Cannabis Grow

Traditional, local, and Indigenous knowledge systems must be prioritized and valued ; according to the World Bank , communities that rely on traditional, local, and Indigenous knowledge systems, steward an estimated 80% of the world’s remaining biodiversity . Institutions, ranging from non-governmental organizations, government institutions and universities should also be included in the diversity of voices at the proverbial table of translational ecology. The components structuring the communication and engagement dimension of my research was rooted in network building and linguistic competency. My research evolved from communication and direct engagement with various entities, which began from my own network – the Ukrainian-American community in Washington D.C. It was through this network that I was put into contact with a friend of a friend who was as Fulbright scholar, Yurij Bihun. His guidance and mentorship connected me to individuals at the Ukrainian National Forestry University which later served as my host institution during my Fulbright student award . Once in Ukraine, I spent 4 months grounding myself in this new context, meeting new people, and establishing key contacts. I met the head of the World Wildlife Fund Ukraine , Dmytro Karabchuk. He invited me to attend various conferences sponsored by WWF-Ukraine and I had an opportunity to edit WWF-Ukraine’s illegal logging assessments. It was also during this time that I had an opportunity to travel extensively throughout the Hutsul and Zakarpattia regions with the facilitation and guidance of Yurij Bihun to meet with NGOs, like FORZA,4×8 grow table with wheels and key scientists at the Carpathian Biosphere Reserve before the start of my research process.

Many professors at UNFU connected me with his own contacts in the Hutsul Carpathian Mountains. It was through these various contacts that I found a place to live in the Carpathian Mountains, providing a base point to build relationships with other community members throughout the region as well as park at the Verkhovyna National Nature Park and the Hutsulshchyna National Nature Park. Those first four months were pivotal, where I relied on previously built networks , to expand and make new networks , Ukrainian National Forestry University, Verkhovyna National Nature Park, Hutsulshchyna National Nature Park which greatly aided in the research process and connecting with village community members. The building of these relationships was in many ways contingent on my linguistic fluency of Ukrainian and my understanding of worldview, culture, and day-to-day life. It is through language that culturally distinctive values, knowledge, meanings, and world views emerge . My ability to speak and understand Ukrainian was a starting point to many discussions with new colleagues and collaborators, which created an opening and opportunity to share my personal story. In many ways, engagement and collaboration was the first step in trust-building, and this was brokered by linguistic competency. However, when I first arrived in Ukraine, the shift to my daily routine to speaking primarily in Ukrainian presented its own set of challenges. I had to learn how to distinguish the type of vocabulary I knew versus the one I would need to learn . This learning curve extended its way to living in Hutsul villages for over the course of a year, where elder generations spoke a mix of Hutsul and Ukrainian. Hutsul is a unique dialect that is endangered due to socio-economic pressures . In many instances, Hutsul is indistinguishable from Contemporary Standard Ukrainian . This mutual intelligibility created an opportunity to learn Hutsul vocabulary and connect with community members in their language, grounded in their place.

My goal was to amend my research questions and methodologies to address and include Hutsul TEK as a central part of the process. Engagement occurred at multiple levels – from community members from various villages, national parks , educational institutions , and international institutions . I lived with families in Hutsul villages, where I was able to spend time talking to families that I was living with, asking about their community needs and day-to-day life. Additionally, I spent time speaking to a range of scientists at the Hutsulshchyna National Nature Park and Verkhovyna National Nature Park about illegal logging issues and community development goals. This would include formal meetings, but mostly hiking trips, discussions over tea, and various field trips. This engagement continued throughout the interviewing process. Before beginning interviews, I worked with key Hutsul experts to refine specific interview topics and improve question framing. I gathered over 70 interviews throughout two field seasons, and in the field season of 2019, Hutsul mycologist, Mariia Pasailiuk, greatly aided me, actively interviewing prominent community members with me. Various trips with scientists at the Hutsulshchyna National Nature Park occurred throughout 2017-2018, assessing old growth forests. Maintaining continual dialogue with people included visiting their homes, making phone calls, and providing open avenues of discussion and availability. These connections and continual active engagement were pivotal in the research and collaboration process .The main goal behind the translational approach is to produce policies based on transparent co-production of knowledge by all stakeholders impacted by those same policies .

Language plays a role in the development and understanding of policy to broader audiences. The term ‘translation’ in translational ecology refers to the interpretation of meaning from one language to another, with the goal of conserving the integrity of information in addition to being open to possibilities of varying interpretations . The ability to translate science into understandable terms to various stakeholders is imperative to generating communicable policy grounded in mutual understanding. Additionally, careful attention and understanding to multi-cultural, real-world contexts in which ecological science is applied, are essential to the framing and designing of research questions, and successful implementation of policy decisions and management. For example, ecologists can advocate for science-informed policies and, depending on their research scope, follow the CARE principles for Indigenous Data Governance by ethically prioritizing TEK that community partners contribute . Otherwise, there is the real possibility of generating “paper policies”, which are written but are not fully integrated, followed or supported by communities. The status of policy making in Ukraine is tenuous, given its legacy of Soviet colonialism and corruption. Environmental policies struggle to be enforced, with illegal logging being a main regional challenge. Organized criminal networks manage illegal logging operations under the guise of semi-legitimate corporations and businesses . Minimal legal and financial penalties make these unenforced activities accessible within organized crime networks. However, local national parks and World Wildlife Fund Ukraine are using multi-time satellite images, DNA, and isotope analyses of wood, along with citizen activism, to help combat illegal logging . Starting in 2020, the WWF-Ukraine is working with local communities to protect forests, while collaborating with forest enterprises to sustainably manage forests . There is an active shift within the region to include communities in the decision-making process, and prioritize their active participation in addressing social and environmental issues. One of the ways to make meaningful policy is to form research questions that address a need or find an already existing question that needs answers. My research questions changed and morphed throughout my dissertation process, as I learned more from elders and as I built relationships with various institutions. In many cases, I had already built relationships with people before formally interviewing them later. Traditional ecological knowledge was the central theme, and conversations were open-ended. There were many days in which I spent an entire day with a community member in their home, eating, drinking,grow tray stand and talking about a range of topics. I conducted a few informal discussion groups both formally and informally regarding changes seen in the region as well as the specific gathering practices of culturally important species. Environmental changes came up continuously in discussions with park scientists, elders, community members, herbalists, and farmers. Reiterated continuously was the direct link between forest dependence on resources and proximity to habitats. This pattern of discussion helped to form my questions and guide my discussions with personnel at local national parks. One of the main efforts behind my dissertation work was to co-publish with Hutsul scientists, facilitating the dissemination of knowledge on their terms, rather than on researcher terms. Currently, the last chapter of my dissertation, which was co-created by two Hutsul scientists along with myself, is under review. It synthesizes my second chapter along with in-depth analysis of TEK to explore factors contributing to Hutsul regional resilience. Additionally, it clearly identifies coping mechanisms and adaptive strategies that maintain food sovereignty in the region. That chapter will serve as published affirmation of the importance of Hutsul ethnobotany in regional economy building. The next step after publication in English would be publication of this paper in Ukrainian and Hutsul, since it would then be accessible to populations in which aided in the publication of this work. There are various levels of translation that occurred through my dissertation process – from Ukrainian/Hutsul to English and vice versa, in addition to translating scientific terminology to understandable and relatable terminologies in both languages. These non-English publications would look very different from their current English form, given the need to translate not only the data, but also to use terms, sentence structure, and images which would be accessible, relatable, and recognizable to broader populations in Ukraine. Ample time and multiple levels of translation would occur in the making of this Ukrainian and Hutsul publications.

This translational approach would reseed organized information surrounding Hutsul TEK back into the communities of origin, helping build trust with communities and instill transparency in the research process. The publication of the third chapter will serve as basis for policy development in Hutsulshchyna; a policy document is currently being written by Hutsul scientists, Maria Pasailiuk and Oleh Pohribnyi, at the Hutsulshchyna National Nature Park, highlighting the importance of gathering and selling culturally important species .Education is a process that invites an individual to explore and build upon their prior knowledge, while actively engaging and contextualizing new information into an existing framework of understanding. This dynamic process occurs both organically and intentionally through lived experiences and reflection. Education in the research process is resilience building,by creating awareness, supporting co-production of knowledge, and encouraging integration of community-driven, evidence-based practices . The dimension of education is central to collaborative research processes, as a way to effectively communicate and address needs, world views, and priorities of multiple stakeholders. In order to address my own knowledge gaps of the region, and community needs, it was imperative to interact with community members and educate myself before the research process began. I addressed my lack of practical knowledge of landscape, day-to-day challenges in Hutsulshchyna, and current institutional culture with a three-pronged approach: 1) reading and attending lectures and conferences, 2) extending my immediate network of people to include a variety of voices, and 3) living in the region. Firstly, I attended lectures, gatherings, and conferences sponsored by the Ukrainian National Forestry University, Hutsulshchyna National Nature Park and WWF-Ukraine. These opportunities allowed me to meet people and ask questions regarding specific environmental threats and policy needs and to gain a broad perspective on the institutional work being done in Ukraine. On a local level, I gathered books on history, forestry, and ecology and spent ample time at the Kryvorivnia village library with the head librarian, Katya. Additionally, I befriended a Peace Corps volunteer, Jesus Segovia, who had already spent two years as an educator in the Carpathian Mountain region, who provided great support and extended his network to me. Lastly, I addressed my lack of understanding of day-to-day challenges for Hutsul community members by engaging with community members every day while living in various villages with community members over the course of the year. Educating myself, reaching out to people, and actively listening to others was key to beginning the collaborative process with community members, in a culturally relevant way . One of the main cultural shifts that occurred during my fieldwork season was the broadening in my understanding in how time is experienced and perceived. Within the field of anthropology, culture is noted as the learned foundation of collective and individual assumptions, beliefs, values, priorities, and behaviors within a population over time . Cultural world views are the foundations of values, beliefs, and assumptions that guide our everyday behavior. Much of this is unnoticed unless we stumble upon a situation that interjects or presents another worldview in contrast to our own worldview. I encountered many of these insightful interjections in my fieldwork experience and they were central to how I approached my research process.

The negatively correlation between latitude and THC and CBD contents supported by a study reported that latitude decreases can result in cannabinoids level reduction, and plants from high latitudes exhibited a low ∆9-THC. Moreover, this study indicated that the populations at the high elevation showed a trend towards lower concentrations of THC and CBD. For example, Sam-01 at 1858 m above sea level had lower cannabinoids, and Dez01, Dez-02, and Bsh-01 at a low elevation had higher amounts of THC and CBD compared to other locations studied. The two populations located in the warmest state of Iran, including Dez- 01 and Dez-02, had the highest concentrations of THC, consistent with the positive effect of temperature on cannabinoid accumulation and growth. Overall, these results showed that environment is also likely to play a role in cannabinoids concentration, suggesting that controlled environment studies or multi-year trials should be completed to further elucidate the importance of these G × E interactions. Fresh plant materials were air dried at room temperature in darkness for up to 14 d until the leaves become brittle. The drying time varied depending on inflorescence density: plants with compact and tight buds took 14 d, whilst plants with branched buds with space between branches were dried after 7 d. At this stage, the water content of the plant materials was approximately 10%,grow rack which was uniform for all populations. Coarse dried female flower buds were then selected, crumbed, and pulverized until ensuring accepted tolerance homogeneity of the samples.

After testing different protocols, sonication was found to be the best process to agitate samples for cannabinoid extraction. Thus, 50 mg of fine tissue powder was weighed and extracted with 2 mL of a mixture methanol/chloroform by sonication for 40 min and centrifugation at 10,000 rpm for 15 min at 10 ◦C. The upper phase was separated overnight to evaporate the solvent, and residue was dissolved in 1 mL of HPLC grade MeOH. In order to filter the extract, centrifugation was performed at 13,000 rpm for 10 min. Finally, the supernatant was transferred into an amber vial and 20 µL applied for injection to HPLC apparatus. Starting a successful breeding program in cannabis using a new elite germplasm requires profiling of cannabinoids and terpenes in selected superior chemotypes that harbor ideal morphological characteristics for diverse needs to develop hybrid seeds. A deeper insight into the patterns of recreational, industrial, and medical cannabis use is a high priority for both public health and industry. So far, there is still a great lack of information about chemical composition and cannabinoids profile of Iranian cannabis populations in terms of THC and CBD contents. The present study as a first survey provides a deep insight into THC and CBD profile of 20 natural dioecious cannabis populations morphologically distinct from various geographical regions of Iran and the plausible correlation of these contents with environmental and geographical conditions of regions of origin. The results showed that diverse THC and CBD contents both between and within populations represented three chemical phenotypes as type I , type II , and type III . Ard-01 with THC/CBD ratio of 1 was chemically distinct, which may increase the capacity of commercialization and medical industries. The THC content of all plants of population Sam-01 characterized with THC level ≤ 0.3% contribute to increase the potential of law enforcement programs in Iran.

Additionally, differences in unique and important morphological features of this collection may indicate the difference in their chemical type. Correlations between geography and climate of site of origin were also identified, suggesting that both THC and CBD production were positively and negatively correlated with temperature and latitude, respectively, but more research is required to tease apart these G × E interactions more fully. In conclusion, our study unravels the natural diversity to delineate cannabis resource with variations in THC and CBD contents and morphological traits, providing a foundation to initiate breeding programs in Iranian cannabis towards different industrial and medical purposes. Therefore, this study will promote future possibilities for the burgeoning cannabis industry in Iran. Traveling over the ridges and through the fertile valleys of Humboldt, Mendocino and Sonoma counties, one encounters a variety of farms, ranches, wineries and farm stands — and now a proliferation of cannabis industry billboards. Touting cannabis appellations and the ease of acquiring cannabis goods and services, their message is loud and clear: legal recreational cannabis has arrived. As the cannabis sector has come fully into public view, so too has its interaction with non-cannabis agriculture. In Humboldt, Mendocino and Sonoma counties, as in other California counties, cannabis regulations over the expansion of recreational cultivation are still being refined. The uncertainty about how they will impact local economies, environments and communities is also affecting the non-cannabis agricultural community. The changes farmers and ranchers will undoubtedly face are situated within broader questions about farmland transitions in the United States.Across the United States, farmland is increasingly subject to financial investment and speculation. Research suggests that financial investment in the food system has already had considerable impacts on food production in some regions, including investments in farmland, food processing, agricultural inputs and more .

Questions of scale and implications of ownership have long been a focus of agricultural research, as these factors clearly shape farming communities and can lead to negative socioeconomic and community outcomes . In some rural areas of the United States, outside financial investors have caused land values to rise and increased farmer tenancy while decreasing farmer ownership. U.S. Department of Agriculture statistical data confirm this trend in California; many counties have seen an increasing amount of both rented land and non-operator landlords — common indicators of financial investment in farmland . Other research has reported on these trends, particularly how financial actors — from hedge funds to university endowments — have acquired farmland across the United States . The expansion of recreational cannabis production in Northern California intersects with this trend. Articles have highlighted entrepreneurs developing industrial-scale cannabis farms in the Central Coast , rapid consolidation of cannabis markets across North America and large corporate alcohol interests — Constellation, Molson Coors and others — investing billions of dollars in the cannabis industry . Outside investments in land can amplify the challenges food producers face. Already in much of California there is a history of significant land use change and crop regime shifts . Particularly in Northern California, food producers have experienced the effects — for example, Sonoma County apple growers have been impacted by the arrival of grapes and a related increase in farmland prices. More broadly, conventional growers in California have been impacted by organic production increasing the price of farmland . But grapes and organics are not directly analogous to cannabis. Until recently, cannabis had never legally been grown for recreational use on California land zoned for agriculture; it was instead part of the counterculture .The uncertainty being experienced in the non-cannabis agricultural community also extends to environmental concerns. Reports have been published about rodenticide poisoning and excessive irrigation use in cannabis ; furthermore, recent research described how despite the overall small footprint of cannabis production on the landscape, it can have significant negative impacts, including to landscape fragmentation and important ecosystem processes . The shift to legal production of recreational cannabis brings with it a chance to create environmental standards for the industry. Regulations might begin to curtail negative environmental impacts as producers transition into the legal framework. Furthermore, now that production has been legalized, some non-cannabis growers might choose to diversify their agricultural operations to bring an influx of new revenue. A recent article asked whether Ukiah, in Mendocino County, could become the “Napa of pot” .As cannabis development continues and counties negotiate policy and regulatory decisions,greenhouse grow tables it is vital that evidence of impacts and opportunities be collected and that community members, including non-cannabis farmers and ranchers, maintain a voice in the negotiations. My research project was undertaken to better understand and articulate the farming and ranching communities’ perspectives and needs post Proposition 64 in Northern California. It was born out of conversations with UC Cooperative Extension specialists who noticed an increased frequency with which the non-cannabis farming and ranching communities discussed interactions with the cannabis sector surrounding the passing of Proposition 64. Of specific interest was how these interactions were being talked about at food policy council meetings in Northern California. At the outset, it was clear that these conversations covered a spectrum of opinions ranging from apprehension to optimism.

It was also clear that while the division between the cannabis and non-cannabis communities was not always completely transparent — in some cases, non-cannabis farmers may at times have grown cannabis on the side — this framing was useful for beginning to understand key themes related to what could be a divisive topic. The project took place in the summer and fall of 2017, and it was completed before Jan. 1, 2018, when legal recreational cannabis cultivation began. Research was approved by the UC Berkeley Committee for Protection of Human Subjects Institutional Review Board, Protocol ID 2017-05-9973. Humboldt, Mendocino and Sonoma counties were selected because they approximate a gradient of food production versus cannabis development, include a diversity of food and fiber production, and adopted different regulatory frameworks for recreational cannabis. Livestock is the largest agricultural enterprise by gross production value in Humboldt County, and wine grapes are the main enterprise in Mendocino and Sonoma counties . Average farm size in Humboldt and Mendocino counties is similar, around 630 acres; in Sonoma County, there are many more farms and the average size is 165 acres . In terms of acreage, all three counties have most land farmed as pasture . Information about land use and top-ranked non-cannabis crops produced in each of the three counties is provided in figures 1 and 2 and table 1. These figures and tables are from 2016 county-level crop reports that track agricultural commodities, which do not include cannabis. At the time of this research similar data on legal recreational cannabis was not available, and collecting information such as historical production trends and the identity of cannabis growers was not the focus of this research. To date, USDA census of agriculture data does not exist, as cannabis remains federally illegal. I conducted preliminary interviews with UCCE and related agricultural professionals to develop research questions before interviewing 24 key informants across the three counties. The interviewees were selected to include a wide range of people familiar with cannabis and agricultural trends in the region but especially those who were closely connected to the policy making and regulatory process: they included state and county officials involved in agriculture, cannabis regulation, planning, building and zoning; realtors; food policy council members; members of prominent farming and ranching organizations and agriculture and ranching– related nonprofit organizations; and other key agricultural community members. Interviews were open ended, semistructured and generally lasted 1 to 2 hours. I asked questions about access to land and other resources, trends in investment, change to land use and natural resource use, and the character of the county’s agriculture and ranching . The interview recordings were transcribed and analyzed for key themes using NVivo qualitative data analysis software ; then interviews were coded and representative quotations selected as evidence. A range of perspectives from these findings are summarized in table 3. Four main themes emerged.The research findings suggest that a range of interactions have been evolving between cannabis growers and non-cannabis farmers and ranchers in Humboldt, Mendocino and Sonoma counties. The non-cannabis sector has faced many new challenges and uncertainties during the process in which recreational cannabis transitioned to legality. Accordingly, interviewees continued to express mixed feelings about how these actions would continue to unfold. The comparison of cannabis growing to vineyards, while imperfect, was nonetheless generally useful for interviewees to begin to picture what types of landscape and community changes could come about, particularly in Mendocino and Sonoma counties. Lessons may be gleaned from the precedent of transitions to wine grape vineyards, and may be used to inform policy and community approaches to both harmonizing and mitigating impacts of cannabis on non-cannabis communities. For example, when considering Sonoma’s transition to wine grapes and the correlating increase in farmland prices, it would be useful to identify what strategies non–wine grape producers relied on to keep farming non-grape crops, and whether certain producers found ways to subsidize non-grape crops .

As voters in Arkansas, Florida, and North Dakota approved the ballots for medical marijuana legalization in November 2016 , approximately 60% of the population in the U.S. now lived in states that permitted marijuana use for medical purpose. Despite the increasing support from the public, the scientific research on the public health impacts of medical marijuana legalization has not reached a consensus. Existing evidence primarily concentrated on the changes in the prevalence of marijuana use and provided mixed findings . The use prevalence, however, is arguably not the greatest public health concern. While occasional use is not without health risks, marijuana is most harmful to regular users and early initiators and largely harmless to most occasional users . Research on stronger indicators of adverse effects of medical marijuana legalization is needed. Given that marijuana is not directly associated with mortality , hospitalization probably represents one of the most serious health consequences of marijuana, which imposes substantial economic burdens to the healthcare system and the society . No previous studies have investigated how medical marijuana policies were associated with marijuana-related hospitalizations. In parallel to the heated debate on marijuana legalization, there were overwhelming concerns about the epidemic of opioid pain reliever abuse and overdose. In the last two decades,cannabis dry rack the mortality rate related to OPR overdose and the quantity of prescribed OPR at least quadrupled in the U.S. . In 2014, more than 14,000 deaths were related to OPR overdose . States have advocated or adopted a series of policies to combat this increasing trend, such as prescription drug monitoring programs and regulations of pain management clinics.

The positive effects of these policies on reducing OPR-related outcomes were reported by some studies but not all . Recent studies started to investigate whether medical marijuana legalization would have any influences on the OPR abuse and overdose epidemic. Marijuana has therapeutic effects for chronic pain and is being used by patients prescribed with OPR. If the patients with legitimate prescriptions for OPR were substituting OPR partially or entirely with marijuana, the increased availability of marijuana as a result of medical marijuana legalizations may reduce the risks of OPR-related health consequences. On the other hand, marijuana use for recreational purpose may serve as a gateway drug to OPR and increase the risk of OPR initiation . Should medical marijuana policies have any impacts on marijuana use for medical or recreational purpose, they may unintentionally lead to changes in OPR use and related hospitalizations. Four recent studies reported reduced OPR-related outcomes in association with medical marijuana legalization , but the evidence is still limited. The objective of this study is to examine the associations between medical marijuana legalization and hospitalizations related to marijuana and OPR. Using state-level administrative records of hospital discharges from 1997 to 2014, we focused on the severe health consequences of medical marijuana legalization and exploited the variations of policy implementation in different states at different times. This study is expected to add to the still-limited literature regarding the intended and unintended impacts of medical marijuana legalization and provide implications to OPR policy making. Annual state-level hospitalization data were obtained from the State Inpatient Databases .

Developed for Healthcare Cost and Utilization Project and sponsored by the Agency for Healthcare Research and Quality , the SID provide administrative records of hospital discharges in community hospitals in participating states. The SID cover the universe of non-federal, short-term, general and other specialty hospitals, regardless of funding sources, as well as the universe of hospitalized patients aged 18 years or older, regardless of payer . Containing approximately 97% of all hospital discharges in a state , the SID offer an almost complete overview of state-level hospitalizations. The advantage of using hospitalization records is to represent objective measures that are free of self-reporting biases commonly seen in survey data. The annual SID data were obtained for 18 years between 1997 and 2014. The 14 states that did not participate in the SID as of 2014 were excluded from the study; these states were Alaska, Alabama, Connecticut, District of Columbia, Delaware, Georgia, Idaho, Louisiana, Mississippi, Montana, Ohio, Pennsylvania, South Dakota, and Virginia. We further removed 10 states from the main analysis, because they do not have full-year observations in the SID before or after implementing medical marijuana policies. The main analysis included 27 states. We utilized all the years available in the SID for these states with the only exception of Colorado, which implemented recreational marijuana policies at the beginning of 2014. The 2014 Colorado SID data were therefore removed to avoid potential confounding from recreational marijuana legalization. The number of years that a state had the SID data available varied; on average, a state had 14 observations during the study period. There were 382 state-year observations included in the main analysis.

Data availability and inclusion and exclusion of states were described in detail in the supplementary material1. The effective dates of marijuana- and OPR-related policies were obtained from various sources of legal and policy reviews, including RAND Corporation , the Policy Surveillance Program at Temple University , National Alliance for Model State Drug Laws , and Centers for Disease Control and Prevention . The effective dates of these policies for the study sample can be found at the supplementary material1. State socioeconomic data were obtained from Census, Bureau of Labor Statistics, and Tax Foundation. The outcome variables were annual rates of hospitalizations related to marijuana and OPR. Specifically, we used International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] to define 3 types of hospitalizations: those involving marijuana dependence or abuse , those involving opioid dependence or abuse , and those involving OPR overdose . We searched diagnosis codes in all-listed diagnoses including principal diagnosis as well as additional conditions diagnosed at admissions or stays. During 1997–2014, the 27 states had 2.2 million hospitalization records involved with marijuana dependence or abuse, 2.2 million records involved with opioid dependence or abuse, and 0.4 million records involved with OPR overdose. To account for the variations in healthcare utilization across states, we standardized hospitalization rates as the number of discharges for a specific category per 1,000 discharges. We assessed the implementation of medical marijuana policies, the primary policy variable of interest, in three ways. It was first coded as an indicator to represent the presence of medical marijuana policies in the state and year. All the years prior to the implementation year were assigned with value 0, and all the years after the implementation year were assigned with value 1. The value for the implementation year was coded as the number of months adopting the policy divided by 12 months to represent partial year of policy implementation . Among the 27 states included in the main analysis, 9 states implemented medical marijuana policies between 1997 and 2014 . In the second analysis, we allowed for independent effects of permitting medical marijuana dispensaries, the major and most common provision of medical marijuana policies . The open dates of the first operating medical marijuana dispensary in a state were used to code an indicator for the presence of medical marijuana dispensaries in the state and year. Among the 9 states that implemented medical marijuana policies in our sample, 8 states had operating medical marijuana dispensaries during the study period. The third model added 1-year, 2-year, and 3-year leads and lags to the contemporary indicator of medical marijuana policy implementation. Adding the series of leads allowed us to test the assumption about identical counterfactual trends in the states adopting and nonadopting medical marijuana policies . The significant associations, if any, trimming tray will indicate that the implementation of medical marijuana policies endogenously responded to the marijuana or OPR outcomes. If no significant effects are found, any variations in the outcomes can be interpreted as the results of exogeneous policy shocks rather than some preexisting differences between states adopting and non-adopting the policies. Whereas adding lagged effects allowed for the detection of heterogeneous policy effects at different time points after policy implementation. In all the regressions, we included 3 additional time-varying state-level policy variables related to marijuana or OPR: the indicator of marijuana decriminalization, under which marijuana use is illegal but controlled by non-criminal statues and exempt from criminal processing and consequences ; the indicator for the presence of prescription drug monitoring program; and the indicator for the presence of pain management clinic regulation. Other time-varying state-level factors that may influence marijuana or OPR-related hospitalizations included population size, unemployment rate, median household income in constant 2014 dollars, beer tax rate per gallon in constant 2014 dollars, and uninsured rate.

We assessed collinearity of these variables by variance inflation factors and no collinearity was found.We plotted the average hospitalization rates related to marijuana or OPR by year and compared them between the states that did and did not implement medical marijuana policies during the study period. The unit of analysis was the state-year observation. We assessed the associations between medical marijuana policy implementation and hospitalization rates using linear time-series models with two-way fixed effects. Year indicators were included in all the models to account for unobserved year fixed effects that were common to all the states at the same time, for example, the reformulation of OxyContin. State indicators were also included in all the models to account for unobserved time-invariant factors at state-level, such as social norms. The annual hospitalization rates were log transformed to address right skewness and improve ease of interpretation. The coefficients of policy indicators therefore represented the average percentage difference in hospitalization rates between the periods before and after the policy implementation, controlling for contemporaneous variations in the states that did not adopt the policy. Hospitalizations for marijuana dependence or abuse, opioid dependence or abuse, and OPR overdose were examined in separate regressions. In addition to the three models that included different forms of medical marijuana policy indicators, we performed a series of robustness checks. First, we replaced the policy implementation date with the policy passage date to identify the presence of medical marijuana policies. Second, we conducted specificity tests by estimating the associations between medical marijuana policies and hospitalization rates of two diseases that are not directly related to marijuana : heart disease and septicemia . Third, we identified hospitalizations using principal diagnosis codes instead of all-listed diagnoses. Because cases with principal diagnoses identified as marijuana dependence or abuse were insufficient to provide statistically meaningful information, we restricted this sensitivity analysis to OPR-related hospitalizations only. Last, the 5 states that legalized medical marijuana in the last year of the study period and had partial year of post-policy observation were added as states adopting medical marijuana policies in the regressions. Because the SID provide a census of hospital stays in a state, the data were not weighted. The standard errors in the regressions were clustered at state level to allow for intrastate correlations. All the statistical analyses were conducted with Stata 14 in 2016. The IRB review was waived by the University of California, San Diego because all the data are secondary, de-identified, and publicly available. Figure 1 demonstrated time trends of hospitalization rates without any adjustment. During 1997–2014, the average hospitalization rates related to marijuana and OPR increased dramatically by approximately 300% in states that did or did not implement medical marijuana policies. In these 18 years, the average hospitalization rates increased from 4.49 to 16.04 per 1,000 discharges for marijuana dependence and abuse, from 5.14 to 15.15 per 1,000 discharges for opioid dependence and abuse, and from 0.47 to 2.10 per 1,000 discharges for OPR overdose. It appears that the gaps in hospitalizations involving marijuana dependence and abuse were continuously widened between the states adopting and nonadopting medical marijuana policies with states adopting medical marijuana policies increased more sharply. Throughout the study period, the states with medical marijuana policies continuously had higher rates of hospitalizations related to opioid dependence or abuse. Hospitalization rates related to OPR overdose were originally higher in the states with medical marijuana policies, but increased less rapidly compared to the states without medical marijuana policies. Table 1 reports the associations of hospitalizations to the indicator of medical marijuana policy implementation, controlling for time-varying marijuana-related policies, state-level socioeconomic factors, and state and year fixed effects.

This CI reduction stems from assumed industry-wide adoption of CCS as well as increases in volumes of sugar ethanol in the near future and cellulosic ethanol toward the end of the decade. Therefore, we consider a scenario in which the ICS CI projections are realized. We refer to these set of assumptions as A3 in Table 12. In addition to ethanol, the future path of the CI value for BBD is uncertain, as previously mentioned. We consider a scenario in which the volume-weighted average CI rating of BBD rises from its current level of approximately 32 to 50, a rating more commensurate with soybean oil feed stocks. This represents a future in which soybean oil makes up the majority of the BBD feed stock pool, to provide a bound of uncertainty in this parameter. This is assumption A4 in Table 12. Beyond the four scenarios presented in this paper, we considered adjusting other assumptions in our analysis; none had a qualitatively different impact on the implied BBD blend rate results. For example, a scenario where a cleaner electricity grid is achieved, resulting in a grid-average CI reduction for electricity, as would occur as renewables’ penetration continues, did not substantially impact results. Even with a zero CI rating for electricity over the compliance period had only small impacts on the implied BBD blend rate required for compliance. CI rating improvements for electricity are diluted relative to those for other fuels due to the relative efficiency of electricity, measured by the EER. Similarly, additional penetration of biogas with a substantial negative CI rating due to methane capture, into the natural gas used as a transport fuel did not have a large impact. Other potential scenarios that may be salient to LCFS compliance,greenhouse benches such as expanded use of book-and-claim for low-CI rated electricity and biogas elsewhere in the production process, are left to future research.

Here we present the output from four different compliance scenarios and discuss their differences from the baseline. In each scenario, we calculate the volume of CARB diesel, BBD, and the resulting implied blend rate of BBD in the diesel pool using , , and , respectively. Figure 22 shows the implied blend rate resulting from the baseline scenario and Figure 23 shows the blend rate under the alternative scenarios. For brevity, we present only the implied blend rates here, but the volumes of BBD and CARB diesel resulting from each scenario can be found in the appendix Figure A-6. Because we force annual compliance, the annual quantities of BBD and ULSD, and the implied BBD blend rates, in the figures are conditional on compliance in the previous year. Due to the decreasing CI standards, shown in Table A-6, this characteristic has important implications for interpretation of our results; all else equal, BBD production shifted from one year to the next will earn fewer credits since the CI rating will be closer in magnitude to the standard, and the yet-to-be displaced diesel would earn more deficits as its CI rating falls farther above the standard. Therefore, if the path of any of the blend rates pictured in this section weren’t met in early years, the implied blend rate required for compliance in later years would rise disproportionately more. In that sense, all of our scenarios depict a lower-bound of BBD implied blend rates needed for overall compliance over the eleven-year span. The annual compliance constraint also abstracts away from real-world optimization decisions on credit banking and deficit carryover. We did not model a proposed provision for credit borrowing.Figure 22 shows that, under the baseline scenario, the median outcome calls for an increase in the BBD blend rate from the 2018 level of 17% to 70% in 2030.

In nominal terms, given our demand projections, this outcome implies ramping up BBD consumption in the state to 3.5 billion gallons in 2030, nearly a 300% increase from current levels, and a reduction in CARB diesel consumption to 1.7 billion gallons in 2030, more than a 50% reduction below current levels. Our median baseline scenario results in a BBD blend rate in diesel fuel similar to the high demand/low EV scenario in CARB’s ICS, which is the highest among their four scenarios. Shown by the dashed lines in Figure 22, 90% of the blend rates from our simulations fall between 60 and 80 percent BBD in 2030. Next, we alter our baseline assumptions one by one and observe how the implied blend rate required for annual compliance changes. Figure 23a shows that allowing for the largest number of credits from the other sources in the ICS in each year would result in a blend rate of 50% BBD, rather than 60, for the median draw from the simulations. Thus, the range of possibilities for the other pathways makes only a small difference to the BBD required to meet the standard. Thus, although pathways such as renewable natural gas, off-road electricity, CCS and innovative crude production at refineries, alternative jet fuel, and hydrogen receive significant attention in LCFS policy discussions, their influence on compliance scenarios is relatively minor, as considered in the ARB scoping plan modeling.In contrast, rapid EV growth has the potential to reduce the blend rate below 25% in 2030, as shown in Figure 23b. This is by far the largest reduction from the baseline in any of our scenarios, and it is the only scenario that projects compliance without dramatic changes in the diesel pool. The median required BBD blend in 2030 is approximately 20%, and the 90% confidence interval ranges from 12% to 27%. Scenarios A3 and A4 move the difficulty of compliance in opposite directions. A declining ethanol CI rating, due to CCS and increases in cellulosic and sugar ethanol volumes, would reduce the pressure on BBD production. Figure 23c shows that the median draw would have a BBD blend rate of approximately 45%, compared to 60% in the baseline.

The lower bound of the 90% confidence interval is 37%, which is double the current BBD blend rate. On the other hand, if the CI rating for BBD were to increase due to insufficient availability of low-CI feed stocks such as used cooking oil and a corresponding shift towards soybean oil, then the median BBD blend rate would need to rise to 90 percent in 2030 to achieve compliance, as shown in Figure 23d. The upper bound of the 90% confidence interval exceeds one, which means that compliance would not be achieved even if every on-road diesel gallon was 100% BBD. We have no reason to believe that one of A3 and A4 is more likely than the other. These two scenarios can be viewed as a widening of the baseline confidence interval to include possibilities that are both more optimistic and more pessimistic for compliance.The California LCFS sets out to achieve a 20% reduction in carbon intensity in the state’s transportation sector below 2011 levels by 2030. Reaching the standard will require dramatic changes in the fuel mix in California, but the relative push needed from individual fuel sources is uncertain and will depend upon both demand and supply factors over the next decade. One of the most critical aspects of understanding compliance is future demand for fuel; the demand for LCFS credits will be explicitly tied to consumption of gasoline and diesel fuel in the state. Therefore, we estimate a distribution of fuel demand under business-as-usual uncertainty, i.e. the continuation of historic trends, in order to estimate a distribution of demand for LCFS credits over the 2019-2030 compliance period. We estimate that gasoline and diesel will generate between 320 and 410 million metric tons of deficits in the LCFS program over the eleven-year period. In 2018, a total of 11.2 MMT credits were generated. For context, if the lower-bound of the distribution of credit demand were realized,growers equipment the market would need to supply 29 MMT credits per year on average, nearly a 170% increase from 2018 levels. State policies such as those targeting VMT and efficiency standards, represent a separate source of demand uncertainty, although the BAU uncertainty embraces a wide range of potential trajectories for each measure. On the credit supply side, uncertainty surrounding compliance stems from the unknown future market penetration of alternatives to the internal combustion engine, such as electric vehicles, as well as uncertainty around adoption of technologies such as carbon capture and sequestration . We assume the marginal compliance fuel in the LCFS is biomass-based diesel and we show that BBD’s role in compliance could vary widely depending on, in addition to BAU demand conditions, the pace of EV adoption in the state.

The adoption of CCS and other CIreducing technologies and the market for feed stocks used to produce BBD also could have significant effects. In our baseline scenario for credit generation, LCFS compliance would require that between 60% and 80% of the diesel pool be produced from biomass. Our baseline projections have the number of electric vehicles reaching 1.3 million by 2030, however if the number of electric vehicles increases more rapidly than what is captured under BAU conditions and reaches Jerry Brown’s goal of 5 million vehicles by 2030, then LCFS compliance would require substantially less biomass-based diesel. Under this scenario, annual compliance could be achieved with between 10% and 25% biomass-based diesel in the diesel pool, which is commensurate with recent levels and could be achievable with an indexed $200 credit price through 2030. Outside of rapid ZEV penetration, hitting 2030 targets with the $200 credit price may be much more difficult. For instance, a scenario in which CCS is widely adopted in ethanol plants would bring the median BBD blend rate down to approximately 45% BBD in 2030, rather than 60%. However, a 45% blend rate in 2030 under this scenario still results in nearly a 125% increase from current levels. Additionally, if increasing BBD production calls for an increasing level of higher-CI feed stocks, the implied blend rate required for compliance could increase above the baseline. If the volume-weighted average CI rating of BBD were to increase only to 50, the median draw requires nearly 100% of diesel to be biomass-based. Since 2016, ARB has expanded credit generation opportunities in the program, and some opportunities are relatively new. This study provides a range of the magnitude of credit generation, under uncertainty, that such expanded opportunities would need to provide to appreciably change the compliance outlook from one more to one less reliant on cost containment mechanisms. New mechanisms to allow firms to generate credits by building electric vehicle charging stations or hydrogen fueling stations have minor implications for overall compliance. This mechanism represents a major departure from the original design of the LCFS as it does not directly subsidize the consumption of a low carbon fuel. Rather, the credits subsidize a fixed cost of providing network infrastructure that may encourage adoption of EVs, the technology which may in turn use a low carbon fuel. In the same way, however, the infrastructure credits can reduce the very effect that LCFS critics have focused on as the central flaw in the regulations design: the encouragement of low, but still non-zero carbon fuel. Nonetheless, because the total quantity of infrastructure credits is restricted to be relatively small, their effect on potential compliance scenarios is small.As laws legalizing the recreational use of cannabis diffuse around the globe, governments face the need to coordinate cannabis control policies with existing regulations on alcohol. Policy coordination is important because the availability of cannabis can influence the consumption of alcohol as a substitute or complement . Cannabis is frequently co-used with alcohol , and when people co-use, it doubles the odds of im-paired driving, social consequences , and harms to self compared to alcohol use alone . Canada, Uruguay, and Portugal have recognized a need to coordinate recreational cannabis legalization policies with those regulating alcohol and tobacco . Similarly, the US has entertained a federal initiative called the “Regulate Marijuana Like Alcohol Act” . Although cannabis use remains illegal at the federal level, a growing number of US states have legalized recreational cannabis and now permit large commercial markets selling diverse types of cannabis products to anyone aged 21 years or older. Some US state governments have passed identical policies on alcohol and cannabis, for example those addressing minimum ages of legal access and advertising restrictions .

Comparing the East Coast results here – which are for Trenton, NJ – to their results from Newark, NJ for unbranded E10, I find lower rates of pass through, especially when dropping the RIN Price Shock period. Like mine, their sample includes a period with a significant upward shock to RIN prices – the first eight months of 2013 – that has a significant impact on estimates of pass through. In that period, D6 RIN prices rose from under 10 cents/gal to over $1/gal and was the first time RINs represented a substantial portion of gasoline margins. They argue that much of the findings of incomplete pass through are driven by the market learning how D6 RIN prices affected rack margins. Figure 12 suggest a different story. The soybean boom that began in 2020 put substantial upward pressure on bio-diesel prices, and therefore, D4 RIN prices. RIN subsidies for bio-diesel surpassed $3/gal in 2021, more than tripling since 2020, and nearly double its all-time high . Blenders adjusted quickly to this, fully passing through the subsidy as it grew exponentially. This is visually clear in Figure 16, and suggests the RIN subsidy is salient to market participants. In fact, only when excluding the RIN Price Shock period can I reject complete pass through in the Gulf and East Coast. Although reaching record highs, the RIN subsidy was still meaningful prior to the RIN Price Shock period it represented around half the price of B100 for much of the time. Pass through of the RIN subsidy was lower prior to the RIN Price Shock period, so the salience argument doesn’t explain the finding of incomplete pass through of the RIN subsidy in this paper.In this section, pass-through of the LCFS subsidy to rack margins for bio-diesel are considered. An important difference relative to RIN subsidies, LCFS subsidies exhibits less daily variation,grow lights for cannabis which introduces a lack of statistical power, especially in the short run. Generally, however, the results presented in this section will suggest that LCFS subsidies is not fully passed through in the California rack markets in my sample.

Table 5 presents short- and long-run estimates from the unrestricted and restricted models in and , respectively. Columns 1 and 2 show that all short-run coefficients are statistically insignificant when the LCFS and RIN subsidies are included separately in the model. The coefficients in column 3, however, are statistically significant and suggest 70 cents/gal of the combined subsidy is passed through in the long-run, and it takes over a week to reach the long-run rate of pass through. The restricted model is more parsimonious, but the combined subsidy may better explain variation in rack margins since they are stacked, and blenders are total policy revenue is what’s salient to the blender.Long-run pass through of the individual and combined subsidies exhibits heterogeneity within in California. Table 6 shows that pass through is lower in larger cities in the sample and higher in the smaller cities . The RIN subsidy is fully passed through in the smaller cities on average, and 60 cents/gal of the LCFS subsidy is passed through on average, but the 95 percent confidence interval includes both zero and one. The 95 percent confidence interval for the combined subsidy in the smaller cities is. The majority of operational bio-diesel production capacity is in Los Angeles, San Diego, and San Francisco . Los Angeles and San Francisco also both have major spot market hubs for ULSD. Therefore, the remainder of this section will focus on those larger cities. Only half the RIN subsidy is passed through in the urban markets on average and pass through of the LCFS subsidy is not statistically different from zero. Therefore, complete pass through is rejected for all three variables.The results of the LCFS subsidy analysis discussed thus far have been averages over the full sample. So, for example, it could be that those estimates reflect an average of incomplete pass through in earlier years due to a lack of salience but pass through becomes complete later in the sample as the market better understands how LCFS credits affect margins . Also, the LCFS subsidies for bio-diesel have risen from an average of 9 cents/gal in 2015 to over $1/gal since 2018, so it may have been easier to hide changes in the subsidy when levels were so low.

To explore the aforementioned questions, I estimate and , keeping observations in Los Angeles and San Francisco, for each sub-sample defined in Table 2. I present those results in Figure 14. The first observation is the downward shift in the rates of pass through from the Low LCFS Price period to the Mid LCFS Price period. Pass through of the RIN subsidy, on average, is close to one in the Low LCFS Price period and falls to nearly a quarter in the next period. There isn’t much signal in the LCFS subsidy during the Low LCFS Price period, but the point estimate is also close to one. In the Mid LCFS Price period, pass through of the LCFS subsidy falls to 0.06 but the 95 percent confidence interval includes up to half. Since the LCFS subsidy estimates are so imprecise in the Low LCFS Price period, I’m not able to confidently rule out the salience argument, but the near-zero point estimates in later periods, and confidence intervals with upper bounds around a half, suggest that a change in salience is unlikely to be the driver of the finding of incomplete pass through of the LCFS subsidy when utilizing the full sample. Results from the restricted model resemble RIN pass through from the unrestricted model, which is to be expected as there is more variation in RIN subsidies than LCFS subsidies over most of the sample. These RIN subsidy pass-through estimates are put into context with other cities in the sample in Figure A-4, which shows that RIN subsidy pass through, apart from the East Coast, was complete or near complete in all sub-samples.Figure 13 showed some RIN subsidy pass-through heterogeneity across blends in California. Figure 15 paints a similar picture for the LCFS subsidy; B20 is the only blend with a confidence interval including complete pass through and point estimates decrease with the share of ULSD in the blend. This result, combined with Figure 13, is consistent with blenders having greater market power in the higher blends, especially above B20. The bottom panel of Figure 16 plots rack margins for B100 in Los Angeles, along with the LCFS subsidy, the RIN subsidy, and the combined subsidy. It is important to reemphasize that west coast margins are calculated using the B100 spot price in NY Harbor Barge and therefore neglect transportation and other costs, which will inflate the observed margins above true levels by an unknown amount. I assume these costs are constant over time but don’t speculate as to their level. With that assumption, I plot the same thing but shifting margins down to better visualize comovement with the subsidies in the top panel of Figure 16. At first glance, it appears that the rack margin follows the combined subsidy well , especially in early 2016 when the LCFS credit price rose. That’s not the case, however, because the BTC was put back in place in 2016, and, under the assumptions laid out earlier in this section, blenders received an additional 50 cents/gal of B100 from the BTC. This, coincidentally,indoor cannabis grow system coincided with the LCFS subsidy increasing by about 50 cents/gal of B100 due to the modeling change by CARB. In subsequent years, rack margins generally followed movements in the RIN subsidy, but not the LCFS or combined subsidies. I use Los Angeles B100 as an illustrative example in Figure 16; however, the picture looks similar in San Francisco and other blends.Pass through of the LCFS subsidy to blended bio-diesel prices is not statistically different from zero, and in the preferred specification, pass through is 0.02 on average. There are a few important limitations that could significantly impact the results presented above. First is, again, the lack of a clear understanding how the BTC affected the relationship between RIN subsidies and rack margins, and whether the effect is different for California relative to other U.S. regions.

Second is the absence of a California-specific spot price of SME B100. If the assumption that the spot price, or the blender’s marginal cost, of SME B100 is equal to a NY Harbor Barge basis plus a constant transportation cost is violated, the estimates of LCFS subsidy pass through will be biased if California-specific costs are correlated with the LCFS subsidy. Specifically, if transportation costs exhibit a positive relationship with the LCFS subsidy, I will systematically underestimate the rate it is passed through. With the data available at the time of writing, the prevalence of that relationship is untestable. Lastly, margins for diesel blended with SME bio-diesel are volatile and data availability limit the analysis to SME bio-diesel only, which is rarely used in California. The advantage of focusing on SME bio-diesel, however, is that its CI has been relatively constant over time . Yet, if the CI of SME bio-diesel used in California changes significantly within any given year, it will have two direct effects on the models used to estimate subsidy pass through, and . The first is that the true spot price of SME B100 in California will likely move inversely with the CI, which will violate the assumption that the California spot price equals the NY Harbor spot price plus a constant. The second is that the implicit subsidy calculation in will be inaccurate. Take a simplified example. Suppose blenders start purchasing bio-diesel with a lower CI and a higher price mid-year and nothing else changes. The observed margin in will not change because I don’t observe the true California spot price. Since the number of credits per gallon would not change. The subsidy calculated in would only change if the decreasing CI is associated with an increase in the LCFS credit price, which would attenuate the estimates of LCFS subsidy pass through. However, it’s unlikely CI scores of SME bio-diesel are changing meaningfully within years in my sample. Accurate, high-frequency bio-diesel, as well as renewable diesel, pricing data for feed stocks and localities would allow researchers to study pass through using prices for fuels that reflect a much more significant market share of the biomass-based diesel consumed in the state. Additional data on the CI of fuels in the rack pricing data would allow for more accurate calculations of the implicit LCFS subsidies they receive, instead of assuming the volume weighted average CI score for the listed feed stock. Quantity data would also be particularly useful in the LCFS analysis given how thin the market for SME bio-diesel is in California. Many of the rack prices in my sample for California may come from transactions with relatively small quantities of fuel and may not be fully representative of the entire market.Credit market data for the CFP is only available since 2017 and there hasn’t been much variation in credit prices. Additionally, spot prices in the PNW and Oregon rack margins are very volatile. This makes identifying pass through of the CFP subsidy difficult and results presented here are imprecise. Table 7 presents the short- and long-run estimates from and , using the Oregon cities in the sample. All estimates of CFP pass through are statistically insignificant. Like California, short-run estimates of the combined subsidy are measured more precisely than either of the individual subsidies. An important contribution of this paper is utilizing institutional details and context to build an understanding of how the stacked costs and incentives from multiple market-based environmental policies propagate through the supply chain of fuels. This paper provides a framework to evaluate tax and subsidy pass through in the diesel sector, which is nontrivial, especially relative to the gasoline sector, due to the intermittent nature of the Blender’s Tax Credit . Although a similar tax-subsidy scheme is used, pass through of the LCFS and CFP taxes and subsidies can’t be evaluated in the same way as the RFS, due to nuanced policy differences. Section 1.4 showed that applying the same framework to the LCFS leads to the wrong conclusion about tax pass through.

Such a project could provide land managers and law enforcement with the support they need to adequately monitor areas and respond accordingly. It could also encourage individuals to write to governmental officials and create pressure for policy makers to act. Mexican DTOs are the foremost cultivator group and have the single largest impact on the marijuana industry. The same organizations responsible for the majority of marijuana production on California public lands are the heart of the bloody Mexican drug war. President Obama met with officials in Mexico City and augmented “ongoing US aid to Mexico under the Merida initiative: a three-year, $1.4 billion package aimed at helping Mexico fight the drug cartels with law enforcement training, military equipment and improved intelligence cooperation.”However, this money is yet to incur any noticeable effect on drug cartels.In order to disrupt DTOs, the United States needs to halt the flow of money and weapons from the US to Mexico. By upholding current regulations, we empower cartels to continue their destructive, violent practices. Marijuana cultivation on public lands is a significant problem with viable solutions, but without essential changes in law enforcement strategies and nationwide public policy, it is a problem we can expect to continue,vertical grow rack system putting the future of our lands and our people at risk. The US war against marijuana has increasingly escalated since its conception because it is not a war that can be won.

Drug production has become increasingly destructive and dangerous despite an estimated $7.7 billion spent annually by the US Government to enforce marijuana laws.Such regulation inflates the steady revenue flowing to criminal organizations that in turn generate widespread crime and violence. Regardless of the legal status of marijuana, as long as it remains in high demand there will be a market to supply it, regulated or unregulated. Government-imposed prohibition gives rise to black market systems that are dominated by major criminal organizations that control production and distribution. This system of perpetual crime and punishment is sustained at the cost of all parties involved, and requires a fundamental change in the system itself. Public policy plays the most crucial role in dictating the status of marijuana markets and their effects on governance and fiscal resources. The most powerful mechanism for opposing cultivation trends is to change the role of marijuana in California and the United States through legalization. California legislator Tom Ammiano proposed the Marijuana Control, Regulation, and Education Act in 2009 in an effort to take marijuana cultivation out of cultivator control and put it to use for the government through tax revenues. It was estimated that marijuana taxes could generate over a billion dollars in tax revenues while saving the state of California hundreds of millions more in enforcement, legal, and incarceration costs. The Regulate, Control & Tax Cannabis Act, Proposition 19, was put on the California ballot in November, 2010, to legalize marijuana and control it like alcohol. Though Prop 19 failed by a narrow margin, widespread legalization could bring marijuana out of the black market and into the mainstream, enabling governmental controls that are impossible under the current system, such as barriers to marijuana access for youth.

On a national scale, such a system would de-incentivize DTO operations by reducing their profit margins, and removing black market demand. Legalization would create a legitimate marijuana industry through which cultivators can be regulated, resulting in more efficient and less damaging practices. Consumers could then buy less harmfully produced marijuana because it would be available through established institutions. Finally, alternative uses of hemp including fibers, oil, and protein could be re-established within legitimate and competitive industries. Decarbonization of the U.S. and global economies requires a transition away from fossil fuels to renewables, especially in the transportation sector – the largest contributor to U.S. greenhouse gas emissions.The environmental costs associated with the production and combustion of petroleum fuels have not been internalized by producers and consumers, respectively, prompting government intervention. Federal and state governments have increasingly looked to market-based environmental policies to reach their decarbonization goals, often by enacting credit trading schemes for markets to meet an annual standard. This dissertation studies the most prominent of such U.S. public policies that incentivize displacement of petroleum fuels with renewable and low carbon transportation fuels. The Renewable Fuel Standard is the largest program to support renewable fuels in the U.S., requiring a variety of bio-fuels to be blended in the national fuel supply. The RFS is criticized for being technology biased, as it specifies how much of which biofuels must be used to reach its emissions reduction goals. State and other federal governments now increasingly look to carbon intensity standards in the transportation sector, which provide a technologyneutral policy option.

The largest of such policies is California’s Low Carbon Fuel Standard , which sets a carbon intensity standard for the state’s transportation fuel supply. This dissertation explores the past, present, and future of low-carbon fuel incentive programs. Chapter 1 begins with the present, addressing an important ongoing challenge associated with these policies – namely incomplete pass-through of incentives and costs to fuel prices. Chapter 2 looks ahead a decade, forecasting a range of compliance outcomes for California’s LCFSthrough 2030. Finally, lessons from the last decade are drawn in Chapter 3, exploring trends in the three standing carbon intensity policies worldwide using publicly available historical data. Chapter 1 provides an empirical analysis of credit revenue pass-through. Specifically, time series techniques are used to estimate the extent to which implicit taxes and subsidies generated from the RFS, LCFS, and CFP are passed through to a variety of diesel fuel prices. In a second best policy framework, an efficient RFS and LCFS achieve their respective GHG targets while minimizing compliance costs. If fuel blenders have market power, they have the incentive to drive up compliance costs, leading to an inefficient outcome. The findings from Chapter 3 suggest that obligated parties completely pass through their implicit taxes from the RFS, LCFS, and CFP to wholesale diesel prices. They suggest incomplete pass through, on the other hand, of bio-diesel subsidies to rack blended diesel prices. The RFS, LCFS, and other carbon intensity standards all tout an attractive feature: revenue neutrality. These policies are revenue neutral to the transportation system because the implicit tax revenue generated from obligated parties purchasing compliance credits is used to lower the price of alternative fuels, effectively subsidizing them. Market imperfections, however, may restrict how much of the credit revenue is being fully passed through to consumers in the form of lower prices for alternative fuels. Chapter 2 assesses if and how California is likely to achieve the 20 percent CI reduction target by 2030 set forth by their LCFS. Using a Vector Error Correction model, LCFS credit demand is projected through 2030 under business-as-usual uncertainty. The model is trained using 30 years of historical trends in gasoline and diesel demand, vehicle miles travelled, oil prices, and other economic indicators. Several policy scenarios are simulated and evaluated against a baseline scenario, which extrapolates current trends. Biomass-based diesel, the marginal fuel for LCFS compliance, makes up between about 60 and 80 percent of finished diesel in 2030 in the baseline scenario, reflecting a substantial increase from current levels. Under most alternative policy scenarios,vertical grow system and especially in the case of rapid electric vehicle deployment, compliance is met with significantly less biomass-based diesel. The first two chapters analyze the LCFS and CFP, which are a relatively new policy instruments used to reduce transportation emissions reductions. As more and more states continue to adopt similar carbon intensity standards, it is imperative to understand similar existing programs have performed, however comprehensive analyses on them are relatively scant.

Aiming to fill that gap, the final chapter, Chapter 3, reviews the three standing carbon intensity standards in California, Oregon, and British Columbia using publicly available data and information. British Columbia was the first jurisdiction to implement a CI standard in 2010, followed shortly after by California in 2011, and later followed by Oregon in 2016. California’s program is the largest given the state’s voluminous population and fuel demand. Low CI scores associated with avoided emissions have brought about staggering growth in the use diesel alternatives such as bio-diesel, renewable diesel, and biogas in the three jurisdictions. In California, diesel alternatives generated the majority of LCFS credits, generating nearly two billion dollars in revenue in 2020 alone, a third of the total. Since diesel are so critical to compliance, this dissertation pays special attention to that side of the transportation sector and seeks to impart an understanding of how diesel markets and alternative fuel policies interact.Renewable and low carbon fuels are becoming an important part of decarbonization strategies worldwide. Several policies have been, or are being planned to be, implemented in the United States. There are three policies, one federal and two state, that lead this effort. The U.S. Renewable Fuel Standard requires certain percentages of gasoline and diesel be displaced by renewable fuels each year. California’s Low Carbon Fuel Standard and Oregon’s Clean Fuels Program set targets to reduce the CI of transportation energy in their states. The RFS, LCFS, and CFP all rely on systems of tradeable credits for compliance which prompt implicit tax-subsidy schemes in fuel markets. Firms pay a penalty on their petroleum products and the revenue is transferred to alternative fuel producers effectively in the form of a subsidy. The efficacy and efficiency of these policies hinge on the implicit taxes and subsidies propagating through fuel supply chains. This paper studies pass through across two dimensions in the diesel sector: implicit taxes placed on petroleum diesel and implicit subsidies awarded to bio-diesel. Implicit taxes and subsidies from the RFS stack with those from the LCFS and CFP in California and Oregon, respectively, and therefore are evaluated both separately and together. There are three points in fuel supply chains where pass through is relevant, this paper studies two of them: the wholesale market to blenders and blenders to retailers. This paper does not investigate pass through from retailers to consumers, which must also be complete to achieve efficacy of the policies. The pass through of bio-diesel subsidies to retail prices of blended diesel is an important area for future research, especially given evidence of incomplete pass through of ethanol RIN subsidies to E85 retail prices in the literature . U.S. crude oil refiners and petroleum importers are required to purchase Renewable Identification Numbers , the compliance credits in the RFS, for each gallon of gasolineand diesel supplied, which act as an implicit tax. California and Oregon refiners and importers face a similar obligation under the LCFS and CFP, respectively, namely deficits that are generated for each gallon of gasoline and diesel consumed in-state. There are robust markets for RINs, LCFS, and CFP credits and the market price, along with the stringency of the policies, determine the level of the taxes and therefore the cost of compliance. Fuel blenders purchase bio-fuels with a RIN attached to it. Once the fuel is blended, the RIN is separated from the fuel and can be sold on the RIN market. The value of the RIN then, acts as an implicit subsidy on the bio-fuel. If blenders have market power in selling RINs, they have the incentive to drive up RIN prices, which in turn, raises compliance costs for refiners and consumers. How much of the RIN tax that is passed through by refiners will determine the incidence of the increased RIN prices resulting from the incomplete pass through of the RIN subsidy. The same relationship between the tax and subsidy is present in the LCFS and CFP. This paper is the first to analyze RIN pass through on both sides of the tax-subsidy mechanism, the first to examine pass through of bio-diesel subsidies, and the first to consider either the LCFS or CFP. Indeed, most studies to date on pass-through for implicit taxes and subsidies for fuels have focused on the federal RFS and the gasoline industry, with much less focus on state policies and the diesel industry. Diesel fuels accounted for 27 percent of total transportation energy in 2020.3 Biomass-based diesel earns the lion’s share of credits in California’s LCFS and a growing proportion in Oregon’s CFP, making diesel an important piece of the transition to lower carbon fuels. Furthermore, pass-through results from the gasoline industry may not hold for the diesel industry because of differences in costs, production, storage, and blending constraints, demand and supply elasticities, and market structure.

Marijuana cultivation on state and federal lands became a major law enforcement priority and the US Forest Service, National Guard, CAMP and other cooperative task forces have taken on primary roles in conducting counter-cultivation efforts.New law enforcement objectives were established in the “Strategic Plan” which identified short-term and long-term goals, as well as the methodology “to eliminate, disrupt and dismantle the leadership, command, control, and financial infrastructure of Drug Trafficking Organizations.”The key developments within the agencies regulating marijuana cultivation were year round operations and investigations that targeted whole organizations. However, sustained operations required benchmarks for progress. Enforcement agencies would use short term results to measure progress on long term goals. Previous measures of short-term success persisted, including site location, plant eradication and cultivator arrests. However, law enforcement agencies created divisions strictly dedicated to opposing DTOs by assigning patrol officers exclusively to the issue, reassigning alternative workloads, and removing extraneous administrative duties of those in charge in order to focus the necessary resources to impact DTOs. In addition, increased funding allowed agencies around the state to begin a training and recruitment process to significantly increase staffing. In the Pacific Southwest Region of the Forest Service, the additional staff would include 1 supervisory special agent, 3 patrol captains, 18 special agents, 50 law enforcement officers, pipp drying racks and 6 administrative assistants, all of whom will be dedicated almost exclusively to marijuana control.

This will allow for long-term engagement in year round counter-cultivation efforts that utilize preventative measures as an advantage. Instead of waiting for a site to be found in July or August, agents will be able to look for and follow up on leads throughout the year. Equally important, they can identify priority cases for full investigation so they may be completed to a “reasonable conclusion.”Investigations will be prioritized based on existing intelligence, site logistics, available resources, and special public interest. The process of site review involves a methodical documentation of evidence such as cell phone contacts and the origin of supplies, which is entered into records and scrutinized for pursuable leads. Previously, useful evidence would have remained untouched at the site, or on rare occasions, kept in police storage. The potentially useful information left at sites was lost to neglect. Now, a significant portion of the evidence left behind is subjected to intelligence analysis. Increased utilization of intelligence analysis centers has made this process much more efficient and effective, which enables preventative tactics and helps governmental agencies learn about and infiltrate tight drug trafficking institutions. Governmental agencies have also changed investigation and detection strategies. While some authorities claim that there is nothing better than a helicopter and a well-trained eye, enforcement agencies are developing the use of more sophisticated techniques. These include, but are not limited to, ultraviolet, infrared, and electronic detection systems. Other techniques include night time patrols in high risk areas when cultivators may be less attentive, year-round patrols, and new detection methods such as monitoring for irrigation and cultivation supplies, comparing watershed precipitation with surveys of water flow quantities, and testing for chemical nutrient imbalances in bodies of water.

The more time that is dedicated to research and detect sites early, the less time is required to raid and eradicate each site. Raids are carefully planned efforts, designed to reach set goals while minimizing the risk to agents. First, team leaders develop a raid plan and develop logistics such as funding sources, equipment requirements and invasion methods. Agents in charge then gather a team that they brief, supply and prepare. New agents and officers are required to complete a thorough training program to learn remote raid techniques. Teams sometimes hike into sites for covert operations, but more often, they rappel down from a helicopter into the nearby area. Officers face major disadvantages when raiding sites because cultivators have been living at the location for months. Covert operations involve the most risk because hiking conditions and landscape characteristics can subject officers to ambush and provide cultivators with vantage points for armed engagement. While no officers have been fatally wounded during remote operations, there have been various cases involving gunshot wounds. During helicopter raids, cultivators generally flee from the scene while law enforcement officers are lowered into the area. While living on-site for months, cultivators develop elaborate escape routes and hiding spots. Hiding places can be as close as one hundred feet from a grow site, and are rarely found without K-9 assistance. The cultivators that are obtained are generally low-level employees with minimal knowledge about the larger organization that employs them. To complement tactical operations, government agencies have developed another significant long-term goal to develop an understanding of commercial scale, remote marijuana cultivation, within the broader public.

Regional leadership conducts public education programs by presenting PowerPoint demonstrations about DTOs at meetings, forums, and presentations for politicians, government employees, and the general public. Law enforcement organizations facilitate information sharing with the media and local contacts, and have developed “bi-lingual material to be distributed in high risk areas seeking information and offering rewards.”These programs aim to increase the awareness in an effort to increase reports of suspicious activities. When marijuana related activities are reported early, enforcement agencies gain a strategic advantage in combating individual sites. In addition, early detection allows more sites to be discovered and raided throughout the year because enforcement efforts are spread over a longer period of time. Public education creates an understanding of the consequences of marijuana production on various scales. This can provide political support for the prevention of DTO related activities in California, as well as alter patterns of marijuana acquisition and consumption within the general public. The production of potent marijuana requires intensive resource inputs to achieve high yield. This means that carefully planned and executed cultivation systems are crucial to developing quality marijuana harvests, and that cultivators manipulate the environment to optimize conditions for Cannabis plants. The widespread influence of Mexican cartels on outdoor cultivation in California causes similar processes to be performed at separate sites dispersed across large geographic distances. DTO operated grow sites have developed systematic patterns of behavior that occur with regularity and make their efforts distinct. Cultivators inhabit remote sites over long periods of time to develop plantations, and create a multitude of adverse effects in the process. Site selection is a crucial aspect of the cultivation process. DTOs often choose prospective locations long before they enter into a site. Some key elements that they look for on maps and aerial photographs are isolated water sources, slight canopy cover and adequate sunlight exposure. Sites are created in areas such as logged landscapes, conservation reserves, remote areas of national parks,pipp horticulture and other places with difficult access and visually indistinct features from a birds-eye view. These are often areas where people rarely go because entry is made difficult by physical barriers such as cliff faces, steep talus slopes, dense clusters of vegetation such as poison oak, and even man-made berms. Due to the rugged and highly vegetated condition of most prospective sites, preparing land for marijuana planting is both labor intensive and time-consuming. Laborers work long hours to provide Cannabis plants a monopolistic domination of the landscape. The dynamics of landscape alteration depend on site-specific characteristics, but many similar practices occur throughout DTO operations. During the site supply process, cultivators cut or wear trails into the landscape that weave back and forth making site access for material transport easier. In order to avoid detection, laborers try to avoid leaving evidence of their presence up to a certain point, such as a major physical barrier, after which distinct paths are worn into the ground. The sheer weight of laborers’ equipment loads combined with regular use of the trails is enough to trample and kill small vegetation.

The paths connect site entry routes to the food preparation area, sleeping area, latrine, and various marijuana plantations. One site may contain 30,000 plants, but within that site the plants are often divided up between multiple smaller plots. Laborers’ movement along the paths is responsible for the introduction and distribution of non-native plant species to new areas. Laborers accumulate and transport seeds or spores on their bodies, clothing, shoes and equipment. In the California central coast region, cultivator movement along self-created paths is cited for the spread of Sudden Oak Death syndrome in Tan Oak, Black Oak, and Coastal Live Oak trees.Studies conducted by the Santa Lucia Conservancy show that the occurrence of SOD is facilitated by remote inhabitance through transmission of the plant pathogen responsible for SOD, Phytophora ramorum. Marijuana cultivators contribute to the spread of Phytophora ramorum to uninfected oak trees and exacerbate the effects of Sudden Oak Death syndrome by moving throughout affected landscapes that are part of their widespread system of sites. Movement by any person or animal can effectively transmit this pathogen to uninfected oak trees, but cultivators navigate through these areas more frequently than other people who may pass through. Their movements are also responsible for the spread of a variety of harmful invasive species including thistles, Vinca, Periwinkle, English Ivy Yard, and others.Invasive organisms often out-compete native species because they possess adaptive characteristics and lack natural competitors when introduced in new areas, which results in widespread alterations to the food-web, nutrient cycling, fire regimes, and hydrology of otherwise well preserved ecosystems. Many attributes of remote ecosystems are not ideal for agriculture, so laborers invest much time and energy in altering land to make it suitable for Cannabis cultivation. Workers clear understory vegetation to eliminate potential competition and prepare the soil for Cannabis plantations. The cleared vegetation, referred to as “slash piles,” are discarded in stream beds, causing impediments to hydrologic flows, or used to create berms up to 8 feet tall in order to bar site access.Throughout the growing season, cultivators use chemical techniques to maximize THC content and bud production. These intensive methods change soil dynamics, nutrient levels and chemical makeup, thus creating the opportunity for a new composition of vegetation to emerge. Landscape alteration may awaken seed banks in the soil that have sat dormant for up to hundreds of years, alter the ability for some plants to re-grow because of changes in soil chemistry, destroy habitat for a variety of organisms, and have many other adverse affects on otherwise preserved ecosystems. In short, remote Cannabis cultivation forever changes the ecosystems in which it takes place. In highly mountainous areas, growers dig out terraces on hill slopes to create planting beds. In the process, soil is displaced leading to accelerated rates of hill-slope erosion. Some terrace beds are stabilized by falling trees, trimming them into logs, and inserting the logs into the terrace walls to hold the dirt in place. This is an important step to provide somewhat stable access to individual plants on steep slopes, and to prevent landslides that could destroy entire plantations. However, when these are removed, the stock of topsoil is greatly diminished. On slight grades or flat surfaces, cultivators mound soil around Cannabis stems to optimize nutrient uptake. For plantations with high percentages of gravel or sand, growers will bring in loamy soil to provide proper soil composition and nutrients. The affects of these changes on the natural environment can vary. For instance, fallen trees naturally promote the growth of under story species; however, the cutting of trees can disturb soil and impact the ecosystem services that they once provided such as habitat, nutrient cycling and moisture retention. Many land alterations remove perennial root structures that stabilize sediment causing the hillsides to lose stability and become more susceptible to small landslides and sedimentation of water sources during precipitation. Sedimentation alters water flow, reduces the capacity of water stocks, degrades the habitats of various species, and makes waters turbid – reducing the capacity for organisms to photosynthesize. Further, chemical toxins and metals bind to clay particles in fluvial sediment, are consumed by bottom feeding organisms, and bio-accumulate in higher order predators throughout the food chain. Cultivators approach land alterations with utter disregard; falling old growth trees, discarding of brush in stream beds, and littering the ground indiscriminately with waste. In sites intended for continued cultivation, laborers dig deep holes that are used to dispose of trash at the end of the harvest season in order to reduce the chances of detection between one season and the next.

There are many possible explanations for why deer and gray fox space use might be more influenced by cannabis farms than lagomorphs. These generally have to do with characteristics on the farms themselves. Wildlife may be interacting with the increased presence of domestic cats and dogs on cannabis farms , for instance, for deer as potential or perceived prey, or gray foxes as competitors . Alternatively, deer and gray foxes may be responding to behavioral cues from increased human presence and activity on cannabis farms . It is possible that lagomorphs are more behaviorally flexible than deer and gray foxes and can avoid altering their spatial patterns by instead shifting their temporal activity patterns, for instance, becoming more nocturnal . More research is needed to disentangle these potential mechanisms. Both detection rate summaries and model results suggest that cannabis farms appeared to disproportionately influence the space use of larger wildlife species. Black bears had a higher detection rate on comparison sites compared to cannabis farms and the model results indicate that larger black-tailed deer and gray foxes might avoid cannabis farms, while smaller animals such as lagomorphs appear to be unaffected. This result is expected, as large bodied animals such as deer may be unable to access space on the farms if they are physically blocked by fencing,vertical grow system while smaller species are still able to move through these barriers .

Despite variation in which species responded to cannabis farms, we did not find evidence from either detection rate summaries or model results to suggest that predators were attracted to these sites. Other studies have shown predators tend to avoid agricultural development, and our results seem to support the same trend . By contrast, there has been recent suggestion that cannabis production on public lands may serve as an “ecological trap” by attracting carnivores to production areas that then expose individuals to deadly toxicants . Our results, at least in the short-term, suggest that this dynamic may be less likely to occur on small-scale private land cannabis farms. This highlights the different potential ecological threats and processes playing out on public versus private land cannabis production sites. Not only do private land cannabis farms seem to use fewer toxicants , but they may also have higher human activity levels on site compared to public land production located in more remote areas. Wildlife may in turn tend to avoid this human presence rather than being attracted . This study begins the discussion regarding a glaring shortage of data on animal space use on cannabis sites, but there are many further avenues for future research. For example, the relative importance of cannabis farms in their influence on animal space use should be analyzed in the surrounding landscape context. The influence of roads on the modeled detection results implies that cannabis cultivation, despite occurring in a rural area in this case, was not the only form of human disturbance to which animals were responding. It may therefore be useful to compare cannabis and other forms of rural land use.

In addition, it is necessary to conduct further study at broader spatial and temporal scales in order to examine long term wildlife community response to cannabis and unravel the complicated set of potential contributing factors.Wildlife are likely to have species-specific responses to small-scale outdoor cannabis farms, and, thus, the specific land use practices occurring at a site may be influential for biodiversity conservation in these communities. Future studies should examine the role of fencing, timing of human activity, presence of domestic dogs and cats, and other site level practices that may influence wildlife use. Many small-scale cannabis farms are not part of a licensed production system , and therefore cannot be regulated for their production practices . For these producers, a mix of educational resources on wildlife friendly growing practices, grower enforced community standards or expectations, and law enforcement efforts to reduce noncompliance, may play an important role in increasing or maintaining biodiversity. For species deterred from cannabis farms, such as was implied by our deer and gray fox results, further research is needed to understand the mechanism for this avoidance. If, for example, fencing, artificial lighting, or sound are identified as major causes of this deterrence, then careful consideration should be given to the regulations on these practices at cannabis farms and their relation to critical habitat features such as water sources or animal migration routes.There is a national trend toward statewide legalization of medical marijuana despite federal classification of marijuana as a Schedule I illicit drug. There are compelling arguments for and against medical marijuana legalization and its potential impact on an array of complex social issues .

Residents in states where medical marijuana is legal are more likely to have tried marijuana, report current marijuana use, and be diagnosed with marijuana abuse or dependence . Additionally, there is preliminary evidence to suggest that there is likely a dose-response relationship between the number of years since legalization and marijuana prevalence rates . A key question regarding more liberal marijuana policies is whether and how they affect use of other drugs including addictive and harmful substances like tobacco. Previous studies have found a strong positive association between cigarette and marijuana use . Epidemiologic data indicate that the prevalence of tobacco and marijuana co-use has increased from 2003 to 2012 . Moreover, the increase in co-use occurred specifically among those ages 26–34 years, and the greatest percent increase, in those ages 50 years and older . It is unknown, however, if this national increase in co-use is directly associated with statewide legalization of medical marijuana. If marijuana policies are indeed associated with co-use, the current trend toward legalization of medical and/or recreational marijuana, without any regulatory action, has the potential to influence patterns of cigarette and marijuana use/co-use over time. An increase in cigarette and marijuana co-use has the potential to create challenges for cigarette smokers who want to quit. There is evidence to suggest that cigarette and marijuana co-use is associated with greater nicotine dependence . Possible explanations for this link include the role of the endocannoboid system in nicotine metabolism , genetic predisposition for co-use , and various environmental and cultural influences . The relationship between co-use and nicotine dependence, however, is understudied in adults, particularly among those ages 50 years and older. Since nicotine dependence is influenced by both nicotinic receptors and nicotine associated metablism that change with age ,pipp racking we can expect nicotinedependence among cigarette and marijuana co-users will also vary over the lifespan. Few studies have examined cigarette and marijuana co-use and nicotine dependence from adolescence through adulthood. As the nation is well-past the tipping point on medical marijuana legalization, studies are needed to take a closer look into whether marijuana policies have the potential to influence tobacco control efforts at the population level. For example, over time, it is likely that greater access to legal marijuana will increase the absolute number of co-users who have greater nicotine dependence and difficulty quitting cigarettes. Such data can help to identify subset populations at higher risk of nicotine dependence and could have both policy and treatment implications in tobacco control. In this study, we sought to examine relationships between medical marijuana laws and cigarette and marijuana co-use. Additionally, we examined the likelihood of nicotine dependence in co-users. We analyzed data from the 2013 National Survey on Drug Use and Health and stratified the analysis by age categories. Results from this study can inform the direction of future medical marijuana policies that may inadvertently affect tobacco control efforts.We analyzed cross-sectional data from the 2013 NSDUH conducted by the Substance Abuse Mental Health Services Administration . The primary purpose of NSDUH is to measure prevalence and correlates of drug use in the civilian, non-institutionalized U.S. population aged 12 years and older. Since 1991, NSDUH has consisted of an independent multistage area probability sampling design for each state and the District of Columbia and uses a combination of the Computer-Assisted Interviewing and Automated Computer Assisted Interviewing instruments in selected individuals and households . The survey offered $30 in cash to participants and was conducted in 2013 by Research Triangle Institute . The final survey consisted of 67,838 CAI interviews with a weighted screening response rate of 84% and an interview response rate of 72%. The public use file consisted of 55,160 records due to a sub-sampling step which included a minimum item response requirement for weighting and further analysis.

A detailed description of the questionnaire items, sampling methodology, data collection/ response rates, and sample weights is published elsewhere . The present study was exempt from the University of California San Francisco’s Human Research Protections Program approval since data were publically available and subjects cannot be identified. In this analysis, only those with complete responses for all measures were included. Additionally, while the analysis included participants aged 50–64 years, those 65 years of age and over were excluded due to a small sample size . The final sample included 51,993 participants. The item “How long has it been since you last used marijuana or hashish?” was used to classify respondents into three categories: “Within the past 30 days” ; “more than 30 days” ; and “never used marijuana” . Current marijuana users reported frequency of past 30-day use [Range = 1–30 days]. Cigarette use was assessed with an item asking whether and how recently participants had smoked “part or all of a cigarette.” Past 30 day users were categorized as current cigarette smokers, other than “within the past 30 days” as former smokers, and “never used cigarettes” as never smokers. Participants were coded as co-users if they had smoked at least one cigarette in the past 30 days and used marijuana in the past 30 days. Respondents who indicated blunt use were not included in our analysis since our analysis includes comparison of nicotine dependence in cigarette smokers who use marijuana vs. those who do not marijuana .Nicotine dependence was measured in two ways: the 17-item Nicotine Dependence Syndrome Scale and the single “time to first cigarette” item from the Fagerstrom Test of Nicotine Dependence . Respondents’ average NDSS scores were calculated over 17 items across five aspects of dependence and current smokers with a cutoff score of 2.75 or above were categorized as nicotine dependent. Those who responded smoking cigarettes in the past month and having their first cigarette of the day within 30 minutes of waking on the TTFC were categorized as nicotine dependent. Additional information on NDSS and TTFC questionnaire items, scoring procedure, and methods used for cutoff scores are published elsewhere . We examine both NDSS and TTFC scores to potentially increase the reliability of our findings. Descriptive statistics are reported for demographics, cigarette and marijuana use, and lifetime depression as well as chi-square tests of differences by statewide medical marijuana legalization status . One-way ANCOVA models tested for differences in marijuana use and cigarette and marijuana co-use in the overall sample, and separately for each age category, between states where medical marijuana was legal vs. illegal, adjusting for age , gender, race/ethnicity, education, age at first cigarette initiation, age at first marijuana initiation, and lifetime depression. Additionally, we calculated mean NDSS and frequency of TTFC scores by statewide legalization categories across age groups. In the overall sample and within each age category, two logistic regression models examined nicotine dependence, as measured by NDSS and TTFC scores, in cigarette and marijuana co-users . Models were adjusted for age , gender, race/ethnicity, education, lifetime depression, and statewide medical marijuana legalization status. Bonferroni adjustments were applied to all models with over five independent variables . In this analysis, we used the Taylor series method for replication methods to estimate sampling errors of estimators based on complex sample designs. The regression coefficient estimators were computed by generalized least squares estimation using element-wise regression. The procedure assumes that the regression coefficients are the same across strata and primarily sampling units . All models were run in SAS 9.4 using the SURVEY procedures to obtain weighted estimates to increase the generalizability of the findings . The study sample was approximately half male, majority non-Hispanic White , and more than a quarter was college-educated .

Data were analyzed by a t-test, one-way or two-way ANOVA with Prism 9 software , as appropriate. Significant main or interaction effects were followed by Bonferroni post-hoc comparison with correction for multiple comparisons. The criterion for significance was set at α = 0.05 two-tailed.In these studies, we sought to examine how adolescent exposure to nicotine, THC, or co-exposure may alter later reward- and relapse-related behaviors. For translational relevance to youth, THC was administered orally as related to edible consumption, and nicotine was administered via e-cigarette aerosol exposure. However, for the nicotine treatment, we aimed to compare to our prior findings with subcutaneous injections, so this additional group was included. Given the different routes of nicotine administration, we desired to first validate the respective level of nicotine’s metabolite, cotinine, for both methods. Moreover, given other findings in our lab suggesting that THC may alter nicotine metabolism [unpublished data], we also examined cotinine levels in the THC and nicotine coexposure groups. Higher blood cotinine levels were found across all nicotine-treated groups compared to the vehicle , thereby validating the measure. When comparing among drug-treated groups,vertical grow rack system co-exposure to nicotine vapor and the higher dose of THC led to lower cotinine levels as compared to nicotine vapor alone or co-exposure to nicotine vapor and the lower dose of THC .

This indicates that the high dose of THC did alter nicotine metabolism. Importantly, males exposed to only nicotine, whether via injections or vapor, did not differ in blood cotinine levels, indicating that both of these administration methods resulted in similar levels of nicotine exposure.Next, since adolescent drug exposure could possibly alter general growth, body weight was examined across the adolescent treatment days and in adulthood. Body weight was measured throughout the treatment period and in adulthood .The post-hoc analysis revealed that males exposed to either the lower or higher dose of THC, as well as those co-exposed to nicotine and the higher dose of THC , gained less weight from PND 38 to 49, as compared to control subjects. The post-hoc analysis revealed that adolescent exposure to the higher dose of THC led to lower body weight than vehicle exposure . Thus, these data indicate that adolescent exposure to a higher dose of THC, but not when co-administered with nicotine, induced persistent changes in body growth into adulthood.To examine whether adolescent drug exposure altered the subjects’ ability to learn an operant task, groups were examined for their ability to press a lever to earn food reward. Post-hoc analysis revealed that co-exposure of nicotine and lower dose of THC in adolescence led to a higher level of active lever pressing than the control group in adulthood, but only in session 3 . In session 7, males exposed to nicotine vape alone exhibited a lower level of active lever presses than the control .

With regard to subjects co-exposed to nicotine and the higher dose of THC, a higher level of active lever pressing was found for sessions 6 , 7 and 8 .Thus, to further investigate if the active lever differences are reflected in the number of food pellets obtained across sessions 6-8, we next compared the mean pellets earned. with the exception of the co-exposure nicotine and higher dose THC group that earned significantly more food pellets compared to the control. Therefore, these findings indicate that higher dose THC and nicotine co-exposure during adolescence in males induces more persistent effects on the drive to obtain food in the operant paradigm in adulthood.Next, to determine whether adolescent nicotine and/or THC exposure alters the reinforcing properties of nicotine in adulthood, mice were assessed for intravenous nicotine self-administration. Specifically, compared to control subjects, significantly more nicotine infusions were earned following adolescent exposure to the lower and higher dose of THC , and co-exposure to nicotine and the lower dose of THC . Given these findings with THC altering later nicotine intake, it is surprising to note that differences were not found with co-exposure to nicotine and the higher dose of THC, even though this group exhibited a greater drive to obtain food reward. Taken together, these results indicate that adolescent use of cannabinoids have a persistent effect on reward consumption, which is dependent on THC dose, nicotine co-exposure, and type of reward.Since drugs of abuse may differentially alter development dependent on sex, we next examined whether adolescent nicotine, THC, or co-exposure in females results in similar physiological and behavioral outcomes in adulthood.As above, all of the nicotine treatment groups resulted in a significant level of detectable cotinine .

When comparing among treatment conditions, injections of nicotine resulted in lower cotinine levels than nicotine vapor and co-exposure of nicotine and low dose THC , although it is important to note that all of these groups exhibited levels of cotinine >50 ng/ml which is in the range of that found with human e-cigarette and tobacco smokers. Interestingly, similar to that observed in males, females exhibited significantly lower cotinine levels with nicotine vapor and the higher dose of THC as compared to nicotine vapor alone or co-exposure to nicotine vapor and the lower dose of THC , suggesting that the high dose of THC interacts with nicotine metabolism. Posthoc analyses revealed that the females gained less weight from PND 38 to 49 if exposed to either the lower or higher dose of THC or coexposed to nicotine and the higher dose of THC , compared to vehicle. The posthoc test revealed that the high dose of THC, either in the absence or presence of nicotine , led to decreased body weight differences that were maintained into adulthood, compared to vehicle. Even so, a trend was noted with higher dose of THC potentially resulting in a lower body weight than vehicle . Together, these data indicate that a higher dose of THC during adolescence may have persistent developmental effects on body growth.We next focused our investigations of operant food training in the female mice. The post-hoc analysis revealed that females exposed to the higher dose of THC exhibited a higher level of active lever pressing for sessions 7 and 8 compared to control. Further, co-exposure to nicotine and the lower dose of THC resulted in greater active lever pressing across sessions 6 and 7 , but no difference on the final session 8 compared to the control. Thus, these findings indicate that regardless of adolescent exposure, females were able to acquire the food training task,grow rack with lights although high dose THC may have led to increased responding to obtain food pellets in later sessions, an effect not found with nicotine co-exposure. We then examined intravenous nicotine self-administration during adulthood in female subjects with a history of drug exposure.The post-hoc analysis revealed that a higher dose of THC during adolescence led to increased nicotine intake in adulthood compared to vehicle . While not statistically significant, we also noted a trend with the co-exposure nicotine and lower dose of THC group having higher intake compared to control . Taken together, these findings reveal that a high dose of THC during adolescence increases the drive to consume both food and nicotine in adulthood, an effect which appears to have been counteracted by the co-exposure of nicotine.Re-exposure to the auditory, visual, and/or olfactory cues associated with drug taking has been shown to enhance relapse-related behaviors. Thus, after intravenous nicotine self-administration acquisition, we examined lever pressing behavior for a visual and auditory cue in the absence of nicotine infusions. Since this procedure has been mainly used in rats, it was important to first demonstrate that control subjects could exhibit a robust incubation of nicotine craving effect, as validation of this protocol in mice. For our analysis, we also included comparisons of active lever pressing that correspond to the nicotine self-administration data presented in Figures 1E and 2D .

These data were important to include to determine whether the mice exhibited an extinction burst on the first day of incubation testing , which could have implications for interpretation of the later incubation effect on Day 24. Therefore, the post-hoc analysis compared incubation day 1 to the other sessions . In the post-hoc analysis, there was a significant increase in active lever pressing comparing incubation Day 1 to Day 24 for both males and females . However, active lever pressing did not differ when comparing responding for nicotine infusions to incubation Day 1 . Thus, these findings demonstrate that incubation of nicotine craving can be readily detected in mice. For the nicotine vapor group, the post-hoc analysis revealed an increase in active lever pressing on Day 24, as compared to Day 1, of incubation , but no differences were found comparing Nicotine to Day 1. This effect was interesting given that these groups did not differ in the level of cotinine, suggesting that the differences in duration of daily adolescent exposure may be relevant. While both of the ANOVAs indicated a statistically significant effect, post-hoc analyses did not reveal significant differences among sessions, although with nicotine vapor exposure a trend was noted between the Nicotine and Day 1 sessions suggesting a potential burst in responding. Given the differences found in body weight and food training with some of the THC exposure groups, we predicted that significant differences would also be found for incubation of craving. These findings suggest that the higher dose of THC during adolescence may have led to overall increased active lever pressing, suggesting either overall increased general activity , or alternatively, a premature incubation effect with higher immediate and persistent drug seeking behavior.Finally, we sought to determine whether nicotine and THC together would have unique effects on relapse-related behaviors. Surprisingly, co-exposure elicited differential outcomes compared to what we previously reported for single drug exposure.For all of the above co-exposure comparisons, statistically significant differences were not found between baseline Nicotine and incubation Day 1. Together, these findings indicate that nicotine and THC can interact to induce a differential effect than either substance alone during development, thereby sustaining a heightened response to drug associated cues to propagate increased nicotine seeking behavior and potential risk of relapse.This study sought to determine whether prior nicotine and/or THC exposure during adolescence would alter operant learning, drug reinforcement, and nicotine seeking behaviors. Importantly, we found that nicotine exposure in adolescence regardless of route of administration resulted in significantly high levels of cotinine in both sexes; but coexposure with the higher dose of THC altered the metabolism of nicotine as evidenced by significantly lower cotinine levels in these subjects than those exposed to nicotine alone. Males that were co-exposed to nicotine and the higher dose of THC in adolescence also exhibited increased food self-administration in adulthood. In contrast, none of the female groups differed in food self-administration. Furthermore, males that were exposed to either dose of THC alone in adolescence or co-exposed to nicotine and the lower dose of THC had increased nicotine intake in adulthood. Whereas females with adolescent exposure to only the higher dose of THC exhibited increased nicotine intake in adulthood. Following nicotine self-administration, both male and female control mice exhibited increased nicotine-seeking behaviors following a 24-day abstinence period. Males exposed to nicotine vapor or either dose of THC alone also demonstrated this increased cue-induced nicotine seeking. However, adolescent exposure to nicotine via injections in either sex or to nicotine vapor in females did not result in this later enhanced nicotine seeking behavior. Interestingly, for both sexes, co-exposure to nicotine and THC at either dose in adolescence does result in this incubation of nicotine craving effect in adulthood, even when single drug exposure does not. Nicotine and cannabis use during adolescence has been shown to have lasting implications on later learning and memory. However, our findings did not reveal any differences in the subjects’ abilities to learn the operant food training task in either sex. All groups were able to sufficiently dissociate between the active and inactive levers during training and further achieved the lever pressing criteria within a similar number of sessions. Rather, differences in lever pressing behavior were only found in later sessions once the learning already occurred. Males co-exposed to the higher dose THC and nicotine during adolescence as well as females exposed to the higher dose of THC alone demonstrated a higher level of responding for this task and maintained a more persistent drive to obtain food, which may be indicative of greater hedonic value of food for these subjects.

Building on and expanding the scope of the international obligations enshrined in the Vienna Convention and the INCB recommendations, the US has made extensive use of bilateral treaties to create an issue-linkage between states’ willingness to adopt zero-tolerance models of drug policy and their eligibility for foreign aid. Over the next decades, such bilateral agreements provided a basis for the operation of extensive cooperation and capacity-building projects in countries as diverse as Afghanistan, Colombia, Mexico, Nigeria, Peru, Ghana, Thailand, and many others. Along with these multilateral and bilateral instruments used to influence the drug policies of other countries, the US government has had an extensive reliance on unilateral tools of imposing economic and reputational sanctions on non-compliant states. In 1986, Congress introduced the Omnibus Drug Enforcement, Education, and Control Act, which created a certification process for drug-producing and drug-transit countries.The certification process requires the president to withdraw financial assistance and support in multilateral lending institutions from countries that fail to comply with requisite benchmarks of anti-drug policy. To enable congressional deliberations over such sanctions, the US Department of State submits an annual International Narcotic Control Strategy Report that identifies the major illicit drug-producing and drug-transit countries and evaluates the extent to which their domestic policies are in compliance with the US counter narcotic agenda. The INCSR narrative explores a wide range of countries . The certification process is applied to countries included in what came to be known as the Majors List .

The success of the US to coerce and to induce dozens of countries to adopt its preferred models of implementing cannabis prohibitions promoted convergence of drug laws across jurisdictions and thus increased the degree of concordance between the transnational and the national levels of this TLO. However,rolling grow tables the global diffusion of tougher cannabis laws cannot be sufficiently explained by focusing on the coercive mechanisms employed by the US alone. This diffusion was also a product of broader social transformations stimulating increasing political mobilization around law and order issues during the final decades of the twentieth century.41 Illustrating Durkheim’s observation that societies have a functional need to construct categories of deviance,the instigation of moral panics concerning drug abuse epidemics provide a useful tool of identifying “suitable enemies” and scoring political points.In an era during which a broader shift from welfare oriented to punitive-focused approaches to governing social marginality took place,strengthening state capacities to condemn and to penalize drug dealers and users proved to be a far more attractive project for politicians than undertaking to address the public health implications of drug use. As the primary international organization responsible for monitoring the implementation of the UN drug conventions, the INCB played an important role in facilitating the concordance between the transnational and national levels of the cannabis prohibition TLO. In its annual reports, the INCB has repeatedly supported the “gateway drug thesis,” according to which the use of cannabis serves as a risk factor in increasing the user’s probability of using harder illicit substances, such as amphetamine, cocaine, or heroin. Based on this thesis ,the Board’s 1983 Report criticized those “circles in certain countries” that “apparently assume that to permit unrestricted use of some drug, regarded by them as less harmful, would permit better control of other drugs which they deem more perilous to health.”

This criticism was leveled at supporters of the separation of markets strategy, which came to be endorsed by Dutch policymakers at the time.In its later reports throughout the 1980s and 90s, the Board adopted an increasingly critical stance toward the Dutch attempts to depenalize cannabis usage. In its 1997 Report, the selling of cannabis in coffee shops was depicted as “an activity that might be described as indirect incitement.”The focus on the Netherlands and its singling out for disapprobation reflects the rarity of open contestations of the prohibitionist imperatives enforced by the Board during that period. The extensive institutionalization of the cannabis prohibition TLO throughout the 1980s and 1990s facilitated the international spread of tougher laws, severer penalties, and more aggressive policing strategies. However, the very success of this TLO to propagate its policy models highlighted its failure to deliver on its own promise to reduce the prevalence of cannabis use and to eliminate its illicit supply chains. The intensification of enforcement activities also brought into focus the adverse human rights impacts of implementing the prohibitionist cannabis policies. The increasing criticisms of the failures and boomerang effects of the cannabis prohibition TLO prompted both internal and external processes that eroded its legitimacy and compromised its ability to continue guiding the practices of legal actors at the national and local levels. From the early stages of the institutionalization of the cannabis prohibition TLO, it became vulnerable to criticism of its inherent input legitimacy deficiencies. As discussed earlier, the central role played by the US in shaping the goals and strategies of this TLO has largely depended on the exercise of unilateral measures of coercion and inducement. The degree to which the certification process has realized basic standards of transparency, inclusiveness, and accountability is obviously limited. The procedures by which the INCB defines and applies its compliance criteria seem conspicuously insulated from ongoing public debates regarding the impact of cannabis prohibition laws on marginalized populations.

These legitimacy deficits are conveniently set aside by proponents of the war on drugs, who tend to focus more on the ability of these measures to promote global public goods than on the quality of the processes through which these measures are created. As Niko Krisch observes, such tendency to prioritize output legitimacy considerations is pronounced in various contexts of global governance and often produces pressure to move toward more informal and hierarchical modes of transnational governance in these issue-areas.However, this view is becoming increasingly difficult to maintain in the issue-area of cannabis policy given the mounting evidence on the failure of this TLO to achieve its regulatory goals. Despite billions of dollars of investment and extensive law enforcement resources, a sizable body of scholarship has documented the growing availability of the drug during the 1990s, the widespread prevalence of its usage among adolescents, and the increasingly tolerant attitudes toward cannabis consumption among both users and non-users.Drawing analogies to the failure of the “Noble Experiment” of the alcohol prohibition period,criminologists developed thorough critiques of the underlying assumptions of the cannabis prohibition TLO. The assumption that the availability of cannabis can be meaningfully reduced by the deployment of militarized policing strategies has been criticized for overlooking the resilience of cannabis markets and their high levels of adaptability to changes in their regulatory environments. Studies have shown that rather than eliminating supply chains, such interventions served to disperse, displace, and fragment supply sources and distribution routes.In turn, such interventions precipitated a spillover of armed violence to new geographical areas and exposed otherwise uninvolved indigenous populations to new risks and insecurities. The inherent flaws of this dimension of the cannabis prohibition TLO are often illustrated by referencing the “balloon effect” metaphor, depicting the ways in which efforts to suppress the cultivation of cannabis in one geographical area causes a convenient shift of its production elsewhere. The legitimacy of the cannabis prohibition TLO has also been damaged by evidence regarding the immense human rights violations that the implementation of war on drugs policies has entailed. Advocacy networks led by prominent transnational NGOs,flood drain table such as Amnesty International and Human Rights Watch, have exposed the disproportionate punishments imposed under the banner of the war on drugs in various countries. In the US, such criticism focused on the contribution of marijuana prohibitions to the nation’s internationally unparalleled incarceration rates and its distinctive patterns of racially-skewed law enforcement.A recent ACLU report using data extracted from the FBI’s Uniform Crime Reporting Program indicates that between 2001 and 2010, there were over eight million marijuana arrests in the US, of which 88% were for marijuana possession.In 2010, there were more than 20,000 people incarcerated for the sole charge of cannabis possession. Outside of the US, human rights activists focused on the increasing use of capital punishments for drug offenses from the late 1980s onward, as part of the broader escalation of enforcement efforts during the war on drugs era.The exportation and importation of illegal drugs constitute capital offenses in more than 30 countries. In China, Saudi Arabia, and the Philippines, the death penalty is exercised regularly for cannabis trafficking offenses. By the mid-1990s, the criticism leveled at the cannabis prohibition TLO began to stimulate increasing advocacy activity in favor of reform.

These activities failed to change the direction of drug policy making at the international level. Indeed, the “outcome document” issued in the wake of the 2016 UN General Assembly Special Session on drugs kept in place the existing framework of cannabis prohibition and did not endorse the calls to reclassify cannabis as a less dangerous drug. However, the criticism of the prohibitionist approach had a considerable transformative impact on the development of drug policies at the national and subnational levels. Before long, the diffusion of liberal cannabis policies across national borders began to jeopardize the normative settlements institutionalized by the cannabis prohibition TLO in previous decades. The efforts to liberalize cannabis regulations have focused on three distinct models of reform: depenalization, decriminalization, and legalization. Under formal depenalization regimes, the possession of cannabis is still formally prohibited; however, such prohibitions are enforced through intermediate justice measures rather than through conventional penal sanctions such as incarceration. The Netherlands pioneered the experimentation with depenalization strategies in 1976 when it formalized the use of the expediency principle to guide the enforcement of drug prohibitions. Based on this principle, Dutch prosecutors are instructed not to bring charges when cannabis use offenses take place within the user’s home or within the so-called coffee shops, where cannabis can be openly consumed and purchased.From the 1990s onward, many national and subnational jurisdictions introduced cautioning and diversion schemes to deal with drug use offenses.Cautioning schemes authorize police officers to avoid arresting suspected drug offenders under certain circumstances. Instead, the cautioning schemes require them to issue a written warning of the possible consequences of the illegal behavior. Diversion schemes, which may operate at the pre-trial, pre-sentence, or post-conviction stages of the legal process, are intended to shift offenders from the criminal justice system and its carceral institutions to other channels of legal intervention. When applied before the sentencing stage, such measures may require the offender to participate in certain treatment and education programs as part of the bail conditions. After the sentencing stage, diversion measures may subject a convicted offender to community-based or rehabilitative measures . The widespread transnational diffusion of depenalization regimes is enabled by the structural mismatch between the actors shaping the formal rules of the international drug control system and those implementing these rules in national and local contexts.The diffusion of these regimes was not initiated by international organizations or powerful countries. Rather, it has evolved through uncoordinated processes of institutional isomorphism, reflecting converging professional concerns regarding the complexities of implementing criminal prohibitions that are extensively violated by ordinary citizens and that do not reflect widespread social disapprobation of the targeted activity. From the perspectives of ground-level enforcement officials and more senior bureaucratic elites, the implementation of cannabis prohibitions raised pragmatic concerns regarding the limited effectiveness of conventional penal measures and the immense costs that such efforts entailed. In democratic systems committed to the principle of legalism, it seems natural to expect that schemes of depenalization would translate into de jure changes in the statutory definitions governing processes of criminalization. The international drug conventions place constraints on the ability of national legislatures to introduce such reforms. However, the treaties also contain textual ambiguities that provide leeway for negotiating the scope and ambit of such prohibitions. The movement began to gain ground in the early 1990s, focusing its efforts on promoting ballot initiatives at the municipal and state levels in the US.Within the next two decades, it effectively initiated the enactment of laws decriminalizing the medical use of marijuana in thirty-one states across the US and inspired norm entrepreneurs in dozens of other countries to campaign for the adoption of similar models.