2022
DOI: 10.3389/fsufs.2022.879161
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Multi-Level Influences on Center-Pivot Irrigation Adoption in Alabama

Abstract: Rates of poverty and economic inequality in rural Alabama are among the nation's highest and increasing agricultural productivity can provide a needed boost to these communities. The transition from rain-fed to irrigation-fed (RFtoIF) agriculture has significantly increased farm productivity and profitability elsewhere in the United States. Despite this potential to enhance stability and resilience in rural economies, irrigated cropland accounts for only 5% of Alabama's total cropland as numerous barriers rema… Show more

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Cited by 6 publications
(3 citation statements)
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“…Moreover, the weight of biophysical factors such as crop type and weather, noted in IRSIS, has been observed also in USA (Gibson et al, 2018); while the lack of an extension service, highlighted by IRSIS farmers, has been reported as a barrier to adoption also in Australia (Koech et al, 2021). As observed at IRSIS, Price et al (2022) showed that the adoption of centre-pivot in Alabama (USA) depends on multiple factors operating at multiple levels.…”
Section: Discussionmentioning
confidence: 97%
See 1 more Smart Citation
“…Moreover, the weight of biophysical factors such as crop type and weather, noted in IRSIS, has been observed also in USA (Gibson et al, 2018); while the lack of an extension service, highlighted by IRSIS farmers, has been reported as a barrier to adoption also in Australia (Koech et al, 2021). As observed at IRSIS, Price et al (2022) showed that the adoption of centre-pivot in Alabama (USA) depends on multiple factors operating at multiple levels.…”
Section: Discussionmentioning
confidence: 97%
“…In summary, in addition to the difficulties for the collective action needed to manage and maintain a shared centre-pivot system (Theesfeld, 2004;Takayama et al, 2018), the cost of irrigation was a major barrier to full adoption of centre-pivot technology in IRSIS. Cost as a major determinant of irrigation technology adoption has been identified in other countries (de Witt et al, 2021;Tesfaye et al, 2021;Price et al, 2022). Moreover, the weight of biophysical factors such as crop type and weather, noted in IRSIS, has been observed also in USA (Gibson et al, 2018); while the lack of an extension service, highlighted by IRSIS farmers, has been reported as a barrier to adoption also in Australia (Koech et al, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…For instance, dynamic models of climate change adaptation in agriculture systems represent farmer decisions to adopt new farm management practices (e.g., climate-smart irrigation). In certain regions of the United States, such as the Southeast, where large farms are disproportionately owned by White farmers due to socio-economic and policy barriers (e.g., lack of access to credit and capital) faced by Black owners, inequalities in farm size drive trends in irrigation adoption ( 93 ). These empirical findings motivate the inclusion of land markets in agent-based models to better capture interacting influences on adoption and their inequitable distribution.…”
Section: Examples Throughout the Modeling Processmentioning
confidence: 99%