Small farms, for example, may be less able to engage with the legal supply chain or obtain favorable pricing in the legal market, or they may systematically differ from larger farms in risk tolerance. Thus, because we are unable to directly control for these factors in the regression analysis, it is unclear which of these potentially omitted variables might be driving the size-application relationship. That ambiguity suggests a topic for future study. We also find that existing farms that expanded during the “green rush” years were more likely to apply for permits. This finding could arise via multiple pathways. Perhaps farms that expanded during this time were those endowed with, or able to accumulate, sufficient capital to enter the regulated market. Alternatively, some farms may have invested more heavily specifically in anticipation of formalization and legal marketing opportunities. We also found that farms that were established after 2012 were less likely to apply for permits, all else equal. Whether these newer farms will continue to operate illegally or abandon their operations remains unknown. Nevertheless, it suggests potential divergence in formalization strategies between newer entrants and older producers. Whether that divergence is driven by systematic differences in operators’ human capital and experience levels, in financial capital or in other unobserved factors like risk tolerance or “taste”- based considerations remains a subject for further research. Indeed, while formalization is clearly favored by larger farms, we do find evidence that smaller farms traditionally associated with Northern California cannabis production have not been completely shut out of the legal market. Though permit application rates for the smallest farms are substantially lower than those for large farms, the small farms that do apply tend to be farms with longer production histories. Our work documents permit applications at a dynamic moment in formalization,hydro tray and we suggest that the trends we have seen to this point may change going forward.

Many farms that applied for permits may not complete the application or gain approval, or may fail to receive necessary permits from state offices. Likewise, new cannabis investments continue in the county and some farms that initially resisted formalization may now decide to join the market. New cooperative businesses that specifically focus on supporting small farms are emerging, and these organizations are assisting small farmers in the permitting process. The final chapter of formalization is yet to be written.In 1953, amid reports that cannabis was growing around San Mateo County, the local sheriff’s office and the UC Agricultural Extension Service in Half Moon Bay issued a booklet entitled Identify and Report Marihuana. The booklet envisioned “total eradication” of cannabis. The authors couldn’t have imagined that, in 2017, the San Mateo County Board of Supervisors would pass an ordinance allowing greenhouse cultivation of cannabis in the county’s unincorporated areas. A lot can happen in 60-plus years — such as voter approval of Proposition 64, the 2016 ballot measure that altered California law to allow the recreational use of cannabis by adults. The measure’s passage presented policymakers with the challenge of regulating, licensing and taxing a large, complex and fast-changing recreational cannabis industry — a challenge made more acute because scientific research on many aspects of cannabis in California had never been conducted at scale. UC is now working to fill that research gap. At least nine UC research centers, most of them new, now focus entirely or in part on cannabis.That said, federal restrictions still inhibit many aspects of research . Cannabis research is also inhibited by funding constraints. The $10 million in annual research funding that Proposition 64 allocated to California universities has not begun to flow, and the Bureau of Cannabis Control — the entity responsible for disbursing the money — reports that it is still establishing guidelines for doing so. Despite these obstacles, UC cannabis research in the legalization era is well underway, as attested by this special issue of California Agriculture. The research articles presented here fall into three broad categories — research into cannabis production, into the economics of the cannabis industry in California and into the social and community impacts of cannabis.

The three articles focused on cannabis production include the results of the first known survey of California cannabis growers’ production practices, by Wilson et al. . In the article “Characteristics of farms applying for cannabis cultivation permits” , Schwab et al. combine data on cannabis farms with information about applications for cultivation permits, establishing that, of farms within the dataset, those seeking permits tended to be larger and to have expanded faster than other farms. And on page 146, Dillis et al. analyze data submitted to the regional water quality control board to characterize the water sources used by cannabis cultivators in the Emerald Triangle region . Articles focused on the economics of the cannabis industry include a study by Goldstein et al. analyzing online retail prices for cannabis flower and cannabis-oil cartridges as changes in regulation and taxation have taken effect in recent years. ValdesDonoso et al. analyze data from sources including California’s cannabis testing laboratories to estimate the cost per pound of testing under the state’s regulatory framework. Four articles explore the social and community impacts of cannabis production. On page 161, Valachovic et al. report the results of a survey of timberland and range land owners in Humboldt County, who shared their experiences with the rapid expansion of cannabis production in their region and its attendant social, economic and environmental challenges. LaChance interviewed noncannabis farmers, ranchers and others across Humboldt, Mendocino and Sonoma counties, eliciting their views on issues such as increased land prices amid cannabis legalization. For the article “Growers say cannabis legalization excludes small growers, supports illicit markets, undermines local economies” , Bodwitch et al. surveyed cannabis growers to gain insight into their experiences with the state’s system for regulation of commercial cultivation. Finally, on page 185, Polson and Petersen Rockney employed ethnographic methods to study cultivation regulations in Siskiyou County and their effects on the county’s Hmong-American community. The special issue was conceived by Van Butsic and Ted Grantham — UC Cooperative Extension specialists based at UC Berkeley — and Yana Valachovic — a UCCE forest advisor and director for Humboldt and Del Norte counties. Butsic, Grantham and Valachovic developed the issue in collaboration with Daniel Sumner, a UC Davis professor of agricultural economics and director of the UC ANR Agricultural Issues Center, and with the staff of California Agriculture. The growing controversy regarding cannabis legalization in the United States is based in part on the question of whether increased access is associated with escalations of both use and misuse, with the latter currently affecting approximately 6% of the population.

Longitudinal studies have classified young cannabis users into those who remain casual users, those who transition to moderate levels of use and remain stable, those who show initial increases followed by declines in use and, importantly, those who demonstrate accelerated use and progression to problem use. Outlining the factors that contribute to the likelihood of progression to problem use might provide insights into targets for intervention. Cannabis use and misuse are heritable . Several genome-wide association studies have attempted to identify loci that might contribute to this heritable variation. For cannabis use, the largest published study to date identified four independent genome-wide significant loci and found a genome-wide single nucleotide polymorphism heritability of 10%, suggesting that the aggregated effects of common SNPs captured a sizeable proportion of the heritability of cannabis use. Polygenic risk scores offer a complementary approach to the study of such aggregated effects. In brief, a PRS is a person-specific index of genetic propensity to a trait ; PRS are constructed by multiplying the effect size from a discovery GWAS by the number of risk alleles that an individual possesses at that SNP. PRS approaches are widely used in psychiatric genetics, including substance use and dependence, and can be used to assess whether genetic risk for one disorder or trait is associated with aspects of the same trait or with a correlated disorder/trait. For instance, one study found that PRS for schizophrenia risk predicted cannabis use in individuals with bipolar disorder. However, few studies have explored how genetic propensity to cannabis initiation influences patterns of cannabis use across development. In addition to genetic risk, affiliations with cannabis using peers are believed to be among the leading contributors to persistent cannabis use. However, results from longitudinal samples remain mixed . While peer use is readily viewed as an ‘environmental’ agent of risk, it can also represent heritable aspects of underlying behavior,planting table with at least one study suggesting a heritability of 25–28% for general peer group deviance, a broad measure including peer marijuana use. That study also found that approximately 50–78% of the genetic variance in peer group deviance was attributable to genetic factors related to cannabis use. Another study reported that the heritability of perceived peer alcohol use ranged from 7% at age 12–14 to 38% by age 18, and that the relationship between peer alcohol use and one’s own alcohol use was attributable to genetic factors with a correlation of 0.83.

Taken together, these observations raise the possibility that polygenic risk for cannabis use may interface with peer cannabis use in several possible ways, ranging from a main effect to a potential interactive effect. To our knowledge, these hypotheses remain untested. To understand more clearly the role of genetic propensity and peer use in the longitudinal course of cannabis use, we used data on 1167 individuals of European descent who were part of a large longitudinal study of the genetics of addictions. We first identified trajectories of cannabis use frequency, and then examined whether trajectory class membership was related to cannabis use PRS and/or perceived peer cannabis use when the subject was aged 12–17 years. We also examined whether the relationship between polygenic risk, perceived peer use and trajectory membership could be explained by an interaction model where perceived peer use moderated the influence of polygenic risk on trajectory membership. Results from these analyses can provide a framework for how genetic liability and peer use might interface to shape the developmental unfolding of cannabis use.There are three key implications from our study. First, we found a statistically significant association between cannabis PRS and trajectory membership, and the effect size was consistent with other PRS analyses. Thus, genetic propensity to cannabis initiation derived from a large, heterogeneous discovery sample appears to differentiate between classes derived from frequency of cannabis use in an ascertained, longitudinal cohort. Interestingly, life-time cannabis use was not significantly related to PRS. However, maximum frequency of use and DSM-5 CUD were associated with PRS in the larger sample of 1840. It is possible that even though the discovery GWAS was aimed at assessing genetic propensity to life-time use, that polygenic liability is better captured along a developmental spectrum in these data. While, to some extent, the classes differed in severity of use , associations with class membership far exceeded cross-sectional associations with CUD, suggesting that class membership in this young and ascertained sample may be a superior index of genetic propensity than cross-sectional indices alone. Secondly, the ‘environmental’ risk factor in our study, perceived peer cannabis use, explained up to 11.3% of the variance in trajectory membership. This suggests that, although genetics certainly plays a role in the progression of cannabis use, established environmental influences such as peer use are better predictors of cannabis use than PRS at the moment, and this is also likely to be true for other complex behavioral traits. Uniquely, genetic propensity to cannabis use was also associated with greater perceived peer engagement in cannabis use. Consistent with prior heritability studies, this finding of genetic contributions to perceived peer use might reflect gene–environment correlations or causal processes, such as Mendelian randomization. However, both PRS and peer use remained significantly associated with class membership when simultaneously modeled, suggesting some independent effects. Thirdly, we found no evidence that peer cannabis use is a moderator of polygenic contributions to cannabis use trajectories. Previous studies have found some evidence for interaction effects between peer substance use and genetic liabilities for substance use, but few have used genome-wide PRS to do so. Although results from the discovery GWAS for cannabis use were genetically correlated with risk-taking, we found no evidence that our measures of risk-taking were consistently related to the cannabis use PRS.