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.