Monthly Archives: October 2023

The U-shaped pattern is explained by the relationship found between urbanization and land value dynamics

As previously discussed, the high degree of correlation between precipitation and maximum temperature means would introduce multicollinearity if both were included in our analyses. In addition to including the mean precipitation values, we test the impact of short-run temperature and precipitation variability on likelihood of sales and land sale value. None of the climate variables studied impact the likelihood of selling farmland in Riverside County from 2000-2017. The 5-; 10-; and 30- year mean precipitation also do not impact farmland value. This is similar to the results in Deschenes and Kolstad . However, short-run precipitation variability has a significant influence on farmland value. A unit increase in the 5-year precipitation coefficient of variation reduces the value of farmland by 56% per acre. Population rate exhibits a significant relationship with both likelihood of land sales and land value. For example, a unit increase in the 5-year population rate decreases the likelihood of selling farmland by 32%, and increases farmland value by 85%. The exact relationship varies across model specifications, but remains significant. Further, population rate exhibits a U-shaped relationship with likelihood of land sales and a hill shaped relationship with land value. Urbanization naturally follows from population increase, and urbanization tends to increase the value of farmland . This may provide incentives to growers to hold on to their land, rather than selling it. However, the marginal productivity of farmland continues to decline with increasing urban encroachment . And, this makes selling farmland more attractive. Citrus and vineyard are less likely to be sold than avocado, while all land uses tend to be more valuable per acre than avocado. The significance of citrus and vineyards tends to vary across model specifications,grow racks with lights although that of general irrigated agriculture and dates remains robust across these specifications.

At the water district level, the results suggest that more valuable farmland is more likely to be sold. Coachella Valley Water District has the most valuable farmland compared to the other 3 districts. This suggests that, controlling for other factors, the characteristics of a given water district may add significant value and may be sold to achieve a positive return rather than minimize a loss.Resilience to water scarcity is fundamentally related to grower responsiveness to the external environment. We have quantified grower responsiveness to farm- and parcel level microclimate in two desert and two coastal counties in Southern California, using primary survey data . Our metrics include gross revenue per acre , likelihood of technology adoption , land value per acre , and likelihood of land sale . Although we study several grower and farm characteristics, climate, water source, farm type, and share of income from agriculture are the most robust variables in our farm-level analyses. The results of the parcel-level analyses of Riverside County in Chapter 6 suggest that short-run variability in annual precipitation may have negatively impacted land value over the past 17 years, though a relationship with precipitation variability and the likelihood of land sale during this same period is not supported by our results. Our analysis of grower responsiveness begins with a farm-level Ricardian model using several micro-level variables collected from our survey instrument . We study the climatic impact on gross revenue per acre in 2014, which is an annual measure of farmland productivity. In Chapter 5, we evaluate the extent to which adoption of irrigation management practices represents adaptation to an increasingly warm and dry climate. These monitoring practices require growers to be more pro-active in scheduling irrigations , and minimizing inefficient leaching practices , and thus represent the next generation of on-farm water management advances. The parcel-level analysis of Riverside County in Chapter 6 includes two complementary analyses: an exploratory analysis of the extent to which likelihood of land sales are impacted by short-run fluctuations in weather; and an analysis of the impact of these short-run fluctuations on land values.

These studies focus on adaptation to extreme climatic events, such as the droughts experienced in Southern California from 2007-2009 and 2011-2016. We introduce two sets of dynamic variables into the analysis: climate and population. Not only do we explore the extent to which these dynamic variables individually impact parcel sales and value, but we explore a preliminary relationship between likelihood of a sale and the relative value of the parcel. In addition to our empirical analyses, we learned how to construct a complex spatial dataset from primary data and existing public data sources on agricultural land values, climate, soil, groundwater, zoning, and utility boundaries. Chapter 3 provides detail on the questionnaire development as well as these multiple external data sources. Ultimately, the benefits of creating a rich dataset outweighed the cost in time.The 5-year total annual precipitation mean and 5-year total annual precipitation variability are both significant in both our binary logistic regression analyses. The positive relationship between the precipitation mean and adoption is counter-intuitive. We would expect this relationship to be negative because a decrease in precipitation associated with the drought would influence growers to monitor water quantity/quality if this grower were using monitoring as an adaption to the drought. We also observe a positive relationship with 5-year total annual precipitation variability, as we expected if monitoring were truly an adaptation to the drought. It is challenging to reconcile these seemingly contradictory results, and ultimately we are cautious about drawing a strong conclusion either way. Precipitation is a complex phenomenon, and further analysis with a larger sample may be necessary. Farm type and percentage of income generated from agriculture may be stronger determinants of adoption. Adoption that is not consciously tied to perceived changes in climate is often called “autonomous adaptation” . This is often observed in the short-run as relatively quick-fixes to production plans.

Given projections of increased frequency and duration of droughts during the current century, growers will develop the most effective, cost-minimizing strategies if they are intentionally addressing these long-run climatic changes today. Almost 1/3 of growers in our sample view drought as their primary threat to water security, and a greater link between monitoring and drought mitigation may even increase the level of adoption in the short-run. In addition to UC Cooperative Extension programs, there are several competitive grants that could incentivize growers to think in these intentional terms. As such, monitoring soil moisture and salinity could be a gateway into managing for long-run climatic changes.Yet, based on the results from our logistic regression, growers who primarily receive their information from state and federal institutions are roughly 3 times more likely to adopt either monitoring practice than those who receive from other sources . This suggests that government programs may benefit from strategic partnerships with industry and small farmers’ networks, without compromising their neutral political role. UCCE and NRCS, in particular, may be able to streamline and leverage their water conservation initiatives with other state government institutions . Our results from the farm-level Ricardian model suggest that a 5% increase in water price increases gross revenue per acre by 1.4%.1 We also study how frequently water price has increased over the past decade. We find that increasing the number of times the price has increased by one unit ,rolling benches for growing increases productivity per acre by 3.4%. This suggests that water price may direct growers to produce higher value crops. Future research on the role of price increases and frequency of these increases for lower value crop farms is important. The challenge is that crops with the lowest value per acre tend to be produced in districts with senior water rights, which do not regularly implement water price increases . Notably, although Coachella Valley Water District holds senior water rights, they have increased agricultural water price 4 times over the past decade. In constructing our dataset, we benefitted greatly from the spatial data from several generous agencies . We also lost both time and data due to poor quality data, which these agencies dedicate valuable resources to collect. Most surprising was the lack of standardization in parcel identification numbers between files from the same agency . There may be a role for academics in setting standards or creating repositories of quality data. The results from the two analyses in Chapter 6 suggest that the relationship between farmland sales and farmland value is attribute specific. Population influences sales and value in the opposite direction, whereas water district and land use attributes influences sales and value in the same direction. Even with limited resources, we were able to collect complete data on 187 growers. This suggests that growers are responsive to providing information to universities. We included a comments page in our survey, which we did not evaluate in our empirical analyses. Many of the comments suggested these individuals were receptive to information that would help them with their production plans , but they did not know how to find or even translate the information. One grower even commented, “We are not your farmers. You are our research university.” There is high potential to foster a positive relationship with growers both directly and, indirectly, through extension research. Perhaps growers could serve as partners in collecting quality data that would prove invaluable to academic research.We did not anticipate the large share of tree crop growers in our sample. This suggests that such growers are both more abundant, and likely more responsive to surveys.

Coupling this with the results from Chapter 6, which reveal that avocado parcels were most devalued and more likely to be sold in Riverside County, warrants a focused analysis on tree crop growers. It also warrants a separate analysis of field crop growers. More data, both across time and space, is needed to evaluate the likelihood of land sale and the potential implications of climate change. As analytics become increasingly accessible, it will be interesting to evaluate the adoption of these data tools and the extent to which productivity is affected. Indoor dust is the most commonly used material to assess microbial exposures in the built environment for studies that link to human health and disease. While the relationship between actual inhalation exposure and microbial measurements from aerosols is more straightforward than for house dust, bioaerosols are highly dynamic in nature and consequently difficult to collect in a way that represents average conditions. House dust is thought to be a long-term integrated sample of particles that have been airborne, thereby proving a composite view of microbes in the indoor environment. Another reason for the popularity of dust samples is the convenience of collection, which typically does not require costly sampling equipment and can be done in a standardized manner even by building occupants themselves and thus enables high replication, all major virtues in large epidemiological studies.There are different types of house dust samples and many ways to collect a sample. Here, we differentiate between dust reservoirs, such as floors and mattresses, and airborne particles that become settled dust. Reservoirs of dust are a popular choice for collecting an integrated sample of what building occupants may be exposed. However, some studies that relate different house dust sample types with bioaerosols sampled through active collection find that sampling reservoirs of dust may not closely represent airborne, inhalation exposure. Reservoir house dust and airborne particulate matter can be disconnected for several reasons. First, there are biases in the settling of small particles, and settled communities are expected to inefficiently contain small-bodied microbes leading to their under representation relative to larger bodied taxa. Second, in the case of floor or mattress samples, the dust also contains material tracked indoors on shoes, paws, or clothes, and in the case of mattress dust, the occupant is the major source of microbial material. Third, the time window sampled by dust reservoirs is variable and typically not precisely known. Instead, studies assessing different indoor sampling approaches attest that a much closer representativeness of actual airborne exposure is dust that settles on a standard sampler surface located above floor level. Passive collection on an elevated surface has two specific advantages: first, particle collection onto the standardized sampler surface occurs over a discrete and known time period. Second, placing passive samplers on a sufficiently elevated surface likely captures airborne dust rather than tracked-in, floor-based particles that may never get sufficiently airborne to contribute to human inhalation exposure. Due to these features of elevated surface samples compared to dust reservoirs, passive collectors of settled dust have been used in several studies, health-based and otherwise, to assess the microbes that occupants encounter in the built environment.

Serial concentrations of deltamethrin were prepared and used for the CDC bottle assays

The usual culprit is A. fumigatus, a fungus that grows in soil, decaying vegetation, food, water, and/ or dust. Other fungi, including Penicillium, Helminthosporium, Curvularia, and Candida, may cause a similar disease. Sensitization to the fungus leads to an inflammatory response in the lungs and airways, which includes eosinophil infiltration and increased mucus production. Eventually, bronchiectasis and pulmonary fibrosis can occur. Symptoms include wheezing, shortness of breath, cough productive of brownish mucus, fever, and malaise. Changes observed in chest radiographs are consistent with pneumonia. Laboratory studies have revealed high levels of Aspergillus-specific IgE and elevated peripheral blood eosinophils. Aspergillus skin testing reveals sensitization, but the test is also positive in patients with a simple allergy to Aspergillus. Treatment for ABPA includes corticosteroids and antifungal agents. Allergic fungal sinusitis is a disease that is pathologically similar to ABPA, but the sites of inflammation are the paranasal sinuses. Other features include nasal polyposis, nasal and sinus accumulation of fungal debris and allergic mucin, and crust formation . Cultures from the sinuses yield Aspergillus, although this is not pathognomonic, nor is the lack of positive Aspergillus cultures enough to rule out AFS. It is estimated that approx 5% of all patients with chronic rhinosinusitis have AFS. It is more common in atopic patients who have a diagnosis of allergic rhinitis and who test positive to one or more fungal allergens. AFS primarily affects young adults,vertical rack and most cases are geographically distributed in temperate areas with high humidity. Aside from Aspergillus, AFS can be caused by dematiaceous fungi, including Bipolaris, Curvularia, Exserohilum, Drechslera, Alternaria, Helminthosporium, and Fusarium. There is controversy regarding whether AFS is an infectious or allergic disease.

The fact that most patients with AFS have positive skin test and radio allergosorbent test to fungal allergens, as well as the prominent incidence of atopy in patients with AFS, support an allergic component to this disease. Eosinophils also play a significant role in AFS, and ECP levels were significantly higher in the mucin of patients with AFS compared with control patients . Criteria for diagnosis of AFS include radiographical evidence of sinusitis, positive fungal stain or culture from the sinus at time of surgery, presence of allergic mucin, absence of fungal invasion, and absence of contributory factors such as immuno deficiencies or diabetes mellitus . Differential diagnoses of AFS include saprophytic fungal growth, fungus balls of the sinuses, eosinophilic mucin sinusitis, and invasive fungal sinusitis. Hypersensitivity pneumonitis is another respiratory disease that is probably caused by microbes, but it is primarily an allergic disease. Hypersensitivity pneumonitis frequently occurs as occupational asthma, and several etiological agents have been cited. Examples of hypersensitivity pneumonitis and their suspected source include Farmer’s lung , bird fancier’s lung , pigeon breeder’s disease , hen worker’s lung , bagassosis , mushroom worker’s lung , air conditioner lung , cork worker’s lung , malt worker’s lung , sequoiosis , and woodworker’s lung . Symptoms include fever, chills, cough, and respiratory distress occurring 4 to 8 h after re-exposure to the inciting agent. If prolonged exposure is present, then the disease progresses into a chronic form and fibrosis develops, eventually leading to respiratory failure. Diagnosis is primarily based on clinical features, but it is supported by identification of the source agent, presence of specific antibodies in blood, chest radiography, pulmonary function tests, and lung biopsy. Treatment is based on avoidance and the use of corticosteroids. Therefore, it is important that individual patients be examined, including vigorous review of medical histories, physical examinations, and appropriate diagnostic testing to confirm and establish diagnosis and begin appropriate therapy.

We are continuously exposed to a wide variety of environmental pollutants, and many of them individually have been shown to have detrimental effects on health and development in experimental animals. Fewer studies exist for humans, and the results are not always consistent. This is not unexpected, however, because almost all current research neglects that humans are exposed to a myriad of environmental pollutants and that interactions between compounds may be responsible for the various symptoms and diseases that have reportedly increased in incidence in recent decades. Certain VOCs, formaldehyde, phthalates, and possibly OPs and carbamate pesticides have all been linked to lower respiratory symptoms in humans. Not only OCs, but also OP compounds, may induce subtle neurodevelopmental defects. Similarly to certain phthalates, the major DDT metabolite, p,p’-DDE, has been shown to be a potent anti-androgen in vitro and in vivo . Gestational exposure to p,p’-DDE resulted in reduced anogenital distance at birth and retention of thoracic nipples on postnatal day 13, but it did not decrease testosterone levels. Similarly, exposure to TCDD and certain PCBs can cause developmental toxicity that is manifest particularly in the male reproductive system . Conversely, o,p’-DDT, a minor component of technical grade DDT, and some DDT metabolites exhibit estrogenic activity, as do some hydroxylated PCB metabolites, whereas other PCBs and their metabolites act as anti-estrogens . This indicates a substantial potential for interactions among this large variety of compounds. Associations with decreased semen quality have been suggested not only for certain phthalates but also for PCBs overall and/or individual PCB congeners and their metabolites , p,p’-DDE , and OP pesticides . Results from an exploratory analysis suggest a greater than additive interaction between MBzP and MBP and PCB-153 and CYP450-inducing PCBs . It was proposed that this interaction could result from the inhibition of UDP-glucuronosyl transferase by hydroxylated PCBs, which results in greater amounts of free phthalate monoesters, believed to be the main biologically active metabolites. Unfortunately, neither OH-PCBs nor the ratio of free vs glucuronidated phthalate monoesters was determined. There have been few attempts to address the interaction of mixtures of compounds at physiologically relevant concentrations.

A notable exception is the pioneering work by Kortenkamp and colleagues. For example, they showed that a mixture of the OCs, o,p’- DDT, p,p’-DDT, p,p’-DDE, and β-hexachlorocyclohexane exhibited combination effects on MCF-7 human breast cancer cell proliferation when each of the components was used at concentrations at or below their respective no-observed effect concentrations . Similar results were obtained with combinations of up to 12 estrogenic chemicals in the yeast estrogen screen assays . Generally, the concentration addition model provided excellent predictions of the observed effects, whereas the independent action model, for the most part, did not. However, there were indications that cytotoxic or growth inhibitory effects of compounds included in mixtures might compromise the ability of the model to predict combination effects . The model ofconcentration addition was also found to accurately predict the effects of certain binary mixtures of environmental estrogens in vivo, using juvenile rainbow trout as the animal model and vitellogin induction as the measured end point . These findings “put into sharp relief the limitations of the traditional focus on single agent effects during hazard and risk assessments” , not only of the endocrine-disrupting chemicals this comment referenced but of many other environmental toxicants. Organic matter, such as proteins derived from living organisms, or toxins emitted by living organisms can also be associated with respiratory diseases. Combinations of aero-allergens can result in chronic allergic illnesses, including allergic rhinoconjunctivitis, sinusitis, and asthma. Mycotoxins released from fungi have not been demonstrated to cause human illness,bud drying rack although in vitro studies have demonstrated numerous cellular effects. Further research needs to be performed to characterize whether or not clinical effects of mycotoxins exist. SBS has been described since 1982, but there are no consistent data showing a common cause for the myriad of symptoms described. We do know that the symptoms are nonspecific and occur in more than one person in the same building and that multiple agents, as described earlier, have been cited as etiological factors. In addition to toxins, chemicals, and bioaerosols, there may be a major psychological component to SBS. We need the concerted effort of scientists from many different disciplines—particularly from informatics—for the identification of biological and nonbiological toxicants and the unraveling of their contribution to health effects in humans and wildlife. This should finally bring the power of computers to bear on the inordinate complexity of interactions among environmental pollutants as well as the interactions between pollutants and the organisms they affect.Mosquito survival status was examined at 24-hour post-exposure, where the survived and dead mosquitoes were collected and preserved at -20˚C prior to molecular analysis. Percentage mortality was calculated for both indoor and outdoor F1 mosquitoes.The involvement of oxidase resistance mechanism in pyrethroid resistance was determined by pre-exposing test populations to the oxidase inhibitor; Piperonyl butoxide synergist . Briefly, unfed females aged 3–5 days were pre-exposed to 4% PBO impregnated test papers for one hour. After pre-exposure to PBO, the mosquitoes were immediately exposed to each of the three pyrethroids separately for another hour. One batch of 25 females was only exposed to 4% PBO without insecticide asa control. Mosquitoes were transferred to holding tubes and supplied with 10% sugar solution. Mortality was recorded after 24 hour recovery period.

Insecticide resistance intensity testing to deltamethrin was determined by using CDC bottle bio-assay with serial dosages.The bottles were coated in batches for each working concentration, to which mosquitoes were exposed as per the CDC procedure guide MR4. The number of knocked-down mosquitoes was recorded every 10 minutes until either all mosquitoes in the test bottles were dead or it reached 1 hour after the start of the experiment. Mosquitoes were transferred to holding cups and fed on 10% sucrose solution. Mortality was recorded after 24-hours.This study set out to determine the level of insecticide resistance of Anopheles mosquito species between populations found resting indoors and those resting outdoors. Generally, high phenotypic, physiological resistance was observed in the progeny of indoor resting malaria mosquitoes than the outdoor resting vectors. In the lowland sites of Kisian , An. arabiensis was the most abundant malaria vector compared to its sibling species An. gambiae s.s. whereas in Kimaeti , the dominant species was An. gambiae s.s. similar to earlier reports . The lowlands tend to have high temperatures and low humidity which favour the more resilient An arabiensis whereas in the highlands, there are low temperatures and high relative humidity which favour An gambiae. The indoor population recorded high phenotypic resistance to pyrethroids than outdoors. The phenotypic insecticide resistance to pyrethroids in An. gambiae s.l. is widespread in Western Kenya evident in previous studies. The resistance to pyrethroids by An. funestus was observed and has as well been reported before. These regions of Western Kenya have been reported to have increasing resistance to pyrethroids which are the public health approved insecticides for use in LLINs. There was 100% susceptibility to malathion of mosquitoes just as similar studies have shown in Ghana. Synergist PBO pre-exposure restored susceptibility for both indoor and outdoor resting mosquitoes, revealing the role of detoxifying metabolic enzymes in the insecticide resistance in these regions. This means, therefore, that there are more factors at play contributing to the insecticide resistance present in Western Kenya similar to studies before. Increasing the concentration of the deltamethrin in CDC bottle assays restored susceptibility to 100% suggesting that the continuous exposure to the current dosage in LLINs and possible interaction with non-lethal doses in agricultural chemicals could have been at play to contribute to the development of resistance to pyrethroids as previously demonstrated in indoor resting and outdoor resting malaria mosquitoes. The result showed moderate intensity insecticide resistance since the mosquitoes succumbed to the highest concentration according to the WHO test procedures for insecticide resistance monitoring in malaria vectors. The buildup of the phenotypic resistance which was higher in indoor resting mosquitoes compared to the outdoor resting counterparts might be threatening current insecticide-based malaria control interventions as suggested by prior studies. The presence of resistance-associated point mutations was more in indoor resting mosquitoes than their outdoor resting counterparts. This can be attributed to the adaptations from selection pressures due to constant exposure to insecticide-based interventions such as LLINs and the extensive chemicals used in the tobacco farms in Kimaeti. The study also detected, even though in lower frequencies, a significant proportion of the vgsc-1014S and 1014F in An. arabiensis a phenomenon that has been previously reported. This is in line with studies that have shown the occurrence of more than one kdr associated point mutation within a population of An. gambiae s.l. already reported previously.

Negative control quartz filters were extracted and analyzed with each set of air samples

Anthropophily was highest in An. funestus compared to An. arabiensis in the irrigated zone. These findings are consistent with previous studies that have reported An. funestus s.s. to exhibit anthropophagic behavior in Kenya and in other parts of Africa . However, in recent reports, they have been shown to also feed on bovine in the presence of LLINs. This plasticity of the feeding behavior of the vector may influence malaria transmission, leading to residual transmission after the densities of endophilic and endophagic vectors have been reduced by the interventions . The life histories of An. arabiensis population of southern Tanzania were simulated in a model by Killeen et al. and estimated that two-thirds of the vector feeds outdoor in an area where bednet usage is high . Studies have indicated that An. arabiensis exhibits behavior that mediates residual transmission such as feeding outdoors on humans or cattle and rapidly exiting houses without fatal exposure to insecticide-treated surfaces . Findings of the present study demonstrated that An. arabiensis fed on humans both indoors and outdoors with a higher HBI outdoors and predominantly fed on bovine. However, it remains capable of transmitting malaria whenever it can feed on humans. There was a significant difference in the risk of malaria transmission by An. arabiensis in the two zones, with higher transmission risk in the irrigated zone. These results show that irrigation has an effect on malaria transmission and An. arabiensis played a significant role in transmission. In addition, this species contributed almost equally to both indoor and outdoor transmission. In many studies, irrigated areas have been associated with increased malaria transmission than neighboring non-irrigated areas ; however, in some cases, introduction of irrigation schemes reduces or has no impact on malaria transmission . Hence,vertical farming equpment the impact of water development projects on malaria transmission is variable and the transmission dynamic likely depends on the local epidemiological setting.

Our data also suggest that the zoophagic behavior of An. arabiensis could be accounting for the low transmission in the irrigated zone whereas the low vector densities limited transmission in the non-irrigated zone. The zoophagic tendency of An. arabiensis indicates zooprophylaxis may be a potential strategy for malaria control. The limitation of our study is the lack of information on the movement of endophagic mosquitoes as they exit the house after feeding and/or resting. This information would have improved the understanding of the effect of insecticide based vector control interventions in the houses on the normal movement, density, and reticence feeding of endophilic species .Endotoxin is a cell wall component of the outer membrane of gram negative bacteria. Sources include animals and agricultural activities. In its purified form, it is known as lipopolysaccharide, which is both toxic and immunogenic. A small and variable mass fraction of fine particles < 2.5 μm in diameter may contain endotoxin. Experimental inhalation of endotoxin in humans leads to airway inflammation, characterized by activation and migration of neutrophils. Exposure to endotoxin has been associated with exacerbation of respiratory allergic diseases including asthma, and with increased asthma prevalence. Ryan et al.were the first to show that settled house dust endotoxin and estimated exposure to traffic related air pollution positively interacted in relation to risk of persistent wheeze at age 3 years in a birth cohort of 624 children. Many other studies have also assessed respiratory and allergic health effects of endotoxin using only house dust samples as a surrogate of subject exposures to airborne endotoxin, often with only one measurement. However, exposure studies have shown considerable within-home, and temporal variability of house dust endotoxin. Furthermore, the exposures of interest come from resuspended indoor dust and endotoxin infiltrated from outdoor air that both determine indoor airborne concentrations. Airborne endotoxin measurements are expected to reveal stronger associations between endotoxin and respiratory outcomes than settled dust measurements of endotoxin. Several studies have evaluated household and other determinants of house dust endotoxin, and of airborne endotoxin inside and outside of the residence of pediatric subjects.

There is a considerably larger literature regarding airborne endotoxin exposures in occupational settings with organic dusts. However, despite the potential importance of endotoxin in particle-related respiratory health effects, only one study has assessed the impact of personal airborne endotoxin exposure on acute asthma outcomes in children. It is also the only study to have evaluated whether personal endotoxin exposure relates to airborne micro-environmental endotoxin levels among children. Investigators followed a panel of 24 school children with asthma with personal exposure monitors operated at 2 L/min over 24 hours for 164 person-days. They found that personal PM2.5 endotoxin and PM10 endotoxin exposure was associated with decreased expiratory lung function and increased asthma symptoms. Geometric mean personal endotoxin was higher than indoor or outdoor school levels and was not correlated with these stationary site measurements. This finding suggested that personal endotoxin exposure likely included substantial contributions from other particle sources. Sources include many indoor and outdoor micro-environments and personal dust cloud exposures to particles generated from personal activities or from exposures to non-stationary sources near the subject . In the present study we tested the consistency of the personal exposure assessment findings of Rabinovitch et al.using a repeated daily measures in a cohort panel of 45 children with asthma followed over a period of up to 10 days, and using home rather than school endotoxin measurements in a subset of 14 subjects. We also evaluated potential household and other determinants of personal and indoor airborne endotoxin exposures. Data include 376 person-days of daily endotoxin data collected from PM2.5 quartz filters using personal exposure monitors operated at 4 L/min, daily ambient endotoxin measurements collected from central ambient sites, and daily indoor and outdoor home endotoxin measurements in a subset of 14 children at 12 residential sites in Riverside and Whittier, California.

We also assessed the relationship between personal endotoxin exposures and concurrent personal exposure to air pollutants, including PM2.5 mass, PM2.5 EC, PM2.5 organic carbon , and NO2. We then assessed the relationship of personal endotoxin exposures to central site measurements of the same air pollutants, and to indoor and outdoor home PM2.5 mass, PM2.5 EC, and PM2.5 OC.We conducted a longitudinal study with 10 daily repeated measurements of health outcomes and exposures in a panel cohort of school children with diagnosed persistent asthma who were ages 9-18 years , nonsmoking, and unexposed to environmental tobacco smoke in the home. Results relating to asthma outcomes and air pollutants have been previously published. Two regional panels were conducted during warmer seasons of southern California. The first panel was conducted in Riverside, California, from August through early October 2003. This is a down-wind smog receptor site,4×4 grow tray which is a consequence of being just inland from Los Angeles County. The second panel was conducted in Whittier, California from July through November 2004. This is a region of eastern Los Angeles County that is immediately down-wind of vehicular emission sources. Riverside experiences higher temperatures and lower relative humidity than Whittier as a result of being further from the Pacific Ocean and closer to the inland desert. The Institutional Review Board of the University of California, Irvine approved the study protocol. Informed written consent was obtained from all subjects and one of their legal guardians. Subjects were recruited through notification of parents by local public schools. We recruited only subjects with mild to moderate persistent asthma. The present study focused on assessing endotoxin exposures in 45 subjects with complete outcome data including four 10-d periods in Riverside involving 13 subjects and eight 10-day periods in Whittier involving 32 subjects. The expected predominance of asthma among males vs. females was evident in this population . This was a diverse population with a majority of subjects identifying themselves as Hispanic along with 5 African American subjects and 14 white non-Hispanic subjects.Harvard Impactors were used to collect ambient PM2.5 and operated at a flow rate of 10 L/min. They were sited at a central site within 10 km of homes in Riverside and 5 km of homes in Whittier. We also collected indoor and outdoor home PM2.5 with Harvard Impactors in one subject’s home during each of the 12 tenday sampling periods. Indoor samplers were located in or near the main activity area of the home, usually the living room or family room. There were a pair of sibling subjects in two of the homes . PM2.5 , and PM2.5 EC and OC were collected at the stationary sites simultaneous with personal samples. PM mass on Teflon filters was estimated using standard gravimetric methods. For both personal and stationary site quartz filter samples, particulate carbon was speciated into organic and elemental carbon using the thermal manganese dioxide oxidation technique [20]. Criteria pollutant gases were measured by the South Coast Air Quality Management District at central sites and they included hourly O3 and NO2.Endotoxin was measured from extracts of archived PM2.5 quartz filters collected as described above . We do not have quartz PM10 samples. Although endotoxin is found in the coarse PM fraction , the respirable PM2.5 fraction is more relevant to lower airway dose and thus airway inflammation. All quartz filters were baked to remove organic carbon before sampling.

Only around 10% of the filters’ surface area was punched out using heat sterilized instruments for the EC-OC measurements, leaving sufficient filter media for endotoxin assays. The remaining surface area for personal endotoxin measurement was calculated for each filter to estimate particle mass using mass data from the 24-hr average PEM PM2.5 or gravimetric measurements from the Harvard Impactor PM2.5 Teflon filters for the stationary site measurements. For the endotoxin assay, we developed a rapid and thorough method of extracting endotoxin from quartz PM2.5 filters. Briefly, the extraction procedure combines the efficient disruption of quartz filter membranes by using a high speed, reciprocating instrument with conventional sonication. First, the quartz filters were transferred into pyrogen-free extraction tubes with 4 mL pyrogen-free water. The tubes were loaded into the FastPrep and processed at 6.5 m/second for 60 seconds to efficiently homogenize the filter membrane. The extraction tubes were then rotated for 30 min followed by 15 minute sonication and clearing of the aqueous extracts of quartz fibers and particles by centrifugation . The undiluted supernatants were then directly used for endotoxin assay using the Limulus Amoebocyte Lysate kinetic chromogenic assay according to the manufacturer’s protocol .The detection limit for the overall method was estimated at 0.004 endotoxin units /m3 air .Descriptive analyses of exposures were used to determine the shape of the distribution, central tendency, and spatial trends . We examined the Spearman rank correlation of personal endotoxin to ambient endotoxin measured at a central site in the 45 subjects, and to outdoor and indoor home endotoxin in the subset of 14 subjects. This was intended to establish the extent to which fixed site home and regional measurements are related to personal endotoxin exposure. Similar to other studies we found notable regional differences in concentrations and in correlations between Riverside and Whittier. Therefore, we present these correlation results separately for the two regions. House dust samples for endotoxin were not collected because the study objective of the parent project was to assess daily acute changes in asthma outcomes and airborne exposures. Because the endotoxin data for all measurement types were log-normally distributed, we used natural log transformation of the endotoxin variables prior to all regression analyses. We first examined the relation of indoor to outdoor endotoxin in linear regression models. Multiple regression analyses of the relation of continuous log-transformed personal endotoxin to stationary endotoxin measurements were conducted using the general linear mixed model. The mixed model estimates both fixed and random effects and incorporates the basic longitudinal design of the study in which multiple measurements are taken on each subject. Subject random intercepts were modeled to reflect the principle that measurements taken for the same individual are likely to be correlated . The following a priori adjustments were made in the mixed models for prediction of personal endotoxin by stationary site endotoxin: personal temperature and relative humidity , and study region. We fit an autoregressive-1 correlation structure given the observed error covariance.

The results of the Harvard Six Cities Study were independently validated

Particles with a 50% cut-off aerodynamic diameter of 10 µm can be inhaled into the lungs and, therefore, are referred to as thoracic, respirable, or inhalable particles. Since 1987, mass concentration of PM10 has been used in setting the US National Ambient Air Quality Standard for particulate air pollution . PM10 consists of fine particles with an aerodynamic diameter of 2.5 µm and coarse particles , and the contribution of PM2.5 to PM10 was relatively constant in a given area but varied between 35 and 80% by region . In 1997, the EPA proposed standards for PM2.5 . PM2.5 can be further divided into nucleation mode or ultrafine particles with an aerodynamic diameter less than 0.1 µm and accumulation mode particles . Whereas measurements of larger particles are commonly based on their mass concentration, UFPs have very little mass but comprise the vast majority of the total number of particles. Therefore, they are measured as number concentration. In Europe, there is a rather longstanding tradition of assessing levels of black smoke, which consists of black particles with an aerodynamic diameter less than 4.5 µm and measures elemental carbon . Based on the once valid assumption that black smoke originated mostly from burning coal, the OECD defined a standard of converting reflectance of these black soot particles into mass concentration. These standards are no longer appropriate because coal burning has decreased considerably in most industrialized countries over recent decades. Today, an estimated 60 to 90% of the atmospheric EC content is produced by diesel-powered vehicles. It is estimated that more than 80% of diesel exhaust particles have an aerodynamic diameter of 1 µm or less . Nonetheless, compared with purely gravimetric methods, measuring reflectance has the major advantage of providing some important information on the composition of particles.Coarse particles are generated from soil and other crustal materials mostly by the mechanical processes of agriculture, mining, construction, and road traffic,drying room but they also include particles of biological origin, such as pollen and fungal spores.

The most important sources of fine particles are incomplete combustion processes, formation of secondary particles via gas-to-particle reactions, and coagulation processes in the atmosphere. To varying degrees, ambient urban PM levels depend on both primary regional emissions and long-range transport. Indoor particle concentrations are determined by the concentration of particles outside and the generation of particles indoors. The contribution of outdoor PM2.5 to indoor levels has been estimated to average between 30 and 80% for homes from different geographical areas of the United States and Europe but can vary from 0 to 100% between individual buildings within these areas . This large variability results from the fact that the fraction of indoor PM derived from outdoor sources depends on various factors. These factors include particle penetration efficiency, particle deposition rate, air exchange rate, and the extent of particle generation during indoor activities of the residents, which, in turn, are subject to circadian and seasonal variation . The penetration efficiency of outdoor particles has been found to be close to one independent of particle size, indicating that building shells essentially do not filter particles nor do they provide protection from inhalation exposure to ambient PM . However, the effective penetration efficiency or infiltration efficiency depends on particle size because larger particles have higher deposition rates, whereas resuspension involves almost exclusively particles greater than 1 µm . The most important indoor source of particles is ETS . Considerable generation of particles also occurs during cooking and certain cleaning activities; vacuuming and the overall movement of people resuspend particles and contribute to indoor concentrations . Notably, one of these studies has provided evidence that terpeneozone reactions can result in pronounced elevations in fine particles and UFPs . As previously discussed, the products of terpene-O3 reactions have been shown to act as strong airway irritants . ETS results in elevated particle counts in all size ranges, but appears to more strongly affect the size fraction smaller than 1.0 µm . Cooking is one of the major indoor sources of UFP, with frying, toasting, baking, and barbecuing generating particles mostly in the ranges of 0.02 to 0.1 µm and 0.1 to 0.5 µm . Sautéing produces particles both in the ultra fine and coarse modes .

Although dusting, vacuuming, and walking constitute important sources of PM2.5, they predominantly raise the concentrations of coarse particles . Note that indoor particle events are brief and intermittent and not only have a pronounced effect on the size distribution of particles but can also raise particle number concentrations up to 100-fold and can result in peak mass concentrations that are several orders of magnitude higher than the values obtained from time-integrated samples .Inhalation is the major pathway of exposure to airborne particles, and adverse health effects can occur when particles are deposited in the lung or enter the systemic circulation via the lung. The fractional deposition of fine particles and UFPs is fairly high, generally ranging from approx 0.4 to 0.7 for UFPs, depending on the nature and size of the test aerosol and the breathing pattern . Total lung as well as peak deposition within certain regions of the lung depend on particle size, becoming greater with decreasing particle size for particles less than 0.5 µm and with increasing particle size for particles greater than 0.5 µm . The site of peak deposition also depends on particle size, with the site of maximal deposition shifting proximally with decreasing particle size for particles less than 0.1 µm and with increasing particle size for particles greater than 1 µm. This entails that local deposition dose can greatly exceed the average dose of the entire lung. Whereas fine and coarse particles deposit by gravitational sedimentation and inertial impaction, diffusion is the predominant mechanism of deposition of particles for the UFP range and up to a diameter of approx 0.3 to 0.5 µm. Peak deposition of UFP was observed in a volumetric lung region corresponding to the transition zone between the conducting airways and alveolar regions . Similarly, autopsy studies of lung tissue from subjects who had lived in areas with high particulate air pollution have indicated that tissue retention of fine particles is mostly observed in this transition zone . There is some evidence that UFPs are not necessarily retained in the lung but can diffuse directly into the systemic circulation . In healthy subjects, the magnitude of the total deposition fraction for fine particles and UFPs mainly depends on tidal volume and respiratory time and does not differ significantly between young and elderly subjects using the same controlled breathing patterns. Consistent with these observations, deposition of UFPs increases markedly with exercise as a result of both increased minute ventilation and an increase in the depositional fraction .

The influence of lung function parameters on the deposition fraction appears to be essentially negligible in healthy subjects . However, this is not applicable to patients with obstructive airway disease. Results from several recent studies indicate that deposition of fine particles as well as UFPs is greater in patients with asthma or chronic obstructive pulmonary disease than in healthy subjects , whereas clearance does not differ significantly . Examination of autopsy lungs indicates that particles are retained in lung parenchyma from residents of areas with low-to-moderate air pollution and that particle burden is significantly higher in lungs from residents of more highly polluted areas . A vast majority of these particles have aerodynamic diameters smaller than 2.5 µm, but UFPs constitute only a small fraction of the total . Such studies further show that retention of fine particles occurs primarily in terminal and respiratory bronchioles and is associated with inflammatory changes and small airway remodeling that may contribute to chronic airflow obstruction .In an ever-growing number of time series studies from around the world,trimming marijuana plants short-term increases in PM10 are statistically associated with increased cardiopulmonary morbidity and mortality . Conversely, there are indications that reduction of particulate air pollution is associated with a significant decrease in daily mortality . Fewer studies have addressed the effects of fine particles, but studies that have analyzed both PM10 and PM2.5 have provided evidence of much stronger associations of morbidity and mortality with the fine fraction . High correlations between PM and other air pollutants have been reported in some locations, and other criteria pollutants have also been linked to increased morbidity and mortality . However, at least part of the effect of PM appears to be independent of other air pollutants, and it remains a matter of debate whether gaseous pollutants are confounders, effect modifiers, or actual surrogates for PM exposure . Effect estimates for the increase in overall mortality associated with a 10 µg/m3 increase in PM10 range from approx 0.2 to approx 0.7% . Corresponding estimates for cardio respiratory mortality are usually considerably higher, and there is a markedly greater increase in respiratory compared with cardiovascular mortality . However, because cardiovascular disease affects far more people, the absolute number of cardiovascular deaths associated with particulate air pollution is substantially greater than that of respiratory deaths. Cross-sectional time series suffer from the inability to control for confounding factors such as smoking, alcohol consumption, diet and nutrition, body mass index, occupational exposure, and socioeconomic factors. However, the results from several large prospective cohort studies, in which such corrections are possible, have not only confirmed that higher ambient particulate pollution levels are associated with significant increases in deaths from lung cancer and cardiopulmonary disease but have yielded much larger effect estimates .

In a recent extended follow-up of one of the American Cancer Society cohorts, an increase in annual mean PM2.5 concentration was found to correlate with increases in all cause, cardiopulmonary, and lung cancer mortality of at least 4, 6, and 8% of subjects, respectively; the estimate depended on the time period during which PM2.5 levels were measured . All other causes of mortality were not associated with particulate air pollution. In partial contrast, in a cohort of nonsmoking Seventh-Day Adventists, ambient concentrations of PM10 were significantly associated with all-cause mortality in both genders and with lung cancer deaths in males only but were not associated with cardiopulmonary mortality . However, there was a significant association with deaths for which the death certificate made any mention of nonmalignant respiratory disease as an underlying or contributing cause of death. There are indications that the elderly and people with underlying heart disease, respiratory disease, or diabetes are more susceptible to the adverse effects of particulate and other air pollution . Nonetheless, the increase in daily mortality associated with particulate air pollution does not appear to be simply “ premature harvesting”—that is, the advancement of death by a few days in individuals with severe illness. Instead, some recent analyses have suggested that particulate air pollution shortens life expectancy by at least several months . Additionally, consistent with the results of prospective studies, the effect size estimates become considerably larger when longer lag periods are considered . We emphasize that although the effects of acute PM exposure on mortality are very small, a vast majority of the world population is exposed to this type of pollution, making the number of premature deaths associated with this exposure substantial. A recent estimate stated that 800,000 deaths worldwide are attributable to particulate pollution alone, of which approx 65% occur in Asia . Note that adverse effects associated with particulate air pollution are evident at levels below the standards set by various governmental and supra governmental agencies. Furthermore, the relationship between PM concentrations and adverse health effects is essentially linear, and there does not appear to be a threshold below which exposure can be considered safe . The biological plausibility of a causal association between particulate air pollution and adverse cardiovascular and respiratory health effects is supported by the fact that adverse effects of particulate and other air pollution on mortality and morbidity have rather consistently been reported from numerous areas worldwide with widely differing mixtures of air pollutants, absolute levels of PM, particle sources, and, therefore, particle composition. However, there are considerable differences in the size of the effect estimates. This is most likely attributable to differences in absolute exposure levels, particle sources, and their size distribution and composition, but may also include differences in the subjects and in the definitions of outcome measures.

Risk assessment of OP pesticides requires knowledge of the magnitude of the exposure

It has been shown that a semivolatile pesticide such as chlorpyrifos can volatilize days after its indoor application and can be adsorbed to various surfaces . Children’s felt toys, in particular, and, to a lesser extent, plastic toys accumulated significant levels of chlorpyrifos. For a young child exhibiting typical mouthing and hand-to-mouth behavior, dermal and nondietary oral exposure to such conditions were estimated to constitute a dose of 64 µg/ kg/d under the most conservative absorption assumptions and to contribute between 40 and 60% of the total dose. This greatly exceeds the allowable daily intake of 10 µg/kg/d proposed by the US EPA.Therefore, either environmental or biological monitoring is used. In recent years, environmental monitoring has yielded information on concentrations of OP pesticides in outdoor, indoor, and personal air; indoor dust; soil; and foods and beverages . All of the measured values vary considerably, but it is difficult to determine whether they reflect mostly methodological differences or represent true differences in pesticide concentrations. Note that many of the available studies have focused on chlorpyrifos and diazinon. The US EPA eliminated essentially all indoor residential uses of these pesticides by 2002, but they continue to be used in agriculture. Several important findings have emerged from these exposure assessment studies. OP pesticides are detectable in essentially all media analyzed, including food, indoor air, dust, and soil near the home. Interestingly, OP pesticides were not detected in duplicate beverage samples in two studies , whereas others reported their detection in 4 of 21 beverage samples; 4 of 9 of the samples that included apple juice contained azinphosmethyl . Comparisons of pesticide concentrations in dust, soil,cannabis curing and surface and hand wipes have clearly indicated that exposure of agricultural families is considerably greater than that of non-agricultural reference families . This higher exposure appears to result from both take-home pathways and proximity of the residence to farmland , although the association with proximity is not a consistent finding .

Using food consumption data from the Nurses Health Study and the Health Professionals’ Follow-Up Study combined with the data from the Food and Drug Administration Total Diet Study, researchers estimated that mean daily dietary intakes of chlorpyrifos, diazinon, and malathion were 0.8, 0.5, and 5.5 µg/d for women and 0.9, 0.5, and 6.1 µg/d for men, respectively . From duplicate diet samples, adult dietary chlorpyrifos and malathion exposure has been estimated to be 0.5 and 1.3 µg/d, respectively , and dietary chlorpyrifos intake in children was estimated to be 0.263 µg/d . Mean aggregate chlorpyrifos exposure from a total of six pathways was calculated to be 1.39 µg/d ; inhalation made the greatest contribution , whereas only between 7 and 13% was attributable to pesticide residues in solid food, and the dermal route was negligible . In two studies of children’s pesticide exposure, however, solid food made the greatest contribution to the cumulative intake of chlorpyrifos, malathion, and diazinon . Interestingly, despite the high contribution that food appeared to make to aggregate chlorpyrifos exposure in the Minnesota Children’s Pesticide Exposure Study, there was a much stronger correlation between urinary metabolites of this pesticide and concentrations in personal air than with levels in the ingested solid food . Additionally, note that the estimates of dermal absorption neglected to account for the volatilized portion of chlorpyrifos. The finding of a high correlation between chlorpyrifos in indoor air and in the corresponding dermal wipes suggests that this route of exposure may be important . The reported dietary pesticide intakes were generally well within the US EPA or similar reference values . However, it has been noted that dietary intake estimates greatly depend on the assumed value of nondetect samples, with assumption of a zero value underestimating exposure by a factor of 10 to 60 . Bio-monitoring of OP pesticide exposure most commonly involves measurement of their urinary metabolites or, much more rarely,quantification of the pesticides themselves and/or some of their metabolites in plasma .

Whereas urinary dialkylphosphate metabolites are nonspecific because they can be derived from a wide variety of OP compounds, certain other urinary metabolites are specific for one or two pesticides . Recall that urinary metabolites of OP pesticides can provide only rough estimates of exposure because the amount of absorption and the fractional excretion of specific metabolites are not really known, nor have all the metabolites been identified. Additionally, it cannot be determined whether and to what extent urinary metabolites represent exposure to one or more parent compounds or direct exposure to their metabolites. Furthermore, urinary metabolite concentrations should be corrected for dilution, but the appropriate method is still under debate , particularly because marked seasonal fluctuations in creatinine levels were observed in small children . Bio-monitoring of prenatal exposure involves the measurement of pesticides and their metabolites in umbilical cord blood, amniotic fluid, or meconium. A total of eight pesticides were detectable in 45 to 77% of maternal plasma samples obtained at delivery and in a similar percentage of cord plasma samples from 230 mother–infant pairs from New York City . Their concentrations in maternal and cord plasma were similar and highly correlated, indicating the occurrence of transplacental transfer and substantial in utero exposure . A further indication for transplacental transfer comes from the finding that the DAP metabolites DEP, dimethyl phosphate, and dimethylthiophosphate were detected in 10, 10, and 5% of amniotic fluid samples, respectively . Meconium consists of fetal bile secretions along with the content of the amniotic fluid that the fetus swallowed, representing exposure from the second trimester through delivery, and is usually not excreted by the fetus until after birth. DEP and diethylthiophosphate were present in 95 and 100% of 20 meconium samples from New York newborns, respectively, whereas other OP metabolites were detected in only one or none of the samples . Similarly, the detection of diazinon , malathion , parathion , and chlorpyrifos , along with various organochlorine compounds, has been reported in meconium samples from infants in the Philippines . Up to six or seven pesticides were detected in 4 and 5% of the samples, respectively. Some investigators detected an association between reported indoor residential pesticide use and urinary concentrations of specific pesticide metabolites, but this association was not detected in several other studies of children and adults . Reported pesticide use in the garden is also not consistently associated with urinary DAP levels .

A significant correlation was reported between levels of chlorpyrifos, diazinon, and the carbamate propoxur in personal air and the concentrations of these insecticides or their metabolites in plasma obtained within a month of the personal monitoring, but there was no correlation in plasma obtained at later time-points . Because of the relatively short half-lives of these pesticides, the relevance of these correlations is difficult to evaluate without further information about the regularity or chronicity with which the women were exposed to these pesticides. Several studies in which urinary pesticide metabolite levels were measured have confirmed the findings of environmental monitoring studies that farm children are exposed to higher levels of OP pesticides compared with children from non-agricultural reference families ,drying weed particularly during periods of pesticide application . In one of these studies, azinphosmethyl was the pesticide detected with the highest frequency and at the highest concentrations in house dust and was significantly correlated with dimethyl DAP metabolites in urine . Only the study that detectedan association between house dust levels of azinphosmethyl and phosmet and proximity to farmland also found higher dimethyl DAP levels in children living near treated orchards compared to those living at a greater distance . In the same group of subjects, however, urinary levels of the major chlorpyrifos metabolite, 3,5,6-trichloro-2-pyridinol were not significantly different between children from agricultural and non-agricultural families and did not reflect distance from orchards, although chlorpyrifos was present at higher concentrations in house dust of farming families and was increased with increasing distance from pesticide-treated areas . Although studies of exposure to individual pesticides, even those considering aggregate exposure, have generally found the estimated exposure levels to be well below the RfD , there is increasing evidence from biological monitoring studies that exposure to OP pesticides overall may exceed reference doses in a substantial number of subjects from both agricultural and non-agricultural areas. Calculations of exposure using urinary DAP metabolites are difficult because these metabolites can originate from a large variety of OP pesticides with highly different chronic toxicity and RfD values. In 2- to 5-yr-old children from urban and suburban areas of Seattle, the percentage of exposure estimates exceeding US EPA guidelines ranged between 0 and 100%, depending on which pesticide was assumed to be responsible for the exposure . When pesticides commonly applied in an agricultural community in Washington were used to calculate the absorbed daily dose in children age 6 yr or younger, 9 to 56% of children from agricultural families and 0 to 44% of reference children exceeded the EPA RfD for azinphosmethyl and phosmet during the spray season . Similar calculations for the same age groups of children from Yuma County, Arizona, indicated that the highest daily dose values were 61 to 385 times higher than the EPA RfD . In a study of pregnant women in the Salinas Valley in California, the estimated exposure to OP pesticides exceeded the oral benchmark dose10 of the US EPA in 0 to 36% of the women, depending on the index chemical on which the estimate was based and exceeded the benchmark dose for 10% response in approx 15% of women regardless of the parent compound .

The benchmark doses for 10% response are doses expected to result in a 10% reduction in brain cholinesterase activity in rats. Notably, there is evidence from urinary DAP assessments that suggests that consumption of a predominantly organic diet can greatly reduce dietary exposure to OP pesticides as well as the associated risk . However, daily consumption of a single meal prepared with organically grown produce was not sufficient to significantly influence urinary levels of DAP metabolites .OP pesticides and carbamates inhibit acetylcholinesterase . Because AChE inactivates acetylcholine at neuronal junctions, its inhibition results in ACh accumulation and continued neurotransmission. Because the autonomic, the somatic, and the central nervous systems all use ACh, the symptoms of OP-mediated AChE inhibition are manifold and include dizziness, headache, confusion, convulsions, blurred vision, respiratory distress, bradycardia and hypotension, fatigue, weakness, ataxia, muscle cramps, and increased lacrimation and salivation. Although the effects of environmental OP exposure are milder, they can resemble those of acute poisoning and, incidentally, include some well-known SBS symptoms, such as tearing eyes, chest pressure/tightness, and feeling dazed . Numerous animal studies have documented the developmental neurotoxicity of gestational or early postnatal exposure to OP pesticides at relatively low levels that did not result in overt systemic toxicity and inhibited cholinesterase to a minor extent in the dam. Such exposure resulted in impairments in maze performance, locomotion, coordination and balance, righting reflexes, and cliff avoidance. The molecular and cellular changes in the fetal or newborn brain that could account for these effects include inhibition of brain AChE and choline acetyltransferase activity , alteration of muscarinic receptor function via inhibition of ligand binding and permanent reduction in the density of muscarinic cholinergic receptors , altered synaptic development and function that can persist into adulthood , decreased expression and activity of multiple components of the adenylyl cyclase cascade , impaired DNA and RNA synthesis , and reduced cellularity and brain weight in offspring. Most of these studies were performed using chlorpyrifos, but similar effects and mechanisms were observed with other OP pesticides as well as two different pyrethroids . Few studies have addressed possible neurodevelopmental effects of prenatal OP exposure in humans. Recently, the association between prenatal OP pesticide exposure and neonatal neurodevelopment as assessed by the Brazelton Neonatal Behavioral Assessment Scale was investigated in 381 full-term infants in the CHAMACOS project. Table 11 includes maternal DAP metabolite levels during pregnancy in this cohort of women, which contained a substantial portion of agricultural workers from the Salinas Valley and other women with rather high environmental exposure to pesticides because of their heavy use in this agricultural center.

The greatest increase in product formation was seen when the reactants originated indoors

Occupational exposure to VOCs and formaldehyde are associated with some of the samesymptoms as SBS . However, levels of these compounds in office and other buildings are considerably lower than those found in industrial settings. Concentrations of total VOC in office buildings commonly range between less than 100 µg/m3 and several thousand micrograms per cubic meter, but maximum values of up to 50,000 µg/m3 have been reported . More than 350 VOCs have been detected at concentrations exceeding 1 ppb in indoor air , but generally only about 30 to 70 are routinely measured and even fewer are consistently detected in a majority of office buildings . When a group of Nordic scientists reviewed the literature up to early 1996 regarding VOC/ TVOC and health, they concluded that neither exposure nor epidemiological studies provided conclusive evidence that TVOC provided a risk index for health and comfort effects in buildings . A similar conclusion was reached in a review of studies that examined the association between SBS symptoms and indoor airborne PM, to which VOC can be adsorbed . However, the Nordic scientists stated that indoor air pollution, including VOCs, was most likely causally linked to effects on health and comfort. They also emphasized that there were “problems of principle with the concept of TVOC as such” because it is poorly defined— that is, it refers to different mixtures of chemicals with varying biological effects and is used in an unsystematic manner. Additionally, the use of various different sampling and analytical methods constitutes a major source of variability between studies . There are various other problems with the way current assessments of factors related to SBS symptoms are conducted. Measurements are often taken in only a few locations in a building, without accounting for the fact that there are microclimates in buildings resulting from differences in the ventilation rates,cannabis grow supplier in the number of occupants and the amount of bio-effluents they produce, and in the furnishing and equipment and, therefore, in the sources of chemical compounds and their source strength.

Additionally, symptoms are generally assessed via questionnaires, and these differ between studies and are not always validated. The period for which symptoms are assessed also varies from the single day on which environmental measurements are taken to as long as the previous year. In several studies, there is a considerable lapse of time between these measurements and the assessment of symptoms. The number and type of factors included as covariates or confounders in the statistical analysis also varies substantially between studies. Additionally, none of the available studies that we reviewed accounted for the fact that people are exposed to a wide variety of chemicals in micro-environments other than the workplace—particularly at home, where they spend the majority of their time. These considerations may explain the frequent failure to detect an association between VOC/TVOC and SBS. Various other hypotheses have been proposed to explain why VOCs may be an important factor in SBS, although the evidence is inconclusive . For example, it is possible that SBS is associated with a subgroup or subgroups of VOCs rather than TVOC and/or with intermediates or products of reactions between certain types of VOCs and ozone or various reactive oxygen and nitrogen species. Principal component analysis has become an important tool for identifying groups of chemicals and other factors that could explain the different frequencies of SBS symptoms in different buildings. It condenses a set of highly correlated variables into a smaller number of linearized sums . This works particularly well for VOCs because subsets of them have common sources. Because VOCs can originate from more than one source, they can be associated with more than one PC. PCA on a total of 39 VOCs measured in 12 California office buildings was used to identify exposure metrics—that is, mathematical expressions of the potential or actual agent that causes an adverse health effect . The exposure metric termed irritancy/PC emerged as the most significant predictor of irritant symptoms.

It consisted of the two most relevant vectors obtained by PCA, which were identified as representing carpet and building material emissions and emissions from cleaning products and water-based paint; it also accounted for the irritancy of VOCs relative to toluene. When analyzed separately, the cleaning products and water-based paints source vector provided the most important symptom prediction, with statistically significant adjusted ORs ranging from 1.7 to 2.2 for eye, skin, throat, stuffy nose, and overall symptoms. Other studies that used PCA on VOCs, but without accounting for their irritancy, linked photocopier emissions to mucous membrane symptoms; paint-derived VOCs to sore throat symptoms; construction material emission to dry eyes, mucous membrane symptoms overall, and short breath; and VOCs associated with furniture coating to shortness of breath . A combination of PCA and partial least squares analysis of VOCs desorbed from dust samples from nine office buildings identified a set of compounds that could account for 80% of the variance in the frequency of mucous membrane complaints and another set of compounds that explained 66% of the variance in difficulty concentrating . The possibility that oxidative degradation products of α- or β- pinene were among the compounds associated with mucous membrane irritation was particularly intriguing. As discussed later, the oxidation of terpenes produces formaldehyde and other aldehydes, and there are indications that some considerably more irritating substances are also formed. PCA was also used to identify factors that would be able to distinguish buildings with a high prevalence of SBS symptoms from those with a low prevalence of SBS symptoms . The most complex model was able to separate 71% of high-prevalence from low-prevalence buildings, and the most important variable was the higher concentration or more frequent detection of compounds with higher retention times in gas chromatography analysis in buildings with a low prevalence of symptoms.In five office buildings with different frequencies of reported SBS symptoms, cluster analysis was used to identify “hot” and “cold” spots—that is, areas with high and low symptom frequencies—in each building . Only people working in areas where chemical and other measurements had been taken were included in the analysis.

The most striking finding was that the same factors were associated with different symptoms and the same symptoms were associated with different factors in the various buildings. Furthermore, a recent comparison of personal exposures to aldehydes, amines, NO2 , O3 , particles, and VOCs in eight office buildings in a town in northern Sweden found that intra-individual differences accounted for the variation of 78% of the 123 measured compounds, whereas differences among buildings were the major source of variability for only 14% of the compounds . This highlights the inadequacy of a few stationary measurements in buildings and underscores the need for personal exposure measurements. Weschler and Shields noted that the inability to identify irritants in an indoor setting does not mean that the setting is free of irritants but may simply reflect the difficulty or even impossibility to detect the relevant compound with the analytical techniques routinely used to monitor indoor air quality. It may not be the VOCs that cause SBS symptoms; rather, it may be reaction products,cannabis drainage system particularly the reaction of unsaturated VOCs with O3 and various oxygen and nitrogen radicals . The major source of O3 in indoor air is outdoor-to-indoor transport . Additionally, office equipment, such as laser printers and photocopiers, has been shown to emit not only VOC but also O3 . Monoterpenes are unsaturated VOCs that contain one or two double bonds that react readily with O3 , OH radicals, and nitrate radicals to yield various aldehydes, ketones, carboxylic acids, and organic nitrates . The reaction of terpenes at concentrations below their no observed effect level with O3 yielded reaction products that acted as strong airway irritants in an established mouse bio-assay . Although known irritants were among the reaction products, they did not fully account for the observed effect, suggesting that one or more highly irritating intermediates and/or as yet unidentified products were formed. A possible candidate is submicron particles, which have been shown to form when O3 reacts with terpenes under simulated office conditions . Modeling and experimental measurements demonstrated that the product formation of uni- and bimolecular reactions increased at decreasing ventilation rates, whether or not there was sufficient time for the system to achieve steady state .Therefore, the decrease in SBS symptom frequency observed with increasing ventilation rates is likely to reflect not only the removal of pollutants with indoor sources but the restriction of reactions among indoor pollutants. A study of 29 office buildings in northern Sweden is frequently cited to support the hypothesis that reaction products, rather than VOCs themselves, are associated with SBS symptoms . Compared with buildings where TVOCs were higher in the room air than in the intake air, buildings where VOCs were “lost” from intake to room air had an OR of 39 of being SBS buildings .

The more TVOCs were lost, the higher the concentration of formaldehyde was, providing indirect confirmation of prior experimental data and indicating that VOCs reacted with O3 to form various aldehydes, including formaldehyde . A major shortcoming of this study is that VOCs were measured up to 6 mo after SBS symptoms had been assessed by questionnaire. Furthermore, PCA of the data from the same 29 office buildings did not confirm the significant association of lost TVOCs with the prevalence of SBS symptoms . However, this may have been attributable to the simultaneous “loss” and “gain” of TVOCs in separate rooms within the same building. It is rather striking that investigations of the possible associations between VOCs and SBS have focused exclusively on VOCs at the workplace, although exposure occurs in almost all micro-environments—particularly at home, but also in cars, public transportation, restaurants, pubs, stores, and movie theaters . Although rather different half-lives of elimination have been reported for VOCs from blood, there is general agreement that VOCs are rapidly taken up and that their elimination is characterized by a two-exponential, and in some cases a three-exponential, equation . This suggests that blood VOCs are distributed to multiple tissues for storage and that the kinetics of elimination vary with the storage site. This is confirmed by measurements of VOCs in breath, which suggest that under steady state conditions, the residence times for bloodor liver, organs, muscle, and fat are approx 3 min, 30 min, 3 h, and 3 d, respectively . From these data, it appears possible that bio-accumulation occurs and, therefore, that not only the kinetics of VOC uptake and elimination but also the threshold for adverse health effects may differ after acute and chronic exposure. It remains to be established whether cumulative exposure to certain groups of VOCs is a better predictor of SBS symptoms than exposure in the work environment alone.In recent years, several environmental monitoring studies other than those attempting to identify factors involved in SBS symptoms have focused on VOC exposure. A major impetus for such studies was provided by the fact that several VOCs are among the 189 hazardous air pollutants listed in the US Clean Air Act Amendment. These include the known human carcinogens, benzene and 1,3-butadiene, and the probable human carcinogens, styrene, methylene chloride, and carbon tetrachloride. The International Agency for Research on Cancer also recently reclassified formaldehyde from Group 2A to Group 1 . Until recently, the majority of research on VOCs focused on identifying exposures in outdoor air, but data on indoor residential exposure to VOCs are beginning to accumulate . In studies measuring personal and residential indoor as well as outdoor concentrations of VOCs, personal exposure of adults and children generally exceeded residential indoor exposure by a substantial margin, and indoor concentrations were considerably higher than outdoor levels . An analysis of data on personal, residential indoor and outdoor, and work environment indoor concentrations of VOCs in Helsinki, Finland indicated that the geometric means of residential concentrations of VOCs exceeded those of work environments . Notably, the sample was representative of the population of Helsinki and included people with occupational exposures to VOCs, as indicated by the high maxima reported for the work environment, which were two orders of magnitude higher than mean residential concentrations.

Previous studies have raised many concerns about the cannabis industry’s potential effect on wildlife

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,vertical farming supplies 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. 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, 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 indoor greenhouse 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, 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 cannabis cultivation appears to generally follow one of two development trajectories

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.

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