We are facing an ever-increasing environmental crisis on our planet, with multiple threats from humankind. Industrialisation, deforestation, overpopulation and exploitation of our natural resources is driving species to extinction and changing the environment we live in. We need to plan for the future in order to adapt or mitigate these risks. Recent advances in computing and analytical techniques, plus the rise of readily available spatial data, provide us with a means to understand the complex interactions between species, environmental change and human activity. Coffea arabica (Arabica coffee) is a critically important crop species in several tropical countries. Globally its export value is over $13 billion dollars per year. Wild populations of this species are of immense importance to the global coffee sector, due to the traits associated with the standing genetic diversity, such as disease resilience, new flavour profiles, and agronomically favourable morphological variation (root length; compact habit). In its countries of origin, Ethiopia and South Sudan, the wild species provides the planting stock for a multi-million-dollar export sector. Arabica coffee is well known across the globe, as the increasingly popular beverage coffee. The ubiquitous cultural nature of coffee drinking means that coffee acts as a flagship species for demonstrating science and the benefits of conservation and sustainable use, enabling the findings of this thesis to gain traction with a wider audience, who might otherwise not engage with research and social and environmental issues. Coffea arabica is greatly influenced by climate. The wild and cultivated variants of this species are restricted to a relatively narrow climate niche, within Ethiopia and anywhere where it is cultivated. Coffee production is considerably influenced by changes in rainfall, temperature or seasonality. Ethiopia has already experienced climate change; mean temperatures from the 1960s onwards show an average increase of 0.28 °C per decade, a shortening wet season, and an increase in the number of hot days. The continuation of this rapid change in climate will influence both wild populations and production of Arabica coffee in Ethiopia. Within this thesis I forecast the fate of wild and cultivated Arabica coffee in Ethiopia, under climate change, reviewing risks and opportunities from the recent past until the end of the century. To do this I developed several novel methods, which are initially used to project the future of wild and cultivated coffee cultivation in Ethiopia. For the wild species, I have developed several new spatial techniques, particularly dealing with the issue of the “modifiable areal unit problem” within species extinction risk assessments. I have updated and refined existing techniques into one package, allowing multiple future climate scenarios/projections to be processed and assessed quickly. I present my scientific findings in the form of five submitted manuscripts (see ‘List of original articles’, on p.8). Using the findings, results and recommendations from these papers, I repurpose the outputs and impact of the science, graphically and within various media (including two more manuscripts, media and social media), for multiple audiences. Using these spatial techniques and visualisations, I show the impact climate change will have on Arabica coffee in Ethiopia, both as a crop and as a wild species within the humid forests of the country. I show that the present coffee-growing areas could be reduced by up to 60% if no interventions are made, but conversely, that there is an opportunity to increase the coffee growing area of Ethiopia four-fold if the right actions are taken. For wild Arabica coffee I show that the species is threatened with extinction due to climate change. Specifically, I show that wild Arabica coffee would be assessed as Least Concern (under little or no risk; IUCN Extinction Red List) if climate change is not factored in, as opposed to Endangered (threatened with extinction) if climate change is included in an extinction risk assessment. The work in this thesis demonstrates the power of spatial analysis, modelling, and high data quality, for plant conservation.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:757520 |
| Date | January 2018 |
| Creators | Moat, Justin |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.nottingham.ac.uk/52174/ |
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