The analysis in this section uses data from 100 years of local climate history and 60 years of crop acreages in Yolo County, California, to establish statistical relationships between climate change and changes in the crop acreage pattern. Most of the land in Yolo County is devoted to field crops such as alfalfa, rice, and wheat. Vegetables, primarily processing tomatoes, orchard and vine crops, and seed crops are also important. Econometric models can relate the evolution of acreages of each major crop to changes in relative prices and climate variables through time. This provides a way to investigate how farmers have responded to the central tendencies of weather, and to test if their responses have been strong enough to affect changes in acreages of either annual crops and perennial crops in Yolo County. Such models are not designed to fully account for all of the year‐to‐year fluctuation in acreage or to link acreage to the full complement of expected prices and other drivers. But they can be used to guide projections about future acreage patterns, utilizing climate projections from scenarios provided by Global Climate Models . Of particular interest to this project are the B1 and A2 scenarios from 2010 to 2050. Past crop‐climate relationships help us understand the general magnitude of potential crop responses caused by future climate change. Such historical relationships can inform planning,nursery grow bag even though future crop patterns will also be heavily influenced by changes in market conditions and policies, including policies for resource management and environmental quality.
In 2009, farmers in Yolo County sold $462 million worth of farm products on 330,000 acres of cultivated cropland . About 80 percent of this revenue is divided almost evenly among orchard crops, field crops, and vegetables.Animal‐related products represent only about 5 percent of the revenue, and the rest is accounted for by organic, nursery, and seed crops. Field crops occupy two‐thirds of farmland, and orchard crops and vegetables together cover only 23 percent of cropland. We include irrigated pasture among the field crops, but exclude dry land pasture from the cropland. Dry land pasture was >100,000 acres in 2009, but contributed only $1.0 million dollars of revenue . Organic acreage or revenue is reported as a single category and not separated by commodity. Therefore, organic production is included with the “other” category. Field crops have a much larger share in the value of output in Yolo County than in California as a whole ; 26 percent versus 10 percent, respectively. Animal‐related products account for 5 percent versus 22 percent, respectively. While farming is one of the leading businesses in Yolo County, it represents only about 1.3 percent of California farm revenue, ranking about 23rd among the 58 counties in the State.In each crop category, only a few crops account for a large share of crop revenue: 80 percent of field crop revenue comes from alfalfa, rice, and wheat; close to 90 percent of orchard crop revenue is from wine grapes, almonds, and walnuts; and 90 percent of vegetable revenue is from a single crop: processing tomatoes. In terms of economic importance, processing tomatoes are by far the largest revenue crop, followed by wine grapes and rice.A consistent time series on crop acreage, production, and revenue in Yolo County covers the period from 1950 through 2008 . Data are available as early as 1937, but were discontinued during the Second World War, and there were many missing values before 1950.
Since 1960, total crop acreage in Yolo County has been declining. Vegetable and orchard crop areas have increased, while field crop acreage has declined . There has been an increase in higher‐revenue‐per‐acre crops, especially a shift out of barley, and an increase in processing tomatoes, wine grapes, and walnuts.Field crop acreage in Yolo County rose from 300,000 acres in 1950 to >500,000 acres by the end of the1950s. Since then, it has continued to decline—first rapidly until the end of the 1960s and then slowly, reaching about 200,000 acres currently . Even a small change in field crop acreage dominates any other acreage changes in Yolo agriculture. The very high prices since 2008 may stimulate more field crop acreage. The most important change in terms of acreage has been a massive shift out of barley in the 1960s . These shifts can be explained by changes in relative prices and farm structure. When barley prices stagnated, alfalfa increased. Dairy, which uses alfalfa rather than barley as feed, had expanded in California. The virtual disappearance of sugar beet acreage was due to lack of competitiveness with other regions in the United States and costs of production and processing that were far above import prices. Almonds were the single most important orchard crop in Yolo County for more than half a century, but the rise of grape acreage put the almond crop in the second place in terms of acreage . Wine grape acreage increased from 1,700 acres in 1993 to >10,000 acres in 2001. Grapes have mainly replaced row crop acreage. For grapes, a main driver behind the rapid expansion in acreage is an increase in wine consumption in the United States. For the last several decades, walnuts have become the third most important orchard crop in Yolo County. Declines in crops such as apricots have been a statewide phenomenon, due to very high labor costs, reduction in demand for processed fruits, and availability of imports of dried fruit.We specify 13 acreage equations, each associated with an individual crop that currently has significant acreage in Yolo County.
Each equation includes acreage of a specific crop as the dependent variable and a set of climate variables, prices, and other factors as independent variables. Below, acreage is expressed as a function of these independent variables. Our guiding principle, in specifying each equation, is that crop acreage depends on market conditions, water availability, climate considerations, and other agronomic factors such as crop rotations which may be specific to the crop in question . In each acreage equation, product market conditions are represented by own product price and prices of substitute crops. Price data used in our analysis are obtained from the U.S. Department of Agriculture sources . The USDA publishes prices of major agricultural commodities, and the state level is the smallest geographic unit for which consistent price data are available. Statewide, markets are spatially integrated and price is highly correlated within relatively large regions allowing us to use California prices for Yolo County. All prices are converted into real prices using the gross domestic product deflator . Note that in many annual crop equations we used prices that were lagged one period because acreage decisions are usually made based on the information available prior to the crop year, with an exception of alfalfa, which usually is grown for multiple years once the field is developed. For perennial crops, we used prices of much more distant lags, since many orchard crops take three to seven years from the time of planting until commercial harvest. Nevertheless, the specific lag may differ for each orchard crop and is not known with certainty. Multiple lags form a moving average of own prices. The concept is that the perennial crop acreage harvested in year t is based largely on planting decisions made several years in the past. The climate variables used are annual growing degree days and winter chill hours, mostly with the former for annual crops and the latter for perennial crops. Note that climate variables here are intended to represent the general trend of climate rather than year‐to‐year short‐term changes in weather. Thus,plastic growing bag to smooth out short‐term fluctuations and identify a long‐term trend, we use a ten‐year moving average of each climate variable. The effects of irrigation water supply are captured by two lagged precipitation variables and a variable for the effect of water availability from a nearby reservoir . Most California crops are irrigated, and precipitation here is used as a proxy representing irrigation water availability. In California, one important supplier of irrigation water is reservoirs, and previous years’ rainfall is important for replenishing water supply in reservoirs.The dummy variable, Dind, captures the effect of the Indian Valley reservoir, which began operating in 1976 and increased flexibility in supplying water in Yolo County farmland . The reference period for this binary variable is the period of post‐Indian Valley reservoir. The GDDwinter variable reflects the winter growing season. Most wheat produced in Yolo County is spring wheat that is planted in winter.The GDD winter is also used for tomatoes and alfalfa, even though these crops are mainly summer‐harvested crops. In Yolo County, tomatoes intended for early harvest are planted as early as February. Alfalfa is a perennial crop and the first harvest occurs in April in California .
The GDD during the winter season is particularly relevant to these crops because they usually have sufficient growing degree days during the summer in California.We also include variables representing prices of substitute or rotation crops where these are relevant. In Sacramento Valley, irrigated small grains are grown in rotation with alfalfa, cotton, corn, rice, safflower, and a wide range of vegetable crops. The choice of rotation crops also depends on the specific site and the economic prospects for the rotation crops . For each equation, we report the models that include variables which had significant effects and explained more of the variation in acreage. Finally, a just few comments on technical issues related to econometric methods are needed. For the regression techniques to generate unbiased parameter estimates, the data must be transformed to meet certain statistical properties. Of particular relevance here, explanatory variables used in the model are transformed to have constant mean and variance over time. We conducted specification tests which evaluate statistical properties of all the time series. We report the test procedure and results in Appendix 2. In order to satisfy the needed conditions, we used each variable in a first difference form. For example, the dependent variable in each model is the year‐to‐year change in acreage, and the explanatory variables are also represented as year‐to‐year changes. That is, in the estimated models, we regress the first difference in acreage on the first differences of explanatory variables.Among the field and vegetable crops, own prices are found to be important for rice and wheat acreage decisions . For these crops, the favorable own price contributes to the expansion of acreage, and likewise, the unfavorable own price has a negative effect on acreage. Own price of tomatoes is found statistically significant at P≤0.1. Irrigation water availability also affects acreage decisions. Our regressions use previous years’ precipitation as a proxy for irrigation water availability; the effects are positive for alfalfa and corn, and negative for wheat and safflower . Among the field crops considered here, the most water‐intensive crops are rice and alfalfa . For rice, own price is significant but precipitation variables are not, indicating the relative importance of economic variables over water availability for rice acreage. This conjecture is supported by crop values per acre, which, averaged over the last ten years, were $738 for alfalfa and $1,019 for rice. The results on wheat and safflower are also consistent with their low dependence on irrigation and low per‐acre value. Thus, abundant water supply would induce farmers to shift away from these crops and the opposite would occur with constrained water supply. Note that the wheat equation includes current period precipitation, as well as two previous years’ precipitation, because the current year’s precipitation season ends in April which is many months before the wheat planting time in November.Summer temperatures did not directly affect the allocation of acreage among crops in Yolo County.The minor changes in temperature during the months of April, May, June, July, and August for the past 100 years apparently have had little effect on the planting pattern. Winter temperatures had significant effects on acreage equations for both alfalfa and wheat .Warmer winter growing seasons have had a negative effect on wheat acreage, but a positive effect on alfalfa acreage. In many winter wheat growing regions in the United States, winter kill caused by a harsh winter is a major risk , but this is not a problem in California. In California, spring wheat varieties do not require a period of cool growing conditions to trigger reproductive growth .