Hemp Growing

Previous studies emphasized that microbiota change depending on whether it is associated with solid particles or liquid fractions. As a consequence, the mode of manure application will likely to influence the microbial load in the cropland receiving manure as fertilizer. Both liquid and solid manure are applied as fertilizer in developing as well as developed countries; however, a detailed research in terms of microbial communities of compost manure and irrigation manure is rare—if not unavailable. Increasing public concern with regards to the microbial load in manure fertilizers and associated health risks necessitates the scope of such studies. Moreover, the trend in dairy industry shows that larger dairies, which confine the relatively large animal population in limited acreages, are more efficient than smaller dairies, and their number is increasing consistently. This means that the manure production in future dairy farms will increase as a result of higher animal density in a relatively limited area. Eventually, the increased manure production will be applied in cropland with or without treatment. There are many treatment options for manure, including anaerobic digestion, composting, lagoon,and drying, and the impacts of these methods on microbial population are relatively unknown at a large scale. In addition to manure treatment methods, both environmental and dairy farm specific factors influence the microbial communities in manure. Previous studies, rolling grow tables which have explored the microbial community in anaerobic digestion treatment of various waste including sludge, dairy manure, and slaughterhouse waste, indicated the presence of microbial communities of Bacteroidetes, Proteobacteria, Firmicutes, Chloroflexi, Spirochetes, Clostridia, and Synergistia.

Other studies reporting the microbial population of cow gut indicated the presence of various microbial communities including Spirochaetes, Flavobacteria, Sphingobacteria, Actinobacteria, Chloroflexi, Firmicutes, and Proteobacteria species. Of these, all studies dealing with animal waste-borne microbial pathogens indicated that animal waste may act as a reservoir of human pathogens, and it has a potential to contaminate ambient water resources and pose risk to public and animal health.The risk of microbial pollution caused by the application of manure fertilizer can be minimized by improving the existing understanding of microbial population in manure, and the effects of available treatment methods, which are in general used or recommended. This reconnaissance research based on our hypothesis proved that a relatively large microbial population persists in manure even after treatment. Regardless of composting, drying, solid-liquid separation, and lagoon, a diverse microbial population that includes pathogenic bacteria resides in manure, and the elimination of these microbial pathogens in manure requires further research. The ranking of top 15 species in FP and CP is shown in Table 1. In general, the abundance of bacteria for FP and CP was different than the abundance in FM, PL, and SL . As an example, the top right corner showed the high abundance of microbial communities mostly in CP and FP, and these microbial communities were less abundant in top left corner of heat map mostly showing FM, PL, and SL . Similarly, species such as Desulfobulbus, Bacteroidetes, Clostridiales, Clostridium, and Ruminococcaceae were more abundant in FM, PL, and SL than in CP and FP . A heat map displaying the bacterial community in liquid samples and solid samples and corresponding PCA plots are shown in supplementary figures . Considering that manure is abundantly used as fertilizer, we hypothesized that the methods of manure handling may have different impacts on microbial population in liquid manure.

We examined the top 15 microbial communities in liquid manure samples obtained from lagoons. Table 2 indicates the rankings of top 15 microbial communities in FM, PL, and SL samples. In PL, Bacteroidetes, Ruminococcaceae, and Cloacibacillus accounted 10.6%, 6.7%, and 4.5%, respectively. The unclassified bacteria in PL accounted 12.4%. Compared to PL, the three most abundant species in FM were Ruminococcaceae, Clostridium, and Flavobacteriaceae accounting for 8.9%, 5.1%, and 2.8%, respectively. The unaccounted bacteria in FM were 18.1%. The abundance of the top three species in SL samples was 9.8%, 7.6% and 2.6%, respectively. Moreover, the pathogenic bacteria of genus Clostridium persist in all three types of liquid samples . Compared to liquid manure samples, this population was not as dominant in solid manure samples. Solid manure, which was collected in this study, had been passed through either a compost or piling system. One plausible reason could be ascribed to the elevated temperature of manure piles. In general, the temperature profile of compost piles reaches to 55–60˚C, while the temperature of lagoon manure remains low . Considering our sampling strategy, which involves collecting samples from multiple dairies, certain differences in microbiota among solid and liquid samples are expected, and results are tabulated in Tables 1 and 2. The ranking of top 15 species in overall solid and liquid samples was developed, and results are shown in Table 3. The common species in solid and liquid samples include Flavobacteriaceae, Ruminococcaceae, and Pseudomonas. As asserted in our hypothesis, the level of microbial population in manure fertilizer changes with the mode of samples , which indicates that the treatment methods such as composting may have different impacts on manure in terms of microbial population compared to lagoon system. The results listed in Table 3 and Fig 5 prove our hypothesis to be true. Overall results showed that manure pile samples cluster together, while the flushed manure and lagoon samples cluster together.

Additionally, fresh solid samples cluster with the flush manure samples, indicating a certain degree of microbial commonality in untreated fresh liquid and solid samples. The distinct microbial communities in solid and liquid samples might be attributed to the varying effects of the anaerobic process in lagoon environment and composting process in the pile system. Interestingly, fresh piles and old piles did not show considerable differences in microbial communities, which suggest a need for further investigation to understand the effect of manure drying and composting on the change in microbial communities. In general, primary lagoon samples showed relatively high clustering. Secondary lagoon samples were less varied, which suggest that over time, microbial communities in lagoon environment develop similar profiles. Future studies focused on understanding the effect of manure retention time in lagoon microbial community and functional profile can provide additional insights needed for evaluating the microbiota of manure fertilizers. The results of this study suggest that the microbial diversity can potentially change during manure handling, and adapting suitable methods may influence cropland soil microbiota positively.Excessive application of dairy manure as fertilizer is considered to be a cause microbial pollution in ambient water. To understand the potential impact of dairy manure application as fertilizer in terms of microbial pollution and diversity, here we studied the microbiome of dairy manure under various treatment conditions. Analysis was performed on the flushed manure, solid manure, and manure of lagoon systems. The 16S rRNA-based microbial analysis demonstrated that a large, diverse bacterial population inhabits the manure and changes with manure treatments. Results showed a considerable difference in population among microbiomes of liquid and solid manure. The microbiomes of primary and secondary lagoon manure were comparable. The microbial populations of fresh manure piles and old manure piles were similar, which might be attributable to a lesser impact of composting and drying under the studied conditions. The considerable differences among microbiomes of liquid and solid samples indicate that the application of solid manure as fertilizer may have different impacts on cropland in terms of microbial population compared to when liquid manure is applied as fertilizer.This thesis deals with two important trends in the U.S. dairy industry: 1) increases in farm size, and 2) the increases in prevalence of female dairy farm operators. This research explores detailed data on farm size changes in major U.S. dairy states and document consolidation and other trends in the patterns of dairy farm size distributions. The dairy industry is of interest, not only because it is an important industry measured by production value, flood drain table but also because of its environmental and social importance. Declines in the number of dairies have raised concerns based on their impact on rural communities, particularly movement of dairies out of local regions and, the potential fall in local employment opportunities. New data on farm operator characteristics allow us to better analyze the trends of gender demographics and the influence of operators’ ages relative to farm size. There has been very little economic research related to the increasing role of female operators in the dairy industry. Trends toward more women operators and fewer dairy farms suggests correlations between the role of women in the dairy industry and herd size per farm and other farm characteristics. Looking overall at U.S. trend in operations with milk cows, Figure 1.1 shows that since 1982, the number of operations with milk cows has decreased rapidly and the average number of milk cows per farm has increased. This graph describes a trend of consolidation in the dairy industry, as defined as operations with milk cows. Despite the slight decrease in number of milk cows there has been an increase in the U.S. milk production . These changes characterize the consolidation within the dairy industry.These national trends mask large differences by state. Some states, such as California, has seen growth of herd sizes into the range of 2,000 or more milk cows per farm. Other states, such as Wisconsin have experienced equally rapid increases in herd size per farm in percentage terms, but herd sizes of larger farms in Wisconsin are in the range of 500 cows per farm. Consolidation is common in other farm industries. An important contribution of this thesis is to document and characterizes this trend over time for an important industry, which is of significance to agricultural economic research.

Consolidation may have allowed dairies to capture improved productivity and efficiency on the farm. How dairy farm size changes in response to these and other factors are important in considering future trends in farm size and their impact on milk production in the United States. My research seeks to help explain recent patterns of farm size change in the dairy industry, considering trends in operator characteristics and management, while accounting for regional differences. The share of women dairy farmers has increased. Historically, farming has been a stereotypically male occupation. Despite contributing to farm production and farm management, surveys, and censuses, have been limited in their collection of data on the contributions of women as farm operators. I hypothesize that some of growth in female contribution to farm operation is due to changes in social and gender norms in reporting. One contribution of my research is to attempt to separate, to the extent possible, changes in management and operations on dairy farms from how such activities are reported. Demographic trends in farm operation and management are important because they help researchers and policy makers get a better sense of who runs the operations in an industry by age, gender, and other characteristics. The dairy industry remains predominately male. However, since 2002, there has been a substantial increase in the share of women dairy farm operators and an increase in the absolute number of dairy farms with at least one female operator in many places. The share of commercial dairies with at least one female core operator has increased across all states, except New Mexico. New York saw the largest increase in the share of commercial dairies with at least one female core operator from 36% to 55%. California saw a 40% increase in the share of commercial dairies with at least one female core operator. This trend, which has occurred while dairy farm consolidation has proceeded at a similar pace suggests that the participation of female dairy farm operators may positively affect dairy farm herd size and economic viability.As noted in the previous chapter, for the statistical estimation in the thesis I will utilize data for the USDA COA. Under “Census of Agriculture Act of 1997”, The COA is a federally mandated Census of all U.S. farms and ranches every five years, and it captures individual farm-level data on production costs, operators’ characteristics, land use, number of milk cows, revenue, etc. The data and statistics resulting from this Census are reported at the county or state level and research using the individual level data is restricted to USDA research or special request for non-USDA entities. I was given special permission to have access to individual farm-level data for census years of 2002, 2007, 2012, and 2017 from the following specified states: California, Idaho, New Mexico, New York, Texas, and Wisconsin.

As shown in this gives a good combination of accuracy and efficiency for this problem class. Having a well-designed boundary-layer mesh in wind-turbine simulations is critical for achieving engineering accuracy with a reasonable number of degrees of freedom. During operation, wind turbine blades undergo large global rotational motions, as well as local flap wise and edgewise bending, and axial torsion deformations. As a result, in order to account for the blade motion and to simultaneously maintain good-quality boundary-layer discretization, a moving-mesh technique should be employed where the boundary-layer mesh follows the blades as they moves through space. In the case of standalone wind-turbine-rotor FSI computations this may be accomplished by applying a global rotation to the entire aerodynamics mesh, and handling the remaining blade deflection using elastic mesh moving as in [18]. A jacobian-based stiffening technique in elastic mesh moving is essential for maintaining the integrity of the elements in the blade boundary layers. In the case a full machine is considered, the spinning rotor interacts with the tower. This interaction is strong and needs to be modeled explicitly. In the recent wind-turbine FSI computations presented in the wind-turbine hub was assumed to spin with a fixed, prescribed angular velocity, and the tower was assumed to be stationary. The aerodynamics of rotor-tower interaction was handled using a sliding-interface technique. In this technique, 2×4 flood tray rather than rotating the entire computational domain, only the inner cylindrical subdomain that encloses the rotor undergoes a spinning motion inside the cylindrical cut-out of the outer stationary domain. The two domains do not overlap, and, as a result, create a sliding cylindrical interface with a priori non-matching discretizations on each side.

The continuity of the kinematic and traction variables across the non-matching sliding interface is enforced weakly.In order to simulate more complicated FSI scenarios, such as rotor yawing for HAWTs, or even basic operation for VAWTs, additional computational technology is required. In the case of HAWT rotor yawing motion, the entire gearbox undergoes rotation parallel to the tower axis, and this rotation must be transferred to the rotor and hub without interfering with the rotor spinning motion. In the case of basic VAWT operation, the air flow spins the rotor, which is connected to a flexible tower with struts. Furthermore, the moving-mesh aerodynamics formulation for this expanded problem class can no longer have a fixed sliding interface. For example, in the case of the rotor yawing motion, in order to keep the good quality of the aerodynamics mesh and prevent the rotor blades from crossing the boundary of the rotor cylindrical domain, it is preferred that the sliding interface follows the motion of the gearbox, while accommodating the spinning rotor. This results in two cylindrical surfaces moving together while one spins inside the other. Another challenge in FSI simulations is to model the geometrically complex structures with its nonlinear material distribution, which undergoes large deformation. A combination of a rotation-free multilayer composite Kirchhoff–Love shell and beam allows for the rotor to spin freely and for the tower and blades to undergo elastic deformations. An isogeometric analysis with NURBS based elements representation is used to construct analysis-suitable geometry. The NURBS-based IGA may be seen as a combination of CAD basis functions and the isoparametric concept and may be extended to T-splines and subdivision surfaces. Because of the rational nature of the basis functions the circular shapes can be represented exactly which reduce the geometrical-approximation error when modeling complex-shaped wind turbine blades.

Furthermore, the higher order continuity is achieved with NURBS basis functions and the geometry is preserved unchanged under the mesh refinement process, which is not the case in FEM. The dissertation is outlined as follows. In Chapter 2 we state the ALE-VMS formulation of aerodynamics in combination with our sliding interface approach for the simulation of mechanical components in relative motion. To validate our aerodynamic formulation we show the computations of a small-scale Darrieus-type wind turbines. One is a 3.5 kW wind turbine tested in NRC wind tunnel. For this turbine two cases were simulated: A single turbine, and two counter-rotating turbines placed side-by-side in close proximity to one another. For a single turbine a mesh refinement study was performed, and results were compared to experimental data. Another turbine is designed by Windspire with rated power of 1.2 kW. For this case the computational results were compared to a field test experiments conducted by the National Renewable Energy Lab and Caltech Field Laboratory for Optimized Wind Energy. In Chapter 3 we present the coupled Kirchhoff–Love shell for an arbitrary composite layup of wind turbine blades. To verify the model we perform the eigen frequency analysis of recently designed offshore wind turbine blade and CX-100 blade, which compare favorably to the experimental data. In Chapter 4 we introduce the coupled FSI formulation employed in this work with non matching discretization of the aerodynamic and structural domains. Later in the chapter we present FSI computations of the Micon 65/13M wind turbine. Both the aerodynamics and FSI torque results fall within the range predicted by the field tests for this wind turbine. The FSI case shows high-frequency fluctuations in the aerodynamic torque, which are due to the high-frequency vibration of the blades. Next, the FSI computations of offshore HAWT under yawing motion is presented and the discretization techniques employed and the aforementioned enhancement of the sliding-interface formulation are described.

We conclude with the FSI computations of the Windspire VAWT and discuss start-up issues. In Chapter 5 we draw conclusions and discuss possible future research directions.The aerodynamics simulations are performed for a three-blade, high-solidity VAWT with the rated power of 3.5 kW. The prototype is a Darrieus H-type turbine designed by Cleanfield Energy Corporation. Full-scale tests for this turbine were conducted in the National Research Council low-speed wind tunnel at McMaster University . Experimental studies for this turbine focused on the application of VAWTs in urban areas. The turbine has a tower height of 7 m. The blades, 3 m in height, are connected to the tower by the struts of length 1.25 m. This value is taken as the rotor radius. A symmetric NACA0015 airfoil profile with chord length of 0.4 m is employed along the entire length of the blades. See Figure 2.1 for an illustration. The computations were carried out for constant inflow wind speed of 10 m/s, and constant, fixed rotor speed of 115 rpm. This set up corresponds to the tip speed ration of 1.5, which gave maximum rotor power as reported in [32,58]. However, it was also reported for the wind tunnel tests that the control mechanism employed was able to maintain an average rotor speed of 115 rpm with the deviation of ±2.5 rpm. This means the actual rotor speed was never constant. The air density and viscosity are set to 1.23 kg/m3 and 1.78 × 10−5 kg/, respectively. On the inflow, flood and drain table the wind speed of 10 m/s is prescribed. On the top, bottom and side surfaces of the stationary domain no-penetration boundary conditions are prescribed, while zero traction boundary condition is set on the outflow. No-slip boundary conditions are imposed weakly on the rotor blades and tower. The struts are not modeled in this work to reduce computational cost. The struts are not expected to significantly influence the results for this VAWT design. The computations were carried out in a parallel computing environment. The meshes, which consist of linear triangular prisms in the boundary layers and linear tetrahedra elsewhere, are partitioned into subdomains using METIS, and each subdomain is assigned to a compute core. The parallel implementation of the methodology may be found in [80]. The time step is set to 1.0 × 10−5 s for all cases.We first compute a single VAWT and assess the resolution demands for this class of problems. The stationary domain has the outer dimensions of 50 m, 20 m, and 30 m in the stream-wise, vertical, and span-wise directions, respectively. The VAWT centerline is located 15 m from the inflow and side boundaries. The radius and height of the spinning cylinder are both 4 m. Three meshes are used with increasing levels of refinement. The overall mesh statistics are summarized in Table 2.1. The finest mesh has over 17M elements. The details of the boundary-layer discretization are as follows. For Mesh 1, the size of the first element in the wall-normal direction is 0.000667 m, and 15 layers of prismatic elements were generated with a growth ratio of 1.15.

For Mesh 2, the size of the first element in the wall-normal direction is 0.000470 m, and 21 layers of prismatic elements were generated with a growth ratio of 1.1. For Mesh 3, the size of the first element in the wall-normal direction is 0.000333 m, and 30 layers of prismatic elements were generated with a growth ratio of 1.05. Figure 2.14 shows a 2D slice of Mesh 2, focusing on the boundary-layer discretization of the blade.Time history of the computed aerodynamic torque is plotted in Figure 2.5 together with the experimental value reported for these operating conditions. Only the mean value of the torque was reported in [32, 58]. Note that after a couple of cycles a nearly periodic solution is attained. Mesh 1 predicts the average torque of about 52 Nm, Mesh 2 gives the average torque of about 70 Nm, and Mesh 3 predicts the average torque of about 80 Nm, while the targeted experimental value is about 90 Nm. Looking further at the curves we observe that the largest differences between the predicted values of the torque between the meshes occur at the maxima and minima of the curves. Also note that the torque fluctuation during the cycle is nearly 200 Nm, which is over twice the average. One way to mitigate such high torque variations is to allow variable rotor speed.Figure 2.6 shows a snapshot of vorticity colored by flow speed. The upstream blade generates tip vortices near its top and bottom sections. Note that no large vortices are present in the middle section of the blade. There, as the flow separates on the airfoil surface, larger vortices immediately break up into fine-grained trailing-edge turbulence. The tip vortex and trailing-edge turbulence are then convected with the ambient windvelocity, and impact the tower, as well as the blade that happens to be in the downwind position in the spin cycle. However, as it is evident from the torque time histories shown in Figure 2.5, these do not produce a major impact on the rotor loads, at least for a chosen set of wind and rotor speeds. The situation may, of course, change for a different set of operating conditions.Here we investigate two counter-rotating turbines placed side-by-side in close proximity to one another. The wind and rotor speeds are the same as before, however, the turbines rotate out of phase, with the difference of 60◦ . The distance between the towers of the two turbines is 2.64R, where R =1.25 m is the rotor radius. This distance between the turbines falls in the range investigated in the experimental work of [1].The stationary domain has the outer dimensions of 50 m, 20 m, and 33.3 m in the stream-wise, vertical, and span-wise directions, respectively. The centerline of each VAWT is located 15 m from the inflow and 15 m from its closest side boundary. The radius and height of the spinning cylinders are 1.45 m and 4 m, respectively. A 2D slice of the computational-domain mesh focusing on the two rotors is shown in Figure 2.7. The boundary layer discretization employed for this computation is the same as that of Mesh 2 in the previous section.Figure 2.8 shows the time history of the aerodynamic torque for the two-turbine case. The time history of the torque for a single VAWT simulation is shown for comparison. Note that while the maxima of all curves are virtually coincident, the minima are lower for the case of multiple turbines. Also note that the multiple-turbine torque curves exhibit some fluctuation near their minima, while the single-turbine torque curve is smooth near its minima.

SAMMIE CAD provides a 3-D environment and full control of human mockups, which makes it possible to evaluate those complex interactions. The simulations performed in SAMMIECAD consisted of: creating 3-D human mockups; creating 3-D ATV mockups; and integrating and in the virtual environment to simulate their interaction. For each simulation, the correct reach posture was achieved by positioning the human limbs according to the specific task’s requirement. For example, a seated position was adopted when evaluating fit criterion 10 , as shown in Fig. 3a. On the other hand, a standing straddling posture was selected when evaluating fit criterion 4 , as shown in Fig. 3b. Some criteria involve the youth reaching a specific control . The feature ‘‘Reach” under the ‘‘Human” menu on SAMMIE CAD was used to evaluate the ability of the youth mockups to reach the selected controls. The ‘‘Reach” was set as ‘‘Absolute,” and ‘‘Object Point” was set as ‘‘Control.” When the selected control could be successfully reached, the software would display an animation of the human limb reaching the desired object . On the other hand, if the control was out of reach, SAMMIE CAD would show an error window and display the required distance for the human limb to reach the desired control . Simulations involving buttons and levers were performed with the fingertip of the index finger or the thumb, accordingly. All controls on the right side of the ATV were simulated with the right hand/foot, and all controls on the left side of the ATV were simulated with the left hand/foot.

Specific controls that required using both hands, such as the handlebars, seedling starter trays were simulated with both hands. Criteria 1, 2, 3, and 11 were evaluated through Matlab because their assessment required the computation of simpler calculations, such as the distance between the rider’s knee and the ATV’s handlebars. Matlab also provided the ability to automate the calculations for a more efficient data analysis. A code was generated based on conditional statements to assess whether riders’ anthropometric measures conformed to the constraints imposed by the ATV design. For instance, when evaluating criterion 1, the distance between the ATV footrests and the handlebars minus the rider’s knee height must be greater than 200 mm . For each reach criterion, riders received a binary score . Riders with a total score of 11 were classified as ‘‘capable of riding the ATV.” On the other hand, riders with a total score below 11 were classified as ‘‘not capable of riding the ATV.”In order to validate the results of the virtual simulations, an experiment including three adults and one study ATV was carried out. Each subject had completed an ATV safety riding course prior to the experiment and was awarded a certificate from the ATV Safety Institute . The capability of the subjects to fulfill each fit criterion was evaluated and recorded. For the field tests, a measuring tape graduated in mm was used to measure distances and a digital angle finder to measure angles. To assist in some of the angle measurements, a straight edge 4800 ruler and a mag-netic level were used. The anthropometric measures of the subjects were taken with a body-measuring tape and then used as input in SAMMIE CAD to create 3-D mockups.

The results observed in the experimental setting were then compared to those observed in the virtual simulations through the Cohen’s Kappa coefficient , which is a statistic widely used to measure inter-rater reliability for qualitative items . A Z-test was performed to evaluate whether the value of K was statistically different than zero, which would imply that the virtual simulations are reasonable.Seventeen ATV models were evaluated from eight different manufacturers. Engine capacity ranged from 174-686 cc, with most vehicles in 100–400 cc . Moreover, 58 % of the ATVs evaluated included electric power steering , 4 wheel-drive , solid suspension , and manual transmission . Findings of individual reach criteria for the ATV models are presented in Tables 2 and 3, for males and females, respectively. The last column of those tables represents the percent of observations for which riders scored 11 points . Criterion 1 seemed difficult for 16-year-old-males of the 95th body-size percentile. This result may be attributed to the height of these subjects, which decreases the gap between their knee and the handlebars .Unlike criterion 1, criterion 2 did not present any difficulty for the virtual youth . Indeed, virtual subjects of all ages, body-size percentiles, and genders succeeded in this criterion for all evaluated vehicles. Criteria 3, 4, 6, 7, 8, 9, 10, and 11 all presented a similar trend where young riders do not conform well to these criteria, but older riders do . The contrast in success rate among subjects of different ages and height percentiles are likely also attributed to the variations in height among the subjects. For example, virtual 8-year-old-female riders of the 95th percentile did not pass criterion 5 for any of the evaluated ATVs. In contrast, their 16-yearold-counterpart passed the same criterion for 75 % of the evaluated ATVs , a surprising difference of 75 %. The results from Tables 2 and 3 indicate that 8-year-old youth would probably not be able to control utility vehicles when traversing rough or uneven terrains . This finding likely explains the fact that youth are more subject to loss of control events than adults .

The results of the simulations related to Criterion 7 indicated that youth 9 years old and younger are more likely to lean forward over 30 when raised off the seat to reach the handlebars of agricultural ATVs. As a result, the center of gravity of the ATV can shift forward, thus increasing the chances of a tip over. Lastly, some results of the simulations related to Criterion 5 were concerning. Males up to 11 years old and females up to 13 of the 50th percentile passed this criterion for less than 50 % of the evaluated ATVs.The percent of ATVs in which riders passed all criteria is presented in Fig. 4. The main finding is that certain youth should not ride most utility ATVs. For instance, the average male operator aged 16 passed all 11 safety criteria for less than 60 % of the evaluated vehicles. That number decreases sharply for younger youth or youth of the same age but smaller height percentile. A similar trend was also observed for female operators.The results of the validation tests are presented in Table 4 and summarized in a confusion matrix . In the confusion matrix, the outcome of the test is labeled in both horizontal and vertical axes. The horizontal axis represents the number of outcomes predicted by the virtual simulations, and the vertical axis represents the ground truth data . The results of the virtual simulations were very close to those of the field tests, with a total accuracy of 88 %. The Z-test determined that the Cohen’s Kappa coefficient was significantly greater than zero , botanicare trays indicating that the virtual simulations are reasonable. This approach to evaluate ergonomic inconsistencies between youth’s anthropometry and the operational requirements of ATVs proved to be an effective and accurate technique. Not all results of the virtual simulations matched those of the field tests. One unexpected result is related to criterion 6 . It was observed that the mean angle between the riders’ upper leg and the horizontal plane was 16.7 , slightly above the recommended threshold . Similarly, two subjects failed to pass criterion 5 in the actual field tests but passed it in the virtual simulation. During the field tests, riders were asked to sit comfortably as if they were just about to start riding the ATV. We argue that it would be possible for riders to adjust their way of sitting so they would pass both fit criteria; however, it would not result in the most ergonomic posture from the rider’s standpoint. On the other hand, in the virtual simulations, our ultimate goal was to place the 3-D subjects’ mockups to physically conform to the proposed fit criteria. Thus, it was impossible to predict whether the final adopted postures in the simulations would match those selected by the riders in the validation tests. Therefore, we argue that despite some outcomes of the virtual simulations did not match those of the field tests, the results of the virtual simulations are still reasonable. One just has to be cognizant that the outcomes of the virtual simulations represent a hypothetical scenario where the rider is able to attain a posture based on their anthropometric measures relative to the ATV, not on their preferences.

This study evaluated limitations in youth’s anthropometric dimensions when riding commonly used ATVs. Using a combination of actual field measurements and a novel digital simulation approach, the present study evaluated 11 ATV fit criteria for youth. The major finding was that youth are not recommended to ride adult-sized ATV models, which is a common practice in the United States , 2010; Jennissen et al., 2014. This finding raises serious concern regarding youth’s ability to ride ATVs, especially when unsupervised.The present findings outlined that some youth are too small, which makes them incapable of properly reaching the vehicle’s hand/foot brakes, resting their feet on the footrests, or having to lean forward beyond 30 to reach the handlebars when rising off the seat. Failing to activate the ATV brakes limits the youth’s ability to reduce the speed or to stop the vehicle, which likely prevents them from avoiding unexpected hazards, such as obstacles or bystanders . In fact, previous research has shown that a significant number of ATV incidents include hitting a stationary object . In addition, the inability to place the feet on the footrests when not breaking the ATV entails a functional loss of control of the vehicle. ATV LCEs occur frequently and are a significant cause of injury and death in agriculture . This finding indicates an opportunity for manufacturers to consider changing the design of their machines, allowing riders to adjust the ATV’s seat height, which would likely reduce longitudinal torso impact while traversing rough and uneven terrains. Furthermore, leaning beyond 30 can cause the ATV to tip forward, resulting in a rollover. Most ATV-related crashes on farms and ranches, especially those resulting in deaths, involve rollovers . On the other hand, some youth are too tall, which decreases the clearance zone between their legs and the handlebars. A clearance zone smaller than 200 mm makes it difficult for the rider to properly reach and steer the handlebars . Consequently, riders may lose control of the vehicle or have difficulty keeping it at a safe speed. As mentioned before, these series of events can lead to injuries and deaths.Furthermore, despite some results showing that youth are capable of riding many of the ATVs evaluated in this study, other risk factors such as experience, psychological, and cognitive development cannot be overlooked . Youth who are high in thrill-seeking are more likely to engage in risky ATV riding behaviors, regardless of their safety awareness . Those cases require external interventions, such as changes in legislation, improved ATV design, and use of crush protection devices .The results of this validation experiment showed that some riders failed criteria 5 and 6 even though they seemed able to operate the study vehicle comfortably and safely according to our ATV safety research team. Particularly, subjects 1, 2 and 3 presented elbow angles of 129 , 170 and 172.5 , respectively. While fit criterion 5 recommends an elbow angle between 90 and 135 , it is not uncommon to see motorcycle riders reporting comfortable elbow angle values up to 168 . Moreover, subjects 1, 2, and 3 presented upper leg angles of 14 , 14.7 , and 21.4 , respectively . A previous survey regarding motorcycle riders’ perceived comfortable posture reported optimum upper leg angles as high as 23 . It is our understanding that fit guidelines 5 and 6 are rather conservative, and their proposed thresholds may rule out riders that are perfectly able to ride utility ATVs safely and comfortably. As such, we propose some modifications to those fit guidelines. First, we recommend that the rider’s elbow angle should be between 90 and 170 as long as the rider feels comfortable steering the handlebars and is able to pass fit criteria 8 and 11 .

All Cannabis germplasm is completely interfertile, suggesting that the genus consists of a single species, with two subspecies and subsp. indica . Through DNA analysis, evidence pointed towards C. sativa, C. indica, C. ruderalis populations of Cannabis as being distinct subspecies of Cannabis sativa . Common vernacular terms, sativa and indica, have been used to describe different types of marijuana, causing much confusion for consumers who believe that these different forms of Cannabis happen to function in different ways. Generally, sativa types are plants with tall and slender morphology, narrow leaflets, and late maturation while indica types have shortened stature, broad leaflets, and early maturation . Whatever true population differences there may have been between indica and sativa types of C. sativa subsp. indica have become lost over generations of repeated hybridization events , although clearer population differentiation between hemp and marijuana still exist . Thus, industrial hemp is simply classified taxonomically as Cannabis sativa L. with low amounts of THC . One way to classify genotypes or populations of C. sativa is through their chemotypes, or chemical phenotypes, based on the predominant cannabinoids in the plant, in particular, cannabidiol , cannabigerol , and tetrahydrocannabinol . C. sativa is divided into five different chemotypes: THC dominant, referred to as the drug-type, CBD dominant, referred to as fiber-type, and one which THC and CBD are present in equal proportion. Two other chemotypes, CBG dominant and those which contain low concentrations of cannabinoids, are less frequently used in scientific literature . The classification of C. sativa germplasm with chemotypes enables scientists to easily classify individuals for breeding for certain uses like pharmacology, fiber, or seed . Cannabis sativa L. is a dioecious plant with individuals from the male and female sexes having distinct morphological differences .

Male individuals are described as slenderer in stature than their female counterparts and have less reproductive biomass compared to a females’ dense inflorescence . Differences in morphology, how to cure cannabis specifically between the sexes of hemp plants, only become apparent after the seedling stage . The genetic basis for sex in Cannabis is determined by the inheritance of either an X or Y chromosome from the male parent. Female plants have a sticky inflorescence that captures wind-dispersed pollen from male plants . Male flowers, within their hanging panicles, have a perianth of five sepals that surround the androecium; the anthers at maturity split lengthwise, releasing the pollen grains . Female flowers develop as thick clusters called racemes, and receive the pollen grains through insect, wind, or mechanical dispersion onto the pistils. In production settings, formation of seeds is undesirable if the use of hemp is the extraction of essential oils or the sale of the flowers themselves; consequently, most hemp producers prefer to grow only female individuals and avoid fertilization from male plants . Grandular trichomes, a form of sessile trichomes, cover the surface of female flowering tissues and produce cannabinoid oils . The secreted oils which burst from these trichome sacs coat the surface with a sticky resin, which results in flowers that are waxy in texture . Cannabinoids likely serve multiple purposes within the Cannabis plant, such as a defense response against herbivory from insects and the dissipation of heat stress in the environment. Cannabinoids are produced in substantially higher quantities when exposed to UV-B radiation , suggesting they act as a barrier against the damaging effects of UV-B radiation .

There are over 180 different cannabinoids present in C. sativa, with the primary cannabinoids being THC, also called Δ9-THC, CBD, and CBC . These cannabinoids coexist along with their acid-precursors: tetrahydrocannabinolic acid , cannabidiolic acid , and cannabichromenic acid . The acid forms of these cannabinoids change into their decarboxylated forms primarily from the application of lightand/or heat onto the harvested crop, but the decarboxylated forms still exist at certain levels within the flowering tissue before harvesting . All acid forms of cannabinoids come from a primary precursor phytocannabinoid called cannabigerolic acid . CBGA is a product of two metabolites, olivetolic acid and geranyl diphosphate, which are formed from the polyketide pathway and plastidial deoxyxylulose phosphate/methyl-erythritol phosphate pathway , respectively . Cannabinoids have been used as a component of human therapeutic medicine for thousands of years . Specific cannabinoids have been used to minimize chronic pain, improve sleep quality, and treat a wide variety of other ailments. C. sativa has obtained more attention over the last 30 years as a source of medicine in America after California passed the Compassionate Use Act of 1996, a bill which allowed the state to provide patients with access to medical marijuana “in the treatment of cancer, anorexia, AIDS, chronic pain, spasticity, glaucoma, arthritis, migraine, or any other illness for which marijuana provides relief” . Since then, there has been increasing interest in the use of cannabinoids as a way of minimizing pain, a malady affecting 1 in 5 Americans on a daily basis . CBD is of particular interest because it can provide pain relief without the psychoactive effects that come with other cannabinoids like THC .

The global value of CBD products is 2.8 billion dollars as of 2020 and is expected to increase on the order of 20-23% year-to-year over the next five years . In America, Cannabis was a widely grown crop for many years during the 18th and 19th centuries before being replaced by cotton as the predominant crop used for textiles . With increased interest in the crop medically for its oils, it has also renewed interest in its fiber , oil, and seed . Hemp bast, the long fibers from the outer stem of hemp, can be used to make carpets, shoes, diapers, insulation, yarn, composite materials, and plastics . The hurd, or inner core fibers of the hemp plant, can be used to create hempcrete, animal bedding, potting mix, and soil amendments . With a wide variety of uses, industrial hemp fibers, as of 2019, have a current market value of $4.46 billion with an expected compound annual growth rate of 33% through 2027 to total $43.8 billion . With the value of industrial hemp between its fiber and CBD products currently being valued at over $7.2 billion, there is increasing interest in agronomic improvements for the crop. Hemp is typically grown in field settings but can be grown in greenhouses when growers are focusing on greater pest control, year-round growth, and control of lighting regiment. In field settings, hemp generally is grown on well-drained soil which is high in fertility . Planting density varies among varieties and the grower’s intended use for the crop. Hemp grown for oil extraction requires wider spacing to promote branching and flower development; planting densities for the purpose of harvesting its fiber is typically double that of oil seed varieties, however, in general the architecture of the plant itself is strongly associated with the density of planting, nutritionally availability within the soil, and the length of day that the plant is exposed too during its life cycle . Hemp is either planted by direct seeding or through the transplantation of seedlings or clones . When hemp is grown for medicinal oil extraction, the field typically consists of only female plants. Usually this is accomplished by using “feminized” seed, which is produced from female plants that have been induced to produce male gametes and seed using either chemical or environmental stress which results in seeds which will produce seeds which result mostly in female plants . This process of masculizing female hemp plants on an industrial scale is done through foliar applications of silver thiosulfate . The rationale for producing feminized seeds, outside of maintaining genetically identical inbred lines for commercial sale, is to minimize the production of seeds within the flowering tissue of female plants due to consumer, grower, and processor preferences. Hemp improvement can be done through the use of phenotypic recurrent selection, aka mass-selection, by selecting the best individual plants based on field performance and using their seed for the next evaluation cycle . Once an elite variety has been developed, back crossing can be used to incorporate new traits from undesirable germplasm . For traits such as fiber quantity and quality, with high trait heritability, trimming cannabis mass-selection can work well . Other breeding practices have been employed for the purpose of either increasing variation, specifically when crossbreeding individuals, or for fixing a trait through inbreeding to produce inbred lines and/or to capitalize on heterosis of F1 hybrid cultivars .Advances in biotechnology can accelerate the incorporation of a trait into an existing population with high accuracy and speed using next generation sequencing and marker assisted selection .

Marker assisted selection works to track the phenotype of an individual plant by associating genetic polymorphisms with trait variation, enabling selection on seedling plants without having to grow the individual to maturity . Recent advances in sequencing technology, specifically with the development of next-generation sequencing , has reduced the price of sequencing whole genomes of individual plants , making marker identification and use more tractable. Day neutrality is a trait which is present in many agricultural crops such as soybeans, wheat, barley, rice, tomatoes, strawberries, and alfalfa . Several genes involved light sensing contribute to differences among genotypes in time of flower and in day neutrality; the major genes appear to be conserved across species. For instance, day-neutrality is controlled by CONSTANS , a gene which encodes a transcription factor involved in the transduction of light signals, promoting the expression of other genes downstream . The genetic basis for the change from vegetative growth to flowering within hemp cultivars is mostly unknown. Petit et al. , identified six QTLs related to genes which control the perception and transduction of light and their associated transcription factors. However, hemp germplasm has a wide range of flowering times, affected by both genetics and the environment . Hemp, Cannabis sativa L. is a valuable medicinal, fiber, seed, and oil crop. Understanding and manipulating the flowering time of hemp could facilitate cultivar development for diverse environments and cropping systems. The time at which hemp transitions from vegetative growth to flowering is critical for the development and quality of the final harvested product. Most hemp germplasm requires short days to begin flowering and producing seed, oil, and cannabinoid products . Before the transition to flowering can occur, a period of vegetative growth stage controlled by the accumulation of thermal time in the environment is necessary . Vegetative growth for hemp is optimal around 30o C and continues to a maximum temperature about 42o C. Around 300 to 600 units of cumulated thermal time over 1o C must occur for the plant to be able to initiate flowering if the critical daylength is reached . While typically a short-day plant, hemp germplasm has considerable variation in TOF . Some hemp germplasm has day-neutral flowering, which means that regardless of photoperiod, they will flower after a certain amount of thermal time has accumulated . Day-neutral Cannabis varieties can go from seed to flowering in a soon as four weeks, and some varieties can be harvested within 100 days after seeding. The trait for day-neutrality originated from the ruderalis variety of Cannabis sativa in parts of Southern Russia. These plants are described as being short and stalkyin nature, while producing small amounts of flower with low concentrations of THC . Despite its undesirable attributes, ruderalis has been used to introgress day neutrality into high yielding flower and oil varieties. The day neutral trait can provide significant agronomic benefits by standardizing harvest time and potentially enabling growers to have more harvest cycles in one year compared to those growing day-sensitive varieties of hemp which takes much longer to flower in most environments. The genetic basis for day neutrality, specifically in hemp, is currently unknown. We hypothesized that at least one major locus controls day neutral flowering with multiple minor loci affecting the variation in time to flower within day neutral or daylength sensitive germplasm. To test this hypothesis, we hybridized day neutral and daylength sensitive accessions of hemp and evaluated the progeny for flowering time across three field trials over two years in order and genotyped them using next generation sequencing technology to identify genetic loci involved in flowering time. Hemp seeds were placed into 72-cell flats containing potting soil mix, composed of mostly perlite, and were then covered in vermiculite and watered daily.

The remote and rugged terrain that once attracted illicit cultivation attempting to avoid detection may now hinder the ability of farms in these areas to comply with environmental regulatory standards and ultimately become licensed. Multiple environmental permits may be required in order to obtain a CDFA cultivation license if growing outdoors or in greenhouses, and the fees and information requirements may represent significant hurdles to some farmers . Initial evidence indicates the first wave of regulated, industrial scale cannabis has largely begun not in the historical epicenter of Northern California, but in the hills and isolated valleys of the Central Coast. Although select counties in the Central Valley have allowed a token number of large cannabis farms , licenses for farms of equivalent size have been issued en masse in counties such as Santa Barbara and Monterey . In these areas, it is not yet clear if large-scale cannabis farms will more commonly repurpose existing infrastructure or stake out new territory further from existing agriculture and closer to natural spaces. Understanding the potential environmental impacts of industrialized cannabis requires knowing where and why extensification or intensification occurs, patterns of natural resource use, and how these dynamics relate to regulatory mandates. For example, regarding the issue of water, the legacy of illegal cannabis cultivation sites and their tendency to divert from streams and springs has led to these sources of water becoming tightly regulated within the legal cannabis industry. In particular, air racking extraction from these sources is prohibited during the growing season and farms that rely on them must either instead collect and store this water in the off season or use an alternative source.

For the majority of regulated cannabis farms, the choice has been to use well water and this is already the most common source for irrigation . Given the hurdle of developing sufficient storage, especially at increasingly larger farm sizes, the use of wells will likely increase in frequency . While the story of groundwater depletion in California is common knowledge , the use of wells by commercial cannabis farms is fundamentally different, given their tendency to occur outside of large aquifer basins . Such wells that are located instead adjacent to watercourses, in small alluvial aquifers, or fractured bedrock have potential to reduce crucial stream flow during the summer months , although this topic is currently understudied and generally beyond the purview of current California groundwater policy . This is a concern not only for large-scale farms in the new frontier of the Central Coast, but also for farms on the North Coast that must compete with these operations. The prospect of farms on the North Coast increasing in size to compete and shifting to groundwater extraction to comply has latent environmental implications, deserving further research. Characterized by geographically isolated, small farms, the informal cannabis cultivation sector represented a form of agriculture distinct from California’s consolidated, credit-supported industrial model. The historic legacy of the cannabis industry in Northern California has differentiated this region and led to worldwide recognition of its products. However, remoteness has now isolated traditional cultivation regions from an emerging legal supply chain and new markets, while obligating farms to navigate high regulatory costs associated with operating in environmentally sensitive locations.

How farmers in these remote watersheds respond holds importance for the future of the cannabis industry and its socio-environmental dynamics. Formation of grower cooperatives , appellation systems , caps on farm size and license consolidation , or a return to medical provisioning collectives may provide tools to overcome steep start-up and licensing costs for small farmers. Due to ongoing federal prohibition, farmers do not have access to traditional supports such as bank loans or crop insurance and instead must rely on private capital, limiting engagement in legal markets by many smaller farmers. Paradoxically, if barriers to capital are reduced, it may invite institutional investment and accelerate further industrial consolidation and up-scaling. More research is needed to understand the socio-ecological dynamics that underpin changes in cannabis cultivation in California and beyond. California’s statewide legalization opens some research pathways through regulatory databases, harmonization among institutions and jurisdictions, and new funding mechanisms. Yet, federal prohibition still creates a “quasi-legal challenge” for robust research , with consequences for effective policy-making and environmental health . Federal prohibition can inhibit institutional funding , discourage participation of informants in studies , lead to suspicion of researchers by potential study participants , create difficulty for Institutional Review Boards and researchers to estimate and mitigate risks for human subjects, and create asymmetries in data collection and knowledge types. High numbers of producers operating outside of regulatory systems impede the ability for comprehensive and representative studies and projects limited to only “compliant” producers cannot account for the total socio-ecological dynamics of cultivation.

With a lack of robust research, resulting policies cannot be driven by direct research on cannabis, may impair social equity in the transition of informal producers to formal markets , and complicate implementation of strategies to govern common environmental resources . Further, policies that incentivize industrial consolidation and eliminate small producers may have environmental consequences . Among cannabis producers, decisions about production can alter ecological and hydrological conditions, requiring attention not just to stream flows, pest management, indicator species, and wildlife movement patterns, but also to the social calculus of decision-making. Analyses of production decisions necessitate the development of qualitative research methods to understand how policy formations, social norms, knowledge access, and enforcement practices, among other variables, shape production practices across different kinds of ecologies and regions. In particular, many farmers are electing to avoid compliance . Factors influencing non-compliance may derive from prohibition or may only emerge post-legalization . Understanding the perspectives of non-compliant farmers is crucial to researching the social and ecological dynamics of cannabis production. Equally important is a qualitative, political economic understanding of how and why policies take particular forms in certain jurisdictions at certain times. Which interests and groups are most and least influential in forming polIcy? Who bears the consequences and rewards of the resulting regulatory regimes? Rapid transformations in cannabis policy are corresponding to the emergence of new scales, practices, and ecological consequences of cannabis cultivation. Lessons from other legal forms of agriculture suggest that increased market pressures may lead to industrialization, extensification and/or intensification, and increased reliance on credit fueled by debt. Siting patterns described here indicate that all three may already be trending upward in California since legalization of production for recreational use. As changes rapidly occur, research is urgently needed to understand the relations between regulatory change, farm size, location, environmental outcomes, and the geographical distributions of benefits and impacts. Such analyses will aid policy maker’s ability to govern and farmer’s capacities to participate in this newly regulated industry. If done with an eye toward equitable and just outcomes, drying weed it may also point the way toward a cannabis agriculture that incorporates and learns from the lessons and failures of industrialized agricultural production. Assessing the environmental impacts of the cannabis industry in Northern California has been notoriously difficult . The federally illegal status of cannabis has prevented researchers from obtaining funding and authorization to study cultivation practices . Fear of federal enforcement has also driven the industry into one of the most sparsely populated and rugged regions of the state , further limiting opportunities for research. An improved understanding of cannabis cultivators’ water use practices is a particularly pressing need.

Given the propensity of cannabis growers to establish farms in small, upper watersheds, where streams that support salmonids and other sensitive species are vulnerable to dewatering , significant concerns have been raised over the potential impacts of diverting surface water for cannabis cultivation. The environmental impacts of stream diversions are likely to be greatest during the dry summer months , which coincide with the peak of the growing season for cannabis. Further, because cannabis cultivation operations often exhibit spatial clustering , some areas with higher densities of cultivation sites may contain multiple, small diversions that collectively exert significant effects on streams . An important assumption underlying these concerns, however, is that cultivators rely primarily on surface water diversions for irrigation during the growing season. Assessments of water use impacts on the environment may be inaccurate if cultivators in fact use water from other sources. For instance, withdrawals from wells may affect surface flows immediately, after a lag or not at all, depending on the well’s location and its degree of hydrologic connectivity with surface water sources . Documenting the degree to which cannabis cultivators extract their water from above ground and below ground sources is therefore a high priority. In 2015, the North Coast Regional Water Quality Control Board , one of nine regional boards of the State Water Resources Control Board, developed a Cannabis Waste Discharge Regulatory Program to address cannabis cultivation’s impacts on water, including stream flow depletion and water quality degradation. A key feature of the cannabis program is an annual reporting system that requires enrollees to report the water source they use and the amount of water they use each month of the year. Enrollees are further required to document their compliance status with several standard conditions of operation established by the cannabis program. These include a Water Storage and Use Condition, which requires cultivators to develop off-stream storage facilities to minimize surface water diversions during low flow periods, among other water conservation measures. Reports that demonstrate noncompliance with the Water Storage and Use Standard Condition indicate that enrollees have not yet implemented operational changes necessary for achieving regulatory compliance. In this research, we analyzed data gathered from annual reports covering 2017 to gain a greater understanding of how water is extracted from the environment for cannabis cultivation. The data used in this study was collected from cannabis sites enrolled for regulatory coverage under the cannabis program. The program was adopted in August 2015, with the majority of enrollees entering the program in late 2016 and early 2017. The data presented in this article was collected from annual reports submitted in 2018 , which reflected site conditions during the 2017 cultivation year. The data therefore represents, for the majority of enrollees in the cannabis program, the first full season of cultivation regulated by the water quality control board. Because the data was self-reported, we screened reports for quality and restricted the dataset to reports prepared by professional consultants. Most such reports were prepared by approved third-party programs that partnered with the board to provide efficient administration of, and verification of conformity with, the cannabis program. Additional criteria for excluding reports included claims of applying water from storage without any corresponding input to storage, substantial water input from rain during dry summer months and failure to list a proper water source. Reports containing outliers of monthly water extraction amounts were also identified and excluded due to the likelihood of erroneous reporting or the difficulty of estimating water use at very large operations. Extreme outliers were defined as those values outside 1.5 times the bounds of the interquartile range . Farms were not required to use water meters, and those without meters often estimated usage based on how frequently they filled and emptied small, temporary storage tanks otherwise used for gravity feed systems or nutrient mixing. The final dataset included 901 reports. Parcels of land where cannabis was cultivated — including multiple contiguous parcels under single ownership — constituted a site, and this is the scale on which reporting was conducted. The spatial extent of the cannabis program included all of California’s North Coast region ; however, only a subset of the counties in this region allow cannabis cultivation and therefore reports were only received from the following counties: Humboldt , Trinity , Mendocino and Sonoma . Because Sonoma County contributed relatively little data, we combined Sonoma County’s enrollments with those from Mendocino County when making county-level comparisons. The data used for this analysis included the source and amount of water that cultivators added to storage each month as well as the source and amount of water applied to plants each month. We did not analyze absolute water extraction rates. Rather, we used the amount of water extracted each month — whether water was added to storage or applied to plants directly from the source — to analyze seasonal variation in each water source’s share of total water extraction. Water sources included: surface , spring , rain , well , delivery and municipal .

By tracing the evolution of prohibition through its U.S. history I seek to show the roots of our current drug laws and the role of scapegoating, dichotomization, and racism in their passage. I begin the chapter with a brief review of relevant sociological literature and a short sketch of the historical development of prohibition, as drugs became the target of state and federal laws one by one. Next, I analyze the discourse of prohibition using conceptual tools from the sociology of affect. My goal in this chapter is to show the entrenched rhetoric and emotion of drug prohibition to give the reader an idea of the task confronting the drug policy reform movement. In chapter two I use in depth interviews, archival materials, and Internet research to trace the development of the drug policy reform movement. I theorize the movement as made up of three branches; marijuana law reform, harm reduction, and anti-prohibitionism. My analysis of the movement is guided by concepts from the social movement literature including insights and categories from Resource Mobilization theory. After a discussion of the historical context of the 1960s, I give an in-depth analysis of the development and decline of the National Organization for the Reform of Marijuana Laws in the 1970s. I use the categories of Resource Mobilization to emphasize the role of social movement organizations in the movement and to conceptualize the ways the various organizations in the movement relate to one another and funding sources as a social movement industry beginning in the 1980s. After a brief detour through the harm reduction movement in the late 1980s and 1990s, I trace the rise of the anti-prohibitionist branch and how it relates to the two earlier branches of drug policy reform.

I close the chapter with a brief description of the current state of the movement and the chief areas of concern for its participants. In chapter three I seek to highlight the sites of activity for the drug policy reform movement. My goal is to address a lack of focus on physical space and location in the social movement literature. This chapter sprang from my fieldwork and represents a foray into “grounded theory.” Using an ethnographic approach, I attended numerous conferences, hemp rallies, protests, how to cure cannabis and meetings to discover the importance of such sites to the movement. To theorize the role of such events I sought to build on the existing concept of repertoires of contention. I discuss some of he insights I gleaned from attending movement events, including points of contention, issue framing and the role of emotions. In chapter four, I use political process theory to analyze the birth of medical marijuana in the San Francisco Bay Area in the early 1990s. I theorize the unique political opportunity structures that gave rise to the early medical marijuana movement. Next, I highlight the role of resources, social movement organizations, and elite benefactors in the campaign to legalize medical marijuana at the state level through the Proposition 215 ballot initiative. Finally, I analyze the rise of dispensaries and trace their evolution from cannabis buyers’ clubs to medical cannabis dispensary collectives. I also examine the importance of dispensaries as sites of continued movement activity. Chapter five, “A Tale of Three Cities” looks at medical marijuana dispensaries and how the regulatory climate and political opportunity structures of three different metro areas in the state affect the number and type of dispensaries that take root. By looking at the varying experiences of San Francisco, Los Angeles, and San Diego with the regulation of medical marijuana, I analyze both the structure of political opportunities and the ways that activists alter those structures.

Using interview data, observations from attending City meetings, and official City documents, I focus on the ways that medical cannabis providers participate in the political process that affects them. Theoretically, this chapter builds a dynamic view of the concept of political opportunity structures. By looking at the variety of tools that activists use to change the opportunity structures they confront, this chapter also serves as a model for future drug policy reform activists. Chapter six looks at the transition of medical marijuana from a social movement to an industry and the way that the hybrid movement straddles the fields of activism and commerce. I argue that the hybrid status of medical marijuana is unique among social movements and an interesting site for empirical exploration and theory building. Hybrid status also brings significant tensions for participants, and these tensions have developed into pronounced fault lines and factions. As articulated by movement leaders in a series of panel discussions, the hybrid character of the medical marijuana movement and how it should relate to the wider movement for drug policy reform are hotly contested issues. Chapter six concludes by looking at how the state has recently responded to the drug policy reform and medical marijuana movements, and the prospects for drug policy reform in the future.To contextualize the goals of the drug policy reform movement, the opposition it faces, and the discourse that it is seeks to counter, I present a brief history of drug prohibition and an analysis of the “drug control industrial complex’” employs to generate support and insulate drug prohibition from change. After presenting relevant sociological literature and tracing the history of drug prohibition, I analyze the arguments, rhetoric, and imagery that proponents of prohibition have employed over its relatively brief history.

Central to my analysis is a discussion of the emotions that anchor prohibitionist discourse to its cherished subjects, and how Gordon’s concept of “haunting” can illuminate the workings of drug prohibition. The drug policy reform movement is essentially engaging in an argument with the proponents of prohibition about the merits of the approach. With the advent of the Internet, the proliferation of drug policy reform groups, and their increasing ability to represent reformist discourse in the mass media, participants in the movement are increasingly able to counter the powerful discourse of punitive prohibition. Additionally, as the number of medical marijuana dispensaries has grown, popular culture and news media have made their depiction a favorite subject. The drug policies pursued in the United States present a complex enigma. Penalties for use are among the most stringent in the world, yet Americans are more likely to use illicit drugs than people in comparable nations. The U.S. is also the most vocal and active exponent of global drug prohibition. The federal government remains adamantly opposed to drug policy liberalization, but states including California and Colorado allow and facilitate truly revolutionary approaches to the provision of medical cannabis. Why have policy makers and drug control agencies pursued an approach that favors supply reduction, over demand reduction or harm reduction? Supply reduction depends on police and prisons, whereas supply reduction rests on treatment and prevention. Why have drug policy actors used the criminal law and the punitive capacity of the state as the chief instruments of drug control? And why have drug policy actors depended on stigmatizing drug users to marshal support for the policies of punitive prohibition? Although these questions are addressed in this chapter, my overarching focus is how the sponsors of drug prohibition marshal support for its reproduction. Using theoretical insights from the sociology of affect, and my concept of “the means of representation” I analyze the longevity and seductiveness of prohibitionist ideology. The story of drug prohibition in the United States is complex and multifaceted. Several noted sociologists have analyzed aspects of this history. Gusfield examined the symbolic uses of alcohol prohibition, Becker looked at the role of “moral entrepreneurs” in garnering support for cannabis prohibition, while Duster looked at the shifting demography and consequent status of opiate addicts and the how morality becomes the province of legislation. In a 1978 article, Himmelstein dubbed these studies “drug politics theory.” Other historical analyses have emphasized these changes but focused on the role of individuals in the passage of prohibitionist legislation or argued for alternative historical processes than those posited by their predecessors . Although Spector and Kitsuse did not formally delineate the constructionist approach until the early 1970s, the work of Gusfield and Duster presaged the turn toward constructionism. Within sociology, constructionist approaches to drug prohibition are prominent among narratives about the origin and reproduction of drug prohibition. Reinarman and Levine explored the demonization of crack cocaine for political purposes, indoor grow methods while Beckett showed how politicians constructed drug problems to build consensus around the “hegemonic project” of curtailing the welfare state while increasing the carceral organs of the U.S. government. Reinarman argues that “drug scares” recur frequently in U.S. history and have several consistent components. Reinarman seeks to understand the “appeal” of anti-drug claims in a nation characterized by “recurring anti-drug crusades and a history of repressive anti-drug laws.” According to Reinarman, drug scares and repressive drug policies are distinct social phenomena that often share seven common components.

They are usually based on a “kernel of truth” subject to “media magnification [through] the routinization of caricature,” where worst-case scenario anecdotes are amplified and circulated. Drug scares are the work of mostly self-interested “politicomoral entrepreneurs,” expanding Becker’s concept to the peculiar political capital afforded to American politicians by appearing “tough on drugs,” with no risk of alienating donors or the electorate . By linking use of drugs such as peyote, opium, cocaine, and marijuana with widely unpopular and feared ethnic minority populations, drug control actors began the project of dichotomization and out-grouping that under-girds U.S. drug prohibition. With alcohol, opium and the local phase of cannabis prohibition, American drug control actors were essentially using the drug law to control ethnic minorities. Gusfield theorized that proponents of alcohol prohibition were engaging in “status politics” with wets. With opium and cannabis, others have argued that the regime of drug control was an alternative means of enforcing cultural discipline . According to Reinarman , during successive drug scares, professional groups played prominent roles by generating and controlling the “public definition of a problem.” Although “the media, moral entrepreneurs, and professional interests…[often inflate] extant kernels of truth about drug use” without a “historical context of conflict” the actions of such groups are not sufficient to generate drug scares replete with repressive legislation . The concept of “drug scares,” supports my analysis of drug prohibition and its discourse. I seek to deepen the analysis of these earlier theorists by using newer theoretical inroads provided by affect studies. Although historians trace the impulse to prohibit the ingestion of some psychoactive drugs to early European colonialism , policy makers did not install a formal system to eradicate the use of certain drugs until the dawn of the Twentieth century. The system of drug prohibition sprang from a confluence of interests between elements of the Progressive movement and the U.S. foreign policy elite . When combined with racism, xenophobia, and potent “drug scares” early prohibitionist ideology would be formalized to first prohibit the smoking of opium in Western states in the late 19th Century, alcohol in 1920, and cannabis in 1937 . Other drugs, including LSD and MDMA , would not be prohibited until the 1960s and 1980s. In the U.S. the strategy of drug prohibition has created a “regime of truth” that drug prohibition is necessary for the protection of the citizenry. As constructed through discourse, drug policy is an example of the nexus between knowledge and power par excellence. According to Foucault , “…it is in discourse that power and knowledge are joined together.” Discourses of drug use form the arguments upon which drug policies are built. Through policy, actors are able to naturalize and systemize “regimes of truth” that create subjects who are forbidden to use certain psychoactive drugs. Through the discourse of “punitive prohibition” and the representations it deploys, drug policies are legitimized and sustained. Proponents of drug prohibition, garner support for such policies by representing the discursive formation of punitive prohibition in popular media, professional literature and government reports. I term the various forms of mass media, professional literature and government reports the means of representation. The forms of media available to both proponents and opponents of prohibition have increased throughout the twentieth century. In addition to newspapers, pamphlets and books in the late 19th century, radio, television and the Internet have diversified the means of representation throughout the twentieth century.

Newly hatched larvae could survive two weeks on yolk reserves alone, but were capable of feeding immediately on Artemia salina if provided. Larvae were transferred to beakers of fresh, unfiltered seawater each day. All mortalities appeared due to a failure to completely shed their molt. Each stage, defined as the period between molting, lasted an average of 9 days, with specimens reaching the post-larval stage at day 35 at 11ᵒC. Both the morphological guide and the methods of egg incubation were utilized to guide the present experiment. In the second study from this era, John Wickins investigated the influence of food density, salinity, temperature, and stocking density on the growth rate and survival of P. platyceros. Larvae hatching from females were reared in environments of 13-16ᵒC and 30±1% salinity. Development to post-larva was achieved at 15-29 days, in contrast to the 35-day span for Price & Chew; this is likely due to the warmer culturing temperatures. The stocking density yielding the highest survival rate was 5 larvae per liter at temperatures 13- 15ᵒC. Other key observations were that the size of Artemia fed to larvae did not influence larval growth rate or survival, and while larvae were raised successfully at a range of temperatures, there is a possible trend of fewer post-larvae survivors with increasing egg incubation temperature .The final major study addressing spot prawn rearing built off of those above to define the environmental extremes in which P. platyceros can thrive. Reiterating the others’ findings, Kelly et al. observed the larval period to last 26 to 35 days at 9.5-12.0ᵒC. They also concluded that spot prawns show a maximum thermal tolerance of 21.0ᵒC and salinity tolerance down to 22%. Growth rate was increased in both larvae and post-larvae by supplementing Artemia nauplii with any of four unicellular algae species. Kelly et al. also includes extensive investigation of diets for enhancing post-larvae growth, metal greenhouse benches which can be an important reference for further analysis of aquaculture potential, but the scope of this study is limited to larval development.

The present study attempts to reaffirm that this species can develop in laboratory settings. Using an amalgamation of the environmental parameters and timelines defined above, spot prawn larvae were hatched from ovigerous females caught off the coast of San Diego, California and cultured to post-larvae . The current growth of the aquaculture industry in conjunction with the depletion of wild seafood stocks makes revisiting this prospective aquaculture species a timely endeavor. By culturing eggs to this critical developmental phase, this experiments aims to provide an updated assessment as to whether P. platyceros may be a viable native species for aquaculture along the Pacific coast. The filter screen of the kreisel was large enough to allow Artemia and powdered feed through to the outflow chamber. This made it impossible to conclude if water clear of food matter signified the larvae had consumed everything or if it had been flushed out. The water was typically clear before most feeds, regardless of the Artemia concentration in the prior feeding. Because of this, feed concentrations were increased to compensate for food lost through the filter and the 120k Artemia per day became a minimum guideline. For future, the filtering screen of tanks should be of a finer mesh so as to allow longer retention of Artemia. This may require more frequent tank cleaning, perhaps stressing larvae, but the tradeoff would be observation of true feeding rates, which is required for maximizing efficiency of feeding schedules and densities. Possible cannibalism was observed occasionally, potentially indicating insufficient feed levels. Victims were usually white or translucent in color, which made it hard to distinguish between a mortality or exuviate. Since many crustaceans ingest their exuviae, it is possible this was natural feeding behavior ; it is also possible that larvae were cannibalizing each other due to lack of satiety. The uncertainty of this observation and that this occurred in the presence and absence of food renders this inconclusive.

As Kelly and Price & Chew both observed that most mortalities occurred in ecdysis, it is likely that failure during the molting process caused mortality.In regards to investigating aquaculture potential, future research should include large scaler trials of laboratory rearing with a priority on higher stocking densities and food conversion ratios. Percent survival at higher densities is essential in determining farming feasibility. The developmental period observed here is within the faster end of the range defined in previous studies and it would be useful to know if warmer temperatures could speed up the process further without significant increase in mortality. This trial experienced a maximum temperature of 19.4ᵒC, with sustained 19ᵒC temperatures for up to seven hours. Though not quite at the 21ᵒC thermal maximum, this culturing environment was very different than their natural habitat. Local waters did not reach higher temperatures until about halfway through the trial, so it would be interesting to see what impact consistently elevated temperature has during earlier larval stages. Furthermore, limitations in tank design prevented observations of feeding rates or food conversion ratios. Another essential question for aquaculture is the source of new stock. It is unknown if female spot prawns spawn more than twice in a lifetime, which would result a high turnover of broodstock. Until farmed specimens reached female maturity at four to five years, broodstock would have to be supplied from the wild. It is prudent to learn more about the reproductive capacity of mature spot prawns in order to provide a consistent supply of hardy larvae. Can females spawn for more than two years? Can fecundity be increased or stabilized by environmental conditions or does it continue to decrease each consecutive spawning? Do specimens from San Diego have the same seven- to eight-year lifespan estimated in Alaskan prawns ? Will they spawn in captivity? These questions are critical in establishing any level of commercial production and would also provide valuable information for future management of the wild fishery.

Finally, Litopenaeus vannamei is currently the marine species shrimp with the greatest global production by mass . This results in a wealth of knowledge in regards to techniques for disease prevention, broodstock maintenance, and other marine species obstacles that will likely be applicable to spot prawns. Some of the procedures for the current study were directed by methods used with L. vannamei. Macrobrachium rosenbergii, known as giant river prawns, are a freshwater shrimp that is also farmed. Farming methods for freshwater species are very different, though of all shrimp species farmed at a commercial-scale, M. rosenbergii is genetically of closest relation to spot prawns. M. rosenbergii and P. platyceros are both of the infraorder Caridae, so this freshwater species may provide a stronger biological reference for production timelines and practices . It would be prudent to use both species in directing future research regarding P. platyceros.The medical marijuana movement began in the San Francisco Bay Area in the early 1990s in a climate of official repression. This movement represents the most successful branch of the forty-year old drug policy reform movement. Using oral histories, participant observation, and archival research this dissertation explores the genesis, growth, and transformation of the medical marijuana movement in California from 1990 until 2012. I theorize the longevity of prohibitionist ideology over the course of the twentieth century in chapter one. Chapter two narrates the social history of the drug policy reform movement and its three branches; marijuana policy reform, harm reduction, and anti-prohibitionism. The three branches are characterized by diversification, as new organizations form to pursue different areas of drug policy reform, and competition for funding, but they maintain cooperative relationships with each other. My ethnographic fieldwork uncovered three types of physical sites, rolling greenhouse tables which play important roles in recruiting, networking, and facilitating cooperation on campaigns. The context and political opportunity structures of the San Francisco Bay Area were crucial factors in the genesis of the medical marijuana movement, but that activism and civil disobedience were also necessary for the movement to form. Activists and organizations in the metro areas of San Francisco, Los Angeles and San Diego were able to shape different political opportunity structures that affected the regulation of medical cannabis dispensaries in each specific locale. Medical marijuana began as a social movement and then transformed into an industry by shifting from the field of social movement action to the field of commercial action. New types of participants, a perceived change in political opportunity at the national level, and a more prominent public profile typify this shift. The shift also contributed to a refocused federal campaign to dismantle the system of medical cannabis provision that activists and entrepreneurs built over the twenty-one year history of the medical cannabis movement in California.The four decades old drug policy reform movement is comprised of individuals and organizations working to liberalize drug policies and move away from the system of “punitive prohibition” that typifies current drug policy in the U.S. According to Blain this “campaign is a ‘movement’ in the sociological sense that it employs the conventional repertoire of contention .” Drug policy reform organizations have trained their efforts on a wide variety of policy arenas, including, marijuana decriminalization, needle exchange programs , medical marijuana, and decreasing the penalties for drug offenses. Over the years, the number of organizations has increased and the specific concerns of various organizations have fragmented. The movement is made up of advocacy and membership-based organizations , a shifting mass base, and wealthy benefactors. Although the movement is ideologically powerful and well funded, successful campaigns in the political arena are few and far between. The drug policy reform movement has encountered opposition from both parent groups opposed to drug policy liberalization , and, uniquely, resistance from government agencies such as the Office of National Drug Control Policy and the Drug Enforcement Administration. The various organizations in the movement focus on a variety of campaigns of local, state,and national scope, yet the two most successful forms of drug policy reform have been medical marijuana and needle exchange programs Medical marijuana has been the most successful form of drug policy reform. In early 2012, sixteen states and the District of Columbia, have laws that allow qualified people to use marijuana for medicinal purposes. Individual medical marijuana dispensaries, storefront locations that sell cannabis to qualified patients, operate openly in California, Colorado, Montana and Washington. Clandestine medical cannabis dispensaries have been opened in several other states including Nevada, Michigan and Oregon. Along with needle exchanges and safe injection facilities, medical cannabis dispensaries represent specific modalities of drug policy reform. Modalities are different from changes in drug laws and sentencing policies because they have a physical location and present an active challenge to prohibitionist policies. The drug policy reform movement uses a combination of legal change to alter drug laws it finds unfavorable and direct action to put new policy modalities in place. While legislative change occurs comprehensively through ballot initiatives and the adoption of new legislation, activists, organizations and providers institute change on the ground slowly through protracted interactions with law enforcement agencies and state and local governments.In the 1930s, Alfred Lindesmith became the first scholar to look critically at the harmful consequences of punitive drug policy. His work paved the way for later scholars who looked at the negative effects of a policy that some have characterized as “punitive prohibition” . In the 1940s, Mayor Fiorello LaGuardia of New York City organized a team of scientists to investigate the cannabis use and policy in the Big Apple in response to fantastic allegations put forth by the director of the Federal Bureau of Narcotics in the previous decade. In the 1960s and the early 1970s, sociologists Becker , Gusfield and Duster all looked at the symbolic content of drug prohibition and the role of social status in determining which types of drugs were prohibited. During the 1980s and 1990s, epidemiologists and other scholars concerned with the intersection of drug use and drug policy would develop the harm reduction approach in response to the AIDS epidemic . Beginning the 1990s, the racially discriminatory consequences of the war on drugs became a major area of inquiry for scholars of drug policy .

In cases where the carrying distance is short , simply using the EL should provide an effective means for reducing the risk of LBD during bucket handling. The results of the manual handling of buckets during this study agree with the findings reported by Allread et al. , who showed the LBD risk for youth handling buckets ranged between 29 and 70% depending on the task and material handled . That study highlighted the need to develop interventions to address jobs that place youth on farms at increased risk of LBDs, including bucket handling. The proper deployment of the two interventions introduced in this current study is expected to provide sizeable LBD risk abatement for youth who commonly handle buckets on farms. Although the study showed the potential benefits of the EBC and EL in bucket handling tasks, the results produced relatively conservative intervention evaluations because of the limitations inherent in the design of the experiment, including the age and limited working experience of the subjects. The study included only 16 and 17 years old high school students and younger adult college students who were not experienced bucket handlers working on farms. This may limit the implications of the study results; however, it is also important to note that the participants were neither experienced with the use of the newly introduced interventions; therefore, the relative comparison among the methods should hold. The study focused on the risk of LBD during handling of buckets and did not consider the effects of manual handling or the two interventions on other joints of the body such as the hands/wrist or shoulders. However, rolling greenhouse benches the design criteria for the interventions attempted to consider the effects of these tools on the wrists and shoulder by properly designing the handles and adjusting the devices in accordance to the user’s anthropometry.

Further study should confirm whether these new tools may create new risks to other joints of the body, beyond of what is expected during manual handling. Furthermore, this study focused primarily on the physical risk factors contribution to LBD risk during handling of buckets. Factors such as physical immaturity, growth, and psychosocial factors among youth users might be possible sources of variations in injury risks and patterns. Lastly, improvements and redesign of the EBC and EL are needed so that they may become available to the general public and bring the expected benefits to their users. Considerable resources are spent on sundry health promotion strategies ranging from special diets to social networks to communing with nature to wrist-monitored step counts. But which core interventions are most effective and will produce meaningful health benefits? The evidence supporting much health advice is correlational and piecemeal; the field could benefit greatly from the rigorous research methods and theories of experimental health psychology. This article investigates community gardening for health promotion and presents some of the first well-controlled experimental research conducted on the topic. Community gardening is the practice of group cultivation of fruits, vegetables, and/or ornamental plants; it is widely used in a variety of settings but lacks empirical evidence of when, why, and for whom it promotes health. Community gardening is an especially promising platform to study real-world pathways to health and well-being because it is a deeply rooted, multifaceted intervention that has the potential to slowly shift people onto a healthy trajectory. Community gardening requires persistence, planning, accountability, physical activity, and cooperation with others.

There is significant theoretical and empirical reason to expect that each of these elements may lead to new, healthier psychosocial patterns. That is, in addition to harvesting the direct benefits of garden labor—fresh produce, exercise, and a close-to-nature scene—gardening may reinforce productive patterns in other areas of life. Research on gardening and health is usefully categorized into five general domains: diet, education, environmental stewardship, social competence, and psychological well-being . First, with regard to diet, gardening can lead to increased vegetable intake . Relatedly, gardeners have a lower average body mass index than non-gardeners —perhaps because of the combination of a healthy diet and physical activity that gardening reportedly promotes . Second, regarding education and cognitive development, school gardens show promise for engaging students in academics and improving test scores, especially in science-based subjects . By teaching biology, math, or even history using hands-on examples in the garden—a setting where students can move and interact— teachers may encourage deeper learning than in a traditional classroom. Third, many school garden programs have a focus on the environment, which fosters ethical and political interest in protecting the earth . Fourth, various social benefits of community gardens have been documented: gardens may facilitate social capital , collective efficacy , and social support . In other words, gardens can strengthen the local social fabric. Finally, gardens may enhance individual psychological well-being . Gardeners report that gardens promote relaxation, creativity, and restoration , and gardeners have been shown to score higher in eudaimonic well-being and quality of life than non-gardeners . One of the few true experiments on the effects of gardening found that after a stressful task, a gardening group exhibited reduced cortisol levels and reported improved mood above and beyond a reading control group .

Much of this research, however, is correlational, weakly controlled, or narrowly targeted. For example, most gardening studies to date lack random assignment, thus undermining confidence that observed effects are due to gardening rather than preexisting differences, self-selection, varying situations, or other confounds and artifacts. Second, many studies do not include baseline measurements, thus limiting the precision of assessment. Third, typically only the immediate effects of gardening are measured, overlooking possible long-lasting, fundamental shifts that might change a lifestyle and thus have a more meaningful impact on wellness. In short, there is a need for true experiments of gardening that comprehensively measure lasting effects. Perhaps the most complex and challenging limitation in the extant literature on gardening is the dearth of adequate comparison groups—a key to in-depth understanding of the effects of gardening. Many studies focused on dietary impacts of school gardens have properly used nutrition education as a control group, but there is a remarkable lack of adequate comparison groups in studies of effects beyond school gardens and diet. Including proper control groups is critical to understanding causal pathways— what it is about gardening that might drive the beneficial effects. Are the effects due to being active? Being outdoors? Growing something? Simply participating in a supervised activity? Such deeper understanding is necessary both for refining the psychology of health promotion and for designing effective interventions.Impervious land cover, habitat degradation and modification, and fragmentation spur biodiversity loss within urban areas . Yet, depending on local or landscape characteristics, urban habitats may support taxonomically and functionally rich communities of arthropods and associated ecosystem services. The relative importance of local and landscape drivers of urban biodiversity varies for different organisms, such as arthropods. At the local habitat scale, arthropod abundance and species richness increase with plant richness and woody plant presence. At the landscape scale, natural vegetation cover enhances arthropod abundance and species richness. In contrast, impervious surface negatively affects arthropods, including pollinators and natural enemies. Species life history and functional traits—phenotypes that affect ecosystem processes—can also determine how local and landscape scale changes in urban environments drive community formation. Feeding habits, habitat preference, body size, commercial drying racks and dispersal ability are traits that may be vary in sensitivity to local and landscape factors. For example, changes in leaf litter differentially affect cavity and ground-nesting bees. Increases in impervious cover more strongly affect light-preferring than xerophilous spiders, and negatively impact spiders with high dispersal ability . Thus, landscape-scale urbanization and local habitat management can selectively filter for certain traits, thereby structuring urban communities. Changes in both taxonomic and functional richness and the traits of individuals within communities are important to monitor because arthropods provide ecosystem services. Thus, understanding to what extent local and landscape factors affect arthropods informs both conservation and function. Beetles are abundant, diverse, and play important roles in urban ecosystems, but carabid diversity and community composition vary along urban to rural gradients and carabid functional traits vary with local and landscape factors. Beetles are natural enemies, detritivores, and bio-indicators of ecosystem-level processes. In particular, ground beetles are sensitive to environmental changes, taxonomically and functionally diverse, easy to sample, and are often used in ecological research. Carabids respond to changes in landscape forest cover and to local agroecosystem management, such as hedgerow or field margin planting.

As carabids might positively respond to intermediate levels of urbanization, urban ecosystems may conserve relatively high species diversity when compared to more natural habitats. Carabid traits and landscape connectivity and quality influence the dispersal and distribution of carabids , influencing habitat colonization across urbanization gradients. Individual carabid species have three types of wing development and dispersal ability: monomorphic brachypterous ; monomorphic macropterous ; and, dimorphic or polymorphic. High dispersal species are common in farms, prairies, and highly disturbed habitats, and low dispersal species are associated with older, less disturbed habitats. Smaller carabids may disperse farther, depending on wing morphology, and they are more abundant in areas with highly degraded, modified, and fragmented habitats. Yet, in agroecosystems, larger carabid species consume more prey and provide better pest control. Thus, environments with fewer large carabids may experience less pest control. An impervious surface may be an environmental filter of carabid functional traits, like body size, but less is known regarding how local management and landscape surroundings affect carabid activity, species richness, and functional traits in urban ecosystems. Urban agroecosystems provide an ideal system to examine the drivers of carabid taxonomic and functional diversity, community composition, and traits. Differences in urban habitat composition and structure influence carabid activity, diversity, and may result in changes in the abundance of beetles with certain traits . Although urbanization generally leads to biodiversity loss, it is important to determine what urban habitats, and which characteristics of those habitats, can support biodiversity conservation in the future. To this end, we compared activity density, species richness, functional group richness, and traits of carabids in urban community gardens that differ in local and landscape features. In order to determine how gardeners might promote carabid activity and taxonomic and functional richness for conservation purposes or to promote ecosystem services that are provided by carabids, we examined: Which local habitat and landscape features of urban, community gardens influence carabid activity density, species richness, and functional group richness? and, Which local habitat and landscape features of urban, community gardens influence carabid community and trait composition?We sampled carabids with pitfall traps for 72 h in each site monthly . The pitfall traps indicate carabid beetle activity density, not necessarily abundance. Pitfall traps were made of 12 oz. clear plastic tubs . We placed traps at the center of the 20 × 20 m plots in two rows of three traps, and separated each trap by 5 m. We buried traps flush to the soil level and filled traps with 200 mL of a saturated saline solution with a drop of unscented detergent to break the surface tension. We placed green plastic plates over each trap and elevated plates 7–8 cm above the ground with nails to limit the rainwater influx and to capture non-target taxa. Upon collection, we rinsed arthropods with water, separated them to order, and then stored insects in vials with 70% ethanol. Our sampling effort was unfortunately not as high as some other studies that examined carabids along urbanization gradients. We placed pitfall traps in active garden beds . Thus, we were unable to leave traps out for longer than 72 h or to get permission for putting traps more than three times during the summer growing season. KWW at the Essig Entomology Museum at the University of California, Berkeley , used published keys and descriptions and a comparison to authoritatively identified specimens in EMEC to identify the beetles. Nomenclature follows Lorenz . For each individual, we measured body length and grouped beetles into small and large size classes. We determined the flight wing morphology for each beetle by lifting the elytra under a dissecting microscope and noting wing state.

Samples are collected on an annual basis as part of the national disease surveillance programme, and consist of pooled organ homogenate supernatants which are then stored at −80◦C. In these samples, PMCV was first detected from broodstock fish on a marine site in July 2009, with infection in 100% of the pools . It was later detected in December of the same year in 100% of pools of broodstock fish at a second broodstock farm. These are subsequently referred to as the index cases, to be used as the starting point for simulation of the epidemic. The rationale behind setting these two farms as index cases is that they are the earliest detections , and do not seem to be epidemiologically connected. There were 9 parameters in the SIE compartment model . Following the approach used by Widgren et al. , and for model parsimony, the shed rate α was fixed at 1.0 per day, thereby defining the unit of the environmental infectious pressure variable ϕi. In the absence of more detailed data, it was assumed that the threshold for two seawater farms being connected by local spread was an euclidean distance of 10 km. It was further assumed that freshwater farms were not connected via local spread but only via fish movement. In the model, four event types were defined. “Enter” concerns hatchings and international imports. “Internal transfer” occurs on the day that individual fish change their age category, from egg-juvenile to smolt, or from smolt to growth-repro. “External transfer” occurs when fish move from one farm to another. “Exit” is linked with slaughter, cannabis grower supplies euthanasia or international export, and from this point these fish are no longer included in the simulation.

Each of the scheduled events was executed in the model once the simulation, in continuous time, reached the time for any of the events. Individuals were sampled at random from the compartments affected by the event. For example, for an external transfer event of n smolt from farm 1 to farm 2, n smolt were randomly selected from all smolts in farm 1 and placed into the same compartments in farm 2. Fish that entered the model were assumed to be susceptible in their respective age category. Imported fish were assumed to be susceptible, noting the aim of the study to explore spread in Ireland without considering international importation of PMCV. On average, 2,176,111 eggs were imported per year during the study period, according to information from the Irish Marine Institute . Fish remained in the same infection state whilst changing age category, from egg-juvenile to smolt or smolt to growth-repro, or moving between farms. Figure 1 presents the conceptual SIE compartment model for PMCV spread in farmed Atlantic salmon, including indirect transmission via the environment and fish movements between holdings. There is an EU legal requirement for aquaculture production businesses to be registered, and to keep records of all movements of aquaculture animals and products, both into and out of the farm . In Ireland, the storage of these movement data is undertaken by the MI. This database contains several variables, including the date of fish movement, origin and destination sites with geographic coordinates, life stage, species and quantity of fish moved. The present study was based on all fish movement reports to the Fish Health Unit of the MI covering the period from 1 January 2009 to 23 October 2017. This included 648 reports, with information about the identifier of the origin farm, identifier of the destination farm, the number of fish and age group and the date of the movement. Each record was linked to the geographical coordinates of the farms provided by the aquaculture production business records, to allow for incorporation of local spread during the modeling phase of this study.

A farm was considered “active” if any fish were present on the farm, according to movement records. The following data processing steps were used to generate events for the simulation. Enter events, i.e., hatchings or imports , were imputed as needed to ensure that farm-level fish numbers were sufficient to allow fish shipments between farms as recorded in the fish movement database . The date of the imputed hatching events was calculated based on the average residence time of fish prior to shipment in the farm. In total, 90 enter events were imputed, including approximately a third of these during the first year of the simulation . This represented on average 10 imputed enter events per year. Most of this imputed enter events corresponded to eggs or juvenile fish , but some fish were entered as smolts , growth , or broodstock fish . Internal transfer events, i.e., moving from egg juvenile to smolt or from smolt to growth-repro, were imputed when the relevant time during the simulation had been reached. When moving from egg-juvenile to smolt, fish were aged a week prior to shipping to seawater farms, and for aging from smolt to growth-repro, smolts were allowed to remain on the farm for 180 days. Exit events, i.e., mortality, slaughter, or euthanasia, were generated either the day prior to the last shipment of a fish cohort, when it was evident, based on the records, that the fish destination of the whole cohort was another farm , or after a fixed amount of time if it was clear from the records that the farm was the final destination of the fish . The duration of this period was 300 days in freshwater farms and 600 days for seawater farms. Broodstock fish in freshwater farms were assumed to live until 1 week prior to an egg shipment. A total of 55 unique farms were used for the simulation, with the following event types: enter, including reported imports , internal transfer , external transfer , and exit . A time-series was created to explore seasonality in the input data, focusing on the number of events, the number of farms with at least one fish and the number of fish per age category. A further time-series was produced to investigate the proportion of farms connected to at least one other farm, for each month of the year. A smoother was added to each of these time-series, using local polynomial regression fitting in order to describe the temporal trend . The disease spread model was implemented in SimInf , which is an R package for data-driven stochastic disease spread simulations. This package was adapted, in part, from the Unstructured Mesh Reaction–Diffusion Master Equation framework . It interfaces high performance compiled code and OpenMP, which allows work to be divided across multiple processors and computations to be performed in parallel. The disease spread simulations were performed using the SimInf package version 5.1.0 and R version 3.4.2. The simulation was initiated by first supplying the model with an initial state in every farm, together with all events.

At the outset, infection prevalence was assumed to be zero, since the earliest detection of the agent in the country, dry racks for weed on archived broodstock samples, was in July 2009 . The initial environmental infectious pressure, ϕi, was also set to zero, as it was assumed that PMCV was not present in the country at the time of initialization . Based on test results on archived broodstock samples , the introduction of the agent was assumed to have occurred in two separate occasions at two different farms: 1 month prior to the time of sampling of the first positive archived sample in the population of broodstock fish resident in the farm at the time of sampling, and a second time in November 2009, affecting broodstock fish in a broodstock farm where it was later detected in December of that year.With the final model, farm and fish PMCV prevalence were estimated on a daily basis following the simulated introduction of the agent. The spread of the agent was plotted as a time series and the modeled epidemic curves were described. The role of both local spread and fish movement was evaluated by setting either D to zero , or moving all fish shipped to the susceptible compartment at the time of shipment .In addition, we evaluated the effectiveness of an improved bio-security in specific farms. For the purposes of the simulations, our definition of bio-security refers to measures that prevent infected fish from entering a farm, akin to a bio-security strategy that is 100% effective in preventing infected fish from entering or leaving a farm. As described above, this was done by moving all fish shipped to the susceptible compartment at the time of shipment. Six strategies were tested. In the first strategy, all farms were targeted for an increase in bio-security. This would be a very costly approach, but a good ideal for comparison. In the remaining strategies, we targeted the 8 most central farms in terms of a specific farm centrality measure, which were indegree, outdegree, incloseness, outcloseness, and betweenness,using the same methodology described previously by Yatabe et al. . The sample size was chosen arbitrarily, representing ∼25% of farms in Ireland at that time. Briefly, indegree describes the number of different farms from which a farm receives fish, outdegree describes the number of different farms to which a particular farm sends fish, incloseness is an estimate of how close all other farms reach to a respective farm, outcloseness is an estimate of how close a respective farm reaches to other farms, and betweenness is a measure of the degree to which a particular farm falls on the shortest path between all pairs of farms in the network . For estimating these centrality measures, at the beginning of every year the movement records from the preceding 2 years were used for estimation. For example, on 1 January 2011 centrality measures of all farms were estimated based on fish movement data from 1 January 2009 to 31 December 2010, farms were ranked and the top 8 for each centrality measure were selected for an increased bio-security. There were two exceptions to this 2-year window for estimation of centrality measures: the year 2010, where only the data from 2009 was used to estimate centrality measures, and 2009, where no data from previous years were available. Therefore, during this latter year no control measures were applied. The former six strategies were evaluated using two approaches for preventing the spread of a newly introduced agent into the country: firstly, by applying the control measures 1 month after the agent was first detected , from now on the ‘reactive’ approach, and secondly by applying the control measures as a standard practice from before the first detection of the agent , from now on the “proactive” approach.Based on the data available for 2009, a rapid increase was observed that year in the number of active farms and fish . However, this is an artifact as many farms had not yet been involved in fish movement and thereby appeared inactive . As a consequence, our results are reported from the start of 2010. The number of active farms declined slightly during the period 2010–2017 with relatively stable numbers during the 2010-2014 period, and a decrease during the 2015–2017 period . The total farmed Atlantic salmon population in Ireland had an increasing trend from 2010, with a peak of more than 32 million fish in early 2015, to later decrease until the end of the simulation, although not dropping to previous levels, where it reached ∼13 million fish. This increase was related to a large increase in the number of juveniles during 2014 and 2015. The number of fish within each age category varied seasonally, with juvenile fish showing peaks during winter and dips during autumn , the former associated with spawning and the latter with the transition of juvenile fish to smolts prior to stocking in seawater farms in autumn and spring. For the smolts, the converse was true, with peaks during autumn and spring. This age group decreases roughly every 180 days, as this is the amount of time after which they were aged into the growth-repro age group. This in turn determines the peaks of this latter age group. The reduction in the numbers of fish in the growth-repro age group were mainly in spring-summer and autumn-winter, being a mixture of elimination of fish stocked in a farm as smolts after 600 days and elimination of fish stocked at older ages after spending the mean residence time in the farm .

The second peculiarity of the entry process is the existence of a matching stage where upstream entrants and downstream entrants form vertical relationships and decide on API trade. While in principle such a stage can be built into the econometric model, the incremental benefit from doing so is unlikely to compensate for the computational difficulty that it entails. Therefore, I assume that matching in the API market takes the following simplified form: every upstream entrant, including the upstream plants of vertically integrated entrants, is matched with every downstream entrant including units belonging to vertically integrated firms. In other words, every downstream unit is entitled – from a regulatory point of view – to use the API produced by any of the upstream units. Once we ignore patent challenges and allow every upstream entrant to be matched with every downstream entrant, the generic entry process can be characterized as a simple simultaneous-move game with discrete actions. Potential entrants choose their actions and receive payoffs according to the oligopoly game played out in the resulting vertical market structure. I do not explicitly model how firms trade the intermediate good and compete against each other in the post-entry vertical oligopoly; the effects of such interactions among firms are summarized into reduced-form payoff equations that have the actions of rival potential entrants as arguments. For a firm that is a potential entrant in the downstream segment but not in the upstream segment, the action set is {Not Enter, Unintegrated Downstream Entry}. Similarly, a firm that is a potential upstream entrant but not a potential downstream entrant has the action set {Not Enter, Unintegrated Upstream Entry}. Finally, grow vertical the choice set of a firm that is a potential entrant in both segments is {Not Enter, Unintegrated Downstream Entry, Unintegrated Upstream Entry, Vertically Integrated Entry}.

It is assumed that only pure strategy Nash equilibria of the entry game are played. Therefore, market structure outcomes that are not pure strategy Nash equilibria – for example, one unintegrated downstream entry and no other entries, or one independent upstream entrant and no other entrants – are ruled out. Elberfeld shows that vertical entry games are characterized by multiple equilibria even if entry decisions in one vertical segment are made prior to those in the other segment. This implies that the existence of multiple equilibria is an unavoidable aspect of simultaneous-move vertical entry games. Before moving on to the empirical analysis, let us briefly consider the motives for, and effects of, vertical integration in the generics industry. A former executive at Sandoz, one of the largest firms, mentions lower API costs, earlier access to APIs, and stability of supply as the advantages of vertical integration . Others have mentioned the possibility that vertical integration allows better control over the information flow between segments as well as better risk-sharing , which would presumably lead to higher levels of productive investment. These point to the existence of efficiency effects generated through vertical integration. Such effects are likely to benefit final consumers through lower prices, more reliable supply of drugs, or higher product quality. On the other hand, recent antitrust cases suggest that vertical integration can generate anticompetitive foreclosure effects. In FTC v. Mylan et al. , the Federal Trade Commission claimed that an exclusive dealing contract, signed between a finished formulation manufacturer and its upstream supplier, regarding the APIs for lorazepam and clorazepate tablets contributed to price increases of between 1,900 and 3,200 percent for the downstream product.7 Unlike exclusive dealing contracts, vertically integrated entry in the generic drug industry is not subject to antitrust scrutiny.

As a result, such anecdotal evidence on foreclosure effects is not readily available in the case of vertical integration. There is, however, no reason to assume that vertical integration cannot have similar anticompetitive effects.8 Estimation of the model is based on a maximum likelihood framework. At each iteration of the parameter search, I calculate the probability that the market structure observed in each of the sample markets is an equilibrium of the entry game. Loosely speaking, the likelihood contribution of a market is calculated by integrating over the region of the error term vector where the observed market structure is predicted as an equilibrium. Thus, the first tool we need is a mapping from the error term vector to equilibrium market structures. I implement the mapping by programming an equilibrium finding algorithm. The error term vector in my model has fairly high dimensionality and the region of integration is expected to have a complex shape. As a result, we can expect no closed-form solution to exist for the market structure probability. I therefore approximate the integral using a simulation-based method in which draws of the error term vector are taken . For each draw, the equilibrium finding algorithm is run to see if the market structure observed in the data is predicted as an equilibrium . The market structure probability is approximated by calculating the proportion of the draws for which the observed market structure is an equilibrium. In general, vertical entry games are characterized by multiple equilibria . Therefore, the equilibrium finding algorithm often indicates more than one market structure as a possible outcome of the entry game in a given market. When such equilibrium multiplicity occurs, an additional assumption is required in order to assign a unique value to the probability that the observed market structure is generated by the model.18 One possibility is to assume that the equilibrium with the highest joint profits is always realized.. Alternatively, one can specify an equilibrium selection function whose arguments consist of the characteristics of each equilibrium, such as whether or not it is Pareto dominant . Following Bjorn and Vuong , I employ the simpler rule that when there are multiple pure strategy equilibria, each market structure has the same probability of occurring. The entry game for each generic drug market involves a large number of heterogeneous players, which makes the equilibrium finding algorithm time-consuming. Even if one has a fast algorithm, the large number of evaluations that are required during estimation suggests the need to economize on the number of runs of the algorithm. To this end, I employ the method of importance sampling with change-of-variables . The advantage of this method is that the equilibrium finding algorithm needs to be run only once during estimation. In the remainder of this section, I describe the equilibrium finding algorithm, the simulation-based approximation of the market structure probability, and the importance sampling with change-of-variables method.As mentioned at the beginning of Section 2.5, there are 128 generic drug markets that satisfy the following criteria: the market opened up to generic competition during 1993-2005; the downstream product is the first one, among all single-ingredient products using the same API, to become generic; the downstream product is an oral solid, injectable, or topical formulation; and data on market characteristics are available for the product. These are the markets where we are likely to see upstream and downstream entry decisions being made at around the same time. 43 of the 128 markets are subject to a patent challenge by one or more of the generic entrants. These are identified by the Food and Drug Administration’s list of drug markets where one or more Abbreviated New Drug Applications containing a paragraph IV certification have been filed. As discussed in Section 3.3, the existence of a patent challenge changes the market structure formation process from a simultaneous-move entry game to a race to be the first-to- file entrant. Meanwhile, my econometric model is only designed to estimate the parameters of a simultaneous entry game. Therefore, the 43 markets with paragraph IV certification are dropped from the analysis. This leaves a sample of 85 markets that are not subject to patent challenge by any of the entrants. The exclusion of paragraph IV markets raises concerns of sample selection.

If the incidence of paragraph IV certification is correlated with any of the error terms of the model, vertical grow systems the removal of paragraph IV markets from the sample may lead to biased estimates. While acknowledging the importance of such concerns, the estimation conducted in this chapter does not take them into account. The main reason is the difficulty of incorporating selection into the econometric model. As in Chapter 2, sample selection can be modeled by specifying a dichotomous choice process for the determination of paragraph IV status at the market level, and allowing the error term in the paragraph IV equation to be correlated with the remaining error terms of the model.27 In practice,however, I find that the parameter estimates fail to converge when joint estimation of the vertical entry model and the paragraph IV equation is attempted.28 Another factor that may allow us to ignore the sample selection problem is that, according to the results in Chapter 2, the error term of the paragraph IV equation is not likely to be strongly correlated with the error terms of the firm-level payoff equations.29 The definition of downstream and upstream market entry follows that in Chapter 2. Downstream entry into market m is observed when a potential entrant’s ANDA for that market is approved by the FDA. Upstream entry is observed when the potential entrant’s submission of a DMF for that market is publicized by the FDA. Vertical entry occurs when the potential entrant receives ANDA approval and submits a DMF in the same market. The definition of potential entrant status also follows from Chapter 2. A firm is a potential downstream entrant of market m if its previous entry into the downstream segment of another market was less than five years before the market opening date of market m. 30 Similarly, a firm is a potential upstream entrant if its previous upstream entry in another market was not more than seven years before the market opening date. If a firm is both a potential downstream entrant and a potential upstream entrant, it is considered to be a potential vertically integrated entrant. Table 3.1 shows summary statistics for the number of potential entrants and the number of actual entrants in each market. The number of potential upstream entrants is greater than the number of downstream entrants. On average, there are 75.859 potential upstream entrants in a market while the average number of potential downstream entrants is 30.635. 18.929 of those entrants, on average, are potential vertically integrated entrants. The actual number of entrants is much smaller: an average market structure contains 3.365 unintegrated downstream entrants, 3.565 unintegrated upstream entrants, and 0.647 vertically integrated entrants. The estimated coefficients on the two continuous market characteristics, User Population and Per-User Expenditure, are largely within expectations. User Population has a significantly positive coefficient in the unintegrated downstream payoff equation, while in the other equations its coeffi- cient is not significantly different from zero. The Per-User Expenditure variable is not significant in the unintegrated downstream and vertically integrated payoff equations, but it has a significantly positive coefficient in the unintegrated upstream payoff equation. These results support the notion that larger market size and higher willingness-to-pay raise firms’ entry incentives. The dichotomous market characteristic variables have contrasting effects in the three equations. The Gastrointestinal/Endocrine-Metabolic dummy variable has a significantly positive impact on unintegrated downstream payoffs but its effect on vertically integrated payoffs is significantly negative. This conforms to the finding in Chapter 2 that vertical integration probabilities are lower in markets belonging to the gastrointestinal and endocrine-metabolic classes. It may be because the tighter control over upstream manufacturing processes afforded by vertical integration is less important for such drugs than for other drugs. Another finding that agrees with the results in Chapter 2 is that the Injectable dummy variable has a significantly negative coefficient in the unintegrated downstream and upstream equations, while its coefficient in the vertically integrated equation is significantly positive. This confirms the intuition that tighter manufacturing controls through vertical integration are more important for injectables than for other dosage forms. The Post-2000 dummy variable follows the same pattern as the Injectable dummy: it is significantly negative in the unintegrated downstream and upstream equations while being significantly positive in the vertically integrated payoff equation. One possible explanation comes from the finding in Chapter 2 that vertically integrated entry became more common after the year 2000 .