Community Trust Determines Whether Aquaculture Gets Social Approval

Aquaculture has become the primary driver of growth in the global seafood supply. More than half of all seafood consumed today is farmed, and that share is expected to climb. In the U.S., federal agencies have set ambitious targets for industry expansion, yet aquaculture development frequently stalls not because of biological or logistical barriers, but because of public opposition. Local resistance is well documented and, in some cases, can prevent companies from ever moving beyond the planning stage. Understanding why some communities resist aquaculture, and how that resistance operates, is essential for anyone invested in the future of coastal ecosystems.

This technical report from the National Oceanic and Atmospheric Administration seeks to fill a gap in how researchers and industry planners think about community acceptance. The central concept it explores is “social license to operate” (SLO), the informal, ongoing approval that communities grant (or withhold) from incoming industries, separate from any official regulatory permit. Existing models of SLO focus almost entirely on what companies do to earn acceptance, while overlooking the role of community characteristics. The authors’ goal was to develop a preliminary framework of factors linked to a community’s willingness to grant SLO before an aquaculture operation even arrives.

The researchers synthesized three bodies of literature:

• The first review examined SLO in resource-extraction industries, especially mining, where the concept originated in the 1990s.
• The second review looked at how SLO has been applied specifically to aquaculture.
• The third review covered empirical public opinion surveys on the social acceptability of aquaculture conducted in countries including the U.S., Canada, Norway, Ireland, Scotland, Germany, Italy, Sweden, Spain, Israel, Chile, Australia, and New Zealand.

Seven Factors That Shape Community Trust

By collating the survey results into a comparative table, the authors identified seven themes that were linked to public support for or opposition to aquaculture development.

Theme 1: Environment

Environmental concerns were the most consistently documented factor. Communities with greater worry about aquaculture’s impacts on marine ecosystems, wild fish populations, and water quality tended to be less supportive of development. For instance, in three studies where participants ranked concerns by importance, environmental impacts were consistently rated highest.

That said, the relationship wasn’t always straightforward: in some cases, some environmentally concerned respondents were more supportive of development, and the degree of concern varied significantly by place.

Theme 2: Economy

Respondents who saw aquaculture as good for local employment and economic growth were more likely to support development. In one comparative study, for example, around 85% of Norwegian respondents and 95% of Irish respondents agreed that aquaculture generates local jobs. However, economic benefits didn’t always translate into support. In Canada, while 85% believed that aquaculture creates good jobs, only 36% of Pacific coast respondents said those benefits led to a favorable view of the industry.

Where environmental and economic values conflicted, a community’s economic circumstances appeared to shape which takes priority. Research consistently found that residents in less affluent communities were more likely to prioritize the economic benefits of aquaculture, while those in wealthier areas were more likely to prioritize minimizing environmental harm.

Theme 3: Knowledge

Knowledge of aquaculture was generally low across the surveys reviewed. Higher levels of knowledge tended to be associated with more positive attitudes toward development, though some studies found mixed or null results.

Theme 4: Use Conflict

Competition over shared coastal resources was another factor, though this varied dramatically by place. For instance, respondents in the U.S. and Norway who believed that aquaculture interfered with recreational uses of the coast were less likely to support development, while a New Zealand study found no such relationship.

Theme 5: Experience

Proximity to aquaculture operations produced conflicting results across studies, with some finding that nearby residents were more supportive and others finding them more sensitive to development. A few studies didn’t uncover a link.

Engagement with the industry also had variable impact. Participants who had visited aquaculture sites were more likely to be concerned about the environmental impact, though the causal direction of this relationship is unclear. Respondents with personal connections to people working in aquaculture were more likely to support it, as were those who consumed farmed seafood regularly.

Theme 6: Government And Regulation

Trust in regulators was mixed. For example, between a quarter and half of respondents in one Australian study reported low levels of trust across all levels of government. In another study, respondents who believed that the regulatory system would ensure the best environmental outcomes had higher trust in the aquaculture industry itself.

The opportunity to participate in planning processes was highly valued by the public, with one study finding that respondents who attended planning meetings were more supportive of future aquaculture development.

Theme 7: Health And Safety

Public perceptions of the health and safety of farmed seafood were mixed. In the U.S., for instance, most respondents (85%) believed that aquaculture yields a healthy product, yet they were split on whether farmed or wild-caught seafood was actually safer. In other studies, respondents who believed that farmed fishes were more likely to contain pollutants or that farmed salmon was unhealthy were less likely to support aquaculture.

Trust As The Thread

The authors situate all seven factors within a single organizing concept: trust. Drawing on an established model from the mining literature, they propose that community characteristics function as moderators, influencing how receptive a community is before any company interaction even begins. A community’s willingness to trust, shaped by these seven factors, determines how effective company actions can be at ultimately generating SLO.

Limitations

The authors acknowledge several key limitations. The framework is based on a synthesis of existing literature rather than original data collection, and hasn’t yet been empirically tested with aquaculture data.

The survey research captured individual-level attitudes that may not fully reflect collective community dynamics. Causal direction is unclear in several of the relationships identified. For example, it’s uncertain whether distrust of regulators causes opposition to aquaculture, or whether opposition drives distrust.

Finally, the body of SLO research specific to aquaculture remains relatively small.

What This Means For Advocates

For advocates working to protect aquatic animals and marine ecosystems, this framework offers meaningful insight into where community-level resistance to aquaculture expansion is most likely to take root — and how to support it.

Communities with strong environmental values, low confidence in regulators, negative prior experience with the industry, and concerns about use conflict are the least likely to grant social license. These are also communities where advocates could have the most impact, supporting public education efforts and amplifying already-present community concerns.

The SLO concept itself is worth understanding as an advocacy tool. It functions as an informal veto that communities can exercise through organized opposition, public comment, consumer pressure, and political advocacy. Aquaculture expansion depends not just on permits, but on public acceptance. The research here suggests that acceptance can’t be assumed, and that the characteristics of host communities are as important as the behavior of companies in determining whether that acceptance is ever granted.

This summary was drafted by a large language model (LLM) and closely edited by our Research Library Manager for clarity and accuracy. As per our AI policy, Faunalytics only uses LLMs to summarize very long reports (~50+ pages) that are not appropriate to assign to volunteers, studies that contain graphic descriptions of animal cruelty or animal industries, and research on niche topics. We remain committed to bringing you reliable data, which is why any AI-generated work will always be reviewed by a human.