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A Case Study of Bellona Community in Solomon Islands

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A Case Study of Bellona Community in Solomon Islands VULNERABILITY AND IMPACTS OF CLIMATE CHANGE ON FOOD CROPS IN RAISED ATOLL COMMUNITIES: A CASE STUDY OF BELLONA COMMUNITY IN SOLOMON ISLANDS. by Joseph Maeke A thesis submitted in fulfillment of the requirements for the Degree of Master of Science in Climate Change. Copyright © 2013 by Joseph Maeke Pacific Centre for Environment and Sustainable Development (PACE-SD) Faculty of Science, Technology and Environment The University of the South Pacific July, 2013 DECLARATION OF ORIGINALITY Statement by Author I, Joseph Maeke hereby declare that this thesis is the account of my own work and that, to the best of my knowledge; it contains no material previously published, or submitted for the award on any other degree or diploma at any tertiary institution, except where due acknowledgement or reference is made in the text. Signature: Date: 19th July 2013 Name: Joseph Maeke Student ID No: S01004381 Statement by Supervisor This research in this thesis is performed under my supervision and to my knowledge is the sole work of Mr. Joseph Maeke. Signature: Date: 19th July 2013 Name: Prof. Elisabeth Holland Designation: Principal Supervisor DEDICATION Dedicated to my best friend and wife, Samantha Annonna Maeke for the endless support from the initial stage of this thesis until its completion. Thank you ACKNOWLEDGEMENT This thesis would have not been possible without the scholarship and financial support of PACE-SD (Pacific Centre for Environment and Sustainable Development) through the AusAID Future Climate Leaders Project (FCLP) of which I am grateful. I am indebted to my initial principal supervisors Dr. Morgan Wairiu and Dr. Dan Orcherton who directed and advised me during the initial stage of the thesis until their departure from PACE-SD. I would also like to thank Prof. Elisabeth Holland who is willing take on the principal supervisor role and supported me in the completion and submission of this thesis. My sincere gratitude goes to my co-supervisor Mr. Viliamu Iese and advisor Dr. Upendra Singh who coached and trained me on DSSAT crop modelling simulation and analysis. For facilitating my DSSAT training abroad, administrative and logistical matters, I would like to thank Mr. Sumeet Naidu the coordinator of the FLCP for his support. I would also like to acknowledge the support rendered by various agencies in Honiara such as the Geology Division, Ministry of Mines for using their GeoChem lab, Statistic office-Ministry of Finance, Solomon Islands Visitors Beaureau, Solomon Island Meteorological Services and Climate Change Division-Ministry of Environment, Climate Change, Disaster Management and Meteorology. To Mr. Gareth Quity, thank you for your assistance and support in instructing me on DSSAT initially when I had no idea on what crop modelling is all about. My outmost gratitude to the people and community of Bellona who participated in the household survey interviews, focus group discussion and for allowing their garden plots to be observed. In particular, I would like to thank Mr. Wilson Tongabaea for his rich knowledge on Bellonese farming systems and my tour guides and interpreters: Baiabe Tuitupu, Eric Mamu, Ezekiel Tuhenua and Michael Saosogo. I would also like to thank the Renbel Provincial Secretary Mr. Adrian Tuhanuku for giving me permission on behalf of the Renbel Province to conduct this research in Bellona. I am also indebted to my committed research assistant, Mr Jeamond Gumizama for his invaluable assistance in getting the most out of my household survey and focus group interviews as well as field data collection. i ABSTRACT Climate change is a serious threat for Solomon Island communities’ food security. Therefore it is very important to understand the current vulnerability of Solomon Island communities’ food security to adverse impacts of climate change in order to develop important adaptation strategies to improve food security and reduce the impacts. This study examines the impacts of climate change and extreme events on food crop production in Bellonese communities in the Solomon Islands. Household interviews and surveys were conducted for 25% of households in four Bellona wards (West and East Ghonghau, Sa’aiho and Matangi) to collect and document information on food security systems and livelihood. The crop management information from the farmers were also used as inputs to calibrate and run the DSSAT (Decision Support System for Agrotechnology transfer) version 4.5 crop models to simulate the impacts of climate change (current, future) on taro (Colocasia esculenta), cassava (Manihot esculenta) and corn (Zea mays) growth and yield in three wards (West and East Ghonghau, Sa’aiho). Crop production impacts already observed in the four Bellonese wards included wilting, decline in crop yield, tuber/corm size, survival rate of young seedlings, crop growth, early or delay in maturity, abnormality of fruits/tubers, increase in pest and diseases, rotting, loss of some crop varieties, and loss of tuber flavor. Crop model projections for the three wards based on climate, atmospheric CO2, and soil type indicated that for Sa’aiho; C. esculenta yields are projected to decline by 12%, M. esculenta yields are projected to increase by 15.6%, and Z. mays yields are projected to decline by 13.2% for 2090. In both West and East Ghonghau, C. esculenta yields are projected to increase by 4.6% and 6.7% respectively, M. esculenta yields are projected to increase by 18.5%, and 24.1% respectively, and Z. mays are projected to decline by 8.3% for 2090. Based on crop model simulations of currently grown cultivars, C. esculenta cultivation will be restricted to the two fertile soil types, Kenge ungi and Kenge toaha found in West and East Ghonghau respectively. Z. mays yields are projected to decline. M. esculenta yields are projected to be the most resilient of the three crops, with sustained yields for all sites in all climate projections. The DSSAT crop model simulations also agreed with farmers reported impacts of El Niño induced drought of 1997. To improve food security in a changing climate in the studied sites, it is recommended for farmers to continue to implement their traditional ii sustainable cultivation and adaptation strategies which include; shifting cultivation, bush fallow practice, crop rotation, intercropping, diversification of crops, shade maintenance, mulching, planting fast yielding/resilient crops, adjust planting dates, increase number of plots, change planting sites, increase mound size, and planting distribution according to soil fertility and crop type. Furthermore, according to the crop models simulations farmers yield in Sa’aiho could be improved if they plant other C. esculenta cultivars; Bun long, Lehua, and Tausala-Samoa, with projected increased yields by 4.7-6.5 fold (3027-4209kg/ha) for 2090 and Z. mays cultivars; GL 482, PIO 3457 orig., WASH/GRAIN-1with projected increased yields by 3.9-4.4 fold (1040-1173kg/ha) for 2090. For West Ghonghau farmers yield could improve if they plant C. esculenta cultivars; Bun long, Lehua, and Tausala-Samoa, with projected increased yields by 2.3-3 fold (3574- 4972kg/ha) for 2090. Use of Z. mays cultivars, GL 482, PIO 3457 orig., WASH/GRAIN-1 with projected increased yields by 3.6-4.4 fold (962-1173kg/ha) for 2090. For East Ghonghau, farmers yield could improve if they plant C. esculenta cultivars, Bun long, Lehua, and Tausala-Samoa, with projected increased yields by 2-2.5 fold (3666-4681kg/ha) for 2090. Use of Z. mays cultivars, GL 482, PIO 3457 orig., WASH/GRAIN-1 with projected increased yields by 3.7-4.4 fold (965-1173kg/ha) for 2090. Overall, the study demonstrates the usefulness of crop modeling tools to assess the impacts of climate change on food crops in Bellona and to make actionable recommendations to increase food security and community resilience under a changing climate. iii TABLE OF CONTENTS Acknowledgement………...………………………………………………….. i Abstract……..………………………………………………………………… ii List of tables……...…………………………………………………………… x List of figures…………………………………………………………………. xii Chapter One: Introduction………………………………………………….. 1 1.1 Background…………………………………………………………... 1 1.2 Research problem context…………………………………………..... 3 1.3 Objectives of the research……………………………..…………….. 5 1.4 Research questions…………………………………………………... 6 1.5 Methodological approach……………………………………………. 7 1.6 Structure of thesis…………………………………………………… 8 Chapter Two: Literature review…………………………………………….. 9 2.1 Climate change at the global and national (Solomon Islands) level…. 9 2.1.1 Global perspective……………………………………………. 9 2.1.2 Solomon Islands perspective…………………………………. 10 2.2 Theoretical proponents and supporting knowledge of climate change and its impacts on agriculture and food crops……………… 15 2.3 Current knowledge on the impact of climate change on food crops. 16 2.3.1 Impact of increasing carbon dioxide concentration (CO2)……. 17 2.3.2 Impact of increasing temperature on crops…………………… 20 2.3.3 Impact of interactions between increasing temperature and carbon dioxide………………………………………………... 23 2.3.4 Impact of rainfall variation……………………………………. 24 2.4 Identified impacts of extreme events on food crops at both global and national level…………………………………………………….. 25 2.4.1 Definition of extreme event…………………………………… 25 2.4.2 Observations and evidence of extreme events globally………. 26 2.4.3 Observations, evidence and impacts of extreme events nationally for Solomon Islands………………………………. 27 2.5 Projection of future climate change and extreme events…………….. 31 2.5.1 Global climate change projections……………………………. 31 iv 2.5.2 Global extreme events projections……………………………. 32 2.5.3 Solomon Islands climate change projections…………………. 35 2.5.4 Solomon Islands extreme event projections…………………... 36 2.6 Use of crop models to simulate impacts of climate change on crops………………………………………………………………….. 38 2.6.1 Rationale for using DSSAT crop models…………………….. 38 2.6.2 History of the birth and use of DSSAT……………………….. 39 2.6.3 Description of DSSAT………………………………………... 40 2.6.4 Applications of DSSAT………………………………………. 43 2.6.5 DSSAT use and application globally…………………………. 43 2.6.6 DSSAT use and application in Pacific islands………………... 44 2.6.7 DSSAT limitation and uncertainties…………………………..
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