Khai thác thương mại lâm sản ngoài gỗ và đời sống các hộ gia đình trong hoặc gần rừng. Nghiên cứu ở thôn Quế(Con Cuông) và thôn Ma(Tương Dương), Nghệ An, Việt Nam.In Vietnam, NTFPs has become an important source of cash income for local people living in or near the forests. The commercial collection of these products could reduce both the number of species and population of a species in the forests. In order to keep the balance between biodiversity and commercial collection of NTFPs, this paper evaluates the dependence of forest dwellers on NTFPs and identifies the relation between household characteristics and cash income generated by NTFP collection. As a result, commercial collection of NTFPs is negatively correlated to dependency ratio, poverty level and distance
Trang 1Commercial collection of NTFPs and households living
in or near the forests:
Case study in Que, Con Cuong and Ma, Tuong Duong,
Nghe An, Vietnam
Dang Viet Quang*, Tran Nam Anh
Center for Agricultural Research and Ecological Studies, Hanoi Agricultural University, Trau Quy, Gia Lam, Hanoi, Vietnam
Article history:
Received 25 August 2005
Received in revised form
19 February 2006
Accepted 4 March 2006
Available online 27 April 2006
In Vietnam, NTFPs has become an important source of cash income for local people living in
or near the forests The commercial collection of these products could reduce both the number of species and population of a species in the forests In order to keep the balance between biodiversity and commercial collection of NTFPs, this paper evaluates the dependence of forest dwellers on NTFPs and identifies the relation between household characteristics and cash income generated by NTFP collection As a result, commercial collection of NTFPs is negatively correlated to dependency ratio, poverty level and distance
to the provincial city, and positively correlated with female labors of households Moreover, NTFPs are proved to be very important in poor households or in those who lack rice or high rate of female labor The households who have higher dependency ratio benefit less from NTFPs sold, while those who lack rice for their own consumption or have a higher rate of female labor depend more on NTFPs Poor households are more dependent on NTFP collection than other groups Finally, the result of this study highly recommends that the Government of Vietnam be aware of gender balance, distance to provincial city, poverty level and dependency ratio when applying a policy related to NTFP conservation An appropriate incentive policy for woman and poor households might be a possible solution for less commercial collection of NTFPs The poor households who have low dependency ratio or high female labor rate should be encouraged to participate in the forest management system to control the balance between commercial collection of NTFP and conservation
© 2006 Elsevier B.V All rights reserved
Keywords:
NTFPs
Livelihood
Commercial collection
Dependence on NTFPs
1 Introduction
Forest products, which can be classified into timber and
non-timber products, are numerous and play an important role in
the livelihood of people living in or near forests People in such
areas often collect forest products and use forest land for
cultivation They use forest products both for household
consumption and cash income generation (Fisher, 2000) In subsistence economies, forests can provide many essential products and services for the life of local people such as“food, utensils, clothing, shelter, medicines and objects of spiritual or cultural significance” (Wong, 2000, pp 3–4) In open economies where forest dwellers can sell or trade their products, forest products generate considerable employment and income In
⁎ Corresponding author Fax: +84 4 8766642
E-mail addresses:quang74@hn.vnn.vn,quang74@cares.org.vn(D Viet Quang)
0921-8009/$ - see front matter © 2006 Elsevier B.V All rights reserved
doi:10.1016/j.ecolecon.2006.03.010
a va i l a b l e a t w w w s c i e n c e d i r e c t c o m
w w w e l s e v i e r c o m / l o c a t e / e c o l e c o n
Trang 2India, for example, non-timber forest products generate US
$700 million annually in Madhya Pradesh and US$115 million
annually in Maharashtra, while commercial wood provides US
$72 million in Madhya Pradesh and US$29 million in
Mahar-ashtra (Osman et al., 2000) Furthermore, forest products are
the center of research on forest management, biodiversity,
conservation, and poverty alleviation (Lawrence, 2003;
Ambrose-Oji, 2003)
Non-timber forest products (NTFPs) are diverse and consist
of an assortment of products The number of NTFPs might be
larger than that of timber-based products because the NTFPs
come from many different parts of the plants (Chamberlein III,
2000) Due to the diversity of NTFPs, they are extremely
important to biodiversity, conservation, and forest
manage-ment NTFPs, therefore, have attracted the attention of many
researchers all over the world In 1999, at the Conference on
Forest Communities in the Third Millennium: Linking
Re-search, Business, and Policy toward a Sustainable Non-Timber
Forest Product Sector, Iain Davidson-Hunt reviewed literature
on NTFPs and divided it into seven categories, those are:
“ethnographic studies, traditional ecological knowledge,
eco-nomic botany, forest management and policy, biology and
ecology of forests, forest products research and business
organization and marketing” The definition of NTFPs in this
conference was extremely broad including foods, materials,
health care, decoration, environmental products, etc (
David-son-Hunt et al., 2001, pp 1–3)
More specifically, socioeconomic research reveals that
NTFPs become important in the livelihoods of many poor
households who live in or near forests, especially in the
tropics Many of these studies find that the livelihoods of poor
households still depend on NTFPs from fallow1and natural
forest2relatively more than the other groups (Sills et al., 2003;
Tickin, 2004; Osman et al., 2000; Roderick and Hirsch, 2000;
Belcher and Kusters, 2004) The dependence of farmers on
NTFPs mostly differs from this region to others.“In remote
areas, NTFPs provide subsistence goods like food, medicines
and building materials” Near urban areas, where trading and
commercial networks perform better with the environmental
functions of the forests, the farmers have more options They
can find a job related to NTFPs or can produce NTFPs mainly for
commercialization (Ros-Tonen and Wiersum, 2003, p 17) Most
farmers collect NTFPs both for subsistence and for trading in
order to mitigate the risks as well as to diversify their income
sources (Subhrendu and Sills, 2001) Nevertheless, if farmers
can get high profitability from NTFPs, their harvesting could
reduce both the number of species and population of a species
in the forests Roderick's work showed“a positive
relation-ship between low biodiversity and high NTFP profitability”
(Roderick and Hirsch, 2000, pp 124) For those reasons, in
Southern and East Africa, the management, roles and
depen-dence of different groups on non-timber forest products were
given the highest priority in research (Ruiz et al., 1997)
In general, NTFPs play an important role both in forest conservation and improving livelihoods for forest dwellers They can provide the incentive for participatory forest management (Ros-Tonen, 2000) Additionally, research of Wendy Cocksedge in 2001 indicated that the use of NTFPs is
a possible solution to release the dependency of local people
on timber Thus, they can be a sustainable source of income for people living in or near the forests (Cocksedge, 2001) Moreover, research in South-west Cameroon shows that the value of forests will be improved by increasing the use of NTFPs, if it can incite users to engage with improved management and conservation strategies (Ambrose-Oji,
2003) Other crucial important roles of NTFPs are “poverty avoidance, filling gaps during periods of low income, spreading risk, and functioning as a safety net” (Belcher and Kusters, 2004, pp 1–22) Thus, the idea integrated from this literature review is that the collection of NTFPs should be controlled in relation with forest conservation by a partici-patory management system However, which type of house-hold should participate in this management system is still a question for both researchers and policy makers in Vietnam This question can be answered by identifying the relation between households living in or near the forests and NTFPs collection
In Vietnam, more than 24 million people live in and near forests, accounting for 30% of country's population (Beer,
1993) Similar to other countries, there is no doubt that NTFPs can fulfill several functions In the households which live in or near the forests of Vietnam, NTFPs can provide food, materials for construction, fodder, fuel-wood, and cash income (Beer,
1993) A case study of dependency on forest and tree products for food security in the Northern Mountainous Region of Vietnam shows that wealthier groups of forest dwellers use forest vegetables for their own consumption or buy them from the poor The poor sell vegetables, bamboo shoots and mushrooms from the forest and use the money to buy rice The wealthier families hunt to improve the quality of their meals while poorer families hunt to earn more income (Yen et al., 1994, cited byRijsoort, 2000)
There is little doubt that NTFPs are very important for household livelihoods and for conservation of biodiversity in the forests Meanwhile, research on the importance of NTFPs
to either of these themes is rarely done in Vietnam On the other hand, in order to keep the balance between conservation and NTFP collection, the relation between households and commercial collection of NTFPs should be identified first This research, therefore, aims to analyze the dependence of households on NTFPs (measured as a percentage of total cash income) in two different forest locations of Vietnam and identify the significant relations between households and commercial collection of NTFPs through a Tobit regression model
In order to achieve this goal, the following hypotheses will
be tested in this study:
Hypothesis 1. The community living closer to provincial city where majority of business activities are performed will collect more commercial value of NTFPs
Hypothesis 2. Households in research locations have scarce labor and must allocate it efficiently in order to maximize their
1
The fallow actually is the young secondary forest with
cultivated areas covering between 33% and 50% of total area
(www.fao.org/gtos/tems/land_cover_classification.htm)
2The natural forest is continuous forest cover It can be closed
capony forest, open capony forest or long fallow (www.fao.org/
gtos/tems/land_cover_classification.htm)
Trang 3incomes Thus, the cash income generated by collecting NTFPs
will compete with the income generated by other activities If
the cash amount obtained from NTFP sales is high, the cash
received through other income sources is low Thus, the
household characteristics related to both labor and income,
such as female labor rate, dependency ratio, income from
different sources and poverty level, will influence the NTFP
collection of local people
2.1 Concepts and definitions
All over the world, non-timber forest products have been
studied in various fields such as forestry, ethno-biology,
economic botany, social development, natural resource
eco-nomics, conservation biology, protected area management,
agro-forestry, marketing, commercial development, ecological
anthropology, cultural geography and human ecology This
cross disciplinary study has led to the development of many
terms and definitions for different types of forest products For
example: alternative forest products (AFP), minor forest products (MFP), non-timber forest product (NTFP), non-timber plant products (NTPP), non-timber resources and values (NTRV), non-wood forest benefit (NWFB), non-wood goods and services (NWGS), special forest products (SFP), etc (Wong,
2000) In many publications by the Food and Agricultural Organization of the United Nations (FAO), authors use two terms extensively: non-timber forest products (NTFPs) and non-wood forest products (NWFPs), of which NWFPs are goods
of biological origin, other than wood NWFPs also include services that are related to the collection and processing of these products such as rope making and gum collecting (Hoskins, 2003) In this research, however, Non-Timber Forest Products are defined as those biological organisms, excluding timber, collected by humans for both consumptive and selling purposes found in various form of forests (Davidson-Hunt et al., 2001, cited inBerkes et al., 2002)
Additionally, in this paper, the livelihood of a household living in or near the forest is understood as the cash earned through different means of living Through this definition, contribution of NTFPs to household livelihood or dependence
of a household on NTFPs is measured by the proportion of
Ma Hamlet
Que Hamlet
Hamlets
Legend
Communes Vinh city River Road
Research Sites in Nghe An province
N
S
E W
Fig 1– Research sites in Nghe An Province
Trang 4cash generated by NTFP collection in total cash income.
Moreover, the cash income generated by selling NTFPs is
used to describe the commercial collection of NTFPs in this
paper
2.2 Study sites
In December 2003, researchers from Center for Agricultural
Research and Ecological Studies (CARES) and the Institute of
Geography at the University of Copenhagen (IGUC) organized a
research survey in two villages of two different districts: Ma
hamlet in Tuong Duong district and Que hamlet in Con Cuong
district
Although both of these hamlets are located in Nghe An
province along the Basin of Ca River and are home to similar
Thai people, they are extremely different in terms of
geographical location and market access Located in a remote
area, 40 km up the Ca River from Hoa Binh Town, Ma hamlet
lies in the center of a triangle that is formulated by Khe Ma and
Khe Xuong streams and the Nam Non River There is no road
connecting this hamlet to other parts of the district The only
way that people in this hamlet can reach the center of district
is by motorized boat Trading activities between members of
this community and outsiders can only be conducted after a
4-h commute by boat Meanwhile, Que hamlet is located in a
place which is 35 km away from the center of Con Cuong
district An inter-communal road connects this hamlet to
other communes and to the district center Even though the
road is in poor condition, it is very important for local people
in terms of facilitating the buying, selling and exchanging of
goods Motorbikes, cars and small trucks use this road to go to
Que hamlet Moreover, Que is closer to provincial city than Ma
as depicted inFig 1
2.3 Data analysis
In the first part of this paper, we apply the descriptive
analysis using means and Coefficient of Variation (CV) to
compare the household demography, income, NTFPs and
animal husbandry between the two hamlets Additionally,
T-test is applied to examine the significant differences in
means of these variables between the two hamlets At first,
this analysis aims to provide the reader with a picture of the
household economy in the two research locations Secondly,
it will identify the differences between households in two
hamlets
In order to identify the dependence of households on
NTFPs, we classified the households into four groups
accord-ing to cash income: less than 5 million, 5–10 million, 10–20
million VND and more than 20 million VND In each group, we
divide the households into different categories according to
percentage of cash income gained by selling NTFPs: smaller
than 5%, 5–25%, 25–50% and larger than 50% The data in this
table will show the dependence of households on NTFPs by
cash income level The households who have less than 5%
cash income from NTFPs are considered to be independent of
NTFPs, 5–25% is weak dependence, 25–50% is moderate
dependence and the households who earn more than 50% of
total cash income from NTFPs are strongly dependent on
these products The proportions of households in each
category will be used to compare the dependence on NTFPs between two communities namely Que and Ma hamlets
In addition to descriptive analysis, censored regression model is employed to identify the relation between house-holds and commercial collection of NTFPs which is defined by the sold value of collected NTFPs Another dependent variable
is dependence of households on NTFPs which is measured as the percentage of cash income generated by NTFP collection Both commercial collection and dependence of household on NTFPs are used to regress with the same group of independent variables by Tobit model because the sample data of these dependent variables are censored at zero (Greene, 2003) Regarding Hypothesis 2, the independent variables in these models should be related to both labor and income In fact, there is labor division inside a household between children and adults, male and female For example, children and the elderly are often doing the household work while adults are responsible for farm work; male is in charge of logging and female collects NTFPs On the other hand, the labor allocation competes among the activities The households who devote more labor days in raising animal will have fewer labor days for collecting NTFPs Hence, the dependency ratio, female labor rate and number of cattle, pigs and poultries are selected
to be independent variables in the econometric models Additionally, the cash income generated by other activities could substitute the income gained from NTFPs Other income sources such as off-farm activities, salary and pension, therefore, are also selected Moreover, the cash income is actually important for households lacking rice for the whole
Table 1– Variables in Tobit regression model
Dependent M1 NTFPs value The sold value of NTFPs in each household
(thousand VND)
M2 NTFPs-income share
The share income generated by selling NTFPs (percentage)
Independent
1 Dependency ratio
Number of people younger than 15 and older than 60 divided by the number of active laborers
2 Female labor rate
Number of women between 15 and 60 divided by total labor of household (smaller than one)
3 Food security Number of months that households have
enough rice
4 Off-farm income
Cash income generated by off-farm activities (thousand VND)
5 Salary and pension
Cash received from government budget (thousand VND)
6 Other income Cash received from fishing, relatives,
selling house and social activities (thousand VND)
7 Cash income per capita
Total cash income divided by total number
of household members
8 Self-evaluation
of wealth
Scoring: very poor 1, poor 2, moderate 3 and wealthy 4
9 Location Que: 0; Ma: 1
10 Cattle Number of cattle (buffaloes and cows)
11 Pig Number of pigs
12 Poultry Number of poultry (chickens and ducks)
Trang 5year They use the cash earned from other activities to buy rice
in the month with shortage of rice Thus, food security should
be considered in both selected models Finally, cash income
per capita and the wealth of households are chosen to
represent the poverty level (Table 1)
If a female labor rate inTable 1were equal to one (i.e the
household had no male labor), women would have to do all of
the work, including that a man normally does Thus, their time for NTFP collection would be scarce The value of commercial NTFPs in this household would be lower than others Moreover, according to the group discussion, the collection of NTFPs is normally done by females Thus, the female labor rate is needed to evaluate the relation between gender and NTFP collection
3.1 Descriptive analysis
In general, the households in both Que and Ma collect NTFPs for both selling and their own consumption The number of products solely collected for sale is very few—only one product in Ma and two products in Que However, farmers in
Ma collect NTFPs mainly for consumption while farmers in Que are more specialized in selling certain NTFPs In Ma, although the number of NTFPs both sold and consumed is larger than those in Que, the collection of NTFPs in this area
is mainly for household consumption, because as shown in
Tables 2a and b, the quantity consumed is larger than quantity sold The number of NTFPs sold in Que is less than
in Ma and is also larger than the consumed quantity in Que (Tables 2a and b)
Almost every household in the two hamlets collect NTFPs for either consumption or sale The total number of family members as well as family structure plays a critical role in this activity.Table 3illustrates household demography in Ma and Que hamlets in December 2003 Male and female laborers are people between 15 and 59 years old In Ma, on average, each household has 4.6 members, of which 1.6 are male laborers and 1.4 are female laborers On the other hand, the total average number of members in Que is 5.8, which is higher than in Ma at the confident level of 99% The numbers of male and female laborers in Que are 1.5 and 1.3 respectively There
is almost no difference between the household labor in Ma and Que (<50% significant) Consequently, there are different dependency ratios between two hamlets at the confident level
of 99% Que hamlet has more members per family as well as a greater dependency ratio (Table 3)
Table 2a– Purpose of NTFPs collection in both research
sites
No Products Purpose No Products Purpose
1 Bamboo C 1 Bamboo C + S
2 Bamboo shoots C⁎+S 2 Bamboo shoots C⁎+S
3 Banana C 3 Banana C
4 Fish, birds, wild
animals
C⁎+S 4 Fish, birds, wild
animals
C⁎+S
5 Broom grass C + S⁎ 5 Broom grass C + S
6 Firewood C 6 Firewood C
7 Honey C + S⁎ 7 Honey C + S
8 Mushroom C 8 Mushroom C
9 Pherynium leaf C + S⁎ 9 Pherynium leaf S
10 Amomum sp C + S⁎ 10 Amomum sp C⁎+S
11 Eggplant C 11 Eggplant C + S
12 Local edible
fruits
C 12 Local edible
fruits
C
13 Local edible
vegetables
C 13 Local edible
vegetables
C
14 Plant used for
dying cloth
C + S⁎ 14 Plant used for
dying cloth
C⁎+S
15 Root used to
make incense
S 15 Root used to
make incense
C + S
16 Rattan C 16 Rattan C
17 Zanthoxylum
avicenniae
C 17 “Bach bi” C⁎+S
18 Dioscorea
persimilis
C 18 “Bach bu” C⁎+S
19 Indian taro C 19 “Bu Bup” C⁎+S
20 Palm leaf C⁎+S 20 “Cay cat” C⁎+S
21 Indian Taro C 21 “Cay nat” C⁎+S
22 Calamus sp C + S⁎ 22 “Chac cau” C⁎+S
23 Artocarpus
tonkiensis
C + S⁎ 23 “Chac dang” C⁎+S
24 Alpinia sp C + S
25 Streptocaulon juventas
C⁎+S
26 Fibraurea recisa C⁎+S
27 Schefflera octophylla
C⁎+S
28 “Pau pa” C⁎+S
29 Zanthoxylum avicenniae
C
30 “Sam cau” C⁎+S
31 “Ta phan” C⁎+S Sale only 1 Sale only 1
Consumption only 12 Consumption only 7
Products for both C
and S⁎
10 Products for both C⁎
and S
23 Total collected NTFPs 23 Total collected NTFPs 31
Source: survey data in 2003
“C”: consumption; “S”: sale; “⁎”: larger quantity of either sale or
consumption
Names in quotation marks are local names
Table 2b– Purpose of NTFPs collection in both research sites
Purpose of collection
Number of products
Purpose of collection
Number of products
Sale only 1 Sale only 1 Consumption
only
12 Consumption
only
7 Products for
both C and S⁎
10 Products for both
C⁎ and S
23 Total collected
NTFPs
23 Total collected
NTFPs
31
Source: survey data in 2003
“C”: consumption; “S”: sale; “⁎”: larger quantity of either sale or consumption
BecauseTable 2ais too large, it is reduced into this table
Trang 6Animal raising is important for many households in the two
hamlets Having animals, especially cattle, is as a kind of an
economic safety net for the majority of farmers If the harvest
fails, sickness occurs in the family, or any other bad thing
happens, selling animals provides an economic buffer (Quang
and Jakobsen, 2005) In Ma, 78.6% of the interviewed farmers
owned at least one head of cattle (either cow or buffalo) with
the average number of cattle per household being 5.5
Meanwhile, in Que, these numbers are 74.1% and 3.9 heads
respectively In addition, most people in the two hamlets also
raise pigs at 82.1% of households for Ma and 81.5% for Que, with
the average number of pigs per households being 4.0 and 2.1
respectively Poultry is the category with the greatest
differ-ence between the two hamlets In Ma, on average, each
household owns 14.7 ducks and chickens while in Que, this
number is tripled to 43.1 ducks and chickens, which is a
significant difference (99%) In short, many people in Ma and
Que raise animals and there is almost no statistically
significant difference between these hamlets in terms of
number of cattle and pigs owned by each household but
there is a large difference in terms of poultry because in 2003
the chickens in Ma massively died due to influenza (Table 4)
People do earn income from cutting wood in the forest Yet,
as timber exploitation is considered illegal in the two hamlets,
interviewees were reluctant to talk about this activity
Therefore, in this paper, logging is excluded from calculations
of total cash income
Income sources in the two hamlets are divided into six
categories as follows: agricultural products, animal
husband-ry, NTFPs, off-farm activities, salary and pension, and others
comprised of remittances and compensation from social
activities In Ma hamlet, people sometimes sell some of their
agricultural products to local people or to people from the
lowlands These kinds of agricultural products include tea,
vegetables, rice and bananas However, farmers only get a small amount of money from these products with an average value of 125 thousand VND per capita According to the statistical data from District People's Committee, Que hamlet
is considered to be the poorest in Binh Chuan commune, where 38 households are classified as poor, 14 as average and
15 households are classified as well-off On average, the poor households lack food between 4 and 7 months per year As a consequence, they use all of their agricultural products for subsistence The greatest income in Ma and Que comes from animal husbandry with average value of 760 thousand VND per capita and 426 thousand VND per capita, respectively This income source comes mainly from selling cattle and pigs Salary and pension is the category with the greatest difference between Ma and Que In Ma, on average, people can earn 492 thousand VND per capita, meanwhile, in Que, this number is just 24 thousand VND per capita at confidence level of 98.5% That means there are more people working for the govern-ment with higher salary in Ma than in Que (Table 5)
In terms of NTFPs, people in Que earn more money from selling these kind of products than people in Ma hamlet (104 thousand VND and 22 thousand VND per capita at 99% significance) (Table 5)
Fig 2shows the average cash income shares of households
in the two hamlets As shown, the biggest share in both hamlets comes from animal husbandry at 37% for both NTFP selling is the second biggest share in Que at 33% while in Ma hamlet, it comprises only 5% Income from off-farm activities such as hired labor, shop and services in Ma accounts for 33%
of their total income At the same time, in Que, this number is only 16% (Fig 2)
Table 4– Animal husbandry (unit: heads/household)
Mean CV (%) Percentage of HHs Mean CV (%) Percentage of HHs P (T≤t), two-tail
Source: survey data in 2003
Table 5– Cash income per capita (unit: 1000 VND/person)
Indicators Ma hamlet
(N = 28)
Que hamlet (N = 27)
T-test (0.05) Mean CV (%) Mean CV (%) P (T≤t),
two-tail
Agricultural products
Animal husbandry
760 174 426 165 0.250 NTFPs 22 166 104 85 0.000 Off-farm
activities
445 276 214 235 0.368 Salary and
pension
492 195 24 316 0.015 Others 43 248 73 252 0.458 Total 1886 147 842 125 0.073 Source: survey data in 2003
Table 3– Household demography (unit: number of
persons/household)
Indicators Ma hamlet
(N = 28)
Que hamlet (N = 27)
T-test (0.05) Mean CV (%) Mean CV (%) P (T≤t),
two-tail
Total member 4.6 38.9 5.8 22.9 0.006
Male labor 1.6 63.5 1.5 55.9 0.833
Female labor 1.4 61.5 1.3 52.1 0.421
Dependency
ratio
0.7 75.8 1.2 49.6 0.000 Total labor 3.0 52.1 2.8 37.8 0.538
Source: survey data in 2003
Trang 7Table 6 shows the total cash income as well as the
dependence level of forest dwellers on NTFPs in the two
hamlets In Que, no household can receive more than 20
million VND while 7% of households earn more than 20
million VND a year in Ma The households, who earn less than
5 million VND per year, account for 67% of total households in
Que and only 57% in Ma hamlet (Table 6)
In Que, 30% of households depend considerably upon
NTFPs More than fifty percent of their total cash income is
generated by NTFP collection All of these households are in
the poorest group, earning less than 5 million VND cash a year
In Ma, no household falls into this situation In the other
categories, the cash income of 15% of households in Que
depends moderately on selling NTFPs while this rate in Ma is
only 4% All of these households earn less than 5 million VND
per year, which can be considered to be the poorer of the two
hamlets In the group that is not dependant on NTFPs, Ma has
75% of households while Que has only 26% It means that the
number of households in Ma whose cash income depends on
NTFPs is less than in Que (Table 6)
3.2 Results of Tobit estimation
3.2.1 Determinants of cash income from NTFPs
This part aims to identify the relations between households
and commercial collection of NTFPs by employing a Tobit
regression The models in this section, therefore, only account
for the contribution of NTFPs to the cash income of
house-holds The results estimated by a Tobit regression inTable 7
shows the correlation between household characteristics and
the cash income generated by NTFP collection
The results inTable 7show that there are four independent variables significantly related to the value of NTFPs sold These variables are dependency ratio, female labor rate, self-evaluation of wealth, and dummy variables of location, of which only female labor rate positively correlate to cash income generated by NTFP collection The other independent variables are negatively correlated to the dependent variable 3.2.2 Determinants of household dependence on NTFPs The most important indicator in this paper is the depen-dence of households on NTFPs The identification of dependence is based on the result of Model 2 in Table 8, which depicts the significant correlation between house-holds and the share of cash income generated by selling NTFPs This table shows that seven independent variables are significantly correlated to the dependence of households
on NTFPs of which female labor rate and salary–pension are positively correlated to the dependent variable Five other variables including food security, other income, cash income per capita, dummy location and self-evaluation of wealth are negatively correlated to the dependence of farmers on NTFPs (Table 8)
4 Discussion 4.1 Descriptive analysis The farmers in Que can sell their products more easily than farmers in Ma They just sell the products demanded by consumers in the market In the case of Ma hamlet, farmers
37%
33%
16%
5%
37%
5%
33%
16%
4%
Agricultural products Animal husbandry NTFPs
Off-farm activites Salary & pension Others
Fig 2– Average income shares of households in Ma and Que hamlets
Table 6– Dependence on NTFPs of households at different cash income levels (unit: percentage of households)
Categories (% of total cash
income from NTFPs)
Total cash income (million VND) by group per year Total
<5 million 5–10 million 10–20 million >20 million
Source: survey data 2003 (N = 55)
Trang 8mainly sell their collected products to others in the hamlet or
in the community nearby They seldom sell to outsiders in the
broad market Consequently, in terms of NTFPs, the main
difference between the two hamlets here is the value and
quantity of NTFPs sold
In terms of NTFPs, people in Que earn more money from
selling these kinds of products than people in Ma hamlet
There are two reasons for this phenomenon First, in Que, as
mentioned above, the average family size is larger than in Ma,
therefore, there are more people who can take part in
gathering NTFPs Naturally, they might collect greater
amounts of products Second, in Que, the prices of NTFPs are
normally higher than in Ma For example, in Que, people can
sell one leaf of pherynium for 100 VND, meanwhile, in Ma, the
price is only 20–25 VND/leaf Similarly, 1 kg of broom grass in
Que sells for 2500 VND while in Ma it is 400–500 VND Briefly,
income from selling NTFPs in Que hamlet is greater than that
in Ma while the amount of money received from salary and
pension is smaller (Table 5)
NTFP selling is the second biggest share in Que while in
Ma hamlet it comprises only 5% Hence, in Que NTFPs are
more important for people than in Ma in terms of cash
income (Fig 2)
Income from off-farm activities such as hired labor, shops
and services in Ma accounts for 33% of their total income At
the same time, in Que, this number is only 16% One of the
main reasons for this is because in Ma, people sell more
handicrafts (e.g woven cloth, rattan baskets, etc.) than in Que
The least important source of income in Ma is the other
category at 4%, which includes the compensation from
participation in social activities and remittances from
rela-tives Meanwhile, in Que, salary and pension contribute the
smallest part In fact, for all the interviewed households in
Que, no person received pension from the government In
conclusion, in Ma, the cash income of household comes mainly from selling animals and off-farm activities whereas in Que, the main proportion of cash income is generated by raising animals and selling NTFPs (Fig 2)
When earnings of households cannot satisfy their needs, people who live in or near the forests go to the forests to collect forest products to supplement the shortage in their house-holds The cases in both Ma and Que hamlet show that the less cash the household earns, the greater the share of their income is generated by NTFPs (Table 6)
Finally, it can be concluded that the poor who live in or near forests depend more on the NTFPs than the wealthier house-holds At the same level of wealth, the households who live closer to provincial city can receive more cash income from selling NTFPs than those in remote areas
4.2 Determinants of cash income from NTFPs The negative coefficient of location dummy (Ma = 1) which is significant at 99% of confidence in this model indicates that the value of NTFPs sold in Que is significantly higher than in
Ma (Table 7)
The negative coefficient of dependency ratio implies that households who have higher dependency ratio enjoy less benefit of collected NTFPs because they lack labor for the activities of NTFP collection In Model 1, the dependency ratio negatively correlates to the value of NTFPs sold at 95% of confidence (Table 7)
Moreover, the results of the model inTable 7show that the female labor rate is also significantly related to the value of NTFPs sold at 90% of confidence Thus, at a confidence level of 90%, it can be concluded that the households who have more female labor or collect more NTFPs generate cash income for their households
Table 7– Tobit estimation of cash income from NTFPs
(Model 1)
Independent
variables
Coefficients (beta)
t-value Significance
(P-value)
Constant 1296.14⁎⁎⁎ 3.55 0.001
Dependency ratio −264.990⁎⁎ −2.44 0.019
Female labor rate 589.224⁎ 1.96 0.056
Food security −24.368 −0.99 0.326
Off-farm income −0.001 −0.04 0.970
Salary and pension 0.014 0.54 0.594
Other income −0.067 −0.89 0.381
Cash income per capita −0.064 −0.98 0.330
Self-evaluation
of wealth
−162.475⁎ −1.87 0.069 Location −735.325⁎⁎⁎ −4.31 0.000
Cattle 23.112 1.46 0.151
Pig −0.712 −0.05 0.963
Poultry −0.819 −0.40 0.690
Prob > chi2 0.0026
Log likelihood −402.821
Dependent variable:
NTFPs value sold
N = 55
⁎, ⁎⁎, and ⁎⁎⁎ are significance level at 90%, 95% and 99% respectively
Table 8– Tobit estimation of dependence on NTFPs (Model 2)
Independent variables
Coefficients (beta)
t-value Significance
(P-value)
Constant 105.499⁎⁎⁎ 6.16 0.000 Dependency ratio −8.173 −1.60 0.116 Female labor rate 34.333⁎⁎ 2.44 0.019 Food security −4.588⁎⁎⁎ −3.99 0.000 Off-farm income 0.001 0.78 0.440 Salary and Pension 0.002⁎ 1.88 0.067 Other income −0.007⁎ −1.95 0.057 Cash income per capita −0.006⁎ −1.86 0.070 Self-evaluation of
wealth
−8.724⁎⁎ −2.14 0.038 Location −39.741⁎⁎⁎ −4.96 0.000 Cattle 0.111 0.15 0.882
Poultry −0.104 −1.09 0.280
Prob > chi2 0.000 Log likelihood −234.54
Dependent variable:
NTFPs-income share
N = 55
⁎, ⁎⁎ and ⁎⁎⁎ are significance level at 90%, 95% and 99% respectively
Trang 9The significant coefficients of self-evaluation of wealth
indicate the negative correlation between the commercial
value of NTFPs collected and the poverty level of households
in terms of cash income at 90% of confidence level It suggests
that wealthier households gain less commercial value of
NTFPs than poorer ones
Briefly, the determinants of the value of sold NTFP,
therefore, must be geographical location, dependency ratio,
female labor rate, and the poverty level which is defined by
wealth levels of households
4.3 Determinants of household dependence on NTFPs
According to results of the Tobit estimation inTable 8, both
food security and location dummy negatively correlates to
the dependent variable, the share of cash income generated
by selling NTFPs Both have significance at 99% of
confi-dence Obviously, the coefficient of dummy location (Que = 0,
Ma = 1) indicates that the cash income of households in Que
depends more on selling NTFPs than those in Ma On the
other hand, the coefficient of food security shows that the
households who lack rice for their own consumption will
depend more on NTFPs than others who have enough rice
for the whole year
An important finding in this model is the female labor rate,
which is calculated by the rate of female labor and total family
labor This variable positively correlates to the share of income
generated by selling NTFPs at a significance level of 95% It
suggests that the households with higher rates of female labor
will depend more on NTFPs than others in the same location
except the case of households without male labor.3This result
is very important because, following other research, it
continues to emphasize the role of women in NTFP trading
and collection (Belcher and Kusters, 2004)
Additionally, the results in Model 2 show that both cash
income per capita and wealth levels of households
nega-tively correlate to the share income generated by NTFPs
This result suggests that the poor are more dependent on
NTFPs than the wealthier households There are several
reasons behind this result The first reason is the low capital
requirement for extraction of NTFPs Secondly, because of
low income from other sources people have to collect
commercial NTFPs to supplement or increase their
house-hold income The lower income from other sources also
makes the income share of NTFPs higher, which in turn
makes some people more dependent on these products or,
in other words, more dependent on the forest Moreover, the
coefficient of other-income variable also has a negative
value at a significance level of 90% It indicates that if
farmers receive more income from remittances and
com-pensation from social activities their livelihood would rely
less on the forest Moreover, the positive coefficient of salary
and pension indicates that the compensation from
Govern-ment for wage employGovern-ment and retired persons cannot help
them rely less on NTFPs collection They still collect NTFPs
but not much, the coefficient is relatively low, equal to 0.002
(Table 8)
Finally, it can be concluded that the determinants of a household's dependence on NTFPs are location, female labor rate, food security, other income, and the poverty level of the household
Generally, the households who live in or near the forests collect the NTFPs for both sale and consumption However, the balance between consumption and sale of NTFPs is not the same in all locations In Ma, the quantity of NTFPs consumed
is greater than the quantity sold while the converse is true in Que Consequently, households in Que earn more cash from these products than those in Ma NTFPs, therefore, are more important for people in Que than in Ma in terms of cash income That is the main difference between the two hamlets
in terms of NTFPs Additionally other aspects of household economy including labor, cattle, and income sources are also different between two hamlets
Furthermore, NTFPs are very important in poor households
or in those who lack rice, have a high dependency ratio, or high rate of female labor The households who have higher dependency ratio benefit less from NTFPs sold, while those who lack rice for their own consumption or have a higher rate
of female labor depend more on NTFPs Poor households are more dependent on NTFP collection than other groups
As a result, the determinants of household's dependence
on NTFPs are geographical location, gender balance, food security, other income and poverty level which is defined
by cash income per capita and wealth level of house-hold The determinants of NTFPs sold are geographical location and dependency ratio, gender balance and po-verty level
For two communities living in or near the forests with the same ethnicity, the community living closer to provincial city will collect more value of NTFPs and the livelihoods of households in this community is more dependent upon the NTFPs
The results of this research highly suggest that the Government of Vietnam should consider gender balance, location, poverty level, dependency ratio in order to keep the balance between conserving the biodiversity of NTFPs and the earnings of forest dwellers because these characteristics are significantly correlated to the dependence of farmers living in
or near the forests upon NTFPs as well as cash income generated by NTFPs
Additionally, the Government of Vietnam should pay attention to the food security of forest dwellers in order to conserve the forest Households who live in or near the forests should have enough food throughout the year Otherwise they will collect as many NTFPs as possible This might lead to low biodiversity
An appropriate incentive policy for woman and poor households might be a possible solution for less commercial collection of NTFPs Generally, the poor households who have low dependency ratio or high female labor rate should be encouraged to participate in the forest management system to control the balance between commercial collection of NTFP and conservation
3In fact, this argument is presented in Data analysis
Trang 10Policies of poverty alleviation should be applied to the
forest dwellers with priority to the households with low
dependency ratios, high female labor rates or those that lack
foods in many months of a year, to lessen their dependence on
NTFPs in order to achieve efficiency in conserving biodiversity
and forest management
Acknowledgements
First and for most, we would like to express our sincere thanks
to Professor Tran Duc Vien and Stephen Leisz who provided
essential information for this research Our special thanks go
to Amanda Allbritton and Meg Hiesinger who devoted their
time to edit the English of our paper Especially, we are
thankful for the Danish International Development Agency for
funding the University Support to Environmental Planning
and Management Project (USEPAM) to collect the data in both
research sites Finally, we would like to thank all researchers
of CARES and all partners in USEPAM project who have
contributed their comments to our paper in the workshops
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