Using geospatial analysis and qualitative research to advance knowledge on the social-ecological suitability of agroforestry

Castle, Sarah Elizabeth

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https://hdl.handle.net/2142/125518 Copy

Description

Title

Using geospatial analysis and qualitative research to advance knowledge on the social-ecological suitability of agroforestry

Author(s)

Castle, Sarah Elizabeth

Issue Date

2024-06-18

Director of Research (if dissertation) or Advisor (if thesis)

• Miller, Daniel C
• Wardropper, Chloe

Doctoral Committee Chair(s)

Brazee, Richard J

Committee Member(s)

Baylis, Kathy

Department of Study

Natural Res & Env Sci

Discipline

Natural Res & Env Sciences

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Agroforestry
• forestry
• social-ecological systems
• geospatial analysis
• multi-criteria decision analysis
• nature values
• conservation targeting
• land use
• Illinois

Abstract

Agroforestry, or the intentional integration of trees and woody shrubs on agricultural lands, is becoming more widely promoted in the United States (US). Agroforestry practices like windbreaks, riparian buffers, silvopasture, or alley cropping offer the potential to advance sustainability goals, but their adoption remains limited, especially in highly productive agricultural regions like the US Midwest. Current farming practices in these regions tend to have negative environmental impacts and are projected to be significantly affected by climate change. Realizing the full potential of agroforestry in such high-productivity regions requires knowledge of the opportunities and constraints facing greater uptake of locally appropriate agroforestry practices. However, such knowledge remains lacking, with current approaches failing to integrate biophysical with socioeconomic data at the state or regional scale. Further, the rapidly evolving availability of different remotely sensed tree cover datasets, an important input into suitability models and other sustainability analyses, poses a challenge to researchers interested in understanding forest and tree cover dynamics. This dissertation addresses these research gaps. I do so, first, by developing an agroforestry suitability map using a holistic approach based on geospatial analysis and modeling to identify potential priority areas for targeting agroforestry in Illinois. This suitability map shows regions where agroforestry is expected to reduce the risk of environmental degradation, support productive tree growth, and be socioeconomically viable. This framework for agroforestry suitability modeling was developed based on agroforestry literature and key informant interviews to identify model parameters and user needs. Results reveal considerable opportunities for expanding agroforestry practice within specific regions, where policies could be targeted. The suitability map can be used to inform agricultural conservation policy and decision-making related to agroforestry in specific locations. This work also provides a theoretical foundation for interdisciplinary suitability modeling that can be adapted for use in other global regions. Expanding agroforestry in highly productive regions like the US Midwest may help address numerous environmental and social challenges, but an array of social, economic, political, and technical barriers inhibits greater adoption. I focus on agroforestry practices within the state of Illinois as a case study to examine stakeholder views of an agroforestry landscape transition (increasing agroforestry up to 5-10% of land). Specifically, I analyze the roles of values in agroforestry adoption decisions to inform more sustainable and reflexive agroforestry planning and policy. I conducted semi-structured interviews with producers (18 agroforesters and 7 conventional farmers) and program administrators (13) throughout the northern, central, and southern regions of Illinois. I examined the perceived positive, negative, and neutral values of agroforestry on nature (intrinsic), ecosystem services (instrumental), and quality of life (relational). I then assessed how the nature values of participants influenced their adoption decisions and explored the perceived opportunities and barriers for expanding agroforestry in the region, including those related to financial risk and funding, management, equipment and plant material, market access, science knowledge and education, and climate change. Satellite-derived global forest cover and forest cover change data are available at increasingly high resolutions and are used to address a range of sustainability challenges, and such products are critical for analyses like suitability assessments. However, global forest datasets (GFD) vary in their spatial resolution, forest definition, classification methodology, and temporal consistency and span. This variation could substantially affect results from a wide range of forest-related analyses. Understanding such variation is essential for well-informed use of GFD. The third core chapter of this dissertation therefore maps the area-based spatial congruence of eight commonly used GFD and assesses the influence of dataset choice on estimates in three sustainability domains: carbon sequestration, forest-poverty relationships, and endangered species distribution. Results show only 26% congruence among all GFD globally, with wide variation in congruence across biomes. This divergence led to an order of magnitude difference for our analyses when using different datasets. The findings reveal the need for careful GFD selection and using multiple GFD to generate ranges of estimates. This work contributes to the broader knowledge base around human and nature interactions, social-ecological systems, and land system and sustainability science. The results can be used to inform agricultural conservation policy and decision-making related to agroforestry and rural land use, and I discuss future directions for agroforestry research, practice, and policy in the US Midwest and beyond.

Graduation Semester

2024-08

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/125518

Copyright and License Information

Copyright 2024 Sarah Elizabeth Castle

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