Cannabis Grow

Fragments were visualized by silver staining with a commercial kit . Scoring for each marker was double checked, and any ambiguous accessions were rerun, or scored as missing data. In the later part of the study, fragments were separated and sized on an ABI 3130 Genetic Analyzer . Products from up to four primers were analyzed in one injection by using different fluorescent labels on different primers and taking into account the expected fragment size. PCR products were added to an 11 μl: 0.2 μl mixture of HD-formamide and GeneScan HD 400 ROX as the internal size standard, respectively. The fragments were denatured for 2 min at 92°C then injected into a 36 cm capillary filled with the polymer POP-7 . Fragment sizes were determined and rounded using Genotyper 2.5 software . Four to six common V. vinifera cultivars were used as an internal control and to ensure allele calls were consistent with samples run on silver stained sequencing gels.Allele size data for 133 accessions from the INRA Domaine de Vassal germplasm collection were generated in France for 20 SSR markers following procedures described by Laucou et al.. Allele sizes were transformed to match the allele sizes from the UCD data set based on known references and samples common to both group’s data sets. Multi-locus accessions from the INRA set were compared to the UCD data set to identify synonymous samples. Unique accessions from the INRA set were analyzed at UCD with an additional 14 markers to increase marker overlap with the UCD data set.Powdery mildew resistance evaluations were made on selected accessions in a field nursery trial under unsprayed conditions. These trials were carried out in the summer of 2009 and 2010. Accessions that carry either one or both flanking SSR marker alleles linked to the Ren1 locus were evaluated.

Powdery mildew resistant and susceptible accessions from the UCD breeding program, flower bucket and well known resistant interspecific hybrids and highly susceptible V. vinifera cultivars were used as positive and negative controls . A total of 65 accessions were screened in 2009. Five to six replicates of each accession were propagated from hardwood cuttings and planted in three field nursery rows with 30 cm between plants and rows. Powdery mildew symptoms were evaluated based on the extent of infection following the Organisation Internationale de la Vigne et du Vin criteria and scored from 0 to 5: 0 ; 1 one or two very small spots; 2 limited patches of powdery mildew infection; 3 patches of infection wider than 5 cm in diameter; 4 many powdery mildew infection spots and abundant mycelium growth; and 5 where leaves and other Thissue types were covered with unlimited patches of powdery mildew infection. In 2009, disease evaluations were carried out twice on the same plant during the last week of August and last week of September. Each observation was considered as one replicate for that accession. A total of 43 accessions including positive and negative controls were screened in 2010 . The majority of these accessions were Chinese or Central Asian species that were difficult to propagate by hardwood cuttings. These accessions were propagated from herbaceous cuttings that were dipped in rooting hormone and rooted under intermittent mist with bottom heat. Rooted cuttings were planted into small plastic pots and once established were planted into the field nursery. Disease symptoms were evaluated twice during the first week of September and first week of October as described above. Four of the wild V. vinifera subsp. sylvestris accessions with the resistance allele of the closely linked marker SC8-0071-014 were screened in 2012 under the conditions described above. Accessions maintained in the INRA collection that had Ren1 linked alleles were evaluated for powdery mildew resistance in an unsprayed greenhouse with susceptible controls and artificial inoculum in 2012. Because powdery mildew disease symptoms were recorded as discrete categories, the ordinal logistic regression model platform of JMP was used to estimate the effectiveness of the screen by comparing the significance level of genotype, date, field nursery bed and year.

Two SSR markers were reported to co-segregate with Ren1 locus in ‘Kishmish vatkana’ and ‘Karadzhandal’. A sequence fragment was obtained using the PN40024 genome by aligning the sequence of SC8-0071-014. Primers were designed around the region of SC8-0071-014 that generated a 625 bp ampliftication product. PCR products were cloned for 16 accessions using the pGEM®-T Easy vector system using standard protocols. ‘Khwangi’ was the seventeenth accession that had the 143 bp allele, but it was powdery mildew susceptible in the field trial and was not included for sequencing. Eight to twelve positive colonies were selected for each accession and DNA was extracted using the Qiagen plasmid mini kit. PCR ampliftications were carried out with the SC8-0071-014 primers in order to identify two alleles of each accession using standard protocols. Sequencing with SP6 primer was carried out only on those samples that represent 143 allele haplotype. Sequences were aligned with the Clustal V method by using the MegAlign application of DNASTAR Lasergene V8.1.Accessions with seven or more missing data were not included in the genetic diversity analysis. Next, two different data sets were prepared: the first set consisted of 394 unique accessions that included interspecific hybrids, European reference wine grape varieties and North American species; there were 380 accessions in the second set after the 14 samples of hybrids, North American species and European wine grape varieties were excluded. Simple matching distance was calculated with 19 and 34 SSR markers on both data sets. Hierarchical clustering and principal coordinate analysis were carried out with DARWIN V5.0.158 to determine the number of groups. Following these analyses, STRUCTURE V2.3.1 was used to infer the number of clusters with 19 and 34 markers, and with both data sets of 394 and 380 accessions. The membership of each accession was run for a range of genetic clusters with K values of 1 to 10 using the admixture model, and it was replicated 10 times for each K. Each run was implemented with a burn-in period of 100,000 steps followed by 400,000 Monte Carlo Markov Chain replicates using no prior information and assuming correlated allele frequencies.

The posterior probability was then calculated for each value of K using the estimated log-likelihood of K to choose the optimal K . The results from STRUCTURE were displayed by DISTRUCT software. The microsatellite tool kit software was used to calculate standard parameters of genetic variability: expected heterozygosity ; allele frequencies ; and observed heterozygosity . The deviation from Hardy-Weinberg equilibrium at each locus was examined by calculating the inbreeding coefficient ‘FIS’ for each group, and the overall differentiation index ‘FST’ with FSTAT V2.9.3.2 software. The probability of identity , probability of exclusion and LOD likelihood ratios for potential parent-progeny relationships were calculated with FAMOZ software. The 10,000 simulated pairs were performed to identify a log of the odds ratios score threshold to assess a potential parent pair with 34 SSR markers. A discrepancy of a maximum of two loci was allowed to cover possible data errors, null alleles, and clonal mutations as previously described. Potential parental pairs were further evaluated if a discrepancy in the allelic data was observed. They were ampliftied and repeated either on denaturing polyacrylamide gels or using the ABI 3130 Genetic Analyzer. Additional markers were also added on putative parental pairs.Managing the benefits people receive from nature, or ecosystem services, requires a detailed understanding of ecosystem processes. In particular, biodiversity-driven services, such as pest control on farms, requires knowledge of cropping systems, the habitats in and around croplands, square flower bucket and the interactions among the many organisms that inhabit them. Interactions are complex and often change over space and time ; therefore, a critical first step is identifying the species and populations that provide benefits to society . Identifying service providers, however, may not be straightforward. For example, predation is rarely witnessed directly, making it difficult to identify the predators of crop pests. Pest control is a critical service; in the United States, insect predators save farmers billions of dollars annually in avoided pest damage . Several different techniques have been utilized to identify predator–prey interactions. An indirect approach is using stable isotopes to determine trophic positions . A direct approach for identifying predators is visual identification of prey remains in predators’ guts or feces . While visual identification of prey gut contents can sometimes yield the necessary taxonomic resolution to identify insect pests, the necessary inspection labor is considerable and sampling techniques often result in high mortality rates among study subjects. Molecular identification techniques, however, offer great potential to yield insight into predator–prey interactions . These techniques often rely on targeting and sequencing a standardized DNA region across species to facilitate identifications . Applications of this approach are diverse; for example, detecting diet shifts in ancient humans , characterizing biological communities in hydrothermal vents , identifying illegal trade in endangered species , and surveying rare mammals with DNA from leeches . Similarly, molecular identification in feces,regurgitate, and stomach contents from carnivores, insectivores, and herbivores of diverse taxa has been used to infer diet . While the application of molecular diet analysis is becoming widespread, the technique is not without limitations. First, predators vary in gut retention times and digestion processes, which may affect detection rates and complicate comparisons among species . Second, DNA assays can misattribute diet in the presence of intraguild predation— that is, if the DNA of the prey of an intermediate predator is found in the fecal samples of a top predator . Finally, digestion degrades prey DNA, making fecal analysis more sensitive than other PCR procedures to DNA quantity . Despite these shortcomings, several studies have used molecular techniques to identify suites of pest predators, largely through DNA analysis of arthropod predators’ gut contents . Less work has focused on vertebrate insectivores, despite their great potential to control pest infestations .

Those that have studied vertebrate predators of insect pests tend to analyze single predator species rather than communities . Further, analyses have neglected the biologically diverse, tropical countries that may stand to benefit most from conservation-minded pest-management plans . We used molecular fecal analysis to identify bird predators of coffee’s most damaging insect pest— the coffee berry borer beetle . Coffee is cultivated across the tropics, with a total export value over US$20 billion and twenty million households involved in its production . The borer has invaded almost every coffee-producing country in recent years. In fact, the borer invaded Costa Rica in 2000 and our study sites in 2005. It spends the majority of its liftecycle within coffee berries, overwintering in unharvested berries and undergoing a major dispersal event several months after the first rains . Previous exclusion experiments have shown that birds consume the borer, likely during the primary dispersal event or secondary movements to adjacent berries throughout the year . The borer’s small size makes directly witnessing predation unlikely . Our work builds on Karp et al. , which used exclosures to quantify bird-mediated borer control. Here, we sought to characterize more completely which species are borer predators, supplementing their analysis with an additional 961 fecal samples and 33 bird species . In addition, we verified this approach through feeding trials with three insectivorous bird species. Finally, we compiled a database of bird conservation and functional traits to make a preliminary determination of the traits associated with borer consumption and to assess whether species that important for controlling damaging insect pests are also conservation targets.Our investigation cenThered on coffee plantations in southern Costa Rica, near the Las Cruces Biological Station of the Organization for Tropical Studies. We worked on two coffee plantations—a small family plantation and a large commercial operation. Both are situated at ~1100 m asl, and cultivate coffee under sun. We collected fecal samples from birds in April-May of 2010 and 2011, when borers were at peak dispersal. All animals were treated humanely, in accordance with the Institutional Animal Care and Use Committee guidelines and approved by the Administrative Panel on Laboratory Animal Care of Stanford University . We placed three mist-netting stations at each plantation and visited each station three times per year. Each station was composed of 20 12 m × 2.5 m mist nets, located between rows of coffee and within patches of forest next to plantations. Our surveys began at sunrise, continuing for 5–6 hours until bird activity subsided. All birds were placed in breathable cotton bags until they could be identified and uniquely marked with a metal leg band.

The case management database was embedded in the same Sea Table cloud-based platform as the GAL. Core components of the case management database that informed both process and outcome evaluation measures included data from the Enrollment Form, Exit Form, and the Demographics Questionnaire. Upon enrolling a student, a RAYS program coordinator was responsible for recording the reason for referral to the RAYS program, date of enrollment, student status, school information, point of youth diversion, participation status , and any notes from the disciplinary incident report. During this same meeting, students were prompted to complete the Demographics Questionnaire, which collected information on race/ethnicity, gender identity, and age. Once the student completed RAYS, a program coordinator would submit an Exit Form where they would document the RAYS activities that the student was initially assigned via their Restorative Plan, which ones they completed, reason for exiting the program , and date of the program exit. Individual data from the Enrollment Form, Exit Form, and Demographics Questionnaire all formed each enrollee’s Student Profile which was linked to any RAYS activities that a student participated in.To inform the outcome evaluation, pretest and post test surveys were developed and administered to students to examine any changes in the enrollees’ sense of self-responsibility, past 30-day AOD use behaviors, perceptions of AOD use, and awareness of resources. Questions and scales were adapted from the 2019-20 California Student Tobacco Survey and the 2021-22 Mapping Youth Health Behavior Survey , 4×4 grow tray both of which are population-based survey instruments developed and utilized by Professor Shu-Hong Zhu’s research team with dimensions in substance use and relevant covariables .

Both pretest and posttest survey instruments were programmed and administered using the Qualtrics PlatformXM . The pretest included approximately 35 questions on the above mentioned variables while the posttest included an additional 6 questions on student experiences in RAYS. Students took approximately 8-10 minutes to complete either survey. Participants were asked whether they had used marijuana , vapes with nicotine or just flavoring, alcohol, or opioids to get “high” in the last 12 months. Questions pertaining to opioid use were not added to the pretest and posttest instruments until Fall 2022; as such, data on opioid use behaviors and perceptions are not reported here due to the low number of responses. Utilizing a skip logic design, participants were asked to indicate past 30-day use of any products they said they had used in the last 12 months. Participants were also asked product-specific follow-up questions on frequency of use and intentions to quit any product they reported using in the past 30 days . All students were prompted to indicate their perception of the harm of using each substance “some days” and “every day” with a 5-point scale ranging from “not at all harmful” to “extremely harmful”. A 4-item scale on self-responsibility and personal awareness included questions derived and adapted from Mergler and colleagues’ personal responsibility scale for adolescents. A 4- item Likert scale was used to assess student awareness of resources. For the posttest instrument only, students were also prompted to assess their overall experience in RAYS via a 3-item Likert scale reflecting on RAYS components and likelihood of recommending the program to others. Additional open-text questions prompted students to provide feedback on what they liked and disliked about the program, as well as what they believed could be changed.

RAYS program coordinators administered the pretest to students upon program enrollment, ideally prior to their first exposure to an intervention activity. The posttest was administered to students upon exiting the program . Each RAYS student was randomly assigned an alphanumeric passphrase upon enrollment which was linked to their student profile in SeaTable. Students were instructed to enter their assigned passphrase when taking the pretest and posttest surveys to allow for longitudinal linkage. Pretest and posttest responses were linked utilizing these passphrases in lieu of student names. Prior to analysis, data was deidentified by reassigning each linked pretest and posttest response pair with a new passphrase to ensure student confidentiality and by removing the linkage to their respective student profiles.Suspension data was extracted from the CDE’s public data repository, DataQuest. Multi-year, aggregate reports on suspension counts were exported for each of the four school sites in Nevada County. Four comparable school sites were matched to the Nevada County sites and used as comparators. Discipline data reports from comparable sites were included in this study to examine any differences in the number of suspensions over time from Nevada County sites. Data was categorized into overall suspension and drug-related suspension counts to allow for the examination of changes in drug-related disciplinary incidents from the 2017-18 to 2021- 22 academic year.Data from the SeaTable activity log and case management databases for the reporting period May 2021 to January 2023 were exported and converted to Microsoft Excel® files. Activity data was cleaned, filtered by implementation date, and tabulated to report the number of activity exposures by attendee type . Case management data, including demographics and enrollment and exit data, was cleaned and relinked to passphrase-matched enrollee profiles. Suspension data for Nevada County schools and matched comparable sites was examined for changes in overall and drug-related suspensions from the 2017-18 to 2021-22 academic years.

Comparable school sites from a neighboring county were identified utilizing school-level data from CDE site profiles. Each Nevada County school was matched with a comparable site based on enrollment size, racial/ethnic breakdown, and regional proximity. For reference, during the 2021-22 academic year, all four Nevada County sites reported a cumulative enrollment of 3,001 compared to 2,900 at the comparable sites. No drastic changes in enrollment numbers were reported for either the Nevada County or the comparable sites from the 2017-18 to the 2021-22 academic year. RAYS program coordinators approved the selection of these comparable sites. Differences in these suspension counts between Nevada County schools and comparable sites were examined to inform the evaluation of the potential impact of RAYS on the number of disciplinary incidents over time. Pretest and posttest survey data was exported and converted to Microsoft Excel® files from the Qualtrics PlatformXM® online survey database. Using the randomly assigned passphrases, each respondent’s pretest and posttest data was linked to analyze behavioral outcome changes from pretest to posttest. Descriptive analytical methods were employed to tabulate counts and percentages for each question response option at pretest and posttest. To evaluate changes in enrollee knowledge, perceptions, and behaviors, the percentages of participants who selected each response option for each question were compared from pretest to posttest. All percentages reported are of the total pretest and posttest survey sample . RStudio© statistical software was used to conduct all analyses while Microsoft Excel® was used to tabulate all activity and case-level data.The following sections report results from the RAYS pretest and posttest survey responses. The findings reported here should be interpreted with caution given that these results are from an intermediate evaluation. All findings are preliminary and should not be considered as a comprehensive assessment of the RAYS program. Additionally, greenhouse racking due to a small pretest and posttest survey sample size, data may not be inclusive of all students who participated in the RAYS program. Overall, a total of 21 out of the 48 participants who exited RAYS during this evaluation period submitted a matched pair of pretest and posttest survey responses, equating to an approximate 43.75% response rate. Discussions with program coordinators revealed unanticipated logistical challenges with ensuring all students who exited RAYS submitted both pretest and posttest survey responses. Nonetheless, current protocols are being revised to increase pretest and posttest survey response rates. Despite these limitations, the findings reported here may provide insight into the potential individual-level impacts of the RAYS program on select variables of interest.Differences in student responses to questions on self-responsibility and personal awareness from pretest to posttest are found in Table 5.

The proportion of students who strongly agreed or somewhat agreed with statements on self-responsibility did not significantly change from pretest to posttest. There was a slight increase in the percentage of students who agreed that before they do something, they think about how it will affect the people around them; however, agreement levels for other statements remained the same or did not change drastically.Table 6 presents the percentage of students at pretest and posttest who reported using a substance in the last 30 days. Out of the 21 students, 52.38% reported having used a marijuana product in the last 30 days at pretest whereas 38.1% said they had recently used marijuana at posttest. A similar reduction was seen with the proportion of students reporting past 30-day vape use, with 66.67% of students reporting using a vape with nicotine or just flavoring at pretest and 38.1% at posttest. There was a slight decrease in the percentage of students who said they had drunk alcohol, with 19.05% reporting past 30- day alcohol use at pretest and 9.52% at posttest.To measure changes in awareness of resources prior to and after going through RAYS, students were prompted to indicate how much they agreed with statements on identification of services and resources at their school. Table 8 reports the proportion of students who either somewhat agreed or strongly agreed with statements on student self-efficacy of being able to identify mental health and substance use services. There was a slight increase in the percentage of students who believed they could name at least one person or place that they could go to for support with mental health-related issues with 90.48% saying they could at pretest and 95.25% at posttest. Awareness of support or resources for substance use-related issues also increased, with 71.43% saying they would be able to name a place or person at pretest and 90.48% at posttest. When asked if they would be able to refer a friend or classmate to such services, 71.43% said they would be able to at pretest and 85.71% at posttest.To assess overall student experiences in RAYS, participants were prompted with both quantitative and open-text questions at posttest. Table 9 presents the proportion of students who either somewhat agreed or strongly agreed with statements regarding RAYS. Of the 21 participants who exited RAYS between August 2021 and January 2023, 80.95% believed that the program helped them to think about how their substance use affects others. The majority of students found the resources provided through RAYS to be available when they needed them. Additionally, 80.95% said that they would recommend the program to others.Students were also asked what they liked and disliked about RAYS and what they would change about the program via open-text questions. Overall, enrollees expressed their appreciation for the education received through RAYS, with some students highlighting their preference for substance use education in lieu of traditional forms of punishment. Some students also indicated that they enjoyed learning about drugs, what is and isn’t a drug, and how to identify harmful substance use behaviors. One student noted the information they learned through RAYS was “valuable” and that they could “take [it] with [them] in life” citing the program as a “second chance” to change their health behaviors. One student specifically mentioned how it “wasn’t just adults involved” but also other “kids going through things just like [them], with the same experiences that [they] have”. Enrollees also cited the people involved as important contributors to making the program helpful and enjoyable. Students described the individuals involved in administering and implementing RAYS as welcoming and open-minded, fostering a non-judgmental environment. One student noted how RAYS advocates and staff are “open and listen to what you have to say” and provide valuable support in helping the students obtain the resources they may need.The self-reflective nature of RAYS components was also brought up by multiple students. They noted how RAYS helped them to reflect on the mistakes that they had made in an educational rather than a punitive environment. These alternative to punitive approaches were highly regarded by students as something valuable and engaging. One enrollee said that they “liked that it gave [them] an opportunity to understand what [they] did wrong without just being taken out of school” while also giving them “the chance to take constructive criticism about [their] substance use”. Students also noted the community engagement piece in positive regards as something that allowed them to maintain a relationship with their peers and school community. When asked what they disliked about the program, most students noted that there wasn’t anything they felt that they strongly disliked or would like to see done differently. Nonetheless, a few enrollees cited aspects related to the logistics of program delivery and knowledge of peer advocates.

To address these limitations, future studies should incorporate validated, evidence-based instruments to measure suicide risk, such as the Suicide Probability Scale or the Suicide Inventory Questionnaire , which have been cross-culturally validated for use in Native American contexts . Validated, evidence-based instruments to measure the selected predictors should also be incorporated. Another limitation of this study is the need for further expansion and validation work to optimize its accuracy before deploying it in a clinical setting to improve clinical decisions. For example, the model’s transportability to Native American youth in different settings outside of California should be evaluated via external validation. The model’s development sample comprised participants from a non-randomized study, which may not be generalizable to Native American young people not in a public high school setting. Future studies may also benefit from incorporating a longitudinal design of the data to substantiate temporal precedence beyond the single academic year evaluated in this study. Furthermore, a limitation of the study is that it relied on existing data from a survey whose questions may not fully capture the relevant factors. Further research should investigate whether the model’s predictive value could be improved by adding other factors such as predictors in the spiritual-historical domain, which is absent from CHKS. One example includes the Historical Loss Scale , which is a validated instrument designed to measure historical trauma. Before using the risk scores in practice, the clinical utility of the model and its feasibility and acceptability need to be measured. Although a factor may be statistically significantly associated with suicidal ideation, as seen in previous research, grow trays it may not necessarily have predictive power and not contribute to predicting suicidal ideation in new cases as indicated by the subset of predictors excluded after lasso regression.

As such, even though foster care placement was not retained as a predictor in the final model, future studies should still consider this risk factor in conceptualizing suicide-related behavior. Despite these limitations, the study’s main analyses comprised 438 participants with the outcome and 10 potential predictors, which conforms to the minimum of 10 events per predictor variable required for reliable prediction modeling . Moreover, a robust 10-fold cross-validation was utilized for internal validation, which produces less biased estimates than split-sample validation, resulting in more confident predictions . Efforts to improve the reliability of solar photovoltaic systems have, to date, largely focused on the core components of modules and inverters. With weather-related damage becoming a prominent industry issue, the importance of failures with other array components such as racking, fasteners, and wiring systems now deserves industry attention. The entirety of the solar PV system must be examined for reliability. Statistically significant datasets of storm-caused failures validate and inform our understanding of weather effects and clarify conclusions and corrective actions. Emerging patterns of field failures as reported by stakeholder groups are beginning to provide evidence of current inadequacies in design, construction, and operations. These patterns of failures also are revealing ways to improve performance and durability related to severe weather events, which would help ensure that solar PV systems can be used as a resilient power source in diverse climates. The ability of the solar industry to incorporate lessons learned in a timely manner is essential for continued technological and financial advancement. Many industry stakeholders now have direct experience with weather impacts and have gained valuable insights into root failure modes, cost impacts, and performance and availability reductions.

These insights comprise critical lessons learned that should be widely shared, yet many firms keep this information private. Lack of dissemination of storm-damage data are a central barrier to widespread resolution of these issues. Current industry practice reflects a wide variety and immaturity of codes, standards, and design principles that result in unpredictable long-term operational outcomes. Intense price pressures, along with many new industry entrants and exits, may provide some explanation. There is a wide variation in the understanding and application of codes and standards, design practices, construction methods, and operations. Most important, many engineers lack awareness of where serious code gaps exist and how to compensate for them. Similarly, buyers of manufactured racking systems are unaware of the design flaws inherent in the products they are procuring for a project. There are many examples of code-compliant arrays that did not withstand forces of even routine weather events such as summer thunderstorms. The goal of this report is to provide an operations-focused synopsis of how solar PV systems are affected by both severe and regular weather events. The findings are drawn from an existing body of small research efforts and field observations that have implications for the design, construction, and operations life-cycle phases of a solar array. Nearly every location in North America experiences at least one form of severe weather . During the 30-year operating period of a solar PV system, it is statistically likely that a significant weather event will strike. Impacts stemming from severe weather events appear to present a serious hindrance to the continued advancement of solar PV as a resilient, cost competitive, and dispatchable energy source. Insurance data supports the assertion that weather-related impacts should be a serious industry concern.

Insurance data are tied closely to weather events, but an examination of insurance claim data is often very sensitive to the time period selected. Years may go by with no problems, but a severe weather event like a hurricane or hailstorm will affect a large number of systems all at one time. A research report by GCube, a leading insurance underwriter in renewable energy, highlights that weather-related losses are a leading cause of solar PV claims worldwide. Events such as tornadoes, floods, windstorms, and hail damage have all contributed to damages. From 2011 to 2015, weather-related events accounted for 49.8 percent of all insurance claims . There are regional differences in these claims; within North America, approximately half of all solar PV claims are attributed to weather impacts, while the global percentage is approximately 25 percentage . Generally speaking, there has been a significant increase in weather-driven PV claims in the last five years . The report also identified key factors that influence the financial impact, as well as recommendations for preventing failures in the future. Another analysis of insurance claims indicated losses to solar equipment using claim information from Verisk, a leading compiler of property-casualty loss data. It showed that 95 percent of the 15,128 claims over the period of 2014 to 2019 had weather-related causes. Figure 1. Of those weather-related causes, the most frequent cause of loss was from hail , the second most frequent cause was wind , and the third most frequent cause was fire . The largest average claim size for losses including solar equipment was from fire , followed by lightning . The fire claims in this collection of data concentrated around the dates of three large California wildfire events — indicating the significance of losses from these events.Peer-reviewed literature encompasses both experimental and field-related analysis regarding different influences of weather on PV systems. For example, Santhakumari and Sagar provided a comprehensive review of the impact of different environmental conditions on PV module performance. With regard to extreme weather events of snowfall and ice buildup, the authors noted that orientation and tilt angle of the modules can greatly influence the amount of production loss . Hail damage can also lead to power loss; up to 30 percent, due to impact cracks affecting electrical performance . A number of snow events were also documented in the Northeastern United States, leading to significant under performance in the region in 2011 . Andrews et al. monitored the PV system for two winters in Canada and determined that the losses due to snowfall were dependent on the angle and technology being considered. Over the two years studied , pruning cannabis the losses ranged from -3.5 to +1 percent of expected yearly yield for sites in southeastern Ontario. The increase in expected energy was attributed to increased albedo for modules with higher inclinations . Heidari et al. quantified energy losses of PV systems with different architectures, and tilt angles were quantified for a test site located in Calumet, Michigan. Based on their study, the authors found that snow-related energy losses ranged from 5 to 12 percent for three unobstructed, elevated modules, and from 29 to 34 percent for comparably tilted modules mounted next to the ground .

Although many of the researchers documented the influence of specific ambient conditions on PV systems , the primary discussions for extreme conditions are generally limited to a survey of damages observed for a general event. For example, Ghazi and IP noted that precipitation higher than 12 millimeters and wind speed lower than 30 kilometers per hour led to poor efficiency of PV panels in the southeast United Kingdom. However, this level of specificity is generally lacking in evaluation of extreme weather events, with limited information presented regarding the quantity, timing, or dimensions of the extreme weather events that led to specific PV system impacts and damages.The field observations reported here were documented by both U.S. Department of Energy laboratories and industry. The field-observed failures and a summary of the root cause failures is provided. The full list of field failures observed and discussed in this report is limited to examples that are considered by the authors to be the most common and serious, therefore, this is not a comprehensive list of field-observed failures. While this chapter presents an introductory overview, failures and losses from specific weather events are discussed in greater detail in subsequent chapters, and more suggestions for improvements are offered. Various aspects of PV projects can contribute to their failure, ranging from materials and people to codes/standards and business models. In a 2018 study, the Rocky Mountain Institute conducted field visits to investigate the root causes of PV system failures and survivals within the same region. They documented a number of recommendations to improve the resilience of PV systems during hurricanes . Failures during hurricanes were attributed to orientation issues, training, and module mounting hardware. For example, the report notes that systems that survived had bolted modules and lateral racking supports . The authors noted that in addition to specifying the different hardware used, collaboration is also needed to ensure that module, racking, and equipment suppliers are implementing representative load tests and are documenting associated assumptions . Specifications and construction guidance recommendations have also been made for rooftop systems, including the use of mechanically anchored PV rails and use of rated locking panel clamp bolts .Wind is the most common damaging element stemming from nearly every significant weather event. Design engineers use simple wind speed values plugged into software tools or hand calculations that are done to meet required codes. These simple wind speed values do not capture the unique wind dynamics that stem from different weather events, and thus the design of solar PV structures lack consideration of the highly dynamic forces that result from different storm types. Comparing, for example the wind speeds and resulting damage between hurricanes, tornadoes, and derecho events illustrates the need for engineers to adapt updated design practices. Even an F-0 rated tornado on the Fujita scale of less than 73 mph can easily destroy a solar array, while the same wind speeds from a hurricane or routine thunderstorm would do little damage. This is due to the high-pressure differentials generated by a tornado over a short distance with strong updrafts inside rotating winds. Similarly, there appear to be unique and dynamic forces stemming from the powerful down burst clusters generated with derecho thunderstorm events. More investigation is needed to fully characterize wind forces from different storm events, and these insights must be used to inform and update design practices.System owners and operators may be working under the false assumption that the bolted joints, fasteners, and racking systems can withstand the design wind speeds used to meet ASCE-7 code. Field evaluations of damaged arrays indicate failures are occurring at well below design wind speeds. Currently there appears to be poor correlation between design wind speed and actual wind speeds in terms of the survivability of solar structures. Some engineers have recommended the use of stamped structural drawing sets as a solution; however, there are concerns that the engineering process itself and underlying supporting calculations and software modeling tools need to be updated.

Food use is the second highest use category cited by Hutsul community members, with the common phrase, “food is medicine.” Many highly ranked culturally important food species are also noted for their medicinal qualities. Culturally important species are found in a variety of habitats, with different degrees of human interaction, providing accessibility during times of need or disturbance. Various regional changes, including lasting reverberations of colonial policies, commercial harvesting, illegal logging, and climate change are impacting the landscape with its effects cascading to culturally important species, which also have economic importance . Comparing ethnographic data to our findings on a species-by-species basis of noted fallback foods of the past show that many fallback foods have maintained cultural importance in the day-to-day lives of Hutsul community members, exhibiting a diversity of uses, while also serving as nutrient-dense foods in times of scarcity, uncertainty, and regional disturbance. It is this deep emergent response to disturbances, resultant of years of tumult seen through world wars, food shortages, shifting borders, colonialism, that drives resilience-thinking and action. The term resilience was first framed within boreal ecosystem functioning, attributed to Crawford Holling . Ecosystems retain a type of cyclical nature with an emphasis on persistence, change and unpredictability – elements embraced by modern adaptive management philosophy . Socio-ecological resilience became defined as the “capacity of a [social-ecological] system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity and feedbacks” . Socio-ecological resilience, pots for cannabis plants as it emerged in both discourse and reality, became a community of practice that engages both ecological and social sciences.

A resilience-based approach includes mitigating disturbances by strengthening and encouraging the self-healing capacity of ecosystems. Resilience looks directly into the face of change, crisis and uncertainty, as embedded parts of life. Ecosystems continually adapt to disturbances at various scales and cannot be managed formulaically to maintain optimal levels of functioning . It is the coupling and intertwining of both spheres, social and ecological, that elicits the complexity in understanding the dynamics of resilience in the region. In this case, the question is: how do Hutsul communities maintain livelihoods and self-determination in acquiring healthy and culturally appropriate food in the face of these disturbances?Traditional ecological knowledge in the region informs adaptive capacity through short term and long-term responses . As noted in the methods, interviews were conducted in Ukrainian, while participants responded both in Ukrainian and Hutsul. Language is a critical part of memory formation; culturally distinctive values, knowledge, meanings, and worldviews transit and emerge through language . How do Hutsul names relate to the environment? In Table 3.7, names allude to plant phenology, habitat, physical characteristics, medicinal qualities, gathering cues, taste as well as stories of colonial invasions, and historical land uses. A more extensive look at Hutsul ecocultural names is in Appendix C. Plants such as Acorus calamus and Orchis mascula are culturally important naturalized plants brought to Hutsulshchyna through the Mongol invasions of the 1200s. The story behind the introduction of Acorus calamus in this region coincides with Tatar invasion, illuminating the ecological placement of this plant in Hutsul culture, as expressed in the local name, which translates to “Tatar potion/herb.” Other local species names are connected to landscape elements that are prevalent and distinctive in Hutsul lifeways, including “toloknyanka” and “polonynskyi hran” . These plants are found, respectively, on tolokas and polonynas; culturally and biologically cultivated areas for centuries. As described in Table 3.1, tolokas are traditionally held pastures located typically on a nearby hillside from the home, and passed down from one generation to the next, ensuring both connection and access to land. Polonynas are summer alpine meadows, providing grazing for communal livestock, which produce culturally important dairy products. All livelihoods of Carpathian highland people are somehow tethered culturally or economically to the maintenance of polonynas .

This ecocultural memory is embedded in language and practiced through maintenance of polonynas. In forest-dependent communities, human interdependence with the land is nurtured and recognized daily – whether it is going to the communal hillside to milk the cows, or to gather mushrooms for a religious meal in the surrounding conifer forests. Hutsul communities in the Carpathian Mountains have maintained and passed down many ecocultural memories, forming the foundation of traditional ecological knowledge. Ecocultural memory guides day-to-day practices, embedding TEK to place and culture. TEK is embedded not only in the spoken language or words that are used to describe plants or landscapes; it is practiced through the acts of gathering and interacting with the local ecology. Holidays, songs, traditional foods, embroidery, dance keep this memory living through practice. For example, memories are nested in family recipes of traditional foods derived from the landscape. The direct reliance and interactions with abundant ecosystems prove the importance of maintaining regional biodiversity, while community structure facilitates a self-reliant, socioeconomic stability in the region. Memories become lived experiences through practice and through active acknowledgement. A memory that fades, no longer exists in said reality. Additionally, a practice without memory also faces risk of extinction. Due to regional ecosystem, climatic and cultural changes, TEK can present itself in disjointed, incomplete ecocultural memories; memories that are not continuously or completely passed down from one generation to the next. For example, placing boughs of a sweet flag , branches of Quercus robur or branches of Carpinus sp. at the entrances and gates of houses on a holiday without knowing why, is an example of expressing an active, practice upheld by disjointed memory without context. Without TEK recognized and nurtured, contextualizing the past to forge a future can ultimately be challenging, ultimately leading to threats of TEK loss. TEK forges the coping mechanisms and adaptive strategies that emerge in maintaining a food system that culturally ties people, health, and land; TEK is the thread that unites ecosystem health and resilience to regional sustainability. There are two distinctive responses to mitigate disturbances and support adaptive capacity: short-term and long-term . TEK informs these responses, providing a basis for supporting food sovereignty.

Two important coping mechanisms include: 1) modifying subsistence activity patterns, or changing how, where, and when to gather culturally important plants, and 2) incorporating a diversity of species use intensities at various landscape levels. These are adaptive, immediate responses based environmental changes mentioned above. They include shifts in climate patterns and logging practices, compounded by land degradation seen continuously through erosion , pollution and flooding . Increased seasonal variability and logging have caused local communities to adjust the timing of their seasonal gathering and garden planting. Phenological shifts in flowering, and extended rainy seasons as described by local experts have resulted in shifts in gathering practices of culturally important plants. Waiting has become a common coping strategy for community members as they inform one another on the status of flowering or fruiting of economically important species. Another response has been following plant communities, especially medicinal species, as they climb in elevation. Due to climatic shifts, certain species are now found at higher elevations , causing community members to hike to higher elevations to gather. The question of accessibility arises in response to climatic shifts impacting distance and time need to gather cultural important medicinal species for community members . In addition to climatic changes, illegal logging remains a significant regional challenge, indoor cannabis grow system causing increased flooding and erosion in the last decade . WWF Ukraine has determined that 44% of the timber harvested from the Carpathian Mountains and exported to the EU is illegal , reinforcing the fact that sanctions for committing forest crimes remain unenforced. The use of multi-time satellite images, DNA and isotope analyses of wood and local activism has recently helped combat illegal logging in the region . In a recent study in Northern Bukovina in Ukraine, Hutsul knowledge holders stated that exploitation of forest resources is driven by immediate economic return, with logging companies harvesting timber year-round . The impacts of illegal logging, as stated by Hutsul locals, encourages succession of species such as Rubus idaeus, Rubus caesius, Vaccinium myrtillus, Chamaerion angustifolium, Orchis macula, and Aronia melanocarpa. These culturally important species are used, appreciated, and gathered fairly frequently, for personal use and sold. However, community members note that species such as Rubus caesius can hinder forest growth and regeneration, and the gathering of these species helps manage forest health. Illegal logging also weakens mushroom growth and nutrient cycling, impacting cultural gathering of mushrooms. By modifying and continually adapting to both climate change and logging impacts within the region, coping mechanisms arise such as waiting, communicating with other community members, and shifting gathering practices to higher elevations.Another coping mechanism includes varying the intensity of habitat use as well as gathering culturally important species in various habitats . Communities are reliant on the diverse landscapes for their nutritional needs, spatially radiating from homes to gardens , pastures, fields, tolokas , meadows, woodlands, forests , alpine meadows as well as culturally-tended alpine meadows called polonynas , and more recently the incorporation of local, convenience stores. These radiating layers of habitats nest spatially, and vary in use intensity temporally. Some landscape levels are used more intensely in targeted seasons, ensuring time for regeneration and growth. Other levels are used at a constant low intensity and require accounting of time and distance to resource. Each of these nested habitats provides a layer of redundancy, ensuring a societal effort to live sustainably within the limits of the environment, while actively monitoring habitat changes from season to season. Additionally, most culturally important species are found in a range of habitats with varying levels of human structuring, ensuring availability to communities . Diversification is a well-known risk-spreading strategy used to mitigate unexpected events and uncertainty , by increasing system complexity . By identifying potential food and medicinal resource redundancies and spreading out use intensities in a variety of habitats, coping mechanisms emerge, helping to secure both ecosystem and community survival. Reliance on local forests, tolokas, fields, meadows, woodlands, and pastures requires observation of conditions and vegetative states of preferred plants. If family pastures are maintained , grazing and milking of livestock requires interaction with landscape and observation of ecological and weather changes. Dialogue between locals and their surrounding forests occurs ritualistically with sharing traditional meals as well as observation of specific Holy days that integrate blessing of these species . For example, August is a particularly important month for the blessing of healing herbs, plants, flowers, and grain, which coincides with the time where most herbs, flowers, stems, leaves, and roots are collected. Among many observed holy days, there are four holy days that occur in the summer that integrate plant use into Christian church ritual . There is acknowledgement of the importance of the environment in daily nourishment as seen through community gatherings on church holy days . They address community needs to maintain diversity, redundancy of species’ uses and landscape types, while managing connectivity of culturally important species and people through holidays, song, and traditional food; Ultimately, holidays act as mechanisms to maintain ecocultural memory, keeping TEK alive. While coping mechanisms play an immediate, responsive role in maintaining resilience, Hutsul communities have also integrated long-term adaptive strategies. These strategies include modifying rules and institutions to ensure livelihoods . Adaptive strategies are grounded in TEK , slowly changing, and emerging at larger spatial scales. In their work in Arctic communities, scholars including Krupnik and Jolly among others present two adaptive strategies including 3) inter-community trade as well as 4) social networks to provide mutual support . In the context of this study, inter community trade is expressed through the economy of gathering, and the interdependence of social networks in the integration of fallback foods. The act of gathering plants and mushrooms for personal use in Ukraine is embedded in seasonal and holiday rhythms, with harvesting carried out mainly from spring until autumn. With the rise of the COVID-19 pandemic, there has been an uptick of families picking and selling mushrooms . In the forests of Ukraine, 25 tons of birch juice are harvested annually, 150 tons of commercial honey, more than 7,000 tons of dried mushrooms, 7 thousand tons of wild fruits and berries, as well as 5 thousand tons of medicinal plants . Hutsulshchyna is considered one of the most economically depressed regions of Ukraine and the gathering and selling of medicinal roots and berries is common.

Out of the 40 people interviewed, 18 mentioned the gathering of mushrooms and stated the importance of mushrooms in culture, economics, and diet. This dataset is small since it was incidental knowledge gathered through interviews and participant observation on plant knowledge; it does not fully capture the extensive deep and rich mycological knowledge rooted in this region. Most people go out with their families and gather mushrooms in the summer and fall. It is a recreational and seasonal activity that bonds generations. For example, one elder mentioned, “I take my grandson and we go together to pick mushrooms. I show him the place where mushrooms grow.” [Mykola ] Participant observation over the course of a year as well as an additional summer field season reveals the importance of mushrooms. Considering cultural importance , frequency of citation , relative frequency of citation , relative importance , and use reports among mushrooms noted, fly agaric ranks first and penny bun ranks second. Chanterelle ranks third in terms of cultural importance and relative importance , and ranks fourth in terms of relative frequency of citation . The ranking of the frequency of citation and relative frequency of citation is as follows: fly agaric , followed by penny bun and common stink horn . A total of 68 UR were provided by participants . In Appendix A, Table 5A shows all mushrooms, uses and their corresponding fidelity levels. Amanita mascara is abundant in the region,cannabis equipment growing in association with a diversity of tree species including pine, fir, birch, cedar, oak, and spruce .

Fly agaric, noted for its toxicity, is typically used in medicinal cancer treatment. Use of this fungus is not ubiquitous but rather specialized among experts due to its toxicity. Two stories were told in interviews whereby a man was sick and decided to poison himself by cooking and ingesting the fly agaric. Instead, the man ate it and went to sleep. He woke up feeling better, and eventually recovered. Its toxicity is noted as well as tincture preparation discussed extensively. One participant stated that fly agaric is even considered delicious but needs to be specifically prepared to be edible. While it was discussed the most, it is sparingly gathered and if gathered, rarely. Its bold presence in the analysis has more to do with its symbolic prevalence and ecologically frequent presence in the region than its use in everyday life. For this reason, it also holds symbolic importance. Penny bun, plentiful in the region, grows in symbiosis with pine and spruce tree species. It is gathered following local ecological cues and is symbolically important in Hutsul culture. Penny bun, typically eaten, is noted to be of great importance, culturally, economically, and nutritionally. Although there are other mushrooms that are edible in the Carpathian Mountains, this mushroom is preferred; its use is frequent in traditional foods . Extremely important in day-to-day life, most people gather this mushroom as a source of nutrition as well as source of secondary or tertiary income. One participant noted its medicinal use as a tincture, used topically to treat pain. Chanterelle, commonly found in coniferous forests, is both a source of food and medicine. As an economically important mushroom, these mushrooms are typically sold at a higher price than other mushrooms.

Common stink horn , which has distinctive physical characteristics, is also used for cancer treatment. While it is considered rare in local forests, it is still present. Lastly, Red pine mushroom was not explicitly mentioned in interviews is gathered seasonally . Culturally important species derive their importance and presence in culture from their various uses as stated by Hutsul community members. Why do Hutsul community members gather these species? What uses are continually cited as being relevant, useful, and salient? Three commonly cited uses emerged in my analysis – medicinal , food and ecological uses . By exploring the nuances of medicinal and food uses as stated by Hutsul community members, the reliance on landscape as an ethnoecosystem serving as a safety net emerges . Looking closer at the medicinal uses in the region, 92 taxa were used for medicinal purposes, including the unique documentation of two lichen species and three fungi species . Among the taxa noted, 17 species were explicitly noted to be given to children treating ailments including fevers , warts , digestion issues , coughs , colds and wound treatment . Several plants also provide a source of vitamin C , while others contain sedative properties . Out of the 62 medicinal use categories, the most cited medicinal categories include: 1) treating various stomach ailments , 2) reducing fever , 3) providing a source of vitamin C , 4) regulating blood pressure , and 5) treating topical wounds . Two of the most cited medicinal categories address preventative care concerns – providing a source of vitamin C and regulating blood pressure while the other three address treatment of an ailment . To date, research in the southeastern Hutsul region highlights how the policies of sociopolitical change and geography influence changes, trends and differences seen in Hutsul ethnobotanical plant uses . While governance structures play a role, Hutsul culture and knowledge transmission could also cross these borders. As seen in Table 2.5a, there are 31 plant taxa and corresponding medicinal uses shared by Hutsul communities on both sides of the Ukrainian-Romanian border as well as in Hutsul communities in the historical cultural center . Thirteen of these noted species are also in the top 20 species of noted cultural importance, showing high fidelity levels in medicinal plant use across borders, and therefore cultural significance in Hutsulshchyna due to their prevalence, breadth, depth, and continuity of use.

When considering previous studies alongside this study, St. John’s wort , bilberry , raspberry , mint and arnica all share high cultural importance in the Hutsul landscape on both sides of the border, occupying diverse habitats. As noted in a recent study, Hutsul interviewees in Bukovina reflected a sense of pride in their forests, underlining the strong curative power of medicinal plants derived from these forests . While these species are culturally important, by extension the various habitats in which they are nested are also greater or at least of equal importance . Each of these species is found in a range of habitats. Raspberry, St. John’s wort and bilberry are found in five habitats, while arnica is found in four habitats and mint in three habitats. These plants exhibit generalist life strategies and inhabit a broad range of environments with a varying range of human interaction. Of the 20 top culturally important species and their habitat ranges, the most cited habitats that species grew were polonynas, followed by woodlands, forests, meadows, tolokas, roadsides, pastures, alpine meadows, gardens, and fields . Species that were specialists, such as high elevation species occupied a narrower ecological range yet exhibited high cultural importance, specifically for their curative medicinal qualities. Interestingly, several species that inhabit almost all ten habitats did not share high cultural importance according to the indices. An explanation for this could be that these plants are available and accessible and therefore not specifically sought out due to their accessibility, availability, and ubiquity. Two habitats unique and important in Hutsul landscapes are tolokas and polonynas. Tolokas are generationally held pastures typically located on a nearby hillside, and passed down from one generation to the next, ensuring both connection and access to land and species. Polonynas are communal summer alpine meadows,vertical grow shelf which provide grazing for communal livestock. All livelihoods of Carpathian highland people are somehow tethered culturally or economically to the maintenance of polonynas . Tolokas and polonynas have coevolved with agricultural practices and rely on human interaction to maintain community function, structure, and composition . The most culturally important species inhabit a diversity of habitats and are commonly encountered . This is due to their visibility in the landscape and their accessibility to the community. It is the habitats nested within larger ecosystems that harbor a multitude of complex relationships between community members and landscape, providing medicine, fodder, firewood, clean water, and sustenance. Plants, mushrooms, and lichen serve as the multi-directional tether between humans and land; uses are one means of defining and understanding these relationships. TEK is the reservoir of place-based knowledge that illuminates critical ecological relationships seen through language, storytelling, art, rituals, and sensory experiences guiding gathering practices.While indices tangentially address cultural importance on the scale of frequency of use and citation, importance, fidelity levels, other factors, such as accessibility and availability are missing. By exploring the place-based knowledge that TEK encompasses, issues of accessibility versus availability to a habitat arise.

The terms “available” and “accessible” tend to be used interchangeably; a species that is accessible is most likely available. However, a plant that is abundantly available, may not be accessible due to various socio-political or environmental factors. Accessibility implies ease of retrieval, an ability to interact with a species, through gathering, within a landscape. Availability is the first step to accessibility in terms of gathering a specific species. For example, species that are endangered are less available, less persistent in the landscape, and therefore less accessible as well. On the other hand, some plants may be preferred over others due to medicinal and/or cultural factors, yet constrained by their level of accessibility. For example, in the Hutsul context, a forest raspberry may be preferred due to its medicinal property, but a garden raspberry is more accessible and therefore more commonly used as food. While the forest raspberry has greater medicinal importance, its reduced immediate accessibility plays a considerable role in plant use and relationality in use. The importance of accessibility arises when delving deeper into land stewardship policy and implications for maintaining livelihood for forest-dependent communities such as Hutsuls. Scholars Ribot and Peluso define access as the “ability to derive benefit from things” . They state that the notion of “being able” incorporates pivotal social relationships, highlighting power dynamics, that underpin accessibility. Further, Ribot and Peluso exemplify the notion of access as networks of power that allow actors to obtain, direct and keep access. In the Hutsulshchyna, practical accessibility to forests and meadows can be hindered and redefined by local government officials, logging companies, borders, state parks and outdated laws. A plant may be available in relative abundance in a habitat, but not accessible. Access to a plant and rarity are often conjoined by shared geography , but not always. Rarity of a plant can arise due to negligent harvesting practices seen in commercial harvesting, illegal logging, climate change, historical colonial management practices thereby making the plant less available to the local populations that depend on them . If the relationship to the plant is weakened due to its rarity, it can impact the culture surrounding its use such as Edelweiss . For example, interwar efforts in the region to fertilize pastures and meadows with manure caused the succession of tall grasses, eventually leading to the endangerment of Edelweiss, a once culturally important yet very endangered plant. Historically, there were many stories, songs and folklore surrounding this plant. Today, its presence on alpine pastures is rare and its cultural significance is also waning . In interviews, it was only mentioned once as an endangered species. Therefore, incorporating a more explicit accessibility factor into a cultural importance index could provide important community-driven insights regarding local forestry policy. This factor would acknowledge the difference between availability which denotes the relationship between species and environment, and accessibility which emphasizes governance factors surrounding its use. The definition of accessibility includes the ability to benefit from species, habitat, people, and institutions while property underlines socially acknowledged claims or rights, by law, tradition or custom . Since 1991, Ukraine has experienced more democratic governance. However, under Soviet rule, private property was surrendered to the Soviet government, causing access to places to become an even more important function and sign of resistance. Although Marxist philosophy states that labor with land or resource use takes the place of state institutions of property, Communist policies in Hutsulshchyna saw even ownership of cattle as thievery of state property, essentially eroding traditional governance in the region. Policies included culturally destructive practices such as resettlement actions, Sovietization, and depopulation measures.

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.