The focus on small-scale outdoor private land cannabis cultivation sets my dissertation apart from other studies which have focused on public land production , indoor cultivation , or large scale cannabis development in emerging regions . Each style of cultivation has its own ecological risks and social, economic, and ecological trade offs . However, private-land outdoor cannabis production in rural legacy regions provides the best opportunity to study land use consequences for wildlife communities within a social-ecological context. I approach legacy cannabis landscapes as an intertwined social-ecological system . The history and context of cannabis, described in part above, influences the development of cannabis as land use drivers . These drivers in turn shape the ways in which the associated cannabis land use change affects local ecosystems. The ecological impacts can feed back into the land use drivers by way of social attitudes towards nature, or changes in regulation and enforcement. All these interactions are influenced by the shift in overarching policy brought by recreational legalization. Each of my chapters addresses different components in this system, going from a broad to fine scale.My first chapter generates baseline descriptive data on cannabis land use and examines its broad scale overlap with wildlife habitat in southern Oregon . I use publicly available satellite imagery to characterize the development patterns of outdoor and greenhouse cannabis land use in Josephine County, Oregon, during the first year of recreational legalization. I then examine the overlap of cannabis production with potentially sensitive ecological features, including predator distributions and salmonid habitat. This broad overview provides a baseline to understand patterns of cannabis development relative to all available private lands. It also identifies areas where overlap may create potential for wildlife impacts . My second chapter adds depth and context to the baseline data provided in the first chapter,hydroponic drain table by examining the drivers of cannabis land use change before and after legalization .

I use interview data with cannabis farmers to generate social and ecological covariates for models of cannabis land use and land use change. I interpret model results using the themes from the interviews and discuss possible conservation implications. The third chapter moves to a finer spatial scale, investigating how the overlap presented in Chapter 1 affects wildlife on and surrounding cannabis farms in southern Oregon . I use wildlife cameras to monitor animal space use and space use intensity as a function of distance to cannabis farms. I also identify general patterns of response by functional groups. Finally, the fourth chapter presents a research design to investigate potential mechanisms for the wildlife responses observed in Chapter 3. I detail the methods for field experiments that measure the effects of light and noise on multi-taxa wildlife responses, mimicking conditions on active cannabis farms in a controlled setting. I present example data from field trials conducted in northern California. Taken together, these chapters present multiple approaches to understanding the ecological outcomes of cannabis legalization. More generally, research on cannabis agriculture can provide insights on the intersections between rapid changes in human land use and wildlife communities, especially at rural-wild land interfaces. By taking a multi-scalar approach to understanding a unique industry at a critical moment in time, I hope this dissertation sheds light on land use change processes to help promote human-wildlife coexistence in an ever-changing world.Land use change is one of the oldest and most pervasive threats to global biodiversity , yet it often occurs over time spans that obscure pattern , or in tandem with multiple development drivers that are difficult to disentangle . An exception to this is when abrupt changes in law or regulation accelerate development, creating what is known as a “policy-induced rapid land use change frontier” . The acceleration of development at these frontiers enables researchers to assess how land-use change affects biodiversity or ecosystem function over short time periods .

One such unique opportunity to study land use change frontiers has emerged recently in the western United States of America with the legalization of cannabis production and use . Over the past decade, 17 states and the District of Columbia in the U.S. have legalized recreational cannabis, or marijuana , and the rate of recreational legalization has increased over that time. This policy change has initiated rapid development of cannabis cultivation, particularly in areas with a history of illicit or medical cannabis farming . Note that because of the complex policy background of cannabis and its quasi-legal status , this expansion occurs across types of cultivation including licensed and unlicensed producers. As with any development frontier, the rapid expansion of recreational cannabis is likely to come with ecological costs. Indeed, cannabis production has sparked considerable conservation concern for its potential effects on water, land, and wildlife . These effects may occur in part through water withdrawals that lower freshwater availability , road construction or use of pesticides that lower freshwater quality , clearing or fencing of undeveloped land that removes or degrades wildlife habitat , toxicants or poaching that directly kill animals and pose particular risk to terrestrial carnivores like the fisher , and human disturbance that alters animal behavioral cues . These five impact pathways likely vary depending on surrounding context, production practices, and license status, but provide a general guideline for potential ecological effects . Much of the existing research on ecological effects of cannabis has focused on illicit production on public lands . However, private land production is quickly becoming a dominant source of cannabis in the western U.S. while illegal public land production in the region either appears to be declining , shifting, or possibly increasing in some areas with increased enforcement.The first pathway consists of many, smaller farms in rural areas with a history of illicit or medical cultivation . The second path is dominated by fewer, larger farms in new areas more conducive to large-scale, industrial farming .

Note that although the legacy pathway is characterized by historical growing practices, this form of production can also expand with emerging development frontiers. Research on these development trajectories in California suggests that, although both trajectories are expanding, the legacy pathway may require policy intervention if it is to fully transition to, and persist in, the legal industry . 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,rolling benches hydroponics 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 , ringtail , cougar , bobcat , gray fox , and coyote. We anticipated that due to the cultural dominance of historical growing practices, 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 sub-watershed 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.

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, ringtail, cougar, bobcat, gray fox, and coyote. For individual species, 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 Steelhead . 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.