Tag: planting in pots ideas

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Past county yields are from crop reports published by the California Department of Food and Agriculture

The gains are much higher than the ones found in the 1996 report. This is partly due to increased economic activity in general, but probably has to do with more adoption of smart irrigation as well. The total yearly gains in agriculture range between $492 million, taking only the intensive margin effects, and up to about $1,982 million considering the extra acres that can be grown with the saved water. A surprisingly large sector using CIMIS is landscaping and golf courses, with yearly monetary savings of at least $201 million for our survey sample alone. Several other user types were included in the survey, indicating a substantial role of CIMIS in areas crucial for California’s economy. Respondents use CIMIS to plan drainage in agricultural and urban settings, taking advantage of CIMIS historic rainfall records. CIMIS is used for water budgeting and even pricing. Researchers in the public and private sector use CIMIS for diverse purposes, from basic research to calibration and verification of other weather related products. These are just a few of many additional uses of CIMIS we know about, but do not quantify here due to the complicated methodological framework required. The economic gains from CIMIS surely surpass the ongoing costs of a system with less than a dozen employees. However, could these gains be achieved by the private sector? The decreasing costs of weather sensors mean that growers and other users could potentially access precise data on their own. If we wanted a cheap weather station, costing about $1,000, for every 1,000 acres of drip irrigated land in California, the total cost would surpass$2.8 million, plus some ongoing costs for maintenance. This, however, would prevent many benefits from the centralized aggregation of data and the historical records that are crucial for research and planning, as one could not assure that aggregation of the data from all these separate private stations would occur. While several online aggregators of weather information exist,planting in pots ideas many rely on the public information provided by networks such as CIMIS and other government bodies such as airports and air quality monitoring systems. It is not obvious that private aggregators would be profitable if they had to purchase this information, or what their WTP would be.

Moreover, the ET measurements which many growers use are usually not captured by commercial stations, and there are concerns regarding the reliability of ET approximations by other variables. The development of satellite technology might change these conditions in the future.California pistachios are a high value crop, with grower revenues of $1.8 billion in 2016. The most common variety is “Kerman” , and almost all the California acreage is planted in five adjacent counties in the southern part of the San Joaquin valley. In recent years, rising winter daytime temperatures and decreasing fog incidence have lowered winter CP counts. Climatologists have concluded that winter chill counts will continue to dwindle , putting pistachios in danger at their current locations. To better predict the trajectory for this crop and make informed investment and policy decisions, the yield response function to chill must first be assessed. This task has proven quite challenging. The effects of chill thresholds on bloom can be explored in controlled environments, but for various reasons these relationships are not necessarily reflected in commercial yield data. For example, Pope et al. report that the threshold level of CP for successful bud breaking in California pistachios was experimentally assessed at 69, but could not identify a negative response of commercial yields to chill portions of the same level or even lower. They use a similar yield panel of California counties, but only have one “representative” CP measure per county-year. Using Bayesian methodologies, they fail to find a threshold CP level for pistachios, and reach the conclusion that “Without more data points at the low amounts of chill, it is difficult to estimate the minimum-chill accumulation necessary for average yield.” The statistical problem of low variation in treatment at the growing area, encountered by Pope et al., is very common in published articles on pistachios. Simply put, pistachios are not planted in areas with adverse climate. Too few “bad” years are therefore available for researchers to work with when trying to estimate commercial yield responses.

An ideal experiment would randomize a chill treatment over entire orchards, but that is not possible. Researchers resort either to small scale experimental settings, with limitations as mentioned above, or to yield panels, which usually are small in size , length , or both. Zhang and Taylor investigate the effect of chill portions on bloom and yields in two pistachio growing areas in Australia, growing the “Sirora” variety. Using data from “selected orchards” over five years, they note that on two years where where chill was below 59 portions in one of the locations, bloom was uneven. Yields were observed, and while no statistical inference was made on them, the authors noted that “factors other than biennial bearing influence yield”. Elloumi et al. Investigate responses to chill in Tunisia, where the “Mateur” variety is grown. They find highly non-linear effects of chill on yields, but this stems from one observation with a very low chill count. Standard errors are not provided, and the threshold and behavior around it are not really identified. Kallsen uses a panel of California orchards, with various temperature measures and other control variables to find a model which best fits the data. Unfortunately, only 3 orchards are included in this study, and the statistical approach mixes a prediction exercise with the estimation goal, potentially sacrificing the latter for the former. Besides the potential over-fitting using this technique, the dependent variables in the model are not chill portions but temperature hour counts with very few degree levels considered, and no confidence interval is presented. Finally, Benmoussa et al. use data collected at an experimental orchard in Tunisia with several pistachio varieties. They reach an estimate for the critical chill for bloom, and find a positive correlation between chill and tree yields, with zero yield following winters with very low chill counts. However, they also have many observation with zero or near-zero yields above their estimated threshold, and the external validity of findings from an experimental plot to commercial orchards is not obvious.Pistachio growing areas are identified using USDA satellite data with pixel size of roughly 30 meters. About 30% of pixels identified as pistachios are singular. As pistachios don’t grow in the wild in California, these are probably missidentified pixels. Aggregating to 1km pixels, I keep those pixels with at least 20 acres of pistachios in them. Looking at the yearly satellite data between 2008-2017, I keep those 1km pixels with at least six positive pistachio identifications.

These 2,165 pixels are the grid on which I do temperature interpolations and calculations. Observed temperatures for 1984-2017 come from the California Irrigation Management Information System , a network of weather stations located in many counties in California, operated by the California Department of Water Resources. A total of 27 stations are located within 50km of my pistachio pixels. Missing values at these stations are imputed as the temperature at the closest available station plus the average difference between the stations at the week-hour window. Future chill is calculated at the same interpolation points,growing blueberries in pots with data from a CCSM4 model CEDA . These predictions use an RCP8.5 scenario. This scenario assumes a global mean surface temperature increase of 2o C between 2046-2065 . The data are available with predictions starting in 2006, and include daily maximum and minimum on a 0.94 degree latitude by 1.25 degree longitude grid. Hourly temperature are calculated from the predicted daily extremes, using the latitude and date . I then calibrate these future predictions with quantile calibration procedure , using a week-hour window. Past observed and future predicted hourly temperatures in the dormancy season are interpolated at each of the 2,165 pixels, and chill portions are calculated from these temperatures. Erez and Fishman produced an Excel spreadsheet for chill calculations, which I obtain from the University of California division of Agriculture and Natural Resources, together with instructions for growers . For speed, I code them in an R function . The data above are used for estimation and later for prediction of future chill effects. For the estimation part, I have a yield panel with 165 county-year observations. For each year in the panel, I calculate the share of county pixels that had each CP level. For example: in 2016, Fresno county had 0.4% of its pistachio pixels experiencing 61 CP, 1.8% experiencing 62 CP, 12% experiencing 63 CP, and so on.Figure 3.1 presents chill counts and their estimated effects in percent yield change for two time periods: 2000-2018 and 2020-2040. The top left panel shows the chill counts in the 1/4 warmest years between 2000 and 2018 . The top right panel shows the chill counts in the 1/4 warmest years in climate predictions between 2020 and 2040. Chill at the pistachio growing areas is likely to drop substantially within the lifespan of existing trees.Results from the polynomial regression are presented in Table 3.2 . The first coefficient is for an intercept term, and it is a zero with very wide error margins. This makes sense, as centering around the means also gets rid of intercepts. The second coefficient is positive, as we would expect, and statistically significant. The third coefficient is negative, as we would also expect since the returns from chill should decrease at some point, but not statistically significant even at the 10% level. However, as dropping it would eliminate the decreasing returns feature, I keep it at the cost of having a wide confidence area. With the estimated coefficients, I build the polynomial curve that represents the effect of temperatures on yields. It is presented in Figure 3.2 with a bold dashed line. The 90% confidence area boundaries are the dotted lines bounding it above and below. Note that the upper bound of the confidence area does not curve down like the lower one. This is the manifestation of the third coefficient’s P-value being greater than 0.1. In both cases, the confidence area was calculated by bootstrapping. The data was resampled and estimated 500 times, producing 500 curves with the resulting parameters. At each CP level, I take the 5th and 95th percentiles of bootstrapped curve values as the bounds for the confidence area. This approach also deals with the potential spatial correlation in error terms. Another minor issue requiring the bootstrap approach is that the implicit potential yield estimation should change the degrees of freedom in the non-linear regressions when estimating the standard errors. In the lower panel of Figure 3.2, a histogram of positive shares is presented. That is, for each chill portion, the count of panel observations where the share of that chill portion was positive. The actual shares of the very low and very high portions are usually quite low. This shows the relatively small number of observations with low chill counts. The two yield effects curves look very similar in the relevant chill range. By both estimates, the yield loss is very close to 0 at higher chill portions, and starts declining substantially somewhere in the upper 60’s, as the experimental literature would suggest. Interestingly, the polynomial curve does not exceed zero effect, although it is not mechanically bounded from above like the logistic curve. This probably reflects the fact that historically, the average growing conditions has not deviated much from the optimal range. The “within” transformation hence did not deviate the potential yield much from the optimum in this case. At currently low chill portion ranges of 55-60, the effect is around −25%, again consistent with the stipulation of Pope et al. that a significant effect threshold would be located there. Considering alternate bearing and other factors contributing to the background fluctuation in yields, it is easy to understand how such effects on relatively small areas within the pistachio growing counties have not been picked up by researchers so far.

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A different kind of adaptation among edge growers is to change the commodities grown

Anticipating either that they will have the chance to sell their land for development or that surrounding urbanization will restrict their farming activities, farmers in such situations avoid continuing investment in their enterprises with capital improvements, new technologies, and management time and energy. This uncertainty about the future may in fact serve as a self-fulfilling prophesy, pushing landowners to seek development deals and thus accelerating the rate of farmland conversions in high growth areas. In the interim, much farmland may be idled or underutilized, production shifted from more to less intensively cultivated crops, and individual farm parcels bypassed or surrounded by development. For California farmland owners, the annexation plans of nearby cities are a key sign as to whether or not agriculture is likely to survive in particular areas . Research in other states suggests that urban-related uncertainties often lead to inefficient land use .Not all agricultural landowners in edge locations give up on the future, accepting what others regard as the inevitable demise of productive farming in their areas. There are sufficient stories of individual farmers continuing to invest in and aggressively manage their edge properties to suggest that continued farming in the shadow of urbanization is an important pattern for California agriculture. One reason is that not all edges experience ongoing development pressures. Even in high growth regions, California cities do not grow out in all directions at the same time; rates of expansion also are often gradual, allowing years of stability to some edges. Some landowners thus are unrealistic in anticipating that the path of urban expansion in their area will give them the near-future opportunity to sell their land for development.

In a guide to the easement option for California agricultural landowners,growing raspberries in pots the authors estimate that more than three-quarters of Central Valley farmland “cannot realistically be expected to develop to urban uses within the next 40 years” . Yet even in stable edge areas where agricultural operations are likely to continue indefinitely, the very proximity to residential and other urban land uses usually requires some degree of adjustment on the part of farmers. Operating in the shadow of urbanization demands more in farm management skills and the use of technology, according to some accounts. These abilities and the willingness to adapt and continue to farm in urban-influenced areas are not equally distributed among farmers in such locations. Age and family circumstances play a role.A study of dairy farms in a Hudson Valley area of New York experiencing growth pressures, finds that younger operators with fewer family problems were more likely to stay in business at that location and adapt their operations to the urban environment . Adaptations include various kinds of changes in production practices to minimize negative impacts on urban neighbors and to secure crops and equipment from vandals and trespassers. Integrated Pest Management techniques for reducing or controlling the use of pesticides and other chemicals are widely used by California farmers, drawing from a large body of university and private sector research. IPM covers both biological and engineering innovations, including investment in new spray equipment . Other changes include muffling pump motors, measures to reduce dust, and avoiding late-night and early morning operations that are noisy. Because of these and other adaptations, production costs for edge farming are usually higher than in other locations, whether because of equipment investment or the inefficiencies created by operational changes.One example of urban-influenced adaptation is provided by the experience of Southern California’s poultry farmers during the 1980s.

They invested in new types of buildings to remove laying hens from the floor and thus isolate waste material, changed procedures for drying and disposing of waste, landscaped the areas around poultry housing, and improved fencing and installed alarm systems to reduce vandalism and theft . Some poultry farms in the region chose instead to sell their land for development and relocate in more remote locations, investing some of their proceeds in new facilities—the ultimate strategy by farm operators impacted by urban growth. Generally this means shifting to higher value commodities, or to those that are less vulnerable to urban impacts. Commodities that produce more income per acre, such as tree, ornamental, and vineyard crops, also typically involve more intensive and expensive cultivation practices. But the motivation for shifting in this direction is the already higher costs of farming in urban-influenced areas, including the land costs for farms that acquire more land to expand their operations . Such adaptations allow some productive and profitable agricultural operations to continue in locations highly impacted by urban growth. This is suggested by changes in farm operations in several of California’s largest metropolitan counties recorded in the half century between 1950-2001, a period of considerable population growth and farmland conversion. Table 3 shows the changes during this period in population, agricultural market value, and top four farm commodities for five of the state’s eight counties with more than 1 million residents . Located in coastal areas, they include the four most populous counties of California. All five counties recorded a substantive shift in dominant commodities over the half century, with nursery products or flowers taking over the top spot. Citrus, poultry, dairy products, and field crops—ranking commodities in 1950—were largely eliminated from the top four spots by 2001.The significance of the shift to nursery plants is that they are often grown in greenhouses, enclosed environments that limit impacts on urban neighbors and are relatively secure from vandalism and other encroachments. Nursery products also have a ready market in nearby urban areas. Table 3 also reveals the continued importance of agricultural to local economies in four of these metropolitan counties.

With the exception of Alameda, all had farm market values of at least $250 million in 2001. Even Los Angeles County made this list in 2001, due to $152 million in nursery sales, although the agricultural significance of this most populous California County dropped greatly from the late 1940s when it was the state’s top producer in market terms. In 2001 Los Angeles ranked 27th in farm value among California’s 58 counties. San Diego County stands out as the only county in this sample with an increase in farm market value during 1950-2001 that exceeded the rise in California’s consumer price index during this half-century. In 2001 San Diego ranked eighth in the state with a market value of $1.3 billion, fueled by more than $700 million in nursery and flower production and $138 million in avocados.In pointing to the survivability of farming in metropolitan areas, however, these numbers are more suggestive than conclusive. The “metropolitan” designation is only a rough and imprecise indication of the extent to which local agriculture is influenced by urbanization. The counties in this small sample in fact contain vast rural areas, leaving open the possibility that many of the most productive farms are not close to urban development. Also not examined in this analysis is the extent to which commodity shifts are the result of other factors, including market forces and water supply.Research in several eastern states supports the survivability thesis for urban influenced farming. The common generalization from several studies is that urban proximity can provide profit-making opportunities as well as problems for farmers, considering the potential for direct marketing, other forms of access to urban consumers, and off-farm income for operators. . But only certain kinds of intensely-cultivated farms,plastic plant pot including vegetable producers, seem to benefit from such locations . A USDA review of the available information on farms in metropolitan areas characterizes them as smaller, producing more per acre, more diverse, and more focused on high-value production than farms in non-metropolitan areas .Land use policies and regulations can be seen as largely proactive efforts to direct the location and form of new urban development in ways that would minimize impacts on agricultural activities. This is the general intent of policies that call for keeping development away from agricultural areas, in particular restricting residential growth in the countryside and directing it instead to existing cities, either as infill development or as incremental additions to municipal areas as cities gradually annex adjacent territory. Some conversion of farmland is inevitable in this process where cities are surrounded by agricultural uses, as throughout the Central Valley. But the assumption is that this is preferable to allowing building in unincorporated areas, because city development occurs at relatively high densities that convert less farmland in relation to population housed, it is less costly in public infrastructure terms, and it is more likely to produce solid and less exposed edges with farming. Also cities that are surrounded by agricultural land of varying quality and productivity have the option of directing their expansion away from the best farmland. City-oriented growth strategies are supported by the LAFCO process and county city agreements on the location of future urban development.

LAFCOs are California’s boundary control agencies at the county level, semi-independent boards that have the power to review, deny, or change city plans to annex territory and to designate their future growth areas . LAFCO actions, guided by orderly growth and farmland projection objectives, are a major restraint on extensive sprawl. Some counties and cities in agricultural areas have negotiated agreements that divert urban development from unincorporated areas to city areas, usually in return for financial considerations that allow the county to share in municipal growth revenues . The two land use policies that most specifically address edge issues are agricultural buffers and mitigations imposed on new development for the loss of farmland or to limit negative impacts on farming. The two are closely related, since buffers are a type of mitigation frequently recommended by the environmental reviews conducted by county and city governments of proposed urban projects. Buffers essentially create a separation between agricultural and urban uses, using barriers or distance to minimize negative impacts on both sides of an edge boundary, especially the effects of chemical drift from farming activity. Agricultural buffers come in different forms—natural barriers created by landscape features such as waterways, roads, landscaping, walls, residential setbacks, open space greenbelts, and combinations of various types. Key issues in their design and creation are their permanence, maintenance, and which landowners—developer/homeowner or farmer—provide the land or barrier. Although the general plans of many California counties and cities call for use of buffers to protect farmland, the implementation of the technique and application to specific urban projects is quite spotty, as Mary Handel noted in a 1994 M.S. thesis in Community Development at UC Davis. Especially controversial are the desired widths for setbacks and greenbelts, with farm chemical applicators and other agricultural experts calling for the biggest possible separations while urban developers and city governments argue for smaller widths because of land cost considerations. In Handel’s study of buffer use in 16 counties and 6 cities, designated widths range between 50-800 feet. She also finds great variations among farmers and urban neighbors in the perceived effectiveness of different forms of buffers to limit specific negative impacts. For example, farmers generally judge setbacks or open space buffers as ineffective in dealing with trespass, vandalism, litter, theft, and dogs while urban residents see them as generally effective in reducing chemical drift, odor, and dust from farm operations . More recently, the Great Valley Center published a short guide on agricultural buffers for urban planners .As contrasted with the land-use control approach of trying to head off edge problems by influencing the location and design of urban development, other strategies seek to deal more directly with farm-urban neighbor tensions, often after they have emerged. Government policies and programs in this category include right-to-farm ordinances, California’s extensive regulation of pesticides and other agricultural chemicals, and restrictions on farm animal facilities driven by clean water policies. When first adopted by California local governments in the late 1980s after enabling state legislation, right-to-farm ordinances were seen as a promising tool for protecting routine farm operations from nuisance law suits and complaints by urban neighbors. The central feature of most such local laws is a disclosure requirement—notifying home buyers of parcels adjacent to farms of the possibly negative effects of agricultural operations. In this way, the assumption goes, new residents especially would learn about the realities of modern farming and would be less inclined to complain or even go to court over sprays, dust, odors, noise and other results of nearby agriculture.