Cannabis was located on average 273 m closer to coho salmon habitat than private parcels overall, 387 m closer to fall run chinook, and 132 m closer to winter run steel head, though the IQR intervals overlap. This proximity to freshwater in Josephine County was also generally closer than observed in other legacy cannabis regions . For example, the proportion of sites in Josephine County within 500 m of coho habitat was more than twice the proportion in northern California . Butsic et al. used intrinsic potential data rather than direct fish population data, which may overestimate fish populations , so this difference could be even more extreme. Coho salmon spawn in smaller upstream tributaries that may be particularly susceptible to drought or water withdrawals . This proximity to coho may be explained by the large number of cannabis sites in proximity to small, head water streams , which could further indicate potential threat to other species that depend on these habitats, such as headwaters-dwelling amphibians. Therefore, this proximity to fish habitat could be an ecological concern if farms are drawing water from small rivers or shallow wells during the dry season . Whether or not metrics summarizing the proximity of farms and sensitive habitats result in actual ecological harm largely depends on the individual land use practices occurring on cannabis farms. There is a rich history of different approaches to cultivating cannabis , which could lead to variation in how cannabis affects ecosystems. Unfortunately, we still do not have a complete picture of cannabis land use practices, nor their mechanisms underlying their ecological effects. So far, available published research suggests that much of small-scale private land cannabis production may not be as ecologically damaging as previously believed , though a consensus has not been reached, and effects may vary over time. Given our current knowledge, therefore, the snapshot of private land cannabis in 2016 in Josephine County does not on its own indicate widespread ecological effects. There could however be an increased concern for local biodiversity if cannabis indoor grow system development expands in size or intensity while remaining in the same spatial configuration—located in forested vegetation, and in proximity to a few key sensitive carnivore and fish species.
Certainly, the large number of new farms in the first year of legalization suggest a rapidly expanding industry. This concern suggests a need to consider development pathways and future trajectories that sustain conservation values. The recent boom in outdoor cannabis farming has created a rapid development frontier in the 19 US states that have legalized cannabis production . For decades, outdoor cannabis was grown illegally, often in rural, remote areas, but with state-level legalization, production in those same “legacy” regions has rapidly expanded . In some of these rural, legacy-production regions, cannabis production on private lands can transform development patterns at a regional scale . This development frontier can foster new cultural, economic and demographic dynamics . Importantly, these new patterns of land use also incite concerns for ecological impact related to habitat fragmentation or degradation, potential effects on freshwater quality/availability, and direct or indirect effects on wildlife populations . To understand, reduce, or mitigate these potential impacts, it is important to identify the social and ecological factors that drive cannabis development on private lands across space and time. For example, understanding why farmers choose to cultivate at particular sites may help lawmakers craft and prioritize appropriate regulations for licensed cannabis. Additionally, spatial distribution and socio-cultural drivers are important for understanding where risks of environmental impact or human-wildlife conflict may arise, and for predicting the future trajectory of the cannabis industry. However, there remain many challenges to understanding drivers of cannabis development in these complex systems. Outdoor cannabis production in legacy regions is unique from other forms of traditional agriculture and functions as a closely tied social-ecological system. In these small-scale cannabis systems, the history of illicit farming lays a foundation for production practices that are vastly different from crops that did not have to be concealed, or that were grown following standardized agricultural practices across an industry.
Given the continued barriers to bringing legacy farmers into legalized cannabis systems and the existence and persistence of illegal markets, historical context is likely to influence current growing patterns, even as they move into licit markets and expand on private lands . In addition to historical practices that initiated the industry, there are other factors that likely influence whether, where, and how cannabis is produced, including federal, state, and local regulation and enforcement, social acceptance of cannabis within a region, access to education and communication of production practices among growing communities, short- and long-term economic trade offs, and others. These factors will influence the spatial distribution and predominant production practices of cannabis over time, which could shift the proximity of cannabis to terrestrial and aquatic wildlife habitats, or alter cannabis impacts on the local environment. These perceived or actual environmental impacts from cannabis can feed back into cannabis land use via shifts in attitudes that could lead to voluntary changes of production practices, increased enforcement, regulatory changes, or shifts in community acceptance for local production . Previous attempts to assess the drivers of cannabis land use or predict the current or future distribution of cannabis production have relied heavily on biophysical and bio-climatic models, using variables such as slope, forest land cover, distance to streams, aspect, canopy cover, and precipitation . These models have demonstrated that compared to other forms of farming, cannabis is generally less influenced or predicted by biophysical variables . This is unsurprising, however, given that social and cultural variables are likely to profoundly shape the spatial distribution of cannabis production. For example, depending on the production style, a cannabis farmer might forgo a less bio-physically ideal production area in order to stay concealed, or to grow near hospitable neighbors or close to other cannabis farmers with whom they can share labor or knowledge. Thus, social variables may be relatively more predictive of cannabis industry dynamics than biophysical variables. Ultimately, bridging social and ecological knowledge may be key to understanding the spatial dynamics of cannabis land use.
Integrating a more complete social-ecological context into models of land use presents multiple challenges. First, it requires an in-depth understanding of the system to be modeled. In the case of cannabis agriculture, its illicit history is an impediment to research. Federal restrictions on research funding to study an illicit crop have meant that there are few studies to draw on for characterizing patterns or trends in cannabis equipment production, particularly on private lands . Given the lack of formal research on the fledgling recreational cannabis industry, those who understand the industry best are likely those engaged in it directly. Thus, interviews of cannabis farmers may be a particularly valuable approach for identifying and understanding potential drivers of cannabis land use. Interviews come with weaknesses, however; small or biased interview pools may fail to uncover the most important drivers of cannabis land use, or farmers themselves may be unable or unwilling to articulate the drivers that are most relevant to their landscape-scale decision-making. The second major challenge to integrating social and ecological understandings into land use models is that some potential drivers may not readily lend themselves to quantitative analysis. The transformation of qualitative knowledge into quantitative data is an inherent challenge for many interdisciplinary studies that attempt to merge opposing ontologies. For example, translating attitudes or perceptions into numerical data is a longstanding dilemma in quantitative social science where doing so risks losing context and being misunderstood . Nonetheless, integrating environmental modeling with social, economic and political drivers will enhance our understanding of system dynamics . In this study, our goal was to identify, assess, and contextualize potential drivers of private land cannabis farming in Josephine County, Oregon, between pre- and post-recreational legalization , using both sociological and environmental variables. We used cannabis farmer interviews to generate a list of sociological and ecological covariates for models of cannabis land use early in the process of recreational legalization. Our method for addressing issues around the translatability of qualitative to quantitative data was to mitigate risk of misinterpretation by only looking at drivers conducive to quantitative modeling, while those that were less conducive were used to help interpret the results. We supported our driver selection with insights from existing cannabis literature, and experience living in Josephine County for two years during data collection.
One of the most common factors mentioned in farmer interviews was the importance of community, both in terms of their connection to other cannabis farmers as well as to their surrounding neighbors. For example, in the quote above, the farmer was describing how his relationship with his neighbors instilled a sense of both community and responsibility that translated into on-the-ground decisions he made on his farm, such as when or how to use grow lights. The interviewed farmers explained that having a good relationship with neighbors was critical for surviving in the industry, regardless of whether they were licensed or not. In addition, they described that best growing practices were often communicated through social networks, both online and in person, and so they often relied on other cannabis farmers for advice or assistance. Interviewed farmers explained that cultural norms dictated practices, which in Josephine County are often influenced by legacy production styles and attitudes. Some farmers also mentioned the advantage of being able to help each other with labor when living close to other farmers. In translating this theme into quantitative variables for potential land use drivers, we focused on farmer reliance on other local cannabis producers. We quantified proximity to other cannabis farms by calculating the smallest non-zero distance from each parcel to the nearest cannabis farm both pre- and post-legalization, using the ‘st_nn’ function from the nngeo package for R . This package calculates the k-nearest neighbor distance between features. We calculated a large number of neighbor distances for each parcel, then selected the minimum distance excluding all zero values. We also attempted to estimate neighborhood tolerance for cannabis farming. To do so, we used the density of cannabis within a 1 km radius around each parcel both pre- and post-legalization as our spatial proxy. Cannabis production in Josephine County is clustered at multiple spatial scales and so any distance threshold that represents a localized area might be appropriate, but we chose 1 km because this generally encompasses a local neighborhood. Using the sf package in R, we generated buffers around parcel centroids, intersected them with centroids of cannabis sites, and then converted the count to density by dividing by buffer area. All farmers interviewed expressed personal values related to environmental stewardship. In the context of the quote above, the farmer was comparing his impact from cannabis farming to nearby clear cut logging, and explaining his deep conviction that his style of land use was environmentally sustainable compared to larger industrial and extractive land uses. In the opening quote from the introduction, “Money actually does grow on trees out here, and that’s a blessing,” a different farmer expressed similar sentiments, connecting his farming to both nature and livelihood/profit, while expressing gratitude that the place itself, Josephine County, enabled that relationship. Many of the interviewed farmers explained that their motivations for growing cannabis stemmed from a desire to connect with the land or nature, although only a few had been farmers before cultivating cannabis. Interviewees often mentioned that the ruralness of Josephine County was an attraction because of its biodiversity. Many farmers reported personal connections with and fondness for the wildlife on their production sites.For example, farmers highlighted concerns about pesticide or rodenticide use, trash/plastic waste, animals caught in netting, water pollution , excessive water withdrawals, waterway diversion, imported soils, clear cuts, and paving. Multiple farmers raised concerns that the state or county regulatory process did not support environmental stewardship, and some expressed concerns that following regulations made it more difficult to practice what they saw as sustainable or regenerative farming practices such as intercropping, or crop rotation. The interviewed farmers generally considered themselves as having less impactful growing practices than other cannabis producers in the region, while farmer descriptions and farm visits both demonstrated a wide variety of production practices across all farms.