After hand pollination, we re-bagged flowers with breathable mesh bags to exclude pollinators while simultaneously permitting the flower to experience conditions like those experienced by flowers open to bees . After the bee-pollinated and hand-pollinated flowers closed , we randomly selected flowers to estimate either pollen deposition, or fruit and seed set. To estimate pollen deposition, we first used a single-edged razor blade to remove bee and hand-pollinated floral stigmas, which we immediately placed in a solution of 70% ethanol and basic fuchsin dye . We randomly selected two stigmatic lobes , counted all pollen grains present on these lobes under a dissecting microscope at 50x magnification, and then calculated the mean pollen count between both lobes . We calculated the total stigmatic pollen count as the mean pollen deposited per lobe plus any stained grains present in the ethanol solution. As expected, pollen deposition was higher in hand-pollinated plants: total pollen count on stigmas pollinated by hand was more than two-fold higher compared to that on stigmas pollinated by bees . We harvested fruit 50 days after pollination . Developed seeds from mature fruit were dried and weighed. We report total seed mass per fruit per plant as a measure of seed set. Mean seed mass did not depend on seed number in this experiment . For all statistical analyses performed in this study, we used R version 3.6.1 and used the package ggplot2 to prepare figures . We inspected qq plots to test for normality and used Bartlett tests to assess homogeneity of variances. We also tested the residuals of each model with the Shapiro-Wilk test for normality.

For bee-pollinated plants in the Temperature x irrigation experiment, we used general linear models with two fixed factors, soil moisture and temperature , raspberry plant pot to examine their direct effects on individual floral traits : total flower number, self and non-self flower number, flower size, nectar volume, nectar concentration, pollen mass, and pollen viability. We also used general linear models with soil moisture and temperature as fixed factors to examine bee visitation and behavior rates in flowers. We conducted a second set of analyses with an additional fixed factor to test whether or not differences in fruit set and seed set resulting from soil moisture and temperature variation could be mediated by interactions with pollinators. For all analyses in the Temperature x irrigation experiment, plant is the experimental unit of analysis. All plants were given at least one chance to set fruit from a pollinated female flower. For plants that set more than one fruit , we used mean values for total seed mass.For the floral trait analyses, the response variables of total female flowers and total available self male flowers were right-skewed and thus log10 transformed to improve normality of the residuals. Pollen mass in male flowers was right-skewed and thus square-root transformed to improve normality, although pollen mass still did not have equal variances after transformation. Nectar concentration in female flowers and proportion viable pollen in male flowers were left-skewed and thus square transformed to improve normality, although pollen viability still did not have equal variances after transformation. Variances were marginally equal for nectar volume in male flowers. For the bee visitation analyses, all rates of bee visits per flower per minute were proportions and thus arcsine square root transformed to improve normality; however, except for Apis visit rate to female flowers, the residuals were still not normal even after transformation.

For the bee behavior analyses, all behavior rates were right-skewed and thus log10 transformed to improve normality of the residuals; however, the residuals were still not normal for Eucera behaviors in male flowers and the variances were still not equal for Apis pollen collection per min. For the fruit and seed set analyses, the residuals were not normal for fruit set. To determine if bee-pollinated plants experienced pollen limitation, we calculated pollen limitation using the pollen limitation index, L = 1 – . In this equation, B represents total seed mass for a bee-pollinated plant, and H equals total seed mass for a hand-pollinated plant. For each hand-pollinated plant in the equation, we matched a corresponding bee plant that had similar mean plant soil moisture and was from within the same experimental group. For hand and bee plants with more than one fruit in July, we used mean values of total seed mass for each plant. We used a general linear model containing soil moisture and temperature to examine their direct effects on pollen limitation. Soil moisture values used in the analysis are those of the matched bee-pollinated plants. We also estimated pollen limitation using a second method in which we used all bee-pollinated plants and the mean values of their matched hand-pollinated plant treatment groups. This second method yielded results that are qualitatively similar .From June through September 2017, we tested how irrigation level affected the degree to which bee pollinators of squash transfer self pollen versus non-self pollen. This particular research focus was stimulated by one of the results of the Temperature x irrigation experiment, namely that the availability of non-self, male squash flowers increased with increasing soil moisture experienced by individual plants . Given this result, pollinators may be transferring increasing amounts of self pollen with decreasing soil moisture, which may cause reduced seed set.

In Irrigation experiment I we grew squash in a similar manner to that in the Temperature x irrigation experiment, but in the present experiment we grew C. pepo plants under different levels of irrigation and did not manipulate temperature. We used a drip-line system to irrigate plants every morning; the irrigation treatment included two levels: 1.3L water/plant/day and 0.38 L water/plant/day . We monitored soil moisture levels as in the Temperature x irrigation experiment and found that volumetric water content decreased by an average of 17% for plants in the low irrigation treatment . Soil moisture levels again exhibited substantial variation within each experimental group. Mean volumetric water content, for example, varied from 38 – 63% to 10 – 54% . For this reason, we again consider soil moisture as a continuous variable in all statistical analyses but use treatment group designations in the organization of the experiment. All analyses are restricted to data collected from July 28 – August 25 during the height of flowering and pollinator visitation. To test for differences in the transfer of self pollen and non-self pollen as a function of irrigation level, we used florescent powdered pigments to track bee movements among plants . On each day of the experiment, we identified 1-2 focal plants that each had one female flower and at least one male flower open that day. Before allowing bees access to flowers, we used flat toothpicks to apply powdered DayGlo© fluorescent pigments to the anthers of focal male flowers . On a given day, the male flowers of each focal plant received its own unique pigment color; all male flowers on non-focal plants received a different pigment color. Each day we switched the pigment color assignments between focal and non-focal plants to mitigate for any color preferences exhibited by bees. When bees contacted the anthers of a male flower with pigment, blueberry production pollen grains as well as pigment particles adhered to the bees’ bodies. Therefore, the number of pigment particles acted as a proxy for the number of pollen grains transported by bees to the stigmas of the female flowers . We estimated pollen deposition as follows. Following pollination, removed stigmas were immediately placed in 100% ethanol . Prior to adding basic fuchsin solution to dye pollen grains, we used a dissecting microscope to count pigment particles under 40x magnification . We then added basic fuchsin solution and used a dissecting microscope to count the number of pollen grains on the entire stigma and in the ethanol solution containing the stigma .

Mean total pigment particle count on bee-pollinated stigmas was highly correlated with mean total pollen grain deposition . To assess whether or not irrigation level affects the deposition by bees of self versus non-self pollen, we used general linear models to compare pigment and pollen deposition as a function of soil moisture.From June through September 2018, we conducted a field experiment that involved irrigation and hand-pollination to test how pollen source , and pollen identity affect the seed set of plants grown under different levels of soil moisture . To hand pollinate female squash flowers, we used identical methods as those employed in the Temperature x irrigation experiment, except that we reduced the amount of pollen deposited to stigmas to emulate levels observed in bee-pollinated flowers, and to decrease pollen competition below levels that likely occurred in the hand-pollination treatment in the Temperature x irrigation experiment. When stigmatic pollen deposition is adjusted to levels comparable to those delivered by bees, reduced pollen competition would presumably allow the majority of pollen grains to germinate and not just those that were most viable . This scenario should thus provide greater sensitivity to detect differences in how plants respond to self or non-self pollen under varying degrees of water stress. Squash rearing was performed in a similar manner to that in the Temperature x irrigation experiment, but in this experiment we grew C. pepo plants under different levels of irrigation and did not manipulate temperature. We used a drip-line system to irrigate plants every morning; the irrigation treatment included two levels: 2.4 L water/plant/day and 0.38 L water/plant/day . Mean volumetric water content for plants in the low irrigation treatment was 11% lower than that of plants in the high irrigation treatment . The volumetric water content for plants in the high irrigation treatment ranged from 41 – 54%, whereas that of plants in the low irrigation treatment ranged from 31 – 41%. All analyses are restricted to data collected from August 3 – September 8 during the height of flowering and pollinator visitation. Once squash plants began to flower, we hand-pollinated female flowers with either self pollen or non-self pollen from plants within the same irrigation group. We measured pollen deposition as in Irrigation experiment I and fruit set and seed set as in the Temperature x irrigation experiment. To test how soil moisture affects the seed set of flowers pollinated with pollen that varied in terms of its source and its identity, we considered two different measures of soil moisture. First, we used soil moisture values of the plants that produced focal female flowers. Second, we used the mean soil moisture experienced by the plants that provided pollen used for hand pollination . In the fruit set analysis, we did not use mean soil moisture experienced by the plants donating pollen because some plants had multiple chances to produce non-self fruits, and each of these chances utilized pollen from different plants with different soil moistures. To test how flowers pollinated with self pollen versus non-self pollen responded to soil moisture variation in terms of fruit set, we ran separate general linear models , each containing soil moisture as a fixed factor. Given the number of zero values in our data set , we used a zero-inflated negative binomial model using package gamlss to analyze seed set, which included zero values. This model contained two fixed factors, soil moisture and pollen type , and one random factor . We adopted this approach because as mentioned previously, plants in this experiment were given multiple opportunities to set fruit, and plants had the opportunity to grow both self and non-self fruits. We ran these models first using the plant’s soil moisture and then again using the mean soil moisture of the two plants donating pollen for the non-self fruits.From June through September 2018, we conducted a field experiment that involved irrigation and bee-pollination to test how pollen source affected the seed set of plants grown under different levels of soil moisture. For this experiment, we allowed bee visitation on plants grown under a gradient of soil moistures. Therefore, bees could move freely between flowers in both high-irrigation and low irrigation treatment groups and, consequently, deposit pollen from both high and low moisture plants on stigmas of plants grown under different levels of soil moisture. Squash rearing was performed in a similar manner to that in the Temperature x irrigation experiment, but in this experiment we grew C. pepo plants under different levels of irrigation and did not manipulate temperature.

Flavonols play an important role as antioxidants; for example, they protect ascorbic acid from autoxidation in juices and which can lead to juice discoloration. Although flavonoids are abundant in fruit, and fruits or beverages can be a significant source of dietary flavonoids, levels will vary depending on the varieties, environmental conditions, soil, and climatic factors. Berries are a good source of quercetin and its derivatives , whereas the most abundant dietary flavanone glycoside is hesperetin-7-O-rutinoside present in citrus fruits. Peterson et al. reported that the most prevalent dietary flavanone aglycones are naringenin, hesperetin, isosakuranetin, and eriodictyol. ,e same authors demonstrate that a citrus fruit is also a primary source of narirutin, eriocitrin, didymin, neohesperidin, naringin, hesperidin, neoeriocitrin, and poncirin. ,e ratio of these compounds to each other can vary. For example, narirutin and naringin were detected in grapefruit in high ratios, while the levels of hesperidin and narirutin in oranges and eriocitrin in lemons were even higher. In addition, some flavanone glycosides such as 7-rutinoside are tasteless, in contrast to neohesperidin , naringin, and hesperetin which have an intense bitter taste isolated from bitter oranges and grapefruit. Apigenin is another key flavone found in fruits, vegetables, spices, and herbs and is abundant in grapefruit, beverages, some vegetables, and herbal plants such as chamomile. Isoflavones are present in plants in the glycosylated forms but are converted to aglycone forms through the action of intestinal microflora. Isoflavones are detected commonly in legumes such as green beans, fava, and soybeans, and among them, container size for raspberries genistein -4H-1-benzopyran-4- one and daidzein -4H-1- benzopyran-4-one are the two major forms of dietary isoflavones and are consumed in soy products.

Fermented soy products also contain an additional seven isoflavone aglycones in significant levels. Due to the structural similarities to human hormone estrogen, isoflavones have potent estrogenic properties. Anthocyanins are another important class of flanovids that are colorful water-soluble glycosides and acylglycosides of anthocyanidins. 3-O-glycosides or 3,5-di-O-glycosides of malvidin, delphinidin, pelargonidin, cyanidin, petunidin, and peonidin are known as the most common natural anthocyanins and are classified based on the number and position of hydroxyl and methoxy groups. Anthocyanins are responsible for the brilliant colors of various plant parts including flowers and leaves and especially fruits having red, blue, purple colors, particularly strawberries, blueberries, black currants, cherries, raspberries, and red and purple grapes. Anthocyanidins are also responsible for the color of red wines. ,eir color based upon the degree of methylation and with pH is discrete from other phenolics by the range of colors each forms. Color differences of anthocyanins depend on the substitutions of the B ring, the pattern of glycosylation, and the degree and nature of esterification of the sugars with aliphatic or aromatic acids, and also on the pH, temperature, type of solvent, and the presence of copigments. Berries are a good source of anthocyanins, and 100 g of berries can provide up to 500 mg of anthocyanins. Flavan-3-ols have been previously reported as an antioxidant, chemopreventive, and immunoregulation agents. Procyanidins exist in a wide range of foods and often exist in foods in a range of galloylated forms. Most widely used techniques for phenolics are HPLC , LC/MS, GC , GC/MS, UV-Vis spectrophotometry, mass spectroscopy, electrochemical, and fluorometric methods. Liquid chromatography mass spectrometry is used to determine phenolics in both APCI and ESI techniques, ABTS+ and DPPH.

Sample preparation and extraction methods varied widely based on the nature of the sample matrix of the fruit or vegetable and based on the chemical structures of the phenolic compounds being extracted. As most samples contain a mixture of simple and complex polyphenolic compounds, such as phenolic acids, flavonoids, anthocyanins, and proanthocyanins, it is critical to choose a suitable method for sample preparation and extraction. Proteins, carbohydrates, lipids, or other elements may play negative effect to extraction of phenolics. In addition, it is not always possible to extract fresh samples, and special preparation techniques such as lyophilization, nitrogen pulverization, or drying may be needed. Particle size of extracted material and solvent-to-solute ratios need to be considered. As seen in Figure 1, there are many reliable qualitative and quantitative methods available for the measurement and characterization of the phenolic content in different natural products. Moreover, the success of these techniques will depend on the most effective sample preparation and extraction methods. Extraction efficiency is greatly influenced by solvent choice and composition and plays a critical role in the extraction yield of phenolics from fruits and vegetables. Generally, for the extraction of phenolics, water, acetone, ethyl acetate, alcohols , and their various percentages of mixtures are used. In addition to the solvent type extraction conditions, parameters such as temperature and duration also influence the yield of phenolics.Khoddami et al. previously reported that recovery of phenolics varied from one sample to another sample. It is also reported that acid- or base-catalyzed hydrolysis is also an important consideration for the stability of the phenolics in extracts. Davidov-Pardo and Marn-Arroyo reported that the extraction pH plays an important role in the extraction efficiency of phenolic compounds, and the same authors implied that catechins and their isomers are detected more efficiently in alkaline conditions as compared with acidic ones. Extraction of phenolic compounds are commonly done using either liquid-liquid or solid-liquid extraction technique. However, liquid-liquid extraction has some disadvantages because of using costly and potentially toxic solvents. For this reason, improved extraction methods such as solid-phase microextraction and solid-phase extraction techniques are used to extract phenolics from liquid samples.

In general, inexpensive and simple methods such as soxhlet, reflux, and maceration processes are the more conventional procedures used to recover phenolics from solid samples. In addition, ultrasound-assisted extraction , microwave-assisted extraction , ultrasound microwave-assisted extraction , supercritical fluid extraction , subcritical water extraction , and high hydrostatic pressure processing are the methods that help us to shorten extraction times and decrease the release of toxic pollutants through reducing organic solvent consumption and are relatively simple to perform. Pulsed electric field is also another extraction technique that can be applied at room temperature conditions and performed in a matter of seconds requiring low energy to increase cell membrane breakdown in mass transfer which were applied previously in several fruits such as strawberry and grapes.,e analysis of phenolic acids and flavonoids by liquid and/or gas chromatography techniques is the most widely and commonly applied methods for the quantification of phenolics in fruits and vegetables. In addition, spectrophotometric assays are used as nonspecific methods used for evaluating the levels of phenolics in many fruits and vegetables.Although, fruits differ in the quantity and types of phenolic antioxidants, degree of conjugation, and composition of sugar, total phenolic compounds can be estimated in fruits using the reagent proposed by Otto Folin and Vintila Ciocalteu and recently modified by Li et al.. ,is Folin–Ciocalteu method is robust, highly reproducible , convenient, and fast, requiring only a UV spectrophotometer. ,e method is typically standardized with either gallic acid, rutin, or a combination of pinocembrin/galangin. ,e Method is based on a reaction of the chemical reagent with phenolic electron transfer. ,e phenolic compounds are oxidized to phenolates by the reagent at alkaline pH in a saturated solution of sodium carbonate resulting in a blue molybdenum-tungsten complex and can be measured at 765 nm. ,e absorbance of each sample can be compared with those obtained from the standard curve, and the obtained data are expressed as µmol gallic acid equivalents per gram of fresh or dry matter. Because the reaction is quantitative and presumable, the analysis of a mixture of phenols can be recalculated based on any other standard. ,e assay comprises of monophenols and provides predictable reactions based on the phenols and provides measuring of all compounds readily oxidizable under the reaction conditions.Recently, chromatographic techniques such as highperformance liquid chromatography , HPLC electrospray ionization mass spectrometry , big plastic pots gaschromatography-mass spectrometry , capillary electrophoresis , and near-infrared spectroscopy techniques are developed for identification, separation, and quantification of phenolics. Phenolic content of plant materials can be measured and identified using HPLC employing different stationary phase-solvent combinations and various detectors. HPLC relies on comparisons of unknown compounds with standard reference compounds to make both qualitative and quantitative analytical measurements. Columns can be selected to impart specific separations based on the stationary phase type and the size and structure of the packing materials to which the stationary phase is bound to [52].

Detector choice can also be manipulated to enhance detection and especially quantifi- cation. Phenolic compounds can easily be measured using UV-Vis, photodiode array detection , fluorometric detection , and electrochemical detection . Each stationary phase-detector combination will provide specific information on the phenolic composition of a sample. For example, UV detection can be used to measure benzoic acid at 246–262 nm, gallic acid at 271 nm, and 275 nm for syringic acid. Two different wavelengths 225–235 nm and 290– 330 nm can be used to measure cinnamic acids, but the common wavelength of 280 nm is issued for the general analysis of phenolics. However, many factors such as sample purification, column and detector types, solvents used as mobile phase and solvent purity, and their pH affect HPLC analysis of phenolics. It is previously reported that mixtures of water, methanol, acetonitrile, formic and acetic acids, and trifluoroacetic acid are used for mobile phase for phenolic compounds in reversed phase chromatography using octadecyl silica columns. Generally, among the HPLC detectors, UV-Vis and DAD detectors are more common compared to the fluorometric detection . Common stationary phases include C18 RP columns employing an acidified mobile phase and ammonium acetate buffers of organic solvents . Detection efficiency can be improved by using SPE cartridges composed of styrenedivinylbenzene to purify phenolic compounds from crude extracts prior to HPLC analysis. ,e wavelength selected for monitoring phenolics is an important criterion and generally ranges between 190 and 380 nm. Gradient elution is generally preferred rather than isocratic elution. Some of the authors previously reported that phenolics such as flavonones, flavonoids, and flavan-3-ols of plum, blueberry, raspberry, strawberry, orange, apple, and tea are possible to be measured by common HPLC techniques. In general, for identification and quantification of phenolics, individual stock solutions of each standard are prepared in methanol and stored at −20°C until analysis. ,e working standard mixture solutions are made by diluting the appropriate amount of each stock standard solution to obtain at least 5 calibration levels. Measurements of flavanols, hydroxycinnamates, flavonols, and anthocyanins of fruits can be detected at 280, 320, 360, and 520 nm by using HPLC. External standards are used to quantify the phenolic compounds. Stable isotopes can also be used to quantify phenolic compounds when HPLC-ESI/MS is being used as described below.HPLC-ESI/MS is used to increase the range of phenolic compounds detected in a sample and to improve sensitivity as compared with standard chromatographic methods. HPLC-ESI/MS is a robust and selective quantification method that is effective at measuring the complex array of phenolics typically found in fruits and vegetables. Mass spectrometry methods can be performed on a variety of instruments including electrospray ionization ion trap instruments, triple quadrupole instruments , and time-of flight instruments . ,e mass spectrometer is an analytical detector that gives both qualitative and quantitative measurements based on separation of ions by their m/z ratio and 0.01% correction. Mass spectrometry involved three stages: ionization, mass analysis, and detection of ions. Separation of phenolic compounds is best achieved in aqueous-organic extracts of foods with HPLC prior to MS analysis although GC can also be used. ,e most common solvent reduction and ionization technique is electrospray ionization . ,is can be performed using different voltages to create negative or positive pseudomolecular ions that can be accelerated into the mass analyzer. ,e mass analyzer separates ions based on the flight path as with a magnetic /electric field separation, time-of-flight in a filed free region, or by altering ion trajectories using quadrupole and ion trap mass analyzers. Detection is usually achieved with an ion multiplier tube. Triple quadrupole analyzers and ion trap analyzers are often used when higher sensitivity and specificity, or structural information is required for identification. Fidelity of MS measurements can be increased using MS/MS techniques. For example, a common technique is to create product ions through collision-activated dissociation of selected precursor ions in the collision cell of the triple quadrupole mass spectrometer , analyzing the fragment ions in the second analyzer of the instrument .

Despite being non-native in the great majority of places where they were studied, honey bees were as efficient, on average, as the native floral visitors studied. The fact that honey bees are as efficient as the average pollinator, even where non-native, is perhaps not surprising since they are a super-generalist pollinator. As super-generalists, the honey bee is adept at extracting pollen and/or nectar from many plant species within a landscape rather than being specialized on one or two plant species. Such a generalist will develop strategies to exploit many types of floral architectures, although efficient exploitation of a floral resource does not necessarily correspond to efficient pollination. Body size may help to explain why honey bees are relatively efficient pollinators of the majority of plants they visit, despite their floral diversity. Honey bees have fairly large bodies, which may better facilitate pollen transfer compared to small bodied pollinators; for example in commercial apple, larger body size of bumblebees was suggested to explain their higher pollen deposition rates relative to smaller pollinator taxa . Honey bees were however less efficient than the top pollinator. This pattern may be partially a statistical artifact. Whenever multiple floral visitors are studied, even if they are all in fact equally efficient, the estimate for the efficiency of honey bees is expected to be less than that of the top pollinator /n of the time where n is the number of pollinating taxa studied. However, blueberries in containers growing honey bees were significantly less efficient than the top pollinator measured in 15 of the 34 plants studied. Honey bee generalist pollinating behavior may make them as proficient as the average floral visitor. However their generalist strategy could also explain the gap in efficiency compared to the top pollinator, which may be more specialized, at least in some cases.

Although honey bees were less efficient than the top non-honey bee pollinator, honey bees were no less important. Lack of a statistical difference between pollinator types may partly be due to lower sample size. However, given the data at hand any lack of per-visit performance by honey bees in comparison to the top non-honey bee pollinator was made up for by relative visitation frequency. We conclude that for plant species where honey bees are the most frequent floral visitor, they may often account for the majority of pollination services. Honey bee relative efficiency did not depend on whether or not a plant was domesticated, again suggesting that bees are reasonably efficient across species from a wide range of plant families and floral architectures. However, unlike undomesticated plants, honey bees were found to be less important for agricultural plants than the other pollinators studied though the sample size for domesticated plants is quite small . These plants may have been selected for study partially because of high visitation rates of non-honey bee species. Low relative honey bee importance in this small group of agricultural crops may also be due to special pollination systems for plant species studied; for example, tomato is buzz pollinated, but honey bees don’t perform buzz pollination and species of Cucurbita are visited by specialist bee species from the genera Peponapis and Xenoglossa that become locally abundant and move between flowers much more rapidly than honey bees, leading to high visitation rates. In sum, for plants where honey bees are frequent floral visitors, we can generally expect them to provide adequate pollination services in natural communities. As a result of habitat fragmentation or climate change, the pollination services from specialist pollinators species may diminish or be lost . Where specialist pollinators have been lost, our results suggest that honey bees may be able to substitute for the pollination services formerly provided by the pool of diverse pollinators originally present, for the plants they visit.

However, there may still be cases where, for particular plant species, the switch from one or more native pollinators to predominant visitation by honey bees could cause reproductive declines. Furthermore, given that, honey bees do not visit all plant species within natural communities , the integrity of plant reproduction on an ecosystem scale may still suffer with pollinator diversity loss, even where honey bees increase in abundance. Therefore, while honey bees, even where introduced, can provide important pollination services to naturally occurring plants, maintenance of a diverse pollinator assemblage may still be required to ensure adequate reproduction of entire plant communities. Further research is needed in order to more thoroughly understand community wide impact of changes to pollinator assemblages in response to current and future environmental stressors. Chapter 1, in part is currently being prepared for submission for publication of the material. Hung, Keng-Lou James; Kingston, Jennifer M.; Albrecht, Matthias; Holway, David A.; Kohn, Joshua R. Keng-Lou James Hung was the primary investigator and author for this paper.Approximately one-third of food produced globally is lost or wasted, yet fewer resources are devoted to postharvest research and development than to efforts for improving productivity. The modular design of plants allows plant tissues and organs to remain biologically active even after harvest. Therefore, capitalizing on the ability of harvested vegetables and fruits to continue to sense and respond to diverse stimuli, similarly to intact plants, may be a powerful approach to promote postharvest quality. Research demonstrating the biological advantage of a functional circadian clock in plants led us to investigate whether maintaining diurnal cycles may promote longevity and therefore reduced yield loss during postharvest storage of vegetables. The circadian clock enables plants to anticipate and prepare for the daily environmental changes that occur as a consequence of the rotation of the earth. Coordination of plant circadian rhythms with the external environment provides growth and reproductive advantages to plants, as well as enhanced resistance to insects and pathogens. The circadian clock also regulates aspects of plant biology that may have human health impact, such as levels of carbohydrates, ascorbic acid, chlorophyll, and glucosinolates in edible plant species.

Plants exhibit exquisite sensitivity to light stimuli, and isolated plant leaves maintain responsiveness to light after harvest and can continue light-dependent biological processes, such as photosynthesis. Additionally, the clocks of postharvest fruit and vegetable tissues can been trained with 12-hour light/12-hour darkness cycles producing rhythmic behaviors not observed in tissues stored in constant light or constant dark. A few studies have examined the effects of light on performance and longevity during postharvest storage. For example, light exposure delays broccoli senescence and yellowing but accelerates browning in cauliflower, a close relative of broccoli . Other studies report that light exposure to broccoli during postharvest storage either provides no additional benefits or decreases performance. Postharvest light exposure improves chlorophyll content in cabbage, but leads to increased browning of romaine lettuce leaves. Although exposure of spinach to light during postharvest storage can improve nutritional value, light can also accelerate spinach water loss, leading to wilting. Together, these findings are inconclusive as to whether light exposure during postharvest storage can be generally beneficial, and the variation of the results may be attributable to differences in the plant species examined and the specific conditions used during postharvest storage, such as lighting intensities, temperature, humidity or packaging. Alternatively, light may be advantageous but only if present in its natural context with 24-hour periodicity because of such timing on circadian clock function. This study aimed to examine whether mimicking aspects of the natural environment predicted to maintain circadian biological rhythms during postharvest storage of green leafy vegetables improves performance and longevity compared to postharvest storage under constant light or constant darkness. We focused this work on several popular and nutritionally valuable species, planting blueberries in containers including kale and cabbage , members of the Brassicaceae family with worldwide production of approximately 70 million tons. In addition, we analyzed green leaf lettuce and spinach , which have worldwide production of approximately 25 and 22 million tons, respectively. Here, we report on the promotion of postharvest longevity, including tissue integrity and nutritional value, of green leafy vegetables by provision of 24-hour light/dark cycles during storage compared to storage under constant light or constant darkness.Fruits and vegetables after harvest can respond to repeated cycles of 12-hour light/12-hour dark, resulting in circadian clock function and rhythmic behaviors. Because a functional plant circadian clock is physiologically advantageous we sought to address whether postharvest storage under conditions that simulate day/night cycles, thereby potentially maintaining biological rhythms, would affect postharvest longevity. We chose to address this question using green leafy vegetables, including commonly consumed kale , cabbage , green leaf lettuce and spinach , because we anticipated that the leaf organ would likely maintain light sensitivity and responsiveness even after harvest. To begin to determine whether daily light/dark cycles during postharvest storage affects leaf longevity, we compared the overall appearance of leaf disks that were stored at 22°C under cycles of 12-hour light/12-hour darkness versus leaf disks stored under constant light or constant darkness for various lengths of time . Under cycles of 12-hour light/12-hour darkness, kale leaf disks were dark green after 3 days of storage . After 6 days and 15 days of storage, the kale disks showed lighter green coloration than the kale disks stored for 3 days . However, the kale leaf disks stored under constant light were lighter green than the kale disks stored under light/dark cycles and showed some brown or yellow discoloration after 3 and 6 days . By 15 days, the kale leaf disks stored under constant light lost nearly all green coloration and showed light and dark shades of browning with shape changes resulting from leaf folding and shrinkage . The kale leaf disks stored under constant darkness resembled those stored under constant light, except that the 3-day kale samples were darker green than the 3-day constant light-stored kale leaf disks , suggesting that the constant light may have constituted a greater stress on the kale leaves than constant darkness. These results indicate that postharvest storage with daily cycling of light and darkness improved the appearance of the kale leaf tissue compared to storage under either constant light or constant darkness. However, the preservation benefit obtained from postharvest storage under light/dark cycles at 22°C appeared to be less than that provided by refrigeration; kale leaf disks stored at 4°C with constant darkness, were comparable in their dark green coloration whether stored for 3, 6 or 15 days . Cabbage leaf disks stored under cycles of 12-hour light/ 12-hour darkness showed brown spots along the disk edges that increased in intensity over the storage period of 7, 14, and 21 days . However, although the 7-day cabbage leaf samples were light green in coloration, the 14- and 21-day cabbage leaf disks stored under light/dark cycles had darker green coloration , suggesting increased photosynthetic activity over storage time. In contrast, although the cabbage leaf disks stored under constant light were also light green after 7 days of storage, the 14- and 21-day cabbage leaf disks were more yellow and included more brown discolorations . Remarkably, the absence of light exposure during post-harvest storage had a dramatic effect on the cabbage leaf disk coloration. Cabbage leaf disks stored under constant darkness at either 22°C or 4°C were pale tan or yellow after 3 days of storage . The constant darkness-exposed cabbage leaf disks stored at 22°C appeared nearly white in color by 14 and 21 days; those at 4°C had a yellowish appearance after 2 or 3 weeks of storage . Lettuce and spinach leaf disks tissue were nearly uniformly green, with little difference in color intensity between 3 and 6 days of storage under cycles of 12-hour light/12-hour darkness . By 9 days of storage under light/dark cycles, however, both lettuce and spinach leaf disks looked slightly less green, and most of the spinach leaf disks had distinct patches of yellow . In contrast, the loss of green coloration and increased yellowing over time was much more apparent in the lettuce and spinach leaf disks stored under constant light; the lettuce leaf disks were pale green by 9 days , and all the spinach disks had large yellow patches . After 6 and 9 days of storage under constant darkness, the lettuce disks had large wet patches of darkened tissue .

MS data was obtained using the positive scan mode for all of the extracts considered in the study. Compared to the underivatised UV-VIS and DPPH‚ chromatograms, the positive scan mode MS chromatograms show very different profiles . The cinnamon myrtle chromatograms are dominated by a peak that elutes with a retention time of 11 min. This peak does not appear in either the underivatised UV-VIS or DPPH‚ chromatograms. A small number of secondary peaks occur in both chromatograms, although they too do not appear to correspond to any major peak in either the underivatised UV-VIS or DPPH‚ chromatograms. Unlike the cinnamon myrtle, the negative scan MS chromatograms of the lemon myrtle are not dominated by a single peak, but show a number of peaks with similar intensity. Additionally, some of these peaks match in retention time to peaks that appear in the underivatised UV-VIS and DPPH‚ chromatograms. In particular, peaks with retention times of 3 and 4.5 min appear in a similar area of the chromatogram to peaks that respond to both underivatised UV-VIS and DPPH‚ . Additionally, the large peaks at around 12 min in the underivatised UV-VIS chromatograms appear as small peaks in the MS negative scan. As the number of peaks identified in the MS in positive scan mode was smaller than expected, growing raspberries in container the multiplexing experiment was repeated for the water extracts using both negative and positive MS scan modes. The water extracts were chosen as they showed the greatest number and intensity of antioxidant peaks in the DPPH‚ chromatograms. Both cinnamon myrtle and lemon myrtle showed a greater abundance of peaks in negative scan mode compared to positive scan mode.

Additionally, both chromatograms showed a large number of peaks eluting within the first 5 min of the chromatogram where the majority of the compounds that gave a response to DPPH‚ eluted. Table 1 shows the peaks that were detected in the DPPH‚ chromatograms along with the masses of those peaks as determined in the MS scans and possible identification based on the MS data. Due to the non-specificity of the MS scan, a number of the peaks that were identified in the MS data were due to more than one major m/z value indicating the presence of two co-eluting species being detected. Furthermore, a number of peaks that were detected in the DPPH‚ chromatograms did not show peaks in the MS data, indicating that these species did not ionise in the MS conditions used in the method. Additionally, it can be seen that a number of peaks that eluted had a m/z ratio that is either lower than typically observed in antioxidants, such as the peak at 0.5 min in the cinnamon myrtle water extract, or higher than that of typical antioxidants, such as the peaks at 3.3 and 4.6 min in the lemon myrtle water extract . This indicates that two different peaks may be eluting at these retention times, one of which is observed in the DPPH‚ chromatogram and the other that is observed in the MS chromatogram. Finally, it can be seen that where MS peaks were evident in both positive and negative scan modes, most of the peaks observed had very different m/z ratios in each mode, indicating the presence of co-eluting species. From the MS data it is possible to perform some investigation into the identification of the antioxidants that were present in the extracts. The m/z ratio of each of the peaks identified in the MS chromatograms was compared to the molecular masses of known antioxidants. If a match between the m/z ratio of the peak and the molecular mass of one or more antioxidants was found, this was considered a possible identification for that peak. For example, both lemon myrtle extracts show peaks with a m/z ratio of 139 Da indicating that the peak may be due to hydroxybenzoic acids.

However, positive identification is impossible without additional information such as MS/MS data and/or the comparison of the peaks with standard solutions. Due to the non-specific nature of the MS data that was collected in the study, only preliminary identification of the peaks could be performed. Thus a number of peaks could either not be identified or were identified as one of a number of possible antioxidants.In recent decades, advances in the final frost dates of winter or early spring have been observed throughout North America while advances in the timing of flowering have been documented in many angiosperm taxa . In response to recent climate warming, the flowering times of many species have changed, which may alter the risk of reproductive structures being exposed to spring frosts . Exposure of reproductive tissues to frost is hazardous for many plant species, as floral tissues are often the most vulnerable to frost damage, and the exposure of floral tissues to frost or freeze events can reduce pollen and seed production or result in reproductive failure . Over multiple generations, reductions in reproductive success due to increases in frost exposure may lead to progressive declines in local abundance, potentially resulting in local extirpation . Accordingly, the ability to initiate and to complete flowering and fruiting without exposure to frost or freeze events plays a major role in determining the geographic range of many species . Previous studies have predicted that progressive warming could increase the risk of frost damage to floral tissues for many species if,in response to warming, flowering times advance more rapidly than the date of last frost, defined as the date that marks the beginning of that portion of each year during which daily minimum temperatures remain above 0°C . This pattern has been particularly well documented among shrub and forb species whose flowering time is primarily driven by snowmelt , resulting in reductions to annual flower and seed production . Conversely, warming climates may advance the date of last frost more rapidly than plant species advance their flowering times, thereby reducing their risk of frost exposure ; this pattern has been detected among 14 European angiosperm species .

Warming conditions may also delay bud break and flowering of those taxa that require an extended period of winter chilling to break dormancy, protecting them from flowering prior to the onset of the frost-free period . While the phenological responses of flowering time to climate warming have been measured in thousands of species , and broad-scale temporal reductions in frost risk to developing leaves have been detected among North American trees , no large-scale examinations of shifts in frost risk have yet been conducted on a sufficient array of taxa to detect or to characterize general trends in a continental flora. As a result, the general effects of recent climate change on the risk of frost exposure to floral tissues remain largely unknown. Additionally, flowering phenology has previously been documented to be evolutionarily conserved among co-occurring taxa that are closely related . Given that exposure to frost depends on a species’ phenology at a given location, it is also possible that frost risk is phylogenetically conserved. However, no systematic examination of the degree to which frost risk is phylogenetically conserved among closely related taxa has yet been conducted. To address these gaps, we conducted the first continent-wide assessment of frost risk by evaluating the flowering times of 1,653 species collected in flower from 1920 to 2015 and represented by 475,694 digital records of herbarium specimens collected throughout North America, with specimens primarily concentrated in the Western and Eastern United States. By comparing rates of temporal changes in dates of last frost experienced by each species among the sites where it was sampled to rates of temporal changes in flowering date from 1920 to 2015, we determined that, for most species, the advancement of the last frost date has outpaced the advancement of flowering date, resulting in a reduction in the risk of floral exposure to frost. Furthermore, this pattern persisted across regions that historically experienced both early and late dates of last frost. We also conducted a phylogenetically informed analysis to determine whether,as has been found for flowering time itself , the risk of exposure to frost exhibits a phylogenetic signal. Finally, we compared the degree of frost risk experienced by native versus exotic species, and evaluated whether the relatively low risk exhibited by the latter is due to differences in the mean climate conditions they occupy or to differences between natives and exotics in the degree of phenological change that they exhibited.Phenological data pertaining to flowering times in this study consisted of 475,694 specimen records of angiosperm species collected in flower. These data were derived through filtering of a larger dataset consisting of 894,392 specimen records accessed from the digital archives of 72 herbaria , and cleaned using several criteria described below.

Estimates of mean flowering date from herbarium specimens have been reported to provide accurate estimates of species’ flowering times and have yielded estimates of phenological change similar to those derived from in situ observations of living plants across both temporal and spatial climate gradients . To ensure the quality of the data used in this study, large plastic pots for plants specimens were included in the dataset analyzed here only if, at the time of digitization, herbarium personnel had: verified that the specimens were collected when in flower; recorded GPS coordinates of the location from which the specimen was collected; and provided the precise date of collection . Only those specimens that were explicitly recorded as being in flower within either the DarwinCore “reproductivecondition” or “lifestage” fields of their source’s database were included in this study. Specimens that were listed only as “buds present” or “fruiting” were not considered to be in flower for purposes of this analysis, as some perennial species collected during the winter may be described as “buds present” when buds are completely dormant, or may retain aborted or unripe fruits that cannot be distinguished from recently matured fruits preserved on herbarium specimens. The taxonomic nomenclature used to identify all specimens, which sometimes changed over time or differed among collectors, was standardized according to The Plant List and TROPICOS using the Taxonomic Name Resolution Service iPlant Collaborative, Version 4.0 and subsequently filtered to eliminate all taxa not identified to species level within the megaphylogeny used by the PhyloMaker package in R , which similarly used a standardized taxonomy derived from TPL and TROPICOS . To avoid pseudoreplication, duplicate specimens were also removed. The resulting dataset included 475,694 specimens representing 1,653 species distributed throughout North America . In this study, we calculated the frost risk of each sampled species using annual estimates of the date of last frost at each collection site obtained from ClimateNA version 5.5.1. Frost risk of each species was defined as the proportion of its specimens collected in flower before the date of last frost in the years and locations in which they were collected. Frost risk in this context does not invariably predict the risk of reproductive damage, which depends not only on species- and population-specific cold tolerances, which are undocumented for most taxa , but also on microclimate conditions that cannot be easily incorporated into continental-scale datasets, such as humidity, wind speed, and recent precipitation . Nevertheless, temperatures of 0°C have been documented to damage floral tissues ofa wide variety of species , as radiative cooling often results in damage to floral tissues and emerging leaves under nighttime temperatures of 0°C even in species that otherwise remain hardy to subzero temperatures . Thus, frost risk is used here as a standardized metric indicating the likelihood of exposure of floral tissues to frost or freeze events.To estimate historical frost risk for each species, we calculated the proportion of specimens of each species collected from 1920 to 1979 that were collected prior to the date of last frost at the site and year of their collection. To estimate recent frost risk, we similarly calculated the proportion of specimens of each species collected from 1980 to 2015 that were collected prior to the date of last frost at the site and year of their collection . To ensure that a sufficient number of observations of each species were available to produce meaningful estimates of frost risk within both periods, we eliminated all species that were not represented by at least 50 specimens both prior to the year 1980 and after the year 1979.

A large number of these genes were identified as differentially expressed over the course of fruit development, which is consistent with previous studies of transcriptome changes during fruit ripening in sweet orange . However, most genes showed similar temporal expression patterns among all rootstock genotypes. Furthermore, only ~15% of the genes were genotype-specific . Therefore, the remainder of this study focused on DEGs identified between these rootstock genotypes during fruit development. A total 684, 388, 361, 178, 395, and 885 genes were significantly differentially expressed between RL vs SO, CZ vs SO, TF vs SO, RL vs CZ, TF vs CZ and TF vs RL rootstocks respectively . The majority of the differentially expressed genes are observed in comparisons involving rough lemon rootstocks, especially compared to trifoliate orange. This is consistent with the observed differences in fruit quality traits, as fruit of trees grafted on rough lemon rootstock showed consistent significant differences from fruit of trees grafted on the other three rootstocks in many of the traits measured . These results suggest that rough lemon and trifoliate rootstocks show the greatest effects on the scion and are good candidates to identify graft-related genes playing a role in fruit quality. The largest and most significant changes in gene expression between rootstocks were observed at time points two and three . Among the DEGs were several genes with functions involved in fruit quality traits, such as those relating to starch and sucrose metabolism, fructose metabolism, and hormone signaling related genes. KEGG pathway analysis displayed plant hormone signal transduction, carotenoid biosynthesis, plastic pots for planting and fructose and mannose metabolism pathways to be significantly enriched. Several genes involved in various hormone-signaling pathways were DE, mainly genes in the abscisic acid and auxin-response pathways.

Several genes involved in these pathways were chosen to validate the RNA-seq data by qRT-PCR due to their potential biological significance regarding rootstock effects on fruit quality.ABA has been known to be a regulator of fruit ripening and response to abiotic stress in non-climacteric fruit. AHG1, a homolog of Arabidopsis PP2C family protein, was DE in this study. PP2C is a negative regulator of the ABA hormone-signaling pathway. This gene was slightly up-regulated when comparing fruit of trees grafted on trifoliate to fruit of trees grafted on rough lemon rootstock at time two and significantly down-regulated at time three . Upregulation of AHG1 is in accordance with previous studies showing this gene being induced by water stress, which may have occurred in September. The downregulation of this gene later in the season could be correlated with increased fruit maturation in fruit grown on trifoliate rootstocks. This is in agreement with a study in tomato where suppression of PP2C expression led to increased ABA accumulation and higher levels of ABA-signaling genes that increase the expression of ABA-mediated ripening-related genes.Auxin signal transduction is mediated by Aux/IAA and ARF genes. Aux/IAA proteins are negative regulators of the auxin signal transduction pathway. In this study, a gene encoding an Aux/IAA protein, IAA16, was up-regulated in fruit grown on trifoliate compared to rough lemon rootstocks at time two and three . A previous study revealed that a gain-of-function mutation in IAA16 displayed reduced response to auxin and ABA, which led to reduced plant growth. Silencing of related Aux/IAA genes increased fruit size in tomato due to auxin control of cell expansion and elongation. In addition to Aux/IAA, another early auxin-response gene, SAUR78, was DE in this study. This gene was down-regulated in fruit grown on trees grafted onto trifoliate compared to rough lemon rootstocks at time two and three . Small Auxin Up RNA genes are a group of auxin-inducible proteins.

Other SAUR genes have also been shown to promote cell expansion. Furthermore, a MYB77 gene encoding a transcription factor was DE in this study, displaying a slight increase in expression in fruit grown on trifoliate rootstock at time two, but a large decrease in expression at time three . This gene was previously described as a regulator of the auxin signal transduction pathway. This protein was shown to interact with ARFs to promote plant growth. Interestingly, the effects of MYB77 in Arabidopsis were found to be increased by endogenous exposure to ABA and further promote plant growth. While these two studies were performed in roots, this transcription factor was shown to be involved in citrus fruit ripening, where it was highly correlated with ABA and suggested to have a similar function in response to the hormone.Although there were not statistically significantly differences seen in other genes in the auxin- and ABA-signaling pathways, trends could be observed during hierarchical clustering of these genes. Many of the genes within a family shared common expression levels and generally follow the predicted regulatory patterns in their respective pathways . Taken together, the changes in ABA- and auxinresponsive genes suggest a potential mechanism for induced ripening by trifoliate rootstock and larger fruit produced when rough lemon is used as a rootstock.The expansion phase of citrus fruit development involves cell enlargement and water accumulation. Given the changes in hormone-signaling pathways that likely lead to changes in fruit size, other genes related to fruit growth, such as transporters and genes related to cell wall metabolism were investigated. This led to the identification of two DEGs that could be influencing fruit size. The first, a Plasma membrane Intrinsic Protein 2 gene encoding an aquaporin was down-regulated in fruit grown on trifoliate rootstock . Water import in plants is mediated by aquaporins and essential for cell expansion.

These genes were highly expressed in expanding green grapes and one was identified as a candidate gene under the QTL for berry weight. PIP genes were also associated with an increase in volume of fruit in apple and strawberry. The second DEG, an expansin , was also down-regulated in fruit grown on trifoliate rootstock . Expansins play various roles in fruit development, including cell elongation and cell wall softening. A homolog of EXP1 in tomato was expressed during green fruit cell division and expansion with maximum accumulation of EXP1 during the late phase of green fruit expansion and early maturation. The increase in expression of these two genes in fruit grown on rough lemon rootstock could contribute to the larger fruit size observed. In addition to cell division and cell expansion, during fruit development, fruit softening is also an important feature that relies on cell wall metabolism. The Trichome Birefringence-Like gene, which encodes a protein required for cellulose biosynthesis, was identified in our study as DE. Mutations in this gene caused a reduction in the amount of pectins and an increase in pectin methylesterase activity. PME catalyses the demethylesterification of pectin, which may undergo depolymerisation by glycosidases. TBL23 was up-regulated in fruit grown on trifoliate rootstock compared to rough lemon , suggesting a potential role in fruit softening during citrus ripening. Transcription factors also play an important role in plant development and fruit ripening. Several transcription factors were differentially expressed in this study. GO enrichment showed the molecular function GO term ‘DNA-binding transcription factor activity’ was significantly enriched. In addition to the MYB77 transcription factor gene described earlier, a GRAS transcription factor gene, HAM3, was DE in this study. GRAS transcription factors were previously found to play a role in berry development and ripening in grapes, tomato, and citrus. This transcription factor showed increased expression later in the season when fruit were grown on trifoliate rootstock, drainage for plants in pots suggesting the rootstock influences its role in improved citrus fruit quality.The largest phenotypic differences seen in mature fruit grown on trifoliate compared to rough lemon rootstock were in the levels of total soluble sugar and titratable acid in ripe fruit. The levels of sugars and acids and their ratio in fleshy fruits is one of the most important determinants of sensory traits such as taste and flavor. Two genes were identified as differentially expressed that could play a role in the accumulation of these compounds. Firstly, a P-type ATPase was DE in fruit growing on trees grafted onto trifoliate versus rough lemon. This gene was down-regulated at time two, but upregulated at time three . Studies have proposed a number of ATPases as proton pumps that are responsible for organic acid accumulation in citrus fruit.

The reduced expression of this ATPase gene later in the season in fruit grown on rough lemon rootstocks could contribute to the lower accumulation of titratable acid levels in these fruits. This ATPase gene identified in this study was not identified in the previous citrus studies, but the regulation of acid accumulation is a complex, as can be seen in other fruits, such as papaya and apple. It is possible this is a graftinduced effect observed with these specific rootstocks, which were not examined in the previous studies. Secondly, a homolog of Arabidopsis BETAFRUCT4 was down-regulated in fruit of trees grown on trifoliate rootstock compared to rough lemon at time three . This gene encodes a vacuolar invertase. Decreased expression of vacuolar invertases has been associated with increased sucrose content and accelerated ripening. Interestingly, by using an antisense acid invertase gene in transgenictomato to reduce acid invertase activity, fruit displayed higher levels of sucrose, as well as smaller fruit. We see similar trends in sugar accumulation and alterations in fruit size in this study. Klann et al. suggested that the water influx that drives fruit expansion is closely related to the concentration of osmotically active soluble sugars and therefore, all genotypes accumulate water until they reach a similar threshold of soluble sugar concentration. This could also contribute to the increased size of fruit grown on rough lemon fruit compared to trifoliate rootstocks.This study did not identify any statistically significant differentially expressed miRNAs from our fruit small RNA seq data. Therefore, potential miRNAs that target DEGs were predicted. An in-house R-script was used to select for miRNA-mRNA interaction pairs with an expected negative correlation in gene expression. These pairs were identified for the ten genes described above. All ten miRNA genes and their target mRNAs were detected by qRT-PCR. Pearson correlation coefficient value between the relative expression level detected by qRT-PCR and by RNA-sequencing was highly significant with r = 0.94. Of the ten interaction pairs, eight followed expected fold changes between timepoints . Therefore, it is likely that these eight target mRNAs are being regulated to some extent by their respective miRNA.Citrus is now grown in more than 140 countries in tropical, subtropical and Mediterranean regions. It is one of the most economically important crops in the world. Citrus are rarely grown from seed and virtually all commercial citrus is propagated by grafting. This reduces the juvenile phase, allowing for the trees to produce fruit many years earlier than would trees grown from seed1 . Due to the large variation in growing conditions and climate in the regions where citrus is grown, different citrus rootstocks are required to improve yield and fruit quality in numerous diverse climates, as well as resist various pests and diseases. Rootstocks impart certain traits to the scion and the effects of rootstocks can be large. The most significant impacts are on growth, vigor and yield, tree nutrition, stress resistance, and fruit quality. The rootstock effects on various aspects of tree growth and fruit development are well documented, but the molecular mechanisms underlying most of these differences are unknown. Previous studies have shown changes in the transcriptome of various rootstock genotypes, especially in response to biotic and abiotic stressors. These types of changes have been seen in Arabidopsis, corn, mulberry, tomato, and poplar. In citrus, gene expression profiling has been used to understand rootstock effects and responses to biotic and abiotic factors. In another study, expression studies of leaves from mandarin grafted onto various rootstocks were analyzed in order to explain rootstock effects on the growth of scions. There is extremely limited tissue-specific transcriptome knowledge in citrus, especially for root tissue. A small number of studies have evaluated trifoliate, trifoliate hybrid, and mandarin root transcriptomes in response to citrus diseases, but these studies each assessed only one genotype. Only recently has an RNA-seq based approach been used to establish a reference transcriptome for citrus and of the 28 samples used in the study, only two were obtained from roots.

Urban ecosystems are temporally dynamic systems, yet historical factors associated with land use legacy and time lags as a result of development have largely been overlooked. Because human-altered landscapes are relatively recent, it is particularly important to recognized that the observed biodiversity may be undergoing a process of change from the previous land use type to the new one when interpreting observations. Just as urban ecosystems are dynamic across years, they are also dynamic intra-annually, with resulting phenological shifts within urban landscapes compared to surrounding natural habitat. The urban heat island effect is a well-documented phenomenon where the city environment can be significantly warmer than the surrounding landscape as a result of impervious surface area that retains heat and higher energy usage, causing changes in the timing of ecological patterns. As a result, plants bloom earlier the more densely urban the surrounding habitat is and bird migration advances earlier in urban contexts. Another potential effect of land use change in urban and agricultural landscapes beyond climatic can be the variety and timing of floral resource availability. Urban areas, while having less green space, often grow many exotic plants which are supplemented with water and nutrient inputs that allow for an extended flowering season. As a result, urban areas are characterized by relatively low , but constant, floral resources throughout the year. Agricultural landscapes have large patches of dense, often homogenous, floral resources that will fluctuate greatly from early spring to the end of the summer due to mass-flowering monoculture crops. In contrast, pot with drainage holes many natural areas in California experience a large burst of diverse floral blooms in the spring, and by the end of the summer, there are very few floral resources available.

Bees provide the majority of animal mediated pollination services on which an estimated 87.5% of flowering plants depend . The value of pollination in agriculture is estimated at $200 billion worldwide, largely due to many foods that are essential for food security and a healthy human diet, including numerous fruits, vegetables, and nuts that require bee pollination. In addition, there has been growing interest in urban agriculture to ensure food security and access to healthy foods for urban populations. One study estimated the economic value of urban fruit trees in the one city of San Jose, California to be worth $10 million annually. Honey bee populations and many bumble bee species are declining worldwide, while many other bee species have not been closely documented enough to determine their status. One of the reasons proposed to be negatively affecting bee populations is land use change. A review of 265 papers studying the effect of land use change on pollinator populations found more negative than positive impacts with a wide window of variability. This could partially be attributed to the wide diversity of pollinators themselves, as well as the varying definitions that people use to constitute land use change. We propose that an additional cause of high variability can be explained by investigating how the seasonal patterns of bee communities may shift in different neighboring land use types which experience highly different availability and suites of floral resources. Although bee seasonality has been documented in urban and agricultural landscapes, no studies to our knowledge have specifically investigated the differences in seasonal patterns of population abundances of bees between human-altered landscapes and neighboring natural habitat, despite the established seasonality of bees and variability of floral resource availability.

Bees are often sampled throughout the season, but all of these data are typically lumped together, potentially obscuring subtleties in change . Here, we investigate how local bee communities shift over the course of the flowering season in urban, agricultural, and natural land use types. We make use of a “natural experimental design” in which urban, agricultural, and natural areas intersect in a peri-urban landscape on the outskirts of the San Francisco Bay Area in Contra Costa County, California. To study the impact of changing land use on local bee community population dynamics, we sampled the bee community flying through the landscape at four time points over the course of the season for three years at 24 sampling locations.At each site we laid out a standardized pan trapping transect of fifteen 12 ounce bowls spaced 5 meters apart in alternating colors of fluorescent blue, white, and fluorescent yellow. Bowls were filled to the brim with soapy water . In 2010, transects were set up for a 4 hour period between 10:30am to 2:30pm , with 4 sites sampled per day, and all sites sampled on consecutive days. These 2010 transects were run twice, once in the early summer, and once in the late summer. In 2011 and 2012, sampling was conducted over a 24 hour period, so that more sites could be run simultaneously and more samples could be collected per site per year. All 24 sites were sampled within two consecutive collecting windows , and were run four times each year: early spring, late spring, early summer, and late summer. Because we were interested in landscape level effects, we tried to control local variables as much as possible. All sites were selected in easily accessible, open areas that received full sun. Natural areas were in grassland habitat, so we selected agricultural sites that were either weedy field margin edges or fallow fields, and urban sites that were vacant lots or green ways.

The human-altered sites were deliberately selected to not be adjacent to any mass flowering plants of agricultural crops or gardens. The goal of collection was to sample the bee community that was flying through the site searching for resources. Bees were collected from the pan traps by using a metal strainer, rinsed with water, frozen overnight or longer, and then pinned and labeled. Specimens were sorted to the genus level, and then to the species level with the assistance of Dr. Robbin Thorp , Professor Emeritus, UC Davis. The only exception to identification at the species level were bees of the genus Lasioglossum, large pot with drainage due to their overwhelming abundance, limited availability of taxonomic expertise for this group, and lack of known ecological diversity. Voucher specimens and the majority of the total collection will be deposited at the Essig Museum of Entomology at UC Berkeley.For response variables including aggregate bee abundance, species richness, Shannon diversity, and number of rare species, we tested for the effect of land use type, seasonality, and their interaction with generalized linear mixed models using the R package lme4. We designated collecting method , land use type, seasonality, and the interaction of land use type and seasonality as fixed effects, and site and year as random effects. We analyzed the effect of time both categorically by collecting period and continuously by day of year. Day of year was normalized on a scale of 0 to 1 from the first collecting date to the last. Shannon diversity was fit with a Gaussian distribution while all other variables were fit with Poisson distributions.We found that the bee communities in human-altered landscapes experienced different phenological patterns than the neighboring natural areas. Increased temperature in urbanized areas as a result of the urban heat island effect is often cited as the driving force for changed ecological dynamics. We propose another driver of local phenological shifts: the timing and quality of floral resource availability, due to irrigation that extends the flowering season throughwater inputs and landscaping choices in urban residential, public, and commercial zones, as well as mass flowering crops in agricultural fields. For example, Eucera actuosa was collected most frequently in human altered sites in the early spring and very little in late spring, whereas in natural sites it was collected in lower numbers in early spring and peaked in late spring. Another bee, Melissodes lupina , is a later flying bee than E.actuosa and experienced the opposite pattern. Melissodes lupina was collected most frequently in the early summer for natural areas, but was collected more often in the late summer in human-altered landscapes. Both E.actuosa and M. lupina demonstrate a pattern of relative abundance of species being shifted in different land use types. Even further, the temporal direction of relative abundance in both examples areas skew towards higher abundance during the middle of the season for natural areas and higher abundance at the more extreme ends of the season in the human-altered landscapes.

In other words, these are not simple patterns where species in human-altered landscapes always are collected earlier, which is generally the result of the urban heat island effect. Instead, this is likely due to irrigation effects extending flowering times in human-altered landscapes that provide bees with necessary resources for extended flight periods. This supports our theory that patterns of change in bee community distribution throughout the year are a result of the different land use types offering variable seasonal floral resources. While ecologists have used time as an important variable in many different systems, only recently has time begun to be incorporated into urban ecology. These differences in relative bee abundance throughout the year could be the result of resource tracking or a shift in emergence timing between different land use types. Shifts in plant phenology have been well documented in temperate urban landscapes. Urban areas have been associated with earlier plant blooming closer to the city center, and the urban heat island effect also can directly affect animal populations. In addition, historical temperature and museum collection records show a link between climate change and advancing bee emergences. Bees could be responding to local climatic differences or floral availability respectively, with both emergence timing and length of the flight season of bee species being impacted differentially at a micro-scale between different land use types. Pollinator responses to land use change are generally more often negative than positive, although there is high variability of outcomes due to many different experimental design types, systems, and the use of simple community metrics rather than more species specific analyses. Using functional groups such as nesting type, generalized foraging , and sociality, more patterns have emerged about traits that may be most sensitive to anthropogenic disturbance, although the type of disturbance will affect bees differently. For example, ground nesting species may be more successful in intensified agricultural landscapes, while cavity nesting species may be more common in urban landscapes because of increased nesting resources. We had 7 species that were collected almost exclusively in human-altered sites . These species positively associated with anthropogenic change covered a range of functional groups for sociality, nesting type, foraging generalism, size, and distributional range. Two of these are non-native , and as a group they have a wide diversity of life history traits. For example, Ceratina dallatorreana, a species of small carpenter bee originally from theMediterranean region first collected in California in 1949, has the unusual life history trait of female parthenogenesis in its local population here. Megachile rotundata is another nonnative bee accidentally introduced to the United States from the Mediterranean , is a solitary leaf cutter species that have become an important managed pollinator in the Western United States. Andrena chlorogaster, is a native California bee, with a generalized life habitat and wide range, while the squash bee, Peponapis pruinosa, is a solitary specialist on cucurbits. These species that favor human-altered landscapes not only fail to share many life history traits, but they are also diverse phylogenetically, comprising several different bee families. These different patterns of bee distributions could be the result of two possibilities: either bee populations are tracking resources between the different land use types, or the bee communities in the different land use types are experiencing different emergence timing. Bee movement has been notoriously difficult to study because of the size, mobility, and life history of this group. Some species and system-specific conclusions about bee foraging distances and size based models of foraging distances have been made. However, these are all based on foraging movements anchored around a central nest that a female bee is provisioning, and in contrast almost nothing is known about dispersal movement—in other words, how far bees might travel from their emergence site to mate and select their own nest site.

Environmental studies professor Greg Gilbert and Center director Carol Shennan served as faculty advisors to the project, with Leap, garden manager Christof Bernau, and members of the apprenticeship course offering additional advice and information. Research for and development of the web site was supported by funds from the Center’s competitive research grants program .Blueberries offer small-scale growers a potentially profitable “niche” crop that can be developed as a U-pick operation or incorporated into other marketing activities. Although the plants need several years to get established and require careful soil preparation and fertility management, a successful blueberry crop can generate $30,000 to $50,000 per acre . To learn more about the best-performing varietal options for organic growers on California’s central coast, the Center initiated a variety trial of mostly low-chill, highbush blueberries at the UCSC Farm in the fall of 2003. This project is being conducted in collaboration with Aziz Baameur, Small Farm Program Advisor for Santa Clara County’s UC Cooperative Extension office, and Mark Bolda, UCCE’s central coast Strawberry and Caneberry Advisor. Blueberries need well-drained, acidic soil in order to thrive. In November 2003, UCSC Farm manager Jim Leap applied sulfur to the trial site at a rate of approximately 2,000 pounds per acre as well as 3–4 inches of acidic mulch, then created raised beds for the plants. With the help of second-year apprentices Aaron Blyth, Carissa Chiniaeff, Allegra Foley, Estrella Phegan, Ratoya Pilgrim, and Matthew Sutton, round pot the research team planted out 17 varieties of blueberries in January 2004. The trial includes 4 replicates of each variety planted on 3-foot plant in-row spacing with 5 feet between rows.

Peat was applied in the planting hole to further lower the pH. Varieties being tested are: Biloxi, Bluecrop, Duke, Emerald, Jewel, Jubilee, Misty, Oneal, Ozarkblue, Millennia, Santa Fe, Sapphire, Sharpblue, Southern Belle, Southmoon, Star, and Windsor. After planting, the beds were mulched with several more inches of acidic bark, and drip tape was laid on top of the mulch. Plants are irrigated weekly with the drip tape, and during each irrigation vinegar is injected into the irrigation water to maintain a low pH. Phytamin, a liquid nitrogen fertilizer, is being applied through the drip lines monthly during the summer to maintain adequate nitrogen levels and get the plants off to a strong start. Over the next several years, the research group will evaluate a variety of factors, including overall plant vigor, disease and pest resistance, and eventually, harvest dates, fruit taste and quality, and fruit production. Although the first harvest is still 12 to 18 months away, Leap is excited about the trial. “Blueberries offer a great marketing opportunity for small scale organic growers,” he says, adding that, “this project has also created great opportunities for interactions between the Center and our local UCCE advisors.” A blueberry field day organized by the Center, UCCE, and the Community Alliance with Family Farmers was held in early June, bringing farmers and gardeners to the UCSC Farm for a look at the new plantings. Speakers included Baameur, Leap, and Bolda, as well as UCCE researchers Richard Smith, who discussed organic weed management, and Laura Tourte, who talked about blueberry economics and marketing.As an environmental scientist, Center faculty affiliate Deborah Letourneau believes policy decisions should be based on the best information available at the time. That’s why she’s trying to fill an information gap with her latest research on genetically modified plants.

As insect-resistance is bred into major crops, Letourneau wonders how those crops’ wild relatives might be affected if they pick up the new traits. “There’s been a lot of research on crop-to-crop movement,” said Letourneau, referring to the contamination of organic corn grown adjacent to genetically modified corn. “But we don’t know that much about the biology of wild crop relatives. If genes transferred, would it make them more weedy, more hardy, more invasive?” To address these questions, Letourneau, a professor of environmental studies at UCSC, along with doctoral candidate Joy Hagen and Ingrid Parker, an associate professor of biology, have begun a three-year study to see what the consequences would be if GM genes transferred from Brassica plants through cross-pollination to their wild relatives. Plants in the Brassica, or cole, family include many vegetable crops, such as broccoli, Brussels sprouts, cabbage, cauliflower, and kohlrabi, as well as common weeds like wild radish and wild mustard. “Weed problems translate into economic problems for farmers,” said Letourneau, noting that 75 percent of cole crop production in the United States is concentrated on the Central Coast of California. Stubborn weeds require more herbicide applications, with accompanying higher labor costs and environmental impacts, she said, adding that highly invasive weeds can threaten native species on non-agricultural lands, too. Letourneau is a leading authority on the genetic modi- fication of plants. A member of the National Academy of Sciences’ 12-member panel investigating the environmental consequences of GM plants, she also coedited the 2002 book, Genetically Engineered Organisms: Assessing Environmental and Human Health Effects. Parker’s background is in applying mathematical models to ecological risk assessment for GM crops. A growing number of crops are being genetically modified to increase insect resistance. More than 25 percent of corn grown in the United States has been genetically engineered to contain the toxin of the Bacillus thuringiensis soil bacterium, which disrupts the digestive system of a caterpillar.

Transgenic cotton and potatoes also produce Bt toxin. Little is known about the role Bt-susceptible herbivores, round plastic planter including caterpillars, play in regulating the health and spread of wild crop relatives. In their research project, Letourneau and Hagen are protecting wild relatives from caterpillar damage to see what could happen if modified genes moved from Brassica crops to their wild relatives. The simulation is necessary because the research is being conducted in open fields—not inside greenhouses—where risks of contamination by GM plants would be high, said Letourneau. To mimic an effect of gene transfer, the UCSC researchers are spraying Bt on wild radish and wild mustard growing adjacent to commercial cole crops, and they will use models to evaluate the subsequent fitness, weediness, and invasiveness of the weedy relatives, said Letourneau. “We can’t use real transgenic crops, but we wanted to conduct this work where wild relatives live side-by-side with commercial crops,” said Letourneau. Research sites include the Center’s on-campus Farm and agricultural parcels adjacent to natural ecosystems from Wilder State Park to Elkhorn Slough Reserve. Genetic links between crops and weeds are remarkably common, and cole crops are no exception, noted Parker. “In the past, the evolution of many weeds has been driven by genes coming from crops,” she said. “Now those genes will be specially engineered by humans.” Research on consequences for wild relatives is overdue, said Letourneau, noting that field-testing of GM cole crops for California has been under way since 1999. “This kind of research is important now, during the process of risk assessment, to know whether new modified crops should be deregulated or not,” she said. “There are a lot of Bt crops in the pipeline. Anything we can find out now can be used by regulators to make more informed decisions.” Letourneau takes nothing for granted as the research gets under way. The project will use a large number of sample plants on varied research sites, and the experiments will be replicated over three years. Hazards of GM corn, including allergenicity and contamination of adjacent fields, were identified during extensive testing that was required because it is a food. Because similar tests are not required on nonfood plants, it’s harder to know what the hazards might be, and what the probability is that they’ll occur, said Letourneau. “It might be that transgene movement to wild relatives would be no problem at all,” she said. “If we don’t detect any problems or hazards, we’ll feel we’ve tried to provide the data needed for risk assessment.” The three-year project is funded by a $335,000 grant from the U.S. Department of Agriculture.Botta’s pocket gopher , the smallest gopher in the U.S. at approximately 6 inches long, is the dominant species in central California. The pocket gopher is named for the external cheek pouches it uses to carry food and nesting materials down into tunnel storage areas. They feed on a wide variety of vegetation, but generally prefer herbaceous plants, shrubs, bulbs, and trees. Gophers can bear two to four litters per year of up to ten pups each , so populations can climb quickly under ideal conditions. Once weaned, the young disperse immediately, traveling on the surface to search for new, unoccupied territory. Except during the breeding season, pocket gophers are solitary and territorial. Population densities average approximately 30–40 per acre, although up to 200 per acre have been observed where food is plentiful and other conditions are favorable. As they dig their burrows, gophers push soil to the surface, creating mounds of loose soil adjacent to the plugged burrow entrance. A gopher usually creates one to three new mounds per day, excavating and constantly enlarging and moving its main feeding burrow. Gopher numbers are often overestimated due to this activity, and to the mistaken belief that gophers live in colonies. Because they are quick to repopulate empty burrow systems it may appear that the burrows are populated communally, when in fact gophers will fight to the death to protect their territories.By thinking of a gopher infestation as a pest problem that has similar attributes to, for example, an insect pest problem, cultural practices can be adjusted to create conditions that discourage the presence of gophers. As with other pests, gopher populations increase when food is abundant. Leaving overwintering corn trash or other culls that do not decompose rapidly in the field will boost the gopher population. Weeds that gophers prefer to feed on, such as malva , dock, clovers and dandelions, will also help maintain a higher wintering population. Artichokes and other crops with large crowns are especially susceptible, and some growers have begun to grow these crops as annuals in part to avoid building up gopher populations in the winter season. Young orchard trees seem to provide the most winter-time food for gophers; however, mature orchards and vineyards also harbor gophers through the winter months.Some cover crops can both benefit your crop rotation or winter fallow and help limit gopher populations. Research has shown that gophers much prefer clover cover crops over small grains such as barley, oats and Sudan grass. And although most clovers attract gophers there is a sour clover that appears to discourage them. This can be used as a winter cover combined with a small grain to move populations out of the fields to areas where they can be trapped. I’ve also observed that gopher populations move to farm road edges and other border areas when a winter cover crop of bell beans or fava beans are planted. A focused trapping effort in these areas during winter will help limit breeding numbers. Be aware, though, that many studies have shown gophers to be extremely adaptable in their feeding habits, so no cover crop will guarantee a gopher-free field. When considering rotations on diverse farms, include gophers in the equation. If you follow a crop that attracts gophers, such as potatoes, with another that they feed on, like onions, you will exacerbate gopher problems by providing a continual food source. However, if you follow potatoes with a sour clover or small grain, populations are less likely to rise.Farmers and gardeners have tried all manner of barriers to discourage gophers. These include wire mesh, gravel, trenches filled with glass and rocks, corrugated roofing, even trenches with buried buckets that act as pitfall traps—anything that presents an obstacle for persistent gophers. These all have some effect on slowing invasions. The most promising approaches are those that create both an above- and below-ground barrier. One of the most successful is fencing made of steel corrugated roofing. Not only is it impenetrable, but gophers cannot climb the exposed portion. Because gophers can scale a welded wire fence, above-ground wire barriers must have the wire bent outward at the top or a wooden or metal rim installed. I’m currently experimenting with a material called “Root Guard,” a thirty-six inch wide plastic sheeting seventy mils thick used by landscapers to keep bamboo roots from spreading.

Root dry weight of inoculated plants was highest after using oxathiapiprolin at either rate or fluopicolide at the high rate in both experiments, mandipropamid at the high rate in the second experiment, or fluopicolide at the low rate in the first experiment. Increases as compared to the control ranged from 192.8% to 306.5% . Root dry weight was not significantly different as compared with the control after potassium phosphite treatment in the first experiment.In this study, the four new Oomycota-targeting fungicides ethaboxam, fluopicolide, mandipropamid, and oxathiapiprolin demonstrated high in vitro toxicity with relatively low mean EC50 values to the avocado root rot pathogen P. cinnamomi. The in vitro sensitivities for each of these compounds displayed a unimodal distribution and a narrow range of EC50 values for mycelial growth inhibition of 71 isolates representing the current P. cinnamomi population in major avocado growing areas in California. The narrow ranges in sensitivities among isolates with no distinct less sensitive outliers in the distribution may suggest a reduced potential for selection of resistance with the proper use of these fungicides. Because P. cinnamomi isolates were never previously exposed to ethaboxam, fluopicolide, mandipropamid, and oxathiapiprolin, the sensitivity ranges reported herein can be referred to as baseline distributions that can be used as references in future monitoring for fungicide resistance in populations of the pathogen.In our study, 10 liter drainage pot oxathiapiprolin had the lowest EC50 values for all isolates among the new fungicides evaluated ranging from 0.0002 to 0.0007 µg/ml. This fungicide also was shown to be highly inhibitory to other Phytophthora spp. from a wide range of hosts by others with mean EC50 values of less than 0.001 µg/ml .

Similarly, Gray et al. found that oxathiapiprolin had the lowest range of EC50 values of 0.0002 to 0.0015, 0.0002 to 0.0003, 0.0003 to 0.001, and <0.0003 µg/ml for P. citrophthora, P. syringae, P. nicotianae, and P. hibernalis, respectively, as compared with the other three compounds. Together, reported inhibitory values for oxathiapiprolin are generally 10- to 1000-fold lower than those for ethaboxam, fluopicolide, mandipropamid, and mefenoxam, depending on the fungicide-species combination. Thus, the in vitro toxicity of oxathiapiprolin to P. cinnamomi from avocado reported in our study is lower than for any previous fungicide evaluated against this pathogen. EC50 values for fluopicolide, mandipropamid, and ethaboxam for P. cinnamomi in our study were also within the range of values previously determined for several other Phytophthora spp. . The range of EC50 values for mefenoxam in our study was similar to that previously reported for P. cinnamomi from avocado , Fraser fir , and woody ornamentals in the United States. Thus, the current usage pattern for this fungicide to control avocado PRR in California nurseries and orchards has not resulted in mefenoxam resistance in P. cinnamomi populations.In contrast to the other fungicides, a wide range of in vitro sensitivities was detected for potassium phosphite, and there was a significant difference in mean EC50 values between isolates from the two geographical regions, confirming a previous report . The higher value for isolates from southern California production areas may be due to higher field rates or more frequent applications of potassium phosphite to manage PRR in avocado orchards. The bimodal distribution for the 71 isolates in this study separates the current pathogen population into two sensitivity groups indicating a shift in population sensitivity. A baseline for this compound, however, was never established before commercial field usage. Still, prolonged use of phosphite caused a shift toward reduced sensitivity of P. cinnamomi isolates from avocado orchards in Australia and South Africa .

Phosphonate resistance has also been reported for P. cinnamomi from Chamaecyparis lawsoniana in nurseries , downy mildew of lettuce , and recently in P. citrophthora, P. nicotianae, and P. syringae from citrus in California . With direct and indirect effects on the pathogen, the resistance potential of potassium phosphite is considered relatively low . The extensive and often sole use of this FRAC group in California avocado orchards to combat PRR , however, is expected to eventually lead to resistance. In our greenhouse studies, avocado seedlings and rootstocks were inoculated with P. cinnamomi isolates from southern avocado production areas that have been described as more virulent . A high incidence of PRR developed on untreated control plants of seedlings and both rootstocks with more than 75% of plated root pieces colonized by the pathogen. The high incidence on the Dusaâ rootstock that is considered more tolerant to PRR is likely due to our selection of discolored root pieces for plating of all samples. The four new fungicides were moderately to highly effective in reducing PRR and P. cinnamomi populations in rhizosphere soil of the avocado seedlings and rootstocks used. Overall, oxathiapiprolin was the most effective among fungicides evaluated. In experiments with Zutano seedlings, the efficacy of oxathiapiprolin at the low rate of 70 g/Ha was 2- to 33-times higher than that of the other fungicides and 2- to 4-times higher than that of mandipropamid, a CAA fungicide. In a study on managing P. capsici on peppers , the difference in effectiveness of oxathiapiprolin at 30 g/Ha as compared to the CAA dimethomorph at 262.5 g/Ha was similar to our study using the same FRAC codes of fungicides. In response to reducing PRR, avocado plants treated with oxathiapiprolin generally developed more shoot and root growth as compared with untreated plants. On the avocado seedlings and rootstocks used, fluopicolide, mandipropamid, and ethaboxam treatments also effectively reduced the incidence of PRR compared with the control. P. cinnamomi propagules in the rhizosphere soil were only significantly reduced on the Zutano seedlings and the Dusa rootstock. These latter treatments were often significantly more effective than potassium phosphite or mefenoxam; whereas fluopicolide often performed statistically similar to oxathiapiprolin. Still, the efficacy of potassium phosphite was demonstrated with significant reductions in PRR on the seedlings and rootstocks although its overall performance may have been compromisedby the use of three P. cinnamomi isolates with reduced sensitivities to the fungicide in our soil inoculations. These results also could explain why potassium phosphite is still effectively used in managing PRR in California since many growers cultivate avocado trees grafted on the Dusaâ rootstock. Thus, highly effective alternatives to mefenoxam and the phosphonates were identified by us for the management of avocado PRR. Oxathiapiprolin, fluopicolide, mandipropamid, and ethaboxam previously demonstrated high efficacy against selected foliar and root diseases of vegetable and tree crops caused by Oomycota organisms in greenhouse and field studies. Thus, the four fungicides were highly efficacious in reducing Phytophthora root rot of citrus caused by P. nicotianae and P. citrophthora . Oxathiapiprolin, fluopicolide, and mandipropamid were more effective in managing P. capsici on watermelon than mefenoxam or potassium phosphite . In other studies, oxathiapiprolin was shown to be highly effective in managing diseases of vegetable crops caused by Phytophthora species including P. capsici and P. infestans and controlled black shank of tobacco caused by P. nicotianae . Ethaboxam was shown to be an effective treatment for tomato late blight , as well as Phytophthora blight of pepper .

Based on our studies, 25 liter pot registration of oxathiapiprolin for use on avocado has been initiated through the Inter-regional Research Project No. 4 , and ethaboxam,fluopicolide, and mandipropamid are proposed for further development on avocado. Additional evaluations will have to be done under field conditions using rootstocks with different growth characteristics and susceptibilities to PRR. The availability of fungicides with new modes of action and options for rotation and mixture programs using previously registered and new fungicides will help reduce the risk of development and spread of resistance in P. cinnamomi populations in California avocado production. Growers currently rely heavily on the use of phosphonate-based fungicides, and as we demonstrated, pathogen populations are shifting towards reduced sensitivity to this fungicide class. Thus, there is an urgent need to register fungicides with new modes of action. In our greenhouse studies, overall treatment efficacy in reducing PRR and soil inoculum levels of the pathogen on the susceptible PS.54 was reduced as compared with the more tolerant Dusaâ rootstock, indicating additive effects of fungicide use and rootstock selection. In an integrated approach for a durable and effective management of PRR that allows the continued economical production of avocados in P. cinnamomi infested soils, the use of tolerant rootstocks is critical along with irrigation management and cultural practices such as using mulching and planting in areas with good soil drainage.Plant pathogenic oomycetes fall into two general categories when it comes to pathogenicity. There are Phytophthora species that can infect only one, or a few different hosts like Phytophthora infestans de Bary, and then there are species that can infect hundreds or even thousands of different plant species such as P. cinnamomi Rands . P. cinnamomi is of particular interest in California because it causes Phytophthora root rot of avocado, in fact, PRR is the most destructive disease of avocado production worldwide . PRR limits production of avocado by killing feeder roots which reduces fruit yield and can cause tree death . P. cinnamomi impacts other fruit crops such as peach, pineapple, and highbush blueberry, as well as affecting natural stands of eucalyptus, pine, and oak . Areas that have become infested with P. cinnamomi will never completely remove this pathogen from the soil. Current chemical treatments are being challenged by the emergence of isolates that are more virulent and less sensitive to potassium phosphite . The current challenges of PRR treatment of avocado necessitates a better understanding of the molecular and genetic basis of plant-P. cinnamomi interactions. Taking advantage of the wide host range of P. cinnamomi, we developed a detached leaf assay in Nicotiana benthamiana to elucidate the molecular and genetic basis of plant immunity against P. cinnamomi . The hemibiotrophic lifestyle of P. cinnamomi was confirmed in this model system through differential staining and quantitative PCR pathogen DNA quantification. The model plant, N. benthamiana , has been widely used to study the pathogenicity and virulence of similar broad range and root Phytophthora pathogens such as P. capsici , P. palmivora , and P. parasitica . Furthermore, several studies using model plants, crops, and tree crops to study pathogenicity, virulence, and fungicide efficacy of root rot pathogens such as P. sojae, P. capsici, P. parasitica, P. palmivora, P. cinnamomi, and P. ramorum have been performed using detached-leaf assays . Using the tools developed in previous studies and combining them with RNAseq analysis as well as functional assays using this model plant it becomes possible to gain a better understanding of plant defense responses against P. cinnamomi infection. Previous transcriptomic studies on avocado and model systems provides important information on plant gene expression in response to infection by P. cinnamomi. Avocado defense gene expression has been analyzed three separate times over the last eight years . Mahomed and Van den Berg used the tolerant avocado rootstock Dusaâ to study the gene expression changes after P. cinnamomi inoculation. By comparing expressed sequence tags and 454 pyrosequencing they were able to identify six defense related genes. The defense genes identified encoded: cytochrome P450-like TBP , thaumatin, PR10 , metallothionein-like protein, MLO transmembrane protein encoding gene, and a gene encoding a universal stress protein . In a follow up study, again on the resistant avocado rootstock Dusaâ , 16 additional defense genes encoding: WRKY transcription factors, phenylalanine ammonia-lyase , beta-glucanase, allene oxide synthase, allene oxide cyclase, oxophytodienoate reductase, 3-ketoacyl CoA thiolase, Fbox proteins, ethylene biosynthesis, isoflavone reductase, glutathione s-transferase, cinnamyl alcohol dehydrogenase, cinnamoyl-CoA reductase, cysteine synthase, quinone reductase, and NPR1 were differentially expressed after P. cinnamomi infection. Reeksting et al. found up-regulated transcripts corresponding to cytochrome P450, a germin-like protein , and chitinase genes after P. cinnamomi infection using microarray technology. It has been stated , that an important difference between gene expression in avocado and model systems is that the salicylic acid response is only seen in infected avocado, which is associated with a defense response to biotrophic and hemibiotrophic pathogens. It has been further asserted that P. cinnamomi infection of model plants initiates the jasmonic acid and ethylene pathways associated with necrotrophic pathogens. Although there are differences between expression patterns in avocado and the numerous model plants that have been studied to better understand plant defense to P. cinnamomi, there are also many similarities.

For example, when native pollinator populations have been reduced due to habitat fragmentation or other stressors, honey bees can “rescue” plants from reproductive failure , and, after honey bees have become naturalized, removing them may disrupt pollination of plants they would otherwise visit . However, regardless of whether honey bees are native or naturalized, dramatic increases of any species could disrupt species interactions and ecological processes , particularly when floral resources are limited. For example, in France, where honey bees are native, highly abundant managed honey bees can over-exploit limited floral resources, reducing pollen and nectar collection by wild bees . Indeed, although we studied only one plant species in a specific context, there are likely many systems for which introducing honey bees or other highly abundant generalist pollinators may indirectly reduce pollination by competitively displacing other pollinators. Several recent meta-analyses have revealed that honey bees are less effective than other bees . Furthermore, honey bees have been implicated in the extirpation of native bee species and frequently compete with other pollinators for limited pollen and nectar resources . Hive density is negatively correlated with wild bee abundance and diversity in many ecosystems and honey bees are replacing wild bees as floral visitors in some areas . Thus, indirect negative effects of honey bee introductions may be common where wild pollinator communities already effectively pollinate native plants. Conclusions – Our findings bear on ongoing discussion about permitting of honey bee hives on public lands.

Historically, the placement of managed hives in U.S. National Forests and Parks has been restricted and tightly regulated. However, vertical farm tower beekeepers have successfully lobbied to have honey bees considered a “non-consumptive” use of U.S. National Forest land . If adopted widely, such changes will likely lead to a massive increase in the number of managed honey bees in natural areas. Although honey bees are important pollinators in other systems, we show that indirect negative effects of competition can lead to overall negative effects of honey bee introductions on pollination. As such, introducing hives to sensitive ecosystems should be approached with extreme caution. More fundamentally, we show that introduced pollinators can disrupt plant-pollinator mutualisms and impair ecosystem functioning. These mutualists, although infrequently studied in the invasive species literature, broadly meet the definition of an “invasive” species despite their economic benefits to human society. Untangling direct and indirect effects allowed us to mechanistically understand the functional consequences of honey bee introductions. We recommend that future studies carefully consider indirect impacts of introduced species as biodiversity continues to decline and ecological communities become increasingly homogenous.Over 70% of plants depend to some degree on animal pollinators to successfully reproduce . Among the diversity of pollinators, taxa vary in their contributions to pollination in multiple intricate dimensions, some quantitative , others qualitative . At its core, the functional contributions of different pollinator taxa can be measured by the quantity and quality of visits to plant reproductive success . From a quantitative perspective, although biodiverse pollinator assemblages increase pollination , a few dominant species often provide the majority of floral visits . For example, the numerical dominance of honeybees as floral visitors has been hypothesized to drive their functional importance as pollinators . However, high visit frequencies can impair pollination in some contexts and we know little about whether strongly dominant visitors, such as honeybees, effectively pollinate the plants they visit.

Pollination effectiveness is defined as the per-visit contribution of floral visitors to pollination . A long history of studies within the botanical and evolutionary ecology literature documents variation in single visit effectiveness among plant visitors . To some extent, variation in pollination effectiveness reflects the wide range of methods used to measure it , such as single visit pollen deposition , the number of developed pollen tubes within styles , and/or fruit or seed set . Regardless, evidence for variation in SVE comes from numerous individual studies and this literature has yet to be synthesized in a way that would address whether and why particular taxa are more effective than others and whether dominant visitors are more effective pollinators of the plants they visit. Meta-analysis is a particularly valuable way to investigate such questions. An extensive literature on pollinator importance – the product of per-visit effectiveness and relative visitation rates of different pollinators – has concluded that pollinators that visit more frequently are generally more important . This conclusion suggests that numerical dominance outweighs among-species variation in SVE, but it is also possible that pollination effectiveness and visitation frequencies are correlated. First, frequent pollinators could be inherently more effective because of deep phylogenetic signals. For example, Ballantyne et al. found a positive correlation between a pollinator’s visit frequency and pollination effectiveness when comparing 23 plant species, likely because bees were both highly effective and highly frequent visitors compared to other floral visitors. Second, positive correlations between pollination effectiveness and visit frequency could occur if pollinators that visit frequently do so to the exclusion of other plant species. Such temporary fidelity or long-term fidelity would operate to minimize heterospecific pollen transfer, resulting in more effective pollination . On the other hand, high visitation rates may be the result of many quick and ineffective visits and have a negative or non-significant effect on reproductive success in many contexts . Despite their high visitation frequencies, the effectiveness of honeybees relative to other pollinators remains unclear. Bees are often the most effective pollinators of flowers and Apis mellifera is the most common flower-visiting bee species. However, there are several reasons to suspect that honeybees might be less effective than other bees. First, outside of their native range, honeybees lack the evolutionary history with endemic plants that could have selected for increased pollinator effectiveness . Furthermore, honeybees are floral generalists that visit a high proportion of available plants in ecosystems across the globe , and thus may not be particularly effective at pollinating specific flowering species. Second, honeybees sometimes ‘rob’ plants and efficiently extract and groom pollen from plants without depositing the pollen they extract or collect nectar without contacting reproductive structures . On the other hand, honeybees can be highly effective pollinators, even for plants with which they have no shared evolutionary history , suggesting that honeybees are highly adaptable and capable pollinators. Understanding pollinator effectiveness has important practical implications for safeguarding the production of pollinator-dependent crops. Highly effective non-honeybee pollinators are important for ensuring crop pollination in the face of global change and functionally diverse pollinator communities can increase crop pollination . Furthermore, pollination may differ in cultivated settings because interspecific plant competition, the spatial arrangement of flowers, and the pollinator taxa that provide pollination may vary between agricultural and natural landscapes .

We used a meta-analysis of the pollination effectiveness literature to address three key questions. First, how does the SVE of honeybees compare to that of other floral visitors? We hypothesized that honeybees would exhibit lower SVE relative to other pollinators because honeybees are broad generalists and might efficiently extract nectar and pollen without effectively pollinating plants. Second, to what extent do plant and pollinator attributes predict the comparative SVE of honeybees? Specifically, we evaluated whether pollinator taxonomic groups , crop status , and if plant species exist within the native range of honeybees predict differences in comparative SVE. We hypothesized that the SVE of honeybees would be lower compared to other bees, in crop systems, vertical plant tower and for plant species outside the native range of honeybees because previous studies have suggested such trends . Third, is there a correlation between floral visitation frequency and SVE? We evaluated this question separately for communities where honeybees were present or absent. We expected to find a positive correlation between visitation frequency and SVE that would be reduced when honeybees were present because honeybees are often highly frequent visitors and might be less consistently effective. Although previous studies have synthesized subsets of the pollination effectiveness literature , this paper is, at present, the most extensive meta-analysis to synthetize published results concerning single visit effectiveness.We performed a Web of Science search using a multiterm query designed to capture the highly variable terminology describing pollination effectiveness detailed in Ne’eman et al. . In May 2020, this search yielded 1,036 results. One of us screened the abstracts found by WoS to determine whether they potentially contained single visit effectiveness data. This yielded 388 papers. We also performed a Google Scholar search of the literature using a similar multi-term query , which yielded 116 additional papers. We found 62 papers from the reference sections of previously included papers. After removing duplicates and reading abstracts, we identified 468 papers which seemed appropriate for a more thorough screening. We followed the PRISMA protocol for collecting and screening data from the literature . To be included in our analysis, the paper had to contain empirical data on the per-visit contribution of at least one free-foraging visitor to plant reproduction. We considered pollen deposition, percent fruit set, fruit weight, and/or seed set as measures of SVE. Most studies were conducted with intact flowers, but we also included data from experiments that used the “interview stick” method . We did not include estimates of SVE based on equations or model outputs nor did we include data from trials that manipulated dead bees to deposit pollen. We extracted means, sample sizes, and measures of error directly from the text of the paper or from graphs using WebPlotDigitizer . When lower and upper error estimates were not symmetrical, we used the upper error estimate. When possible, we converted measures of error to standard deviation. When a paper did not report sample sizes, error, or other important information, we contacted the study authors. If we were unable to retrieve or estimate information on mean effectiveness and error, we excluded the paper from our analysis. We also excluded papers if we couldn’t convert other measures of error to standard deviation . After screening papers, 168 studies remained in our analytical dataset. We also extracted data on study year and location, plant species, plant family, whether the plant species was a crop-plant, pollinator taxon, pollinator group , and the native range of pollinator and plant species. We determined range status to bio-geographical realms by looking up the nativity of each taxon in the scientific literature and using occurrence records on the Global Biodiversity Information Facility website. If papers reported SVE outcomes from multiple sites or years, we extracted these data as separate outcomes and dealt with their non-independence statistically . We collected information on the visitation rates of pollinators if it was reported for the same plant species for which pollinator effectiveness data were reported. This rate could be reported as the number of visits to a focal flower or patch of flowers per unit time or the number of flowers visited per unit time and/or per unit area. We did not include data on the relative abundance of different visitors unless data were collected in a homogeneous landscape in which most visitors would have been visiting the focal plant species. If a study reported visitation data, we matched those data to the corresponding SVE data from the same study and plant species. Perfect matches required that pollinator taxa were reported to the same taxonomic resolution and that data were collected in the same year and location. When more than one measure of visit frequency was reported we preferentially used data on the number of visits to a focal flower per unit time. When more than one measure of SVE was reported, we preferentially chose whichever measure was better represented in our data, such that pollen deposition data were chosen over seed set data and seed set data were chosen over fruit set data.To address questions about the single visit effectiveness of honeybees and non-honeybees, we defined the effect size as the standardized mean difference of SVE values between honeybees and non-honeybees for each unique study, plant, site, and year combination. We chose to use Hedges’ g over other effect sizes because it is commonly used in the ecology literature for comparing two means , and it includes a correction for small sample sizes, which occurred with our data. Following Hung et al. , we calculated effect sizes for two separate comparisons: the difference between honeybees versus the most effective non-honeybee taxon and the average difference between honeybees and non-honeybee taxa . The SMD value is > 0 when other pollinators are more effective than honeybees and < 0 if the opposite occurs.

In this section of the paper, we perform a placebo test. We also investigate channels other than information through which congregational mergers might be driving fertilizer adoption, and provide evidence against these other possible explanations.It is still possible that our results are being driven by something other than a congregational merger driven information effect. Here, we explore two other possible explanations for our results. The first is the presence of agricultural extension. Agricultural extension, formally introduced in the United States by the Smith-Lever Act of 1914, plays a major role in information dissemination in agriculture. There is a large literature on the effect of agricultural extension, both in the United States and elsewhere, on agricultural productivity and technology adoption ; Huffman ; Birkhaeuser et al. ; Dercon et al.. Despite the importance of extension, we argue that it is in fact congregational mergers and not extension services that generate the results we find in this paper: because of the fixed effects strategy, in order for agricultural extension to be driving these results, we would need to see agricultural extension services changing differently over time in treatment counties than in control counties, having removed the state time trend, only over the 1959 to 1964 time period. This is potentially plausible, but seems unlikely, especially because extension funding and the number of extension agents allowed is governed by state laws, which do not change often. For example, the Minnesota statutes outlining extension were first passed in 1923, updated in 1953, and were not revised again until 1969. The law allows for “the formation of one county corporation in each county in [Minnesota]” to act as an extension agency, stackable flower pots with in most cases one extension agent and a specified budget, based on the number of townships in the county.

While county extension offices documented their activities for mandatory state reports, these reports were inconsistent across different counties and years. Also, many of the variables measured were endogenous, such as the number of phone calls received or the number of attendees at extension events. As a result, it is impossible to credibly measure the intensity and efficacy of extension efforts over our sample period. We argue in this paper that congregational mergers impact fertilizer use through information. Another plausible explanation would be that the mergers also facilitated increased access to capital. In order to provide evidence against this possibility, we estimate Equation again, this time with the number of farms with each of a variety of capital-intensive technologies as outcome variables. Table 2.8 shows the impact congregational mergers have on the number of farms with cars, trucks, tractors, bailers, and freezers. As expected, we find no statistically or economically significant effect of congregational mergers on capital-intensive inputs: the standard errors are quite wide, and the effect sizes small: the coefficient on cars, for example, is only a 0.01 percent increase relative to the control group mean, and the standard error is almost one hundred times the size of the coefficient. This suggests that congregational mergers did not substantially increase access to capital, and provides additional evidence that information is the main channel through which congregational mergers impacted technology adoption. Finally, one might worry that by only using TALC congregational mergers in our analysis, we are understating the true treatment effect. We argue above that the TALC mergers are exogenous, and, due to the heavily Lutheran populations in these regions, the mergers where we would expect to see an effect. Indeed, the congregations that are merging in these data have, on average, 492 baptized members, so seeing an additional 35 farms begin to use fertilizer is an entirely reasonable effect size. There is another major Lutheran church branch, the Lutheran Church – Missouri Synod , that was not directly involved in the TALC merger, but whose mergers could be attributed to increased discussion about merger surrounding TALC.

We collected data from Concordia Historical Institute, the LCMS seminary, on congregational mergers between LCMS churches during the sample period. There is only one merger that occurs in a non-metropolitan county during this time period, and the inclusion of said merger does not produce a statistically distinguishable result from using only the TALC mergers. Ultimately, given the range of tests that we perform, we have confidence that our results are robust and that we are correctly attributing them to the information effect of congregational mergers.Since the early 2000s, US ethanol production has exploded in response to federal policies incentivizing the production of renewable fuels. In 2005, Congress passed the Energy Policy Act introducing a Renewable Fuel Standard mandating that 2.78% of gasoline sold in the US be from renewable sources. In 2007, Congress passed the Energy Independence and Security Act setting annual renewable fuel mandates for US production with an ultimate goal of 36 billion gallons by 2022. Of these 36 billion gallons, 15 billion are to be conventional bio-fuels – corn-based ethanol in particular. The US ethanol industry has clearly responded to the Renewable Fuel Standards established in the EPAct and EISA. Between 2002 and 2014, US ethanol production has increased from just over 2 billion gallons per year to over 14 billion gallons per year . In order to produce such quantities of ethanol, the number of corn ethanol refineries in the US has increased from 62 in 2002 to 204 in 2014 . The striking increase in US corn ethanol production has raised several important questions about its unintended consequences. One strand of research has explored how increased demand for ethanol has affected land use in the US corn belt as aggregate demand for corn increases . Another strand of research has been more concerned about the environmental externalities of changing agricultural patterns, particularly focused on nitrate runoff and water pollution . In this chapter, I explore both the land use change effects and environmental effects of expanding ethanol production.

In particular, I study the geospatial effect of ethanol re- fineries’ placement on nearby land use change and use my results to estimate environmental consequences. I am specifically interested in how the location of ethanol refineries spatially affects agricultural land, and I do not attempt to identify the full general equilibrium effect of the 14 billion gallon US corn ethanol industry. Put another way, I study how the distribution of ethanol refineries differentially affects different agricultural areas net of the ethanol industry’s aggregate effect on corn prices. I find that within a population of almost 114 million acres of agricultural land in Illinois, Indiana, Iowa, and Nebraska, nearly 300,000 more acres of corn were grown in 2014 than in 2002 due merely to ethanol refinery location effects. This represents approximately 21,000 tons of nitrogen applied as fertilizer. Almost all the 300,000 acres of increased corn acreage exist within 30 miles of an ethanol refinery, suggesting that these refineries have strong local effects on land use change and nitrogen use. There is clear economic intuition for why ethanol refineries would differentially affect nearby and faraway agricultural land. When a corn-fed ethanol refinery is built, it represents a new terminal market for corn. Since refineries operate continuously, they have an inelastic demand for this input. And since transportation costs are significant for grains, one would expect an ethanol refinery to source its corn from the nearest producers. Thus, by reducing transportation costs for nearby producers , ethanol refineries essentially subsidize corn production for nearby farmers. On the margin, this subsidy incentivizes farmers to grow more corn – or grow corn more often – than they otherwise would. As corn production increases, so will nitrogen fertilizer use. Corn requires higher levels of nitrogen fertilizer than other Corn Belt crops, tower garden and particularly high levels of fertilizer when grown successively corn-after-corn. Thus, economic intuition suggests ethanol refineries would have a localized effect increasing corn production and nitrogen fertilizer use. Consequently, these refineries would also have an effect on localized nitrate runoff due to the increased nitrogen fertilizer use. Researchers have previously addressed different components of the ethanol industry’s effects on land use change and nitrate runoff. One line of research has explored whether the hypothesized local corn subsidy provided by nearby ethanol refineries actually exists. In a frequently cited paper, McNew and Griffith find that corn prices at an ethanol refinery are 12.5¢ higher than average, that the effect is slightly stronger for “upstream” refineries than for “downstream” refineries, and that price effects can be detected up to 68 miles from a refinery. However, Katchova and O’Brien both fail to find such a subsidy. Gallagher et al. highlight that locally-owned and non-locally-owned refineries have different effects on corn prices: the authors find that corn prices are increased by proximity to a non-locally-owned refinery, but not by proximity to a locally-owned refinery. Finally, Lewis finds different results in different states: ethanol refineries in Michigan and Kansas affect local corn prices, but refineries in Iowa and Indiana do not.

Fatal and Thurman use county-level data to estimate the corn acreage effect of ethanol re- fineries. They find that a typical ethanol refinery increases corn acreage in its home county by over 500 acres and has effects that can persist for up to 300 miles. Miao also uses county-level data and finds a significant effect of ethanol refineries on corn acreage, as well as a differential effect between locally-owned and non-locally-owned refineries. Turnquist et al. , in contrast to more recent studies, fail to find any significant agricultural land conversion in areas near Wisconsin ethanol refineries. Finally, Feng and Babcock explore the full general equilibrium effect of increased ethanol production and find an unambiguous increase in corn acreage. Several researchers have focused on how ethanol production affects water quality and nitrate runoff. Donner and Kucharik highlight how the aggregate impact of the EISA will likely make achieving nitrate level goals in the Mississippi impossible. Thomas et al. use hydrologic models to estimate the water quality impacts of corn production caused by increased demand due to biofuel mandates. They find significant negative results. While it is likely true that “refineries cause corn,” it is also likely true that “corn causes refineries.” Ethanol refineries are not located at random, and several researchers have explored the topic of ethanol refinery placement. A series of papers have shown, unsurprisingly, that ethanol refineries are more likely to locate near areas with large corn production, near transportation infrastructure, and not near existing ethanol refineries . This finding is important because it highlights that ethanol refinery placement cannot be treated as truly random in econometric analyses without accounting for the underlying drivers of this placement. In my analysis, I argue that field-level fixed effects appropriately account for the major determinants of refinery placement. In particular, I study how distance-to-nearest-refinery affects the probability of a field being planted to corn. Whenever a new refinery is built, its presence differentially affects fields close to it relative to fields slightly farther away.However, due to the spatial characteristics of soil quality and topology, “more-treated” and “less-treated” fields are qualitatively comparable. My project improves upon previous work by leveraging new sources of field-level land use data and exploiting a finer-scaled panel of observations than previous authors. I exploit both the Cropland Data Layer and Common Land Unit to create annual observations of field-level land use. These agricultural micro-data allow for much more nuanced econometric estimation than in previous studies. Other authors have exploited similar micro-data in agricultural research to great effect . I also highlight the locality effect of ethanol refineries rather than the general equilibrium effect, focusing on small-scale heterogeneous effects that have not been well identified in previous work. The remainder of this paper is divided into a theoretical framework , a summary of my data, an overview of my econometric methods, a discussion of my results, and a conclusion.The net increase in corn acreage of 298,718 that I find is only 0.26% of the 113,978,323 acres in my population, but it is 0.76% of all corn acreage in my population in 2014. This is a significant number given that it can be attributed to only the distance-to-nearest-refinery effect. In other words, the effect of new ethanol refineries since 2002 on lowering transportation costs can explain almost 300,000 acres of the corn grown in a subset of the fields across Illinois, Indiana, Iowa, and Nebraska. Figure 3.11 highlights that the entirety of this acreage effect is captured by fields less than 30 miles from the nearest ethanol refinery.