The University of Dodoma University of Dodoma Institutional Repository http://repository.udom.ac.tz
Social Sciences Master Dissertations
2017 Utility of climate change and variability information for rice farming in Babati district-Manyara region
Nkua, Aron Joseph
University of Dodoma
Nkua, A. J. (2017). Utility of climate change and variability information for rice farming in Babati district-Manyara region. Dodoma: The University of Dodoma http://hdl.handle.net/20.500.12661/457 Downloaded from UDOM Institutional Repository at The University of Dodoma, an open access institutional repository. UTILITY OF CLIMATE CHANGE AND VARIABILITY
INFORMATION FOR RICE FARMING IN BABATI
DISTRICT-MANYARA REGION
ARON JOSEPH NKUA
MASTER OF SCIENCE IN NATURAL RESOURCES MANAGEMENT
THE UNIVERSITY OF DODOMA
OCTOBER, 2017 UTILITY OF CLIMATE CHANGE AND VARIABILITY
INFORMATION FOR RICE FARMING IN BABATI
DISTRICT-MANYARA REGION
By
Aron Joseph Nkua
A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of
Master of Science in Natural Resources Management of the University of Dodoma
The University of Dodoma
October, 2017 CERTIFICATION
The undersigned certifies that he has read and here by recommends for acceptance by the University of Dodoma, a dissertation entitled “Utility of Climate Change and
Variability Information for Rice Farming in Babati District - Manyara Region” in partial fulfilment of the requirements for the degree of Master of Science in Natural
Resources Management of the University of Dodoma.
………………………………………………. Dr. Ahmad Kanyama (SUPERVISOR)
Date……………………………………………
i DECLARATION
AND
COPYRIGHT
I, Aron Joseph Nkua, declare that this dissertation is my own original work and that it has not been presented and will not be presented to any other University for a similar or any other degree award.
Signature……………………………
No part of this dissertation may be reproduced, stored in any retrieval system, or transmitted in any form or by any means without prior written permission of the author or the University of Dodoma.
ii ACKNOWLEDGEMENTS
I thank God for giving me an opportunity to undertake this study for my academic fulfilment. My deepest gratitude goes to my supervisor, Dr. Ahmad Kanyama for his guidance and valuable contributions in writing this dissertation. Also, I wish to express my appreciation, thanks to my lovely father and mother, Mr & Mrs. Sanare
Koyee for their sponsorship to my Graduate studies.
Special thanks are due to rice farmers and the village administration in Magugu,
Gichameda, and Matufa for their cooperation and provision of information essential for this study. In addition, the cooperation of the leadership of Babati district is highly appreciated.
I would like to thank all lecturers from the Department of Geography and
Environmental Studies of the University of Dodoma. Also, my thanks are extended to my colleagues, Natural Resources Management students for their moral support. I wish to express my sincere thanks to my lovely uncle Milton Nkua, my father in law, Lomi Ole Meikasi, my siblings Joseph Sanare for their prayers and encouragement which strongly shaped my academic struggle.
Last but not least, I would like to thank my friend Nangda Meikas, Fides Kavishe and Vicky Meikas for their encouragement.
iii DEDICATION
This dissertation is dedicated to my beloved parents, Mr & Mrs Sanare Koyee, my supervisor Dr. Ahmad Kanyama whom together laid the foundation of my Graduate education. May the almighty God provide them with long and healthier life.
iv ABSTRACT
The aim of this study was to assess the utility of climate change and variability information for rice farming in Babati district of Manyara region.The subjects in this study were 122, comprising of 97 rice farmers, 07 key informants and 18 members of FGDs. Primary data were collected through questionnaire and checklist. Multiple responses analysis, chi-square test, linear and logistic regression were used to analyze the collected data. The result showed that 95.1% of the respondents had access to climate variability information that was largely based on low or high rainfall (100%), occurrences of floods (56-70%), and delaying/earling of rain season
(40-53%). Moreover, 88.4% of respondents accessed the information through mass media. Linear regression results showed that there was a gradual increase (R2=0.2) in temperature from 1995 to 2016, and a simultaneous decrease of rainfall (R2
=0.007) and rice production (R2 =0.04). Also, 74.4% of the respondents together with local leaders (WEO, VEOs) were not integrating climatic information in farming decision. This weakness largely was contributed by inadequate institutional support, inadequate climate information, inadequate communication between farmers and extension officers, and disbelieving of climate information. Further logit regression results showed that education level (Wald statistics=19.1 ; p<0.03) and income level of farmers (Wald statistics=9.8; p<0.05) affect the use of climate information. High cost of farm inputs (94-100%), poor access to credit (78-100%), and poverty (78-95%) were the main challenges that faced farmers who were integrating climatic information in farming decision. Clear link and collaboration is required among actors in the area for effective sharing of climate information and for better adaptation.
v TABLE OF CONTENTS
CERTIFICATION ...... i DECLARATION AND COPYRIGHT ...... ii ACKNOWLEDGEMENTS ...... iii DEDICATION ...... iv ABSTRACT ...... v TABLE OF CONTENTS ...... vi LIST OF TABLES ...... xi LIST OF FIGURES ...... xii LIST OF PLATES ...... xiii LIST OF APPENDICES ...... xiv LIST OF ACRONYMS ...... xv
CHAPTER ONE: INTRODUCTION AND BACKGROUND TO THE STUDY .... 1 1.1 Introduction ...... 1 1.2 Background Information ...... 1 1.3 Problem Statement and Justification ...... 3 1.4 Research Objectives ...... 4 1.4.1 General Objective...... 4 1.4.2 Specific Objectives...... 4 1.5 Research Questions ...... 5 1.6 Significance of the Study ...... 5 1.7 Scope of the Study ...... 6
CHAPTER TWO: LITERATURE REVIEW ...... 7 2.1 Introduction ...... 7 2.2 Definition of Key Terms ...... 7 2.2.1 Climate Change ...... 7 2.2.2 Climate Variability ...... 7 2.2.3 Climate Change and Variability Information ...... 8 2.2.4 Rice as a Crop ...... 8 2.2.5 Rice Farming ...... 9 2.3 Theoretical Review ...... 9
vi 2.3.1 Protection Motivation Theory (PMT) in Climate Change ...... 10 2.3.2 An Action Theory of Adaptation to Climate Change ...... 11 2.3.3 Policy Review ...... 13 2.3.4 Climate Change Information: Availability, Accessibility, and Robustness ..... 14 2.4 Empirical Review ...... 15 2.4.1 Climate Change and Rice Farming ...... 15 2.4.1.1 Climate Change and Rice Farming Experience World Wide ...... 16 2.4.1.2 Climate Change and Rice Farming in Sub-Saharan Africa (SSA) ...... 18 2.4.1.3 Climate Change and Rice Farming in Tanzania ...... 19 2.5 Knowledge Gap ...... 20 2.6 Conceptual Framework ...... 21
CHAPTER THREE: RESEARCH METHODOLOGY ...... 23 3.1 Introduction ...... 23 3.2 Research Design ...... 23 3.3 Area of the Study ...... 23 3.3.1 Study Area and the Selection Criterion ...... 24 3.3.2 Location...... 24 3.3.3 Climate ...... 26 3.3.4 Soil and Economic Activities ...... 26 3.4 Research Approach ...... 26 3.5 Sample and Sampling Procedure ...... 27 3.5.1 Targeted Population ...... 27 3.5.2 Sample Design ...... 27 3.5.3 Sampling Unit ...... 28 3.5.4 Sampling Frame ...... 28 3.5.5 Unit of Analysis ...... 28 3.5.6 Sample Size ...... 29 3.5.6.1 Sample Size Distribution...... 30 3.5.7 Time Frame ...... 30 3.5.8 Parameters of Interest ...... 30 3.5.9 Sampling Procedure ...... 31 3.5.9.1 Probability Sampling Method ...... 31
vii 3.5.9.1.1 Simple Random Sampling...... 31 3.5.9.2 Non-probability Sampling Method ...... 32 3.5.9.2.1 Purposive Sampling ...... 32 3.6 Methods and Instruments for Data Collection ...... 32 3.6.1 Types of Data ...... 32 3.6.1.1 Primary Data ...... 33 3.6.1.2 Secondary Data ...... 34 3.6.2 Methods Used for Data Collection ...... 34 3.6.2.1 Face to Face Structured Interviews ...... 34 3.6.2.2 Focus Group Discussion ...... 35 3.6.2.3 Documentary Review ...... 35 3.7 Data Processing, Analysis and Presentation ...... 36 3.7.1 Analytical Design and Data Processing ...... 36 3.7.2 Data Analysis ...... 36 3.7.2.1 Causal Analysis ...... 38 3.7.3 Data Presentation ...... 39 3.8 Data Quality Control ...... 39 3.8.1 Reliability ...... 39 3.8.2 Validity ...... 39 3.9 Ethical Consideration ...... 40
CHAPTER FOUR: RESULTS AND DISCUSSION ...... 41 4.0 Introduction ...... 41 4.1 Demographic Characteristics of Respondents ...... 41 4.1.1 Sex of Respondents ...... 41 4.1.2 Age of the Respondents ...... 42 4.1.3 Education Level of Respondents ...... 42 4.1.4 Respondents’ Occupation...... 43 4.1. 5 Households Size ...... 43 4.1. 6 Respondents Income Level ...... 44 4.2 Climate Change and Variability Information Available to the Community ...... 46 4.2.1 Awareness on Climate Change ...... 46 4.2.1.1 Farmer’s Education Level and Awareness on Climate Change Information 47
viii 4.2.1.2 Farmers’ Understanding of Climate Change...... 48 4.2.3 Climate Change and Rice Production ...... 50 4.2.4 Ways in Which Climate Change Reduce Rice Production ...... 51 4.2.5 Access to Climate Change and Variability Information ...... 54 4.2.5.1 Sources of Farmers’ Access to Climate Change and Variability Information ...... 55 4.2.6 Climate Change and Variability Information Accessed by Rice Farmers ...... 57 4.2.7 Barriers for Accessing Climate Change and Variability Information ...... 59 4.3 The Trends of Climate Change Patterns and Rice Production in the Area ...... 62 4.3.1 Trends of Temperature (Maximum and Minimum) ...... 63 4.3.2 Trends of Rainfall in the Area from 1995-2016...... 64 4.3.3 Trends of Rice Production in Tones from 2000/1-2015/16 ...... 66 4.3.4 Relationship Between the Trends of Rice Production and Rainfall Patterns . 67 4.4 The Integration of Climate Change and Variability Information in Rice Farming ...... 68 4.4.1 Use of Climate Change Information in Decision about Rice Farming ...... 69 4.4.1.1 Farmers’ Characteristics and Use of Climate Information in Farming Decision ...... 71 4.4.1.2 Reasons for not Using Climate Change Information in Decision About Rice Farming ...... 72 4.4.1.3 Adaptation made in Response to Variation in Rainfall and Increase in Temperature Information for Rice Farming ...... 74 4.4.2 Information on Floods Control ...... 76 4.4.2.1 Methods for Floods Control ...... 79 4.4. 3 Information on Soil Management ...... 80 4.4.3.1 Methods for Soil Management ...... 81 4.4. 4 Information on Reducing the Pests and Diseases on Rice Farming...... 83 4.4.4.1 Techniques used to Control Pests and Diseases on Rice Farming ...... 84 4.5 Challenges Facing the Community in the Use of Climate Change and Variability Information in Rice Farming ...... 85 4.5.1 The way Climate Change and Variability Information are communicated ..... 85 4.5.2 Difficulties facing Farmers in the Use of Climate Change Information ...... 86
ix CHAPTER FIVE: SUMMARY, CONCLUSION, AND RECOMMENDATIONS ...... 91 5.1 Introduction ...... 91 5.2 Summary of the Findings ...... 91 5.3 Conclusion ...... 93 5.4 Recommendations ...... 94 5.5 Areas for Further Studies ...... 95 REFERENCES ...... 96 APPENDICES ...... 110
x LIST OF TABLES
Table 1: Sample Size Distribution ...... 30 Table 2: Distribution of Respondents by Social and Economic Characteristics ...... 44 Table 3: Farmers’ Experience in Rice Farming...... 45 Table 4: Farmers’ Understanding of Climate Change and Variability ...... 49 Table 5: The Extent of Drought and Floods Occurrences...... 50 Table 6: Climate Change and Rice Production ...... 51 Table 7: Climate Change Ways that Reduce Rice Yield ...... 54 Table 8: Climate Change and Variability Information Accessed by Rice Farmers .. 58 Table 9: Barriers for Accessing Climate Change and Variability Information ...... 61 Table 10: Information for Reducing the Impacts of Climate Change in Rice Farming ...... 62 Table 11: The Correlation Between Farmers’ Characteristics and Use of Climate Change Information ...... 72 Table 12: Reason for not Using Climate Change and Variability Information ...... 74 Table 13: Adaptation Made in Response to Variation in Rainfall and Temperature Information ...... 76 Table 14: Information on Floods Control ...... 79 Table 15: Means of Floods Control ...... 80 Table 16: Methods for Soil Management ...... 82 Table 17: Techniques Used to Control Pests and Diseases ...... 84 Table 18: Difficulties facing Farmers in use of Climate Change Information ...... 90
xi LIST OF FIGURES
Figure 1: Conceptual Framework for the Study ...... 22 Figure 2: Topographical Map of Babati District Shows the study ward...... 25 Figure 3: Awareness of Rice Farmers on Climate Change and Variability ...... 47 Figure 4: Access to Climate Change and Variability Information ...... 55 Figure 5: Sources of Farmers’ Access to Climate Variability Information ...... 57 Figure 6: Annual Maximum Temperature From 1995-2016 ...... 64 Figure 7: Annual Minimum Temperature from 1995-2016 ...... 64 Figure 8: Annual Rainfall (mm) from 1995-2016 ...... 65 Figure 9:Trend of Rice Production (in tone) from 2000/1-2015/2016 ...... 66 Figure 10: Relationship Between Rainfall Pattern and Rice Production ...... 68 Figure 11: Use of Climate Change information in Rice Farming Decision ...... 71 Figure 12: Information on Soil Management ...... 81 Figure 13: Information on Reducing Pests and Diseases ...... 83 Figure 14 The way Climate Change Information are communicated ...... 86
xii LIST OF PLATES
Plate 1: The Rice Farm which was Affected and not Affected by Drought ...... 52 Plate 2: Channel of Water for Irrigation in Gichameda Village ...... 75 Plate 3: River Kou and Rugina which frequently overflow and water spread to the community residence ...... 78
xiii LIST OF APPENDICES
Appendix I: Questionnaire for Households (for Rice Farmers) ...... 110 Appendix II: Checklist for Focus group discussion ...... 117 Appendix III: Checklist for Key informants (VEOs & WEO) ...... 118 Appendix IV: Checklist for Key informants (Ward & District Agricultural Extension Officer) ...... 119 Appendix V: Checklist for Key informants (District Meteorologist Officer) .. 120 Appendix VI: Climate Patterns Data(Rainfall and Temperature) From 1985-2016 ...... 121 Appendix VII: Babati District Rice Production in Tone From 2000/1-2015/16 122 Appendix VIII: Babati District Rice Production in Tones for 1374 Hectare Grown as a Sample ...... 123 Appendix IX: UDOM Permission Letter for Data Collection ...... 124 Appendix X: Data Collection Permission Letter from Babati District Administrative Secretary ...... 125 Appendix XI: Data Collection Permission Letter from Executive Director of the District ...... 126 Appendix XII: Pay Slip for Climate Patterns Data ...... 127 Appendix XIII: Comments From External Examiner ...... 128
xiv LIST OF ACRONYMS
AC Aon Corporation
ADB Asian Development Bank
ALP Adaptation Learning Programme
ARI Agriculture Research Institute
CAB Congo Air Boundary
CEEPA Centre for Environmental Economics and Policy in Africa
CGIAR Consultative Group on International Agriculture Research
DAEO District Agriculture Extension Officer
DM District Meteorologist
FAO Food and Agriculture Organization
FAOSTAT Food and Agriculture Organization Corporate Statistical
Database
FGDs Focus Group Discussions
GCM General Circulation Model
IPCC Intergovernmental Panel on Climate Change
ITCZ Inter Tropical Convergence Zone
JAICA Japan International Cooperation Agency
MAFSC Ministry of Agriculture Food Security and Cooperatives
MKUKUTA Mkakati wa Kukuza Uchumi na Kupunguza Umaskini
Tanzania
Mm Milimetre
MS Mean Square
NAO National Audit Office
NAPA National Adaptation Programme of Action
xv NGOs Non -Governmental Organizations
NSW New South Wales p p-Value
PMT Protection Motivation Theory
PMT-TTM Protection Motivation Theory- Trans Theoretical Model
RLDC Rural Livelihood Development Company
S South
SS Sum of Square
TDV Tanzania Development Vision
TMA Tanzania Meteorological Agency
UNFCCC United Nation Framework Convention on Climate Change
URT United Republic of Tanzania
USDA United States Department of Agriculture
VEOs Villages Executive Officers
WAEO Ward Agriculture Extension Officer
WEO Ward Executive Officer
WMO World Meteorological Organization
% Percentage
xvi CHAPTER ONE
INTRODUCTION AND BACKGROUND TO THE STUDY
1.1 Introduction
This chapter provides the background information on the utility of climate change and variability information for rice farming. As well, it provides the statement of the problem, research objective and specific objectives, research questions, the significance of the study, and the last presents the scope of the study.
1.2 Background Information
Climate change and its variability are one of the main sources of uncertainty, stresses and risk in many sectors around the world (Fisher & Snapp, 2014). Poor communities in Asian and African region are exposed more to the risks brought by climate change and variability at local scales since relying upon local natural resources for their livelihood activities, are exposed to several hydro-meteorological hazards, and low level of coping capabilities (Jagtap, 2007; Osbahr, Twyman,
Adger & Thomas, 2008).
The integration of climate change and its variability information in government, nongovernment, private sector and individual member of a community in decision making help to adapt and mitigate against the risks of disasters, climate extremes and other related events that threaten vulnerable communities around the world, particularly in Africa and Asian region (Wilkinson, Budimir, Ahmed & Ouma,
2015; Nyasimi & Mungai, 2015).
The Current climate change and its variability, viewed along with future climate change scenarios, highlights the need for delivering climate change information in a timely manner, and effective use in practices to manage current climate risks (floods
1 and drought) and prepare adaptive measure or actions, for many sectors including agriculture sector which is mainly affected (Srinivasan, Rafisura & Subbiah, 2011;
Foresight, 2012; Ahmed, 2013).
According to Rourke (2011) and Foresight (2012), climate change is a threat which exacerbate the failure of the agricultural sector in Africa. For example, it has caused a decrease in agriculture yield by 5-8% from 1980-2008, and the crops that are mostly affected including rice, maize, and coffee. It is projected that the reduction in yield will range from 10-20% by 2050 or even up to 50% and crop revenue to fall up
90% by 2100 ( FAO, 2009). The yield of rice is affected much by frequent flood, precipitation that fluctuate more sharply, high temperature and drought (Wlokas,
2008). For example in Nigeria, the occurrence of flood in 2007 caused much destruction of rice crops, while the reduction in precipitation by 5% in 2010 reduced the yield of rice by 15.72 % (CEEPA, 2013).
Tanzania is one of the African countries which is exemplary for the analysis of high impacts of climate change and its variability in various sectors including agriculture
(Nicholson, 2001; Stige et al., 2006; Giannini, Biasutti, Held, & Sobel, 2008).
These impacts include; flooding, droughts, reduction in agricultural productivity, livestock deaths and intensification of climate-sensitive diseases (Ceven, Omambi &
Gu, 2010).
According to Rowhani, Linderman, Ramankutty & Lobell (2011) by 2050 the projected seasonal temperature increase by 20C in Tanzania will reduce average rice yields by 7.6% , and the continuation of occurrence of floods in several parts of the country will pose more risk including loss of life and properties. In recent years
(2008-2016), floods and heavy rains accompanied by strong winds and drought have
2 resulted in loss of livestock and crops; an increase in vector and water-borne diseases; food shortages; internal displacement; increased disease transmissions; damage to properties, destruction of the environment and economy in Kilosa,
Mbulu, and Babati district (TMA, 2011; Keyyu, 2012; TMA, 2016).
Generally, much emphasis has been directed to point out the impacts of climate change and its variability, promoting means for adaptation and mitigation, but what kind of climate change and variability information available to the community? How well informed the local community is? and how integrated information is for farming?
1.3 Problem Statement and Justification
Climate change and its variability will pose more risks and challenges towards economic growth and economic development if the climate information will not be taken into decision and action by the actors (Srinivasan et al., 2011).
Babati district is highly affected by the impacts of climate change and its variability
(Hackner, 2009). These impacts have resulted into; decline in surface flow, the decline in agricultural production, increasing the period of drought, the rise in temperature and occurrence of floods particularly in Magugu ward (Malole &
Sagenda, 2014; Juma, 2016; TMA, 2016). Various effort have been made by the government including; establishment of farms field school(FFS) famous “mashamba darasa”, locating extension officers, campaign, and the presence of system that monitor and disseminate weather variability information to the community to facilitate the integration of climate information in addressing risks and impacts posed by climate change and variability (Hackner, 2009; Keyyu, 2012).
3 Certainly the use of climate change information enables the community (individual, group, household) to decide or adjust and to conduct the best means that can reduce or mitigate the risk posed by climate change (Srinivasan et al., 2011). Even though there are several studies on climate change in agriculture and sub-sector (Rowhan et al., 2011), still little is known regarding to the kind of climate change information available to the local community, how well it informs the community and the integration of climate change and variability information by the local community in farming.
The study aimed at contributing in addressing these knowledge gaps by pointing out the kind of climate change information available to the local community, how well it informs the community, and the integration of climate change and variability information in rice farming in Babati district.
1.4 Research Objectives
This section presents the objective to be achieved by the study. The researcher outlines both general objective and specific objectives.
1.4.1 General Objective
The general objective of this study was to assess the utility of climate change and variability information for rice farming in the study area.
1.4.2 Specific Objectives
i. To examine the kind of climate change and variability information available
to the community for rice cultivation.
ii. To identify the trends of rice production and climate patterns from 1995 to
2016 in Babati District.
4 iii. To examine the integration of climate change and variability information in
rice farming.
iv. To investigate the challenges facing the community in the use of climate
change and variability information in rice farming.
1.5 Research Questions
i. What kind of climate change and variability information are available to the
community for rice cultivation?
ii. What is the trend of rice production and climate patterns from 1995 to 2016
in the study area?
iii. How climate change and variability information are integrated into rice
farming by the local community in the area?
iv. What are the challenges facing the community in the use of climate change
and variability information in their decision about rice farming?
1.6 Significance of the Study
The finding obtained from this study will widen knowledge on the use of climate information by: motivating the local community on the need of acquiring of climatic variability information that has impacts on their life and on their activities (farming) and use it; encourage decision-makers (local community, politician, planners) to use the climatic variability information which are provided by Meteorological agency and by researchers on their decision upon undertaking measures for overcoming disaster risks and socio-economic activities of an area; encourage meteorological agency and researchers to ensure that they can have a proper way of disseminating the climatic variability information to the local community; encourage the government to decide a best way to ensure the community use climatic information effectively to undertake adaptation and mitigation measure. Further, the study will
5 be a reference to motivate other researchers in the future to conduct more research on the utility of climate change and variability information in disaster management
(flood, drought) and on crop farming in Tanzania, with the purpose of coming up with a long lasting concrete solution for the problem. Finally, this study contribute to partial fulfillments of the requirements for the Master of Science degree in
Natural Resources Management of the university of Dodoma.
1.7 Scope of the Study
This study was conducted in Babati district in Magugu ward. Specifically, it covered three villages which were; Magugu, Matufa and Gichameda village. The three villages were selected from the 7 villages that were found in Magugu ward. The selection criteria was based on how the villages were vulnerable to the impacts of climate variability. The three villages had been hit by climate change in the form of repeated occurences of floods and drought, and most of the inhabitants were involved in rice production.
6 CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
This chapter presents a review of relevant theoretical and empirical literature basing on the utility of climate change and variability information for rice farming, on overcoming the risks posed by climate variability. The chapter starts to present the definition of key terms, followed by theoretical review, empirical review, conceptual framework and lastly highlights the knowledge gap.
2.2 Definition of Key Terms
2.2.1 Climate Change
Climate change and variability is viewed as a systematic change in the key dimension of climate including average temperature, wind and rainfall patterns over a long period of time (Paavola, 2008). According to UNFCCC (2007), climate change refers to a change of climate that is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and that is in additional to natural climate variability observed over comparable time periods. The main characteristics of climate change is increases in average global temperature; changes in cloud cover and precipitation particularly over land; increase in ocean temperatures and ocean acidity due to seawater absorbing heat and carbon dioxide from the atmosphere; melting of ice caps and glaciers.
2.2.2 Climate Variability
Climate variability refers to short-term (daily, seasonal, annual, inter-annual, several years) variation in climate or weather conditions, including the fluctuation associated with storm and disaster such as El Nino or La Nina. Climate variability
7 stems from the redistribution and changes in the amount of energy around the globe, which lead to changes in pressure, temperature, and other climate variables. The causes of climate variability rely on internal factors such as the ocean –atmosphere coupling at playing during various oscillations, and external factors such as natural forcing like active gasses and aerosol (IPCC, 2007).
2.2.3 Climate Change and Variability Information
Climate change and variability information in this context refers to the collection and interpretation of climate-related data. Climate information can consist of the analysis of, among other data: historical observations of the past and current climate; future projections over multiple timescales, typically achieved through various climate- and earth-system models; and climate impacts, vulnerabilities and adaptation options, which require information and analysis from the fields of economics and other environmental, social and political sciences (Jones, Carabine,
Roux & Tanner, 2015).
2.2.4 Rice as a Crop
Rice is the seed of the grass species Oryza Glauber rima for African rice or Oryza
Sativa for Asian rice. As a cereal grain, rice is the most widely consumed staple food for a large of the world population (FAOSTAT, 2012). Since in most parts of the world maize crops are growing for purposes other than human consumption, rice is the most important grain with regard to human nutrition and caloric intake, it accounts for more than one-fifth of the calories consumed by humans worldwide
(Song, 2003). There are various varieties of rice and culinary preferences which tend to vary regionally. Rice as a monocot, grown as an annual plant normally, though in most tropical areas it can survive as a perennial (LI, 2007). The rice plant can grow
8 to 1- 1.8m tall, sometimes more than that, depending on the variety and soil fertility.
It's suitable for regions with high rainfall, however, can be grown practically anywhere, even on a steep hill, with the use of water controlling terrace systems or any place through the irrigation system. The strain of rice is between white, brown, red and black (or purple), and each prevalent in different parts of the world.
2.2.5 Rice Farming
Farming is activity of growing crops or keeping animals by people for food and raw materials. Farming is the part of agriculture. Rice farming is an activity of growing rice and can be cultivated using different methods based on the type of region (Xu,
Cai & Tsuruta, 2003). In spite of using modern methods in various parts of the world, also the traditional method of farming is used. The seeds are transplanted by hand and then through proper irrigation. Rice is grown in different varieties of soil like silts, gravel, and loam. However, clayey loam is mostly suited to the raising of this crop. It also tolerates alkaline and acidic soil (Yu & Diao, 2011). The rice fields should be level and have low mud walls for retaining water, though for the plain areas with excess rainwater is allowed to inundate the rice fields and flow slowly.
Various countries involved in rice farming includes India, Thailand, Japan, Nigeria and also Tanzania.
2.3 Theoretical Review
According to Adam and Aurora (2008), a theory is an interrelated idea about various concepts, processes, relationship or events. Theories are used to describe, predict, explain, and control a phenomena. A theoretical framework is a collection of interrelated ideas based on theories. It is a reasoned set of proposition, which is derived from and supported by data or evidence, (Kombo & Tromp, 2006). In this
9 research protection, motivation theory and an action theory of adaptation to climate change are reviewed.
2.3.1 Protection Motivation Theory (PMT) in Climate Change
Protection Motivation Theory (PMT), is a theory that explicitly relates socio- economic and psychological factors to adaptation. It explains the effects of fear on a risk posed, and responses in order to understand an individuals’ intention to adopt recommended preventive. PMT describes two processes that construct an individuals’ intention to protect itself against a risk posed by climate change and variability. These cognitive processes depend much on climate change information from several resources, like information from the physical environment and agents in their social network (Rogers, 1985).
The first process is climate change risk appraisal in which an individual evaluates the severity and probability of occurrence of an event in the case of a maladaptive response; an individual has to believe that he/she will be at risk posed by climate change and variability, and that risk might cause harm when he/she will not take any adaptive measures. A person will compare this assumed threat with the rewards of maladaptive responses. In absence of appraisal of a certain risk or threat, the process of coping appraisal will not be initiated; if a person does not perceive any risk he/she will not search for and evaluate adaptive responses.
In the second process of adaptation appraisal, a person evaluates the ability to cope with and avert the risk. The coping appraisal process a person has first to believe that an adaptation measure will be effective in reducing harm and he/she has the ability to take measure (Grothmann & Patt, 2005). A person would show adaptive coping behavior when the risk perception resulting from the threat appraisal process
10 and perceived adaptive capacity resulting from the coping appraisal process are both high.
Bockarjova, Van der Veen & Geurts (2009), in using extended Protection
Motivation Theory-Trans Theoretical Model (PMT-TTM) approach investigate the relation between flood risk, drought, high temperature and the readiness of individuals to undertake adaptation in Netherlands. PMT-TTM suggests that people at different adaptation decision-making stages are differentially affected by perceived probability, severity, self-efficacy, and response efficacy.
Weakness, the theory assumes that individuals are rational information processors
(although it does include an element of irrationality in its fear components), it does account for habitual behavior, the role of social (what other do) and environmental factors (opportunities to exercise the adaptation or the work) (Schwarzer, 1992).
2.3.2 An Action Theory of Adaptation to Climate Change
Adaptation to climate change and variability can be targeted at changing conditions or at reducing damage (Füssel, 2007b). Adaptation is said to rely upon the information about the vulnerability to climate change and variability. The vulnerability is neither partially determined by available adaptation options, nor can adaptation change vulnerability (Kelly & Adger, 2000). Effective adaptation which build resilience depends on enabling environment. The author argues that resilience approaches are associated with system properties that enable action (Eisenack &
Stecker, 2011). In order to improve adaptation to climate change, the theory points out that, barriers that inhibit the adaptation should be identified and clear means of reducing it should be developed.
11 The core concept of an action theory of adaptation relies upon the presence of a stimulus, exposure unit, receptor, operators, in which collectively the exposure unit, receptor, and operators can be the actors.
A stimulus is a change of biophysical variable triggered by climate change. It refers to new statistical properties as averages intensity, frequencies or abrupt large-scale events in the earth system such as drought, rise in temperature, flooding, and erratic rainfall. Stimulus is more relevant for adaptation when all those actors, social, technical or non-human systems that depend on climatic conditions are exposed to stimuli (Kelly & Adger, 2000). The impact of climate change based on the theory is a combination of a stimulus and an exposure unit. For example, the public early warning system that informs on upcoming extreme weather conditions (heavy rain likely cause flooding) that bear the risk for the lives of the people, destruct properties and crops. Therefore adaptation, in this case, may be motivated by the impact of more frequent occurrence of floods (the stimulus). The exposure units are those who will be affected directly or indirectly by the impacts, and the operator is those (collective) actors that exercise the response on adaptation to risk (Stecker et al., 2010). The actor or system that is addressed by the purpose of an adaptation is called the receptor. Receptors can be biophysical entities (e.g. the crops of a farmer) and social systems (e.g. the farmer household). In implementing the adaptation to climate change and variability, the operator requires resources, called means. This includes access to financial or other material resources, legal power, social networks, knowledge, and availability of information. The action is shaped by the constraints existing and resources that cannot be controlled by the operator, which is called external conditions (Eisenack & Stecker, 2011).
12 Weakness: an action theory of adaptation focus on social (norms and values), it does not regard much on political and economic changing condition that influence the actors. Also, the theory did not consider that operator may not be existed due to complete ignorance of the impact of climate change and variability or the necessary means are not available while there is an operator. And finally, the weakness relies on that, the means may not sufficiently used although there is an operator to whom the necessary means are available (Eisenack & Stecker, 2011).
2.3.3 Policy Review
Tanzania has been experiencing a number of disasters and risk for years such as drought, floods, pest infestation, strong wind, earthquake, the decline in agriculture yield that result into a food shortage, heavy rain, the rise in temperature as a result of climate change and variability (Stige et al., 2006). The National Disaster
Management Policy of 2004 defines the crucial for a policy framework for disaster surveillance and management as a measure to reduce vulnerability (NAO, 2007a).
The policy addresses issues embracing the disaster management cycle, namely: prevention, mitigation, preparedness, response, and recovery. In 2012, Tanzania released a national climate strategy to address both adaptation and mitigation in line with country’s development vision of 2025 (Nachmany et al., 2015). These included strengthening early warning system for disaster, risk management and preparedness, cross-sectorial adaptation coordination and planning, enhance public awareness on climate, and to strengthen information management on climate change (URT, 2012).
This is to enable the community to acquire climate change information in a timely and effective use of it to make a proper decision upon the impact of climate change and variability (Nachmany et al., 2015). TMA is responsible for monitoring, analyzing and disseminating weather and climate change and its variability 13 information to the community, with the positive outlook response for the community in taking various strategies in overcoming the risk (URT, 2012). In following the national climate change strategy of 2012, the Ministries of Agriculture, Food
Security, and Co-operatives (MAFSC) developed specific agriculture sector response to climate change resilience plan published in 2014. These options included; accelerating the uptake of climate smart agriculture, strengthening knowledge to the actors and system target climate action, improving risk management, and improving agriculture land and water (URT, 2015).
The Tanzanian government reviwed agricultural policy in 2013 focused on transforming the sector to be efficient, competitive and profitable, which will contribute to the economic growth, and poverty reduction (URT, 2013). The
Government was committed to bringing green revolution in agriculture sector including; to help farmers to adapt on climate change through crop intensification, diversification, technological advancement, and involving in irrigation farming.
According to Nyasimi & Mungai (2015) effective adaptation which build resilience require climate information to be integrated in decision making. NAO (2007a) affirmed that climate change information provides insight on how the community can prepare themselves for upcoming risk by undertaking various means for adaptation including proper farming from the household level to the government level or collective action.
2.3.4 Climate Change Information: Availability, Accessibility, and Robustness
The ability and nature of the adaptation response depend on an individual’s, households, or communities for availability and access to information about climate risks and the appropriate responses (Roncoli, Ingram, & Kirshen 2002). Availability and access to climate information helps users to design the best adaptation and risk 14 management strategies which build resilience and improving livelihoods of the people (Nyasim & Mungai, 2015).
According to Vogel & O`Brien (2006) access to climate information and technologies for adaptation is therefore crucial to enable stakeholders to anticipate long-term risks and make the appropriate decision to increase resilience. Despite significant scientific gains in predicting the climate, often there is lack of climate information at the local level due to uncertainty in climate projections and seasonal forecasts (O’Brien, Eriksen, Sygna & Naess, 2006). Several studies have shown that there is a need to make climate information more accurate and accessible by the rural communities (Ziervogel, Bharwani & Downing, 2005; Hansen, Baethgen,
Osgood, Ceccato & Ngugi, 2007). It is also important for expertise on climate change and local communities to work collectively to monitor and assess the impacts exposed to climate change and come up with solutions for reducing/avoiding negative impacts (Valdivia et al., 2010).
Climate change information is an entry point within the context of climate change adaptation in various areas of concern, including flood control and management
(WMO, 2015). The effectiveness of climate change information must be considered in terms of how well they inform the community, and holistic adaptation responses to climate change as a usability of climate information (WMO, 2012).
2.4 Empirical Review
2.4.1 Climate Change and Rice Farming
Climate change and variability impact is a growing global pandemic, which affects farming as well as a threat the livelihood of the people in the world. Douglas et al.
15 (2008) found that climate change and variability is the main factor that threat rice production.
2.4.1.1 Climate Change and Rice Farming Experience World Wide
Climate change and its variability is one of the most development challenges that threaten most of Southeast Asia economy (Attavanich, 2013). Since a larger part of their economy relies on agriculture and natural resources (IPPC, 2007). Changes in climate is realized in Asia through the changes of precipitation patterns, temperature, high-intensity floods, landslides, erosion and increased sedimentation (Karn, 2007).
The countries which were most affected and will be more affected in Asia includes
Thailand, Cambodia, Indonesia, India, Malaysia, and Vietnam.
In Thailand, climate change is considered as a challenge and threat in the development of agriculture sector, especially rice production (Mark, 2011). Rice farming currently in Thailand rely on ample water supply and are more vulnerable to drought stress (Luedi, 2016). Example; during the period of 2010- 2011, the total area planted to rice decreased when flooding caused severe damages to agriculture
(Redfern, Azzu & Binamira, 2012). As the result of the drought in 2015-2016, the rice’s quantity has declined by 16 % from 19.8 million tons to 16.5 million, in which only 9 million set for export (Luedi, 2016). The export values of rice and products in the last quarter of 2011 was less than that of 2010. In 2010 – 2011 the value of rice production decreased from 21,486 to 13,328 million baht (AC, 2012). It is projected that rice yield will fall up to 50% in Thailand by 2100, assuming that there will be no adaptation and no technical improvement (Redfern, Azzu & Binamira, 2012).
In response to that, the government issued three immediate measures to fight with drought effect in rice yield: delaying major rice planting to August and September; 16 encouraging farmers to grow less water-intensive crops instead of rain-fed rice; and teaming up with the Bank of Agriculture to finance farmers who need to grow alternative crops (Thaiturapaisan, 2015).
In Turkey, the study conducted shows that drought resulted in the rice scarcity and the increase in rice prices. It was a country that exported rice to other Asian countries but rice exporters have partially limited their exports (Koc & Ceylan,
2013). The per capita as the result of rice production in Turkey was 6- 6.5 kg in
2005 and it was 5.3 kg in 2006, which implies the decline in 6.9% of rice production in 2006. The deficit of rice was 70 tons in 2007 and projected to increase according to the long-term trend analysis (Dönmez, 2007). The study conducted in Nepal shows that there is a non-linear relationship between maximum daily temperature and rice yields (Baidya, Shrestha & Sheikh, 2008). During the ripening phase, increases in maximum temperature contribute to the positive rice yield up to a critical threshold of 29.90C, but as the maximum temperature exceeds that threshold, rice yield declines. Karn (2014) found that precipitation has a negative effect on rice yield if rainfall increases in the nursery stage. For instance; the increase in temperature by 1.80C in 1975- 2006, with currently increases in temperature by
0.040C per year and the erratic precipitation caused insufficient yield and gradually the situation turned Nepal from a food export country to food import country. In dealing with the impacts resulted in a change of climate, various approaches were promoted and others which are used include: rice intensification, delay rice planting, alternative crops, cloud seeding, alternative wet and dry system, improving in farming technique, inputs (fertilizer, pesticide), and crop rotation (Pokhrel, 2013;
Karn, 2014).
17 2.4.1.2 Climate Change and Rice Farming in Sub-Saharan Africa (SSA)
The extreme temperature, frequent flooding and drought and increased salinity of water supply used for irrigation as a result of climate change and its variability are a threat to socio-economic activities in sub-Saharan Africa (Agom, Idiong, Ohen &
Oji, 2009). According to Ajetomobi, Abiodum & Hassan (2011) the impact of climate changes and variability on rice yield depend on time and duration of the year. For instance; increase in 1% of temperature in January reduced irrigated rice net revenue by 0.5% and dry land rice net revenue for more than 10%, while a higher temperature in April was beneficial. Krishnan, Swain, Bhaskar, Nayak &
Dash (2007) predicted that for every 1.8°C increase in temperature, the yield changes for -7.20% and - 6.66%, respectively. Irrigation is an effective adaptation measure suggested to reduce the harmful of climate change on rice farming in Nigeria
(CEEPA, 2013). A study conducted in Malawi, Mozambique and Ethiopia show that support from the government extension agents, NGOs, research agencies, and private sector on sharing of climate information and other technical aspects helped farmers to adopt science-based interventions (Fisher & Snapp, 2014). Among the adaptation means includes; changing farming practices, diversifying crop, altering cropping systems and technologies, crisis responses, and adopting off-farm interventions (Chipungu, Ambali, Kalenga, Mahungu & Mkumbira, 2012). In regard to the study conducted in Ghana and Liberia, poverty, poor availability and access to necessary farm inputs, poor access to credit, and inadequate climate information sharing limit the widespread of adaptation by farmers in farming (Nordhagen &
Pascua, 2013; Asfaw et al., 2014). Thornton, Van De Steeg & Herrero (2009) asserted that for the farmers to involve in adaptation effectively based on climate
18 change risk and impact in farming, it depends much on the institutional, political, economic and social environment to where they operate their activities.
2.4.1.3 Climate Change and Rice Farming in Tanzania
In Tanzania, rice is mostly dominated by smallholders under rain-fed conditions which account for 71% while 29% depend on irrigation (Ahmed et al., 2011).
Currently, after maize, rice is the second important food and commercial crop in
Tanzania which provide employment, income and food security (RLDC, 2009).
After Madagascar, Tanzania is the second largest producer of rice within Eastern,
Central and Southern Africa (Nasrin et al., 2015). It is mostly produced in Tabora,
Shinyanga, and Morogoro regions where the growing conditions are much favorable, while in Manyara, Singida and Dodoma it is grown in lowlands only
(RLDC, 2009; Mary & Majule, 2009). Most farmers grow a number of traditional varieties, which have a long maturity and long yield, which is currently affected by erratic rainfall pattern, drought, floods, and occurrence of pests which contribute to the yield decline (Mbilinyi, Tumbo & Rwehumbiza, 2011). As the result of climate change and variability, example; in 1998 the area harvested was 209 hectares with the yield of 1.08 (t/ha), 2004/5 the area harvested was 650 with the yield of 0.86
(t/ha), while in 2005/6 the area harvested was 688 and has the yield of 0.83(t/ha)
(RLDC, 2009). Further, In 2011/12 the area harvested was 1119.3 hectares with the yield of 0.02 (t/ha) while in 2015/16 the area harvested was 1000 and has the yield of 0.02 (t/ha) (FAO, 2014; USDA, 2017).
If a good practices are followed in rice farming, one hectare should be able to yield
1.8-6 tons per hectare (Mbilinyi et al., 2011). Samado (2008) observed that the decrease in yield is attributed by drought, weed infestation, pests and diseases and
19 low soil fertility. Ahmed et al. (2011) on his study in Tanzania asserted that with an increase in temperature by 10C, the yield of rice decline by 17 % in a growing season of six months. Likewise Mbilinyi et al. ( 2011) asserted that the run-off water in
Wami-Ruvu basin will decrease up to 10%, at the same time the yields of rice will decline by 10% in an increase of mean night-time temperature by 1oC.
In response to climate change, National Irrigation Master Plan and Kilimo Kwanza point out that irrigation is a means to increase agricultural yield, and income to the stakeholders for growth, and poverty reduction (URT, 2011). Mbilinyi et al. (2011) affirmed that there are 192 660 acres of rice which are under irrigation schemes but are farmed on plots which are very small and produce in a season of the year since it is the irrigation that is dependent on rain water. URT (2010) declared that the inefficiency in irrigation is due to lack of effective policy and a framework strategy for irrigation and increase in flooding. Also, there are other various means that have been proposed to be used in response to climate change impact on rice yield in
Tanzania. These include the use of improved seed in which Agriculture Research
Institute (ARI) and Agriculture Seed Agency are responsible for supplying improved rice seeds and agriculture technology improvement (URT, 2011).
2.5 Knowledge Gap
Studies have been done regarding climate change in agricultural sector, specifically on how it is affected by the impact of climate change and variability in different parts of the world. However, in Tanzania no studies that have been conducted focusing on utility of climate change and variability information on farming. In other words no studies addressed forms of climate change information to the local community and whether the information are integrated in farming decision or not.
20 2.6 Conceptual Framework
A conceptual framework is a set of coherent ideas or concepts organized in a manner that makes them easy to communicate to others (Flick, 2007) or can be defined as a narrative or graphical description of the relationship between study variables.
This conceptual framework assumes that climate change and its variability are independent variables which are composed by changes and variation in patterns
(rainfall pattern, temperature, humidity, and the wind). Changes in climate patterns lead to spatial and temporal rainfall variation, devastating drought, intensity floods, pests and diseases which all these affect the dependent variable which is rice farming.
The changes in climate patterns are received by local community (farmers) and other actors as an information via TMA. Thus, farmers with support of government policy, subsidies, and guidance support, integrate climate information into farming decisions. These include developing and implementing various options for reducing the impact of climate change and improving rice production (Figure 1). The conceptual framework assumes that without accurate and timely climatic information provision, accessible by users (local community, leaders) and taken into farming decision, there will be no success in rice production in the current pandemic effects of climate change.
21
Climate change and variability
Rainfall pattern Temperature Humidity Wind
-Involves in irrigation,
Climate change and Rice -Improved seed,- variability farming changing cropping information pattern and
-Rise in temperature cropping calendar, -Spatial and -pesticide use, temporal variation fertilizer, managing
of rainfall water for farming , -Crop -Devastating drought Government( diversification, Leaders, -flood control, -High intensity TMA, -soi management floods extension etc.
- Increase in wind officers) storm (cyclones wind) - Policy, plan, - shifting of rain strategies Adaptation seasons, etc. (Decision -Monitoring making Arena) and disseminatio Local n of community information, (person, researches, household,grou
NGOs p, farmers)
Source: Author, 2017 Figure 1: Conceptual Framework for the Study
22 CHAPTER THREE
RESEARCH METHODOLOGY
3.1 Introduction
Research methodology involves the systematic procedures by which the researcher starts from the initial identification of the problem to its final conclusions. It consists of procedures and techniques for conducting a study (Singh, 2006).
This chapter begins to describe the research design, followed by area of study, research approach, sample and sampling procedures, methods and instruments for data collection, data processing, analysis and presentation, data quality control and finally, ethical consideration.
3.2 Research Design
Burns and Grove (2003) define a research design as “a blueprint for conducting a study with maximum control over factors that may interfere with the validity of the findings”.
This study employed a cross-sectional research design because the researcher intended to give a rich description of the case in point with multiple sources of evidence (Saunders & Thornhill, 2004). The design helped to produce a broad understanding of the issues concerning utility of climate change and variability information for rice farming at a short period of time and minimal resources.
3.3 Area of the Study
This section (3.3) presents the location of the study area and the selection criterion, climate of the study area, soil and economic activities.
23 3.3.1 Study Area and the Selection Criterion
This study was conducted in Babati District in Manyara Region. The District was selected because it is one of the districts in Manyara Region which is highly affected by the impacts of climate change and variability. Among the impacts include an increase in extreme floods period, cyclic winds, occurrence of extreme drought which is said to be 50% and expected to increase, and erratic rainfall (Mngube,
1997; TMA, 2016). These lead to loss of properties, life, dwindling rice yield, conflict over resource and migration (Häckner, 2009). Three villages (Magugu,
Matufa, and Gichameda) in Magugu ward were selected among 7 villages found in
Magugu ward. The selection of these village was based on the fact that there is documentation which suggests the existing number of events as a result of climate variability including disasters like frequency occurrence of floods, frequent drought, rise in temperature and erratic rainfall in the area. Furthermore, the majority of people are involved in rice farming of which its production is affected much by climate variability impacts which in turn threaten the livelihood of the people
(Sangeda & Malole, 2014; TMA, 2016).
3.3.2 Location
Babati District is one of the six districts of Manyara Region. The District Council is located below the Equator, between Latitude 3o to 4o South and Longitude 35o to 36o of Greenwich East. The District is bordered to the north by Arusha Region, to the south-east by Simanjiro District, to the south by Dodoma Region, to the south-west by Hanang District and to the northwest by Mbulu District. The District is administratively divided into 4 divisions, 21wards and 96 villages, covering an area of 5609 km2, with a large proportion (640km2) covered by water bodies of Lake
Burunge, and Lake Manyara (Babati district profile).
24
Light brown color indicate study ward. Source: Adopted from Google
(http://.www.googlemap/tanzania/babatidistrict/wards/) modified by Author, June,
2017.
Figure 2: Topographical Map of Babati District Shows the study ward
25 3.3.3 Climate
The land surface is characterized by a number of undulating hills and mountains as a part of the East Africa Rift Valley Highlands. Babati District is divided by the Dabil-
Dareda escarpment of the rift valley, providing diverse climatic and agro-ecological conditions due to a wide altitude from 950m - 2450m above the sea level (URT,
2013). The average day temperature is 30°C and night 20°C. Manyara Region has bimodal rain periods and a climate with large natural variations, affected both by the
ITCZ and the CAB.The climate in Babati varies not only from year to year but also cyclically making is harder to see general trends in a shorter perspective (Häckner,
2009).
3.3.4 Soil and Economic Activities
Most of the soils are of volcanic origin and range from sand-loam to clay alluvial soils. In the lower flat lands, like around Lake Manyara, alkaline soils predominate.
About 90% of the population of Babati district live in the rural areas and depend on agriculture and livestock for their livelihood. They are mostly small-scale farmers or agro-pastoralists, practicing a semi-traditional farming system. Mixed crop- livestock, mostly maize based systems are widely found in the district that is intercropped with varying species, such as pigeon peas, beans, sunflowers, according to altitude and rainfall variability. In lowlands, paddy rice is cultivated
(URT, 2013).
3.4 Research Approach
There are three types of research approach, namely, ‘quantitative research, qualitative research and mixed research approach. On this study, the researcher employed both quantitative and qualitative research approach in data collection.
26 Qualitative research approach was employed when the researcher used face to face structured interview and focus group discussion for the collection of qualitative data from different respondents. While quantitative research approach was employed on the collection of data which were in form of quantitative in nature such as socio- demographic characteristics, statistical data from District Meteorologist (DM),
District Agriculture Extension Officer (DAEO), and Ward Agricultural Extension
Officer (WAEO).
3.5 Sample and Sampling Procedure
This section (3.5) presents the targeted population, sample design, sampling unit, sampling frame, unit of analysis, sample size, parameter of interest and sampling procedure.
3.5.1 Targeted Population
Burns and Grove (2003) describe population as all the elements that meet the criteria for inclusion in a study. The targeted population for this study was the rice farmers within the household in Magugu village, Mafuta village, and Gichameda village.
Households of farmers involved in rice farming were appropriate to provide information about the dynamics of rice production in relation to climate change and variability in the area. The study also included village executive officers, ward executive officer, ward extension officer, district agricultural officer, and a district meteorologist as interviewees.
3.5.2 Sample Design
A sample design is a definite plan for obtaining a sample from a given population. It is the technique or the procedure the researcher would use or adopt in selecting the sample (Kothari, 2004).The sample should be representative in the sense that each
27 sample unit will represent the characteristics of the known number of units in the population. This study included simple random and purposive sampling.
3.5.3 Sampling Unit
Sampling unit may be a geographical one such as state, district, village, etc or a construction unit such as a house, flat, etc (Kothari, 2004). It may be a construction unit such as house, flat and buildings. In this study, the households of rice farmers in
Magugu village, Matufa village and Gichameda village were the main units. The reason for selecting these villages was that they were much affected by the impacts of climate change. Also the majority of people were involved in rice farming, and finally, these villages have the highest number of the population compared to other villages.
3.5.4 Sampling Frame
The sampling frame is a complete list of all objects/ elements in the population from which your sample will be drawn. Thus a sampling frame is a complete list of every unit in the population(Adam & Kamuzora, 2008). In this study, the sampling frame was the list of all rice farmers in Magugu village, Matufa village and Gichameda village, and other selected stakeholders such as village and ward executive offices, extension officers and meteorologist officer.
3.5.5 Unit of Analysis
The unit of analysis is the major entity that is being analyzed in a study. In social science research, units of analysis typically include individuals (most common), groups, social organizations and social artifacts (Kothari, 2004). In this study, the unit of analysis was individual rice farmer within the household, VEOs, WEO,
WAEO, DAEO, District Meteorologist and individual member in a FGDs.
28 3.5.6 Sample Size
A sample size refers to the number of items to be selected from the universe to constitute a sample (Kothari, 2004). The record of village executive officer of
Magugu, Gichameda and Matufa village in March 2017, showed that there were
1480, 1000 and 650 rice farmers respectively. This made a total of 3130 rice farmers for the three villages.
The sample size for the rice farmer in a household was determined by using Yamane formula (1967); after obtaining the total number of rice farmers in each village mentioned from village executive officers. . Where:
N = total number of rice farmers from three villages villages (N= 3130); n = sample size; e = precision level (error detection) will be, e = 10%.
= 97 rice farmers. The researcher covered a sample size of 97 rice farmers from the households.
In addition, the study involved 7 key informants who were VEOs (one from each village), 1 WEO, 1WAEO, 1 DAEO, and 1 district meteorologists. Lastly, the study included 3 focus group discussions (one from each village), with 6 members each.
Therefore, the subjects in this study were 122, comprising of 97 rice farmers, 07 key informants and 18 member of FGDs. 97 rice farmers were specifically for obtaining data on objective one, three and four. And members of FGDs were for obtaining more data and views on objective three and four. Furthermore, key informants were used to compliment data as based on their experiences on the area.
29 3.5.6.1 Sample Size Distribution
The number of samples to be taken in each village will be determined by using Israel formula (2009) for proportional sampling, as indicated in equation , where: n - sample contribution/ proportion;
N - Sample size; p – rice farmers of a particular village;
P – total rice farmers from 3 villages.
Table 1: Sample Size Distribution
Village Name Total Number of Rice Numbers of Rice Farmers Farmers per Village Surveyed per Village Magugu 1480 46 Gichameda 1000 31 Matufa 650 20 Total 3130 97 Source: Field Data, March, 2017.
3.5.7 Time Frame
Most interventions research with limited time frames a maximum of seven months from prepare research proposal to the final report. This limitation is often determined by funding and availability of data which are not widely exposed. Thus, in this study the time frame was 9 months from proposal preparation up to the submission of the report.
3.5.8 Parameters of Interest
In determining the sample design, one must consider the question of the specific population parameters which are of interest. In this study, the population parameters comprised rice farmers which are directly or indirectly affected by the impacts of climate change and variability such as flood, drought and erratic rainfall which all 30 these had negative impacts on rice productivition. The respondent age was from 22 years old and above. In this age, the respondents were regarded are matured enough to provide a proper explanation about the topic, since this age is considered as a starting age of the working class in Tanzania (URT, 1977). The age criteria for respondent to be included in the study were determined by asking the respondent to state his or her age first before further interview process.
3.5.9 Sampling Procedure
Sampling may be defined as the selection of some part of an aggregate or totality on the basis of which a judgment or inference about the aggregate or totality is made
(Kothari, 2004). This study employed both probability and non-probability sampling methods. The reason behind is that a single method was not able to accomplish the achievement of the required data and type of respondents.
3.5.9.1 Probability Sampling Method
Probability sampling approaches are randomization or random selection. In probability sampling, people place or things are randomly selected (Kombo and
Tromp, 2006). Every rice farmer in a household had an equal chance to be selected to represent the population.
3.5.9.1.1 Simple Random Sampling
Simple random sampling means that every member of the sample is selected from the group of the population, in such a manner that the probability of being selected by all members of the study group of population is the same (Kothari, 2004). The simple random sampling in this study was used in the selection of rice farmers after obtaining the total number of rice farmers registered in villages’ book. The aim was
31 to ensure all rice farmers had an equal chance to be selected, so as to be free from bias and prejudice.
3.5.9.2 Non-probability Sampling Method
Non-probability is sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chance of being selected.
3.5.9.2.1 Purposive Sampling
Purposive sampling is deliberate selections of particular unit of the universe for constituting a sample (Kothari, 2004). Purposive sampling was applied by the researcher in the selection of key informants; VEOs, WEO, WAEO, DAEO, district meteorologist, and also in the selection of 6 member for group discussion in each village. The criteria for the selection of key informants included adequate knowledge concerning climate change and variability information in relation to farming activities based on their working experience within Babati district.
3.6 Methods and Instruments for Data Collection
This section (3.6) presents the types of data to collected, methods used and tools employed in each methods for data collection.
3.6.1 Types of Data
Data is a fact which enables us to make an appropriate decision (Adam &
Kamuzora, 2008). In research, we consider two types of data, namely, primary data and secondary data. And this study in particular collected both primary and secondary data.
32 3.6.1.1 Primary Data
According to Kothari (2004) primary data refers to information that is collected for the first time. In other words, this is the data which did not exist before. The primary data were collected from the local community whose rice farming was affected by the impact of climate change and variability. Further, data was collected from key informants ( village executive officers, ward executive officers, ward agricultural extension officer, district agricultural officer, and district meteorologist). The data collected from primary sources was for objective one, three and four.
For objective one, the data collected involved: forms of climate information
(delay/early rain season, little or high rainfall, increase in temperature, occurences of floods, and wind storm), means for accessing climate information (radio, television, interpersonal means), information on reducing impacts of climate change (practising irrigation, use of heat tolerant varieties, alternative crops).
In objective three, the data collected involved: best practices approaches (practising irrigation, changing cropping and cropping caallender, drought resistance rice varieties, measure to control flood, pest and diseases, soil management); reason for not using climatic information (inadequate quaidance support, inadequate information, poverty, inadequate climate education).
In objective four, the data collected involved: high cost of farm inputs, poor access to credit, inadequate climate education, fragmented technological support, poor availability of necessary farm inputs, and inadequate guidance on use of information.
33 The primary source is more useful as it gives the first-hand information and much more close to the actual fact or truth of a study.
3.6.1.2 Secondary Data
Secondary data were collected from different documents such as archives, books, internet sources, articles from different journals and research papers, maps, and others from District Meteorologist office (annual mean temperature and rainfall trend from 1995 to 2016), District and ward agriculture office (trends of rice yield in a district from 2000 to 2016). The secondary data helped to identify the methods, techniques, and procedures which were used by different subjects in dealing with climate change and variability in rice farming. It also helped to understand relevant methods, skills and in-depth approaches that are useful in the study.
3.6.2 Methods Used for Data Collection
The data collection involved different method according to the types of data. This study used interview and focuses group discussion method for the collection of primary data from different respondents. The use of interviews, and focus group discussion method provided room to acquire original data. For secondary data, the study reviewed various relevant documents.
3.6.2.1 Face to Face Structured Interviews
It is a method of collecting data which involves the presentation of oral-verbal stimuli and reply regarding oral-verbal responses (Kothari, 2004; Naoum, 2004).
This was used in this study to ensure that each interview were presented with exactly the same questions. Closed and open questions was used to guide the interview for
97 rice farmers and Seven key informants (See appendix I). This brought significance for the study as the answer obtained reliably aggregated and
34 comparisons was made between sample subgroups. The method used mostly to obtain the data on the climate information available to the local community for rice farming (objective one) and integration of climate information in farming decision
(objective three).
3.6.2.2 Focus Group Discussion
A focus group discussion involves a group of individuals selected and assembled by the researcher to discuss and comment on, from personal experience, the topic that is the subject of the research (Powell & Single, 1996). The checklist was used as a guide on the discussion (See appendix II). There were are 3 FGDs in the whole study comprising six participants from each village (1 FGD for each village). The age category, sex and their experience on rice farming in regarding to climate change and variability information were considered in selecting participant member for FGDs. The time per FGD was 1hour and 40 minutes, which is within the time recommended of 1 and 2 hours (Morgan, 1997). The choice of 6 members per group was enough for this study and it falls within the range (5 to 15 members) recommended per group (Gaizauskaite, 2012). The method was used mostly to obtain data on the challenges facing the community in use of climate change and variability information in rice farming (objective four).
3.6.2.3 Documentary Review
Literature review as a technique was also employed by reviewing different documents, specifically this was used to obtain the trends of climate patterns and rice production in Babati District (objective 2). The report/record concerned trends temperature, rainfall and rice production were reviewed. Furthermore other documents such as archives, internet sources and other published data were
35 reviewed. The objectives of the secondary data review were to enable the researcher to get a general understanding of research thematic area.
3.7 Data Processing, Analysis and Presentation
This section (3.7) presents analytical design and data processing, data analysis, causal analysis and last presents data presentation.
3.7.1 Analytical Design and Data Processing
This is the essential for a scientific study and for ensuring that we have all relevant data for making contemplated comparisons and analysis (Kothari, 2004). In this study data collected were processed before analysis to be conducted.
3.7.2 Data Analysis
Data were analysed both qualitatively and quantitatively. For the qualitative data, the qualitative analysis was employed based on the experiences of the individual participants. Also for quantitative data, descriptive and inferential statistics computed.
IBM Statistical Package for social science (SPSS) version 20.0 software and Excel was used for analysis of data.
Objective one: To examine the kind of climate change and variability information available to the community for rice cultivation.
Analysis: Multiple response analysis used to analyse which forms of climate information the community had, barriers in accessing information; percentage was used to determine the means mostly used by farmers in accessing information; chi-
36 square was used to determine whether there is an association between the age, education level and access to climate information.
Objective two: To identify the trends of rice production and climate patterns from
1995 to 2016 in the study area.
Analysis: Linear regression was used to determine the trends of annual maximum temperature, annual minimum temperature; trends of rainfall and trend of rice production. Furthermore, linear regression was used to determine the magnitude of influence of rainfall (independ variable) to rice production (dependent variable).
Consider the regression equation:
y = a + bx; where y-rice production in a year; x- rainfall in a year;
Objective three: To examine the integration of climate change and variability information in rice farming.
Analysis: Multiple response analysis was used to determine changes made
(approaches) regarding use of climate variability information, and reason for not using information; Binary logistic regression model was used to determine the effect of farmers characteristics on use of climate information in farming decision.
Let y –indicating use/not use climate information with 1and 0.
p- be the probability of y to be 1, p= p(y=1).
Let x1…………………………………x6 be predictor.
x1= Age of the respondent, x2- Household size, 37 x3- Income level of the respondent, x4-Education level of the respondent,
x5- Number of years farmer involved in farming, and x6- Sex of the respondent.
Let Bo……………….B6 be parameter values of maximum likelihood.
Logit(p)= logit(p/(p-1))= Bo + B1*x1 +B2*x2 +B3*x3………….+B6*x6. Then p= exp(Bo +B1*x1+……….+B6*x6)/(1+ exp(Bo +B1*x1+…………+B6*x6).
Objective Four: To investigate the challenges facing community in use of climate change and variability information in rice farming.
Analysis: Multiple response analysis was used in analyzing the chanllenges (high cost of farm inputs, poor access to credit, inadequate climate education, fragmented technology, and inadequate guidance on use of information) farmers faced.
3.7.2.1 Causal Analysis
Causal statements describe what is sometimes called a ‘cause and effect’ relationship. The cause is referred to as the ‘independent variable’ the variable that is affected is referred to as the ‘dependent variable’ (Walliman, 2011). The researcher conducted causal analysis to determine how the utility of climate information helped in undertaking the adaptation measure against the impact of climate variability on rice farming. Content analysis is a qualitative form of analysis that consists of an examination of what counted in the text of any form (articles, advertisements, news items, etc.) or other media such as pictures, television or radio programs or films, and live situations such as interviews, plays, concerts (Walliman,
2011). This study employed content analysis on secondary data which were collected.
38 3.7.3 Data Presentation
Different devices of presenting data were used. These include tables, graphs, and charts or combination of these where necessary.
3.8 Data Quality Control
This section (3.8) divided into two sub-sections. The first sub-section (3.8.1) presents reliability and the last sub-section (3.8.2) presents validity.
3.8.1 Reliability
The reliability refers to the consistency or dependability of a measurement technique. It is concerned with the consistency or stability of the score obtained from a measure or assessment over time and across setting or condition (Marczyk,
De-Matteo & Festinger, 2005). It refers to the extent to which data collection techniques or analysis procedures will yield consistent findings (Saunders, Lewis &
Thornhill, 2009). In order to ensure the reliability of data, data were collected from various respondents with the use of different data collection methods and tools to cross-check the veracity of the information.
3.8.2 Validity
The validity is the most critical criterion and indicates the degree to which an instrument measures what it is supposed to measure. In other words, validity is the extent to which differences found with a measuring instrument reflect true differences among those being tested (Kothari, 2004). It refers to the degree in which results obtained from analysis actually represent the phenomenon under the study. Its primary purpose is to increase the accuracy and usefulness of findings by eliminating or controlling as many confounding variables as possible, which allows for greater confidence in the findings of a given study (Marczyk et al., 2005). In
39 order to ensure validity, instruments for data collection such as questionnaires, and interview guide, were translated into Kiswahili and questions were clarified. Also, triangulation was made by comparing data collected through various methods and tools. A pilot study was conducted to standardize the instruments.
Questionnaire pretesting was conducted.The author and research assistant were involved in the pretesting exercise, in each village three respondents were picked randomly and informally (checking understanding and ability to answer the question, and estimate the average time to complete). Among of the adjustments made after pilot study included adding list of options on the barriers for accessing climate information, and adding question on information for soil management.
3.9 Ethical Consideration
Permissions to conduct the study were obtained from relevant authorities. These included the Dodoma University (UDOM) graduate studies, an endorsement from the District Officer of Babati district, and informed consent of participants in the study from the ward and village chairperson for the villages selected. Eligible subjects for the study were informed individually about the purpose of the study and voluntary request to participate. The study ensured that all collected information were confidential and nobody else except the investigator had access to it.
40 CHAPTER FOUR RESULTS AND DISCUSSION 4.0 Introduction
This chapter presents the research findings and discussions. The chapter is organized into five subsections in relation to the research objectives. Section one presents the demographic characteristics of respondents, section two presents the kind of climate change and variability information available to the community (objective one), section three presents the trend of rice production and climate patterns from 1995 to
2016 (objective two), section four presents the integration of climate change and variability information in rice farming (objective three) and section five presents the challenges the facing community in the use of climate change and variability information in rice farming (objective four).
4.1 Demographic Characteristics of Respondents
The socio-economic profile of the respondents examined were sex, age, marital status, education of the respondent, main activities of the respondents, and household size. The purpose of choosing these characteristics was to obtain different views regarding the utility of climate change and variability information on rice farming from different demographic groups.
4.1.1 Sex of Respondents
In this study, during the households’ survey, both males and females were involved.
Table 2 shows that 51.5% of the respondent were females while the rest were males.
The dominance of female to represent the households in this study was due to the fact that it was female who were mostly available and enthusiastic respondents during the study. This result concur with (Ellis, 2007; RLDC, 2009) studies, both of which showed that majority of Tanzanian farmers are women and constitute a
41 significant contribution of 60-80 % in food production, processing, and marketing of foodstuffs. Women play a major role in rice production in the country. They are involved in all aspects of rice value chains such as during planting, weeding, bird scaring, harvesting and trading. However, this results does not limit the aim of the study, because there was no gender aspect that needed special care/attention.
4.1.2 Age of the Respondents
The distribution of the respondents according to age was as presented in (Table 2).
The results shows many respondents (48.5%) were aged between 37 to 49 years while few respondents (2%) were in the age between 63 -76 years. These results show that the majority of the households’ who were engaged in rice farming were within the economic active working age group, and could take actions against the risk posed by climate change and variability by considering the climate change information which is disseminated to them. Mburu, Ogutu & Mulwa (2014) asserted that farmers are inefficiency in production as they become older (specifically from
65 years and above). But in this study most farmers were not older, thus this provides an insight for eliminating the fear of aging to be a crucial factor undermining rice production in the study area.
4.1.3 Education Level of Respondents
Education is the powerful tool in economic production. In this study, education was taken into consideration and the result shows that, the majority (71.1%) of the respondents attended primary school unlike (13.4%) who had informal education
(Table 2). These results implies that the majority of respondents in the area had basic formal education. These results relate to the work of Mwakaje (2013) and Mugula
42 (2013). Both affirmed that most of the respondents in rural areas have primary education and very little have secondary and above.
4.1.4 Respondents’ Occupation
The majority of the respondents in the study area (68%) were involved in rice farming only, while 4.1% were involved in rice farming and were civil servants
(Table 2). The results reveal that most of the respondents in this area depend mainly on rice farming. These results comply with Haggblade (2007) and Mugula (2013) who observed that most of the people in rural areas depend much on crop production while other activities such as business, livestock keeping were taken as adaptation strategies against adverse effect of climate change and variability. Likewise, the study conducted by Chipugu et al. (2012) in Malawi, showed that the majority of people in rural areas depend on farming activities, while off-farm interventions done by few farmers are adaptation strategies.
4.1. 5 Households Size
Information obtained from the field indicated that the majority (53.6%) of the households size ranged from 5-8 while (3.1%) were more than 8 members per household (Table 2). Chi-square test shows there is a significant (Peason Chi-square
= 49.1, df =3, p< 0.04) association between the households size and access to climate information, mainly contributed by information sharing within the household .This result relates to Ali & Erenstein (2016) who observed that household’s size has a positive inputs towards adaptation strategies if they fully participate in farming and collaborate.
43 4.1. 6 Respondents Income Level
The majority of the households (48.5 %) earn less than 2000 Tanzanian Shillings per day, while 10.3% earn more than 4000 Tanzanian Shillings per day (Table 2). This result provide an insight that most farmers in the area were very poor as they earn less than US$ 1.90 per day according to global poverty line.
Table 2: Distribution of Respondents by Social and Economic Characteristics
Variables Frequency Percentage (%) Sex Male 47 48.5 Female 50 51.5 Total 97 100 Age of respondents 24-36 33 34 37-49 47 48.5 50-62 15 15.5 63-76 2 2 Total 97 100 Education level Informal education 13 13.4 Primary 69 71.1 Secondary school 12 12.4 College 3 3.1 Total 97 100 Occupation of respondents Farmer 66 68 Both farming and business 15 15.5 Both farmer and livestock keeping 12 12.4 Farming and civil servant 4 4.1 Total 97 100
44 Households size 1-4 42 43.3 5-8 52 53.6 > 8 3 3.1 Total 97 100 Income of respondents < 2000 47 48.5 2000- 4000 40 41.2 >4000 10 10.3 Total 97 100 Source: Field Survey Data, March, 2017
4.1.7 Farmers’ Experience in Rice Farming The results obtained from the field indicated that many rice farmers (49.5%) had a duration between 5 to 10 years, followed by farmers (40.2%) with a duration of more than 10 years. However, there were few rice farmers (10.3%) with a duration of fewer than 5 years(Table 3). This implies that the respondents had been involved in rice farming for many years. In turn, this shows that farmers had enough experience on aspects related to climate change and rice farming in the area, and hence the respondents suited for this study.
Table 3: Farmers’ Experience in Rice Farming.
Categories of years Frequency Percent (%)
< 5 years 10 10.3 5-10 years 48 49.5 > 10 years 39 40.2 Total 97 100.0
Source: Field Survey Data, March, 2017.
45 4.2 Climate Change and Variability Information Available to the Community
This section (4.2) presents the findings of the first objective which aimed at examing the kind of climate change and variability information available to the community.
To obtain the data for objective the researcher employed structured interview.
The section (4.2) divided into eight (8) sub-sections. The first sub-section presents farmers awareness on climate change.The next sub-section presents the extent of drought and flood occurences. Then, followed with a sub-section that presents climate change and rice production, access to climate change and variability information, sources of farmers’ access to information, climate change and variability information accessed by rice farmers, barriers in accessing climate information, and the last sub-section presents information for reducing impact of climate change in rice farming.
4.2.1 Awareness on Climate Change
Awareness on climate change was measured by asking respondents to state if they were aware of climate change. The result show that the majority of the respondents
(84.5%) are aware of climate change and the rest were not aware of the climate change and variability (Figure 3). These results reveal that people (farmers) were already aware of the existence of climate changes in the area, and this might be due to the experiences on the observable impacts brought by climate change in the area that affected their livelihood. These results are related to the study conducted by
Mary & Majule (2009) who asserted that there is a high awareness among farmers in
Tanzania based on the impacts of climate and variability which causing crop failure and rising cost of production. Slegers (2008) on his study in central Tanzania
46 concluded that small scale farmers are aware of climate change through their experiences.
Figure 3: Awareness of Rice Farmers on Climate Change and Variability Source: Field Survey Data, March, 2017.
4.2.1.1 Farmer’s Education Level and Awareness on Climate Change
Information
The relationship between the level of education and awareness of climate information was tested by using Chi-square test. The result shows that there is a significant (Pearson Chi-square = 55.2, df =3, p< 0.001) relationship between farmer’s education level and awareness of climate change information. The results imply that farmers who attended formal education (such as primary education) are more aware of climate change information, good agricultural practices, and adaptation strategies compared with less educated farmers. This result relates to the study conducted by Mugula (2013) who observed that farmers’ education and skills were important factors in agriculture production activities; adaptation strategies
(options) against adverse effects of climate change. Similarly Benard & Dulle
(2014) observed that educated farmers can easily acquire/access climate variability
47 information from various sources, and can be able to develop options and implement it to reduce the adverse impacts.
4.2.1.2 Farmers’ Understanding of Climate Change
Our climate is changing. Thus, understanding that changes is of crucial importance for farming. In this study, farmer's understanding of climate change is shown in
(Table 4). The majority of the respondents in Magugu village understood climate change as due to increasing in drought period (89%), variation in rainfall patter
(84%) and shifting and variations in rainfall season (76%). Most of people in
Gichameda village understood climate change due to increase in drought period
(97%) followed by frequent floods (88%) and variation in rainfall pattern (76%).
The majority of farmers in Matufa village understood climate change mostly as due to frequent floods (98%), followed by increase in drought (97%), variations in rainfall patterns (97%), and shifting and variation in rain season (80%). This suggested that in the study area, the majority of people understood climate change mostly due to increase in drought, frequent floods, variation in rainfall patterns and shifting and changing in rain season. These answers relate to Karn (2007) who observed that people understand climate changes as they realized the changes of precipitation pattern, the rise in temperature, high intensity floods, erosion, landslides and increase in sedimentation which harms their livelihood.
48 Table 4: Farmers’ Understanding of Climate Change and Variability
Name of village (%) of cases Understand climatic Magugu Gichameda Matufa (n=46) (n=31) (n=20) Variation in rainfall pattern 84 76 97 Increase in drought period 89 97 97 Frequent floods 67 88 98 Rise in temperature 63 64 70 Increases in pest and diseases 43 48 72 Shifting and variation in rain season 68 64 80 Increase in wind storm 26 12 9.1 *Data were based on multiple responses. n –Sample.
Source: Field Data, March, 2017.
4.2.2 The Extent of Drought and Floods Occurrences
The majority of the respondents (75.6%) mentioned the occurrence of drought as was very high level particularly for the last five years. The area also was inflicted with the occurrence of floods in which 87.8% of the respondents pointed that there was frequent occurrence of floods (flash floods and river floods) particularly at
Gichameda village which mostly occurred when River Rugina and Kou overflowed, while in Magugu village and Matufa village it was a flash floods (Table 5). These results relate to a study conducted by Keyyu (2012) who concluded that intensity floods and high drought resulted into loss of crops, food shortage, and damage to properties in Kilosa, Babati, and Mbulu. Similarly a study by Sagenda & Malole
(2014) in Manyara Region showed that the area is inflicted with the occurrence of floods and increasing drought.
49 Table 5: The Extent of Drought and Floods Occurrences
Variables Frequency Percent(%)
Drought Occurrence Small 1 1.2 Moderate 1 1.2 High 18 22 Very high 62 75.6 Total 82 100 99 15 Total 97
Flood occurences Frequent occur 72 87.8 Rarely occur 10 12.2 Total 82 100 99 15 Total 97
99- Not required to answer the question (condition question).
Source: Field Data, March, 2017.
4.2.3 Climate Change and Rice Production
Climate changes and variability has an impact on rice production as the result in
Table 6 show, 97.6% of the respondents felt that climate change impacted rice production. More specifically, 96.3% felt that climate chage reduced the rice production. The results concur with a study conducted by Mbilinyi et al. (2011) on rice farming in Tanzania, who stated that climate changes contributed to the decline in rice yield. Other studies with similar conclusion include report of RLDC (2009) which asserted that climate change has the negative impact on rice yield in
Tanzania.
50 Table 6: Climate Change and Rice Production
Category label Frequency Percent(%) Climate change affected rice Yes 80 97.6 No 2 2.4 Total 82 100 99 15 Tatol 97 How affected Reduced yield 77 96.3 Fluctuate the yield 3 3.7 Total 80 100 99 17 Tatol 97
99- Not required to answer the question (condition question).
Source: Field Data, March, 2017.
4.2.4 Ways in Which Climate Change Reduce Rice Production
Changes in climate patterns brought significant adverse impacts in rice production.
The results in (Table 7) shows how climate change reduced the rice production in the area. Respondents in Magugu village mentioned the decrease in rainfall pattern
(99%), intensity floods (84%) and increase in drought (81%) as the factors that mostly reduced rice yied. In Gichameda village farmers mentioned frequent floods
(100%) as the crucial factor that reduced rice yield, followed by increase in drought
(95%), decrease in rainfall (91%) and pest and diseases (87%). The majoriy of farmers in Matufa village mentioned floods (100%), decrease in rainfall (100%), pests and diseases (81%) and increase in temperature (76%) as the factors that mostly reduced the yield. This indicated that decrease in rainfall pattern was the factor that mostly reduced rice yield in Magugu villages while intensity floods and
51 diseases were the factors that affected most Gichameda and Matufa villages. These results were complimented by the District Meteorological Officer (district, ward, and villages) and Agricultural Extension Officers, who pointed out that rice production in the areas was affected much by the decrease in rainfall, frequent floods, rise in temperature, increased pest and diseases.
The decrease in rainfall patterns was one of the crucial factor affecting rice yield mentioned by the majority of the respondents in the area. The deficit in water limit/prevent rice from reaching maturity and hence reducing the yield. As observed by Agriculture officer at Magugu in 2015; the area was affected hard by drought.
This is in line with Mbilinyi et al. (2011) who accounted that, currently rice production is affected by erratic rainfall pattern.
Rice farm affected by drought Rice farm which was not affected by drought
Source: Photo taken by Author During Data Collection, March, 2017.
Plate 1: The Rice Farm which was Affected and not Affected by Drought
52 High intensity of floods was one of the factors mentioned by the respondents who felt that it reduced the rice yield in the study area. The effect of floods on rice depends on its growth stage, and the duration of flooding, it also reduces the soil fertility and may result in higher level of plants diseases. In 2016 and on April up to early May 2017 in the study area, many rice farms, particulary in Magugu and
Gichameda village were swept away by floods as explained by Magugu Ward
Agricultural Extension Officer . The result relates to the study conducted by Redfern et al. (2012) who concluded that flood is one of the most important factor that limits rice production.
Increase in temperature is also one of the important factos mentioned by respondents that limit production. According to Keyyu (2012), the variation in both averages minimum and maximum temperature have effects on rice production. Rice yield is affected much by an increase in daily minimum temperature or as night become hotter. Temperature effects are raised much by the deficit of water in the soil, while the effects of high temperature in rice production are not only seen on yield but also on grain quality as explained by the District Agricultural Extension Officer. This result relates with Karn (2014) who observed that the increase in temperature affect rice yield negatively, and Rowhani et al.(2011) who observed that increase in temperature in Tanzania will increasingly reduce rice yield up to 2050.
53 Table 7: Climate Change Ways that Reduce Rice Yield
Name of village (%) of cases Ways reduced rice yield* Magugu Gichameda Matufa
(n=46) (n=31) (n=20) Increase in temperature 59 37 76 Decrease in rainfall 99 91 100 High intensity floods 84 100 100 Increase in drought 81 95 75 Increased sedimentation 34 50 27 Pest and diseases 72 87 81
*Data were based on multiple responses. n –Sample. Source: Field Data, March, 2017.
4.2.5 Access to Climate Change and Variability Information
In determining whether rice farmers in the area have access to climate change and variability information, the respondents were required to say if they had an access or not. Most of the respondents (95.1%) felt that they had access while the rest did not have access (Figure, 4). This result shows that farmers get information about climate change and variability. There is no shortage of climate change information in the current world, however, information is useless unless it can be accessed, understood and actioned (Murgor, 2013). Access to climate information by farmers is not enough, it needs to be translated into a format that farmers can understand and act on it. Weather patterns currently are more erratic and climate change has become visible in the unpredictability of the data (Cherotich, Saidu & Bebe, 2012). After disseminating climate information to the community, it is of important to monitor whether are taken into action or not. Famers may have access to climate information but not at timely, accurate, and reliable, which may prove significant obstacles for farmers and other decision makers. Manjula & Rengalakshmi (2015) asserted that
54 delivery of climate information need to be measured as to what extent this information feed into local and regional level. This is because access only does not guarantee they are useful to the user rather it is one of the crucial aspects. Murgor
(2013) asserted that climate information is not downscaled and repackaged in formats that user (farmers) may access at a timely when required, understand and use though may access.
Source: Field Data, March, 2017.
Figure 4: Access to Climate Change and Variability Information
4.2.5.1 Sources of Farmers’ Access to Climate Change and Variability
Information
For the respondents who felt that they had access to climate change and variability information, the majority of them (62.8%) mentioned that they accessed information through radios, 25.6% through television, while the rest accessed information from
Agricultural extension officer, VEOs, and WEO (Figure 5). The results of the respondents concur with the DM who asserted that “ they provide the climate change and variability information through Radio, Television, Magazine/
55 Newspaper, and Farm SMS /phone text mostly”. Furthermore, the DM provides information through informing the DAS, and RAS to inform the community on the climate front. The result implies that most rice farmers receive information on climate change through mass media and not relied on interpersonal sources such as friends, village executive officers, agricultural extension officer, and neighbors. This result relate with the report written by CGIAR & CCAFS (2017) which accounted that climate information services in Tanzania and Malawi are provided mostly by and accessed more through Radio. However, Rogers (2003) observed that interpersonal channel particularly in developing countries like in Tanzania persuade an individual to change his/her attitude and adopt an innovation. Cherotich et al.
(2012) affirmed that user preferred interpersonal channel as they could need/seek clarification, feedback or secure more information about the changes, which was different from using the mass media.
Clearly relying to access information through mass media and less through interpersonal channel may be problematic since people may not believe it, or may require clarification which may not get through mass media. For example one respondent from Magugu village said that “it is true that I access information through mass media, but the problem of information from mass media is too general, not specific to our area, which makes us do not take much consideration”. Thus, accessing climate change information through interpersonal sources is important as it provides the matter to be discussed in villages meeting to be understood.
According to Mason, Kruczkiewicz, Ceccato & Crawford (2015), effective provision of climate and variability information includes varieties of approaches such as posting advisories in public places, announcements over loudspeakers, enlisting NGOs, and extension services to help communities’ clearly understanding 56 information. However, the District Meteorologist asserted that inadequate transport facilities limit them to visit various villages’ meetings so that they tell the community on the issues regarding climate change and variability and the means forward to facilitate the interpersonal information and also to make the community to believe more on information.
Source: Field Data, March, 2017.
Figure 5: Sources of Farmers’ Access to Climate Variability Information
4.2.6 Climate Change and Variability Information Accessed by Rice Farmers
Accessing climate information helps to build adaptive capacity (Cherotich et al.,
2012). In this study, climate change and variability information accessed by farmers was well considered and it is summarized in Table 8. The results show that the majority (100%) of the respondents in all villages were accessing information regarding the presence of little (low) or high rainfall, (56-70%) access information based on occurrences of floods, (54-69%) increase (rise) in temperature, (40-53%) mentioned information regarding the earlying/delaying of rain season in a particular year, and 2-18% of the respondents received information regarding increase in wind 57 storm. The results in this study relate to CGIAR & CCAFS (2017) findings that farmers receive information on the basis delayed rainfall season, increased or decreased rainfall pattern and other warning information such as the occurrences of floods. Accessing such information on climate change and variability help farmers to be aware on the coming seasons (Wilkinson et al., 2015). Climate change and variability have distorted timing of seasons that farmers traditionally were familiar with. Current adaptation need information on climate change and variability on a spatial scale that is meaningful for planning and decision making. Information such as when the rainfall season start, the extent of a rainfall in a particular year, temperature, the occurrences of major storms (such as floods and drought) are tools in the decision for farmers to decide on what to do (WMO, 2016).
Table 8: Climate Change and Variability Information Accessed by Rice Farmers Name of village (%) of cases Forms of information* Magugu(n=46) Gichameda(n=31) Matufa(n=20) Delay/Early rain 53 45 40 season Little (low) or high 100 100 100 rainfall Increase in 65 54 69 temperature Occurrences of floods 56 70 60 Increases in wind 18 12 2 storm *Data were based on multiple responses. n -Sample.
Source: Field Data, March, 2017.
58 4.2.7 Barriers for Accessing Climate Change and Variability Information
The respondents were also asked about the barriers they faced in accessing climate change and variability information. Their responses are indicated in (Table 9). The results show lack of information collection system/climate service provider at the village level, inadequate/absence of clear link between the rice farmers group, extension officers and meteorological agency, low awareness of climate information and the shortage of weather station were the barriers in accessing climate change and variability information by the respondents.
Lack/absence of information collection system/committee in the ward was one of the crucial barriers mentioned by the majority of the respondent in all villages (97%
Magugu, 95% Gichameda, and 87% Matufa) which limits timely access to information(Table 9). Famers and other members of the community may have access to various documentation including various research conducted and other documentation related to climate variability in the area and options to be taken so as to improve their productivity as explained by Magugu VEO.
The absence of a clear link between the farmer's group, extension officers, and DM was one of the main factors mentioned by (83-96%) of the respondent in all villages that limit access to climate information (Table 9). On the whole, extension officers are supposed to get climate information from the DM. However, according to the
Agriculture Extension officer in Gichameda, he was not even aware if there was a
DM in the area. If the Extension Officer does not get information from the DM it is difficult to inform the rice farmers what is expected regarding the climate variability.
Thus, this link gap limits interpersonal sharing of climate information. Clear communication between the farmers and climate services provider improve farmers’ access to climate information (Mason et al.,2015). 59 Low awareness and inadequate education about climate change was one of the factors that limit adequate access to climate information mentioned by the majority
(44%) of the respondents from Magugu, unlike 12-19% from Gichameda and
Matufa villages. According to Murgor (2013) access to climate information may be influenced by people’s level of education. Chi-square test was used to determine the access to climate information and level of education. The results show there is a significant association (Pearson Chi-square = 51.2, df =3, p< 0.03) between the level of education and access to climate information. This implies that people who are more knowledgeable access more information regarding climate change and variability rather that it is counterparts. This is complimented by one respondent who said: “I access climate variability information online through my phone via
Manyara-AccuWeather forecast”. This relates with Murgor (2013) who asserted that people may not have access to climate information because of low level of education, and policy restriction.
Shortage of weather station is also one of the factors mentioned by 35-41% of the respondents in Gichameda and Matufa villages but 22% of the respodents in
Magugu villages. These result concur with the DM who said that there was shortage(only one station) of weather stations in the district, leading to inadequacy in provision of information. Generally, these results relate to the finding of Benard,
Dulle & Ngalapa (2014) in Morogoro who observed that lack of information services such as shortage of weather station, are among of the challenges facing farmers in accessing climatic information needs.
60 Table 9: Barriers for Accessing Climate Change and Variability Information
Name of village (%) of cases Barriers Magugu Gichameda Matufa (n=46) (n=31) (n=20) Absence of clear link between the 83 96 87 farmer's group, extension officer and DM Lack/absence of information 98 95 87 collection system/committee in a ward Inadequate education on climate 44 19 12 information Shortage of weather station 22 41 35 *Data were based on multiple responses. n- Sample.
Source: Field Data, March, 2017.
4.2.8 Information for Reducing the Impacts of Climate Change in Rice
Farming
Before asking the rice farmers to identify which information they got to reduce the impacts of rainfall and temperature fluctuation in rice farming, they were first asked if at all they get such information. The study revealed that 93.5% of the respondents got/had access to information on how to reduce the impacts of climate change in rice farming. Specifically, information which farmers had access included how to grow alternatives crops (77-98%) of the respondents in all villages, how to grow less water-intensive rice varieties (68-88%), practising irrigation (67-80%), other information included timing rice planting, use of pesticide and fertilizer, rice intensification, and how to use drought tolerant rice varieties (Table 10). The results have thus shown that people acknowledged to have the information/means to reduce the impacts of climate change and variability in the area. According to Karn (2014) to reduce the impacts of climate change and variability in rice farming require 61 promotion of various actions such as rice intensification, alternative crops, delaying rice planting, improving farming techniques and others. However, Thaiturapaisan
(2015) observed that promoting means or providing information on how people can reduce the impacts of climate change is one side of the coin, and for local people to take information into action is another side of the coin.
Table 10: Information for Reducing the Impacts of Climate Change in Rice Farming Name of village (%) of cases Information* Magugu Gichameda Matufa (n=46) (n=31) (n=20) Timing rice planting 72 62 55 Involving in irrigation 67 83 80 Grow less water-intensive rice 76 68 88 Grow alternative crops 77 92 98 Rice intensification 47 37 40 Improving farming technique 52 29 55 Inputs (fertilizer, pesticide) 57 54 56 Heat tolerant rice varieties 10 8 2 *Data were based on multiple responses. n- Sample.
Source: Field Data, March, 2017.
4.3 The Trends of Climate Change Patterns and Rice Production in the Area
This section (4.3) is a response to the second research question which aimed at identifying the trends of climate patterns and rice production from 1995 to 2016 in
Babati Distict. To obtain the data for objective the researcher employed documentary review. Secondary data concerned the trends of climate change patterns (temperature and rainfall) and rice production were accessed from TMA and
District Agricultural Extension Office respectively.
62 The section (4.3) is divided into 4 sub-sections. The first one (4.3.1) presents the trends of temperature (maximum and minimum). The second one (4.3.2) presents the trends of rainfall. The next sub-section (4.3.3) presents the trends of rice production. And the last sub-section (4.3.4) presents the relationship between rainfall and rice production in the area.
4.3.1 Trends of Temperature (Maximum and Minimum)
Figure 6 and 7 shows the maximum and minimum annual mean temperature trend in the area from 1995-2016. Generally, over 20 years there has been a gradual (R2
=0.2) rise in temperature (maximum and minimum) in the area. These results for the rise in temperature concur with the DM who observed that there has been an increase in temperature in the area over a period of time in the district. These results about increase in temperature concur with a respondent in Magugu village who asserted that “some times it is hard to sleep in the night due to high temperature”. A study conducted by Rowhani et al. (2011) showed that in general, there is an increase in temperature in Tanzania and it is projected the seasonal temperature will increase by 2 0 C by 2050.
63
Figure 6: Annual Maximum Temperature From 1995-2016 Source: Tanzania Meteorological Agency, March, 2017.
Figure 7: Annual Minimum Temperature from 1995-2016 Source: Tanzania Meteorological Agency, March, 2017.
4.3.2 Trends of Rainfall in the Area from 1995-2016
Figure 8 shows the trends of annual rainfall (mm) for the period of 21 years (1995-
2016), during which there was great fluctuation of rainfall over the years. As a line of regression equation shows, the trend of rainfall is generally decreasing (y = - 64 3.654x + 733.32, R2= 0.007) in the area. This was supported by DM who observed that there was a decrease in rainfall in the area. The DM asserted that the season for lesser rains (mvua za Vuli) that normally start in September up to December now start in November. This view was also shared by (District Ward, Village Extension
Officers) who felt that there was the decrease in rainfall in the area. The results concur with Munishi (2009) who observed that there will be an increase in rainfall in some parts of the country while others will experience a decrease in rainfall.
Furthermore, these results relate to Kihupi, Tarimo & Dihenga (2007) observation that generally in Tanzania there is gradual decrease in the length of growing season, decreasing trend of a number of rainy days during the growing season, and a decrease in seasonal rainfall amount in the area that is mostly vulnerable. According to Keyyu (2012), decrease in rainfall and increase in temperature led to drought in
2008-2009 that caused loss of livestock and crops in Babati district. In general, according to the DM, the area is experiencing the decrease in rainfall over a time period, and the extent increased more from 2007.
Figure 8: Annual Rainfall (mm) from 1995-2016 Source: Tanzania Meteorological Agency, March 2017.
65 4.3.3 Trends of Rice Production in Tones from 2000/1-2015/16
Information from (Figure 9) shows that from 2000/1 season there was a variability
(increase & decrease) in rice production in the area. The regression line indicates that there is a general decline in rice production over the time period. This result was complimented by agriculture extension officers, VEOs and WEO. According to the these key informants, increases in temperature and changes in rainfall characteristics have led to an increase in pests and diseases, decrease in the amount of rains, and in some cases led to floods with associated decline in soil fertility. Some respondents expressed that changes in climate in the area has led some farmers to stop engaging in rice production. The results concur with RLDC report (2009) which pointed out that there will be a great decline in rice production if no action is taken over the impacts of climate change and variability in Tanzania. Likewise, Hackner (2009) asserted that there was a decline in crops production as a result of climate change impacts in Babati district.
Figure 9:Trend of Rice Production (in tone) from 2000/1-2015/2016 Source: Babati District Agricultural Extension officer, March, 2017.
66 4.3.4 Relationship Between the Trends of Rice Production and Rainfall
Patterns
Rice production and climate patterns (such as rainfall pattern and temperature) are closely interlinked. In this study, the relationship between rainfall and rice production was taken into consideration. Linear regression was used to determine how the magnitude of rainfall has an influence in rice production in the area. The results shows that changes in rainfall pattern in the area influence the rice production positively or negatively by 51.7% (y = 3.391x + 2674.1, R2 = 0.517). The remaining
48.3% in rice production are influenced by other factors such as temperature, the nature of the soil, type of rice seed, and fertilizers (Figure 10). This result implies that changes in rainfall pattern (increase or decrease ) in the area has a significant
(positive or negative) impacts in rice production. For example, according to Babati
District agriculture extension officer, in 2006 when the rainfall was 1182.4mm, the total rice production for 1374 hectares grown in the area was 6799 tones, while in
2015 when the rains decreased up to 499.7mm, the rice production for 1374 hectares was 4122 tones. This indicates further that rainfall has a great influence in rice production in the area. These results are related to the study carried out by Eze and
Afolabi (2013), which showed that rice requires a moderate level of rainfall for maximum yield. Too much rainfall or too little rainfall would result in a reduction of yield. These results concur with the study conducted by Wilson & Webster (2005) who affirmed that the yield of rice is at best when water is evenly spread throughout the cycle of growth.
67 8000
7000
6000
5000 y = 3.391x + 2674.1 4000 R² = 0.5176
3000 Rice Production Rice Production Tone in 2000 200 400 600 800 1000 1200 1400
Rainfall(mm)
Figure 10: Relationship Between Rainfall Pattern and Rice Production Source: Babati District Agricultural Extension officer and DM, April, 2017.
4.4 The Integration of Climate Change and Variability Information in Rice
Farming
This section (4.4) presents the findings of the third objective which aimed at examining the integration of climate change and variability information in rice farming. To obtain the data for objective the researcher employed structured interview and focus group discussion.
The section is divided into 8 sub-sections. The first one presents the use of climate change information in decision about rice farming, followed with the section that presents farmers demographic characteristics and use of climate information, reasons for not using climate information in decision about rice farming, adaptation made in response to variation in rainfall, information of floods control, information on managing the soil, and last pest and diseases control.
68 4.4.1 Use of Climate Change Information in Decision about Rice Farming
In measuring the use of climate change information in the decision about rice
farming, respondents were asked to state whether they used climate change
information in the decision making or not. Results shows that, 74.4% of the
respondents were not considering the climate change and variability information in
their decision about farming, while only 25.4% of the respondents were using
climate change information in the decision about rice farming (Figure 11). This
result shows that most rice farmers do not take into consideration the information
regarding climate change and variability and these may be due to some constraints
that limit them. This result concur with VEOs, WEO and Magugu village
agricultural extension officer, who generally felt that inadequate support from
District Meteorologist, inadequate guidance support from extension, inadequate
transport facilities, and inadequate knowledge on climate issues were limiting the
wide use of climate information.
These results can be viewed from an action theory of adaptation to climate change perspective, which emphasises that adaptation rely upon the information about the vulnerability to climate change and variability. The effectiveness of the information depend on four specific channels.The theory points out that there are stimulus which is climate change information, exposure unit which is information provider, receptors which is leaders or extension officers, and operators which are rice farmers. For efficient and effective adapation, a strong link and collaboration is required among the actors. According to this study results, there is no clear link between exposure unit to receptors to operators and finally, no operators such that information are not taken into consideration in the area. Furthermore, the theory pointed out that adaptation is motivated by the impacts of climate change (floods
69 and drought) that people experience(Stecker et al., 2010). This is contrary to what occurs in the study area where by people who were affected by the climate change impacts were not widely involved in adaptation.
According to Majule, Rioux, Mpanda & Karttunen (2014), the Tanzanian government has put in place a number of strategies and action for strengthening awareness on the full impacts of climate change in agriculture, including; strengthening weather projection and early warning systems, providing specific adaptation and mitigation options depending on regional conditions. For ensuring that the community access reliable and timely climate information, the government was committed to increase a number of weather stations and meteorologist, to conduct training on the dissemination and use of weather information for preparedness of floods and drought, sensitization workshop for districts, wards and villages committees on information services (URT, 2013). According to the study results, these policies are not in action in the area (See Section 4.2.6). Arenas (2016) asserted that the government should put more attention on their actions and strategies for early warming systems as most of it are still merely paper exercise.
70
Figure 11: Use of Climate Change information in Rice Farming Decision Source: Field Data, March, 2017.
4.4.1.1 Farmers’ Characteristics and Use of Climate Information in Farming
Decision
A logistic regression was perfomed to ascertain the effect of age, sex, income , education level, number of years involved in farming, and household size on the use of climate information. The logistic regression model was statistically significant
(Chi-square =16.9; df = 13; p<0.04). The model showed 28.7% (Nagelkerke R2) of the varience in use of climate information and correctly classified 74.4% of cases.
Sex, age, household size, and number of years a farmer involved in farming, all showed no statistical significant association with the use of climate information.
Only the level of education (Wald statistics =19.1; p < 0.03) and income level of a farmer (Wald statistics =9.8; p < 0.05) significantly affected the probability of climate information use in farming decision (Table 11). The level of education is positively associated, meaning that the higher the education level the farmer attained, the more likely he or she used climate information. These results concur
71 with Uddin, Bokelmann & Entsminger (2014) observation that education to farmers play virtue role on farming decision.
Table 11: The Correlation Between Farmers’ Characteristics and Use of
Climate Change Information
Variables S.E. Wald p-value Sex of Farmer 0.657 0.1 0.94 Age of Farmer 1.05 2.6 0.45 Education Level of Farmer 0.02 19.1 0.02 Income Level of Farmer 0.09 9.8 0.04 Number of years Involving in 0.87 0.5 0.78 farming Household Size 0 .97 0 .3 0 .27
Source: Field Data, March, 2017.
4.4.1.2 Reasons for not Using Climate Change Information in Decision About
Rice Farming
Using climate change and variability information in a decision making framework help to avoid poor adaptation. This study has shown as to why most rice farmers are not using climate change and variability information in their farming decision.
Results show that most of farmers in the area were not using climate information in farming decisions due to lack of guidance support (84-96%) of the respondents in all villages, inadequate climate information (71-93%), lack of clear communication between rice farmers and extension officer and government such as DM (45-55% ), inadequate/lack of climate change education (39-47%), while other reasons included usual practices of traditional way of farming, disbelieving information, inaccuracy of information, and also delayed of information (Table 12). These were the factors that limit the rice farmers in using climate change information in their farming
72 decision. In a FGDs at Magugu village members felt that “ we need information and we like to use, but mostly we fail as due to inadequence guidance support, inadequate link between the farmers and extension officer, inadequate information on climate change and lack of education about climate change ”. Supporting this,
Magugu ward extension officer asserted that “ we are few in number in relation to the population we are supposed to provide extension services and we lack transport facilities. Furthermore, there is low awareness on climate change issues among extension officers”. According to Thornton et al.(2009), farmers’ to effectiveness in adaptation to climate change and variability depend much on institutional support/guidance.
In 2013, the government reviewed the agricultural policies to bring green revolution in agriculture sector to provide remedies to the impacts of climate change and variability (URT, 2013). These policies provided policy directives and guidelines for addressing adaptation and mitigation measure for the sector (Majule et al., 2014).
Among the policy statements included that: the government in collaboration with others stakeholders shall strive to improve adaptation measures to climate change effects and deal with all the risks involved; coordination of sustainable environmental early warning and monitoring systems shall be strengthened; public awareness on sustainable environmental conservation and environmental friendly crop husbandry practices (sustainable agriculture) shall be promoted (URT, 2013).
Yet, this study has shown that these policies were not implemented Magugu ward.
According to Majule et al. (2014), there were a disconnection between the local government and central government on climate intevation and coordination which is among the challenges which limit the target of the strategies and policy.
73 Table 12: Reason for not Using Climate Change and Variability Information
Name of village (%) of cases
Reasons* Magugu Gichameda Matufa
(n=46) (n=31) (n=20) Usual practices of traditional way of 31 40 32 farming Inadequate of climate change education 43 47 39 Lack of guidance support 84 96 86 Disbelieving information 42 30 29 Absence of clear communication between 55 45 50 rice farmers, extension officer, and government Inadequate climate variability information 93 80 71 Inaccuracy of information 38 33 27 Delaying of information 13 15 18
*Data were based on multiple responses. n- Sample.
Source: Field Data, March, 2017.
4.4.1.3 Adaptation made in Response to Variation in Rainfall and Increase in
Temperature Information for Rice Farming
For those (25.6%) respondents who felt that they were using climate information in farming decision. Results show that the majority (77-96%) of them practice timing in rice planting, 61-81% grew less water intensive rice species, 53-64% are involved in irrigation, 50-60% practise crop rotation, 30-35% practice rice farming intensification, and 69-79% practising alternatives crops as mostly ways used for reduce the impacts of increasing temperature and drought in farming (Table 13).
The results from FGDs in Gichameda village complimented these results as the respondents asserted that, “ timing rice planting particularly during lesser rain (Vuli)
74 period from November to February help us to avoid the effects of floods that mostly occur during the heavy rain of Masika”.
Adaptation measures undertaken in this study are related to Chipungu et al. (2012) who observed that changing farming practices, diversifying crops, involving in irrigation, delaying in planting are some of the practices farmers do in response to climate impacts in rice farming. Likewise according to Thaiturapaisan (2015), delaying the major rice planting, growing alternative crops and practising irrigation help to reduce the impacts of climate change.
Channel of water for irrigation Source of the channel Plate 2: Channel of Water for Irrigation in Gichameda Village
Source: Photo taken by Authour During Field Data Collection, March, 2017.
According to Fisher & Snapp (2014), support from government extension agents,
NGOs, and agencies research is crucial to help farmers to adapt to climate change in rice farming. However, this support is not occurring in Magugu ward because of the 75 inadequate support farmers got. According to Magugu ward extension officer, most rice farmers were in need to be registered in irrigation schemes, but it was difficult as schemes were facing shortage of water and frequently affected with floods.
Table 13: Adaptation Made in Response to Variation in Rainfall and
Temperature Information
Name of village (%) of cases Adaptation means made* Magugu Gichameda Matufa (n=46) (n=31) (n=20) For variation in rainfall Involved in irrigation 53 50 64 Rice intensification 30 35 32 Grow less water-intensive rice 61 81 80 Crop rotation 51 50 60 Timing of rice planting 77 94 96 For Drought Use of heat tolerant rice varieties 23 2 4 Alternatives crops 69 75 79 Spraying drugs for hot or cold 62 75 84
*Data were based on multiple responses. n- Sample.
Source: Field Data, March, 2017.
4.4.2 Information on Floods Control
Concerning provision of information based on calamities such as floods and means to control or reduce the risk to the community, 54.8% of the respondents had information on how to control floods and 45.2% of the respondents had no information (Table 14). For the respondents who felt they had the information, they were asked if they practised floods control, and the results showed that 74.3% of the respondents were not practising flood control measures. This implies that in the area,
76 majority of farmers are not taking any action regarding the effects of floods both for rice crops and for the people safety.
Villages of Magugu, Matufa, and Gichameda are frequently inflicted by floods (both flash and river overflow) which mostly lead to destruction of people’s properties, rendering them homeless and destroyed rice plantation. In Magugu and Matufa village, flash floods resulted into the destruction of the environment around Magugu hill, while for the case of Gichameda, it caused the overflow of river Rugina and river Kou by destroying river banks. Gichameda village is surrounded by the two rivers, and even though floods have become greater barrier in rice farming over the years, most people in the area are not taking any action regarding floods control. In
FGD at Gichameda village, it was observed that other people are cultivating along the banks of the rivers specifically of river Kou although there are rules prohibiting this, requiring leaving at least 60 meters from the banks of the river. This led to the destruction of the riverbank and increased the frequency of floods in the area. The issue of flood control requires much effort and collaboration, as extension officer said rice farmers need support from the government to address these including the land use plan, construction of a bridge of rive Rugina to prevent water from spreading across the whole village. It is clear that the government (Regional, central level) has to put effort in assisting flood control in the area. However, local effort is crucial such that other strategies are to be organized at district or ward level as explained by most of the farmers in the area. This study has shown that this is practically not occurring in the area. Farmers were claiming that there was no clear communication and support from the government in addressing climate challenging issues (See Section 4.4.1.2).
77
River Kou River Rugina Plate 3: River Kou and Rugina which frequently overflow and water spread to the community residence
Source: Photo taken by Author During Field Data Collection, March, 2017.
According to the URT report (2007), Babati Town/District Council has the following activities; mainstreaming disaster management issues in the district/council, monitor the hazard risk and disaster threat and the coordination of vulnerable population within the district council, mobilize and coordinate all interventions from other agencies, identify training needs and conduct training and public awareness, mobilize needed financial and material resources for disaster management, establish response team and civil protection system for disaster. But some respondents expressed that no initiatives have been made specifically for floods control such stopping destruction of environment at Magugu hills, constructing dams for water collection, and drainage system.
78 Table 14: Information on Floods Control
Category label Frequency Percent (%)
Have information Yes 40 54.8 No 33 45.2 Total 73 100 Involving in floods control Yes 8 25.7 No 32 74.3 Total 40 100 Source: Field Data, March, 2017.
4.4.2.1 Methods for Floods Control
The respondents who practice flood control were asked on how they controlled floods. The results show that terraces were the most method used in flood control in all villages, that is, 98% of the respondents who practised flood control in Magugu village, 90% of the respondents in Gichameda village, and 85% of the respondents in Matufa village. Drainage system was found to be used to a lesser extent by farmers (Table 15). Observation in the field showed that terraces were the means that were mostly used by farmers to tackle flooding.They filled in sand into the bags and put in the places prone to floods. This is traditional ways of creating terraces for floods control. According to Magugu VEO, “farmers are using the traditional ways of floods control, but it seems that it does not help much because often floods swept away the terraces, and destroyed the rice”. Furthermore, drainage system was one of the ways used by farmers. However, during FGDs it was observed that drainage channels were few and were practised by few people only and thus they were inadequate to control flood in the village. This was not practised largerly in the area
79 due to the fact that it required financial cost in construction and people in the area were so poor (See Section 4.1.6), but also this was asserted by the WEO.
Table 15: Means of Floods Control
Name of village (%) of cases
Means* Magugu(n=46) Gichameda(n=31) Matufa(n=20)
Creating terraces 98 90 85 Drainage 45 40 38
*Data were based on multiple responses. n- Sample.
Source: Field Data, March, 2017.
4.4. 3 Information on Soil Management
Information to the community on managing the soil is crucial in designing soil management strategies which are compatible in a particular location. Figure 12 shows that 80% of respondents in the study area did not have information on how they could manage the soil. Farmers are supposed to get information and advice on managing the soil from agricultural extension officers and other leaders in a community (Daniel, 2013). Magugu ward agricultural extension officer asserted that inadequate facilities such as transport facilities, and inadequate number of extension officers relative to the population were the constraints in providing information and advice to farmers. These results relates to Hamis & Mbogon (2014), who observed that soil managements in Tanzania has been poor due to inadequate link between researcher, extension officers and farmers, and lack of appropriate dissemination of approach for soil management. Wickama & Mowo’s (2001) work in Tanzania showed that if the majority of farmers are not engaged in soil management how can successful soil management occur? Steike & Snapp (2013) asserted that as climate variability increases, the risk factors associated with cropping and soil management 80 strategies become more prominent. According to FAO report of (2015), in order to meet the current challenges of global food security in current climate situation, soil management practices and agricultures must undergo a transformation. Yusuf,
Mustafa & Salleh (2017) in their work concluded that farmers who identified the decline in soil fertility as a problem, based on erosion or acidic rainfall, were not involved in soil conservation. Under the current climate change and variability information, farmers should be involved in soil management, if not, crop production will face more constraints and continue to decline as a results of variation in rainfall, decline in soil fertility due to floods and acidic rain (Steike & Snapp,
2013).
Figure 12: Information on Soil Management Source: Field Data, March, 2017.
4.4.3.1 Methods for Soil Management
Table 16 shows soil management methods used by 20% of the respondents who felt they got information on managing the soil. Results show that farmers in the area apply crop rotation, slash and burn technique, tillage system and mineral and organic 81 fertilizer, as a methods of soil management. Crop rotation was mostly mentioned by most of the respondents; 88% from Magugu village and 93% from Gichameda and
Matufa villages (Table 16). According to Wickama & Mowo (2001), farmers in
Tanzania use very little mineral fertilizers to improve their crops while the majority use crop rotation and other traditional methods. Likewise, Yusuf et al. (2017) observed that farmers combine crop planting pattern, application of organic and mineral fertilizers practices to manage the soil in their farms.
Most farmers explained that, inadequate information/advice on soil management led to inadequacy farming practice as most of them lack technical skills in employing various methods for soil management. Furthermore, farmers’ leaders in JAICA schemes at Gichameda village asserted that, “we need more information and education based on soil management so as to improve our soil fertility and production”. As the area is inflicted with frequent floods which contribute to soil erosion and decline in soil fertility, soil management is of crucial importance.
Table 16: Methods for Soil Management
Name of village (%) of cases Methods* Magugu Gichameda Matufa (n=46) (n=31) (n=20) Slash and burn technique 44 53 27 Tillage system 55 33 10 Soil amendment (mineral & organic 78 81 33 fertilizer) Crop rotation 88 93 93
*Data were based on multiple responses. n- Sample.
Source: Field Data, March, 2017.
82 4.4. 4 Information on Reducing the Pests and Diseases on Rice Farming
Respondents were asked on whether they got information on how to combat pests and diseases on rice farming. Figure 13 shows that the majority (66.7%) of the respondents did not get/have information on how to reduce the pests and diseases in rice farming. This was due to un clear link between the extension officers and farmers, and lack of information collection sytems (See Section 4.2.6).
Pests and diseases are among the factors that affect rice production in the area. The information provided by farmers and extension officers in the area, reveals that currently there are various diseases that threaten rice production. According to
Magugu Ward Agriculture Extension officer, mostly these are rice yellow mottle virus (MYMV) famous in Kiswahili in the area as “manjano” and bacterial blight
(Xanthomonas oryzae). Sarie (2016) asserted that channeling climate information services to farmers and how to tackle various pests and diseases will enable farmers to plan and decide the better means for controlling pests and diseases.
Figure 13: Information on Reducing Pests and Diseases Source: Field Data, March, 2017. 83 4.4.4.1 Techniques used to Control Pests and Diseases on Rice Farming
Table 17 shows the techniques used by 33.3% of the respondents who felt they had information on reducing diseases. The use of pesticides was the technique mostly mentioned by most of the respondents in all villages; 94% in Magugu, 99% in
Gichameda and 100% in Matufa. Other techniques that were used to combat pests and diseases included; crop rotation, soil tillage, and resistant seeds varieties.
According to Muck (2015), the use of tolerant rice varieties and pesticides are important and more helpful techniques used by rice farmers to control pests and diseases. Likewise, according to NSW (2013) crop rotation is a best method to use while controlling pests and diseases. It has no any negative impacts to the soil and is mostly affordable to poor farmers. The combination of farming strategies, biological control agents, pesticide, and herbicide use is crucial in combating pests and diseases depending on how the information is communicated to the farmers.
Thus, tackling climate sensitive diseases effectively requires better information and tools (Sarie, 2016).
Table 17: Techniques Used to Control Pests and Diseases
Name of village (%) of cases Techniques* Magugu Gichameda Matufa (n=46) (n=31) (n=20) Use pesticide 94 99 100 Clean seeds and resistant varieties 6 2 1 Crop rotation 31 60 50 Soil tillage 12 40 25
*Data were based on multiple responses. n- Sample.
Source: Field Data, March, 2017.
84 4.5 Challenges Facing the Community in the Use of Climate Change and
Variability Information in Rice Farming
This section (4.5) presents the findings of the fourth objective which aimed at investigating the challenges facing the community in the use of climate change and variability information in rice farming. To obtain the data for objective the researcher employed FGDs and structured interview where by in addition respondents were supposed to provides their views on a topic. The section is divided into two subsections. The first one (4.5.1) presents the way climate change and variability information are communicated in the area and last one (4.5.2) presents difficulties facing farmers in the use of climate change and variability information.
4.5.1 The way Climate Change and Variability Information are communicated
Clear means of communicating climate change and variability information build resoluteness in the community. About 81% of the respondents mentioned that, there were no clear means which were used in sharing or communicating climate information in the area (Figure 14). District Meteorogist and extension officer asserted that lack of transport facilities limited them to participate in village meeting for sharing climate variability information. However, Magugu agriculture extension officer asserted that inadequate link between the District Meteorologist and extension officers limited them to share climate information with local community.
Accordingly climate change and variability information were not discussed seriously in village meeting, although the impacts of climate change on rice farming in the area was significant. Most people get information on climate variability in a general form (See Section 4.2.5.1). Some respondents expressed that they share climate information they get through mass media when they meet in Vijiwe (informal meetings) which actually not official. This led to different understanding and 85 awareness, other had information while other did not have; few (25%) integrated climate change information into farming while 74% did not (See Section 4.4.1).
According to Murgor (2013), it is important to have a common way of communicating the climate information in a locality as it provides common way of understanding and encouragement within a community on undergoing coping strategies. Clear means of communicating climate information and community discussion enable effective adaptation to the community (ALP, 2013). Village, ward, and other leaders are responsible for creating better means for communicating climate information locally.
Figure 14 The way Climate Change Information are communicated Source: Field Data, March 2017.
4.5.2 Difficulties facing Farmers in the Use of Climate Change Information
When respondents were asked on whether they faced difficulties in the use of climate change information in farming decision, 85.9% of the respondents responded “yes”. For those who felt, they were asked to name those difficulties. The results show high cost of farms inputs, poor access to credit, poverty, fragmented 86 technological support, and inadequate knowledge on climate change were the difficulties farmers faced in use of climate information. High cost of farm inputs was mentioned by the majority of the respondents in all villages (94% of Magugu, 100% of Gichameda and Matufa). These results are well summarized on table (Table 18).
The high cost of farms’ inputs as mentioned above was one of the difficulties facing farmers while integrating climate information into their decision about farming. It is of reality that when the cost of farms inputs are high, farmers fail to acquire the inputs such as seeds that tolerate the current condition, pesticides, and other inputs.
As the price of inputs become high, it leads to an increase in cost of production. The
National agriculture policy of 2013, highlighted that the government in collaboration with other actors will ensure that the cost of farms inputs relatively low to enable most farmers to transform the traditional way of farming into modern, yet they are still high. One respondent in Matufa village stated that “of course, my rice farm is affected by diseases but I can not afford the cost of pesticides which will cover the whole farm”. Thus, the high cost for farm inputs limits most farmers to move with the current situation. Asfaw et al. (2014) observed that poor availability and the high cost of necessary farm inputs limit the widespread adaptation to climate change.
Poor access to credit was also among the crucial issues mentioned by most of the respondents. In Gichameda (95%) and 100% in Matufa villages respondents felt that poor access to credit limited them to consider and apply climate change information they received (Table 18). According to Ndamani & Watanabe (2015), lack of access to credit facilities are constraints to adaptation to climate change.
Most smallholder farmers are economically poor, facing hardship to acquire farm inputs. Access to credit is among the means to build the capacity of adaptation.
87 According to Tumusiime & Matotay (2013), several iniatives have been put in place to facilitate farmers’ access to credit in Tanzania including establishement of
Tanzania Agriculture Development Bank, with several conditions including farmers to form a group to request credit (loans). During FGD at Gichameda farmers expressed that it is too difficult to access credit (loans) based on the conditions that are set. Asogwa, Abu & Ochoche (2014), reiterated that individual farmers may require for credits (loans), but conditions limit them. Facilitation for availability and accessibility to credit is facing several constraints including dynamism of policy and frequent changing in priorities.
Poverty is yet among the challenges mentioned by most (78%; 95% and 87% ) of the respondents in Magugu, Gichameda and Matufa villages respectively that limited the use of climate information (Table 18). While nations are focusing on reducing poverty specifically income poverty, poverty is the constraint again for adaptation including limiting farmers to transform the way of farming into the mechanized form of agriculture (Asfaw et al., 2014). The results in this study showed that the majority of farmers were very poor, mostly earn less than 2000 Tanzanian shillings per day, which is below the global poverty line earning per day (See Section 4.1.6).
According to WB (2017), more than 12 millions Tanzanians still live in extreme poverty as they earn less than US$0.60 per day. According to Benard & Dulle
(2014), income for farmers influence farm’s information accessibility and adaptation strategies. Thus, in the area as most farmers seem to be very poor, certainly limit accessibility to climate information and performing adaptation.There are various programs and strategies for poverty reduction in global and national level such as
Millennium Developments Goals (MDGs) and Poverty Reduction Strategies Papers
(PRSPs) respectively. In Tanzania, the establishment of PRSPs known as
MKUKUTA in 2000 aimed at reducing income poverty through applying various
88 approaches including pro poor intervention. According to the Ministry of Finance and Planning ( 2016), in spite of the benefits of MKUKUTA, it failed to reach the target of reducing absolute poverty by 8-10 percent for 2015. People were still so poor, particularly in rural communities. According to Thornton et al. (2009), poverty limits adaptation to climate change, therefore for the farmers to be involved effectively in considering climate change information as a tool to adapt to climate change, it will depend on institutional, political, economic and social environment where they operate.
Inadequate knowledge on climate change was one of the challenges mentioned by most of the respondents from Magugu (64%) and from Gichameda (52%) villages
(Table 18). This could be related to the low level of education in the community.
The majority of the respondents attained only primary school education and informal education (See Section 4.1.3). According to Nordhangen & Pascua (2013), inadequate climate education hampers adaptation.The results have shown that even the extension officers had little knowledge on adaptation to climate change.
Magugu village extension officers asserted that they require some workshops regarding climate change so that they become knowledgeable. Babati district agricultural extension officer expressed that lack/shortage of transport facilities such as car has made it hard for them to participate in various village meetings to provide climate education to farmers. Likewise Babati District Meteorologist observed that shortage of staff team in combination with the absence of transport facilities limited the provision of education and information to the local community.
89 Moreover, fragmented technological support was also one of the challenges facing the farmers as it was felt by 35% of the respondents in Gichameda and Matufa, and
23% of the respondents in Magugu village (Table 18). According to MAFSC (
2012), various approaches have been put in place to improve agriculture through the use of morden technology. Among the initiatives we had included; Arusha declaration, food is life (Chakula ni uhai), politics is agriculture (the Iringa declaration of siasa ni kilimo), and the lastest “agriculture first” (Kilimo kwanza).
All these initiatives with different approaches aimed to improve agriculture. For example, for the initiatives of kilimo kwanza, among its focus on implementation was based on science, technology, and human resources. Farmers were encouraged to use modern technologies, and use of machines such as tractors. And in implementing this, many farm inputs/machines’ costs were reduced in favour of farmers. But most of these initiatives were incoherent and short term, thus could not be sustained. According to Nordhagen & Pascua (2013), fragmented technological support, poor availability and access to necessary farm inputs limit the widespread of adaptation to farmers.
Table 18: Difficulties facing Farmers in use of Climate Change Information
Name of village (%) of cases Difficulties* Magugu Gichameda Matufa (n=46) (n=31) (n=20) Poverty 78 95 87 Fragmented technological support 23 35 35 Poor access to credit 78 95 100 High cost of farm inputs 94 100 100 Lack/inadequate climate change education 64 52 28 *Data were based on multiple responses. n- Sample.
Source: Field Data, 2017.
90 CHAPTER FIVE
SUMMARY, CONCLUSION, AND RECOMMENDATIONS
5.1 Introduction
This chapter begins with a summary of the findings of the study based on specific objectives. It is then followed by the conclusion and recommendations for improving the utility of climate change and variability information in farming so as to reduce the burden of climate change impacts. Finally, the suggestions for further studies are stipulated.
5.2 Summary of the Findings
The study focused on assessing the utility of climate change and variability information for rice farming in Babati District. Specifically, the study examined the kind of climate change and variability information available to the community for rice cultivation, the trends of rice production and climate patterns from 1995 to
2016, integration of climate change and variability information in rice farming, and the challenges facing the community in the use of climate change and variability information in rice farming.
Considering the information presented in chapter four, first of all this study found that rice farmers in the area were aware of climate change and variability. The majority of rice farmers in all villages had knowledge of climate change due to an increase in drought period, variation in rainfall pattern, frequent floods, and shifting and variation in rain season. It has been found that in the area of study, climate change and variability affected rice production negatively (96.3%), and this was mostly due to shortage of rainfall, high intensity floods, drought, pest, and diseases, and increase in temperature.
91 Variation in rainfall patterns, occurences of floods, delaying in rain season, were the most forms of climate variability information accessed by farmers(refer table 8).
88.4% of farmers accessed these information through mass medias. Also, it has been found that the barriers for adequately and timely accessing of climate information include; absence of climate information collection system/committee in the area; inadequate link between farmers, leaders extension officers and DM; shortage of weather stations; and inadequate education about climate change. Other factors included inadequate common way of communicating climate information in the area(See Section 4.2.6).
Secondly, with regard to the second research objective, the findings have revealed that there was a gradual increase (R2=0.2) in temperature(minimum and maximum) from 1995 to 2016. Simultaneously, there was a gradual decrease in rainfall
(R2=0.007) and rice production (R2= 0.04).
Third, in respect to the third research question, the finding have depicted that the majority (74.4%) of rice farmers did not consider climate change and variability information in farming decisions. This was not for rice farmers only, even local government leaders including WEO, VEOs and extension officers in the ward. This was mainly contributed by lack of guidance support, inadequate climate information, and absence of clear communication between the farmers, extension officers and
DM. Other reasons included, disbeliving of information (See table 12). Furthermore, logistic regression results showed that education level (Wald statistics=19.1; p<0.03) and income level of farmers (Wald statistics=9.8; p<0.05) affected the use of climate information (Table 11).
About 25.4% of farmers who were using climate information in farming decision had made various adaptations for variation in rainfall and temperature information. 92 Most of the adaptation made included timing in rice planting, growing of less water intensive rice varieties, involving in irrigation, crop rotation, and alternative crops
(See Table 13). However, the result revealed that, 74.3% of farmers were not involving in floods control although floods were seen to be a great threat for their rice production (Table 14) . It was also found that 66-80% of the farmers in all villages had no information on soil management, water, and pests and diseases control. This was due to inadequate link between farmers’ groups and leaders
(extension officers).
Lastly, with regard to the fourth objective the findings have revealed that, farmers
(25.6%) who were using climate change and variability information for better adaptation were facing several challenges. These included high cost of farm inputs, poor access to credit, poverty, inadequate knowledge on climate change, and fragmented technological support (Table 18).
5.3 Conclusion
This study has shown that there is inadequate adaptation to climate change among rice farmers in the study area, mainly due to inadequate climate change information and institutional support. Integrating climate change and variability information in farming decision is crucial in all levels of decision making for effective climate change adaptation. Since decision can be made from the lower level (individual, community, local leaders) up to the high level (central government), each level has to perform its function efficiently and effectively for adaptation. Clear link and collaboration is required among actors/stakeholders for effective sharing of climate information and for the better adaptation.
93 5.4 Recommendations
Local authorities should create a clear link between farmers’ groups,
extension officers group, and DMA so as to enable and improve
interpersonal climate information provision, sharing, and advicing/guiding
farmers;
Local government in collaboration with local people in Magugu ward should
control floods through construction of good and well drainage system,
construction of dams which can accommodate flash floods so that collected
water can be used for economic activities during dry seasons; restricting
farmers to cultivate at the banks of the river Kou; land use plan; making
terraces along river Kou; and construction of bridge at river Rugina;
The government should improve the system of climate information
provision including installation of weather forecast stations in different
places in the district; such as in Magugu ward, increase the number of
Meteorologist staff in the district so that they can able to reach local
communities easily, connecting farmers leaders and extension officers with
FARM SMS information to facilitate quick access of information to farmers,
monitoring climate information how is accessed and used by farmers,
providing timely more accurate and specific area climate information;
The government should facilitate transport facilities such as car or
motorcycles for Meteorologist and agricultural extension officers so as to
enable them to meet with farmers and attend villages’ meetings. Also, should
increase the number of extension officers;
Local government leaders should establish climate information collection
system/committe in the ward which can enable farmers and other decision
94 makers in the area to have access to various climate information including
research document conducted in the area;
The government should encourage, put emphasis and facilitate the
integration of climate information in farming decision and other activities
impacted by climate change at different levels of decision making from the
farmers, community, villages and ward leaders, district leaders, regionals
leaders up to the central government level;
The government should ensure that matters concerning climate change and
variability are communicated well in the villages including to be discussed at
a village meeting;
Conducting training for local community/farmers and extension officers to
build more capacity regarding the climate change and utility of climate
information; and
The government should reduce conditions for the farmers to access credit,
reduce the cost of farm inputs, and increasing effort for poverty reduction,
specifically income poverty.
5.5 Areas for Further Studies
Effectiveness of climate change and variability information in conserving
natural resources such as forest, wildlife animals, and fish;
Climate change and diseases in rice farming;
The utility of Climate Change and variability information at Governmental
levels decision making.
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109 APPENDICES
Appendix I: Questionnaire for Households (for Rice Farmers)
ID………………….. My name is ARON JOSEPH a student pursing a Master’s degree at university of Dodoma (UDOM). The field work and dissertation is part of my course for the fulfilment of the award of Master Degree of Science in Natural Resources Management. You’re kindly requested to respond these questionnaires to accomplishing the topic of ‘THE UTILITY OF CLIMATE CHANGE AND VARIABILITY INFORMATION FOR RICE FARMING IN BABATI DISTRICT. The required information will be treated confidentially and only for academic purposes.
Identification Date:
1.Name of the (a)District……….(b)Division………(c)Ward…………(d)Village………(e) Hamlet… Instruction: Circle the correct response
Section A: General Information
2 Sex of Male 1 Female 2 respondent:
3 Age of respondent ………………….
4 Marital status
Married 1 Divorced 4 Single, 2 Other(specify) 5 Widowed 3
5 Which is the highest level of education have you attained? 1. Informal education [ ] 2. Primary [ ] 3.Secondary school [ ] 4. College 5. University level [ ] 6. Other(specify)......
110 6 What is your primary occupation (whatever you do to earn money) Farmer 1 Both farming and civil servant 4 Both farming and Livestock keeping 2 Other(specify) 5 Both farming and small business 3 6
7 Number of member per household (a) 1-4 (b) 5-8 (d) above 8 8 Number of children (age up 17 years old) ......
9 Number of Adults ......
10. How much do you earn/get per day on average ......
11. For how long have you been involved in rice farming? (1) Less than 5 years [ ] (2) 5- 10 years [ ] (3) More than 10 years [ ]
Section B:
12 Are you aware of climate change? (1) Yes [ ] (2) No [ ]
13. If yes, how do you understand it, multiple response allowed for this question
(1) Variation in rainfall pattern [ ] (2) Increase in drought period [ ] (3) Frequent floods [ ] (4) Increase in temperature [ ] (5) Increase in pest and diseases [ ] (6) Shifting and variation of rain season [ ] (7) increase in wind storm [ ] (8)Others (specify)…………………………………………
14. To what extent does the problem of drought occur in this area?
(a) Small [ ] (b) Moderate[ ] (c) High [ ] (d) Very High[ ] (e) Not known[ ]
15. To what extent does the floods disaster occur in this area?
(1) frequently occur [ ] (2) Rarely occur [ ] (3) Not occuring [ ]
16. Do you think climate change has affected rice productivity in your area? (1). Yes [ ] (2). No [ ]
17. If yes, how has it affected? (1) Reduced yield [ ] (2) increased yield [ ] (3) fluctuate the yield [ ]
111 18. If reduced yield, due to what? Multiple response allowed (1) increase in temperature [ ] (2) decrease in rainfall [ ] (3) high intensity floods [ ] (4 ) drought [ ] (5) increased sedimentation [ ] (6) pest and diseases [ ] (7) others(specify)......
19. Do you have access to climate change information ? (1). Yes [ ] (2). No [ ]
20. If yes, where do you easily access information? (1) From VEOs [ ] (2) From WEO [ ] (3) ward agricultural extension officer [ ] (4) Mass media [ ] (5) others (specify)………………………………………
21 What forms of information you had accessed? Mention (1)……………………………………………………………………… (2)……………………………………………………………………. (3)………………………………………………………………………. (4)…………………………………………………………………………..
22. Is the climate change information accessible at a timely when its required? (1) Yes [ ] (2) No
23. If no, what are the barriers in accessing climate change/variability information? Tick all which is appropriate
(1) Limited network [ ] (2) Lack of information collection system [ ] (3) Low awareness on climate information [ ] (4) Others (specify)………………….
24. Do you understand climate variability information when you get? (1) Yes [ ] (2) No [ 25. If yes, what enables you to understand easily? (1)Training [ ] (2) Guidance from leaders [ ] (3) Education I have [ ] (4) Other (specify)…………………………………………………….
26. If not, why? (1) Lack of education [ ] (2) Absence of guidance support [ ] (3) Absence of training [ ] (4) Others (specify)……………………..
112 27. Do you think the information are helpful in rice farming? (1) Yes [ ] (2) No [ ] 28. If yes, how? Multiple response allowed for this question (1) Enhance adaptive capacity [ ] (2) Better manage risk [ ] (3) Others (specify)……………………………… 29. If no, why? Multiple response allowed for this question (1) Un aware on use [ ] (2) Delaying of information [ ] (3) Inaccuracy of information [ ] (4) Others (specify) ………………………………. 30. Do you get extension services? (1) Yes [ ] (2) No [ ] 31. Are the extension services provided enable you to use climate information on farming? (1) Highly enable [ ] (2) it enable [ ] (3) Not enable [ ] (4) highly not enable [ ] 32. If not or highly not enable, why………………………………………………………….. 33. Do you get information on how to reduce the impact of rainfall and temperature fluctuation in rice farming? (1).Yes [ ] (2). No [ ].
34. If yes, what are those information. Multiple response allowed for this question
(1) Delaying rice planting [ ] 2) Involving in irrigation [ ]
(3) Grow less water-intensive rice [ ] (4) Grow alternative crops [ ]
(5) Rice intensification [ ] (6) Improving farming technique[ ]
(7) Inputs(fertilizer, pesticide) [ ] (8) heat tolerant rice varieties [ ]
(9)Others(specify)......
Section C: 35. Are you using climate change information in decision about rice farming? (1) Yes [ ] (2) No [ ]
113 36. If no, why……………………………………………………………………….. 37. If yes, what have you made in response to variation in rainfall information? Multiple response allowed (1) Involving in irrigation system [ ] (2) rice intensification [ ] (3) grow less water-intensive rice[ ] (4) altenative wet and dry system [ ] (5) crop rotation [ ] (6) Delaying in rice planting [ ] (7)others(specify)...... 38. What other adjustments have you made in response to the rise in temperature information? Multiple response allowed (1) use of heat –tolerant rice varieties [ ] (2)alternative crops[ ] ( 3) others(specify)...... 39. Do you get information on how to reduce pests and diseases on rice farming? (1) Yes [ ] (2) No [ ] 40. If yes, what have you made to control pests and diseases regarding to information ? Multiple response (1) use pesticides [ ] (2) clean seeds and resistant varieties [ ] (3) crop rotation [ ] (4) Soil tillage [ ] (5) others(specify)...... 41. Do you have information on how to control floods in your farm?
(1) Yes [ ] (2) No [ ]
42. If yes, do you involve in floods control?
(1) Yes [ ] (2) No [ ]
43. If yes, what do you do to control floods?
(1) Creating levees [ ] (2) Precision land levelling [ ] (3)use of flood tolerant rice [ ] 114 (4) Drainage [ ] (5) Precision grading of field [ ] (6) others(specify)......
44. Do you get information on managing the soil in your farm? 1. Yes [ ] 2. No [ ]. 45. If yes, how do you manage the soil regarding to the information you got? Multiple response (1) slash and burn technique [ ] (2) tillage system [ ] (3) use of organic residue[ ] (4)soil amendiment(mineral& organic fertilizer) [ ] (5) liming [ ] (6) others(specify) ...... 46. Do you get information on managing water for farming use?
(1)Yes [ ] (2) No [ ]
47. If yes, what kind of information is that? Multiple response allowed for this question. (1) Capturing and storing water [ ] (2) Irrigation scheduling [ ]. (3) Drip irrigation [ ]. (4) Level the field [ ] (5) Construct bunds [ ]. (6) Field channel to control water flow [ ] (7) Others (specify)…………….. … 48. What do you do in managing water for farm use regarding the information you received? …………………………………………………………………………………………
Section D:
49. Do you think you get adequate climate change information? (1) Yes [ ] (2) No [ ] 50. If yes, how...... 51 If no, why...... 52 How do climate change information are communicated in your area?
...... 115 53 Do you face any difficulties in the use of climate change information in rice farming? (1) Yes [ ] (2) No [ ] 54. If yes, what are those ? Multiple response allowed (1) Inadequate quidance support [ ] (2) Poverty [ ] (3) Fragmented technological support [ ] (4) Poor access to credit [ ] (5) Poor availability and accessibility of farm inputs [ ] (6) Dependency on free or subsidized inputs [ ] (7) Lack of education [ ] (8) Others(specify)...... 55. Do you get agricultural technological support to address climate information challenges in rice production? (1) Yes [ ] (2) No [ ]
56. If yes, what are those? (1) Power tillers [ ] (2) Threshers [ ] (3) Alternative wetting and drying (AWD) [ ] (4) Manure and straw management [ ] (5) Others(specify)……………………………………………………………..
57. Are the technological support helpful in adapting to climate variability? (1) Yes [ ] (2) No [ ] 58. If no, why……………………………………………………………………
116 Appendix II: Checklist for Focus group discussion 1. In what ways does climate change affect your area?
2. What are the climatic change information available in this area?
3. How do you get climate change and variability information?
4. What strategies have you made to reduce the effects of floods and drought in
rice farming?
5. What successes have you made in rice farming against the decrease in
rainfall and rise in temperature?
6. What are the major challenges that limit in the use of climate change
information in rice farming?
117 Appendix III: Checklist for Key informants (VEOs & WEO) 1 Do you face climate change and variability in your area?
2. Do you think this has affected your area?
3 In what ways has it affected rice production?
4. What kind of climate change information do you give to the community?
5. How has it been useful in improving rice production?
6. How climate change information are communicated in your area?
7. What do you do to help the commuity understand the climate variability information and use in their decision about farming?
8 How does the community overcoming the effects of drought, floods and rise in temperature for rice farming?
9 What are the major challenges that limit the community in using climate change information in their decision about farming?
118 Appendix IV: Checklist for Key informants (Ward & District Agricultural Extension Officer) 1 Do you face climate change in your area?
2. In which ways does climate change affect rice production in your area ?
3 What kind of climate change information do you give to the farmers?
4 How has it been useful in improving rice production?
5 What challenges do you face in provison of climate change information to farmers?
6 How do climate change information communicated in your area?
7 What challenges do you face in provision of extension services to the farmers?
8 What do you do to help farmers understand the climate variability information and use in their decision about farming?
9 What does the community do in overcoming the impacts of drought, floods and rise in temperature for rice production?
10 What challenges do the rice farmers get in using climate change/variability information in their decision about farming?
**** The trend/status of rice productivity from 1995 to 2016 in the study area
119 Appendix V: Checklist for Key informants (District Meteorologist Officer) 1 To what extent is the variability of temperature and rainfall in this disrict. Expalin
2 Is there any effect on rice productivity? Yes, No
3. If yes, in what forms are rice production affected?
4 Are the information about climate change provided to the community? Yes, No
5 If yes, in which means are the information provided to the community?
6 What kind of information are being provided to the community?
7 How do people use it?
8 What kind of challenges do you face in provision of information to the community?
9 What are the challenges that face the community in the use of climate variability information in their decision about farming?
10. Is there any plan to ensure that the community get accurate climate change and variability information timely ?
*** What are the trends of rainfall and temperature in Magugu ward and the overall disrict from 1995-2016
120 Appendix VI: Climate Patterns Data(Rainfall and Temperature) From 1985- 2016
Lat -4.216667 -3.366667 -3.366667 -3.36667 Long 35.75 36.633333 36.633333 36.6333 Stn ID 9435030 9336033 9336033 9336033 ARUSHA ARUSHA ARUSHA Stn Name BABATI AIRPORT AIRPORT AIRPORT Annual Annual Rainfall Rainfall Annual Minimum Annual Maximum Parameter Total (mm) Total (mm) Temperature (°C ) Temperature( °C ) 1985 730.7 779.5 14.1 25.3 1986 1089.4 1027.6 14.2 25.5 1987 1044.4 622.7 14.3 26.5 1988 1009.1 658.3 14.8 26.4 1989 1377.1 1007.6 14.5 25.3 1990 811.9 1106 14.6 25.3 1991 717.3 646.7 14.3 26.4 1992 474 776.5 14.1 25.6 1993 355.8 615.4 14.3 26 1994 730.7 730.7 14.7 27.2 1995 562.9 670.6 14.6 25.9 1996 581.7 663.8 14.4 25.8 1997 1093 1276.1 14.8 25.5 1998 897 897 14.8 25.4 1999 595.7 595.7 14.6 25.5 2000 960.4 530.8 14.5 26.3 2001 445.7 703.2 14.4 25.7 2002 1216.6 1009.7 15.1 25.6 2003 680 447.7 14.5 26.8 2004 473.3 473.3 15.1 26.2 2005 430 530.3 14.8 26.7 2006 1182.4 1323 14.9 25.5 2007 818.6 665.8 14.4 26.2 2008 803 765.5 14 25.8 2009 595.8 814.1 14.7 26.7 2010 871.7 792.6 15.1 25.9 2011 346.1 491.2 15.3 26.8 2012 542.4 758.7 15.1 26.3 2013 1037 657.4 14.6 25.8 2014 717.9 1188.5 15.3 25.8 2015 499.7 701.8 15.5 26.6 2016 750.6 603.9 15.3 26.6 Source: TMA. March 2017
121 Appendix VII: Babati District Rice Production in Tone From 2000/1-2015/16
HECTAR AVERAGE YIELD TOTAL YIELD IN YEAR GROWN T/H TONE
2000/1 800 3 2400 2001/2 950 4.1 3895 2002/3 950 3.9 3325 2003/4 1100 3.5 3080 2004/5 1374 3 5221.2 2005/6 1374 4.9 6799 2006/7 1935 4.9 6799 2007/8 1935 5 6870 2008/9 3121 5 6870 2009/10 2477 4 5496 2010/11 1890 3 5496 2011/12 3200 2.8 3847.2 2012/13 2069 4.2 5770.8 2013/14 170 4 5496 2014/15 1980 3 4122 2015/16 1980 2.8 3847.2 Source: Babati District Agricultural Extension Officer. March 2017
122 Appendix VIII: Babati District Rice Production in Tones for 1374 Hectare Grown as a Sample HECTAR AVERAGE TOTAL YIELD YEAR GROWN YIELD T/H IN TONE
2000/1 1374 3 4122 2001/2 1374 4.1 5633.4 2002/3 1374 3.9 5358.6 2003/4 1374 3.5 4809 2004/5 1374 3 4122 2005/6 1374 4.9 6799 2006/7 1374 4.9 6799 2007/8 1374 5 6870 2008/9 1374 5 6870 2009/10 1374 4 5496 2010/11 1374 3 4122 2011/12 1374 2.8 3847.2 2012/13 1374 4.2 5770.8 2013/14 1374 4 5496 2014/15 1374 3 4122 2015/16 1374 2.8 3847.2 Source: Babati District Agricultural Extension Officer, March, 2017.
123 Appendix IX: UDOM Permission Letter for Data Collection
124 Appendix X: Data Collection Permission Letter from Babati District Administrative Secretary
125 Appendix XI: Data Collection Permission Letter from Executive Director of the District
126 Appendix XII: Pay Slip for Climate Patterns Data
127 Appendix XIII: Comments From External Examiner
Examiner Observation What has been done
Proof read the document Done
Rearrange specific objective iii and iv
Under Section 2.4.1.3; present also the Presented current production
Under Section 3.7.2 data collection Shifted to data type issues from data analysis and shift it to its relevant section
Note that Content analysis is Not Changed to qualitative qualitative data analysis technique
Atherence to referencing principles done
128