The results are divided into five categories: demographics, gardening background, physical garden elements, garden inputs, and a theoretical comparison. These categories cover all of the survey questions relating to the practical aspects of the respondents’ urban food gardens (for the full list of these questions, please refer to the Supplementary Materials
). The results of this study are intended to provide a broad foundation of survey data. It is the intention of the authors to conduct a follow-up study based on in-field garden inputs (such as labor per activity, water use, and costs) and outputs (such as individual crop yields). Therefore, this survey focused more on gardening methods, rather than crop types, as a basis for future comparison of perception and measured reality. Additional results collected by the EG survey, including motivations, social learning sources, food preservation methods, food distribution frequency and recipients, and the value of growing food will be presented in a separate paper.
The Edible Gardens survey respondents ranged in age from 18 to 81+, with a median age-range of 41–50. The majority of the respondents were women (77% female: 22% male: 1% indeterminate/unspecified). The median number of people living in the household was three, with 34% of households having primary school age or younger children present and 16% having at least one person over the age of 65 present. Postcode data allowed us to map and classify the respondents according to whether they lived inside (82%) or outside (18%) the boundary of metropolitan Adelaide. Figure 1
displays the mapped postcodes across and close to metropolitan Adelaide, the boundaries of which are colored purple on the map. There are 24 additional survey postcodes from across wider South Australia that are not visible in Figure 1
A number of questions were related to relative socio-economic advantage and were used to contextualize the EG survey participant group within the broader South Australian community. Education levels suggested that our respondents were, on average, substantially more educated than the general population with 35% holding a bachelor’s degree and 31% holding a postgraduate degree. By comparison, 14% of South Australians hold a bachelor’s degree and only 4% hold a postgraduate degree [44
]. Using the survey respondents’ postcodes as a proxy for location, we were able to examine their distribution using Australia’s Index of Relative Socio-economic Advantage and Disadvantage (IRSAD) rankings. Figure 2
shows the distribution of postcodes of the EG respondents as compared to the rankings for the whole of South Australia. The majority of the EG respondents’ postcode index rankings (59%) were above the fifth decile, compared with only 39% of the total South Australian rankings. In particular, the highest two deciles were substantially over-represented and the lowest two deciles were substantially under-represented in our survey respondents (as measured by their postcode) relative to the general population.
Home ownership (defined as either owning a home outright or having a mortgage) was high at 85%. Of those remaining, 11% were renting and 4% had other situations. There were statistically significant differences (see Table 1
) between the home owners and home renters, in that home owners had larger food gardens (U = 6990.5, n
1 = 270, n
2 = 35, p
= 0.001), spent more money setting up their food gardens (U = 4875, n
1 = 241, n
2 = 28, p
= 0.001), had higher IRSAD rankings (U = 5668, n
1 = 268, n
2 = 35, p
= 0.043), and had less of a desire to save money by growing food (U = 3592, n
1 = 266, n
2 = 35, p
= 0.021). The difference between the home owners and home renters and their desire to save money by growing food (Table 1
) was particularly interesting. The same comparison is presented for the two highest and two lowest IRSAD deciles (noting that this uses the respondents’ postcode as a proxy). Interestingly, however, no significant difference was found in their perceptions of how much of their weekly fruit and vegetable budget they believed they had actually saved.
3.2. Gardening Background and Approaches
Food gardening experience was categorized as follows: ‘Less than 1 year’, ‘1–5 years’, ‘6–10 years’, and ‘11+ years’. The median response was 6–10 years. Although there was a weak positive correlation between the age of the respondents and their years of gardening experience (Spearman correlation: rs = 0.357, n = 332, p = 0.001), this was not true for everyone. The 29 gardeners who reported having ‘less than 1 year’ of experience ranged in age from 18 to 60 years, and the 116 gardeners who reported having ‘1–5 years’ of experience ranged in age from 21 to 80 years. With regard to gardening consistency, 62% of the respondents reported growing food ‘all through the year’, while 18% grew “on and off again” and 14% grew food ‘seasonally’.
In an attempt to build up a picture of the ‘look’ and ‘feel’ of food gardens in South Australia, gardening approaches were categorized differently from production methods. The list of production methods began as a simple list of different physical methods to grow food; however, there was a need to be able to clearly identify urban livestock as they require specific physical setups. Additionally, fruit trees were identified as an interesting crop/form of food production—one with the potential to grow large volumes of food without too much effort on the part of the gardener. As fruit trees can be grown in in-ground beds, raised beds, pots, or even wicking beds, they were added as an individual production method for easy identification.
Gardening approaches were categorized as the more philosophical approaches with which gardeners may identify. Ten different gardening approaches were listed (based on common approaches used in South Australia and those mentioned previously in the literature [27
]) and survey respondents were asked to select all the approaches they used (Figure 3
). This question was included as different gardening approaches are commonly advocated as ways to improve a garden and are thought to influence many of the practical aspects of UA; for example, organic gardening may require fewer pesticides, and how adding compost can improve the water retention of the soil.
The median number of gardening approaches with which the respondents identified was four. The top five were composting (70%), conventional digging and tilling (66%), organic gardening (57%), companion planting (53%), and low use of chemical fertilizers and pesticides (48%). There were stronger relationships between certain gardening approaches than between others; for example, respondents who used conventional digging and tilling were more likely to also use a low amount of chemical fertilizers and pesticides (78%), yet they were less likely to use no-dig gardening (38%) or permaculture (45%). Whereas respondents who used a biodynamic approach were more likely to make their own compost (93%), use an organic approach (87%), and utilize companion planting (73%), they were less likely to use a low amount of chemical fertilizers and pesticides (33%).
The challenges of growing food in urban areas were split into two questions. First, respondents were asked to list the top three things that delayed or challenged them when they initially began to grow food. Then, they were asked whether there was anything currently making it difficult for them to continue growing food, and if they responded “yes” (as 61% did), they were asked to describe those current challenges (Table 2
3.3. Physical Elements of the Food Gardens
The physical elements of the respondents’ food gardens included the area under production, the types of growing areas, and the total number of growing areas. The total area under production was categorized as follows: tiny (<4 m2
(7%)), small (5–15 m2
(28%)), medium (16–20 m2
(28%)), large (31–50 m2
(16%)), and huge (51+ m2
(16%)) (see Figure S1
). The median size under production was medium (16–20 m2
). The total area under production did not refer to the size of the entire garden, but purely to the space dedicated to food production.
A wide variety of production methods were being used (Figure 4
). Fruit trees were the most common method (84%) followed by pots and planters (74%), in-ground beds (70%), raised beds (61%), chickens (39%), wicking beds (21%), bee hives (8%), other production methods (7%), vertical gardens (7%), other poultry (5%), and aquaponics (4%). As shown in Figure 5
, the strength of the relationship between the different production methods varied. The stronger the connecting line, the greater the likelihood that both production methods were present together in a single food garden. The median number of production methods used was four. The majority of respondents (68%) were using either three, four, or five different production methods simultaneously in their food gardens. The production methods could be grouped according to the number of other production methods likely to also be present in that same garden. In-ground beds, raised beds, pots and planters, and fruit trees were all more than 50% likely to be present with three other production methods. Chickens were more than 50% likely to be present with four other production methods. Vertical gardens, other poultry, wicking beds, and bees were all more than 50% likely to be present with five other production methods, and an aquaponics system was more than 50% likely to be present with more than 6 other production methods. The number of food producing areas ranged from 1 to 20, with four being the median number of areas.
3.4. Garden Inputs
The main garden inputs about which the respondents were asked included time, water, and money. The survey respondents estimated the time spent per week on their food gardens, ranging from less than one hour to more than 20 h (see Supplementary Figure S2
). The most common category of time spent per week was 1–5 h (55%), and the median was four hours. Statistically, there was no difference between the hours spent by men and women (U = 4,107.5, n
1 = 199, n
2 = 50, p
= 0.056). Some children (less than 18 years of age) did help out in the food gardens, although generally for only one hour per week (median = 1 h, range = < 1–10 h).
As reported by Pollard, Ward, and Roetman (submitted for publication), the survey respondents reported a range of water sources, including mains, rainwater, grey water, and recycled/blended water, as well as ‘other’ sources. Respondents dispensed that water using a variety of irrigation methods, including manual irrigation (via hose, watering can, or bucket), drip irrigation, sprinklers, wicking beds, and any method of providing water for animals, as well as ‘other’ methods. Both the water source and irrigation methods reported were not mutually exclusive, with the majority of survey respondents using more than one water source and irrigation method. The respondents were also asked to estimate their water use, yet we found that most respondents had very little idea of how much water they actually used in their food garden areas. Owing to the large diversity of water sources (five in total) and irrigation methods (six in total), we concluded that ‘estimated water use’ was too complex a term to accurately provide a quantifiable result via survey. Future work collecting in-field water use data would be more accurate and beneficial.
A broad range of estimated setup costs were reported by the survey respondents with high variability (Figure 5
). This variability was partially due to the differing levels of detail in the responses. Some respondents included only the cost of seeds or seedlings, others added the cost of soil, fertilizer, and building supplies, and some went to great levels of detail, documenting not only the building of garden beds/wicking beds/orchards, but also the purchase and installation costs of new rainwater tanks, irrigation systems, or grey water recycling systems. The setup costs therefore ranged from $
0 to AUS$
20,000, and the median amount spent was AUS$
500. There was a moderate positive correlation between the area under production and garden setup costs (Spearman correlation: rs
= 0.432, n
= 304, p
When asked to estimate their monthly garden expenses, again there was a broad range of responses from $0 to AUS$1000 per month, with a drop off after AUS$50. The median amount spent was AUS$30 per month. There was a correlation between the total area under production and the monthly costs (rs = 0.379, p = 0.001, n = 325).
Analysis confirms that there was a significant difference between several other parameters for gardens costing AUS$50 or less per month versus gardens costing more than AUS$50 per month. Gardens costing more than AUS$50 per month had higher setup costs, were larger, had a greater number of food producing areas and production methods in use, and took more time to tend. Gardens that cost more than AUS$50 had higher mean ranks for the areas under production (U = 8143.5, n1 = 279, n2 = 46, p = 0.003), a greater total number of production methods (U = 8143.5, n1 = 279, n2 = 46, p = 0.002), a greater total number of food producing areas (U = 8338, n1 = 279, n2 = 46, p = 0.001), a greater number of weekly hours spent gardening (U = 8398.5, n1 = 272, n2 = 46, p = 0.001), and a higher total setup cost (no outliers) (U = 6534.5, n1 = 254, n2 = 35, p = 0.001).
There were also some significant differences between gardeners who spent less than AUS$10 per month and those who spent more than AUS$10 per month. While the majority of both groups agreed that they grew food to save money, those who spent less than AUS$10 per month were more certain that they succeeded in saving some portion of their household fruit and vegetable budget (Mann–Whitney U test: U = 5243, n1 = 58, n2 = 219, p = 0.038, difference (≤10–>10) = 1.00 (CI 95% 0.00 to 1.00)).
Building on the initial cost questions, the survey respondents were asked whether they thought they succeeded in saving money in their weekly household fruit and vegetable budget and if so, to what extent (Table 3
). In all, 47% believed that they did save some amount of their fruit and vegetable budget, 13% were unsure, 13% thought they broke even, 14% didn’t think they saved any money, and 6% were adamant that they did not save any money. There was also a moderate positive correlation between respondents wanting to save money and thinking that they succeeded in doing so (Spearman correlation: rs
= 0.515, n
= 297, p
3.5. Theoretical Comparison Results
Ward and Symons [34
] sought to maximize the net value of hypothetical urban food gardens according to the area under production, by considering the nutritional value and water efficiency of crops in different climates. Two-stage linear programming was used to select an optimal mix of crops according to their water use and dietary value. Constraints were applied to ensure that the model selected a combination of crops from a range of dietary food groups—thus better mimicking the mixed-crops common to home food gardens. This approach was intended to produce a more realistic garden model rather than to optimize purely by yield or crop retail value, which tends to select only single high-yielding, high-value crops (a “cash crop”) that would be unrealistic at the household garden scale. Ward and Symons [34
] contributed the idea that the size of a garden and how it is watered are important to the economic sustainability of urban food gardens, but their model did not allow for the consideration of the related expenses or the labor invested.
The EG survey results, which are applicable to the Ward and Symons [34
] optimization model include the number of people in the household, their years of gardening experience, the size of the area under production, and the types and number of production methods used. Ward and Symons [34
] calculated optimized crop mixtures for different climates and various sized areas under production as m2
per person. The majority (70%) of the EG survey respondents had less than 15 m2
(category 1: tiny (<4 m2
/person) (21%) and 2: small (5–15 m2
/person) (49%)) of area under production per person in their household (see Supplementary Table S1
). According to the optimization model, these gardens would ideally be growing a limited range of crops suitable for Adelaide’s climate, namely: broad beans, basil, zucchini, strawberries, tomatoes, and eggs. While the EG survey did not specifically ask respondents which crops they grew, it did ask which production methods they utilized from a list of 11 possible methods (for example, raised gardens beds, fruit trees, keeping chickens, etc.) Without specific crop data, it was difficult to calculate whether or not the EG respondents were following anything akin to the optimized mix recommended by Ward and Symons [34
]. However, according to their areas under production, the EG respondents were theoretically well-placed to achieve the best possible returns for water applied per unit area and net value.
Keeping chickens for egg production is an interesting production method, with 39% of the EG survey respondents listing ‘Poultry—Chickens’, 5% of respondents listing ‘Poultry—Other’, and some respondents listing both chickens and other poultry. In the optimization model, chicken eggs were consistently selected for all area categories as being both a high-value and water-efficient crop for urban food gardens.
Fruit trees are one of the main points of difference between the optimization model and the EG survey data. Fruit trees were present in 84% of the EG respondents’ gardens, making them the most common production method. In contrast, although a range of fruit trees were available in the optimized model, none were selected for their crop value or water-use efficiency in gardens smaller than 80 m2/person. At 80 m2/person, orange trees were selected for all climates, and once the model reached 160 m2/person, almond trees were also selected but only for Hobart’s climate.