Cannabis Grow

Approximately 23 years later, the same type of system of taxation and self-incrimination would be implemented for marijuana.As Doris Marie Provine illustrates in her book UnEqual Under the Law , Drug laws in the U.S. have always been predicated on racist assumptions of criminality and social control. The first drug law implemented in 1872 in San Francisco’s China Town banned opium smoking. Opium smoking was a common practice amongst the Chinese laborers that worked on the railroad. Various notions about Chinese men luring white women in to opium dens and selling them into sexual slavery pervaded at the time. The Opium law was seen as a way to control the population. White opium users were frequently shielded from the law as they frequently used opium from a vile. In a similar vein, cocaine was outlawed during the Harrison tax act not because of its dangerous properties, but because racist ideas abounded that the use cocaine put black men into frenzies that caused them to rape white women. It was believed that cocaine gave black men super human strength that allowed them to withstand bullets . Much the same way that Chinese and African-American men were demonized in popular culture, Mexicans faced a similar racial drug fear mongering campaign . Following the Mexican revolution of 1910, Mexicans flooded into the United States introducing the recreational use of cannabis. This was the first large scale use of cannabis as a recreational drug in the U.S. although it had been around since colonial times and had been in use in medical practice since the mid-1800s. However, plant growing rack in the 1930s, as the depression era took hold and many white Americans could not find jobs, Mexicans became the target of discrimination .

The hatred of Mexicans was so severe, that in 1931 Mexican repatriation began. Much like the opium laws and ordinances that targeted the Chinese in San Francisco, and the black codes that pursued blacks in the south, anti-marijuana laws were designated primarily for controlling the unwanted immigrant Mexican population . By 1931, based on dubious scientific studies showing links between marijuana use and violence, over 29 states outlawed marijuana. Many newspapers at the time, combined with the film Refer Madness in 1936 promoted this type of propaganda as legitimate. The specific reason given for the outlawing of the hemp plant was its supposed violent, effect on the degenerate races. In 1937, Congress implemented the Marijuana Tax Act, which levied a tax on anyone who dealt commercially in cannabis, hemp, or marijuana. Like the 1914 Harrison Narcotics act, the act itself did not criminalize cannabis use, it simply penalized cannabis handlers who did not get the proper marijuana stamp and pay the proper tax for handling marijuana. The act restricted cannabis use by never issuing marijuana stamps to anybody that may wish to sell, purchase or use the plant. Moreover, in order to get a stamp one would have to have marijuana in hand to get the license, effectively creating a system of self-incrimination .The fact that the marijuana tax act led to a system of self-incrimination, the law was abolished after the court case of Leary v. United States in which the Supreme Court held the tax act unconstitutional since it violated the Fifth Amendment . However, drug laws were by this time so entrenched in the American consciousness, drug crusaders had no problem enacting a law that outright illegalized the plant. This led to the 1970s Controlled Substances Act. This act regulated the manufacture, importation, possession, use and distribution of certain substances . The legislation created five schedules for a substance to be included.

A discussion of the classification criteria and the drugs listed in all five schedules would be far too extensive and not germane to this dissertation. Therefore, I will only discuss marijuana’s classification as a schedule I drug. Schedule I substances are defined by the Controlled Substances Act as a drug or substances that has a high potential for abuse, has no currently accepted medical use, and there is a lack of accepted safety for the use of the drug or other substance under medical supervision . What is noteworthy about this classification is that pure THC is listed as a schedule III narcotic5 under the trademark Marinol . Likewise, far more dangerous drugs such as cocaine, methamphetamine and oxycodone are classified as schedule II drugs, implying that they are less dangerous and less like to cause dependence and abuse . In 1996, California voters passed historic legislation, Proposition 215, concerning the use of cannabis for medical purpose. The proposition was a statewide voter initiative to allow patients with a valid doctor’s recommendation to possess and cultivate cannabis for personal medical use. This was the first stepping-stone in the legalization of marijuana. It also created a conflict between state and federal law, with prosecution and imprisonment still enforceable at the federal level. In response to Proposition 215, the federal government threatened to revoke the license of any physician who recommended the use of cannabis to any patient . Such threats did not last long as the Ninth Circuit Court of Appeals held that, “the harm to patients from being denied the right to receive candid medical advice” and the “the harm to doctors from being unable to deliver such advice” were both insupportable. Proposition 215 was later expanded in 2004 with the introduction of SB 420. Senate Bill 420 was to create a uniform system of guidelines for medical marijuana regulation .

The provisions allows for an individual to possess a minimum of 6 mature or 12 immature plants and a half pound of processed cannabis. The bill established the voluntary medical marijuana identification card program and guidelines on aggregate possession and the operation of cooperatives and collectives . Theoretically, collectives/cooperatives are collectively owned non-profit establishments designed to grow and distribute cannabis on behalf of its members that have neither the time, resources or knowledge to grow on their own behalf. By operating collectively, growers and distributors, known as growing operations and dispensaries/delivery services pull together the aggregate passion of its members to grow on their behalf. Aggregate possession allows for a cooperative to grow and distribute medical cannabis on behalf of its members. This allows cooperatives the ability to grow much more cannabis than would typically be legal for an individual grower or growers. Many medical marijuana patients have not the time, knowledge or ability to grow medical marijuana plants. Moreover, the sale, purchase and trafficking of cannabis is still illegal under California state and federal law for both medical marijuana patients and non-medical marijuana patients alike. Joining a cooperative or collective allows medical marijuana patients that otherwise would have to grow cannabis on their own or buy it from a street dealer the ability to obtain cannabis in a relatively safe and secure way. However, indoor vertical garden system cooperatives are expressly non-profits that operate for the benefit of their members. Cannabis is grown for the benefits of the members and donations are made to keep the cooperative operational.The passage of California’s Compassionate Use Act and the enactment of Senate Bill 420 opened the floodgates for the shifting of public opinions about cannabis and cannabis legalization in the United States. As of this writing April 2016, there are currently twenty-three states in the U.S. that have some form of legalized marijuana production and distribution system either already in place or in the works. On top of that, four states , and the District of Columbia , have outright legalized recreational cannabis for adult use , and another twenty states are working to put pot legalization measures on their November 2016 election ballots . Although times are changing and a trend towards legalization appears inevitable, a new form of racial and class hierarchy is emerging in the recreational marijuana system. As stated earlier in the chapter, drug prohibition and the war on drugs has always relied on a system of racialized assumptions. Today, in response to mounting state debt, and a per capita prison population that far surpasses that of nation states typically considered to be repressive, states are enacting laws to help reduce the economic cost of mass incarceration and the war on drugs. Unfortunately, as history has proven time and time again, the more things change the more they stay the same. Much of the pro-legalization and anti-mass incarceration rhetoric centers around the issue of the taxation burden on the white middle class. In fact, one of the most cited statistics, and perhaps one of the most significant reasons for the wild fire spread of pro-cannabis legislation has been the boon to state coffers following the Colorado and Washington’s marijuana legalization. The state of Colorado alone collected nearly 135 million dollars in marijuana taxes in its first year following the institution of legal recreational marijuana. In the state of Colorado in 2015, licensed marijuana stores sold approximately 1 billion dollars worth of medical and recreational cannabis. Additionally, the state collected 135 million in taxes in year over year totals for taxes and license fees in 2015 .

What is going on today is nothing short of what many have described as a modern day gold rush, or, a “Green Rush” to be exact. In Oregon’s first month of legal recreational marijuana sales, the retailers sold an estimated 13.9 million dollars worth of pot generating 3.48 million dollars in taxes . Unfortunately, everybody does not share in the spoils of cannabis legalization equally. Similar to the way certain cities institute ordinances to effectively bar medical marijuana dispensaries in cities, many of the states that have enacted rules for the application process that effectively bars poor and middle class Americans from participating in the industry.In addition to maintaining class hierarchy, the racial inequity remains intact as a criminal record bars individuals from working in the marijuana industry . By barring former criminals, and in particular, criminals charged with prior drug offenses, the laws practically guarantee a middle-class white work force. Although research unequivocally shows that whites and blacks use drugs at approximately the same rates, blacks have been disproportionately arrested and convicted of drug offenses. And as a consequence of this racial targeting, a defacto system of racial segregation is emerging in this newly found industry. As Amanda Chicago Lewis so eloquently puts it, “After having borne the brunt of the “war on drugs,” black Americans are now largely missing out on the economic opportunities created by legalization.” Moreover, as the application process has become prohibitively expensive, minorities are excluded from entrepreneurial ventures as the lack of wealth of keeps many from attempting to enter the industry. It is estimated that it takes a quarter of a million dollars to start a recreational marijuana business . Thus, the legal marijuana system, at the dispensary ownership level and the production process is still very much dominated by white upper class males. Notwithstanding, regardless of the barriers enacted by the state, city or any other type of governmental entity, it is important to understand that cannabis as a plant can not be controlled, unlike other forms of drugs such as cocaine and methamphetamine, a chemically rigorous production process is not necessary. Any individual with a pot and a plant can grow cannabis and thus the system can never be completely controlled. According to a report released by the Center on Juvenile and Criminal Justice pot legalization hasn’t done anything to shrink the racial gap in drug arrest rates. Although the study pointed to the fact that arrest rates plummeted in states in Washington and Colorado, the racial disparity between black and white arrest remains unchanged . However, it should be noted that while disparity in arrest rates remain consistent, arrest overall in states with legal recreational marijuana has seen dramatic decreases . In the state of Washington alone from 2008 to 2014, arrest rates dropped by 90 percent. Thus, one of the major consequences of our half semi-legalized marijuana system in the U.S. is much the same that it has been for generations, as poor and minorities are locked up for selling and using marijuana, white male capitalists get rich off from the exact same act. Thus, the cannabis industry in the U.S. today is at an interesting crossroad between legalization, taxation and regulation on end and prohibition and the war on drugs and more of the same on the other. However, it is important to understand that the inequities of the war on drugs cannot be redressed with a simple process of legalization without redressing and remediating the inequities the war on drugs produced.

Sociologist Kathy Charmaz describes how to perform grounded theory by, “You begin with an area to study. Then, you build your theoretical analysis on what you discover is relevant in the actual worlds that you study within this area.” . A grounded theory approach gives extra credence to the interactionist nature of the study because my opinions and interpretations of the practice of marijuana use and selling is not clouded by preconceived notions of what I expect to find. Research Setting The study will take place in Costa Mesa, California, following a community of heavy marijuana users and sellers who participate in the partially illicit marijuana trade. All participants names in this study will be changed to conceal their identity. Costa Mesa is a city in Orange County with a population of about 100,000 inhabitants. It is nestled between the extremely upper class, predominantly white area of Newport Beach and Irvine , and the poorer, older, larger and predominantly Latino cities of Santa Ana and Anaheim3 . Costa Mesa is a type of buffer zone between the haves and have-nots in Orange County and it is from this offset situation that the group gets its unique racial and class character . Furthermore, this balanced and relatively stable environment allows the group to avoid the more dangerous nuances of the illicit substance trade while serving as a mechanism where they still have a constant supply of customers from both the richer and poorer elements of the county. The main meeting place for the group is The Corner . The other common “kick it” spot for the group is Natty’s mother’s house. The house is near a popular pool hall in the city of Costa Mesa. It is an older wood house with a front porch type stoop that serves as a gathering and kick it point for the CottonMouth Kings.

Although just off the largest street in Costa Mesa , weed growing systems marijuana is smoked openly on the porch, and Natty Dreads Mother is surprisingly permissive of the behavior. Many nights begin at the House and end at the pool hall and many transactions occur at both locations. The group I decided to research was a cannabis selling and smoking group based in Mid-Orange County. I decided to use the group understudy for two main reasons. One, through a social-network snowball sampling I was able to get in contact with the members of the group. And two, the members of the group each had years of experience smoking, growing and selling cannabis in both the illegal market and the semi-legal medical marijuana market. This gave me the added benefit of comparing cannabis markets before and after the medical marijuana system. Furthermore, having access to a unique set of individuals who participate in a semi-legal, and partially illegal economic venture provided rich data for an under explored market dynamic. This, combined with the groups unique beliefs about cannabis and its beliefs about their own cannabis selling behavior and what it meant made for a fascinatingly rich and distinctive ethnography. Moreover, I chose this group of individuals because of unique characteristics of the group understudy. For one, the group members are not young teenagers. In fact, they are in their late twenties and early thirties and many are parents. Most criminological research examining drug users and sellers focuses on teenage offenders. Two, the members are not dispossessed minorities selling drugs in a dangerous urban area for survival. The study takes place in a relatively middle class area of Orange County with other legitimate economic ventures to pursue. And three, the members are not the typical rich drug dealers documented in films likeScarface. The relative normality of the group with their unique perspective on cannabis and cannabis selling led me to study this group. I provided confidentiality to the participants of the study. Since I as the researcher can identify the members of the study the project is not anonymous. However, all steps possible were taken to insure the confidentiality of the study’s participants.

The names and ages of all participants have been changed. I paid close attention to make sure there was no way to be able to discern the actual identity of the study’s participants. Moreover, the city, and certain locations discussed in the preceding chapters are meant to be purposefully misleading in case anybody who is familiar with the area or with the people I study were to try to determine the actual identity of the participants of the dispensary in the study. Psuedonyms are particularly relevant for qualitative researchers to assure that deductive disclosure does not occur. Deductive disclosure occurs when individual traits of individuals or groups makes them identifiable in research reports . Qualitiative research, and ethnographic research in particular tends to be rich, descriptive and vivid. For this reason, researchers need to pay particular attention to not tipping off potential readers to the actual identities of the participants. Breaches in confidentiality also have the potential to damage the public’s trust in researchers . One famous case of deductive disclosure was Carolyn Ellis’s Fisher Folk . The research participants were able to identify themselves and their neighbors and people from neighboring communities were able to identify them. Ellis later went on to write that the research participants felt ashamed and betrayed by her book . Because of these problems, simple name changes were not enough to protect the anonymity of my informants since deductive disclosure is a possibility. Thus, other aspects such as age and location were changed as well. I employed a confidentiality approach that Kaiser termed the Dominant approach. Although Kaiser is not a proponent of the approach is was ideal for my particular study. I chose to name the group the CM Kings for a couple of reasons. First, they do not consider themselves a gang and thus have no formal name for themselves. Rather, the Kings are a compilation of a group of friends that sold and grew in various capacities and eventually pulled their resources together to set up a marijuana dispensary. However, the name serves another purpose. I use the name as a play on Sudir Venkatesh’s Black Kings. In Gang Leader for A Day Venkatesh chronicles the structure and practices of urban drug dealers on the streets of Southside Chicago.

In this study I counter Venkatesh notion that drug markets are inherently dangerous and violent by showing the structure of suburban cannabis markets and the semi-legal medical marijuana markets and its success in stifling crime and violence in the market.Although not traditionally defined as vulnerable populations such as children, the mentally disabled or individuals with low social status, research on criminal populations present unique challenges for the researcher. Because of the unique circumstances of doing criminological research, the American Society of Criminologist code of ethics states, in relation to research populations that they: a. comply with appropriate federal and institutional requirements pertaining to the proper review and approval for research that involves human research subjects, materials, indoor farming systems and procedures; b. do not mislead respondents as to purposes for which that research is being conducted; c. ensure subjects’ rights of personal anonymity unless they are waived; d. ensure confidentiality of any data not obtained from records open to public scrutiny; e. anticipate potential threats to confidentiality, including the Freedom of Information Act, and adopt various means of coding, storing, and maintaining data to protect the confidentiality of research subjects; f. fully inform potential subjects in cases in which they are unable to guarantee confidentiality; g. make every effort to ensure the safety and security of respondents and project staff; h. obtain informed consent when the risks of research are greater than the risks of everyday life; and i. take special efforts when individuals studied are illiterate, are mentally ill, are minors, have low social status, are not comfortable or familiar with the language being used in the research, are under judicial or penal supervision, or are unfamiliar with social research and its constraints and purposes. . I made sure to follow all the research ethics and more. Social research, by its very nature represents an invasion of people’s daily lives. Moreover, criminological research ask respondents to reveal deviant behavior that may have lasting ramifications such as potential arrest and imprisonement, beyond the study. Revealing information may harm the participants so extra care was taken to shield the participants from potential harm.I attained informed consent from all the study’s participants. Consent forms provide valid and legitimate documentation that the subjects knowingly participated in the project. Notwithstanding, as Dixon noted several years ago research of criminal populations, “is coming under increasing threat from institutional ethics committees which have raised legal and ethical objections to proposed projects” . In particular, Dixon notes the inability of researchers to protect the confidentiality of research subjects, particularly when illegal activities are concerned. Unfortunately, as pointed out by Roberts , signed consent forms provide an identifying link between the participant and the data.

However, they were collected at the request of the University of California, Riverside Human Research Review Board. Yet, as stated earlier, the acitivities of the participants are legal in the state of California where the research was conducted. Natty Dreads is the key informant of the group and the access I have to the group. Thus, to some degree, the study is filtered through the lens of his and my eyes. I met Natty Dreads approximately 15 years ago in high school. At that time, he did not smoke. His transition into marijuana culture was relatively abrupt. Living down the street from me made it convenient to hang with Natty on a relatively frequent basis. In-depth face-to-face interviewing will be conducted with the study’s participants, using an interview question list that will consist of three parts: history of substance and marijuana use, what marijuana culture and marijuana smoking and selling means to them and questions about why the respondent continues to participate in these acts. The interviews lasted approximately two hours each, with follow up interviews conducted as new developments that I witnessed occured, or, if the respondents decided they wanted to share more information about their views on marijuana use. The interviews were semistructured for the purpose of getting the conversation flowing and to learn various demographic and social history factors, but the main purpose of the interviews was to let the group members discuss what marijuana use and dealing means to them and why they participate. Other than a few preset questions, I did not script or prime the interviewees towards certain answers. I allowed the respondents to express what marijuana culture means to them. The interview questionnaire is listed in the appendix. The field notes were recorded in the language my informants spoke and decoded in the dissertation so that is understandable to academics. My informants spoke a form of English heavily coded in marijuana slang. The group frequently discusses marijuana openly but the coded language allows them to stay undetected by non-users. Using phrases like “gaining knowledge” to represent smoking marijuana is one such technique. After recording conversations and viewing the surrounding environment, I will take the condensed account and expand it to discuss relevant information that I did not have time to write down while in the field. Ethnographer James Spradley considers this to be an integral part of ethnographic methods because it allows the ethnographer to fill in detail and record things that were not possible in the field. A key aspect of “grounded theory” ethnographies is an analysis that is inductive, interactive and recursive. Inductive research identifies data and amasses them into larger taxonomies and categories. These categories are explored in interviews as well as in participation and observation to test their internal validity. New observations are compared and contrasted until stable patterns emerge that begins to explain cultural practices. Recursivity refers to the cyclical nature of this process as it moves from inductive analysis, in which the theory is created based on what is observed, and deductive processes through which the datum is compared to the theory. This iterative model is the process I intend to use while in the field to understand the practice of marijuana use. This works by continually raising questions in the field and modifying and clarifying ideas about what is discovered.

This disconnect between the farmers’ perceptions of the industry compared with its rapid expansion could mean that the specific type of producers we interviewed were not benefitting from the industry increase that accompanied legalization. Other research on small scale cannabis producers from northern California supports this interpretation . It is also possible that landscape-scale industry change does not translate to the scale of an individual farm. If this is the case, it might help explain why the model of change in plant count had the fewest significant predictors—rather than being a more simplified process, it might instead be that the drivers for farms that existed before legalization are highly individualized or localized.Despite the uncertainty surrounding the trajectory of legacy cannabis farms, the models for new cannabis development provide insights into predicting the growth of the industry. While we did not project our predictions into the future, due in part to large policy changes that were not explicitly addressed in our interviews or models , our results do provide a baseline and contextualized understanding that could be used for future predictions. For example, based on farmer descriptions for why they may seek out large and rural parcels, it is unlikely that the strength of those drivers would decrease over time. On the other hand, farmers’ stated preference for farm-zoned parcels, which by contrast ended up as a significant driver in the opposite direction for new farm development, rolling hydro tables might be more likely to change over time as a potential driver due to shifts in regulation, enforcement, or social pressures for those renting/selling farm zoned parcels.

While our results are broadly useful for understanding cannabis landscapes in southern Oregon, there are many levels of complexity that are not captured by the models. For example, we treat cannabis agriculture as a single entity for these models, while in reality it contains a diversity of production styles and regulatory statuses. It is entirely likely that a large-scale licensed hemp farmer and a small-scale unlicensed cannabis farmer will reveal different drivers of their land use. Similarly, whether a farmer owns their own land or rents it, or whether a farmer lives on site or off, could also change the relationship with potential drivers. While we did not have detailed information on each cannabis producer at the county level to classify or group production styles, this would be an important avenue for future research. Future research would also benefit from added time points, particularly after the 2018 federal hemp legalization. In addition, this study was largely confined to a small number of small-scale farmers, and thus an expanded interview or focus group data collection process might reveal new drivers that would be relevant for other production styles. The relatively low pseudo r-squared values for our models suggests that there may be additional drivers functioning in this system, which extended interviews could help uncover. Our study focused on private land production, but it is important to remember that public land production also occurs in this area and influences not only the local environment, but the public perceptions of cannabis in the region. Incorporating the links between public and private industries might strengthen our understanding of these systems. Similarly, linking different scales of drivers would be a valuable next step. The interview data indicates that the southern Oregon industry is tied to regional and national markets , and that much of the economic decisions are either very fine scale at the level of the farm, or broader scale at the level of the state. Within the scale of Josephine County, the significant effect of mapped year implies that there may also be different dynamics in the two halves of the county that were mapped at different time points .

Although it did not directly emerge in the interviews, while living in Josephine County, PPS observed different local approaches to integrating cannabis farmers into the community in Williams as opposed to the Illinois Valley. This is an example of a secondary way in which the observations that occur during the interview process can assist with model interpretation. Further research on differences in local policies, community standards, or other regional differences might elucidate this pattern. Capturing interrelated dynamics such as local to county-wide processes would require a complex modeling approach but might lend insights into multi-scalar drivers. Understanding wildlife response to disturbance across landscape gradients is a complex endeavor. Individual animals can respond to anthropogenic disturbance with a variety of different behavioral changes , but these responses are all context dependent . For example, in some studies, coyotes demonstrate a space use preference for agricultural areas , while in others, they avoid farmland ; similarly, at times they are labeled as urban exploiters , and at times avoiders . These differences are often tied to context-dependent responses and differences in landscape configurations . At a wildlife community level, the complexity of responses increases even more. Disturbance may affect some species more than others, or in opposite directions, leading to broader contractions or expansions in species assemblages and interactions . Changes in species interactions, especially if they involve keystone species, can have cascading effects on ecosystem function . The context-dependence of these shifts means that consistently predicting how wildlife communities will respond to rapid land use change at a local level is very difficult and requires understanding multiple interacting mechanisms . Nevertheless, wildlife community responses to disturbance matter because the context-dependent consequences in turn can affect ecosystem health , effectiveness of wildlife management strategies , and human-wildlife conflict . Thus, there is a continuing need to examine the effects of disturbance on wildlife in order to develop strategies to mitigate the negative effects of land use change. Understanding wildlife response to disturbance is particularly important in areas where land use change is occurring rapidly.

Spaces of rapid development for agriculture are called frontiers, and are often spurred by the growth of a new industry, while accompanied by the movement or growth of human populations, and transportation structure improvements . Frontiers are naturally spaces of rapid land use change, and often sites where different approaches to land use planning and conservation clash . While frontiers present a novel disturbance scenario, most studies of wildlife response to agricultural land use have been concentrated in Asia, South America, and Europe , and often in areas that have long been dominated by agriculture. Such studies may miss some of the immediate responses of wildlife to development that occur over shorter spatial and temporal scales . Recreational cannabis agriculture represents an ideal opportunity to study wildlife community response to disturbance generated by a currently expanding land use frontier. In the US, state level legalization of recreational cannabis has initiated a rapid land use frontier for outdoor cannabis production . This frontier is particularly noticeable in rural areas of the western US. Influenced by its illicit history, outdoor cannabis is often grown in remote, bio-diverse regions with minimal other non-timber agriculture . Regardless of individual legal status, private land cannabis farms are typically smaller than those of other commercial crops, and are clustered in space, creating a unique land use pattern of small points of development surrounded by less developed land . This pattern of development locates the cannabis frontier directly at the wilderness boundary—a somewhat rare characteristic for agriculture in the United States . At a broad scale, cannabis development in rural areas overlaps with regions that may be important habitat for wildlife , yet it is unclear whether, where, vertical horticulture and to what extent this broad scale spatial overlap actually results in negative impacts on animals at a local scale. There have been studies suggesting that cannabis production may lead to habitat destruction or modification , and wildlife death due to toxicant use and poaching . However, most studies on direct impacts of cannabis farming have largely been conducted on illegal public land production sites , as opposed to private land sites. The research conducted to date on private land has not encompassed a full landscape gradient around cannabis farms. Not only have private land sites likely seen the largest production increases due to legalization in recent years , they are also often characterized by very different production practices than public sites. For example, on many private land farms, indirect sources of disturbance to wildlife such as noise and light are more common than direct causes of mortality. Private land sites may use high-powered grow lights, drying fans, and visual barrier fencing, which could create potential wildlife disturbance . Such practices are less common on public land. It is possible that as cannabis production expands, particularly in the licensed industry, these forms of indirect impact may be more typical of cannabis production overall. Indeed, indirect effects of production practices on wildlife space use and behavior is a common concern for other agricultural crops , and may also interact with direct effects on mortality .

Therefore, it is critically important to study both indirect and direct effects of cannabis on wildlife communities, particularly on private lands where research is lacking. Because outdoor cannabis farming is a land use frontier and therefore often characterized by different land use practices and patterns from traditional established farming in the US, it is uncertain whether other agricultural systems provide the best models to predict wildlife responses to cannabis development. Wildlife may use, avoid, or display differential responses to cannabis development, depending on whether production more resembles small scale countryside farming , industrial agriculture , or exurban/suburban development . In the case of differential responses, it’s also unclear whether cannabis production would have widespread enough effects to trigger mesopredator release , or generate novel food sources that could be exploited by behaviorally adaptable species like omnivores and small mammals . We based our study in Josephine County, in southwestern Oregon , in 2018- 2019, three years after statewide recreational legalization took effect. Josephine County was an ideal location to capture the start of the cannabis frontier expansion post-legalization in a rural, bio-diverse legacy production region. Our study area sits within the Klamath-Siskiyou Ecoregion, which is one of the most bio-diverse temperate forest regions on Earth . The Klamath-Siskiyou Ecoregion straddles the Oregon-California border and contains several areas identified as critical climate change refugia . Within this ecoregion, Josephine County contains several protected areas including state and federal protected lands , as well as several species of concern, including native salmonids, threatened Humboldt martens , fishers , and spotted owls , all of which are hypothesized to be directly or indirectly affected by cannabis agriculture . Unlike other forms of traditional agriculture, outdoor cannabis is often grown directly alongside or nestled within areas of high biodiversity . Southern Oregon, and Josephine County in particular, has a long history of illicit and medical cannabis cultivation, as well as an active presence in the growing legal industry in Oregon . Southern Oregon became known as a prime destination for outdoor cannabis production even before legalization, and Josephine County had the highest number of licensed producers relative to population size in the state by 2019 . Production in the county accelerated after recreational legalization went into effect in 2015 , in a similar pattern to cultivation occurring across the border in northern California, with clusters of small farms surrounded by undeveloped or less developed rural land . Our study area consisted of farms spread across three sub-watersheds in Josephine County . We set cameras at 1,110 m to 2,470 m above sea level. The study area included a mix of vegetation types, including open pasture, serpentine meadows, oak woodland, and mixed conifer forest. Rainfall in this region varied seasonally and by elevation, with an average of 82.7 cm annually . Mean temperatures ranged between 3.9-20.6°C in 2018–2019 .The small-scale, private-land cannabis farms for this study included one licensed recreational production site, one medically licensed production site, and six unlicensed sites. All farms were producing cannabis for sale, though in different markets depending on their access to licensed markets. We also had cameras placed in three hemp fields next to cannabis farms. We selected these eight cannabis farms because they: were representative of the size and style of cultivation predominant in Josephine County in the years immediately following recreational legalization in 2015 , were all established after recreational legalization except for the medical farm, did not replace other plant-based agriculture, granted us permission to set up cameras on site, and were located next to a large section of unfarmed land that could grant researchers access in order to place cameras across a gradient of distance to cannabis farms.

Proponents often argue that smaller-scale styles of farming are more sustainable , sometimes drawing parallels to industries such as craft vineyards . However, these farms are also often located in more rural, bio-diverse watersheds close to protected wilderness and managed timberlands that could be at environmental risk from expanding development . As land managers and policymakers decide where to prioritize cannabis farming, there is a growing need to contextualize the potential effects of the legacy pathway in ecologically sensitive regions. In Josephine County, Oregon, the co-occurrence of cannabis agriculture within the highly bio-diverse Klamath-Siskiyou Ecoregion has created a natural experiment to examine how the post-legalization expansion of small-scale, private land farms might affect freshwater and terrestrial biodiversity. In this study we ask: what was the development pattern of cannabis land use in Josephine County during the first year of recreational legalization, and how might cannabis production overlap with sensitive ecological features? To address these questions, our objectives were to: map and characterize the spatial configuration of cannabis farms in Josephine County, Oregon in an early stage of cannabis legalization, and examine the proximity of cannabis production to undeveloped land cover, freshwater, sensitive fish species , Chinook salmon , and Steelhead, and terrestrial carnivore richness , coastal marten , ring tail , cougar , bobcat , gray fox , and coyote. We anticipated that due to the cultural dominance of historical growing practices, grow trays 4×4 cannabis production in this region would be comprised of relatively small-scale farms representative of the legacy industry pathway , but most farms would be new since legalization.

Based on research from California pre-legalization , we expected that cannabis in our study area would also be clustered at the subwatershed level. Concerning proximity to ecologically sensitive areas, we expected that cannabis agriculture would be located in more undeveloped lands, closer to freshwater streams or rivers, and closer to sensitive fish species compared with the surrounding context of all private land parcels. The proposed mechanisms behind these predictions are summarized in Table 1 and draw on the five hypothesized pathways of effect for cannabis on the surrounding environment listed earlier . Finally, we quantified spatial overlap of cannabis farms with projected terrestrial carnivore distributions. We focused on carnivores because previous studies have described this group as particularly sensitive to cannabis cultivation , and because this group includes species of regional conservation concern, such as the fisher.Our study focused on Josephine County in Southern Oregon . Josephine county was an ideal location to measure cannabis dynamics of legacy areas and to gain broader insights on the ecological outcomes of cannabis legalization. Josephine County had a long history of illicit and medical cannabis cultivation, and an active presence in the growing legal industry in Oregon . In 2014, Oregon became one of the first U.S. states to legalize recreational cannabis. Southern Oregon has become known as a prime destination for outdoor cannabis production , and Josephine County had the highest number of applications for licensed producers relative to population size in the state . Widespread cultivation of cannabis started in the region during the 1960s and is now viewed as one of the county’s main economic drivers . Josephine County is also located in a biodiversity hotspot.

The study area is part of the KlamathSiskiyou Ecoregion, one of the most biodiverse temperate forest regions, and an area of increasing conservation focus . The KlamathSiskiyou Ecoregion straddles the Oregon-California border and contains several regions identified as critical climate change refugia . The study area contains several protected areas including state and federal protected lands , and several federally threatened and endangered species including northern spotted owl and coho salmon , and state sensitive species such as fisher . To characterize the spatial distribution of cannabis farming, we hand-digitized cannabis production sites across Josephine County using high spatial resolution Google Earth images taken after statewide legalization . We based our methods on those previously used to map cannabis production in regions of northern California . We used publicly available satellite imagery for May or July 2016, the first year with a full growing season after recreational legalization went into effect in July 2015. Next, we characterized the farms themselves. Digitizers counted the number of plants visible in outdoor gardens, recorded whether there was a visible fence surrounding each cannabis production site, and recorded whether each site was new . To estimate the number of plants produced in greenhouses, we used 180 instances where we could count the number of plants through the see through top of greenhouses and divided this count by greenhouse area. This yielded an average of one plant per 7.23 m2 of greenhouse area, which we then used to estimate greenhouse plant counts. See supplement online for full mapping procedure.To test the accuracy of image-based data collection, we visited approximately 30 farms between 2017-2019 to verify and refine our mapping protocol after a pilot mapping process. Because systematic ground-verification for all grow sites was not possible, we used a qualitative confidence score to represent digitizers relative certainty about each mapped site . For consistency, we thoroughly checked all mapped polygons and associated scoring using the same person who conducted on-the-ground site verification . We used only high confidence sites for these analyses, but see supplemental materials for a comparison to the full data set . Finally, we used only sites with more than four plants for analyses because we were focused on the cannabis industry rather than plants grown for personal consumption .

To assess the potential ecological effects of cannabis at the landscape scale, we quantified spatial characteristics and proximity of cannabis to landscape features, fish populations, and carnivore distributions . This proximity doesn’t directly infer effect, but rather whether the configuration of cannabis may increase the opportunities for negative environmental outcomes. We focused on spatial metrics that might approximate some of the five main hypothesized effects of cannabis farming on local environments . To approximate the potential loss of wildlife habitat, we assessed cannabis production in developed versus undeveloped lands. We extracted elevation and 2013 land cover at the centroid of each farm, and then grouped land cover classes into developed and undeveloped categories . The National Land Cover Database Cultivated category includes hay, annual crops such as corn, or perennial crops such as orchards and vineyards; given the resolution of the NLCD dataset compared to average farm size, this is unlikely to include cannabis pre-recreational legalization. To approximate the potential degradation of forested habitat, we assessed the forest structure on farms used for cannabis production . To do so, we extracted canopy cover and stand age at the centroid of each farm . To approximate the potential effects on carnivores, we examined the overlap of cannabis with projected carnivore richness and individual carnivore species distributions. We extracted the average carnivore richness, and individual carnivore occupancy value at the centroid of each farm . For carnivore richness and individual carnivore distributions, we used projected model data for southern Oregon, from Barry and Moriarty et al., unpublished data . Within our study area, the richness layer represents the total number of carnivores expected in a given grid cell for the following species: fisher, coastal marten, ring tail, cougar, bobcat, gray fox, and coyote. For individual species, horticulture products we used calculated distribution data from projected occupancy and this represented the average probability that a given area would be occupied by that species. Marten projected occupancy was almost entirely absent in this region and was not included in individual species summaries. Finally, to approximate the potential effects of freshwater extraction or declines in freshwater quality due to cannabis production, we assessed the proximity of cannabis to freshwater rivers or streams and fish habitat for potentially sensitive species. For vector data with the proximity analysis , we calculated the distance from the centroid of each cannabis farm to the nearest river and fish habitat in R using the ‘simple features’ package . For rivers, we used the National Hydrography Database . We filtered out canals/ditches and underground aqueducts . For fish habitat data, we used Oregon Fish Habitat Distribution data for coho salmon, fall and spring run Chinook salmon, and winter and summer run Steel head . The fish dataset includes any areas used within the past five reproductive cycles for each species. We then calculated summaries of proximity and overlap metrics in R. In order to inform the interpretation of the fish habitat data, we also extracted the stream order of the nearest stream to each cannabis site, and summarized results in R. The conservation effect of these metrics for cannabis likely depends on how they compare to the potential effect of surrounding land uses and available land for development . Therefore, we contextualized the proximity metrics by comparing cannabis farms to all private land parcels in the county. We used all private parcels instead of parcels without visible, high-confidence cannabis because we were mainly interested in how cannabis production fits into the surrounding landscape context of available private lands.

See the supplement for a more local comparison in which we calculated the proximity and overlap metrics for all parcels within a buffer around each cannabis site. For buffer size we used the average home range of fishers from southern Oregon . Outdoor cannabis production across Josephine County in 2016 was generally small-scale but also pervasive, and suggested that recreational legalization greatly expanded the industry locally. We mapped nearly 4,000 individual gardens and greenhouses on 2,220 different farms, all identified as highly likely to be cannabis . Most sites were new since legalization . Most production was in outdoor gardens , but a greater proportion of greenhouses were new . Farms contained an average of 1.76 individual sites, with a maximum of 14. The average size of individual sites and farms was small but highly variable in terms of cultivated area and number of plants . The average parcel size for farms was 0.098 km2 . 99.6% of detected farms were on private land parcels. Out of all private land parcels in the county, 5.7% contained a farm identified as highly likely to be cannabis. The Ripley’s K analysis indicated that cannabis sites were clustered at all observed spatial scales . At the county level, the Getis-Ord Hotspot maps identified two regional hotspots near Williams in the SouthEast, and in the Illinois Valley in the South-West . The sub-watershed analysis indicated that even within these larger regional hotspots, there were pockets of more and less intensive production . Both the county and sub-watershed hotspots seem to follow primary roads or river networks.Overall, cannabis was produced on more undeveloped and forested parcels compared to all available private lands as a whole . The most common land cover for individual outdoor gardens was shrubland , followed by cultivated , and forest . Greenhouse cannabis production occurred in areas already cultivated with other crops , followed by shrubland , and forest . At the farm scale, however, where outdoor and greenhouse production was combined, forest was the most common land cover type . The predominance of cannabis in forest and undeveloped land covers was also supported by the Gradient Nearest Neighbor data on forest structure. Although the GNN dataset uses a broader categorization for forest, it also indicated that cannabis was disproportionately grown in forested areas . Nevertheless, the forest structure of farms was similar to that on all available private parcels .This study is one of the first landscape-scale assessments of small-scale outdoor cannabis farming and its potential broad-scale ecological effects in a rural biodiversity hotspot. Our results suggest two main conclusions. First, private land cannabis farming in Josephine County, Oregon in 2016 was common and spatially clustered, expanded post-recreational legalization , and yet only covered a small portion of the total land area. This supports our expectation that cannabis farming in Josephine County would exhibit characteristics typical of the legacy development pathway, but that these farms would largely be new post legalization. Second, our spatial proximity results highlighted areas of overlap or proximity of cannabis farms and sensitive habitats and species. Compared to the surrounding context of all available private land parcels, cannabis was more frequently located in forested areas and undeveloped land, closer to rivers/streams and coho salmon habitat, and in areas of high value as fisher habitat. These results provided mixed support for our expectation that cannabis production would be in areas that increase its potential ecological impact.

Furthermore, this evaluation may inform limited research of RJP program evaluation with a small, rural school district in a region with a prevalent cannabis cultivation industry. Findings from this project may help to fill the gap in the literature on restorative program evaluation for drug-related incidents in school-based settings. This may inform efforts for developing, implementing, and evaluating public school-based restorative programs with a substance use focus. Data from this project may also provide the grantee with crucial intermediate findings to inform the continuous development and optimization of RAYS program components and implementation strategies.The General Activity Log database was developed utilizing the SeaTable Cloud software service . UCSD researchers conducted training sessions with RAYS program coordinators where data recording protocols were reviewed to ensure accurate and efficient collection of activity data. Links between the GAL and the case management database were established to track participation in RAYS activities at the individual enrollee level. RAYS program coordinators recorded all relevant activity data in the GAL at the time of implementation or ideally within the same month the activity was implemented. Critical activity data for process evaluation included activity name, implementation date, number and type of attendees , engagement levels, vertical racking system and duration of the activity .The case management database was embedded in the same SeaTable 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 posttest 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 , 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.19 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. 19 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, indoor grow facility 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.Table 4 provides a breakdown of all RAYS activities implemented from May 2021 to January 2023. Data in each column presents the total number of exposures for each activity by attendee type – student, staff, administrator, parent, and “other”. The majority of student exposures was through informational presentations as these events reached a broader range of students, not just the youth advocates and students enrolled in RAYS. Exposure counts are reported in place of participant counts as some individuals may have attended multiple sessions or events of the same activity type. Therefore, the counts presented in Table 4 may reflect duplicate exposures to a specific activity.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, 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.

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.