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Green Economy in Biosphere Reserve (Gebr) Project Socio-Economic Baseline Survey Report

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Green Economy in Biosphere Reserve (Gebr) Project Socio-Economic Baseline Survey Report GREEN ECONOMY IN BIOSPHERE RESERVE (GEBR) PROJECT SOCIO-ECONOMIC BASELINE SURVEY REPORT FINAL REPORT SUBMITTED TO UNESCO DAR ES SALAAM OFFICE BY THE CENTRE FOR CLIMATE CHANGE STUDIES UNIVERSITY OF DAR ES SALAAM MAY 2014 Acknowledgements Development of this report received support from various institutions and individuals. Research team would like to express their heartfelt gratitude to authorities and individuals who contributed information and experience which lead to the finalisation of this study. Heartfelt thanks go to the technical staff at Amani Nature Reserve, Tanzania Forest Conservation Group (TFCG), and district officers in Muheza, Mkinga and Korogwe for their logistical arrangements and technical guidance. Thanks go to officials who participated in the key informant interview, village government officials as well as households who participated and provided vital information during household interviews and focus group discussion. Research team is indebted to village government officials and households in Kimbo, Mashewa, Kisiwani, Foroforo, Makumba, Muzi Kafishe, Shebomeza, Kwelumbizi, Mtoni Bombo, Kijango and Hemsambia villages for their information and effective participation in focus group discussion and household interview. Research team also acknowledges the financial support by UNESCO-Dar es Salaam Office, which facilitated the undertaking of this baseline study. i Executive Summary United Nations Education, Science and Culture Organization (UNESCO) with a fund support from Korea International Cooperation Agency (KOICA) developed the Green Economy in Biosphere Reserve (GEBR) project to promote biodiversity and/or green business as a viable tool for conservation while at the same time contributing to household livelihoods. The baseline survey was conducted in order to analysing baseline data of the beneficiary community which will serve as the benchmark for the implementation of the GEBR project activities and the basis of measuring project impacts. This baseline study was conducted in 11 villages surrounding the East Usambara Biosphere Reserve (EUBR). Villages were selected basing on three interrelated criteria: administrative units in order to ensure representation from the three districts surrounding EUBR (Muheza, Mkinga and Korogwe Districts), set of drivers of deforestation and degradation; and past or ongoing interventions to improve forest conservation and communities’ livelihoods. Primary data were collected through Focus Group Discussion, Key Informant Interviews, Household surveys and Direct Field observations. Secondary data were collated from published and unpublished reports obtained from government, non governmental organisations and private sector libraries as well as online searches. Theme-content analysis and Statistical Package for Social Sciences (SPSS) were used for data analysis. Findings are presented in various forms, including the use graphs, charts and tables. About 78% (N=120) of the surveyed households were headed by men and only 22% (N=34) households were headed by women. Males constituted 57 % (N=88) of the respondents and females were 43%. About 35.7% (N=55) of the respondents were aged 51 years and above, 16.2% (N=25) were aged between 21 years and 30 years. Other respondents were aged between 31 and 50 years. About 50.6% of respondents were born in the village and 49.4% ii outside of the studied villages. Most of the migration occurred before 1990s. Reasons for migration included search for arable land, 47%, marriage 21%, following relatives 13%, search for job 18%, and business reasons 1%. About 74% of the total respondents were married, 11.7% widowed and 9.1% divorced. Household sizes ranged from 1 to 15 members. It was also revealed that majority of the respondents were primary school leavers (96%), and only 4% had passed through secondary education and vocational training. Field survey findings indicated that important livelihood activities were crop production, livestock keeping, fish farming, butterfly farming, bee keeping, tea plantation, spice making, herbs and tree nursery and wood and wood products. Majority of households were found to be engaged in single livelihood activity 70.7% (N=109). 12.3% (N=19) are involved in two livelihood activities, 7% (N=12) in three and 2% (N=4) in four livelihood activities. Majority of these activities earned a maximum average of Tshs.100, 000 per month. About 6.5% of respondents indicated that the status of their activities was very good, 28% good and 66 % struggling. Study findings indicated that key natural resources in the area were land (70.8%), forest (17.5%), rivers (6.5%), and natural spring and dams (5.1%). Majority of the respondents (73.4%) were using available natural resources for farming activities. Other uses of natural resources were collection of firewood (12.7%), fetching water for domestic use (8.2%), beekeeping (2.5%), butterfly farming (2.5%), irrigation (1.3%), traditional herbs (0.6%) and building poles (0.6%). Majority of the respondents (83.1%) were depending on firewood as major source of heat energy. Findings show that 88% of respondents use own farms for their livelihood activities while 12% use forest reserves for their activities. Key informants were of the opinion that adjacent iii villages are responsible for deforestation and forest degradation in the EUBR through extraction and artisans/mining activities. Various groups in the surveyed communities had equal access to natural resources for their socio-economic activities. However, inheritance of family resources was mentioned to be favouring men than women with such segregations highly depending on the setting of the individual households. Social capital among respondents across the studied villages was partly associated with the membership to community financial groups. Majority of the respondents who were members to community financial groups had more than Tshs. 100,000 while others had amount ranging between Tshs. 50,000 and Tshs. 100,000 as well as less than Tshs. 50,000. About 91.6% of the respondents in all studied villages reported to have no saving at all, while 8.4% reported to have savings. These savings had estimated highest amount of Tshs. 100,000. Access to microcredit in the surveyed villages was relatively difficult with only 8.4% reporting to have accessed services related to credits. Majority of the respondents were aware of existence of the green economies with some being engaged in green business. Respondents mentioned beekeeping, fish farming, spice farming, processing and selling and butterfly farming as major activities relevant for green economies. Income from green economy activities varied accordingly depending on the level of investment and capability of the household to implement the activity. 72 % (N=111) reported to earn between Tshs. 50,000 and 100,000 per month from green businesses. About 26.6% were earning less than Tshs. 50,000 and 1% were earning more than Tshs. 100,000 per month. About 61.7 % perceived the status of their economic activities as struggling, 24.7% as good and 13.6 % as very good. iv Markets for the green business products varied across the study area. Majority of respondents depended much on selling their produce to neighbours within and adjacent to their villages, individual business people from the district, Tanga, Arusha and Dar es Salaam towns who normally go to their villages for collecting spices and other farm and non-farm products and researchers who visit their villages. Other buyers come from come from Moshi Town in Kilimanjaro region. Respondents informed that there was no clear arrangement for accessing markets for farm and non-farm produce. Other respondents, especially those involved in butterfly farming reach their customers through an agent, mainly the Tanzania Forest Conservation Group (TFCG). Some identified challenges facing green economies are price fluctuation (50%), inadequate capital (39.6%), lack of markets (26%), lack of transparency (25.3%), poor means of transport (19.5%), effects of climate variability (7.8%) that affected normal production patterns of the households and exacerbates more pressure on the biodiversity resources. Other respondents (4.5%) indicated poor farm implements as another challenge affecting their livelihoods. Potential green economies activities in the study area include small scale based enterprises such as beekeeping, butterfly farming, spice farming, spice making; and eco-tourism or cultural industries such camping and canoeing activities, boat riding, site views, parachuting, waterfalls and canopy walk. Key informants emphasized that joint efforts between government institutions, non-governmental organisations including faith institutions, private sector, and individuals will improve the performance of green business activities. v Table of Contents Acknowledgements ..................................................................................................................... i Executive Summary ................................................................................................................... ii List of Tables ............................................................................................................................ ix List of Figures ............................................................................................................................ x List of Abbreviations ................................................................................................................ xi CHAPTER ONE:
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