Dissertations and Theses @ UNI

Award Winner

Recipient of the 2020 Outstanding Master's Thesis Award - First Place.

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Availability

Open Access Thesis

Keywords

Iowa--Rural conditions; Winter storms--Economic aspects--Iowa;

Abstract

Driven by unusually warm air in the Arctic, severe winter weather moves southward to mid-latitude areas, indicating the complexity in the ways that climate change may affect local weather extremes. The vulnerability of farming communities to climate risks and differential response capabilities have drawn much research attention. Winter storms are recognized as one of the common catastrophic events leading to agricultural damage and loss. However, research is notably lacking in understanding the consequences extreme winter weather could bring in farmer livelihood.

This study is concerned with the vulnerability patterns of farming communities shaped under varying climate and socio-physical conditions. Focusing on Iowa as a case study, this research determined indicators capable of differentiating households with unequal vulnerability to winter storms based on semi-structured interviews. Spatial analysis was incorporated to quantify spatial information (i.e. winter temperature variation, natural shelter, energy capacity and facility density) subject to data aggregation. Factor analysis was used to investigate the relationships between adaptive capacity indicators. It extracted three underlying factors that could determine adaptive capacity, namely, farming economic status, environmental institutional capital and innovative capital. The exposure, sensitivity, adaptive capacity and overall vulnerability were calculated for each county in Iowa. The output maps demonstrated high vulnerability in Southeast Iowa due to low farming economic status and innovative capital, and high vulnerability in Northwest Iowa due to high exposure and low environmental institutional capital. The limitations in normalization and index development were also addressed and discussed.

To understand complex farmer decisions that lead to different outcomes in storm losses, a conceptual agent-based model was constructed in an attempt to examine geographically and temporally, the multiple reasons that drive the decisions and key pathways in the response-loss process. This study identified interacting entities and variables characterizing these entities under a simplified farmer decision-making process, with a view to decompose upscaled winter storm loss patterns. The future objective is to explore alternative policy scenarios that can improve farmer livelihoods and reduce vulnerability, thereby providing authorities with a compelling account for making betterinformed decisions about land resource management.

This study provides significant findings that may inform resource management for enhancing farming communities’ adaptive capacity to extreme winter weather. Increasing resilience of farming systems, especially pasture, to winter storms, includes investment in natural capital and enhancement of farming economic status. Further validation for the vulnerability pattern includes surveys investigating farmers’ perceived vulnerability. Future suggestions on vulnerability assessment are to use factor analysis to examine framework-based vulnerability indicator systems through empirical vulnerability case studies at various levels (e.g. tract as the unit). Methodologies could be advanced in exploring complex non-climate scenarios combining ground survey for physical and socio-economical information.

Year of Submission

2019

Year of Award

2020 Award

Degree Name

Master of Arts

Department

Department of Geography

First Advisor

Bingqing Liang, Chair

Date Original

12-2019

Object Description

1 PDF file (ix, 117 pages)

Language

en

File Format

application/pdf

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