Comparative Analysis of In-situ Conservation Costs
of
Aseffa Seyoum[1],
Bezabih Emana[2] and
Franz Gatzweiler[3] Belaineh
Legesse4
Abstract
1.
INTRODUCTION
The underling causes of deforestation are closely linked with poverty, population growth, poor economic performance and inappropriate policy intervention (Demel et al., 2003). Degradation of these natural resources has resulted in low agricultural productivity that in turn reduced quality of life. This has a cumulative impact on actions of these land users that has eventually led to the degradation and depletion of the resources endowed with biological diversity (Shibru and Kifle, 1999). Loss of biodiversity like Coffea arabica genetic resource ultimately has considerable economic loss to the country as well as the world, especially, with the current prevalence of biotic and abiotic[4] agricultural problems (Tadesse, 2003).
There is a
need to develop suitable conservation strategies to safeguard the coffee
genetic diversity along with the entire spectrum to maintain its ecological,
social and economic value to the community, to the nation and to the globe. In
this line, IBC and FARM
The remaining
part of the paper is organized as follows: The next part presents an overview
of conservation effect made so far followed by third part that deal with study
setting and research methodology. The results of the analyses are presented in
the forth part. While part five summarizes the major findings of the study, and
delivers policy implications.
2.
Overview of Forest
and Biodiversity Conservation Effort in Ethiopian
The history
of Ethiopian national conservation programs goes back to 1940s. However, the
forestry part was included as a separate component during the Dergue regime in
the fourth five-year plan in 1974. This was to deal with the state forest
protection, commercial and multi-purpose forestry, private, communal and
household forestry (Shibru and Kifle, 1999). Later, there was also a ten-year perspective plan (1984-1994), which had
emphasized on forestry conservation. In addition, these different development
plans were followed by various actions. There were afforestation and
reforestation, demarcation of natural forest and for different purposes such as
community forest, for fuel wood plantation, for industrial plantation. Moreover,
major national efforts of genetic resource conservation began with the
establishment of Plant Genetic Resource Conservation in 1976 (Melaku et al.,
2000). But, the success was impeded by
the occurrence of drought and civil war.
During the
Dergue regime, a significant level of biodiversity was eroded due to extensive
cultivation and resettlement program through clearing vast areas of natural
forestland. The frequent reallocations
of land by peasants association all over the country also created a strong
feeling of tenure insecurity among land users (Shibru and Kifle, 1999). This had discouraged farm households to
plant trees, which has negative impact to conservation of biological diversity
in both protected and managed ecosystems.
The current regime gave less attention to natural resource
conservation during the transition period when the Ethiopian People’s
Revolutionary Democratic Front (EPRDF) took power. But later, federal
government offered attention to it by developing of Natural Conservation
Strategy (CSE, 996) and declaration of
different legislations. Proclamation number 94/1994 had permitted private forest ownership to
enhance development of the private investors in the sector. But, there has been no clearly defined
guideline for investment in forest area (Kumilachew, 2001; as cited in
Richerzhagen and Virchow, 2002). This
created inconsistent decisions in land allocation to smallholder farmers and
large-scale investments. Although, the concern for natural
resource conservation is getting more pronounced, this concern could not get
out of plan to implementation and achieve results to the desired extent. Most
of the issues of implementation have been linked to participation of local
people, security of natural resource tenure, access to it and financial
capacity (Shibru and Kifle, 1999). The de facto open access to state or community owned natural forest had reduced
security of tree tenure and exacerbated deforestation (CSE, 1996).
Accordingly, Ex-situ
conservation of threatened plants and crops is being carried out on-farm and in
gene bank of Institute of Biodiversity Conservation (IBC). There are about
56,558 sample species preserved by IBC in gene bank. Coffea arabica is
one of the crops being conserved both under in situ and ex-situ
conservation strategy. In this regard, among other, attempts were made for ex-situ
conservation of coffee biodiversity by Food and Agricultural Organization (FAO)
Coffee Mission, Ethiopian National Coffee Collection Program, and recently by
IBC and Ethiopian Agricultural Research Organization (EARO) through collection
and establishment of field gene bank with in the country (Tadesse et al.,
2001). In situ conservation is defined as the conservation of ecosystems
and natural habitats and the maintenance and recovery of viable population of
species in their natural surroundings.
It is a conservation approach serves as a continuous source of
germplasm for ex-situ conservation
(Tadesse, 2003). It enables to preserve evolutionary process that
generates new germplasm under conditions of natural selection to maintain those
components in living and viable ecosystems (Swanson and Goeschi, 2000). In situ conservation has
also been established in Boginda-Yeba (2,764 ha), Geba-Dogi (10,000 ha) and
Kontri-Birhan (9,025 ha) of rainforests to preserve the genetic resources of
arabica coffee gene pool, financed by European Commission through Coffee
Improvement Project (CIP). Furthermore, there is also a plan to establish in
situ conservation in other five parts of the country namely, southwestern
Harareghe, Dambidolo, Mankra, Maji, and Amora-Geddel in Mizani-Teferi
(Agrisystems, 2001).
3. Research
Methodology
3.1. Setting
This study was conducted in the South and
Southwest, Bonga and Yayu forests. Particularly, Gimbo district from Bonga
forest and Yayu-Hurumu district from Yayu forest, which are about 440 and 520
Km from
Bonga forest is located in the Southern Nation, Nationalities & People’s (SNNP) Region, Kaffa administration zone. It covers a total area of about 161,424 ha with altitude of 1000 to 3350 meter above sea level (Ersado, 2001; as cited in Taye, 2003). The five districts bounding the area are Gimbo, Menjiwo, Tello, Decha and Chena. While another study site, Yayu (Geba-Dagi) forest is located in Yayu-Hurumu district, Illubabor zone of Oromia Regional State. This district covers about 162901 ha. The part of Bonga forest found in Gimbo district covers about 22539 ha. Yayu district covers an altitude range of 1200 - 2851.9 meters above sea level with average annual rainfall of 1191.6 -1960.7 mm per year. The average annual temperature of the area is 23.24oc. It is located at an altitude of 1550 -1780 meters above sea level. About 10000 ha of Yayu (Gebe-Dogi) forest is demarcated as protected area for biodiversity conservation (Agrisystems, 2001). The protected area is divided into two as core zone and buffer zone. Core zone is the zone to which no entry of local community is permitted. Whereas buffer zone is the one form which households with de facto land holding are allowed to harvest only coffee. This area was used to deal with the costs of strict in situ conservation strategy.
In
both areas specialization is very low and mixed farming (with some
off-farm) is the main economic activity, in household economy of the study
areas. There is a linkage among
livestock rearing, crop production and forest management and use.
Natural forest is a means of livelihood mainly through extraction of non-timber
forest products such as wild coffee, honey, charcoal, fire wood and hunting of
wildlife. Furthermore, forest remains to be very important source of farm
implements and timber for local construction. There are resettlement and investment
activities like organic coffee production that has been carried out in the
forest area. These activities did not take into consideration the degradation
of natural forest and wild populations of coffee.
Figure. 2. Map of
3.2. Sampling Technique Sample Size and data collection
In the study, two natural coffee forests in
Gimbo and Yayu-Hurumu districts were selected purposively. Then, a
two-stage random sampling technique was adopted in sampling respondents from
these purposively identified districts. Primarily, reconnaissance survey was
undertaken to prepare sample frame of the households in Peasants Associations
(PAs)[7] around the area under conservation. PAs
surrounding the conservation areas were identified for both study sites.
Accordingly, in the first stage, 4 sample PAs from each districts and a total
of 8 PAs were selected randomly. In
the second stage, sample households were selected using probability
proportional to size technique based on the number of farm households in PAs,
so that, each sample units would have equal chances of being selected. The
proportional sampling was applied within a district. The sample units in the
formal survey were the farm households, including both participants and
non-participants of the conservation strategy, in the vicinity of the
conservation area. A total of 204 sample respondents were contacted during the
formal survey.
For this study, both primary and secondary
data were collected. Primary data were collected through focus group discussion
and interview of sample households using pre-tested structured questionnaire.
The questionnaire consisted of socio-economic variables such as land holding
and use, coffee holding under different management practices, difference in benefits
before and after establishment of conservation strategies at farm household
level and so on. In addition, transaction costs of participation and other
relevant information in relation to the area under conservation were also
included. Moreover, secondary data were collected on capital and recurrent
costs under collaborative and strict in situ conservation strategies
from FARM Africa and
3.3. Methods of Data Analysis
3.3.1. Cost-effectiveness analysis
Cost-effectiveness analysis (CEA) is a technique, which is most often important in assisting decision-makers in selecting preferred choice among possible alternatives. It involves assessing the resource requirements of alternative ways of achieving a given objective. It is derived from cost-benefit analysis. Whenever the valuation of benefit is impossible, cost-benefit analysis cannot be computed. This calls for comparison of costs among different meanses of achieving a given output (Lwasa and Mwanje, 2002). It is the economic decision criteria for alternatives in which the benefits to be achieved does not vary significantly (Richards et al., 2003). Moreover, this method of analysis is suitable to deal with a situation where reliable estimation of the benefits of alternative option is not possible (Turner et al., 2004).
The basic concepts of cost-effectiveness analysis are being applied to a broad range of problems in natural resource conservation, social and public health programs. It consists of an attempt to minimize cost to meet a given goal. Cost-effective policy or strategy permits minimization of the compliance costs to meet the desired target. Sekar and Chandrasekaran (2001), in their training manual, explained the appropriateness of the approach in dealing with social and environmental programs whose benefit is difficult to monetarize but when there are different meanses to meet a predetermined standard.
There are two approaches in cost-effectiveness
study: fixed effectiveness and fixed-cost (Lwasa and Mwanje, 2002). In the
former case the best strategy depends on the cost incurred to obtain a given
level of effectiveness while in the latter case it depends on the effectiveness
obtained at a given cost. Moreover, according to Watzold and Schwerdtner (2004),
cost-effective can be identified in two aspects. A given conservation policy is
said to be cost-effective than the other if all costs of conservation in the
first is less than that of the other to achieve a given conservation aim. This
is stated as useful approach in situation with a conservation aim of ensuring a
certain survival probability of an endangered species and wants to find out how
this goal can be achieved at least-cost. On the other hand, a given
conservation instrument is said to be cost-effective if it generates a higher
level of conservation for a given amount of costs. This definition is useful in
a situation where the society is willing to devote a certain amount of
financial resource for conservation. In our analysis a cost-effective is defined
as a strategy that demand least cost to attain sustainable in situ
conservation of forest coffee.
3.3.2. Cost estimation
Primarily, costs both in situ conservation strategies are calculated at household level and comparison was made with the level of participation. Besides, expenses of responsible institutions per hectare as effectiveness in this case is measured based on the total area conserved at a given cost and different cost components at household level were estimated per sample household. In this process, descriptive statistics such as mean, percentage and frequencies were employed.
Conservation
cost estimation at household level enables to get the cost that the households
incur in conservation of coffee forest. These costs arising from implementing
of each conservation strategies were calculated as sum of opportunity costs,
transaction costs and costs due to wildlife attacks.
In this study, foregone benefit is the benefits
that the household used to harvest from a given a given conservation area (Ferraro, 2001; Braatz, et al., 1992). Forgone benefit in the form of timber
forest products was estimated at the demand of a household for timber forest products.
The households were asked about the timber forest harvested from the
conservation area and its lifespan as well as its market price. For those
commodities that have no market price, proxy value were considered. Then, the
annual value of timber forest products extracted from coffee forest was
estimated through straight-line depreciation method[8].
Forgone benefits in the form of farm implements were also computed following
the same procedure. Moreover, each non-timber forest products were listed and information
on the amount that the local people access before and after conservation was
generated through survey. Then, its value was estimated based on local market
prices.
In collaborative conservation strategy, opportunity cost to the participants of the strategy from forest products was defined as benefits before conservation minus benefit after conservation while for non-participants it is the benefit they used to harvest before establishment of forest users groups in the area since the non-participants are prohibited from entering to the conservation area thereafter. Whereas for strict in situ conservation, opportunity cost to participants of the strategy was calculated as value of timber forest products they lost plus benefit before conservation as NTFPs minus benefit they get from buffer zone as NTFPs after the area is delineated for protected conservation. This is because in this strategy, it is impossible to take out any TFPs. But, for non-participants in strict conservation strategy it was the value of forest products that the household would have harvested if there were no conservation at all.
As to institutional costs, it were estimated at conservation site and coordination office level. Institutional costs were categorized as capital and recurrent costs. All cost components were considered at project sites and coordination office level for both strategies (Epperson at al., 1997). Since capital cost lasts for more than one year, it has to be annualized. In annualization process of capital costs, the capital recovery factor was calculated at current interest rate i equal to 3 percent (on deposit) using the formula
Where A = Annual capital cost;
p = Intial capital invested;
i =
current interest rate on deposit
n = lifespan (years).
Capital cost annualization method was used to get annual cost of capital goods equivalent to recurrent cost (Gittinger, 1982; Lwasa and Mwanja, 2002). According to information from MoFED (Minyashal, B., 2005, personal communication) the life span for building, cars, and office furniture and equipments is, on average, 20, 10 and 5 years, respectively. This was adopted in annual capital cost estimation process. These costs were initially recorded in Euro, GBP and USD then converted to ETB using current exchange rate[9]. The recurrent costs were estimated on average value of annual expenditure of the two projects to conserve their respective areas.
4. Results and
Discussions
4.1. Socio-economic characteristics of sampled households
The most
important socio-economic households characteristics that that determine
households decision in relation to participation in conservation and level of
costs that household incur are household assets like landholding, livestock and
level of dependency on the natural forest. Landholding of farm
households is one of the basic resources that affect decision-making of
agricultural production and conservation activities (Konyar and Osborn, 1990).
according to the survey result, average total landholding of samples households
in collaborative and strict in situ
conservation areas was 2.38 ha and 2.30 ha, respectively. This difference in
average total land holding is not statistically significant between the two in situ conservation strategies. Crop production is the primary farming
activity of the respondents. Generally, cereals and coffee were the
major crop types under production activities followed by pulse, horticultural
and other perennial crops like chat[10]
and enset (false banana).
There are four
distinct management systems in the study area with regard to coffee.
There are two common harvesting
systems of coffee cherries in the areas. These are selective picking and
stripping[11].
Most of the farmers in the study area prefer the former system in case of
plantation and garden coffee since it is a method to have quality coffee
cherries. Out of sample households with forest/semi-forest coffee under
production 78 percent and 40 percent of households in collaborative and strict
conservation areas, respectively, had harvested their forest/semi-forest coffee
by stripping in 2003/04
production year. This is basically done
since the forest/semi-forest coffee land that is situated away from homestead
of the owner is subjected to theft problem.
Table 1. Average livestock owned by the sample households in TLU
|
Livestock owned |
Collaborative
|
Strict
|
t-value |
|
Oxen |
1.2 |
1.2 |
0.030 |
|
Cattle |
2.3 |
1.9 |
1.381 |
|
Small ruminant |
0.2 |
0.2 |
-0.953 |
|
Others§ |
0.2 |
0.2 |
0.490 |
|
Total livestock |
3.9 |
3.5 |
0.943 |
§ Include horses, donkeys, mules and chicken.
Household's dependency on coffee
forest refers to the level if contribution of the natural forest to the
livelihood of that household. It was known that NTFPs play an important role in
the well-being of millions of people around the world. Local market prices were
used to estimate the value of NTFPs and other sources of income. Accordingly,
in 2003/04 production year, non-timber forest products constitute 32 percent of
income of sample households from collaborative conservation area while this
percent rises to 56 in strict in situ conservation area. This implies
that respondents in strict conservation area are more dependent on coffee
forest for cash source as compared to collaborative area. Dependency on natural
forest as source of income was significantly different at 1 percent probability
level between the two conservation areas (Table 2).
In case of strict in situ conservation, non- participant sample households generate 62 percent of their total income form NTFPs including forest coffee, highly dependent on natural forest as compared to the participants, who generate about 44 percent of their income, which was significantly different at 5 percent probability level. This implies that effective implementation of the conservation strategy will result in loss of considerable portion of their income. This is the challenge for sustainable coffee forest conservation under strict conservation strategy. Those households who respected the rules and regulations of strict in situ conservation generate more income (757 ETB) from plantation coffee as compared to non-participant household (376 ETB) of the same area. This difference was significant at 10 percent probability level.
Availability of off-farm income to the people in conservation areas may reduce the pressure on biodiversity (Srivastava et al., 1996). In the study area, bee keeping was the main off-farm activity. It is practiced more in collaborative as compared to strict conservation area. About 63 and 56 percent of the total sample households involve in apicultural activity for collaborative and strict conservation area, respectively. As it can be seen from Table 2, the average number of beehives was high in collaborative conservation area as compared to the strict in situ conservation area. Bee-keeping activity has long history with the life of the people, which was highly linked to their culture and existence of natural forest in the areas. It has of considerable economic importance, particularly for those households with less livestock and cropland holding. The mean income from off-farm activity in strict in situ conservation, which is 277.9 ETB for participant and 67.4 ETB for non-participant household, is differing significantly between the two groups at 10 percent probability level. These may imply that households with more income from plantation and off-farm activities are more likely to respect the rules and regulations of strict in situ conservation strategy.
Through not well developed, there are some off-farm
opportunities in the study area. This is evidenced by the fact that 5 percent
of the sample households in each conservation area took part in this activity
in 2003/04 production year.
Table 2. Average sample households income in 2003/04 production year
|
Sources |
CC
|
SC
|
t-value
|
|
|
157.9 |
1127.8 |
-6.409*** |
|
Planted coffeej |
246.4 |
510.3 |
-1.981** |
|
NTFPs |
330.4 |
74.3 |
3.326*** |
|
Crops |
126.5 |
197.9 |
-1.554 |
|
Livestock |
326.4 |
175.9 |
1.767* |
|
Off -farm activities |
180.6 |
141.6 |
0.558 |
|
Total income |
1371.6 |
2227.9 |
-3.385*** |
|
Ratio of incomew |
0.32 |
0.56 |
-4.775*** |
Source: Own survey result, 2004
*, **, *** statistically significant at 10%, 5% and 1% probability levels, respectively;
j Includes garden and coffee planted on farmland;
w Refers to ratio of income form NTFPs including wild coffee to total income of household.