)

- The average family size of all sampled households was 11.27, where the

minimum of 10.44 was for Shah Bunder and maximum of 13.55 for Kharo

Chhan. It is interesting to note that in Shah Bunder where the average family

size was lowest (i.e. 10.44), the average number of males (i.e. 3.46) was

higher than the average number of females (i.e. 3.21) and the associated

average number of children was lowest.

- The levels of education (in terms of years completed) of the respondents

shows that nearly two-third of the 160 households had no education. The

information on highest level of education completed within the family, the

average number of those who completed 12 years or more was 3.69 for Kharo

Chhan, 3.65 for Shah Bunder and 3.4 for Keti Bunder.

- The scale of devastation in these coastal talukas as a result of continuous sea

intrusion has resulted in the loss of fertile agricultural land. Currently,

agricultural land ownership has reduced along the coastal belt of Indus delta.

Only a fraction of land holding is brought under cultivation owning to the fact

that the supply of fresh water has reduced considerably.

- The ownership of livestock was limited in the area. Only 58 households out of

160 (i.e. 36 percent) were keeping livestock. The raising of camels was

reported only by 10 households with 7 from Shah Bunder.

- The pattern of housing construction is similar across the talukas. The

proportion of pacca housing structure in Keti Bunder was twice the proportion

in Kharo Chhan and Shah Bunder. The fact that over 48 percent of houses

were established in huts provides ample evidence of poverty levels prevailing

in coastal areas.

- The situation of housing and provision of civic amenities in the coastal area of

Indus delta, so depicted, reveals extremely poor quality of life. Under this

scenario, it is expected that these coastal communities depend in part on the

non-timber forest products from mangroves to derive a number of direct and

indirect benefits for their livelihood.

- A common view of the area reflects the fact that Keti Bunder has retained its

historical location as well as has acted as a center for various developmental

activities despite facing a number of threats in the form of natural as well as

man made disasters. In contrast, Shah Bunder could not sustain the devastation

of sea cyclone of mid 1990’s and as a result its taluka headquarter was shifted

to another location in the upstream area, its population was scattered and as

such currently the location of Shah Bunder’s proper settlement is lost to

antiquity. As a consequence, Shah Bunder has yet not reversed its position

undermining its fisheries catch and marketing and other economic

development prospects.

- The fisheries as a source of income was highest in Keti Bunder where 29 out

of 40 households (72.5 percent) had it as primary occupation. In case of Kharo

Chhan it was 52.5 percent and in Shah Bunder it was 43.8 percent, of the

sampled households. The highest participation was in fisheries activities all

across.

- Over 90 percent of the respondents reported visiting mangroves either

exclusively to collect forest products like fuel wood, fodder, catching fish

crabs, shrimps, honey, herbs, poles for use in house construction, animal

(iii)

browsing, or to take rest and recreation while going towards open sea for

fishing.

- The highest number of visits to mangroves was reported by respondents of

Keti Bunder i.e. 11.38 visits per month. It can thus be argued that fishermen

(or coastal population) of Keti Bunder visits mangroves more frequently than

those visiting from other talukas.

- When inquired about changes in mangroves cover during the last 50 years or

so, a vast majority (nearly 90 percent) reported that the cover has reduced or

destroyed during this period. The respondents indicated different causes for

this destruction of mangroves. A vast majority (41.8 percent) regarded sea

intrusion and cyclone as the main cause of destruction. Out of 66 respondents,

50 were from Shah Bunder.

- When inquired about the reasons for improvements in mangrove, nearly two

thirds (i.e. 105 respondents) regarded new plantation and another 12.7 percent

regarded proper care of mangroves as the main factors behind the

improvements in mangroves cover. Only 10 respondents argued that no

change took place in the status of mangrove cover (Table 4.15(b)).

- Based on the responses of sampled households towards different socio-

economic aspects, it becomes clearer that local community heavily depends on

fisheries as their exclusive source of livelihood. The incomes are largely

generated from fishing whereas the non-fishing occupations generate over one

third of their incomes.

- The data obtained through primary survey for this study shows that wood

obtained from the mangroves forest is not only used by households for

domestic purpose (non-marketed) but also for commercial purpose as well.

Sale of fuel wood is also generating livelihood for the households (marketed).

Average value of the wood used as fuel domestically was worth Rs.795 per

month while the fuel wood marketed was worth Rs.549 per month.

- Sample survey also indicates huge economic dependence of household on

shrimps, crabs and shell fishes. On average households were earning

approximately Rs.20,175 per month (2997 from crabs + 13946 from shrimps +

3232 from shell fishes).

- The situation is not much different for sale of crab as well. People of Keti

Bunder were on average earning around Rs.5000 per month from the sale of

crab. People of KharoChhan reported were earning almost Rs.2600 per month

while the people of Shah Bunder were earning only Rs.2000 per month from

the sale of crab.

- As the fish catch in the Indus delta is highly dependent on the mangrove

ecosystem, the importance of mangrove in sustaining the productivity of

on-shore and off-shore fisheries cannot be ignored.

- On average, a household was willing to pay around Rs.2,518 per month for the

protection and development of mangrove forest. Keti Bunder being the more

economically developed taluka among the three talukas surveyed, shows that

each household was willing to pay around Rs.4,145 per month.

- The three talukas of Indus delta comprising 254,000 individuals, is supported

by mangroves economically as well as ecologically. Despite massive

(iv)

degradation during the last 70 years or so, caused by reduced flow of sweet

water and sediments to the deltaic region, and increased dumping of untreated

industrial effluents into the sea, the mangroves have sustained and shown

resilience to natural and manmade threats towards its existence.

- The flow of benefits (directly and indirectly) to local communities are

significant. This study tends to show those streams of benefits extended to

communities. The seemingly different streams of on-shore and off-shore

benefits are in fact parts of a natural and integrated system where mangroves

act as a conduit in diversifying the natural production system. In pure

economic terms mangroves act as a production function which yields multiple

products.

- The biodiversity established and sustained by mangroves are its critical

strength. However, this strength has been subjected to tests of intrigue and

innocence over time i.e. the situations when humans knowingly and

unknowingly exert pressures on this great natural resource for their short term

gains.

- The detailed household survey, consultations with stakeholder and available

literature, total value (both economic and non-economic) of mangroves was

computed. The values are represented net of costs incurred by the sampled

households. It portrays a total value of 3.27 Billion Rs. (US$ 32.7 Million) per

year for the whole region (i.e. aggregation of 3 talukas).

- The comparative figures for mangroves estimated for Thailand, Sri Lanka, and

Kenya during the last decade or so, reveal higher values for Pakistan’s

mangroves on Indus delta. Given the higher productivity of fish biomass in the

Arabian Sea in relation to the other oceans of the world, the higher levels of

Pakistan’s potentials not unexpected.

- The study has estimated detailed account of different products particularly

non-timber forest products collected from on-shore locations as well as fish

catches in the off-shore locations.

- The estimated levels seem high in relation to comparable locations in the

region of Asia and Africa. The high productivity potentials, in the Arabian Sea

given its biomass of fish which has highest productivity level in the world,

needs to be harnessed through modernization of the system of fish catch and

its re-generation, scientific processing and marketing in order that the export

potentials of marine products are enhanced, local employment is generated

and poverty levels are reduced.

- In addition to above the communities’ knowledge and interests towards

mangroves needs to been enhanced. Through development of eco-tourism in

the area the local community can participate with much bigger role towards

the sustenance of mangroves and the ecology.

- The socio-economic profiles of the coastal communities show significant

levels of social deprivation which is more severe than income poverty in the

area.

- Whereas the main source of livelihood of communities rests with fishing, their

dependence over mangrove forest in extracting direct and indirect benefits is

central to the overall living standards.

(v)

- The distinction between on-site and off-site activities also reveal the pivotal

and harmonious position mangroves play in extending flow of benefits within

the on-farm and off-farm areas.

- However, such an exclusive reliance on mangroves requires efforts to

conserve and develop mangroves which have long been affected by restricting

flow of sweet water and silt to the deltaic region.

- The historically reduced water supplies to the region and its impact on

mangroves when viewed in the context of all international conventions,

agreements and framework, establishes the right of the coastal communities

for compensation. It is suggested that if 0.10 percent of the annual value added

of Pakistan’s producing sectors (i.e. agricultural and manufacturing) is

allocated for the development and sustenance of mangroves and the coastal

communities of Indus delta, it would create a fund of Rs.10 billion annually.

- The economic analysis of the study reveals a benefit cost ratio of 3.56 which is

quite significant.

- The analysis also reveals an internal rate of return IRR of 25 percent which is

considered suitable for investments.

1

1. INTRODUCTION

This study focuses on the valuation of mangrove plantations established under Sindh

Coastal Community Development Project (SCCDP). It was carried out during the

period February-May, 2013 and was financed by ADB and administered by IUCN

Pakistan. It uses primary data, collected from three talukas (sub-Districts) of Thatta

District of Sindh namely Keti Bunder, Kharo Chhan and Shah Bunder, where

household survey of coastal communities and discussions with different stakeholders

(including Focus Group Discussion) were conducted to assess the local communities’

dependence on mangroves. It also uses literature and secondary data to cover

non-economic factors that impact on mangrove sustenance. In the process, the study

made estimates on different streams of benefits and costs (direct, indirect). In addition

to use values, non-use values were also computed e.g. willingness to participate (in

mangrove plantation) was also computed.

The on-site (i.e. coastal environment) is interrelated with off-site (open sea

environment) and jointly appear as a great natural resource on which the coastal

communities depend heavily for their livelihood. The current state of economic and

social development in coastal areas of Sindh, is extremely poor. These communities

remain isolated in receiving their share in the economic development taking place in

the country. In real term, the inhabitants of coastal areas of Indus delta have

continuously paid heavy cost in terms of the after effects of irrigation/agricultural and

industrial development in the rest of the country. The cost could easily be observed in

terms of reduced flow of sweat water and sediments to the delta, and untreated

effluents of the industrial and trading activities thrown into the delta have jointly put

adverse effects on the sustenance of mangroves.

Given the fact that the coastal areas have roundly been threatened by this perplex

situation where the flows of sweet water and sediments have been reduced, and flows

of untreated effluent from industrial sector have increased, a reversal in the pattern of

flows is required for the overall stability of the coastal area. Thus the damages to the

coastal ecology were doubled whereas the level of compensation in terms of improved

resettlement of affecties, stabilization of mangroves eco-system and improved living

environment for the inhabitants were not given any serious attention. A precise

estimate suggest that even 0.1 percent of the current value added of the producing

sector of Pakistan (i.e. Manufacturing and Agricultural sectors) is allocated towards

development of these coastal areas, particularly in the Indus delta which has been

primarily affected and where 95 percent Pakistan’s mangrove forests are located, the

resulting amount is around Rs.10 billion annually. Such an allocation could be used in

programmes aimed at conserving mangroves through replanting of forest, appropriate

treatment of industrial effluent, desalination plants, use of wind and solar energy and

development of marine fisheries. These developmental efforts could, at least in part,

compensate for the loss the local people and natural habitat have been incurring as a

result of irrigation and industrial sectors development in the upstream over time. The

current situation in the Indus delta amply demonstrates the level of dependence of

coastal population on mangroves for their livelihood (directly and indirectly).

However, if such an exclusive dependence continues in the long run, it may be

productive or unproductive for mangroves based on how this great natural resource is

2

valued by the coastal communities. Such an understanding (or lack of it) would be

pivotal to the long run sustainability of mangroves in the region.

In this back drop, this study focuses on estimating valuation of mangroves in the Indus

delta. The stream of benefits extended by mangroves (directly and indirectly) in the

coastal and off shore areas, as well as those common benefits and costs which cannot

be attributed at individual level, have been included in the estimation of valuation of

mangroves.

3

2. LITERATURE REVIEW

The available literature on the socio-economic aspects of mangrove forest is far and

few. In this section we have provided evidences from both international and nationally

available perspective – mostly on Indus delta.

2.1 International Evidences

Internationally, awareness about the mangrove has been promoted through number of

studies, but a small number of studies estimated and identified the economic value of

mangrove ecosystems. Sathirathai (2000) studied for the area of SuratThani, South of

Thailand. He estimated the total economic value of mangroves as US$ 1,422.48 per

household per year for the area which consists of 1,120 ha of mangroves. According

to the study the net returns from off shore is US$ 8.99/ha/year from mangroves. Also

the value of shoreline protection estimated approximately to

US$ 4,778.66(US$ 239/ha/year).

Emerton, L., and Kekulandala (2003) found out the total economic value of

mangroves, in the region of Muthurajawela wetland in Sri Lanka, asUS$ 7,567,604

per year. The study has divided the economic value of mangroves into flood

attenuation (5,057,396US$), industrial waste water treatment (US$ 1,690,729)

agricultural production (US$ 315,521), support to downstream fisheries

(US$208,333), firewood (US$ 82,917), fishing (US$65,208), leisure and recreation

(US$ 55,000), domestic sewage treatment (US$ 45,000), freshwater supplies for local

populations (US$ 39,375) and carbon sequestration (US$ 8,125).

IUCN (2003) for Kala Oya in Sri Lanka shows the economic benefits of mangrove

ecosystems by adding up the direct and indirect benefits. The direct use value of

mangrove work out to be US$ 8,956/ha/year. The value of mangroves in reducing the

pollution is estimated at Rs.552,960/year. The study also estimated Rs.20 Million as

the shore line protection value, Rs.11.27 million as carbon sequestration value,

Rs.813,930 in terms of flood water control, Rs.193,450 for sea intrusion value. The

government authorities of Kala Oya in Srilank also calculated the value of mangrove

ecosystem at Rs.215,434,350.

IUCN (2007) studied the economic value of mangroves through benefits availed from

the mangroves (fish, shrimp and fuel wood etc). According to the study the total

economic value was Rs.119,438 (US$ 1,171) per household per year. The direct use

of mangrove products (gross value) per household was Rs.9,953 per month. The study

also revealed that the total benefits availed by poor, medium and high income

households were 42 %, 37% and 21%, respectively. The value of mangroves as sea

protective barrier was US$ 392.5/ha and for fish breeding functions it was US$ 1,

77.9 to US$ 474.3/hectare.

United Nations Environment Programme (UNEP) study of 2011 for the region of

Gazi Bay, Kenya to estimate the economic valuation of mangroves in that area

(spread over 620 hectares). The study had included many direct and indirect uses of

mangroves and estimated the economic value for each benefit, by summing all. It

gives the total economic value of US $1,092.30. According to the study, the economic

value derived from mangroves included; fishery (US$ 44.00), wood (US$ 20.80),

4

apiculture (US$ 14.70), aquaculture (US$ 4.80), education &research (US$ 184.40),

tourism/recreation (US$6.50), carbon sequestration (US$ 126.00), shoreline

protection (US$91.70), biodiversity value (US$ 5.00) and existence value

(US$ 594.40).

Patrik (1999) studied the ecological basis for economic value of seafood production

supported by mangrove ecosystems. According to the study the annual market value

of fisheries (that use mangroves as habitat) per hectare of mangroves ranges from

US$750 to 11280. Gujja (1996) showed that the mangroves worked as life-support

systems for sustaining mollusk, fish, and shrimp aquaculture. Robertson (1992)

reviewed some other function of mangroves such as supply of organic carbon and

nutrients near the shore line by the litter (leaves) of mangroves. An estimate shows

that the dissolved material fluxes between mangroves and near shore areas was

379 kg/ha/year.

2.2 Evidence from Indus Delta

For Pakistan, FAO, WWF, Forest Department and IUCN have conducted studies for

the assessment of mangroves area especially for the region of Indus delta. These

studies highlight that mangroves are serving as breeding grounds for shrimp and fish

species. Sindh Coastal Development Authority and other organization had replanted

about 80,000 ha of mangroves along the Sindh coast since 1985. According to Baig

(2010) per hectare value of mangroves in Pakistan exceed to US$8,000. Shamsul

(2012) studied that around 200 fish species are found in the Indus delta region and

these mangroves provide a natural habitat to these fish species. He estimated

economic value of mangrove around US$ 750 to 16750 per hectare for annual

production of marine fish/shrimps. Shamsul (2012) also showed that the mangroves

are important for the shore line protection. According to the study on 20 May 1999 a

sea cyclone killed 6,200 people after making landfall at Shah Bunder. Mangroves can

reduce these losses by providing the supportive barrier against tsunami.

Other important benefit of the mangroves is that it protects the land from sea

intrusion. According to the IUCN (2003) in Sindh coastal area around 1,06,588

hectares of land have been lost to sea intrusion since 1963, and this will increase

to1,33,235 in next ten year due to this sea intrusion. The estimated agriculture losses

for five years 1995-2000 due to sea intrusion was estimated around Rs.265.7 million.

The losses in fisheries were estimated atRs.3.15 million/year. The study revealed that

the presence of mangroves near the shoreline can controls these damages. But

unfortunately mangroves forest of value around Rs.45 million had been lost in the

period of 1995-2000.

According to the study titled “MANGROVES OF PAKISTAN” (IUCN, 2005 a), in

the area of mangroves around 100 species of fish have been recorded and 46 species

of them were fingerling or young stages while 52 in sub-adult or adult stages. The

study explained several reasons for the destruction in mangroves around the coastal

area of Pakistan. One of the reasons was the decrease of fresh water from the Indus

River and other seasonal rives. The reduced supply of fresh water reduced the delta

area from 26,000 sq.km.to 1190 sq.km. Also feeding of mangroves to camels was

recorded in this area at 120,000 kg / day.

5

Khalil (1999) studied the economic aspects of mangroves for the region of Sindh.

According to her, along the 240 km of coastline 600,000 acres of area is covered by

mangroves, in which approximately 40% of the mangroves are in entire tidal belt and

10% in theIndusdelta fan. The study showed that the mangroves ecosystem had

supported the shrimp fishery around the coastal area which has the value of US$100

million/year. Mangroves also protect Coastal area from the erosion. Khalil also

highlighted the major causes for destruction of mangroves; the reduction in water

current flow from 200 million tons to 50 million tons affected the amount of

sediments supply that directly damaged the mangroves. Also mangroves are used as

the feeding ground for the camels and cattle. The estimated consumption of

mangroves as fodder in the delta was 2,560,000 kg/year. The wood from mangroves,

used as fuel, was estimated around 11,352,240 kg/year which had approximate value

of Rs.15.2 billion/year.

Another study by IUCN (2005b) for Preliminary Compendium of Coastal and Marine

Protected Areas in Pakistan shows that currently the Indus delta region is spread over

the area of 600,000 hectares and consists of 17 major creeks, some minor creeks, mud

flats and fringing mangroves. The area of delta is very arid and the average annual

rainfall is approximately 200mm. In the past the mangrove ecosystem grew due to the

normal supply of water from the Indus River but due to the reduced water flow from

150MAF to 10MAF, the mangroves of these areaswas affected heavily. Mangroves

proved a natural habited to the fisheries and birds, due to presences of these

mangroves around 200 species of fishes had been reported in Indus delta region. .Also

52 species of water birds had been seen in the Indus delta region, most of these bird

species were using mangroves as their habitat. Unfortunately mangroves in the west

coastal area decreased from 43% to17% in 2003.

2.3 Focus Group Discussion

A number of Focused Group Discussions (FGD’s) were conducted to understand the

community relationship with mangroves. FGD’s were held both at urban and rural

areas of the three talukas. Participants were chosen in such a manner that their

participation reflected the view of all the stakeholders having relation with mangrove

forest. The group included fishermen, landlord, farmers, businessmen, shopkeepers,

local politician, social workers, teachers and officials of fisheries and forest

departments.

First, their view about the changes taken place in mangroves area over the last 50

years was recorded. Their response was similar and according to the official figures.

All the participants answered that the area of mangroves have declined substantially

over the last 50 year. According to the participants the reasons behind the reduction

are: reduced supply of sweet water and sediments, over cutting of mangroves for sale

of timber, fuel wood and poles for housing. Participants also criticized decision of the

government about restriction on the Indus water flows at Kotri barrage in 1960 and

held that responsible for the reduction in mangroves cover. Some stakeholders also

highlighted that the cutting of the mangroves is due to the unawareness among the

community about its importance. Another reason came under discussion was owners

of camels were using mangroves for camel grazing.

6

Second, the participants were asked to rank the external factors for the destruction of

mangroves in the area. The participant ranks these in the following order of

significance.

1. Sea cyclone

2. Sea level rise

3. Lack of sweet water

4. Illegal fishing nets

5. Commercial cutting of mangroves forest

Third, its importance was discussed to get an overview of the participant’s knowledge

about mangroves. Participants argued that mangroves are very necessary for the

coastal development because these protect community from sea cyclone.

Fourth, the discussion was also done on the effort put forward by different

organization for the development of mangroves. According to the participants a

number of efforts were made by the different organization to reduce the losses in the

area of mangroves. The major work is done by the United Development & Welfare

Organization. They declared area under mangrove as no cutting zone due to which

about 300 hectares of the mangroves is now safe from cutting. Participants also

pointed out that IUCN and the Forest Department are working on the new plantation

of the mangroves that will increase the area of mangroves. Further to

this,theparticipants stressed that the appointment of forest guards will improves the

implement of the No Cutting Zone Law. According to the group, the major

organizations that worked for the preservation of mangroves includes; WWF, IUCN,

NRCP, Aga Khan Foundation, Forest Department and other Local NGO`s. these

organizations are creating awareness in the local community about importance of

mangroves.

Fifth, the group also shed light on the benefits that they are obtaining from

mangroves. They drew attention towards many benefits such as mangroves providing

nursery to the fishes, and serving as habitat for the breeding of other species as well. It

also protects the coastal area from the destruction of sea cyclone - by acting as the fist

line of defense against the sea cyclone. Some participant also pointed out that the

community is using wood from mangrove forest as fuel. The wood from mangroves

produced less smoke as compared to other wood. The community is also using wood

(poles) for building houses. According to the participants the mangroves serve as a

breading place for fish, crabs and prawns that provide monetary benefits to the

fisherman. Small amount of honey and marori production were also been reported by

the participant. Few members also reported that they are hunting a snake named

“Lundi” from the mangroves, used in medicine by the community.

Finally the team asked the participant If the community is willingness to participate in

the improvement or plantation of mangroves? The members responded that the

community can spend 1 - 4 days in a month working for the improvement and

plantation as voluntary labour. According to the members, the community can provide

limited financial contribution for the development of mangroves but the people of the

community are generally not financially strong enough. They emphasized that if

government or NGO’s offer monetary compensation as incentive for mangroves

protection then a large number of community members will participate in mangroves

development.

7

3. BACKGROUND OF THE INDUS DELTA

The Indus delta is a triangular fan-shaped delta and covers around 3 million hectares

area of Sindh.PresentlyIndusdelta occupies an area ofaround 600,000 hectares.The

area compromises 17 major creeks and many minor creeks,mud flats and fringing

mangroves (MeynellandQureshi 1993). The mangrove ecosystem of

theIndusdeltaisthelargest area in the arid climate in theworld. According to Memon

(2005) mangrove of delta covers 263,000 hectares area and it is the sixth largest in the

world.

Memon (2005) highlighted a number of benefits from these mangroves forests to the

community. According to Memon, mangroves provide a transition from the fresh

inland waters to the salty Arabian Sea and actsashabitat for numerous species like

fish, shrimp, lobsters and crabs. It also acts as windbreaker and prevents storms from

reaching inland and prevents any coastal land erosion.

However, Memon (2005) has reported that the mangroves found in Indus delta are not

so diverse. The area is mainly composed of Avicennia marina, a species that is highly

resistant to salinity and is capable of surviving in the region's extreme conditions.

Other species found in Pakistan with their geographical spread isreflected in the

following table:

Table – 3.1

List and Distribution of Mangrove Species in Pakistan

Species Distribution

RHIZOPHORACEAE

Bruguieragymnorhiza (L) Lamk.

Karachi and Indus delta (Hassan) Estuary of

Indus (Murray); no specimen in Kew,

Edinburgh and Pakistan.

Ceriopstagal (Perr.) C.B. Robin Karachi and Coast of Sindh (Stocks) Mouth of

Indus and “Salt Water Creek” (Murray)

Ceriopsdecandra (G.) Ding Hou Sindh tidal zone; existence considered

doubtful

RhizophoramucronataLamk. Tidal marshes at the mouth of Indus:

MianiHor, Las Bella (T&S)

MYRSINACEAE

Aegicerascorniculatum (L.) Blco. Mangrove swamps at mouth of the Indus

(Stocks Ritchie) Karachi (Jafri), KalmatHor

AVICENNIACEAE

Avicennia marina (Forstk.) Vierh. Tidal mangrove swamps; Sands Pit (Stem)

China Creek, etc. (Jafri), KalmatHor

SONNERA TIACEAE

SonneratiaCaseolaris (L.) Engler Mouth of Indus and Tidal Zone (Common,

fide Murray); Indus delta no specimen seen.

Source: Coastal Environmental Management Plan for Pakistan-UN-ESCAP, 1989.

8

Keti Bunder

Keti Bunder is located at a distance of about 200 km south east of Karachi in Thatta

district of Sindh province. It is a taluka (Tehsil) of Thatta district and consists of a

total of 42 dehs (villages) that spread over a total area of 60,969 hectares

(WWF-2008). According to WWF (2004), the sea has engulfed 28 dehs and the total

affected area in Keti Bunder was around 46,137 hectares. The communities are

mainly depended on agriculture and fishing for livelihood. Livestock farming is also

common in Keti Bunder, communities reported raising cattle, buffaloes and camels.

According to Hoekstra et al.(1997) there were about 5000 camels in mangrove areas.

Earlier Qureshi (1985) had reported somewhat higher figure of 16,000 camels in the

entire deltaic region.

According to WWF (2008) report on ketibunder, area under mangrove is around

7,241 ha out of which 1,578 ha area(22% of total area) falls under dense mangroves

forest . The locals community uses mangrove trees for fodder, as fuel wood, camel

browsing and for making of huts. As Mangroves are also the breeding ground for

variety of fish shrimps, crabs and other invertebrates as well, the livelihood of the

people of ketibunder is directly depended on the mangrove. Over all dominant

sources of livelihood includes fishing (about 90%), agriculture and livestock rearing

(about 8%) and services in various sectors (about 2%). The area of mangroves has

declined over the period of 1932 -2005,see Below tables for further tables.

Table – 3.2(a)

Mangroves Density in Keti Bunder (Hectares)

Mangroves Density Classes Mangroves

Area % of Total

Mangroves Area

Dense 1,578 22%

Medium 1,338 18%

Sparse 2,886 40%

Very Sparse 1,439 20%

Source: WWF-2008, based on GIS images.

Table – 3.2(b)

Historical Pattern of Area under Mangroves in Pakistan (Hectares)

Years Mangroves Area

1932 604,870

1986 440,000

1992 160,000

2005 86,000

Sources: 1. Coastal EnvironmentalManagement plan for Pakistan UNESCAP,1996.

2. Mangroves of Pakistan- and Management, IUCN,Pakistan, 2005.

Kharo Chhan

Geographical area of Kharo Chhan is about 57,459 ha. The area can be sub-divided

into two main areas i.e. inland areas and mudflat areas. According to the 1998 census

9

the population of taluka Kharo Chhan and adjacent creeks was about 30,500. The

major sources of livelihood were fishing, agriculture and livestock.

In 2011, WWF conducted a GIS based study to compare the area of Kharo Chhan

before and after flood. According to the report, major dense pockets of mangrove

forests of the Indus delta are present in Kharo Chhan. The mangrove area provides

support to fishes and other species. The dense patches of mangroves mainly

compromises of Avicenna marina. However, the locals are not directly dependent on

mangroves as the forest exists at a distance of 20 kilometers. It required almost a day

to reach the area using boat. The area is very rich in terms of biodiversity. It is an

important flyoverfor migratory birds as well. During the winter season, thousands of

waterfowl stay here for feeding and breeding (see WWF-2011 for more detail).

Table – 3.3

Area Comparison of Pre and Post Flood Land Cover Classes (Hectares)

Class Name Mangroves Area

Pre-Flood Post-Flood

Closed Mangroves Canopy 3,249.32 3,25.38

Closed to open Mangroves Canopy 4,883.76 3,712.14

Source: WWF-2011, based on GIS images.

Shah Bunder

Shah Bunder is located on the Sindh costal area, its geographical area is about

3322.78 km2 which is about 19% of total geographical area of Thatta. Shah Bunder

consists of 92 Dehs.According to the population census of 1988 its population is

around 1,00,575, the recently estimations show that population has increased to

142,924. The socio economic indicators show that there are total 159 schools located

in the Shah Bunder out of which only 4 are high schools. The conditions of health

facilities are also very poor in Shah Bunder, Shah Bunder least deprived taluka of

Thatta. People of Shah Bunder have around 2000 camels,6000 buffalos, and

7000goats. The area of mangroves in Shah Bunder is not reported anywhere officially

in the absence of the official figure,we have computed the area by multiplying the

proportion of area under mangroves in Keti Bunder and KharoChhan to total

geographical area of Shah Bunder. The computer area is around 39,347 ha. The area

however is dense in the eastern part of Shah Bunder as compare to the other region of

Shah Bunder.

10

4. SOCIO-ECONOMIC PROFILE OF THE RESPONDENTS

This section of the report highlights different socio-economic profiles of 160

respondents as anoutcome of household survey in the area. These profiles, prepared

across different classifications of the respondents using the micro level data, are

important indicators of the local population which lives closest to mangrove forests

and in part depend (directly or indirectly) on the forests for their livelihood.

a) Family Size

The average family size of all sampled households was 11.27, where the minimum of

10.44 was for Shah Bunder and maximum of 13.55 for Kharo Chhan. It is interesting

to note that in Shah Bunder where the average family size was lowest (i.e. 10.44), the

average number of males (i.e. 3.46) was higher than the average number of females

(i.e. 3.21) and the associated average number of children was lowest (i.e. 3.77).

Table – 4.1

Average Family Size, Males, Females and Children (# Households)

Taluka Stats. Family Size Male Female Children

Keti Bunder

Mean 11.05 3.35 3.38 4.55

# Observations (40) (40) (40) (40)

Std. Deviation 8.24 3.15 3.36 3.49

Kharo Chhan

Mean 13.15 3.73 4.03 5.35

# Observations (40) (40) (40) (40)

Std. Deviation 6.50 2.33 2.64 3.26

Shah Bunder

Mean 10.44 3.46 3.21 3.77

# Observations (80) (80) (80) (80)

Std. Deviation 8.15 2.87 2.93 4.13

Total

Mean 11.27 3.50 3.46 4.36

# Observations (160) (160) (160) (160)

Std. Deviation 7.83 2.81 2.98 3.81

Source: Household Survey.

Conversely, in Keti Bunder and Kharo Chhan where the average number of males was

less than average number of females, the associated average number of children was

higher (i.e. 3.38 and 4.03). It shows that a larger proportion of females (in relation to

males) seem to be associated with larger number children in the family. This could be

one of the reasons for higher fertility rate.

b) Education: Respondents

The levels of education (in terms of years completed) of the respondents shows that

nearly two-third of the 160 households had no education. In terms of years completed

in school, Kharo Chhan seems to have an edge over other two talukas (Table 4.2).

11

Table – 4.2

Levels of Education of the Respondents

(# Households unless otherwise mentioned)

Education Talukas

Total Keti Bunder Kharo Chhan Shah Bunder

Illiterate

Count 26 27 49 102

% within Taluka 65.0% 67.5% 61.3% 63.8%

% of Total 16.3% 16.9% 30.6% 63.8%

1 to 5

Count 11 6 18 35

% within Taluka 27.5% 15.0% 22.5% 21.9%

% of Total 6.9% 3.8% 11.3% 21.9%

6 to 10

Count 2 4 8 14

% within Taluka 5.0% 10.0% 10.0% 8.8%

% of Total 1.3% 2.5% 5.0% 8.8%

11 to 12

Count 1 2 2 5

% within Taluka 2.5% 5.0% 2.5% 3.1%

% of Total .6% 1.3% 1.3% 3.1%

13 to 16

Count 0 1 3 4

% within Taluka .0% 2.5% 3.8% 2.5%

% of Total .0% .6% 1.9% 2.5%

Total

Count 40 40 80 160

% within Taluka 100.0% 100.0% 100.0% 100.0%

% of Total 25.0% 25.0% 50.0% 100.0%


c) Education: Within Family

The information on highest level of education completed within the family, the

average number of those who completed 12 years or more was 3.69 for Kharo Chhan,

3.65 for Shah Bunder and 3.4 for Keti Bunder (Table 4.3).

Table – 4.3

Higher Education Completed in the Family (# Households)

Taluka No Education Upto 5 5 to 10 10 to 12 12 & above

Keti Bunder 26 4.50 14 3.4

Kharo Chhan 27 7.54 13 3.69

Shah Bunder 49 6.77 31 3.65


Though the overall pattern reflects poor educational attainment in the area, Kharo

Chhan seems to have an edge over here as well in relation to other two talukas.

d) Period of Settlement

Table 4.4 shows variations in the period of settlement of the sampled households

across three talukas. The proportion of those families who have been living for over

50 years was highest in case of Kharo Chhan (i.e. 72.5).

12

Table – 4.4

Association with the Village (# Years Since Living in the Village)

Over All Frequency Percent Less than 10 Years 21 13.1 11 to 20 Years 15 9.4 21 to 30 Years 19 11.9 31 to 50 Years 25 15.6 More than 50 Years 80 50.0 Total 160 100

Keti Bunder Frequency Percent Less than 10 Years - - 11 to 20 Years 5 12.5 21 to 30 Years 9 22.5 31 to 50 Years 5 12.5 More than 50 Years 21 52.5 Total 40 100

Kharo Chhan Frequency Percent Less than 10 Years 1 2.5 11 to 20 Years 3 7.5 21 to 30 Years 2 5.0 31 to 50 Years 5 12.5 More than 50 Years 29 72.5 Total 40 100

Shah Bunder Frequency Percent Less than 10 Years 20 25.0 11 to 20 Years 7 8.8 21 to 30 Years 8 10.0 31 to 50 Years 15 18.8 More than 50 Years 30 37.5 Total 80 100


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Keti Bander Kharo Chhan Shah Bander Overall

Less than 10 Years

21 to 30 Years

Mo

re t

han

50

Yea

rs

Mo

re t

han

50

Yea

rs

Mo

re t

han

50

Yea

rs

Mo

re t

han

50

Yea

rs

Per

cen

tag

e o

f #

Ho

use

ho

lds

13

Similarly, the proportion of those settled rather recently (i.e. less than 10 years ago)

was highest in case of Shah Bunder where 25 percent of households settled recently as

compared to zero percent in Keti Bunder and Kharo Chhan. Since Shah Bunder was

worst affected by sea cyclone in the late 1990’s as a result of which its taluka

headquarter was shifted to upland area, the shifting of settlements was more common

in Shah Bunder taluka. However, on the whole, 50 percent of sampled households

(i.e. 80 out of 160) reported to be living in the area for over 50 years.

e) Agricultural Land

The scale of devastation in thee coastal talukas as a result of continuous sea intrusion

has resulted in the loss of fertile agricultural land. Currently, agricultural land

ownership has reduced along the coastal belt of Indus delta. Only a fraction of land

holding is brought under cultivation owning to the fact that the supply of fresh water

has reduced considerably.

Table – 4.5

Agriculture Land Ownership and Cultivation (#acres)

Taluka Land Not

Owned (Household)

If Own Land Agriculture Land

Owned (acres)

Current Cultivated Area

(acres)

Keti Bunder

Mean - 10.000 .000

# Observations (39) (1) (1)

Std. Deviation - - -.

Kharo Chhan

Mean - 31.46 3.29


Std. Deviation - 55.24 6.13

Shah Bunder

Mean - 18.80 .850



Total

Mean - 23.14 1.71




As such, crop cultivation in coastal talukas of Keti Bunder, Kharo Chhan and Shah

Bunder is away from the coast. Table 4.5 shows that out of 160 sampled households

127 i.e. (79 percent) had no land ownership. Of those who own land, the average size

of holding in Keti Bunder was 10 acres, on which there was no cultivation. Similarly,

in Kharo Chhan and Shah Bunder, the average size of agricultural land holding was

31.46 and 18.8 acres, respectively. Out of this, only 5 to 10 percent was cultivated.

The massive devastation of fertile agricultural land also caused a virtual elimination

of historically famous red rice of the area.

f) Ownership and Value of Vehicles Owned

Table 4.6 shows the number and type of vehicles owned by the sampled household. A

total of 22 motorcycles, one jeep and 1 pick up were owned by the households. A

generally prevalent poverty in the area coupled with dilapidated conditions of roads

14

has tended to reduce the ownership of vehicles in the coastal belt. The locals use

public transport for in their daily routine work and the quality of this transport service

is very low.The economic and social backwardness of the area can be judged from the

fact that in Keti Bunder, there is not a single ambulance service available. The

patients are taken in public transport to hospitals located at 60 to 100 kilometers away

in Gharo or Thatta city.

Table – 4.6

Ownership and Value of Vehicles Owned

Ownership of Vehicles (#)

Talukas Total

Keti Bunder Kharo Chhan Shah Bunder

Motor Cycle 4 5 13 22

Jeep - - 1 1

Car - - - -

Pick Up - 1 - 1

Value of Vehicles

(Rupees)

Motor Cycle

Jeep

Car

Pick Up

38,750

-

-

-

42,000

-

-

600,000

37,423

170,000

-

-

38,704

-

-

600,000


g) Ownership of Boats and Value

Since marine fisheries is the main source of livelihood and some villages are located

in islands, use and ownership of boats is common in the area. Table 4.7 reflects boat

ownership by size and value.

Table – 4.7

Ownership and Average Value and Size of Boat

(# Boats unless otherwise mentioned)

Talukas

Total Keti Bunder

Kharo Chhan Shah Bunder

Ownership of Boat (#) 30 23 36 89

Size of Boat (Feet) 23.8 25.56 26.466 25.33

Value of Boat (Rupees) 1,130,333 1,257,173.9 539,305.6 924,044.9


On average, the households in each taluka reported 23 to 36 boats owned with an

average size (i.e. length) around 25 feet. The average value reported ranged between

Rs.0.5 to 1.3 million rupees.

h) Ownership and Number of Livestock

The ownership of livestock was limited in the area. Only 58 households out of 160

(i.e. 36 percent) were keeping livestock. The raising of camels was reported only by

10 households with 7 from Shah Bunder (Table 4.8).

15

Table – 4.8

Ownership and Number of Livestock (#Animals)

Talukas

Total Keti Bunder

Kharo Chhan Shah

Bunder

Ownership of Livestock 6 16 36 58

Camel 30 (2) 2 (1) 46 (7) 78 (10)

Buffalos 23 (3) 17 (6) 58 (22) 98 (31)

Cows 10 (1) 14 (6) 20 (7) 44 (14)

Goats 16 (3) 27 (7) 6 (3) 49 (13)

Figures in parenthesis show # reporting households.


The total number of camels, buffaloes, cows and goats raised by the 58 households

were 78,98,44 and 49, respectively. The practice of keeping livestock was limited due

to the fact that some villages are located on islands and the transportation and feeding

of livestock is an uphill task for such households. The lowest stock of animals was

reported in Kharo Chhan and the highest from Shah Bunder. However, these

variabilities are largely an indicator of geographical area and population covered by

Shah Bunder (which was also taken into account while assigning weights in the

sampling framework). Nevertheless, the stock of animals kept of the households is a

reflection of the fact that these households depend on mangroves for the supply of

fodder.

i) Civic Amenities Available

Table 4.9 shows type of construction of 158 sampled households. It shows that nearly

half (48.1 percent) were living in huts, another 24.4 percent were living in semi-pacca

houses whereas 26.9 percent had pacca housing structure.

The pattern of housing construction is similar across the talukas. The proportion of

pacca housing structure in Keti Bunder was twice the proportion in Kharo Chhan and

Shah Bunder. The fact that over 48 percent of houses were established in huts

provides ample evidence of poverty levels prevailing in coastal areas.

16

Table – 4.9

# Household Connected with Various Facilities (# Households)

Talukas


Ownership of House 40 39 79 158

1. Construction Type

- Hut 20

(50)

20

(50)

37

(46.3)

77

(48.1)

- Semi Pacca 4

(10)

12

(30)

23

(28.8)

39

(24.4)

- Pacca 16

(40)

7

(17.5)

20

(25.0)

43

(26.9)

2. Piped Drinking Water 0

(0)

0

(0)

10

(12.5)

10

(6.3)

3. Electricity 28

(70)

2

(5)

10

(12.5)

40

(25.0)

4. Gas 0

(0) 0(0)

7

(8.8)

7

(4.4)

5. # Rooms 2.63 2.74 2.29 2.48

Note: Numbers in parentheses are percentages.


The table also reports that 10 out of 80 households in Shah Bunder had access to

piped drinking water in their houses, whereas none of the sampled households in other

talukas had any such facility. Only in case of Keti Bunder, there is a scheme of

providing safe drinking water at a public place atits headquarter. On the whole, only

6.3 percent of households within the sampled households had access to piped drinking

water. The real situation on safe drinking water supply in Keti Bunder is that the

general water supply is provided by private tankers who bring water some 15 to 20

kilometers from a nullah located right on the main road connecting Keti Bunder with

the rest of Thatta district. The water quality is very low and the locals have no option

but to purchase low quality water at higher prices. If this is the situation in proper Keti

Bunder which has a higher proportion of urban population, the situation in other

talukas can be ascertained rather easily.

The system electricity connection was somewhat better than that of water supplies.

Nearly 70 percent of households sampled from Keti Bunder had electricity connection

whereas this proportion was low 5 percent in Kharo Chhan and 12.5 percent in Shah

Bunder.

Only 7 households of Shah Bunder had gas connections.

The situation of housing and provision of civic amenities in the coastal area of Indus

delta, so depicted, reveals extremely poor quality of life. Under this scenario, it is

expected that these coastal communities depend in part on the non-timber forest

products from mangroves to derive a number of direct and indirect benefits for their

livelihood.

17

j) Occupation

Table 4.10 provides information on primary, secondary and tertiary occupations in the

sample talukas. In Keti Bunder, 29 out of 40 (i.e. 72.5 percent) had fishing as their

primary occupation. The respective proportions were 52.5 and 43.8 percent for Kharo

Chhan and Shah Bunder, respectively. This portrays the central occupation in the

coastal area.

Table – 4.10

Occupations Primary, Secondary and Tertiary (#)

All Keti Bunder Kharo Chhan Shah Bunder

Primary Secondary Tertiary Primary Secondary Tertiary Primary Secondary Tertiary

Fishing 29

(72.5)

1

(2.5) -

21

(52.5)

3

(7.5) -

35

(43.8)

3

(3.8) -

Shop or

Business

2

(5)

3

(7.5) -

2

(5)

2

(5) -

5

(6.3) -

Labor 3

(7.5)

2

(5) -

5

(12.5) - -

25

(31.3)

1

(1.3) -

Job 5

(12.5) - -

5

(12.5

6

(15) -

7

(8.8) -

Stitching and

Tailoring

1

(2.5)

1

(2.5)

1

(2.5) -

1

(2.5) - -

3

(3.8) -

Social Worker - - - - - - 1

(1.3) - -

Fishing on

Rented Boat - - -

5

(12.5) - -

2

(2.5) - -

Wood seller - - - - 1

(2.5) -

2

(2.5)

1

(1.3) -

Farmer - - - - 2

(5) -

2

(2.5)

3

(3.8) -

Middle Man

Whole seller - - - - - -

1

(1.3) - -

Planting - 2

(25) - - - - - - -

Rent a Car - - - - - - - 1

(1.3) -

# Household 40 9 1 38 15 - 80 11 0

Total 40 40 40 38 38 38 80 80 80

Note: Figures in parentheses show column percentages.


Wage labourwas reported by 7.5 percent in Keti Bunder, 12.5 percent in Kharo Chhan

and 31.3 percent in Shah Bunder as primary occupation. Similarly, doing a job as

primary occupation was reported by 12.5 percent in Keti Bunder, 12.5 percent in

Kharo Chhan and 8.8 percent in Shah Bunder. It implies that 92.5 percent of sampled

households had these three occupations (namely fishing, wage labour and jobs) in

Keti Bunder. The respective proportions for Kharo Chhan and Shah Bunder were 72.5

and 83.9 percent, respectively. The exclusive dependence on fisheries reveals source

18

of livelihood for coastal community. At this, it becomes difficult to overemphasize the

direct and indirect dependence of coastal communities on mangroves.

The details on secondary occupations of these communities reveal that 9 out of 40 in

Keti Bunder, 15 out of 38 in Kharo Chhan and 11 out of 80 in Shah Bunder had a

secondary occupation as well. Putting jointly, in aggregate terms the three main

occupations account for 90 percent of households in Keti Bunder, over 95 percent in

Kharo Chhan and 90 percent in Shah Bunder. The tertiary occupations were almost

non-existence. The occupational pattern shows an inclusive dependence of coastal

communities on local natural system supported by few opportunities for wage labour

and jobs.

k) Working Force and Employment

Tables 4.11(a) to (d) provide details on average number of persons per household and

days of work per week across gender for each taluka and an overall situation covering

all sampled households.

Table – 4.11(a)

Average Workers and Days in Work in Keti Bunder (# Workers)

Taluka Keti Bunder

Male Female Children

Male Worker

Days Per Week Male

Worker

Female Worker

Days Per Week

Female Worker

Children in Work

Days per Week

Children in Work

Primary

Occupation

Mean 1.95 5.4 - - 0.25 0.72

# Observations (40) (40) (40) (40) (40) (40)

Std. Deviation 1.65 1.36 - - 0.74 1.8

Secondary

Occupation

Mean 0.28 0.75 0.15 0.2 0 0

# Observations (40) (40) (40) (40) (40) (40)

Std. Deviation 0.75 1.84 0.7 1.11 0 0

Tertiary

Occupation

Mean - - 0.03 0.08 - -

# Observations (40) (40) (40) (40) (40) (40)

Std. Deviation - - 0.158 0.47 - -


In Keti Bunder, employment of males in primary and secondary work accounted for

1.95 and 0.28 workers per households, respectively. The respective numbers of hours

per week for males were 5.4 and 0.75 days. There was primary occupation reported

for females. The number of children, on average, was 0.25 and they worked for 0.72

days per week in the primary sector. The secondary occupation was taken, on average,

by 0.28 males and 0.15 females per household. There was no child work reported in

secondary occupation (Table 4.11(a)). There are limited tertiary occupations reported

for females in the area.

19

Table – 4.11(b)

Average Workers and Days in Work in Kharo Chhan (# Workers)

Taluka Kharo Chhan


Male Worker

Days Per Week Male

Worker

Female Worker

Days Per Week

Female Worker

Children in Work

Days per Week

Children in Work

Primary

Occupation

Mean 2.55 5.05 - - 0.13 0.29

# Observations (38) (38) (38) (38) (38) (38)

Std. Deviation 1.8 1.66 - - 0.67 1.29

Secondary

Occupation

Mean 0.53 1.26 0.03 0.03 0.13 0.42

# Observations (38) (38) (38) (38) (38) (38)

Std. Deviation 1.37 2.37 0.16 0.16 0.53 1.5

Tertiary

Occupation

Mean - - - - - -

# Observations (38) (38) (38) (38) (38) (38)

Std. Deviation - - - - - -


In Kharo Chhan, employment of males in primary and secondary work accounted for

2.55 and 0.53 persons per household. There was no female work reported. In case of

children, on average, 0.13 children per households worked for 0.29 days per week.

For secondary occupations, 0.53 males, 0.03 females and 0.13 children remained

associated who, respectively, devoted 1.26, 0.03 and 0.42 days per week

(Table 4.11(b)). There was no reporting of any tertiary occupation in the area.

Table – 4.11(c)

Average Workers and Days in Work in Shah Bunder (# Workers)

Taluka Shah Bunder


Male Worker

Days Per Week Male

Worker

Female Worker

Days Per Week

Female Worker

Children in Work

Days per Week

Children in Work

Primary

Occupation

Mean 2.28 5.86 - - 0.01 0.05

# Observations (80) (80) (80) (80) (80) (80)

Std. Deviation 1.82 1.31 - - 0.11 0.45

Secondary

Occupation

Mean 0.28 0.55 0.03 0.14 0.01 0.08

# Observations (80) (80) (80) (80) (80) (80)

Std. Deviation 0.94 1.6 0.16 0.87 0.11 0.67

Tertiary

Occupation

Mean - - - - - -

# Observations (80) (80) (80) (80) (80) (80)

Std. Deviation - - - - - -


In Shah Bunder, the number of males and children involved in primary occupations

were, respectively, 2.28 and 0.01. No female participation was reported in primary

occupation. These persons devoted 5.86 days and 0.05 days per week in carrying out

their work in primary occupation. In the secondary occupation, the males participation

was on average, 0.28 persons per household, 0.03 persons for females and 0.01 for

children.

20

Table – 4.11(d)

Average Workers and Days in Work in All talukas (# Workers)

All Taluka


Male Worker

Days Per Week Male

Worker

Female Worker

Days Per Week

Female Worker

Children in Work

Days per Week

Children in Work

Primary

Occupation

Mean 2.26 5.55 - - 0.1 0.28

# Observations (158) (158) (158) (158) (158) (158)

Std. Deviation 1.77 1.44 0 0 0.51 1.17

Secondary

Occupation

Mean 0.34 0.77 0.06 0.13 0.04 0.14

# Observations (158) (158) (158) (158) (158) (158)

Std. Deviation 1.02 1.88 0.38 0.83 0.27 0.89

Tertiary

Occupation

Mean - .- 0.01 0.02 - -

# Observations (158) (158) (158) (158) (158) (158)

Std. Deviation - - 0.08 0.24 - -


At all taluka level, the situation has been summarized in Table 4.11(d). In case of

males, 2.26 and 0.34 persons i.e. 2.60 persons per household were employed.

Similarly, in case of females it shows a total of 0.07 females per household employed

in any occupation. The child work jointly shows an average of 0.14 children per

household involved in any occupation.

In terms of days per week of work, it reported 6.13 days, for males, 0.15 days for

females and 0.42 days of children, across all occupations.

The levels of employment across gender reported in Table 4.11(d) when compared

with average number of persons in the household reported in Table 4.1 (discussed

earlier) shows that males employment level was 74 percent ( i.e. 2.60 in relation to

3.50), females employment level of 20 percent (i.e. 0.7 in relation to 3.46) and

children was 4 percent (i.e. 0.14 in relation to 4.36).

Keeping in consideration the old age persons in families, the employment of working

force of males of 74 percent seems close to full employment level. However, female

employment of 20 percent seems underutilization of available female labour force.

The child work of 4 percent, though relatively low, creates concern.

l) Income Levels

Keeping in view all sources of direct incomes (i.e. on-site and off-sites) of all males,

females and children as reported during household survey, total monthly income

levels were computed for each taluka. Table 4.12(a) shows wide variations across

talukas.

21

Table – 4.12(a)

Average Household Income by Taluka (Rs./Month)

Taluka Mean # Observations Std. Deviation

Keti Bunder 64,340 40 121,129

Kharo Chhan 36,621 38 68,329

Shah Bunder 15,743 80 13,269

Total 33,067 158 72,378


The levels, though presented for each taluka on the basis of monthly averages, show

wide variations in Keti Bunder and Kharo Chhan talukas, reported through their

respective levels of standard deviation.

Only in case of Shah Bunder the average level does not show significant variation. If

Shah Bunder’s average income level is taken as base, it implies that at Keti Bunder,

the direct incomes were over 4 times and that of Kharo Chhan there were more than

twice in relation to Shah Bunder.

Table – 4.12(b)

Number of Household across Income Categories (# Households)

Income Category Talukas


0 thru 5000 4 2 14 20

10.00% 5.30% 17.50% 12.70%

5001 thru 10000 6 14 20 40

15.00% 36.80% 25.00% 25.30%

10001 thru 20000 15 11 26 52

37.50% 28.90% 32.50% 32.90%

20001 thru 40000 3 5 17 25

7.50% 13.20% 21.30% 15.80%

40001 thru hi 12 6 3 21

30.00% 15.80% 3.80% 13.30%

Total 40 38 80 158

100.00% 100.00% 100.00% 100.00% Note: Percentages show column percentages.


22

The income level variability discussed above was further analysed across different

income categories which is presented by Table 12(b). It further verifies that Shah

Bunder area consists of larger proportion of low income categories in relation to other

two talukas. For example, upto an average monthly income of Rs.10,000, Keti Bunder

has 25 percent of households, Kharo Chhan 42.1 percent and Shah Bunder 42.5

percent.

Similarly in higher income category of Rs.40,000 and above per month, Keti Bunder

has 30 percent of its households, Kharo Chhan 15.8 percent and Shah Bunder only

3.80 percent.

A common view of the area reflects the fact that Keti Bunder has retained its

historical location as well as has acted as a center for various developmental activities

despite facing a number of threats in the form of natural as well as man made

disasters. In contrast, Shah Bunder could not sustain the devastation of sea cyclone of

mid 1990’s and as a result its taluka headquarter was shifted to another location in the

upstream area, its population was scattered and as such currently the location of Shah

Bunder’s proper settlement is lost to antiquity. As a consequence, Shah Bunder has

yet not reversed its position undermining its fisheries catch and marketing and other

economic development prospects.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Keti Bander Kharo Chhan Shah Bander Total

0 thru 5000 0 thru 5000

Per

cen

tag

e o

f #

Ho

use

ho

lds

23

Table – 4.12(c)

Average Income Level under Different Scenarios (Rs./Household/Month)

Taluka If Fishing is

Primary Occupation

If Fishing is Secondary Occupation

If Non-Fishing is Primary

Occupation

If Non-Fishing is Secondary Occupation

Keti Bunder

Mean 62,531 7,000 66,272 145,525

# Observations (29) (1) (11) (8)

Std. Deviation 92,188 1,835 182,238 213,389

Kharo Chhan

Mean 52,938 2,700 13,752 21,150

# Observations (21) (3) (17) (12)

Std. Deviation 86,785 4,000 14,207 29,944

Shah Bunder

Mean 20,474 6,000 11,328 27,377

# Observations (35) (3) (45) (9)

Std. Deviation 16,332 3,191 7,719 24,213

Total

Mean 42,843 4,728 20,172 57,393

# Observations (85) (7) (73) (29)

Std. Deviation 71,427 71,254.2 122,373


The levels of incomes generated from fishing and non-fishing sources have been

highlighted by Table 4.12(c). It shows that income levels from fishing as primary

occupation in all talukas in terms of the levels and spread. However, fisheries as a

source of income was highest in Keti Bunder where 29 out of 40 households (72.5

percent) had it as primary occupation. In case of Kharo Chhan it was 52.5 percent and

in Shah Bunder it was 43.8 percent, of the sampled households. The highest

participation was in fisheries activities all across. The occurrence of non-fisheries was

highest in Shah Bunder.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

If Fishing isPrimary

Occupation

If Fishing isSecondaryOccupation

If Non-Fishing If Non-Fishing isSecondaryOccupation

Per

cen

tag

e o

f #

Ho

use

ho

lds

24

In relative terms, a somewhat higher attainment of education in Shah Bunder

(discussed earlier in sub-sections b & c) on educational attainments, and a higher

proportion of wage labour (reference Table 4.10) could have created the basis for

higher non-fisheries activities as secondary occupations. In any case fisheries is the

highest and more reliable source of income for the majority of coastal population.

m) Community’s Linkage with Mangroves

Over 90 percent of the respondents reported visiting mangroves either exclusively to

collect forest products like fuel wood, fodder, catching fish crabs, shrimps, honey,

herbs, poles for use in house construction, animal browsing, or to take rest and

recreation while going towards open sea for fishing.

Table – 4.13

Community’s Linkage with Mangrove (# Households)

Talukas Total


No. of Households

Visiting Mangroves

38

(95)

35

(87.5)

72

(90)

145

(90.6)

# Visits / Month 11.38 4,42 4.19 6.08

Fuel Cost* 30,879

(N=14)

16,000

(N=4)

42,857

(N=14)

34,259

(N=32)

Permit Cost* 114

(N=14)

50

(N=4)

454

(N=14)

255

(N=32)

Depreciation Cost* 4,779

(N=14)

3,075

(N=4)

3,964

(N=14)

4,209

(N=32)

Food Cost* 20,664

(N=14)

8,750

(N=4)

16,929

(N=14)

17,541

(N=32)

Other Cost* 218

(N=14)

0

(N= 4)

500

(N=14)

314

(N=32)

Note: 1. Numbers in parentheses are percentages otherwise indicated.

2. * if using to visit mangrove or using it for both, fishing & Visiting Mangroves.


Table 4.13 highlights the cost structure of 14 respondents who regularly visit

mangroves (i.e. 6.08 visits per month) to collect non-timber forest products. It should

also be noted that only 89 boats ownership was reported by 160 sampled households

(Table 4.7). Even if we assume that one household doesn’t own more than one boat, if

implies that over 44 percent of sampled households do not own boat. It does not mean

that non-boat owners do not visit mangrove. They may do so as part of the team (or as

wage labour). It also does not mean that all the boat owners visit mangrove. Some (or

a majority) may go directly into open sea.

Keeping all such scenarios into consideration, it is possible that a majority may visit

mangroves (either as part of primary or secondary occupation) but some of them may

not own boat and only visit as part of the team. In this context, the detailed

information on costs incurred could only be reported by the boat owner (or any one

who keeps account of such expenses). In the light of above, only 14 respondents gave

25

details on costs incurred whereas a much larger number of persons may have visited

mangroves.

The highest number of visits to mangroves was reported by respondents of Keti

Bunder i.e. 11.38 visits per month. It can thus be argued that fishermen (or coastal

population) of Keti Bunder visits mangroves more frequently than those visiting from

other talukas.

It could also be argued that for the marketing of non-timber forest products Keti

Bunder still acts as a major centre. As a result, most of the visitors may go rather

frequently to mangroves. In either case, it looks apparent that the local communities

depend on mangroves for a variety of reasons.

n) Community’s Perceptions towards Mangroves

In addition to direct questions on the quantitative aspects of valuation of mangroves,

the respondents were also asked to reveal their perceptions towards mangroves

through a set of questions.

Table – 4.14(a)

Change in Mangroves Area in Last 50 Years (# Households)

Status Talukas


No Change - 2

(5.1)

9

(11.4)

11

(7.0)

Increase or Improvement 2

(5.0) -

4

(5.1)

6

(3.8)

Decrease or Reduction or

destroyed

38

(95.0)

37

(94.9)

66

(83.5)

141

(89.2)

Total 40

(100.0)

39

(100.0)

79

(100.0)

158

(100.0)

Note: Numbers in parentheses are column percentages.


When inquired about changes in mangroves cover during the last 50 years or so, a

vast majority (nearly 90 percent) reported that the cover has reduced or destroyed

during this period (Table 4.14(a)).

26

Table – 4.14(b)

Causes of Change in Mangroves Area in Last 50 Years (# Households)

Causes Talukas


Cutting 29

(72.5)

2

(5.1)

8

(10.1)

39

(24.7)

Camel Grazing 3

(7.5) - -

3

(1.9)

Lack of sweet water 2

(5.0)

20

(51.3)

7

(8.9)

29

(18.4)

Sea Intrusion and Cyclone 3

(7.5)

13

(33.3)

50

(63.3)

66

(41.8)

Improper Care 1

(2.5)

2

(5.1)

1

(1.3)

4

(2.5)

Total 38

(95.0)

37

(94.9)

66

(83.5)

141

(89.2)

No Change 2

(5.0)

2

(5.1)

13

(16.5)

17

(10.8)



The respondents indicated different causes for this destruction of mangroves. A vast

majority (41.8 percent) regarded sea intrusion and cyclone as the main cause of

destruction. Out of 66 respondents, 50 were from Shah Bunder. Since the mid 1990’s

sea cyclone created higher level damages in Shah Bunder, it was not surprising that

this cause was considered as the major reason for destruction. Nearly 24.7 percent

(i.e. 39 respondents) regarded cutting of mangrove in the past as the second major

cause of mangrove destruction. Here, 29 respondents out of 39 were from Keti

Bunder. Another major cause was attributed to lack of sweet water in the deltaic

region. Here, the majority came from Kharo Chhan where 20 out of 29 respondents

were located. The other factor like camel grazing or improper care of mangroves was

reported by few (Table 4.14(b)).

Table – 4.15(a)

Changein Mangroves Area in Last 10 Years (# Households)

Status Talukas

Total Keti Bunder

Kharo Chhan

Shah Bunder

No Change - 1

(2.6) 6

(7.6) 7

(4.4)

Increase or Improvement 40

(100.0) 37

(94.9) 71

(89.9) 148

(93.7) Decrease or Reduction or destroyed

- 1

(2.6) 2

(2.5) 3

(1.9)

Total 40

(100.0) 39

(100.0) 79

(100.0) 158

(100.0)



27

The respondents were also asked as to what happened to mangroves during the last 10

years i.e. post-sea cyclone period. A predominantly high proportion of respondents

i.e. 93.7 percent regarded the mangroves to improve during the last ten years. At this,

all three talukas unanimously agreed that a reversal has started towards mangroves

development (Table 4.15(a)).

Table – 4.15(b)

Suggested Methods of Improvement in Mangroves Area (# Households)

Causes Talukas

Total Keti Bunder

Kharo Chhan

Shah Bunder

New Plantation 34

(85.0)

27

(69.2)

44

(55.7)

105

(66.5)

Ban on Cutting - - 1

(1.3)

1

(.6)

Ban on Camel Grazing 3

(7.5)

1

(2.6) -

4

(2.5)

Proper Care 3

(7.5)

3

(7.7)

14

(17.7)

20

(12.7)

Naturally - 6

(15.4)

12

(15.2)

18

(11.4)

Total 40

(100.0)

37

(94.9)

71

(89.9)

148

(93.7)

No Change - 2

(5.1)

8

(10.1)

10

(6.3)



When inquired about the reasons for improvements in mangrove, nearly two thirds

(i.e. 105 respondents) regarded new plantation and another 12.7 percent regarded

proper care of mangroves as the main factors behind the improvements in mangroves

cover. Only 10 respondents argued that no change took place in the status of

mangrove cover (Table 4.15(b)).

Based on the responses of sampled households towards different socio-economic

aspects, it becomes clearer that local community heavily depends on fisheries as their

exclusive source of livelihood. The incomes are largely generated from fishing

whereas the non-fishing occupations generate over one third of their incomes.

28

5. ECONOMIC VALUATION OF MANGROVES - METHODOLOGY

In order to evaluate economic value of the natural resources economists have long

preferred estimation of total economic value. The total economic value of mangrove

consists of its use value and non-use value. Use values are further classified into

direct and indirect uses. Non use value on the other hand is based on the satisfaction

consumers derive from knowing that mangroves will exist (option value). A consumer

may or may not necessarily use them. Another possible motive of non-use value is the

desire to preserve mangroves for future generations (bequest value).

Direct benefits are referred here to all the benefits derived from use of the mangrove.

In order to appropriately measure the benefits market prices werebe used. Direct

benefits of mangroves; include wood used for fuel, poles, herbs, shrimps and fish

species. The indirect benefits are hard to estimate as market prices are not available

for these benefits. Indirect benefits derived from mangroves include shoreline

protection, carbon sequestration, habitat for wild animals. These benefits are

sometime difficult to measure. In literature the estimation of indirect benefits such as

shore line protection from tsunami is based on damage costs avoided from the

destruction of economically valuable assets. However, in most of the cases it is based

on assumptions only. For the estimation purposesinformation on the cost of property

destroyed, livelihood loss, injuries and deaths were usually obtained from the site with

mangrove forest and from a control site (not covered by forest). The difference value

of the two costs was then used in literature as the economic benefits of the mangroves.

Under the non use value, option value represents the direct and indirect use of

mangroves in future while the bequest value indicates as to how much individuals

value the use and non use values for their future generation. Option values are often

used as the estimated value that people are willing to pay (WTP) in order to preserve

the mangrove for the use of future generation. This is based on the knowledge that

individual have about the preservation.

5.1 Estimating the Willingness to Pay

There is an on-going debate on how to evaluate the economic benefits of mangroves.

All these studies differ first, because of the range of products obtained from forest

varies; secondly, the types of mangrove management alternatives considered differ for

each study; thirdly, the assumptions regarding ecological linkages of mangroves and

other ecosystems are inconsistent.

There are several methods that researchers have used to evaluate the economic benefit

of the mangroves. Willingness to Pay (WTP) is one of the methods. WTP is often

used to figure out the amount of money local community is willing to spend to restore

or improve the mangrove forest culture.

Researchers have identified two methods to estimate WTP. It can be determined

indirectly by estimating the travel costs or through directly asking how much they are

willing to pay. Travel cost method estimates what people actually pay to protect the

mangrove forest while the direct method differs from traveling cost as it measures

what individuals claim to pay (Clawson et al., 1966; Bockstael et al., 1996 and Carr

et al., 2003). Their willingness to pay is based on the benefits availed form the

29

mangroves. The limitation of this method is that not all the services obtained from the

forest are commercially marketed goods. In the absence of any other method the

second method was used. For this, all the direct and indirect benefits availed from the

forest were quantified.

Second method as stated above determines WTP by asking people how much they

would be willing to pay to restore or maintain mangrove culture (Follain et al., 1985;

Malpezzi, 2008). Socio economic and demographic variables as well as economic

benefits availed from the forest were used to predict the WTP.

The willingness to pay (WTP) was considered as dependent variable:

WTP = B0 - B1(Rs. X1) + B2(X2)+B3 (X3) +B4 (X4) …

B’s are the coefficients to be estimated, Rs.X1 is the amount household was willing to

pay, X2was household income, X3 was highest education completed in years while X4

wasrespondent's family size. The formula to calculate expected WTP was based on

given Haneman (1989) formula:

Mean WTP = (1/B1) * ln[1+𝑒𝛽0+∑𝛽𝑖+𝑋𝑖]

Where, B1was the estimated coefficient of the amount household were willing to pay

and B0was the constant, Bi were the coefficients of independent variables δi were the

mean of independent variables (Hanemann, 1989).

Normally the WTP data is one where the observations at or below zero are censored.

This is because individual may response as: why to pay? What to pay? These forest

are free government may not used the amount collected properly etc. It is important to

note that not all those who gave reasons for not willing to pay are against to protect

forest. They may like to preserve the forest as well. One way of dealing these

responses is to consider the response as invalid and discard the observation. But

discarding these responses may lead to selection bias problem as the sample will not

remain random. The estimated parameters after discarding these cases will become

biased/ inconsistent. In order to avoid this problem Tobit model approach was

followed. Tobit model is an extension of the probit model and is mainly applied when

we have censored data. The standard Tobit model is based on the latent variable

approach. Finally, Emezrton and Kekulandala (2003) have listed a number of techniques to

evaluate the cost and benefits associated with the Mangroves. All the values are

measured in terms of their effects on human life, usually in monetary terms.

Moreover, the techniques listed by Emerton and Kekulandala (2003)are mostly survey

based and allow researchers to evaluate the cost and benefits in local values. This also

helps in assessing non-market as well as market value of the mangroves.

30

Chart – 5.1

Assessment of Total Economic Value of Mangroves

Source: Breidert, Hahsler and Reutterer (2006).

5.2 Economic Valuation of Mangroves - Empirical Valuation

5.2.1 Estimating Direct Values

a) Forest Product – Wood Fuel

Khalil (1999) estimated that the daily household use of wood obtained from

mangroves in the Indus delta, was around 4.5 kg/household/day. The average

price estimated was around Rs.1.45 per kg. The overall value of fuel wood

estimated by Khalil was around Rs.22.5 million per year (approximately US$

385,000/yr). While, Keerio and Bhatti (1999) indicated that wood obtained

from Avicennia marina has lower caloric value hence not desirable as fuel

wood. But it is still used by the local people extensively as fuel wood.

However its market outside the coastal area is very limited almost

negligible.According to Keerio and Bhatti (1999) each household is

consuming 173 kg of wood per month. The rate per kg varies from Rs.1 to 1.5

giving an average value of around Rs.173 to 259.5 per month (Annexure

Tables 5.1 & 5.2).

Table – 5.1

Economic Valuation of Fuel Wood (Marketed) (Rs.)

Talukas


Total

425a 410 681 549

(1059)b (732) (1609) (1308)

(40)c (40) (80) (160)

Note: a,

b and

c are Value, Standard Deviation and # Observations, respectively.


31

Table – 5.2

Economic Valuation of Fuel Wood Non-Marketed (Domestic Use)

(Rs.)

Talukas


Total

1160 490 765 795

(1444) (1038) (1665) (1487)

(40) (40) (80) (160)


0

200

400

600

800

1000

Subsistence Low Middle High

Eco

no

mic

Valu

e (

Rs.)

Income Levels

Figure - 5.1

Economic Valuation of Fuel Wood (Marketed) across Income Categories


0

500

1000

1500

2000


Eco

no

mic

Valu

e (

Rs.)

Income Levels

Figure - 5.2

Economic Valuation of Fuel Wood Non-Marketed (Domestic Use) across Income Categories


32

The data obtained through primary survey for this study shows that wood

obtained from the mangroves forest is not only used by households for

domestic purpose (non marketed) but also for commercial purpose as well.

Sale of fuel wood is also generating livelihood for the households (marketed).

Average value of the wood used as fuel domestically was worth Rs.795 per

month while the fuel wood marketed was worth Rs.549 per month (Tables 5.1

& 5.2). The overall value of fuel wood obtained from the mangrove forest was

therefore around Rs.1,344 per month. The economic value is highest for Keti

Bunder (Rs.1585 per month) while the value is lowest for KharoChhan

(Rs.900 per month). The lowest value for Kharo Chhan is because of the

distance (approximately 20 km) between the community and the forest area

(Detailed information across households of different income categories is

provided in Appendix Table).

b) Forest Product – Poles and Wood for Housing

Although literature has identified that the wood form the mangrove forest is

used for the building houses or building poles as well but our data shows that

in Keti Bunder, the community is not dependent on the wood for building

houses neither the community is using mangrove forest for building poles. The

overall economic value of wood used for building houses or poles is estimated

around Rs.111 per month only. The value is higher for Kharo Chhan area

(Rs.300 per month) while for Shah Bunder the economic value is around 150

per month only (Table 5.3).

Table – 5.3

Economic Valuation of Wood for Pole and House Construction (Rs.)

Talukas Total

Keti Bunder Kharo Chhan Shah Bunder Pole

Marketed Wood for Housing

Pole Marketed

Wood for Housing

Pole Marketed

Wood for Housing

Pole Marketed

Wood for Housing

Total

- - 150 150 148 50 111 62

- - (662) (802) (1125) (447) (861) (510)

(40) (40) (40) (40) (80) (80) (160) (160)


0

100

200

300

400

500


Eco

no

mic

Valu

e (

Rs.)

Income Levels

Figure - 5.3(a)

Economic Valuation of Wood for Pole across Income Categories


33

c) Forest Product – Animal Browsing (Camel and Goat)

Khalil (1999) suggested that the mangrove leaves (including Avicennia

marina) are very nutritious, and support 16,000 camels and 11,000 cattle.

Based on the data from a household survey,Khalil estimated that the Indus

delta yielded 2 million kg of fodder per year that was worth Rs 2.56 million

per year.Her valuation was based on a price of Rs 1.25 per kg of mangrove

fodder.Keerio and Bhatti (1999) estimated that mangroves are populated with

the cattles beyond their capacity to produce fodder to feed. According to

Keerio and Bhatti (1999) there were 6000 camels, 3200 buffaloes and about

8000 goats, sheep and cows dependent on mangroves.

Table – 5.4

Cattle Population in Mangrove Forest Area (#)

Cattles

# Camels # Buffaloes

Total 6,000 3,200

Source: IUCN.

0

100

200

300

400

500


Eco

no

mic

Valu

e (

Rs.)

Income Levels

Figure - 5.3(b)

Economic Valuation of House Construction across Income Categories


34

Table – 5.5.1

Number of Goats and Camels (#)

Talukas Total


# Goats #

Camels # Goats

# Camels

# Goats #

Camels # Goats

# Camels

Total 16 30 27 2 6 46 49 78


0

500

1000

1500

2000

Keti Bunder Kharo Chhan Central ShahBunder

East ShahBunder

Ec

on

om

ic V

alu

e (

Rs

.)

Talukas

Figure - 5.4

Camel Population in Mangrove Forest Area


0

5

10

15

20


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.5.1(a)

Number of Goats across Income Categories


35

Table – 5.5.2

Numbers of Buffaloes and Cows (# Animals)

Talukas Total

Keti Bunder Kharo Chhan Shah Bunder #

Buffalos # Cows

# Buffalos

# Cows #

Buffalos # Cows

# Buffalos

# Cows

Total 23 10 17 14 58 20 98 44


0

10

20

30

40

50


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.5.1(b)

Number of Camels across Income Categories


0

5

10

15

20

25

30


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.5.2(a)

Number of Buffaloes across Income Categories


36

Although Table 5.4 extracted from Shah (1999) shows high population of

camels and buffaloes but our sample survey show very low presence of

animals in the three talukas. Overall 269 animals were reported in the sample

survey (49 goats + 78 camel + 98 buffaloes + 44 cows by 160 households

surveyed). The number is higher for Shah Bunder while lowest for Kharo

Chhan. According to Khalil (1999) on average, fodder consumption per

animal unit was 3.82 kg/day, of which 1.22 kg were mangrove leaves. Hence

overall mangroves represent some 32% of domestic animal feed.

In order to estimate the costs of fodder obtained from mangrove forest,the

estimated total economic requirement were based on the Khalil data (3.82 kg

per day per animal) around 269 animals * 3.82 kg/day = 1,027.6 kg/day/animal.

Second, as only the 32% of fodder is based on mangrove leaves, the economic

value of fodder obtained from mangrove was estimated

[(1027.6 * 32)/100=328.8 kg/day]. Finally we converted the daily value on

monthly requirements(after assuming the price per Kg equals Re.1) as

Rs.9,864/month.

d) Forest Product – Herbs and Medicines

Ruitenbeek (1992) for Indonesia estimated an annual benefit for medicinal

plants of US$ 15/ha for mangroves.The value is based on a general estimate of

the biodiversity value in forests that can be captured. For Pakistan none of the

studies have confirmed the use of Mangrove as herbs or medicines. It was

assumed that the economic benefits of the mangroves do not include

medicines or herbs. But contradictory to the assumptions,it was observed

during visits to Keti Bunder that a group of people was picking Maroore

(a herb found in the stem of mangrove trees). According to the local people

Maroore is used as medicine and they earn around Rs.50 per kg.

0

2

4

6

8

10

12

14


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.5.2(b)

Number of Cows across Income Categories


37

Table – 5.6

Economic Valuation of Herbs Marketed

Talukas


Total

25 0 0 6

(158) (0) (0) (79)

(40) (40) (80) (160)


The average value recorded was around Rs.25 per month. Mostly households

having income 11,000 to 25,000 were involved in Maroorepicking.

e) Forest Product – Honey (Apiculture)

Both Avicennia marina and Rhizophoramucronatta are rich in nectar and

pollen on which honey bees can be reared. Khan (1999) has reported that

mangrove forest in Karachi coast produced 142 kg of honey during

May-June 1997.

Our sample survey shows that the production of honey per household per

month in the mangrove area was valued around Rs.9. The estimated value per

month in Keti Bunder area is around Rs.15 per month while the estimated

amount for Shah Bunder is approx. Rs.11 per month. Local people of Kharo

Chhan have not reported the production of honey in the area.

0

10

20

30

40

50

60

70


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.6

Economic Valuation of Herbs Marketed across Income Categories


38

Table – 5.7

Economic Valuation of Honey Marketed

(Rs./Household/Month)

Talukas


Total

15 0 11 9

(66) (0) (38) (43)

(40) (40) (80) (160)


f) Habitat of Other Species: Crabs, Shrimps (on Site) and Shell Fish (off Site)

According to Khalil (1999) mangroves of Indus delta provide shelter for some

coastal species such as shrimps as well. Kahlil (1999) has reported that

Pakistan's shrimp fishery entirely depends upon the mangrove ecosystem.

Pakistan is earning some US $100 million annually from shrimp export.Our

sample survey also indicates huge economic dependence of household on



3232 from shell fishes). The value is highest for the shrimp catch in Keti

Bunder (approx. 27,378 per month) while households of Shah Bunder and

Kharo Chhanwere earning around Rs.10,000 per month from the shrimp catch.

People of Keti Bunder were also earning approx. Rs.10,000 per month from

the sale of shell fishes as well (Table 5.8).

0

20

40

60

80

100


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.7

Economic Valuation of Honey Marketed across Income Categories


39

Table – 5.8

Economic Valuation of Crabs and Shrimps Marketed (on Site) (Rs.)

Talukas Total


Crabs Shrimps Crabs Shrimps Crabs Shrimps Crabs Shrimps

Total

5218 27378 2630 9458 2070 9474 2997 13946

(10608) (55296) (5209) (20823) (4345) (25859) (6734) (35343)

(40) (40) (40) (40) (80) (80) (160) (160)

Note: For details, see Annexure Tables.


0

5000

10000

15000

20000


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.8(a)

Economic Valuation of Crabs Marketed (on Site) across Income Categories


0

10000

20000

30000

40000

50000

60000

70000


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.8(b)

Economic Valuation of Shrimps Marketed (on Site) across Income Categories


40

The situation is not much different for sale of crab as well. People of Keti

Bunder were on average earning around Rs.5000 per month from the sale of

crab. People of KharoChhan reported were earning almost Rs.2600 per month

while the people of Shah Bunder were earning only Rs.2000 per month from

the sale of crab. Overall these species were almost entirely dependent on

mangrove ecosystem in the Indus delta.The estimated economic value of

mangroves was around Rs.20,175 per month (Table 5.8).

In addition, the households also reported catch of shellfish from all these

talukas. The highest level of Rs.10,425 per month per household was reported

in Keti Bunder, followed by Rs.1,303 in Kharo Chhan and Rs.600 in Shah

Bunder. On the whole, the average value of shellfish for all talukas was

Rs.3,232 per household per month (Table 5.9).

Table – 5.9

Economic Valuation of Shell Fish (Rs.)

Talukas


Total

10425 1303 600 3232

(63199) (2375) (2023) (31631)

(40) (40) (80) (160)

Note: Detailed tables annexed.


g) Recreation and Tourism

Mangrove ecosystem is famous for tourism and constitutes an important part

of world tourism. Estimates show that the number of international tourists has

reached to 940 million in 2010.Travel and tourism generates around 5 percent

of the gross domestic product of the global economic activity and an estimated

6 to 7 percent of the world’s jobs [UN World Tourism Organization (2010)].

International tourists mostly prefer coastal areas for visits. Wetland and

0

10000

20000

30000

40000


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.9

Economic Valuation of Shell Fish across Income Categories


41

Wildlife make them ideal locations for tourism.The incomegenerationfrom

ecotourism could be significant and could provide significant support to the

livelihoods to the local communities.Pakistan’s wetlands are locally and

globally attractive. There are 19 sites of wetlands that have international

importance (these sites are designated as internationally important by the

Ramsar Convention in 2002).These sites although provide good attraction for

tourists but are currently not well developed for international tourism

purposes. Therefore a vast majority of the area has very small recreational

value. Table 5.10 shows among the household surveyed that almost 401

persons responses whowere that householdswere visiting mangrove forest for

bird watching, fish and shrimps viewing and for recreation purposes only.

Specifically 81% of the households visit mangrove to view fish and shrimps,

around 78% for recreation/enjoyment and around 91% visits mangrove area

for bird watching (Table 5.10).

Table – 5.10

# People Visiting Mangroves Area in All Talukas

# People Visiting Mangroves for: No Yes Don’t Know

Fish & Shrimp Viewing 25 130 5

Recreation 28 125 7

Bird Watching 12 146 2


In the absence of the reported data the analysis was based on the available

information gathered through field visits. As one household can visit

mangrove area for multiple purposes, the average of the visits to came up with

an average number of 134 households (i.e. almost 84%) of household visiting

mangrove forest. Assuming that the tourism is the major source of income for

the coastal community, estimated cost of visiting mangrove using the market

price/cost was estimated as follow:

Average Value of Visiting Mangrove = Number of visitors * (entrance fee +

Fuel Cost + food expenditure + any

other expenditure)

Table – 5.11

Costs Incurred in Visiting Mangroves (Based on Sample Households)

(Rs.)

Average Cost

Keti Bunder

Kharo Chhan

Shah Bunder

Fuel Cost 810 1201 1078 479

Permit cost 4 3 3 5

Food Expenditure 376 685 364 228

Other Expenditure 49 56 85 28


42

The cost of visiting mangrove was considered here as the income generated

from the ecotourism. The estimated travel cost of tourism mentioned in table

5.11 is based on the sample survey. In order to estimate the overall amount for

the whole community the economic value was estimated. Table 5.12 explains

the details.

Table – 5.12

Costs Incurred in Visiting Mangroves (Projected at Taluka Level)

(Rs./Month)

Talukas Total Keti

Bunder Kharo Chhan

Shah Bunder

A) # Household 3,989 3,654 10,915 18,558

B) Average # Household Visiting

Mangrove Forest (84% of the total) 3,351 3,069 9,169 15,588

Cost of Visiting Mangrove Forest

C) Fuel Cost 1,201 1,078 479 919

D) Permit cost 3 3 5 4

E) Food Expenditure 685 364 228 426

F) Other Expenditure 56 85 28 56

Ecotourism Value (B*(C+D+E+F)) 6,517,695 4,695,570 6,785,060 21,901,140


Table 5.12 shows that current value of ecotourism in all talukas in mangrove

area was around Rs.22,000. The value was highest for the Shah Bunder area

while lowest for the Kharo Chhan area.

h) Education and Research

Mangrove sites around the world attract a lot of researchers, students and

school classes who want to learn more about this intertidal habitat.

Kairoet al.(2009) and Spurgeon (2002) used value of fundingperstudents to

evaluate the value of mangrove for education and research. We this studythe

amount of funding for Ph.D, M.Phil and M.Sc. awarded by HEC to quantify

the research and education value of the mangroves was used.For that the data

of student doing Ph.D, M.Phil.and M.Sc. on mangroves was utilized. As there

is no published data available, different departments of Karachi University

were contacted to come up with a number of students working on mangroves.

This number was multiplied to the amount of scholarship provided by HEC to

come up with the economic value of mangrove.

PhD = 5 * Rs.10,000per Month

M.Phil = 3 * Rs.5,000per Month

Total value = Rs.65,000 per month.

The funding and research value per month was therefore Rs.65,000. It is,

however, acknowledged that the figure could be under estimated as the exact

number of students studying mangrove could be higher.

43

5.2.2 Indirect Value

a) Support to Fishing

The coastal area of the Indus delta is largely underdeveloped. The local

community depends on fishing and traditional profession. Higher returns

from fishing also result in attracting more people in fishing. The growth in the

sector is also due to the government policy to incraese revenue from the export

of fishes and high quality shrimps.

As the fish catch in the Indus delta is highly dependent on the mangrove

ecosystem, the importance of mangrove in sustaining the productivity of

on-shore and off-shore fisheries cannot be ignored. The review of literature

points out that mangrove forest is serving as breeding grounds for about 200

fish species. The household survey data shows 92 households, out of a total of

160, involved in fishing. The mangrove ecosystem supports production of

fishes of approx. Rs.29,542 per month. Monthly income estimated includes

value of fish used domesticaly and commercialy sold. Avearge value was

higher for Keti Bunder (Rs.63,382 marketed + Rs.2,149 non maketed = 65,

531) while lowest for Shah Bunder (Rs.8060 marketed +Rs.1351 non

marketed = Rs.9411 per month).

Moreover, average mangrove value of fish catch for domestic use was

estimated across different income groups i.e. subsistence (income less than

10,000), poor (income between 11,000 to 25,000), medium (income between

26,000 to 50,000) and rich household (more than 50,000) the estimated levels

were Rs.1113/month, Rs.2033/month, Rs.2227/month and Rs.6116/month,

respectively (Table 5.13). (For details, see Appendix Table 5.13).

Table – 5.13

Economic Valuation of Benefits Marketed and Non-Marketed Fish Catch


Keti Bunder Kharo Chhan Shah Bunder Total

Non-Marketed

Marketed Non-

Marketed Marketed

Non-Marketed

Marketed Non-

Marketed Marketed

Total

3913 29900 2149 63382 1351 8060 2191 27351

(4526) (73494) (2483) (301836

) (1603) (16548) (2986)

(155958

)

(40) (40) (40) (40) (80) (80) (160) (160)

Note: For greater details, see appendix table).


44

b) Shoreline Protection - Buffer to Cyclone

The literature identifies the presence of mangrove forest especially Avicennia

marina to ensure the firm and stable formation of shorelines. The term

shoreline protection is, not clearly defined. The term can refer to either

protection from soil erosion or protection from sea cyclone/tsunamis and

storms. In this study we have focused only on the valuation of mangroves as

protection against extreme weather events such as tsunamis, sea cyclones or

hurricanes.

The valuation of mangrove forest as an instrument for shoreline protection is a

complex subject. The most widely used technique is the Replacement Cost

Technique. For this technique the value of a man-made seawall is derived

having the same protective effect for the shoreline. The value is then applied

0

20000

40000

60000

80000

100000

120000

140000

160000

180000


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.13(a)

Economic Valuation of Benefits Marketed across Income Categories


0

2000

4000

6000

8000


Ec

on

om

ic V

alu

e (

Rs

.)

Income Levels

Figure - 5.13(b)

Economic Valuation of Benefits Non-Marketed across Income Categories


45

to the mangroves (Kairoet al.2009, Spurgeon 2002). The alternate method is

the “Damage Cost Avoid Technique”. This calculates potential damage of a

sea cyclone if mangroves did not exist (Ruitenbeek, 1992).

History of sea cyclone in Pakistan shows that Pakistan first experienced an 8.7

magnitude earthquake in Makran coast in 1945. It resulted in a huge tsunami

in the Arabian Sea and killed more than 4,000 people. Second deadly storms

hit Karachi coast in 1965, causing 10,000 casualties. In 1999, another cyclone

killed 6,200 people after making landfall at Shah Bunder.It was, thus, assumed

that there is only 10% likelihood for a sea cyclone to hit coastal areas in next

20-30 years, given its increased frequency in recent years. Around 18,558

houses having average price equalsRs.500,000 and assuming an additional

protection of 73 per cent, the shoreline protection value of the mangroves was

estimated as follows outlined in Table 5.14(a).

Table – 5.14(a)

Estimation of Value Shoreline Protection at Sampled Population Level (Rs.)

Based on Sample Population Keti

Bunder Kharo Chan

Shah Bunder

Total

A. Number of houses 40 40 80 160

B. Average house price 600,000 400,000 500,000 500,000

C. Average Value of other assets 240,000 160,000 200,000 200,000

D. Total Value of household assests 840,000 560,000 700,000 700,000

E. Value of houses (Rs.) (A*D) 33,600,000 22,400,000 56,000,000 112,000,000

F. Likelihood of severe weather event 10% 10% 10% 10%

G. Value of protection (E*F*0.73 ) Rs. 2,452,800 1,635,200 4,088,000 8,176,000

H. Value per Month Rs. (G/12) 204,400 136,267 340,667 681,333


Table – 5.14(b)

Taluka Wise Projection of Values of Shoreline Protection (Rs.)

Based on Projection at Taluka Level

Keti Bunder

Kharo Chan

Shah Bunder

Total

A. Number of houses 3,989 3,654 10,915 18,558

B. Average house price 600,000 400,000 500,000 500,000

C. Average Value of other assets* 240,000 160,000 200,000 200,000

D. Total Value of household assets 840,000 560,000 700,000 700,000

E. Value of houses (Rs.) (A*D) 335,076,0000 204,624,0000 764,050,0000 12,990,600,000

F. Likelihood of severe weather event 10% 10% 10% 10%

G. Value of protection (E*F*0.73 ) Rs. 244,605,480 149,375,520 557,756,500 948,313,800

H. Value per Month Rs. (G/12) 20,383,790 12,447,960 46,479,708 79,026,150

I. Value per Month per household Rs. 5,110 3,406 4,258 4,258

J. Area Mangroves (ha) 7,241 8,133 39,347 54,721

K. Value shoreline protection

/hac/month (H/J) 2,815 1,531 1,181 1,444


46

e) Carbon Storage and Fish Biomass

U.N. (1996) reports on the level of productivity and carbon fixation (in terms

of grams of carbon fixed per square meter per day) in Arabian Sea. It reveals

that the Arabian Sea is on top of the world with a carbon fixation of 1.5-1.8

gC/m2/day which is 10 times the world ocean and 4 times the average values

of the Indian Ocean (Reference Ryther and Menzel, 1964). Though the daily

estimates on carbon fixation occasionally reaches a level of 5 gC/m2/day in

some oceans but the comparison across oceans are based on averages where

the Arabian Sea appears to be the most productive.

The report quoting the same reference also claims that the Arabian Sea shows

an equivalence of 9.4 million ton of fish biomass in the EEZ of Pakistan. It,

however, needs to be noted with the care that the productivity of the Arabian

Sea is not distributed evenly. The Gulf of Oman has the highest productivity

of fish biomass when compared with other parts of the Arabian Sea.

Economic Perspective (2003) highlights the challenges faced at the World

level due to overfishing and the world leaders concerns. The 25th meeting of

the FAO’s Committee on Fisheries (COFI) and World Summit on Sustainable

Development at Johannesburg in 2002, while expressing world leaders

acknowledgement of the vital role of marine fisheries to economic and food

security and to biodiversity in general, showed its concerns:

“to maintain or restore stocks to levels that can produce maximum sustainable

yield with the aim of achieving these goals for depleted stocks on an urgent

basis and where possible not later than 2015”.

The paper also expresses concerns in the light of UNCED’s Agenda 21 which

pointed out that 50 percent of world population lived within 60 kilometers of

coasts in 1992 and by 2020 this proportion would increase to 75 percent. That

likely upward change will put all living and non-living resources in coastal

zones under increasing pressure.

5.2.3 Non Use Value

The estimated non-use values were based on willingness to pay (WTP)

method.Specifically, it shoedhow much local community is willing to pay for the

conservation, protection and development of the mangroves forest. This expresses the

intrinsic value of mangroves. The value is the acknowledgement of the existence of

the mangroves in the ecosystem (Ghani, 2006).

47

Table – 5.15

Type and Nature of Community Willingness to Participate (# Households)

Community Willing to Participate


As Wage Labour 112 27

(67.5%)

27

(67.5%)

58

(72.5%)

As Voluntary Labour 39 12

(30%)

13

(32.5%)

14

(17.5%)

Not Willing to Contribute 9 1

(2.5%) 0

8

(10%)

Total 160 40 40 80


Table – 5.16

Estimation of WTP Based on Descriptive Analysis


Total

Keti Bunder

Kharo Chhan

Shah Bunder

A. Household visited 160 40 40 80

B. % Household willing to pay (WTP) 25 30 33 18

C. # days per month willing to work 3 4 2 2

D. Average daily Wages in the Village 250 250 250 250

E. WTP (Rs./month) - C*D 750 1000 500 500

F. Total number of Houses 18558 3989 3654 10915

G. Area of mangroves (ha) 54721 7241 8133 39347

H. # of household willing to pay 4453.92 1196.7 1187.55 1910.125

I. Total value (Rs/month) - H*E 3340440 1196700 593775 955063

J. Value of mangroves (Rs./ha/Month) - I/G 61 165 73 24


Tables 5.15 and 5.16 provide estimate on the amount community was willing to pay.

This was the income they were willing to sacrifice for providing the services. During

the fields survey it was specifically askedfrom each household as to how many days

per month they will be willing to work voluntarily. This led to the computationof the

income on daily basis in estimating the income each household werewilling to forgo

in providing labour for the development of mangroves. This forgone income was

taken as the amount they were willing to pay. Table 5.16 shows that out of the 160

household surveyed 25% were willing to pay for the conservation of mangrove forest.

The total amount of the households willing to pay was around Rs.30,000 per month

[160x0.25x750]. By projecting the amount for the overall households in the three

talukas, we estimated an overall economic value of mangrove around Rs.3,340,440

per month per household. However the computation is based on the descriptive

analysis only while literature has identified a number of techniques to compute the

amount community is willing to pay. One such technique is already outlined in an

earlier section on methodology using Tobit model.

We also estimated the regression model using Tobit model to compute WTP. Results

are reported in Tables 5.17 and 5.18.

48

Table 5.17 shows positive and significant effects of the amount household were

willing to pay. This shows that the community was motivated significantly for the

conservation of the mangrove forest. On average, a household was willing to pay

around Rs.2,518 per month for the protection and development of mangrove forest.

Keti Bunder being the more economically developed taluka among the three talukas

surveyed, shows that each household was willing to pay around Rs.4,145 per month.

In contrast to the households of Keti Bunder, households of Shah Bunder, being more

deprived than the rest of the two, shows low willingness to pay (approx.2,177 per

month per household).(Table 5.18).

Table 5.17 also shows significant and positive effect of ownership of livestock on the

household willing to participate for the conservation and development of mangroves.

The reason is straight forward, householdshaving livestock directly dependent on

mangroves for the fodder. However the effect is not significant for Keti Bunder. For

Keti Bunder availability of electricity and per capita household income shows

significant but negative effect. For Kharo Chhan agriculture land ownership shows

significant and negative effects while the effect of agriculture land ownership is

positive and significant for Shah Bunder.Overall goodness of fit test indicates that our

model was not a weak model and explained almost 20 percent of the variation in the

dependent variable.

Table – 5.17


Coef. T-Stats Coef. T-Stats Coef. T-Stats Coef. T-Stats

Amount Willing to

Pay 0.0004 6.4* 0.0003 3.15* 0.0004 2.97** 0.0004 4.69*

Family Size -0.0051 -0.96 -0.01 -1.11 -0.01 -0.94 -0.008 -0.83

Highest Education

Completed -0.0007 -0.07 -0.02 -0.84 -0.0004 -0.02 0.003 0.18

Log per Capita

Household Income -0.045 -1.27 -0.11 -2.4** 0.008 0.07 -0.09 -1.36

Agriculture land

Own -0.001 -0.5 0.02 0.87 -0.003 -1.6*** 0.004 2.27*

Ownership of

Livestock 0.156 2.1** 0.34 1.53 0.239 1.7*** 0.19 1.75***

Ownership of

House -0.110 -1.51 0

0

-0.17 -1.6***

Availability of

Electricity -0.049 -0.59 -0.33 -2.6** 0.11 0.49 0.01 0.04

Availability of Gas 0.196 1.09 0

0

0.19 0.51

Constant 0.970 3.93* 1.85 4.36* 0.52 0.65 1.23 2.61**

Log likelihood -105.6 -12.0 -24.8 -58.1

F-stat 5.23 1.62 2.34 3.1

Prob. > chi2 0.00 0.166 0.047 0.003

Number of obs. 160 40 40 80

left-censored obs. 32 5 8 19

Pseudo R2 0.20 0.48 0.24 0.19


49

Table – 5.18

Willingness to Pay on Household Level (Rs.)

Amount Household Willing to Pay (Rs./Month)

Total Keti

Bunder Kharo Chhan

Shah Bunder

Mean WTP = (1/B1) * ln [1+eβ0+∑βiXi] 2,518 4,145 2,362 2,177


5.3 Derivation of Total Value of Mangroves Forest

In determining the total valuation of mangroves, issues such as number of non-timber

forest products, recreation and tourism, education and research were considered in

addition to support to fish and shoreline protection, willingness to pay to protect

mangroves. A detailed account of such benefits at the level of sampled households has

been presented in Table 5.19.

Table – 5.19

Valuation of Mangrove per Household per Month


Keti

Bunder Kharo Chhan

Shah Bunder

All Talukas

BENEFITS (Per Household per Month)

Fuel Wood 1,585 900 1,446 1,344

Wood for Poles and Housing 300 198 173

Animals Browsing 3,632 2,200 4,732 9,864

Herbs & Medicine 25 - - 6

Honey (Apiculture) 15 - 11 9

Habitat for Other Species 43,021 13,391 12,144 20,175

Recreation and Tourism 1,634 1,285 622 1,180

Education and Research - - - 3.5

Support to Fish 33,815 65,531 9,411 29,542

Shoreline Protection 1,460 1,095 1,278 1,278

Carbon Storage - - - -

Amount Willing to Pay 4,145 2,362 2,177 2,518

Total Benefit of Mangroves 89,332 87,064 32,019 66,093

COST (Per Household per Month)

Fuel Cost 36,037 32,350 14,381 28,287

Permit Cost 87 78 142 113

Depreciation 7,065 6,587 3,247 5,037

Food Cost 20,557 10,927 6,835 11,287

Others (15% of the Total) 9,562 7,491 3,691 6,709

Total Cost of Mangroves 73,308 57,433 28,296 51,433

Total Economic Value 16,024 29,631 3,723 14,660

50

The table also provides cost estimates in acquiring those forest products mentioned

above. It shows an economic value of Rs.14,660 per household per month for the 160

sampled households.

The estimates made at the sampled household level were projected at the taluka level

keeping in view the total number of households and total area under mangrove in each

of the three talukas.

The valuation of mangrove was further classified into marketed (Rs.48,454) and

non-marketed (Rs.17,839) values.Table 5.20 provides disaggregated levels of

valuation across on-site and off-site activities. It also shows levels of indirect benefits

and other benefits i.e. non-use values.

Table – 5.20

Levels of Benefit


Benefits (Use Value) On-Site Off-Site

Marketed (Direct Use)

Fuel Wood (Rs./Month) 549

Wood for Poles and Housing (Rs./Month) 173

Herbs & Medicine(Rs./Month) 6

Habitat for Other Species (Rs./Month) 17,984

Support to Fish (Rs./Month) 29,542

Sub-Total (Marketed) 18,712 29,542

Non-Marketed (Indirect Use)

Shoreline Protection (Rs./Month) 1,278

Animals Browsing (Rs./Month) 9,864

Fuel Wood (Rs./Month) 795

Honey (Apiculture) (Rs./Month) 9

Habitat for other Species (Rs./Month) 2,191

Sub-Total(Non-Marketed) 14,137

Other Benefits(Non-Use Value)

Recreation and Tourism (Rs./Month) 1,180

Education and Research 3.5

Amount Willing to Pay (Rs/Month) 2,518

Sub-Total (Other Benefits) 3,702

Total(Marketed and Non-Marketed) 66,093

It implies that at sampled household level, a total valuation of Rs.66,093 per month

which carries a share of 73.0 percent (for marketed and 21.4 percent of non-marketed

part), and 5.6percent as non-use values.

Table 5.21 summarizes the entire analysis on the valuation of mangroves presented in

earlier sections. It explains the way the valuation of Rs.66,093pr household per month

was projected at the taluka level (i.e. all three talukas taken jointly) keeping in view

the estimated number of 18,558 households. It shows an annual level of Rs.14.719

billion for all talukas level. The table initially shows levels of aggregate benefits (i.e.

all benefits directly, indirectly and non-use values) in sub-section A.

51

In sub-section B, it portrays the levels of costs and shows an annual level of costs as

11.45 billion rupees.

In sub-section C, it shows an estimated level of values of $ 1,762 per household per

yea, and $ 597 per household per hectare of mangrove area.

Tables – 5.21

Computation of Total Benefits and Cost at Aggregate Level (Rs./Month)

A. Gross Benefits

Gross Benefits/Household/Month(Rs.) 66,093

# of Households 18,558

Gross Benefits at Aggregate Level/Year (Rs. Billions) 14.719

Gross Benefits at Aggregate Level/Year(US$ Millions) 147.19

Gross Benefits at Aggregate Level/Household/Year(US$ Millions) 7,931

Forest Area of Mangroves(Hectares) 54,721

Gross Benefits at Aggregate Level/Hectare/Year(US$) 2,690

B. Aggregate Cost

Aggregate Cost/Household/Month (Rs.) 51,433

# of Households 18,558

Aggregate Cost/Year (Rs. Billions) 11.45

Aggregate Cost/Year(US$ Millions) 114.50

Aggregate Cost//Household/Year(US$ Millions) 6,171

Forest Area of Mangroves (Hectares) 54,721

Aggregate Cost//Hectare/Year(US$) 2,093

C. Ratio (B–A)

Net Value/Household/Year (US$) 1,762

Net Value/Hectare/Year (US$) 597

5.4 Comparative Estimates on Valuation of Mangroves

The valuation of mangroves presented in the preceding section was compared with

other estimates made for similar mangroves regions.

Table – 5.22

Comparative Estimates on Valuation of Mangroves (in US$)

Source Year Country Estimation of Benefits

Per Household/Year Per Hectare/Year

1. Sathirathi 2000 Thailand 1,422 239

2. IUCN 2007 Sri Lanka 1,171 -

3. UNEP 2011 Kenya 1,092 840

4. IUCN 2013 Pakistan 1,762 597

Source: Various Reports (including this study).

Table 5.22 presents a comparative statement highlighting valuation estimates on

mangroves in different regions. The current study’s estimates were US$ 597 per

hectare of mangrove per year. Similarly, the estimated value per household per year

52

was US$ 1,762. Those estimates on annual level seem consistent with other regions if

the time factor is taken into account.

Another reason for somewhat higher estimate on Pakistan’s mangroves could be

related to the fact that the Arabian Sea is considered a highly productivity region for

biomass of fishing which is 10 times the world average and 4 times that of the Indian

Ocean.

Nevertheless, these levels of valuation indicate the potentials reposed, and efforts are

needed to make the region’s potentials sustainable in the long run. The amount of

efforts, resources and in-depth scientific work that would be required can hardly be

overemphasized.

5.5 Distribution of Total Economic Benefits of Mangroves Annually

Figure – 5.5.1

Distribution of Total Economic Benefits of Mangroves

Total Economic Benefits

$ 147.2 Million

Use Values $139 Million

Non-Use Values

$8.2 Million

Direct Benefits $107.5 Million

Indirect Benefits $31.5 Million

Eco-Tourism $2.6 Million

WTP $5.6 Million

53

The Flow Chart 5.5 shows distribution of total benefits into use values and

non-use values. Within use values, it decomposes into direct and indirect

benefits. Similarly, in case of non-use values it splits into assumed benefits of

eco-tourism and willingness to pay.

In proportional terms, the direct benefits tend to dominate by exercising a

share of 73 percent of the total value of benefits. The indirect benefits had a

share of 21.4 percent, followed by eco-tourism 3.8 percent. The anticipated

benefits through community’s willingness to pay (participate), for voluntary

work in planting mangroves and its future development, accounting for 1.8

percent of total benefits.

5.6 Derivation of Benefit-Cost Ratio and IRR

Based on the estimates on costs and benefits derived from mangrove forest presented

earlier, the economic analysis focused on the derivation of benefit-cost ratio and

internal rate of return on the plantation of 10,350 hectares by Sindh Forest

Department (SFD) in the Indus Delta under Sindh Costal Community Development

Project (SCCDP).

It would not be irrelevant here to mention the broadly defined benefits received by the

local community under the mangrove plantation. These direct benefits include:

a) employment of nearly 40,000 man days of paid labour in plantation and

maintenance (i.e. replantation to increase success rate).

b) 518 boat days employed in transporting hired labour to the area of plantation.

This activity produced significant income earnings for the boat owners in the

area.

c) employment of 8 guards for the up keep of planted area.

Willingness to Pay 1.8%

Eco-Tourism 3.8%

Indirect Benefits

21.4%

Direct Benefits 73%

Flow Chart - 5.5.1

Distribution of Total Economic Benefits of Mangroves Annually

54

d) employment of IUCN staff comprising supervisors and field assistants.

e) establishment of base camps in the area that provided further income and

employment opportunities in the area.

These above mentioned benefits were measured in the light of the information

provided by IUCN and SCCP directorate. In addition, the detailed estimates on net

valuation of benefits (on a per unit basis) estimated under the study were added to

streamline the annual costs incurred and benefits likely to be received under the

plantation of mangroves under SCCDP.

The SF department carried out the plantation work on 10,350 hectares during the five

year period i.e. 2009-2013. During the period, the success rate was reported at 96

percent in Shah Bunder taluka and 100 percent in Keti Bunder taluka (Monitoring &

Evaluation Report of IUCN, June 2013). Based on this, it is expected that there exists

a higher possibility of success.

Benefit-Cost Ratio

In view of above, derivation of benefit-cost ratio and internal rate of return were

carried out to judge the economic significance of such interventions.

Table 5.23 describes the streams of costs and expected benefits related to mangrove

plantation. The costs are spread over evenly through the first five years of the activity.

Since mangrove plants take longer in providing the benefits, the stream of benefits

was assumed to start from the 15th

year onwards to 30th

year.

Keeping in view the initial fixed costs and net present worth of future benefits (using

an annual discount rate of 10 percent), the activity shows a benefit-cost ratio of 3.56

which is quite significant. It is a conservative estimate and the real benefits may

exceed and thereby would increase the profitability even further. As a note of caution,

however, it must be stressed that such a success depends on higher survival rate as

well as protection of forest from the pressures of human actions i.e. a sustainable

development of mangroves appears as the necessary condition in achieving higher

levels of benefits.

Internal Rate of Return (IRR)

In order for any activity to be acceptable (i.e. bankable) for investment, it is always

necessary to compute internal rate of returns. Based on the flows of cash during the

expected life of the project/activity, as discussed earlier, an implicit rate of interest of

10 percent annually was used in deriving IRR.

An IRR of 25 percent was estimated which provides sufficient capacity for the

investment to take place.

55

Table – 5.23

Computation of Benefit-Cost Ratio on Mangrove Plantation under SCCDP (in US$)

Annual Cost Year 1 to

Year 5 Year 15 Year 16 Year 17 Year 18 Year 19 to Year 26 Year 27 Year 28 Year 29 Year 30

A. Cost of Plantation US$ Area (Hectare) 2070 Plantation Cost /Hectare 99 Total Plantation Cost 204930

B. Cost of Maintenance @30% of Plantation Cost Area(Hectare) 621 Plantation Cost / Hectare 33 Total Plantation Cost 20493

C. Boat Cost Boat Days @ one boat covering 4 hectares 518 Boat Cost/day 140 Total Boat Cost 72520

D. Cost of Guard (8 Guards @$150/month) 14400 E. IUCN (Cost of Supervisor & Field Assistance) 11400 F. Base Camp Cost @ One Percent of Cost of A,B,C,D 3123 C. Total Cost (A+B+C+D+E+F) 326866 D. Benefits of Mangroves US$

Area(Hectare) 2070 2070 2070 2070 2070 Benefits /Hectare (as per estimated of $722/year/hectare) 722 722 722 722 722 Total Benefits US$ 1494540 1494540 1494540 1494540 1494540

1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 2989080 4483620 5978160 7472700 8967240 7472700 5978160 4483620 Total Gross Benefits (Net Present Value @10 % annually) 5,824,194.92 Total Cost 1,634,330.00 Benefits Cost Ratio 3.56

56

Table – 5.24

Derivation of Internal Rate of Return (IRR) on Mangrove Plantation under SCCDP

(in US$)

(A)

Cash Outflow

(B)

Cash Inflow

(C)

Cash flow (B-A)

Year1 326,866 0 -326,866

Year2 326,866 0 -326,866

Year3 326,866 0 -326,866

Year4 326,866 0 -326,866

Year5 326,866 0 -326,866

Year6 0 0 0

Year7 0 0 0

Year8 0 0 0

Year9 0 0 0

Year10 0 0 0

Year11 0 0 0

Year12 0 0 0

Year13 0 0 0

Year14 0 0 0

Year15 0 1,494,540 1,494,540

Year16 0 2,989,080 2,989,080

Year17 0 4,483,620 4,483,620

Year18 0 5,978,160 5,978,160

Year19 0 7,472,700 7,472,700

Year20 0 7,472,700 7,472,700

Year21 0 7,472,700 7,472,700

Year22 0 7,472,700 7,472,700

Year23 0 7,472,700 7,472,700

Year24 0 7,472,700 7,472,700

Year25 0 7,472,700 7,472,700

Year26 0 7,472,700 7,472,700

Year27 0 8,967,240 8,967,240

Year28 0 7,472,700 7,472,700

Year29 0 5,978,160 5,978,160

Year30 0 4,483,620 4,483,620

IRR 25%

57

CONCLUSIONS AND RECOMMENDATIONS

1. The on-site (i.e. coastal environment) is interrelated with off-site (open sea

environment) and jointly appear as a great natural resource on which the

coastal communities depend heavily for their livelihood.

2. However, if such an exclusive dependence continues in the long run, it may be

productive or unproductive for mangroves based on how this great natural

resource is valued by the coastal communities. Such an understanding (or lack

of it) would be pivotal to the long run sustainability of mangroves in the

region.

3. A number of Focused Group Discussions (FGD’s) were conducted to

understand the community relationship with mangroves. According to the

participants the reasons behind the reduction are: reduced supply of sweet

water and sediments, over cutting of mangroves for sale of timber, fuel wood

and poles for housing. Participants also criticized decision of the government

about restriction on the Indus water flows at Kotri barrage in 1960 and held

that responsible for the reduction in mangroves cover.

4. The average family size of all sampled households was 11.27, where the

minimum of 10.44 was for Shah Bunder and maximum of 13.55 for Kharo

Chhan. It is interesting to note that in Shah Bunder where the average family

size was lowest (i.e. 10.44), the average number of males (i.e. 3.46) was

higher than the average number of females (i.e. 3.21) and the associated

average number of children was lowest.

5. The scale of devastation in these coastal talukas as a result of continuous sea

intrusion has resulted in the loss of fertile agricultural land. Currently,

agricultural land ownership has reduced along the coastal belt of Indus delta.

Only a fraction of land holding is brought under cultivation owning to the fact

that the supply of fresh water has reduced considerably.

6. The ownership of livestock was limited in the area. Only 58 households out of

160 (i.e. 36 percent) were keeping livestock. The raising of camels was

reported only by 10 households with 7 from Shah Bunder.

7. A common view of the area reflects the fact that Keti Bunder has retained its

historical location as well as has acted as a center for various developmental

activities despite facing a number of threats in the form of natural as well as

man made disasters. In contrast, Shah Bunder could not sustain the devastation

of sea cyclone of mid 1990’s and as a result its taluka headquarter was shifted

to another location in the upstream area, its population was scattered and as

such currently the location of Shah Bunder’s proper settlement is lost to

antiquity. As a consequence, Shah Bunder has yet not reversed its position

undermining its fisheries catch and marketing and other economic

development prospects.

8. The fisheries as a source of income was highest in Keti Bunder where 29 out

of 40 households (72.5 percent) had it as primary occupation. In case of Kharo

Chhan it was 52.5 percent and in Shah Bunder it was 43.8 percent, of the

sampled households. The highest participation was in fisheries activities all

across.

58

9. Over 90 percent of the respondents reported visiting mangroves either

exclusively to collect forest products like fuel wood, fodder, catching fish

crabs, shrimps, honey, herbs, poles for use in house construction, animal

browsing, or to take rest and recreation while going towards open sea for

fishing.

10. Based on the responses of sampled households towards different socio-

economic aspects, it becomes clearer that local community heavily depends on

fisheries as their exclusive source of livelihood. The incomes are largely

generated from fishing whereas the non-fishing occupations generate over one

third of their incomes.

11. Sample survey also indicates huge economic dependence of household on



3232 from shell fishes).

12. The study tends to portray the levels of benefits and costs to coastal

communities in carrying out their economic activities with particular reference

to mangroves.

13. It further shows that incomes from fishing are highest and central to all

activities related to the natural habitat within the ecosystem, where mangroves

position remains pivotal. The direct benefits amount to 73 percent of all

benefits.

14. In assessing the role of mangroves, the study focused on evaluation of all

benefits (direct, indirect), whether those were marketed on non-marketed. In

the process, it used a combination of primary and secondary data and reviewed

available literature.

15. The analysis also decomposed the total benefits into use and non-use values

which were 94.4 percent and 5.6 percent, respectively.

16. The analysis also reveals on-site benefits as 55.3 percent and off-site benefits

as 44.7 percent of the total benefits. It showed a relatively larger dependence

of coastal communities towards on-site activities in relation to off-site

activities.

17. The socio-economic profiles of the coastal communities, as observed through

the sample survey, reflect extreme levels of social poverty. With an average

family size of 11.27, over 60 percent of head of households illiterate, lack of

safe drinking water (only 6 percent of households with piped drinking water),

75 percent without electricity, dilapidated road structure and 48 percent living

in huts, provide ample evidences to suggest extreme levels of poverty in the

Indus delta.

18. The demographic characteristics also reveal higher family size associated with

larger number of adult females (in relation to adult males). This could be one

of reasons for higher family size.

19. The pattern of economic activities reveal that, on average, one child out of ten

in each household was in the primary occupation, reflecting another dimension

of poverty in the area.

59

20. In each of the three sampled talukas, fishing was the dominating occupation

i.e. in Keti Bunder 72.5 percent, Kharo Chhan 52.5 and 43.8 percent at Shah

Bunder had fishing as their primary occupation.

21. The females in the area have no primary occupation which could generate

incomes of the family. They, however, participate in the secondary

occupations.

22. The direct cash income levels per month, as revealed by the sampled

households, shows that on average, those having fishing as primary occupation

earned Rs.42,843 per month and Rs.4,728 if fishing was a secondary

occupation. Similarly, those households who had non-fishing as primary

occupation earned, on average, Rs.20,172 per month and Rs.57,393 per month

in the event they had non-fishing as secondary occupation.

23. On the whole it appears that these revealed income levels may not suggest

abject poverty in the area from a financial point of view. However, the social

indicators highlighted above, do tend to verify significant levels of social

poverty among the coastal communities of Indus delta.

24. The study uses multivariate techniques to estimate willingness to pay

(participate) from the communities towards the development of mangroves

forests. As part of non-use values, estimation of benefits of tourism was also

conducted which tends to show dependence of coastal communities on

mangroves.

25. The study estimates total valuation of mangroves at Rs.14.7 billion rupees

annually i.e. US$ 147.2 million. The net valuation per hectare of mangroves

per annum was estimated at Rs.59,700 (or US$ 597), and a net valuation of

Rs.176,200 per household per annum (i.e. $ 1,762).

26. The potentials reposed, no matter how big they may appear, refer to the

“crude” values of products mangroves tend to offer in addition to the valuable

services in protecting not only the coastal communities but the entire coastal

area. The situation that arises calls for significant measures required not only

in the conservation and development of mangroves but also towards the

modernization and value addition of the products offered by mangroves.

27. In the broader context based on the findings of this study and a significant lack

of overall economic development in the Indus delta, there is a clear need that

the area be given exclusive attention. By considering the fact that increased

storage of irrigation water in the upstream for agricultural growth has tended

to significantly reduce the flow of sweet water and silt into the deltaic region

thereby extensively damaging the mangroves over time, the need for

compensation to the coastal communities seem fully justified. In addition, the

untreated industrial effluents thrown into the Arabian sea has also damaged

mangroves considerably (through eutrophication). In the obtaining situation,

not only the coastal communities but the entire coastal belt of the Indus delta

has been exposed to threats from the sea. In the light of international

conventions, agreements and framework, it is suggested that 0.10 percent of

annual value added of agricultural and manufacturing sectors be allocated

towards the conservation and development of natural habitat, and the

economic uplift of coastal communities of the Indus delta. At current prices,

such an allocation would be equivalent to Rs.10 billion annually.

60

28. The economic analysis of the study reveals a benefit cost ratio of 3.56 which is

quite significant.

29. The analysis also reveals an internal rate of return IRR of 25 percent which is

considered suitable for investments.

61

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63

Annexure Tables

Annexure Table – 5.1

Economic Valuation of Fuel Wood (Marketed) acrossIncome Categories

(Rs.)

Monthly Income Levels

Talukas Total


Subsistence (Less than 10,000)

300* 313 726 545

(949)** (677) (1687) (1375)

(10)*** (16) (34) (60)

Low (11,000 to 25,000)

875 783 653 730

(1408) (842) (1546) (1396)

(16) (12) (38) (66)

Middle (26,000 to 50,000)

- 333 833 467

- (816) (2041) (1356)

(3) (6) (6) (15)

High (Higher than 50,000)

- - - -

- - - -

(11) (6) (2) (19)

Total

425 410 681 549

(1059) (732) (1609) (1308)

(40) (40) (80) (160)

Note: *, ** and *** are Value, Standard Deviation and # Observations, respectively.


64


Economic Valuation of Fuel Wood Non-Marketed (Household Consumption) across Income Categories

(Rs.)

Monthly Income Levels

Talukas Total


Subsistence

880 325 300 403

(1135) (809) (790) (871)

(10) (16) (34) (60)

Low

1756 700 1189 1238

(1489) (1217) (2177) (1892)

(16) (12) (38) (66)

Middle

1 500 967 587

(1) (1225) (1211) (1095)

(3) (6) (6) (15)

High

864 500 - 658

(1583) (1225) - (1375)

(11) (6) (2) (19)

Total

1160 490 765 795

(1444) (1038) (1665) (1487)

(40) (40) (80) (160)



Economic Valuation of Wood for Pole and House Construction across Income Categories

(Rs.)

Income Levels

Talukas Total

Keti Bunder Kharo Chhan Shah Bunder Pole

Marketed Wood for Housing

Pole Marketed

Wood for Housing

Pole Marketed

Wood for Housing

Pole Marketed

Wood for Housing

Subsistence

- - - - - - - -

- - - - - - - -

(10) (10) (16) (16) (34) (34) (60) (60)

Low

- - 250 500 279 105 206 152

- - (866) (1446) (1623) (649) (1280) (789)

(16) (16) (12) (12) (38) (38) (66) (66)

Middle

- - - - 200 - 80 -

- - - - (490) - (310) -

(3) (3) (6) (6) (6) (6) (15) (15)

High

- - 500 - - - 158 -

- - (1225) - - - (688) -

(11) (11) (6) (6) (2) (2) (19) (19)

Total

- - 150 150 148 50 111 62

- - (662) (802) (1125) (447) (861) (510)

(40) (40) (40) (40) (80) (80) (160) (160)


65


Camel Population in Mangrove Forest Area

(#)

Talukas Cattles


Keti Bunder 1,006 375

Kharo Chhan 1,802 894

Central Shah Bunder 1,823 815

East Shah Bunder 1,197 835

Total 5,828 2,919


Annexure Table – 5.5.1

Number of Goats and Camels across Income Categories

(#)

Income Levels

Talukas Total


# Goats #

Camels # Goats

# Camels

# Goats #

Camels # Goats

# Camels

Subsistence 0 15 18 0 1 4 19 19

Low 0 0 9 2 5 42 14 44

Middle 6 0 0 0 0 0 6 0

High 10 15 0 0 0 0 10 15

Total 16 30 27 2 6 46 49 78


Annexure Table – 5.5.2

Numbers of Buffaloes and Cows across Income Categories

(# Animals)

Income Levels

Talukas Total

Keti Bunder Kharo Chhan Shah Bunder #

Buffalos # Cows

# Buffalos

# Cows #

Buffalos # Cows

# Buffalos

# Cows

Subsistence 0 0 1 0 25 4 26 4

Low 0 0 15 6 29 13 44 19

Middle 3 0 1 0 4 0 8 0

High 20 10 0 8 0 3 20 21

Total 23 10 17 14 58 20 98 44


66


Economic Valuation of Herbs Marketed across Income Categories

Income Levels Talukas


Subsistence

0 0 0 0

(0) (0) (0) (0)

(10) (16) (34) (60)

Low

63 0 0 15

(250) (0) (0) (123)

(16) (12) (38) (66)

Middle

0 0 0 0

(0) (0) (0) (0)

(3) (6) (6) (15)

High

0 0 0 0

(0) (0) (0) (0)

(11) (6) (2) (19)

Total

25 0 0 6

(158) (0) (0) (79)

(40) (40) (80) (160)



Economic Valuation of Honey Marketed across Income Categories



Subsistence

30 0 7 9

(95) (0) (30) (45)

(10) (16) (34) (60)

Low

0 0 14 8

(0) (0) (44) (34)

(16) (12) (38) (66)

Middle

100 0 17 27

(173) (0) (41) (80)

(3) (6) (6) (15)

High

0 0 0 0

(0) (0) (0) (0)

(11) (6) (2) (19)

Total

15 0 11 9

(66) (0) (38) (43)

(40) (40) (80) (160)


67


Economic Valuation of Crabs and Shrimps Marketed (on Site) across Income Categories

Income Levels

Talukas Total


Crabs Shrimps Crabs Shrimps Crabs Shrimps Crabs Shrimps

Subsistence

500 1030 1781 3431 1976 4526 1678 3652

(1581) (1683) (2646) (5692) (3874) (8596) (3293) (7184)

(10) (10) (16) (16) (34) (34) (60) (60)

Low

2731 15769 3167 6283 2382 13713 2609 12861

(2867) (29111) (3243) (6574) (5104) (35898) (4312) (30772)

(16) (16) (12) (12) (38) (38) (66) (66)

Middle

18333 26333 1450 18000 750 13000 4547 17667

(7638) (23029) (2477) (35553) (1837) (14283) (7921) (25010)

(3) (3) (6) (6) (6) (6) (15) (15)

High

9545 68500 5000 23333 1700 2450 7284 47284

(17558) (88175) (12247) (38297) (707) (1061) (14876) (73596)

(11) (11) (6) (6) (2) (2) (19) (19)

Total

5218 27378 2630 9458 2070 9474 2997 13946

(10608) (55296) (5209) (20823) (4345) (25859) (6734) (35343)

(40) (40) (40) (40) (80) (80) (160) (160)



Economic Valuation of Shell Fish across Income Categories



Subsistence

300 844 412 508

(949) (1568) (1184) (1261)

(10) (16) (34) (60)

Low

875 2883 895 1252

(2527) (3355) (2699) (2851)

(16) (12) (38) (66)

Middle

0 667 0 267

(0) (1633) (0) (1033)

(3) (6) (6) (15)

High

36364 0 0 21053

(120605) (0) (0) (91766)

(11) (6) (2) (19)

Total

10425 1303 600 3232

(63199) (2375) (2023) (31631)

(40) (40) (80) (160)


68


Economic Valuation of Benefits Marketed and Non-Marketed across Income Categories

Income Levels

Keti Bunder Kharo Chhan Shah Bunder Total

Non-Marketed

Marketed Non-

Marketed Marketed

Non-Marketed

Marketed Non-

Marketed Marketed

Subsistence

2090 1610 947 2131 903 6894 1113 4743

(3489) (2420) (1410) (3343) (1263) (17703) (1857) (13609)

(10) (10) (16) (16) (34) (34) (60) (60)

Low

3094 6744 2283 164400 1508 9421 2033 36950

(2607) (6455) (1600) (546614) (1549) (17135) (1954) (233253)

(16) (16) (12) (12) (38) (38) (66) (66)

Middle

1300 6667 2567 11400 2350 7333 2227 8827

(954) (11547) (2221) (15435) (2870) (7448) (2253) (11346)

(3) (3) (6) (6) (6) (6) (15) (15)

High

7473 95636 4667 76667 3000 4200 6116 80021

(6180) (119989) (4367) (114310) (1131) (566) (5430) (111444)

(11) (11) (6) (6) (2) (2) (19) (19)

Total

3913 29900 2149 63382 1351 8060 2191 27351

(4526) (73494) (2483) (301836) (1603) (16548) (2986) (155958)

(40) (40) (40) (40) (80) (80) (160) (160)


69

INTERNATIONAL UNION

FOR CONSERVATION OF NATURE

PAKISTAN PROGRAMME

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Clifton – 75500

Karachi, Pakistan

Tel. +92 2135861540

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“VALUATION STUDY OF MANGROVE PLANTATIONS … · · 2016-05-19International Union for Conservation of Nature, Pakistan . Table of Contents ... non-timber forest products from mangroves