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Translating Environmental Potential to Economic Reality: Assessment of Commercial Aquaponics through Sustainability Transitions Theory

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Translating Environmental Potential to Economic Reality: Assessment of Commercial Aquaponics through Sustainability Transitions Theory

Metadata

  • Cite key: hornTranslatingEnvironmentalPotential2024
  • Item type: Journal Article
  • Authors: E.K. Horn, A. Joyce, R.B. Chowdhury, S. Caputo, B. Jacobs, M. Winkler, G. Proksch
  • Affiliation: Circular City and Living Systems Lab, College of Built Environments, University of Washington, Seattle, WA, USA (Horn, Proksch); Dept. of Civil & Environmental Engineering, College of Engineering, University of Washington, Seattle, WA, USA (Horn, Winkler); Dept. of Marine Science, Gothenburg University, Göteborg, Sweden (Joyce); School of Engineering, Deakin University, Waurn Ponds, Victoria, Australia (Chowdhury); Kent School of Architecture and Planning, Canterbury, UK (Caputo); Institute for Sustainable Futures, University of Technology Sydney, Ultimo, NSW, Australia (Jacobs); Dept. of Architecture, College of Built Environments, University of Washington, Seattle, WA, USA (Proksch)
  • Journal: Circular Economy and Sustainability 4, issue 1 (2024) 523-554
  • Date: 03/2024
  • Date added: 2024-12-26
  • DOI: 10.1007/s43615-023-00291-0
  • Funding: Resource-Recovery in the Food-Water-Energy Nexus project (Pegasus 3 Future Earth “take-it-further” grant); builds on CITYFOOD and FEW-meter projects (Belmont Forum / JPI Urban Europe SUGI Collaborative Research Action); CITYFOOD funded by US National Science Foundation (Award 1832213); Acknowledgements additionally credit Future Earth, the Gordon and Betty Moore Foundation, the Belmont Forum, JPI Urban Europe, and the US National Science Foundation
  • URL: https://doi.org/10.1007/s43615-023-00291-0
  • PDF: Horn et al. - 2024 - Translating Environmental Potential to Economic Re.pdf

Opinion

A well-documented qualitative industry assessment rather than a biological or economic-modelling study — there is no fish, plant, water-chemistry, or dollar-denominated data anywhere in the paper; every quantitative element is a count or percentage of the 25 interviewed producers (e.g., “13 low-tech, self-constructed” or “20% (n=5) used the term ‘trial-and-error’”). The TIS-MLP framing (Table 1/2, Figs 1-4) is the paper’s real contribution: a structured, function-by-function map of drivers and barriers that is genuinely reusable as a checklist for future commercial-aquaponics research, even though it produces no numbers a review of trials could cite. The IRB-exempt interview protocol, response-rate reporting (25/152 ≈ 16.4%, consistent with the stated “nearly 17%”), and full inclusion of the interview/coding protocol as an appendix are unusually transparent for this literature. The main limitation for this vault: because the “sample” is producers, not organisms, nothing here can populate trials.csv or plant_measurements.csv, and the paper should not be mistaken for an economic model of aquaponic profitability (it reports producer perceptions of profitability barriers, not measured cost/revenue figures).

Abstract

Despite popular interest and recent industry growth, commercial-scale aquaponics still faces economic and regulatory barriers primarily resulting from political and economic systems which insufficiently address pressing environmental challenges. The sustainability potential of aquaponic food production can help address and overcome such challenges while contributing to the broader development of circular economy and sustainable development of food systems. In response to the current counterproductive gap between potential applications and industry development, the interdisciplinary team of authors identifies pathways to translate the environmental potential of commercial aquaponics into economic success through a sustainability transition theory lens. To evaluate the industry’s current state-of-the-art, drivers, barriers, and future potential, interview data from 25 North American producers collected in 2021, literature, and policy are analyzed through a Technological Innovation System (TIS) assessment within a Multi-Level Perspective (MLP) approach. This supports the consideration of pathways for industry development of aquaponics as an aspect of circular economy within a dynamic sustainable development context. These pathways for action include (1.) advancing clear standards and policies for aquaponics as part of a circular economy, increasing funding and incentives, and reducing support and subsidies for competing unsustainable food production; (2.) developing and promoting cost-effective technologies; and (3.) bolstering consumer preferences for sustainable and healthy food sources.

Summary

The authors conducted 25 semi-structured telephone/Zoom interviews (May-July 2021, IRB-exempt: STUDY00013037) with commercial aquaponics producers drawn from a database of 152 active North American commercial farms maintained by the University of Washington’s Circular City and Living Systems Lab (CCLS), a recruitment response rate of nearly 17%. Interviews covered farm background, operations/design, business model, technology, policy/regulation, and circular-economy practices, and were qualitatively content-coded in Atlas.ti against a seven-function Technological Innovation System (TIS) codebook. The authors combined this interview data with a literature and policy review (~25% North American, ~50% European sources) and analyzed the result through a Multi-Level Perspective (MLP) lens (landscape/macro, regime/meso, niche/micro) to characterize drivers, barriers, and an “ideal niche” for each of the seven TIS functions (Knowledge Development and Diffusion, Entrepreneurial Activities, Market Formation, Resource Mobilization, Development of Legitimacy, Guidance of the Search, Development of Positive Externalities). They found that research productivity, technological advances, and public/consumer interest are the industry’s primary drivers, while small financial resource inflows, absent government/tech-industry funding, fragmented fish/produce distribution channels, and a fragmented regulatory environment (no aquaponics-specific food-safety or organic-certification pathway) are the primary barriers to commercial scaling. The paper proposes three categories of “regime change” strategy for policymakers, industry, and researchers (privileging/supporting/rebalancing via policy; optimizing/knowing via R&D; promoting/evaluating via societal engagement) intended to convert aquaponics’ environmental potential into a defensible market advantage. No fish, plant, or water-chemistry data of any kind are collected or reported; the paper is a qualitative, interview- and literature-based industry assessment, not a biological trial or a quantitative economic model.

Experiment data

  • Location: Interviews conducted with commercial aquaponics producers based across North America (map, Fig. 2, shows sites across the continental USA); research team based at University of Washington, Seattle, WA, USA
  • Design: Mixed-methods qualitative assessment: (1) semi-structured interviews (n=25) with commercial aquaponics producers, recruited by phone from a CCLS database of 152 active North American commercial aquaponic farms (2022 snapshot), conducted May-July 2021, qualitatively content-coded in Atlas.ti against a TIS-function codebook (Appendix); (2) supplementary literature review (scholarly, general, industry, and policy sources, ~25% North American / ~50% European by the paper’s own estimate); (3) collaborative interdisciplinary analysis and iterative manuscript review by the seven-author team. No biological manipulation, no control group, no statistical hypothesis test — descriptive/qualitative functional analysis only, per a TIS (7 functions) x MLP (landscape/regime/niche) framework
  • Replicates / n: n=25 producer interviews (of 152 in the sampling frame; ~17% response rate). NA for any biological unit — no fish, plants, or organisms were studied
  • Duration: Interviews conducted May-July 2021; database snapshot dated 2022; manuscript received 25 Aug 2022, accepted 28 Jun 2023, published online 21 Aug 2023
  • Organisms: NA — this is an industry/producer-level qualitative assessment; fish and plant species (tilapia, trout, sturgeon, salmon, various greens) are discussed only as examples within producers’ business models, not as objects of measurement
  • Statistics: None — qualitative content analysis (Atlas.ti coding against the TIS-function codebook, Appendix) reviewed by two additional authorial-team members; no significance testing anywhere in the paper
  • Technological Innovation System (TIS) functions assessed: Knowledge Development & Diffusion; Entrepreneurial Activities; Market Formation; Resource Mobilization; Development of Legitimacy; Guidance of the Search; Development of Positive Externalities (Fig. 1; Table 1)
  • Multi-Level Perspective (MLP) levels: Landscape (macro, e.g., climate change, resource scarcity, supply-chain issues, environmental awareness); Regime (meso, e.g., rules/policies/structures/practices); Niche (micro, the functional environment aquaponics needs to succeed) (Fig. 1; Fig. 4)

Interview sample and industry scale

This paper: Recruitment drew on a CCLS database of 152 active commercial aquaponic farms in North America (2022), yielding 25 completed interviews (~17% response rate; 25/152 = 16.4%, consistent with the paper’s own “nearly 17%” on recomputation). The authors describe the sample as representative of the known active commercial population in terms of geographic location, growing-area size, and business-model distribution (Fig. 2). For historical context (not this paper’s own count), the USDA Census recorded 73 operating aquaponic farms in the US in 2013 and 83 in 2018, versus 2853 and 2704 aquaculture operations respectively [secondary, cites USDA 2013/2018 Censuses of Aquaculture, refs 72-73].

Compared with: todo Love et al. 2014 — international survey of aquaponics practitioners, cited for the ~30% higher-education-degree finding among interviewees (p.8). todo Pattillo et al. 2022 — survey of aquaponics stakeholders (84% US-based), cited repeatedly as a comparison point for technology-sophistication distribution (p.10), best-practice information needs (p.9), and difficulty securing investor trust (p.13).

System sophistication and technology adoption

This paper: Of the 25 interviewed farms, “thirteen primarily rely on low-tech, self-constructed systems, seven of the farms utilize partly self-engineered infrastructure, and seven use professionally engineered systems installed by a commercial supplier” (p.10) — see Extraction notes on the arithmetic. The largest identified operation combines a cold-water salmon aquaculture system with a large-scale hydroponics system and covers approximately 600,000 sq ft / 60,000 m² of controlled growing area (p.9); the next-largest farm increased its growing area fivefold since 2016, with six further businesses opened in the same period (p.20, Conclusion). Twenty percent (n=5) of interviewees described their farm-level R&D process using the term “trial-and-error” verbatim (p.10).

Compared with: todo Pattillo et al. 2022 — reported “largely similar proportions” of technology sophistication among their (largely US) survey respondents (p.10).

Market formation and revenue structure

This paper: Most farms maintained more than one distribution stream: n=14 sold into restaurant/institutional markets, n=19 engaged in direct consumer sales (on-site/farmers markets), n=11 held grocery-chain or secondary-processor contracts, and only n=3 reported wholesale markets as their primary target (p.11) — these figures overlap because most farms use multiple channels simultaneously (explicitly stated, not a contradiction). Crops generally outperform fish financially because of faster turnover (e.g., ~6 weeks to market for produce versus a year or more for fish, particularly low-value species like tilapia); more than half of interviewed producers (n=14) opted not to sell the fish grown in their systems at all, treating fish purely as a nutrient source (p.11).

Compared with: todo Love et al. 2015 — international survey on commercial aquaponics production and profitability, a natural companion reference for the revenue-imbalance finding (cited in References list, ref 34, but not directly quoted in running text on this point).

Knowledge, workforce, and legitimacy

This paper: Roughly 30% of interviewed producers held higher-education degrees in related fields (agriculture/aquaculture); some leaders of larger companies (n=4) came from business backgrounds; about half (n=13) were largely self-taught; ~9 had taken aquaponics courses or trained with experts; only 20% reported engagement/collaboration with researchers or universities; n=3 cited conference/association involvement; about 70% (n=17) described having a network of key contacts (p.7-9). On legitimacy, only n=4 interviewees specifically maintained formal organic certification, and more than five (n>5) described difficulty securing trust from banks, investors, or business partners (p.13-14).

Compared with: todo Love et al. 2014 — cross-referenced for the higher-education-background proportion (p.8). todo Pattillo et al. 2022 — cross-referenced for the credible-information-access finding (p.9) and investor-trust finding (p.13).

TIS function assessment and regime-change pathways (Tables 1-2, Figs 1-4)

This paper: Table 1 summarizes drivers, barriers, and “niche formation actions” for each of the seven TIS functions (full table reproduced from the PDF’s structured layout, e.g., Function 3 Market Formation: driver = year-round/local-market production; barrier = fish/produce needing separate distribution networks and profit imbalance; niche action = “develop cost-effective production and competitive market-integration”). Table 2 proposes eight named “pathways” of regime change nested under three strategy groups: political/economic regulation (Privileging, Supporting, Rebalancing), R&D (Optimizing, Knowing), and societal engagement (Promoting, Evaluating), each with example strategies (e.g., “expanding legal flexibility for aquaponics through certifiable standards,” “creating payment systems for ecosystem services”). Figure 4 diagrams how four landscape factors (climate change, resource scarcity, global production & trade, environmental awareness) drive three regime-change strategy bundles toward an “ideal niche” (regulatory ease, available financial/physical resources, cost-effective competitive production, advanced technology, cutting-edge knowledge access, consumer/regulator recognition, mutually beneficial partnerships) en route to “Realization of Aquaponics’ Sustainability Potential.”

Compared with: todo König et al. 2018 — prior TIS assessment of aquaponics as an emerging field, undertaken for Europe (2018) (ref 6, cited p.3 as the precedent this paper updates/extends to North America). todo Wiegand 2019 — TIS analysis specific to the Netherlands (ref 39, p.3).

Linked claims

Citations to chase

  • todo Love et al. (2014) — international survey of aquaponics practitioners; source for producer educational-background comparison
  • todo Love et al. (2015) — international survey on commercial aquaponics production and profitability; natural companion to this paper’s revenue/profitability findings
  • todo Pattillo et al. (2022) — survey of aquaponics stakeholders (84% US-based); repeatedly cross-referenced for technology sophistication, information access, and investor-trust findings
  • todo König et al. (2018) — prior TIS assessment of aquaponics as an emerging field in Europe; the explicit precedent this paper updates for North America
  • todo Wiegand (2019) — TIS analysis of aquaponics development in the Netherlands
  • todo Turnsek et al. (2020) — “Challenges of commercial aquaponics in Europe: beyond the hype,” cited for EU regulatory/commercial-expansion barriers
  • todo Greenfeld et al. (2021) — “Monetizing environmental impact of integrated aquaponic farming compared to separate systems,” cited for the need to internalize environmental value economically
  • todo Fruscella, Kotzen & Milliken (2021) — EU organic-certification barriers for aquaponic products under Regulation (EU) 2018/848

Extraction notes

  • Not a contradiction, noted for transparency: the technology-sophistication breakdown (“thirteen… seven… seven,” summing to 27 against n=25) is explicitly flagged by the authors themselves as having “some overlap noted” (p.10) — some farms apparently span more than one category. No cell is affected since this paper produces no trials.csv row; recorded here only so a reader comparing this note against the PDF is not confused by the apparent arithmetic mismatch.
  • Not a contradiction: the literature-review composition (“approximately 25% are from North America and 50% from Europe,” p.6) sums to 75%, not 100%. The paper never claims the breakdown is exhaustive, and the remaining ~25% is plausibly other regions/theoretical sources; this is an incomplete disclosure rather than a conflicting figure, so no WARN severity applies.
  • [not reported]: exact dollar figures for producer revenue, costs, or profitability anywhere in the paper — despite the title’s emphasis on “economic reality,” all economic content is qualitative (producer-described barriers/challenges) or a count/percentage of interviewees, never a measured cost or revenue value. No “NO COLUMN” economic figures were extractable because none of the paper’s numbers are of the kind trials.csv’s Experimental Remarks field is built to hold (kg, $, %/yield) — they are all sample counts/percentages describing producer characteristics, which have no natural home in either output CSV regardless of type.
  • [not reported]: number/proportion of the 25 interviewed farms located in Canada versus the USA (the “North American” sample and Fig. 2 map appear to show only continental US sites, but this is not stated explicitly in text).
  • [unclear]: precise number of literature sources reviewed (no total citation count for the literature-review component is given beyond the ~25%/50% regional split).
  • Type justification (observational, not exploratory/case-study/modelling): The paper collects primary data (25 semi-structured interviews) but performs no manipulation, no controlled comparison, and no biological or economic measurement of any kind — this matches SCHEMA.md’s observational test (“measures without manipulation — surveys of existing systems, monitoring”) far better than exploratory (which implies a still-nascent pilot toward a future hypothesis test on a system the authors themselves run) or case-study (a single system studied in depth; here 25 distinct farms are surveyed at once). It is not modelling: SCHEMA.md defines modelling as “simulation or computational model; no new empirical data,” and this paper’s entire contribution is newly collected empirical (interview) data — the opposite condition. It is not review/narrative-review/policy despite extensive literature and policy discussion, because Section “Data Collection and Analysis” reports data the authors collected themselves (interviews, n=25) under an IRB protocol — CLAUDE.md’s review test (“does the paper report data the authors collected themselves? If yes, it is not a review”) is decisive here.
  • CSV rows: 0. Per SCHEMA.md and the task brief, only experiment, quasi-experiment, field-trial, and exploratory types produce trials.csv/plant.csv rows. This paper is observational, so both output CSVs are header-only by design. Separately and independently of the type classification: even if a CSV-producing type had been assigned, this paper contains no fish, no plants, no water chemistry, and no aquaponic-system operational data of any kind (stocking density, FCR, water volume, pH, etc. are never once reported for any of the 25 farms) — it is a producer/industry-level interview study, structurally incompatible with a one-row-per-treatment schema built around biological trials.
  • plant.csv is 0 rows for the same reason: no plant analytes (biochemistry, mineral, microbiology, proximate) are measured or reported anywhere in the paper.
  • Severity tally: 0 BLOCK, 0 MATERIAL, 0 CHECK, 0 MINOR (the two “not a contradiction” notes above are documented for transparency but do not meet the bar for a WARN tag under the severity rules). No quality: score assigned in frontmatter — the SCHEMA.md quality-scoring table is scored against BLOCK/MATERIAL counts on trials.csv cells, and this paper contributes no trial row for that scoring to apply to.

Source: Horn et al. - 2024 - Translating Environmental Potential to Economic Re.pdf

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