Date of Graduation

8-2016

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Environmental Dynamics (PhD)

Degree Level

Graduate

Department

Environmental Dynamics

Advisor/Mentor

Huang, Qiuqiong

Committee Member

Boss, Stephen K.

Second Committee Member

Matlock, Marty D.

Third Committee Member

Kovacs, Kent F.

Fourth Committee Member

Feng, Song

Keywords

Biological sciences; Health and environmental sciences; Earth sciences; Agrometeorological; Climate change; Drought; Indicators; Precipitation; Temperature

Abstract

Although climate change impacts vary geographically and temporally, studies at local levels are not readily available for stakeholders to better understand how their local communities would be affected and what remedial measures could be more effective in their local contexts. This dissertation has examined climate change and its impacts in two different local contexts: eastern Arkansas in the USA and Nyando in Kenya. The first part of this dissertation develops agro-meteorological indicators and examines the relationship between agro-meteorological indicators and crop yields in eastern Arkansas between 1960 and 2014. Results reveal that temperature based indicators were more strongly correlated to crop yield than precipitation based indicators. However, drought indices also performed very well. The second part projects future climate scenarios in eastern Arkansas using the agro-meteorological indicators developed in the first part. Results show slight increases in total precipitation, extreme precipitation and lengthening growing season duration. The last part identifies the socio-economic factors affecting the Agro-forestry (AFR) technology adoption in Kenya. Results reveal that farmers with more land, more income and/or more education are more likely to adopt agro-forestry technologies. Years of residence, access to information and reliance on crop income also positively affect the likelihood of using AFR technology. This study is very critical for Kenya where the national forest cover is less than 3%.

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