While perceptions of benefits and addiction were not related to use in this study, perceptions of greater health and social risks were associated with lesser odds of using marijuana. Other studies have also found risk perceptions related to use . The fact that perceptions of benefits were not related to use is surprising as other studies have found perceptions of benefits to predict use . It is possible that perceived social norms are more important drivers of adolescents’ decisions to use marijuana than perceived risks and benefits despite the fact that these constructs are linked . While perceptions of benefits of marijuana were not related to use, seeing messages about the good things or benefits of marijuana use was associated with a 6% greater odds of use. In contrast, despite adolescents seeing ads for both risks and benefits of marijuana, messages regarding risks were not related to use. It is possible that individuals who use marijuana are actively seeking and more aware of messages related to benefits of marijuana use. There are limitations to this study. The data are self-reported. Further, given the cross sectional nature of our data, we cannot suggest a causal relationship between factors associated with marijuana use and marijuana use itself. Additionally, some of the factors associated with marijuana use have a confidence interval approaching 1.0. Finally, these data were collected throughout Northern and Southern California and thus are not nationally representative. Despite these limitations, this is one of the few studies to assess perceptions of social norms, risks and benefits for marijuana, blunts, and cigarettes. Additionally, this study assessed how these factors as well as awareness of social media are related to marijuana use. Results from this study offer a number of important public health implications,drying cannabis particularly as states move towards legalization of marijuana for recreational use. As this occurs, states need to take adolescents’ perceptions of risks, benefits, social norms, and peer influences into account.

Though there is mixed evidence on how legalization impacts adolescent marijuana use, advocates for marijuana legalization argue that legalization itself does not increase use among youth . However, there is no evidence that legalization alone does anything to decrease use or access among adolescents. The results from this study have a number of implications for prevention strategies. Perceived rates of marijuana use among friends is higher than participant self-reported use rates and reported national averages of adolescent use. This finding is similar to findings in the alcohol use literature, which finds that youth and young adults tend to overestimate rates of binge drinking. Importantly, dispelling this misperception has been used effectively in a number of social norms campaigns focused on reducing binge drinking in college campuses . This suggests that using a similar social norms marketing approach, in which youth learn that rates of marijuana use among peers are much lower than they think, may be a useful strategy to prevent use. In this study, both perceived friend use and having seen positive messages about marijuana was associated with greater odds that an adolescent used marijuana. These findings also suggest the need for marketing, education and intervention strategies that specifically tackle social acceptability and peer use. This study also shows that adolescents perceive marijuana and blunts to be significantly less harmful than cigarettes, despite the fact that all of these products are combustible smoking products. Additionally, despite the fact that blunts have nicotine, adolescents did not perceive these to be more addictive than marijuana. These findings suggest that there is also a need for educational and marketing campaigns that realistically address what the risks of marijuana and blunt use are for both youth and adults, including risks of addiction. National, state, and local public health agencies should consider lessons learned from regulatory and informational strategies that have been used in tobacco control, and should implement such strategies before legalization occurs .

Aquaculture, which is the farming of aquatic organisms including algae, invertebrates, and vertebrates, has been one of the fastest growing agriculture sectors for the past 40 years . Demand for seafood has continually grown with global fish production in 2018 at around 179 million metric tons , of which 82 MMT comes from aquaculture . While 86.5% of total finfish production occurs in inland freshwater systems, with the majority in Asia , marine culture has the highest growth potential with 2% of oceans being suitable for fish farming . For marine aquaculture growth, Australia, Argentina, India, Mexico, and the United States have the greatest potential based on suitable habitat . Freshwater finfish production has primarily been driven by carp, catfish, and tilapia, while marine fish production is dominated by Atlantic salmon which has a freshwater hatchery stage. Despite the recognized opportunities for marine finfish aquaculture production, very few marine fish species have been successful compared to freshwater fish, due in part to the inability to spawn and produce quality fingerlings in captivity. This has led to the common practice of catching wild juveniles and their transfer to captive rearing environments. In recent years, however, certain high value marine species, including the yellow tail kingfish Seriola lalandi, have been successfully reared in the lab . The Seriola genus, within the family Carangidae, contains several species of yellow tail that are globally distributed across broad temperature range . S. lalandi, is reared in temperate waters across the Pacific Ocean in Japan , Australia , New Zealand , Chile , and North America . Fish, unlike mammals, are not thought to inherit their microbiome vertically. Understanding the factors which influence microbiome development in fish is an important first step in mitigating disease and promoting health. One of the primary challenges in marine fish hatcheries is poor survival rate which is often attributed to a combination of disease and nutrition . Even in the wild, the survival rate for fish larvae is 44× higher for freshwater fish as compared to marine .

Wild marine fish, particularly temperate coastal pelagics like Seriola spp. , are exposed to wide ranges in environmental variables such as temperature, oxygen, and nutrients both diurnally with vertical migration for feeding and temporally with changing seasons. The mucosal microbiome of coastal pelagics is highly differentiated across body sites, primarily in the gill, skin, digesta, and gut tissue with the microbiome on external sites most influenced by these changing environmental variables . In mammals, both phylogeny and diet influence gut microbiome development ,ebb flow whereas fish microbiomes are influenced more by environmental variables including habitat, trophic level, phylogeny, and diet . Diet also varies widely by development stage particularly in the larval to fry stages . While mammals have a significant proportion of their gut microbiome colonized or inherited vertically from the mother during birth , the initial establishment of the gut microbiome in fish is less understood. Even fewer studies have sought to identify the source colonizers of gill and skin communities. Microbial colonization throughout development of the fish is a function of both exposure and host selection. At the earliest stage, bacteria which form biofilms on the outside of the egg eventually can colonize both external and internal mucosal sites of freshly hatched larvae upon ingestion of the yolk sac . Marine fish differ from freshwater fish in that they must drink vast quantities of water to maintain osmoregulation, which in turn provides a large source of potential microbes for gut colonization . The first live feeds the larvae consume, which in hatchery settings are often artemia and rotifers, also contribute to the gut microbiome development . In larval YTK, S. lalandi, gut microbiome composition and density changes most when transitioning from a live rotifer feed to pellet based feeds around 30 days post hatch with many of the gut microbes having anti-microbial functionality . In a study assessing gut enteritis in farmed S. lalandi from seapens, gill, and skin microbiomes correlated with disease state suggesting these communities were either responding to overall health decline or contributing to stress . For a freshwater hatchery, the tank side and tank water were shown to significantly influence the skin and gut microbiomes of Atlantic salmon . Despite the array of studies evaluating impacts of various husbandry methods on microbiome composition of mucosal sites , there is a lack of information for how microbiomes on surfaces in the built environment directly contribute to marine fish. To evaluate how the collective hatchery microbiome influences the mucosal microbiome of a marine fish, we investigated the economically important YTK S. lalandi. This study sought to answer three primary questions: Are body sites differentially influenced by the BE or feed microbiome?, What surfaces within a hatchery environment contribute to the mucosal microbiome of the fish?, and Does the BE and feed microbiome source contribution vary across age and development of the fish? To answer these questions, we sampled the mucosal microbiomes of 92 fish across three broad development stages . Specifically, we used 16S rRNA amplicon sequencing of microbial communities from the fish together with various hatchery surfaces including tank water, tank side, inlet water pipe, air stones, and air diffusers along with feed used in all stages of production.

To our knowledge this is the first study to quantify and compare the relationship of the BE microbiome with the fish microbiome across multiple age classes of a marine fish. All sampling events occurred in June of 2018 in Port Stephens Australia at the Department of Primary Industries New South Wales. Two broad sampling regimes were carried out . A total of 92 “YTK” were sampled in Port Stephens, Australia. In the first experiment, gill and skin swabs were sampled from a total of 36 living fish across three different indoor rearing condition tanks along with corresponding BE samples including tank water, the tank side, inlet pipes, and air diffusers. These fish were all siblings and 130 days post hatch “dph.” Fish were reared in either a flow through system “FT,” a traditional moving bed bioreactor “MBBR” Recirculating Aquaculture Systems “RAS,” or a modified BioGill RAS. Fish were reared at a max of 25 kg/m3 fed at a maximum of 0.5 kg food/day/m3 and reared in 10 m3 tanks. Additional details can be found in the white paper . Fish were non-lethally sampled during routine biometric measurements where individuals were weighed and measured. Prior to taking the weight and length, the skin and gill of each fish was swabbed using a cotton swab [Puritan] and placed directly into a 2 ml PowerSoil tube. For these three tank conditions, “BE” samples were taken from the tank water, swab of tank side , swab of air diffuser, swab of air stone, and swab of inlet water pipe. For the two RAS tanks, an additional inlet water sample was taken which represents cleaned water . Comparisons were made to determine if there was a relationship between the external fish mucosal sites and the BE and if so how that varied across the water filtration or rearing system. For the second experiment, fish were sampled cross sectionally at different ages including 43 dph , 137 dph , and 430 dph . Fish at 430 dph included fish sampled from an ocean net pen along with fish which were transferred from an ocean net pen back to an indoor system. For the age comparison cohort, three body sites were sampled including the gill, skin, and digesta “allochthonous” samples along with corresponding BE samples described in experiment 1. The BE “built environment” samples included tank water, inlet pipe, airstone, air diffuser, and tank side. Specifically 12 fish were similarly non-lethally sampled from three different age classes: 43, 137, and 430 dph from indoor tanks. The 430 dph fish from the indoor tank were initially reared indoor until 245 dph following methods described by Stewart Fielder et al. and then transferred to ocean netpens where they were grown for 106 days. At 351 dph, they were then transported back to the indoor system where they were held until sampled at 430 dph. An additional 20 fish at 430 dph from the seapen were harvested for another experiment and opportunistically sampled. All fish were measured for length and mass with condition factor calculated. A total of 92 fish were sampled across the two experiments.