Several interviewees mentioned that the climate in Josephine County was ideal for cannabis, while others expressed the belief that it was primarily grown in the region because of history and culture. One farmer mentioned that owning versus renting land for cannabis farming might change the relative importance of the physical factors of a parcel that a farmer prioritizes, as might living on the property where they are growing, but they weren’t sure how often producers rented versus owned their farms.We translated the above biophysical parcel qualities into multiple spatial drivers. First, we grouped land cover classes into a binary variable based on ease of clearing for crops. We included the following classifications in the easy to clear category, based on land cover descriptions: Developed Low Intensity, Grassland/Herbaceous, Developed Open Space, Pasture/Hay, Barren Land, and Cultivated Crops. In addition to clearing, we created a binary variable to describe if the majority aspect of a parcel was southern-facing, to reflect parcels with greater sunlight access, using the raster package in R. We also used maximum elevation per parcel to capture elevation as a potential limiting factor, using a 10 m DEM and the exactextractr package in R . We calculated maximum roughness to capture potential preference for overall flat parcels using the ‘terrain’ function in the raster package in R . In the raster package, indoor grow trays roughness measures the difference between the maximum and minimum elevation value of a cell and its surrounding cells.
One farmer mentioned that parcels in Josephine County were smaller than in other regions where he had farmed cannabis, while other farmers implied that they had looked for larger parcels within the county. Multiple farmers discussed the importance of space on the property, whether directly for cannabis production , multiple kinds of cannabis production , or for other reasons, for example to provide a treed buffer or space for a fence between the farm and its neighbors, to have enough room for setback distances required by regulation, or to accommodate other land uses on the same parcel . To translate this into a spatial driver, we used the calculated area of each parcel polygon using the sf package in R. Not all farmers interviewed operated licensed production sites, and many were in a “gray zone” of legality, and so for some, proximity to water on a parcel was more important than specific water rights. Most farmers mentioned that in 2016, regulations on cannabis farming were not yet enforced, and so access to water at that time point might have had more to do with physical parcel qualities than legal access. Because of this, we used proximity of farmed parcels to water as a spatial driver instead of specific water rights on a given parcel for our model. We used the NHDplus flowlines database, filtering to include rivers and streams, as well as artificial paths . We then calculated distances using the sf package in R . While some farmers mentioned that soil quality mattered to them when selecting a site, most said that existing soil was not a primary concern for them, or for most farmers that they knew. Instead, most reported that the industry standard was to grow with imported soils in grow bags or boxes. Some farmers did report growing in native soil, but that they still had to add amendments to do so.
Given the mixed comments on soil quality, we did not include this as a potential spatial driver of cannabis land use.While all farmers interviewed discussed the difficulties of supporting themselves or their families economically in the cannabis industry, none of them specifically mentioned land prices as a factor in their decision making, and we did not ultimately include any drivers based on this theme. In the quote above, the farmer expressed that it was difficult to make a secure living with cannabis farming, which often made it risky to attempt new sustainable techniques. In this case, the farmer was also explaining that in their own attempts to grow with lowered environmental impacts in mind, it sometimes meant an income tradeoff. Thus, farmers reported that economics primarily influenced their decisions on specific land use practices, as well as whether or not to enter the licensed market. The farmers did see broader drivers of supply and demand being important for the industry as a whole, but for their individual decisions, economics was influential in deciding how much to grow, how much to spend on equipment or labor, how to balance different types of production , or when they might have to leave the industry altogether. Most expressed that the industry, both licensed and unlicensed, was full of uncertainty, and economic vulnerability. Many expressed concerns that when operating under economic uncertainty, farmers were unlikely to take a risk on more sustainable or less ecologically-impactful farming practices. All interviewed farmers said that the cannabis farming industry had expanded with legalization, and expressed concerns or uncertainty for the future of the industry. In the quote above, the farmer was looking at their own long history in the cannabis industry and seeing an uncertain future, and comparing it to the other major land-based industry cycles in Josephine County.
Most interviewed farmers compared the cannabis industry to the gold rush, and expressed concern that its rapid increase might not be sustained in the long term. Many farmers, both legacy producers that associated themselves with hippie culture or renegade counter-culturalists, as well as younger farmers that came from more indoor or urban production cultures, described a shift in the industry from one that was culturally or spiritually motivated to one that is primarily economically driven. They expressed concerns that the industrialization of cannabis with the legal market would lead to further ecological harm, while the money involved in the black market would encourage other criminal activities . Many farmers expressed a desire for more research and education, particularly around best growing practices. Most of those interviewed agreed that there was a general lack of knowledge or research-supported farming practices. While few were optimistic about the future, most expressed a belief in small-scale farms to produce in a way that was less harmful to the environment than conventional agriculture, and for persistence of a “craft cannabis” market.For the model of cannabis development onto new parcels post-legalization in 2016 , we found that the following hypothesized drivers had a significant relationship with parcels that developed new cannabis: larger parcels, lower human footprint, lower distance to nearest cannabis, higher density of local cannabis, easily cleared land cover, non-farm zoned, lower elevation, less rough, lower distance to rivers, and mapped in 2013 . All significant drivers performed in the direction we predicted , except for farm zoning, which was negatively associated with the development of new farms, and image year, which did not have an associated prediction. Distance to nearest cannabis, local cannabis density, parcel elevation, and distance to rivers or streams all had approximately linear relationships with the probability of new cannabis development . Parcel area and roughness on the other hand had non-linear relationships with possible threshold effects . The change in probability attributable to individual covariates was generally small , except for parcel area and human footprint . Rural cannabis land use in the western US has traditionally been a difficult topic for research. In this study, we demonstrated the effectiveness of an interdisciplinary approach to identify, assess, and contextualize drivers of cannabis land use and development. We combined generative cannabis farmer interviews with three models of cannabis land use in Southern Oregon during the early period of recreational legalization , to examine the relationship of spatial covariates with cannabis distribution, new development post-legalization, and plant density over time. The majority of our covariates were significant in at least one model, and combined with the context from the farmer interviews, vertical grow racks for sale suggest that they are likely reliable predictors of land use in this system. Previous studies examining cannabis land use and land use change have relied on biophysical covariates. Building on this foundational approach for understanding cannabis distributions, the addition of interview data to inform and contextualize models adds depth to the interpretation of modeling results, and generates new covariates that might otherwise be missed. For example, in Butsic et al. , the authors noted strong network effects on the distribution of cannabis production, and postulated that producer networks might be important in the development of the industry.
The interview data in our current study support this interpretation and produce the same finding in an additional legacy production region. Our approach of incorporating social or cultural data into ecological modeling is not unique to cannabis production, and is becoming more common in contexts as varied as deforestation , marine conservation , and human-wildlife conflict . One strength of incorporating qualitative data into quantitative models is the ability to capture nuances that may be left out or simplified in traditional modeling efforts. For example, while we did not identify any economic covariates functioning at the parcel level for our models, the interview data helped us recognize that broader economic changes are likely to influence changes in regional cannabis production over time. Another example was our use of local cannabis density as a proxy for supportive local attitudes towards cannabis farming. The interview data allows us to simplify a much larger concept of connection to community with this variable, while recognizing that in doing so, we may lose some local nuances – such as locations where there is a high neighborhood cannabis density but also strong negative community attitudes towards cannabis production. Some of the drivers identified in our study raise concerns that farmers may be actively selecting parcels that are in areas of greatest environmental sensitivity. For example, as farmers seek out more rural parcels, these are also likely to be ones with greater terrestrial wildlife habitat—in fact, as the interviews indicate, this faunal biodiversity is often something farmers appreciate and seek on the land in which they live and farm. Similarly, the preference for parcels closer to rivers and streams may result in negative impacts on freshwater systems. Previous research has illustrated a potential overlap of cannabis agriculture in Josephine County with terrestrial and aquatic biodiversity , and our findings here suggest that this overlap is not incidental. It is possible that the ecological overlap observed in other rural cannabis-producing regions could be influenced by similar social/cultural drivers. The significance of ruralness and distance to freshwater in the model of new farm development further raises concerns that this proximity could increase over time. The emergent theme of connection to community, and the strength of its associated drivers for cannabis distribution illustrated the network reliance of cannabis farmers, which further suggests that development over time is likely to occur in areas that are current cannabis hotspots. The context provided by the interview data suggests that some of the same motivations leading farmers to grow in rural areas may also provide opportunities to mitigate potential environmental harm. While our sample of farmer perspectives is relatively narrow, they all expressed strong environmental stewardship values. Similarly, other studies from California have identified commitments to environmental practices among outdoor cannabis farmers . These values alone do not mean that private land cannabis farming has a low environmental footprint — the farmers themselves even expressed concerns over the impacts of the industry. Rather, environmental stewardship values, combined with farmer concerns about the lack of education on best management practices for cannabis, implies that there is a research, education, and outreach gap for sustainable cannabis farming. This gap is one that researchers have repeatedly noted . Moreover, in their connection to community, farmers explained that they rely heavily on learning from other farmers’ practices. Thus, there may also be opportunities to enforce conservation-minded practices via cultural dissemination to receptive farming communities.Our land use models illustrate a rapidly expanding cannabis farming industry, with a 116% increase in parcels with cannabis, and a 227% increase in plant count over 2-3 years from pre- to post-recreational legalization county-wide. Despite this rapid increase in cannabis production, most interviewed farmers were not optimistic about the future of the industry, with frequent comparisons to other “boom-bust” natural resource trajectories. Moreover, many farmers also described an industry that was currently unpredictable, difficult to navigate , and unlikely to result in long term financial stability.