Figure 2 - uploaded by Laura Schreiner
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Total GGH farmland in acres, 1996-2016 (Data sources: Statistics Canada, 2017b; Statistics Canada, no date a; Statistics Canada, no date b)
Source publication
This paper explores Oregon’s land use planning policies and their outcomes for farmland and agriculture in the Willamette Valley. An agricultural systems planning framework is used to guide the investigation, which uses a combination of literature review and key informant interviews to extract lessons which may be relevant in the Greater Golden Hor...
Contexts in source publication
Context 1
... obvious sign is the loss of agricultural land as it is converted to non-agricultural uses. Between 1996 and 2016, over 637,000 acres (2,578 square kilometers) of farmland were lost in the GGH (See Figure 2): a loss of 14% of Outer Ring farmland and 21% of Inner Ring farmland in only 20 years. The conversion of agricultural land to non-agricultural uses is significant because the conversion is almost always permanent; land cannot be recovered for agriculture afterward. ...
Context 2
... could become Important Agricultural Lands if certain circumstances changed. Figure 20 shows the results of the analysis. Rules put into place by LCDC (referenced in the aforementioned statutes) specifically cite this report and encourage counties to include Foundation Agricultural Lands in rural reserves. ...
Citations
Complex agricultural problems concern many countries, as the economic motives are increasingly higher, and at the same time the consequences from the irrational resources use and emissions are becoming more evident. In this work we study three of the most common agricultural problems and model them through optimization techniques, showing ways to assess conflicting objectives together as a system and provide overall optimum solutions. The studied problems refer to: i) a water-scarce area with overexploited surface and groundwater resources due to over-pumping for irrigation (Central Greece), ii) a water-abundant area with issues of water quality deterioration caused by agriculture (Southern Ontario, Canada), iii) and a case of intensified agriculture based on animal farming that causes issues of water, soil quality degradation, and increased greenhouse gases emissions (Central Ireland). Linear, non-linear, and Goal Programming optimization techniques have been developed and applied for each case to maximize farmers welfare, make a less intensive use of environmental resources, and control the emission of pollutants. The proposed approaches and their solutions are novel applications for each case-study, compared to the existing literature and practice. Furthermore, they provide useful insights for most countries facing similar problems, they are easily applicable, and developed and solved in publicly available tools such as Python.
