Horticulture

Potassium phosphite has been an effectively preventative and curative agent against avocado PRR since the early 1980s. However, there are only a limited number of reports on reduced in vitro sensitivities of a few Phytophthora spp., including: P. capsici, P. cinnamomi, P. citrophthora, P. infestans, P. nicotianae, and P. syringae . Although the mode of action of potassium phosphite is still unknown, its effectiveness is theorized to be the result of a number of interactions with both the pathogen and the plant host. Potassium phosphite directly inhibits P. cinnamomi in vitro at certain concentrations , but it has also been shown to be effective in planta at concentrations that were not inhibitory in vitro . This suggests that potassium phosphite may prime plant defense responses. It is likely that the effectiveness of potassium phosphite is the result of a combination of both direct inhibition of the pathogen and an increase in the hosts natural defense response. Metalaxyl was developed by Ciba Geigy Ltd in 1977 and marketed as Ridomil . Mefenoxam is an R-enantiomer of metalaxyl. Phenylamides affect the polymerase I complex of rRNA synthesis of oomycetes .

Phenylamide resistance is the result of a mutation in a single incompletely dominant gene , drainage pot which has been found in P. cinnamomi as well as other Phytophthora spp., e.g. P. infestans, P. citricola, P. megasperma, and P. nicotianae, a few years after metalaxyl or mefenoxam was first applied . The risk of resistance development is considered as high . Sensitivity to phenylamide fungicides of Phytophthora spp. has changed numerous times, especially for foliar pathogens such as P. infestans, due to the introduction of new clonal populations. A few new Oomycota chemistries, including ethaboxam, fluopicolide, mandipropamid, and oxathiapiprolin, have been introduced to various oomycete diseases of different crops . All of these chemicals have unique MoAs that are also different from mefenoxam and potassium phosphite. Ethaboxam, a thiazole carboxamide, disrupts microtubuleorganization in oomycetes such as P. infestans, P. capsici, Plasmopara viticola, and Pseudoperonospora cubensis . Fluopicolide is a benzamide fungicide which delocalizes cytoskeleton-associated spectrin-like proteins . It has proven effective against P. capsici on tomato as well as P. nicotianae on tobacco . Mandipropamid is a carboxylic acid amide fungicide, and its enzyme activity targets cellulose synthase in the pathogen . It was shown to be effective against most Phytophthora spp. and P. viticola . Oxathiapiprolin, a piperidinyl thiazole isoxazoline, targets the oxysterol binding protein of oomycetes .

This fungicide was found to be highly effective against numerous oomycete pathogens including P. nicotianae, P. capsici, P. infestans, and P. citrophthora . None of these new Oomycota fungicides have been registered to control PRR of avocado, so the second main objective of this dissertation was to evaluate the in vitro sensitivities of four new Oomycota-targeting fungicides as well as currently registered fungicides to the P. cinnamomi population isolated in California avocado growing regions, and to evaluate the efficacy of these fungicides against avocado PRR in greenhouse studies. The third main objective of this dissertation was to develop a N. benthamiana–P. cinnamomi model system to identify candidate genes associated with host resistance.No plant resistance genes have been identified previously due to the lack of understanding of the genetic and molecular basis of plant-P. cinnamomi interactions. Identification of genes associated with host resistance to P. cinnamomi in avocado is a challenging task due to the limitations associated with the nature of tree crop biology that only one to three experiments can be completed annually. Currently, the avocado reference genome is not publicly available, and an efficient stable or transient avocado transformation system is still lacking . For this reason, we developed a new model system using the plant N. benthamiana to conduct these studies . N. benthamiana has been widely used to study plantPhytophthora interactions since it can be used for transient silencing and overexpression of genes It was also recently applied to study plant-P. palmivora interactions .

Zea mays, Arabidopsis thaliana, Lupinus angustifolius, Castanea sativa , Eucalyptus nitens, Lomandra longifolia, and most recently N. benthamiana have all been investigated to better understand plant defense gene response to P. cinnamomi infection . Resistance to P. cinnamomi can be elucidated by comparing susceptible and resistant model plants. The gene expression between a susceptible and resistant variety of chestnut was compared and the defense gene expression was found to be significantly higher in the resistant variety especially before inoculation. This increased basal defense to P. cinnamomi may contribute to the resistance of this variety . Previous studies on avocado and model systems have provided important information on plant gene expression in response to P. cinnamomi infection. Several transcriptome studies have been completed on avocado. The initial study compared expressed sequence tags and 454 pyrosequencing results to identify defense related genes, which included: cytochrome P450, thaumatin, pathogenesis related protein 1 , metallothionein, MLO transmembrane protein encoding gene, and a universal stress protein . In a follow up study, 16 additional defense genes were described, including WRKY transcription factors, phenylalanine ammonia-lyase , and beta-glucanase . In Reeksting et al. , up-regulated transcripts of interest included cytochrome P450 and germin-like protein . It has been stated that P. cinnamomi infection of model plants initiates different hormone signaling pathways compared to avocado infection . Currently, there seems to be some differences as well as many similarities in the gene expression of avocado compared to many model plants in response to P. cinnamomi infection. The differences in gene expression should be studied to better understand plant defense to P. cinnamomi. This dissertation represents an integrated approach to study the molecular interaction of P. cinnamomi with its host and provide practical solutions to combat PRR of avocado in the field. This work will contribute in numerous ways to avocado growers in California. Identified variation in genotype and phenotype of prevalent P. cinnamomi populations in California will greatly influence the development of resistant avocado rootstocks as well as efficacious chemical treatments. P. cinnamomi has also been isolated recently from blueberries, valued $123 million at production level in California. As avocado and blueberry fields are at times in close proximity, the presence of PRR in both crops could lead to changes in host resistance and virulence that would potentially be devastating to both industries. Ongoing drought and increased water salinity also necessitate this comprehensive approach to PRR management in California. Efficacious new fungicides on avocado plants will be registered for the treatment of avocado PRR. Candidate host resistance genes associated with and contributing to P. cinnamomi resistance will be targeted and used to implement Marker Assisted Screening to develop new avocado rootstocks more resistant to the diverse population of P. cinnamomi in California.The oomycete pathogen Phytophthora cinnamomi Rands, causal agent of Phytophthora root rot , is the most destructive disease of avocado worldwide . In California, avocado PRR affects 60-75% of avocado growers who lose approximately $40 million annually . This globally distributed oomycete is called “the biological bulldozer” for its capacity to infect over 3000 plant species causing devastating impacts in natural ecosystems, forestry, agriculture, and the nursery industry . The economic impact due to P. cinnamomi infestation is evident in the forest and food industry, affecting eucalyptus, pine, oak , and other fruit crops such as pineapple, peach, and highbush blueberry . Losses include not only decreases in crop yield and product value, large pot with drainage but also large amounts of money spent annually on control measures. There are no effective means to eradicate P. cinnamomi from infested areas as it survives in moist soil or dead plant material as chlamydospores for long periods under adverse conditions . Several PRR control strategies have been found to reduce the impact of this invasive pathogen including the use of chemical treatment , tolerant plants, and management practices . P. cinnamomi is a hemibiotrophic pathogen feeding initially from living host cells and then switching to necrotrophy by killing the host cells and feeding from the nutrients released by them .

The entry into the plant is achieved by the adhesion of the motile zoospores to the host tissue, encystment, and germ tube formation. The germ tubes usually grow and penetrate the root surface via appressoriumlike swelling structures and then plant tissue is rapidly colonized . During its biotrophic stage, P. cinnamomi projects haustoria into the plant cells for the acquisition of nutrients and release of pathogen proteins to aid the infection process in the host . This is followed by a necrotrophic stage characterized by host cell death, hyphal proliferation, and production of numerous sporangia . Currently, the molecular and genetic basis of P. cinnamomi pathogenicity, virulence, and plant immunity against this pathogen are largely unknown due to limitations associated with tree crop biology and the lack of tools available for functional studies in tree crops such as avocado . Arabidopsis and lupin have been used as model systems to study P. cinnamomi-plant interactions . The model plant, Nicotiana 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 . Moreover, several studies using model plants, crops, and tree crops to study pathogenicity, virulence, and fungicideefficacy of PRR pathogens such as P. sojae, P. capsici, P. parasitica, P. palmivora, P. cinnamomi, and P. ramorum have been done using detached-leaf assays . Phosphite is the most widely used chemical control method for managing PRR caused by several Phytophthora spp. including P. cinnamomi . Phosphorous acid dissociates to form the phosphonate ion , also called phosphite. Phosphorous acid and its ionized compounds are often referred to as phosphonate or phosphonite. The specific mode of action of potassium phosphite is largely unknown, however appears to involve both a direct and an indirect effect on the pathogen . Several studies have assessed the in vitro sensitivity of P. cinnamomi to phosphite using mycelial radial growth inhibition in solid and liquid media to identify sensitive and tolerant isolates . In California, avocado growers heavily rely on the use of phosphite products to control P. cinnamomi, however the phosphite sensitivity of California avocado isolates is largely unknown. In addition to phosphite, phenylamide fungicides such as metalaxyl and mefenoxam are also used for managing diseases caused by oomycetes including P. cinnamomi . Resistance to metalaxyl has developed in P. capsici, P. infestans, and P. nicotianae .Phenylamides usually do not inhibit germination of sporangia or encysted zoospores as effectively as they do mycelial growth . Consequently, inhibition of mycelial growth in vitro has been used as the primary method of determining the sensitivity to these fungicides among isolates of Phytophthora spp. . The need for new oomycete-targeted fungicides to control diseases caused by these pathogens especially those that have developed resistance to phenylamide fungicides has resulted in the development of several new chemicals with varying modes of action such as fluopicolide and oxathiapiprolin . Fluopicolide is a pyridinylmethyl-benzamide fungicide that disrupts cell division and mitosis by acting on spectrin-like proteins . This fungicide is effective to control diseases caused by P. capsici and P. infestans . Oxathiapiprolin is the first of the new piperidinyl thiazole isoxazoline class fungicides discovered and developed by DuPont Co. in 2007. The molecular target of oxathiapiprolin is the oxysterol binding protein . This new fungicide exhibits strong inhibitory activity against a range of agriculturally important plant-pathogenic oomycetes including P. capsici, P. infestans, P. sojae, Peronospora belbahrii, and Pythium ultimun . However, its inhibitory activity against P. cinnamomi has not been tested. P. cinnamomi is a heterothallic species that requires the presence of both A1 and A2 mating types to undergo sexual reproduction. Despite that both mating types arepathogenic , avocado PRR disease in California is mainly associated with A2 mating type isolates . Previous P. cinnamomi population studies have revealed low levels of genotypic and phenotypic variation among isolates from different mating types, origin, isolation source, and host plants, however, only a few were conducted or have included isolates from avocado . These studies described the existence of three clonal lineages for P. cinnamomi, one corresponding to the A1 mating type isolates and two different clonal lineages for the A2 mating type isolates . Pagliaccia et al. conducted the first study to assess the genetic diversity of P. cinnamomi isolates from avocado in California and also found two genetically distinct clades of A2 mating type isolates .

Although Willis et al. found no difference in average counts between experts and non-experts, non-expert counts tended to be more variable per specimen. This in part depended on the specimen being assessed—specimens with more objects to count had higher error rates. As with any crowdsourcing project, care should be taken when choosing which specimens and taxa to include . Additionally, CrowdCurio is in the process of implementing additional features to improve data quality, such as filtering users based on their ability to repeat the same task. The phenological data generated within CrowdCurio can be expressed according to the protocol outlined in this paper and shared via Darwin Core Archives.One ultimate goal is to combine herbarium specimen data with other sources of phenological data to make possible the detection of phenological changes across geographic, temporal, and taxonomic scales. The PPO provides an opportunity for herbarium data to be combined with disparate data sources, such as in situ phenological monitoring or satellite imagery. The PPO is a common vocabulary for describing plant phenological traits and was designed to provide a means to support global-scale integration of phenological data.

Ontologies provide highly structured, greenhouse vertical farming controlled vocabularies for data annotation and are particularly useful for standardization, because they not only establish a common terminology but alsoformalize logical relationships between terms such that they can be analyzed using machine reasoning. For example, logical term relationships in the PPO specify that any plant with “expanding leaves” must necessarily also have “non-senescing leaves.” This logical structure means that data can be integrated at different levels of detail and software can be used to establish new facts about the data that were not expressed in the original data sets. This structure in turn enables large-scale integration among a wide range of study types, including: studies addressing similar phenophases but using different methodologies, studies involving different phenophases, and studies not specifically addressing phenology but producing other types of data . Thus, the PPO empowers researchers to aggregate larger data sets, at the global scale, and to address broader questions involving the interplay of phenology and other factors. Accordingly, the PPO is already being used to integrate data resources such as those from the USA National Phenology Network , the Pan-European Phenology Network , and herbarium digitization efforts.

The PPO and associated integration tools are compatible with the Darwin Core and Apple Core standards and associated data-sharing tools discussed above. Never before has an understanding of phenology been so important to humans. We are in a time of massive environmental change, and the organisms upon which we depend will have to adapt or migrate if they are to avoid local or global extinction. We need phenological data from specimens now more than ever, and researchers are ready and eager to analyze high-quality data sets, particularly those comprising high taxonomic diversity, temporal depth, and a broad geographic range. With minimal additional efforts during or post-digitization, specimens can be scored quickly and easily and contribute to our understanding of our changing planet and the flora that sustains it.Competition occurs when species vie for a common but limited resource , leading to decreased population growth of species that fail to appropriately shift their resource use . Ample evidence suggests that competition can alter the structure and function of ecological communities , and ecological theory predicts that two perfectly similar species cannot coexist without one species competitively displacing the other . Yet, there remains considerable debate regarding the degree to which competition drives species evolution and extinctions . Understanding when and where overlapping resource use might eventually lead to competitive displacement is especially important in managing the impacts of exotic species. For example, hyper-generalist honey bees have been introduced into many ecosystems outside of their native range and often overlap with other bees in their use of floral resources .

However, shared use does not automatically indicate that competitive displacement is occurring. Nectar production and replenishment rates vary widely among and within plant species , as does pollen production and floral resources may not be limited if flowers are abundant or if rates of resource extraction equal rates of replenishment.Assessing honey bee vs. wild bee competition is further complicated by the fact that bees may respond to competitive pressures by shifting floral visits to alternative floral resources or by narrowing their diet breadth . As such, a snapshot of resource use may indicate that competitive displacement has occurred, but niche partitioning will not negatively affect the fitness of displaced species unless the quantity and quality of resources collected also declines. As such, knowledge of resource use overlap alone is insufficient to determine whether honey bee competition might have negative consequences for native bee populations . Indeed, although we know that honey bees collect massive amounts of pollen and nectar from flowers , whether such resource collection alters floral resource availability remains poorly tested. Many different studies have assessed competition using many different assessment tools . Field studies provide ample evidence that honey bee competition can alter wild bee visits to plants and restructure the community of interaction among plants and pollinators . At the level of individual foragers, competition among bumble bees can increase floral fidelity and conspecific pollen transport . Although such questions have yet to be investigated in the context of honey bee competition, honey bee abundance can decrease niche breadth at the species-level and parallel changes may be occurring at the individual-level. A few studies have measured the impact of honey bee abundance and apiary proximity on floral resource availability and floral resource collection by native bees. These studies, in concert with field studies of floral visitation patterns, have considerably advanced our understanding of honey bee competition impacts. However, no studies investigate changes in resource availability and resource use shifts simultaneously. Exploitative competition occurs when resource collection by one species negatively impacts resource collection by another species . Thus, studying impacts of increased honey bee abundance on both resource availability and resource use would provide a more complete picture of whether exploitative competition is truly occurring. Perhaps more importantly, such information gets us much closer to understanding whether competition might have negative fitness consequences for displaced species. For example, nft vertical farming if resource availability declines but visitation patterns remain static, there may be few pathways for native bees to behaviorally escape competition by using different resources. On the other hand, without evidence of declining resource availability, one cannot assume that exploitative competition is responsible for shifting interaction pattens. Understanding when and where honey bees compete with wild bees for floral resources has important consequences for agricultural pollination, honey bee management, and conservation policy. Honey bees contribute billions of dollars to the U.S. economy as crop pollinators and wildflower honey is a highly valuable agricultural commodity. However, native bees are also important pollinators, particularly for crop species not efficiently pollinated by honey bees and the integration of managed and wild bees can additively and synergistically improve crop yields . The most popular strategies for supporting honey bees and native bees include planting wildflowers in agricultural landscapes and preserving floral resources in natural landscapes.Indeed, abundant and diverse floral resources may prevent summer colony losses and mitigate negative impacts of disease and pesticide exposure . Unfortunately, floral resources are rapidly disappearing from agricultural landscapes in the United States , increasing interest among beekeepers in pasturing hives in more verdant natural landscapes .

However, scientists and conservation groups worry that non-native honey bees will compete with native bees for pollen and nectar resources , potentially endangering imperiled native bee species . In natural landscapes, and especially on public and protected lands in National Parks and Forests, co-managing for honey bees and native bees by planting sufficient flowers is not a management option. Instead, we must determine how, where, and when honey bees compete with native bees to guide decisions around hive densities and apiary locations. Our objective for this study was to assess whether honey bees compete with wild native bees for pollen and nectar resources using complementary measures of floral resource use and floral resource availability in two contrasting Californian landscapes: montane meadows in the Sierra mountains and wildflower planting neighboring almond orchards in the Central Valley. Both systems provide important floral resources to native bees but are also heavily used by managed honey bees. Wildflower plantings support honey bees immediately after almond pollination contracts and montane meadows provide abundant floral resources for summer honey production. As such, evaluating potential for competition is key to ensuring sustainable shared use of these landscapes. Using plant-pollinator visitation networks and data on the composition of pollen on native bee bodies, we asked whether increased honey bee abundance led to changes in apparent competition between honey bees and wild bees, wild bee specialization, and network-level complementary specialization. We also assessed whether wild bee pollen fidelity, pollen diet diversity, and pollen diet composition responded to changes in honey bee abundance. Lastly, we asked whether honey bee abundance influenced pollen and nectar availability in key flowering species from each system.We conducted this work in the California Central Valley at 5 replicated wildflower plantings neighboring almond orchards which we sampled in 2017 and 2018. We also sampled 15 meadows in the Central Sierra in 2019. In both ecosystems, some variation in honey bee abundance was due to site proximity to commercial apiaries. In the Sierra, we also experimentally supplemented three meadows initially free of honey bees with 20 hives. A full description of honey bee treatments in the Sierra is described in Page and Williams 2022 . For our Central Valley wildflower plantings, site selection and wildflower establishment methods are described in Rundlöf et al. . Sites averaged 1.6 km to the nearest neighboring site in the Sierra and 11.3 km to the nearest neighboring site in the Central Valley. Within each ecosystem, sites were in consistent landscape contexts and drew from the same regional species pools of native pollinators. In the Central Valley, we surveyed pollinators and their visits to flowering plants over four sample rounds from April – May. In the Sierra, we sampled sites from May – July. Most sites were sampled two to four times, but some sites were sampled up ten times if the blooms of Camassia quamash and Penstemon rydbergii lasted long enough. In the Central Valley, we netted insects actively visiting flowers during 10-minute walks of two 100 m2 transects which were each sampled once in the morning and once in the afternoon . In theSierra, we sampled one-hectare subplots that varied in floral species composition, netting active flower visitors while walking 100 m2 transects for two 30-minute periods in the morning and the afternoon . In both systems, we netted exclusively on sunny or partly cloudy days when average wind speeds were below 5 m/s and temperatures were above 13º C. Netted pollinators were collected individually in separate collection vials to minimize pollen contamination and euthanized using dry ice, except for bumble bee queens, which we identified on site and then released. In both systems, we collected up to twenty honey bees during netting transects and counted any additional honey bees. Native bee specimens were identified to morphospecies by expert taxonomists . For network analyses, we excluded bees not identified to morphospecies . Because we were exclusively interested in documenting patterns of honey bee vs. native bee competition, we also excluded non-bee floral visitors from network analyses.In the lab, we swabbed specimens with fuchsin-tinted gelatin cubes which we then melted onto microscope slides. We counted and identified pollen grains carried on bee bodies using a compound light microscope and pollen reference collections. We calculated pollen fidelity as the number of pollen grains from the plant species from which the specimen was caught divided by the total number of pollen grains in the swabbed sample. Most pollen was identified to species, but we sometimes grouped pollen grains at the genus level. We calculated pollen diversity using the Shannon-Weiner diversity index .We assessed whether honey bee abundance in wildflower plantings, measured as the total number of honey bees visiting flowering plants during morning and afternoon netting transects, was associated with perceived apparent competition , wild bee specialization , and complementary specialization using separate generalized linear mixed effects models for each network metric and each ecosystem.

Figure 1.12, in contrast, plots the naïve relationship between average picker productivity and piece rate wages, temperature, and two other observable characteristics: time of observation and worker tenure by season. First, note that productivity and piece rate are negatively correlated, since farmers lower the piece rate when fruit is plentiful in the fields. Second, note that there are no sharp decreases to average productivity at particularly high temperatures, as one may hypothesize. Finally, note that there is a clear increasing and concave relationship between worker tenure within a season and productivity. In other words, there is learning-by-doing in berry picking, and this learning has decreasing marginal returns over time. While most employees out-earn the hourly minimum wage under the piece rate system, some fall below this threshold and are paid according to the minimum wage for the day. As Graff Zivin and Neidell note, if there is not a credible threat that these workers could be fired for their low output, they may shirk and provide less effort than they otherwise would. Figure 1.13 plots the distribution of normalized daily productivity that identifies those picker days where shirking could be a problem. Observations to the left of one are picker-days where the picker’s effective hourly wage is below the minimum wage, raspberry cultivation pot and observations to the right of one are picker-days where the picker out-earns minimum wage under the piece rate scheme.

A picker with a normalized productivity measure of two is earning twice the minimum wage. Productivity in this figure is normalized because both piece rate wages and the hourly minimum wage vary over the sample period. Shirking, if it occurs, could bias my results. In particular, if high temperatures or low wages lead to more pickers earning the minimum wage, and these pickers subsequently shirk, my econometric estimates will be biased upward. I address this concern in section 1.6 by re-estimating my primary results using only those picker-days where employees out-earn the minimum wage. My findings do not change when I eliminate these observations, suggesting that the threat to a picker of being fired if they consistently slack off is a sufficient incentive to keep them from shirking.The model presented in section 1.2.1 motivates my empirical strategy. In particular, my goal is to estimate the relationship between piece rate wages and labor productivity . The primary challenges to this undertaking are twofold. First, many observable and unobservable factors contribute to worker productivity which – if unaccounted for – could lead to omitted variable bias in my estimates of temperature and wage effects. Second, piece rate wages are endogenous to labor productivity. To address factors other than the piece rate wage that could drive labor productivity, I exploit the richness of my data and include flexible controls for temperature, and a host of fixed effects.

Most importantly, I include time fixed effects to capture seasonality , work patterns , and season-specific shocks . I also include field-level fixed effects to capture variation in the productivity of different varieties and plantings of blueberry bushes. The combination of time- and field-level fixed effects gives me a credible control for the average density of blueberries available for harvest at a given time in a given field. In other words, these fixed effects allow me to control for resource abundance . Further, I include worker-specific fixed effects to capture heterogeneity in picker ability. Lastly, I include a quadratic of worker tenure to allow for learning-by-doing. When estimating the effect of temperature on productivity, my identifying assumption is that individual realizations of temperature are as good as random after including the controls described here and the piece rate wage. To address the endogeneity of piece rate wages to labor productivity, I instrument for these wages using California market prices for blueberries. In order for these prices to be a valid instrument for wages, they must be correlated with farms’ piece rates, but not affect labor productivity through any other channel. Figure 1.10 plots piece rate wages and market prices over time and suggests a strong correlation between the two variables. I provide formal evidence of this relationship in table 1.4, which I describe in detail in the following section. As evidence that the exclusion restriction holds – that market prices do not affect labor productivity except through wages – I rely on the size and heterogeneity of the California blueberry industry.

Statewide market prices capture supply shocks from growing regions around the globe, each with different weather, growing conditions, and labor markets. To the extent that environmental conditions agronomically drive blueberry production, they do so differentially across different growing regions of California. Therefore, any one farm’s temperature shocks in a given growing season do not determine aggregate blueberry supply. Additionally, both of the farms I study are quite small in comparison to the statewide market: they are price-takers and cannot independently affect average prices. As a result, market prices capture exogenous variation in aggregate supply shocks and serve as an effective instrument for piece rate wages.While the richness of my data allows me to exploit intra-day variation in temperature, I can also collapse my data to the day-level and investigate how daily temperature affects daily worker productivity. Figure 1.15 reports the results of three different day-level temperature specifications. The first uses time-weighted average daily temperature experienced by each picker, the second uses daily maximum temperature, and the third uses daily minimum temperature. Overall, the results from these specifications support the qualitative results of my primary specification: extreme temperatures lower picker productivity, and cool temperatures are more damaging than very hot temperatures. One threat to the credibility of my findings in tables 1.2 and 1.3 is that temperature and wages may affect workers’ labor supply, both on the intensive and extensive margins. That is, workers may decide to work fewer hours on a particularly hot day, or choose not to come to work at all if the piece rate wage is particularly low. Such behavior would bias my estimates of how temperature and wages affect productivity by introducing unobserved systematic selection into or out of my sample. I investigate this possibility in table 1.5 by regressing temperature, wages, and controls on both hours worked and the probability of working. In column , the dependent variable is the number of hours worked by a picker in a single day, and temperature is measured as a time-weighted average experienced by the picker during that day. Here, I control for a picker’s start-time rather than their picking “midpoint.” In column , the dependent variable is an indicator for whether a picker worked at all in a given day, and temperature is measured as a daily midpoint temperature: /2. I use daily midpoint temperature in column in order to provide a consistent comparison between employees who show up to work and employees who do not, since I do not know when or for how long these absent employees would have worked had they come to work. Figure 1.16 displays the relevant temperature results from columns and of table 1.5. Overall, table 1.5 reports that neither wages nor temperatures affect labor supply in a statistically significant way. Similar to Graff Zivin and Neidell , I find the labor supply of agricultural workers to be highly inelastic in the short run.

This also matches the findings of Sudarshan et al. for weaving workers in India. This evidence gives me confidence in the validity of my baseline results. I now turn to how temperature affects berry pickers’ wage responsiveness. Table 1.6 reports the results of estimating a variant of equation separately across eight temperature bins. I find that wages have no meaningful effect on productivity at most temperatures, low round pots but have a statistically significant and positive effect on productivity at cool temperatures: those between 50 and 60 degrees. In particular, my estimate suggests an increase in the piece rate wage of one cent per pound at temperatures below 60 degrees increases average productivity by 0.28 pounds per hour. This reflects an elasticity of productivity with respect to the wage of roughly 1.6 at cool temperatures, and an elasticity statistically indistinguishable from zero at other temperatures. This “productivity elasticity” is considerably smaller than the 2.14 number estimated by Paarsch and Shearer . Table 1.7, which repeats the analysis from table 1.6 using ordinary least squares , highlights the importance of instrumenting for piece rate wages. This table highlights two important things. First, the effects of wages on productivity at low temperatures do not show up in a statistically significant way without correctly instrumenting for wages with market prices. Second, I am able to rule out any dramatically large effect of wages on productivity at most temperatures. Another threat to my findings is that workers who do not out-earn the hourly minimum wage in a given day may shirk when they know that additional productivity will not increase their take-home pay. Figure 1.13 reports the frequency with which workers fall below this minimum wage threshold. I face an econometric problem if the effects of temperature reduce workers’ productivity, increase the probability that workers earn the minimum wage, and hence encourage shirking. To ensure my findings are not meaningfully altered by this phenomenon, I re-estimate my main results using only picker observations where the picker out-earns the minimum wage for the day. This procedure drops my number of picking period observations from 305,980 to 257,689: a decrease of 15.8%. Figure 1.17 and table 1.8 present the results of my main temperature and piece rate wage specifications using this subsample. Finally, even if temperature and wages do not affect labor supply directly in a statistically significant manner, and even though worker-specific fixed effects capture individual workers’ average productivity levels, I still face a potential adverse selection problem. Specifically, if variation in temperature and wages affects which sorts of workers choose to show up for work, my results may capture workforce compositional effects rather than individual productivity effects. To address this concern, I re-estimate my results only using observations from those workers who work more than thirty days in the relevant season. The intention here is to focus on workers who are likely to have the least elastic extensive labor supply. The results of this robustness exercise are presented in figure 1.18 and table 1.9. Taken together with the other available evidence, these results largely support my baseline findings.My primary finding is that labor productivity, on average, is very inelastic with respect to piece rate wages: I can reject with 95% confidence even modest positive elasticities of up to 0.7. This upper bound is considerably lower than the estimates derived by Paarsch and Shearer and Haley . I show that, without controlling for seasonality, a regression of productivity on piece rate wages results in a negative and significant point estimate . However, even once I control for seasonality, a naïve OLS regression of productivity on piece rate wage may be biased toward zero of table 1.4. By instrumenting for piece rate wages with the market price for blueberries, I can identify a precisely-estimated inelastic effect of table 1.2. However, my primary specification makes the restrictive assumption that wages affect productivity linearly and in the same manner at all temperatures. Table 1.6 confirms that piece rates’ effect on productivity is very much non-linear across different temperatures. Specifically, wages seem to spur productivity at cool temperatures . At other temperatures, wages do not affect productivity in a statistically significant way. This empirical finding directly challenges one of the core assumptions of the model presented in section 1.2.1: that productivity always rises with the wage . What is going on? One possible explanation for my findings is that, at moderate to hot temperatures, workers’ face some binding physiological constraint on effort that prevents them from responding to changes in their wage. Put bluntly, blueberry pickers in general may already be “giving all they’ve got” at the temperatures and wages I observe. Figure 1.19 summarizes this possibility using the theoretical framework developed in section 1.2.1. While the model in section 1.2.1 is straightforward and tractable, it is not the only way to conceptualize worker effort and productivity. In particular, rather than modeling effort as an unrestricted choice variable, one could assume each worker has a finite daily budget of effort that must be allocated across different activities throughout a day and Becker . Such a model would allow Xr to be zero or even negative under certain conditions, implying a backwards-bending effort supply curve, somewhat analogous to the canonical backward-bending labor supply curve .

Phenolic extraction parameters and effects of wet and dried pomegranate peel were studied, aiming to increase the extraction sustainability with reduced cost. The chemical characteristics of the extracted components were also evaluated. The study in Chapter 3 investigated the potential of developing functional food fortified with a value-added ingredient from pomegranate peel extract, specifically Greek Style Yogurt. Products with different levels of protein content and phenolic content were formulated to study the chemical and sensory properties, which provided solid guidance for future product development. In the research of Chapter 4, the hypolipidemic properties of pomegranate peel and extract were investigated in vivo using hamster models. Currently, no literature is available on the functionality of complete pomegranate peel and extract. In this study, dutch bucket for tomatoes it was found that the pomegranate peel and extract were effective in lowering blood cholesterol in hamsters fed with high-fat diets. The study in Chapter 5 studied the co-extraction mechanism of pectin and polyphenol for improved extract yield and phenolic stability.

Ultrasound extraction of pectin and polyphenol in citric acid from pomegranate peel was tested and the corresponding physicochemical properties were evaluated. Unlike most of the research using inorganic acid for extraction, this research utilized GRAS organic acid and provided functional ingredients from fruit by-products without safety concerns. Conclusions and future directions on reutilizing the pomegranate waste as food ingredients are detailed in Chapter 6.Pomegranate belongs to the family Punicaceae. It has been grown since ancient times for its delicious fruit and as an ornamental plant for its red, orange, or occasionally creamy yellow flowers. The estimated global cultivation area for pomegranate is about 300,000 ha, with fruit production of 3.0 million metric tons . Spanish missionaries brought pomegranate to the Americas in the 1500s . Wonderful, a primary cultivar in the U.S., was discovered in Florida and brought to California in 1896. Since then, pomegranate has been grown abundantly in California and Arizona, where mild winters enable the fruits to reach the quality necessary for successful commercial production. In 2015, about 282,000 tons of pomegranate fruit were grown in California, with an economic value of $115.4 million .

Pomegranate consists of three major parts , namely pomegranate peel , pomegranate seed , and pomegranate aril that is the flesh part for pomegranate juice production. Teh studied the different fruit part distribution of 5 pomegranate cultivars grown in California, observed a range of 38.33~50.38% PJ, 38.77~53.01% PP, and 7.71~12.10% PS. The study also determined the components of PP and PS through proximate analysis. The peel portion consisted of 90.6~91.9% carbohydrate as the principal constituent, followed by 3.1~3.9% protein, 1.3~2.3% fat, and 3.3~4.3% ash or minerals. The PS contained higher proportions of protein and fat and included 60.5~71.8% carbohydrate and 1.6~2.5% minerals. PJ consisted of 85% water, 10% total sugars, organic acids,amino acids, and phenolics. Pomegranate exhibits a sweet, sweet-sour, or sour taste, which color ranges from white to pink and red .Traditional processes in the pomegranate juice industry squeezed the whole pomegranate, which had low yield, impurity, and bitter taste due to non-edible parts. Nowadays, novel techniques introduced a deseeding step at the beginning. Then the seed, aril, and juice are separated from the peel and squeezed, while the peel and the remaining pulp are discarded as wastes in landfills or used as animal feed. The juice stream continues to go through the processes of pasteurization, centrifugation, membrane process, storage, and quality assessment. Other juice extraction methods and their features were also discussed by as shown in Figure 1.2. PJ processing generates two types of solid by-products: peel and seeds. PP is non-edible and comprised mainly of bio-active compounds, such as hydrolyzable tannins at concentrations ranging from 27 to 172 g kg-1 , flavonoids ,and complex polysaccharides .

Therefore, PP is an excellent source of phenolic compounds, tannins, flavonoids, sterols, fatty acids, dietary fiber, minerals, and vitamins.Fruit and vegetable pomace has a long history of simply being disposed of in landfills or underutilized as fertilizers and soil conditioners. Several studies investigated the health potential of supplementing PP into animal feed. Modaresi et al., added 12% pomegranate seed pulp into the goat diets and observed increased polyunsaturated and conjugated fatty acids in goat milk. A feed with 1-2% PP lowered cholesterol levels and improved oxidative stability in the harvested boiler chicken meats . Shabtay et al. supplemented PP in calves’ diets and observed a significant increase in weight gain and blood antioxidant contents in the ruminants. Therefore, pomegranate pomace demonstrated great potentials for nutritional feed with improved health benefits in ruminant and chicken feed. Due to the massive quantity of pomace, the convenience of disposal, and low realizable revenue from current waste utilization practices, processors and farmers have a low incentive to apply alternative waste management methods. With the pressure of climate change, energy shortage, and increasing nutritional needs, creating value-added products from the by-products would be an outstanding solution to incentivize novel waste practices. Food additives and packaging materials With an enormous amount and variety of polyphenols within the pomace, pomegranate by-products demonstrated great antioxidant and anti-microbial properties, which contributed to diverse application potentials as food additives and packaging materials. Lipid oxidation is the principal deteriorative reaction during food processing and storage. It sharply reduces the product shelf life, destroys essential nutritional components, and generates toxic compounds which pose hazards to human health . Synthetic antioxidants have been dominantly applied in the food industry to prevent oxidation, such as butylated hydroxytoluene and butylated hydroxyanisole . Natural antioxidants are gaining attention as consumers prefer safe and natural ingredients . Topuz et al. incorporated alcoholic extract of PP into anchovy fish oil and observed a dose-dependent inhibitory effect on lipid oxidation, especially at a concentration of 500–1000 ppm. The antioxidant capacity of 500 ppm of PP extract was comparable with that of 100 ppm of BHT, indicating that PPE could be applied as a potent antioxidant. Turgut et al., infused PPE into freshly minced beef at 5000/10000 ppm and compared it with 100 ppm BHT.Their results demonstrated a lower thiobarbituric acid reactive substances value, peroxide formation, and other parameters, suggesting promising oxidation retarding effect of lipid and protein in pomegranate extract. However, they also observed a potential negative change of sensory value after extract addition, which required further research to quantitatively investigate the effects. Similar research also proved the preservative effects of pomegranate extract in burgers and cheese . A more comprehensive review on the practical use of PP in meat products was reported by Smaoui et al., . PP may also prevent foodborne illness, which has been a worldwide safety concern. In the USA, there were millions of cases related to food contamination and foodborne outbreak each year, posing a severe threat to public health . Traditional synthetic antimicrobial agents may have potential side effects, are expensive, blueberry grow pot and could induce drug resistance of microorganisms as their indiscriminate killing effects . Natural anti-microbial agents are needed. Pomegranate is rich in polyphenols, which can inhibit bacterial growth by interacting with the sulfhydryl groups of bacterial cell wall proteins and forming complexes, and then induce lysis . More applications of pomegranate by-products as anti-microbial agents could be found in Singh et al. . Biotechnological products Biofuel is considered an ideal alternative to fossil fuel, as fossil fuels are experiencing a rapid depletion, uncertainty in the price, and contributing to significant environmental pollution .

Biofuel is produced from biomass via thermochemical processes, including gasification, carbonization, pyrolysis, and direct combustion. Among all the methods, pyrolysis is considered the most viable due to its simplicity, cost-effectiveness, and wide range of final products . Siddiqui et al. studied the optimizedprocess parameters for biochar production from PP. Results showed that, at a temperature of 300 °C, the pyrolysis reaction time of 20 min and the particle size of 3 mm, biochar could be produced at a yield of 54.9% with an improved higher heating value at 23.5 from 14.61 MJ/kg of parent biomass. Besides energy supply, PP-based biochar also demonstrated a desirable ability in eliminating inorganic compounds from water and CO2capture/storage . As for biofuel, Demiray et al. optimized bioethanol production from PP by Saccharomyces cerevisiae and Pichia stipites. They successfully increased the ethanol yield produced by S. cerevisiae up to 44.9%. Ethanol productivity and Ethanol yield of S. cerevisiae increased to 0.46 g/L/h and 0.43 g/g, respectively. These findings along with other similar research have demonstrated that PP is a promising biofuel source.Polyphenols, a family of molecules, are commonly found in fruits, vegetables, nuts, seeds, flowers, and tree bark. These components fundamentally are plant metabolites to attract pollinators, but research concluded multiple pharmaceutical effects, including antioxidant, antimicrobial, anti-cancer, etc . This family derives from a fundamental polyphenol group . The structure ranges from simple elementary substances to complex polymerized molecules , contributing to a diversified classification profile . Furthermore, sugar residues can conjugate with the hydroxylgroups of natural polyphenols through direct linkage of the sugar unit to an aromatic carbon, further diversifying the polyphenol structure . Based on the number of phenol rings and the binding components, polyphenols can be classified into the following 5 types of sub-groups: hydroxybenzoic acid, hydroxycinnamic acid, flavonoids, stilbenes, and lignans , as illustrated in Figure 1.3.According to Fischer et al., , PP is an ideal source for polyphenol, as 48 types of polyphenols were detected within, including 9 anthocyanins, 2 gallotannins, 22 ellagitannins , 2 gallagyl esters, 4 hydroxybenzoic acids, 7 hydroxycinnamic acids, and 1 dihydroflavonol. Among the polyphenols in pomegranate, punicalagin is the most abundant and unique water-soluble ellagitannin within. Besides PP and PJ, PUs are also commonly found in the leaves of Lafoensia pacari .The synthesis pathway of PU is shown in Figure 1.4. Phenolic acids including two gallic acids and ellagic acid are combined to form gallagic acid. With glucose addition, gallagic acid can form punicalin and be further transformed into PU by adding an EA. The difference in the glucose carbon-1 induces two isomers of PU . These features provided higher functionality with a large number of hydroxyl groups and a lower chance of degradation. A typical phenolic composition distribution in HPLC analysis is shown in Figure 1.5 .MAE is another common extraction method with reducing extraction time and solvent consumption. The heat and mass transfer processes take place at the same time and accelerate the overall extraction. Kaderides, Papaoikonomou, Serafim, & Goula compared the extraction performance of microwave-assisted extraction and the UAE. Results showed that the optimal MAE condition was using 60mL 50% aqueous ethanol per gram at 600 W power for 4 mins, with an extract yield of 199.4 mg/g GAE, PU yield of 143.64 mg/g, and radical scavenging activity of 94.91%. In contrast to 10 mins of UAE at 52 W power using 32.2mL water per gram peel at 35⁰C, MAE achieved 1.7 times higher extract yield in a shorter processing time , which was due to higher cell destruction but similar PU yield and scavenging activity. Limited research has focused on this topic so far. Researchers suggested a focus on the MAE-assisted process to achieve a high yield of polyphenols as well as extract with great polyphenol profile and quality.PU is sensitive to temperature and pH. Therefore, conventional hot acidic processing methods might increase the hydrolysis of PU and reduce its bio-activity. Alexandre et al. proposed that cellulase and pectinase degraded the cell wall and released the intact PU along with pectin. They compared extraction under 300/600 MPa high pressure with that using 4% cellulase and pectinase. As result, enzymatic extraction yielded 1481.29 μg/g TPC with 62.9% PU, significantly higher than extraction at 300MPa and slightly lower than 600 MPa . Talekar, Patti, Vijayraghavan, & Arora, applied 55 U/g cellulases at a solvent ratio of 15 mL/g for 4h with 20 min ultrasound treatment. As the results, 84.8 mg/g PU was recovered, accounting for 71.2% of its TPC and was superior to the ones recovered by a conventional method . This result demonstrated reduced hydrolysis of PU under mild enzymatic extraction. Since enzymes could be costly due to low recovery and reusability, biocatalyst became a more sustainable option. Biocatalyst immobilizes enzymes onto solid phase for selective enzyme recovery after the reaction. Talekar et al., experimented with extraction with magnetic nanocatalyst of FeSO47H2O and FeCl36H2O solutions, which yielded 64.2–66.5 mg/g PU . It was lower than their previous research using cellulase . However, the nanocatalysts are recyclable and could reduce the cost of cellulase.Compared to other processing methods, enzymatic extraction might have less TPC. On the other hand, it is desirable for PU retention.

A recent study utilized an industrially scalable delivery of self-replicating viral vectors to transform a variety of crop species, such as tomato, potato, and spinach, with successful alterations to reproduction, stature, and drought tolerance . This method could befurther developed for the introduction of biosynthetic pathways for bio-active phytochemicals into single generations of crop species. Advancements in the host range and efficacy of transient expression will make plants a better platform for the production of plant natural products and the characterization of pathways in hosts before the generation of stable plant lines. Transgenic plants can be grown in open fields, allowing plant natural products to be purified at large scales. However, the generation of stable plant lines is arduous, typically requiring the use of low-efficiency transgene delivery methods with Agrobacterium or particle bombardment, the generation of calli, the growth of the new, transgenic plant, vertical hydroponic nft system and the confirmation that the transgene is properly inserted. This results in long regeneration times, a requirement for numerous generations of backcrossing, and limits the size and location of transgene insertions.

A series of studies have begun to ameliorate this by creating transformation methods in maize that have increased the number of genotypes amenable to transformation, removed the need to generate calli, and utilized systems to remove selectable markers . Additionally, improvements over the size of transgenes that can be inserted have been made. Dong et al. utilized CRISPR-Cas9 in rice to perform targeted insertion of the 5.2 kb carotenoid biosynthesis pathway in a genomic safe harbor to limit adverse insertion effects. This method also limits the segregation of transgenes in subsequent generations, potentially reducing the number of crosses needed. With simplification of breeding efforts, the production of nutraceuticals and phytochemicals in transgenic plants will be ready for market more rapidly by requiring less screening of transgenic plant lines for insertional effects. Another example utilized a gene stacking method called TransGene Stacking II to generate and insert a 31 kb cassette encoding an anthocyanin pathway into rice grain . The utilization of gene stacking and targeted integration will enable long, complex pathways to be inserted with minimal adverse insertion effects . Together, these techniques have improved the feasibility of making stable plant lines expressing complex metabolic pathways for nutraceuticals and phytochemicals.

Many transformation techniques that generate stable transgenics require lengthy and expensive approval processes before becoming marketable . The use of gene editing tools with high target specificity that can be removed from future generations is able to circumvent these approval processes. One example is the modification of soybeans through TALEN site-directed mutagenesis, wherein natural soybean oil contains high levels of linoleic acid, an undesirable compound increasing the risk of heart attacks . In this work, FAD2-1 was disrupted, reducing the content of undesirable linoleic acid while simultaneously increasing its desirable precursor, oleic acid. With the discovery of DNA-free CRISPR-Cas9 genome editing in plants, these same types of modifications could be made to other nutritive regulator genes in a much shorter timescale . While these systems are subject to less regulation, they are unable to incorporate genes in heterologous pathways, limiting their use in plant synthetic biology. In addition to regulatory concerns, criticism of genetically modified crops by the public has slowed the advancement of crop engineering. Further engagement between scientists and the public will be needed to improve the overall opinion of transgenic crops .While supplements generated through microbial production or extraction from a native plant host can often be used as a source for the consumption of nutrients, plants serve as both a production platform and a vector for the delivery of nutritional and therapeutic small molecules. In addition to removing the need for costly purification processes, the delivery of small molecules through edible plants provides a low-cost solution to delivering critical nutrients and medicines.

The expression of pathways to improve the nutrient profile of staple crops is thus a promising method to improve access to the health benefits of a diverse diet. Anthocyanins are commonly consumed flavonoids with antioxidant activity that are believed to play a preventive role in many diseases, including cancer . With the expression of two transcription factors from A. majus by a fruit-specific promoter, tomatoes, normally devoid of anthocyanins, accumulated high concentrations of 2.83 ± 0.46 mg/g fresh weight and displayed purple coloring. Subsequent feeding experiments in cancer susceptible Trp53−/− mice with purple, anthocyanin-producing tomatoes significantly improve life span compared to control groups fed a normal diet or diet supplemented with red tomatoes . If made available to the public, purple tomatoes could serve as a broadly available source of health promoting anthocyanins. Additionally, anthocyanin-producing purple rice was developed through the expression of eight transgenes driven by endosperm-specific promoters, resulting in anthocyanin accumulation of 1 mg/g dry weight . By generating these crops, nutraceuticals can be delivered through the foods we eat, rather than with the use of a supplement. This has the potential to improve the accessibility of nutraceuticals. Artemisinin is a sesquiterpene lactone used in the treatment of malaria, whose biosynthesis has received a large amount of attention. One study optimized the production of artemisinin through the compartmentalization of the biosynthesic pathway to the cytosol, mitochondria, and chloroplast in N. tabacum . Crushed tobacco leaves synthesizing artemisinin, wildtype tobacco leaves, and pure artemisinin were then fed to mice infected with Plasmodium berghei, and parasitemia was monitored. Mice fed with tobacco leaves containing artemisinin showed reduced parasitemia and delayed onset of malaria symptoms compared to mice fed wild type tissue and pure artemisinin . While tobacco is not considered an edible crop, this approach shows the potential for engineered foods to serve as a delivery vehicle for important therapeutics. As plant synthetic biology advances and the yields of therapeutic small molecules in plants are improved, developing methods to control the dose of the target molecule will be needed.As organisms with multiple cellular compartments and tissue types, plants are ideally suited for the expression of complex metabolic pathways that require compartmentalization . The precise control over localization is particularly important when pathway intermediates are toxic. Strictosidine is an important intermediate in the production of the chemotherapy drug, vincristine. The strictosidine aglycone is a toxic intermediate in the strictosidine biosynthetic pathway that is normally sequestered to the vacuole before glycosylation. Viral induced gene silencing of a suspected strictosidine-glycosyl transporter, CfNPF2.9, resulted in blackening of leaf tissue in C. roseus, displaying the necessary role of transporters in plant natural product biosynthesis . As many metabolic pathways are compartmentalized, the use of transporters permits the movement of key intermediates synthesized in one compartment to the location of the enzymes required for the final steps of a biosynthetic pathway. This is further emphasized in the biosynthesis of aliphatic and indolic glucosinolates, which takes place in the cytosol and chloroplast. One study utilized a bile acid transporter to improve the heterologous yields of a precursor to the chemopreventive glucosinolate, glucoraphanin. Bile acid transporter 5 was demonstrated to be a plastidic transporter of the methioninederived α-keto acid and increased the production of the glucoraphanin precursor, dihomomethionine, by 10-fold . Many metabolites are synthesized in one tissue and transported to another as a means of storage or defense. Intercellular glucoraphanin transporters have been identified, which are responsible for the transport of glucoraphanin to seeds in A. thaliana .

The identification of these transporters allows for the transport of chemopreventive glucoraphanin to seeds of crops species to improve dietary consumption. Additionally, nft hydroponic system the use of transporters could allow for the concentration of metabolites into a specific tissue type, which would simplify harvest and extraction. Thus, there is a need to increase our understanding of transporters to enable the utilization of compartmentalization in the heterologous expression of metabolic pathways. However, most current methods are low throughput relying on the generation of complex yeast strains or plants with mutant transporters . One method utilizing Xenopus laevis oocytes expressing putative transporters has been demonstrated to improve the throughput of transporter screening by multiplexing transporters . Moreover, there is also a severe lack of structural information on plant specialized metabolite transporters, with less than a handful of known structures . An increase in the number of solved metabolite transporter structures could alleviate the need for enzymatic characterization through the use of prediction software, such as TransportTP . The compartmentalization of plant natural products into different tissue types provides a unique means for the production and storage of nutraceuticals and phytochemicals. Tissue-specific promoters enable the expression of metabolic pathways in a select tissue type. In one study, a bidirectional, embryo-specific promoter was used to drive the expression of anthocyanin genes in maize . The bidirectional promoter was then engineered with additional cis-elements to generate a construct expressing anthocyanin genes in both the endosperm and embryo . Additionally, specific plant tissues, such as trichomes, naturally accumulate large amounts of valuable plant natural products, thus making them promising targets for metabolic engineering. In one study, two genes required for methylketone synthesis, ShMKS1 and ShMKS2, were expressed constitutively alone or together in N. tabacum, A. thaliana, and cultivated tomato . While this resulted in methylketone production, it also caused severe lesions. However, by expressing ShMKS2 using a trichomespecific promoter, a significant increase in methylketone levels was observed with no other morphological defects . In another study, the trichomes of G. hitsutum L. were engineered to produce melanin through the expression of two genes driven by a cotton fiber-specific promoter. This enabled the production of brown-colored cotton fibers containing melanin, which could serve as a UV protectant and a natural pigment . These studies show the efficacy of tissue-specific expression as a means to produce useful small molecules. Future research should aim to identify and develop tissue-specific promoters that allow for targeted expression of pathways. Plant compartmentalization also enables organelles to produce and accumulate high amounts of a specific molecule of interest . Much work has been done to improve the availability of plant natural product precursors by targeting enzymes to specific organelles. Amorpha-4,11-diene is an important precursor to artemisinin. By targeting two enzymes involved in amorpha-4,11- diene synthesis to the chloroplast, amorpha-4,11-diene concentrations were improved by 40,000-fold compared to plants targeting the two enzymes to the cytosol . Additionally, the localization of enzymes can alter its stability or activity. One study found that targeting tryptophan decarboxylase to the chloroplast improved accumulation and stability of the enzyme compared to its cytosolic counterpart . Targeting enzymes to different cellular compartments can substantially improve the function of enzymes and the production of plant natural products.The expression of heterologous pathways can introduce a tremendous metabolic burden on the host organism. The use of large amounts of cellular resources, such as carbon sources, ATP, and NADH, can lead to undesirable physiologicalchanges that reduce host fitness and product titers . Mitigating the metabolic burden of heterologous pathways can be accomplished through host engineering. Additionally, the use of engineered hosts can improve the yields of target metabolites. Microbial synthetic biologists have used host engineering to improve the production of various important small molecules, which can serve as an example for plant synthetic biology. Phenylalanine is an important precursor for the synthesis of many plant natural products, such as phenylpropanoids and aromatic glucosinolates as well as many industrial applications, such as aspartame production . The E. coli strain, ATCC31884, has been engineered to overproduce phenylalanine. One study utilized ATCC31884 alongside changes to phenylalanine, tyrosine, and shikimate biosynthesis to improve the production of chorismate. The high chorismate producing strain was then used to produce muconic acid, which resulted in yields of 1.5 g/L after 48 h of growth . ATCC31884 has been further altered to improve the diversity of chemicals it can be engineered to make. Huang et al. knocked down two genes required for phenylalanine expression in ATCC31884 while expressing a feedback-insensitive mutant of tyrA to improve the levels of tyrosine, which enabled the strain to make 15- fold greater caffeic acid than the previous highest yield . These examples of microbial host engineering should serve as inspiration for plant synthetic biologists to engineer plant production platforms for optimized production. Plants like N. benthamiana could be altered in a similar fashion to E. coli strain ATCC31884 as a plant background designed for the production of phenylalanine-derived plant natural products.

We then tested how CquiOR21 would respond to other commercially available repellents, i.e., PMD, IR3535, and picaridin. In these new preparations, CquiOR21/CquiOrcoexpressing oocytes responded to DEET and IR3535 with dose-dependent outward currents . Picaridin elicited minor outward currents at lower doses but robust outward currents at 1 mM dose. By contrast, PMD did not elicit outward currents; it was silent at lower doses and gave minor inward currents at the highest dose, 1 mM . We then interrogated CquiOR21 orthologs from the yellow fever mosquito, AaegOR10 , and the malaria mosquito, AgamOR10 . AaegOR10/AaegOrco- and AgamOR10/AgamOrco-expressing oocytes responded with a similar pattern to that observed with CquiOR21/CquiOrco-expressing oocytes . Specifically, DEET generated dose-dependent outward currents as did picaridin at 1 mM, whereas PMD elicited only minor currents. Over the years, stackable planters we have deorphanized multiple ORs from Cx. quinquefasciatus and were surprised to observe that these outward currents generated only with preparations involving ORs sensitive to oviposition attractants. We then tested other ORs for oviposition attractants, namely CquiOR121 , CquiOR37, and CquiOR99 .

Oocytes expressing each of these ORs along with the obligatory coreceptor Orco elicited dose dependent outward currents when challenged with DEET . We also challenged other ORs from the malaria mosquito, which are not involved in the reception of oviposition attractants. Like their Culex counterparts, ORs unrelated to oviposition attractants did not generate outward currents when challenged with DEET . A previously reported larval OR, AgamOR40 generated dose-dependent inward currents in response to DEET as well as to its best ligand, fenchone . By contrast, oocytes expressing AgamOR8 along with AgamOrco generated robust, dose-dependent inward currents in response to 1-octen-3-ol, but it was silent to DEET . Previously, it has been demonstrated that DEET modulates responses of other odorants to ORs , but no outward currents were recorded. When odorants were present in combination with DEET at high I doses, the odorant-induced inward currents decreased significantly , but DEET per se did not elicit measurable currents. At the time of this writing, a small DEETinduced hyperpolarization of a mosquito OR was reported . Our fortuitous discovery of outward current elicited by DEET might occur mainly on ORs sensitive to oviposition attractants.

However, we have recently reported outward current selicited by multiple compounds, including repellents, on a Culex OR, CquiOR32, which is sensitive to a plant-derived compound with repellency activity, methyl salicylate . It is, therefore, conceivable that the phenomenon expands beyond OR sensitive to mosquito oviposition attractants. Next, we challenged CquiOR21, AaegOR10, and AgamOR10 with a panel of 20 compounds, which includes plant-derived and plant-inspired repellents. The compounds are part of pending worldwide and US patent applications and have been previously tested as oviposition deterrents for an agricultural pest, the navel orangeworm, Amyelois transitella . The panel was provided to the experimenter with code names, i.e., BDR1-20. To make certain the compounds would be properly identified post hoc, one of us analyzed each sample by GC-MS before electrophysiology and behavior work. None of the 20 compounds elicited inward currents , and 4 compounds did not generate measurable currents, specifically BDR-7, 11, 15, and 20, which were later decoded by W.S.L. to the experimenter. They are ethyl palmitate, 2-pentadecanol, dihydrojasmonic acid, and 2-pentadecanone, respectively. Other compounds generated robust outward currents at least in one of the three ORs tested. They are BDR-3 , BDR-4 , BDR-10 , BDR-14 , and BDR-19 .

Of note, repellency activity for methyl jasmonate and methyl dihydrojasmonate has been previously demonstrated. Using AgamOR10/AgamOrco-expressing oocytes , we recorded dose-dependent outward currents generated by these compounds at 0.01, 0.1, and 1 mM. We then investigated whether these outward currents would modulate CquiOR21 responses to skatole. Thus, CquiOR21/CquiOrco-expressing oocytes were challenged with skatole alone or in mixtures with one of the test compounds. Based on preliminary experiments showing that DEET modulates the response to skatole, we selected DEET as a positive control and tested two compounds from our panel, which generated strong/moderate and weak outward currents, i.e., BDR-4 and 5, respectively . Skatole was presented at a constant dose of 0.1 μM, and the tested compounds were added at decreasing doses from 1 mM to 15 μM . When mixtures of skatole and DEET or BDR-4 at high doses were applied, outward currents were recorded, whereas attenuated inward currents were observed with mixtures containing BDR-5 at the same doses . The effect of DEET and BDR-4 on CquiOR21 responses to skatole was clearly dose-dependent. When the test compounds were coapplied at 125 μM or lower, only inward currents were recorded. In the case of DEET and BDR-4, the inward currents were attenuated even when these compounds were presented at the lowest dose of 15 μM . Although this dataset clearly shows that responses to skatole were modulated by DEET , it does not explain the mode of action of DEET as a noncontact disengagent . Mosquitoes responding to CquiOR21 are not host-seeking mosquitoes, but rather gravid females searching for oviposition sites. The observed modulation may explain at least in part the “off-label” activity of DEET as a deterrent for oviposition .Next, we asked whether compounds modulating OR response to oviposition attractants would activate a DEET receptor mediating spatial repellency .Previously, we have identified CquiOR136 as a DEET receptor in the Southern house mosquito , which is activated by the four major commercially available repellents, DEET, PMD, IR3535, and picaridin . CquiOR136/CquiOrcoexpressing oocytes were challenged with our panel at three doses . IR3535, which elicits the strongest responses at 1 mM , was used as a positive control. BDR-3 and BDR-14 , among other compounds, elicited robust inward currents . We then constructed concentration-response relationships for all compounds in our panel . These analyses clearly show that BDR-14 is the best ligand for CquiOR136 from all tested compounds thus far. More importantly, our data show that CquiOR136 is very sensitive to plant-derived compounds . Specifically, CquiOR136/CquiOrcoexpressing oocytes gave robust responses to methyl dihydrojasmolate, methyl dihydrojasmonate, ethyl dihydrojasmonate, dihydrojasminlactone, dihydrojasmindiol, and methyl jasmonate, which are plant metabolites or their derivatives . Methyl dihydrojasmolate is a reduced form of methyl dihydrojasmonate , which in turn is the product of hydrogenation of the plant hormone methyl jasmonate. That this DEET receptor is very sensitive to these plant-derived and plant-inspired compounds is consistent with the notion that the primary function of CquiOR136 in the biology of Cx. quinquefasciatus is the reception of plant defense compounds and that DEET mimics these natural products .Our data suggest that mosquito response to oviposition attractants may be modulated by repellents. When ORs sensitive to oviposition attractants were challenged with repellent, stacking pots outward currents were generated. Responses of the OR detecting the oviposition skatole in the Southern house mosquito, CquiOR21 , were reduced when skatole was coapplied with DEET or methyl dihydrojasmolate. These inhibitory currents may explain at least in part, the deterrent effect of DEET on the attraction of gravid females . Therefore, DEET-mediated oviposition deterrence may have two modes of action . More importantly, the discovery of inhibitory currents demonstrates that the integration of chemical signals at the peripheral olfactory system is more complex than previously appreciated.Blueberries have been widely studied for their high phytonutrient content, particularly phenolic compounds.

Dietary polyphenols found in blueberries consist of flavonoids and phenolic acids . Anthocyanins are the pigments responsible for the color of berries and blueberries have one of the highest anthocyanin contents among foods . The individual anthocyanin profile of blueberries is complex and contains 5 of the 6 anthocyanidins commonly present in food: malvidin, cyanidin, delphinidin, petunidin, and peonidin . The glycoside moieties attached to the anthocyanidin are predominantly galactose, arabinose, and glucose , with all combinations of the 5 anthocyanidins and 3 sugars found across blueberry cultivars. Blueberries are also rich in flavonols, with a predominance of quercetin derivatives , and proanthocyanidins, formed by polymerization of catechin and/or epicatechin units . Nonflavonoid phenolic acids are mainly represented by chlorogenic acid, which results from the esterification of caffeic acid with a quinic acid molecule . Blueberry phytochemicals used in the treatment of cells in vitro often consist of a whole extract, delivered as a reconstituted powder, juice, or pomace , concentrated or not. Specific classes of phytochemicals such as polyphenol-rich extracts and phenolic fractions, including anthocyanins, phenolic acids, and proanthocyanidins are prepared using solvent extraction and purified through solid phase extraction.Polyphenols found in blueberries have been shown to contribute to their health benefits . A number of reviews discuss the association between blueberry consumption and cardiovascular health , inflammatory markers , type 2 diabetes, neuroprotection, and ocular health . These claims on the health benefits of blueberry consumption are supported by epidemiological studies , animal studies , and diverse cell culture models . Randomized controlled trials have investigated antioxidant and anti-inflammatory effects of blueberry in the context of hypertension, cardiovascular diseases, arthritis, insulin resistance, and metabolic syndrome and supplemented with doses between 20 and 50 g of wild blueberry powder, equivalent to 1 to 2 cups of fresh blueberries daily for 6 to 16 wk . However, few reported direct modulation of molecular markers via blueberry supplementation, including circulating inflammatory cytokines and adhesion molecules. To complete and extend the body of literature covering the in vivo physiological effects of blueberry feeding, the current review considers mechanisms of action by focusingon in vitro responses to blueberry components. Evaluation of the bio-active potential of berry phytochemicals or extracts often uses cell models , which serve as controlled, simplified systems . Numerous limitations exist regarding cell culture conditions and the artificial environment in which the cells are maintained, because they are not completely representative of the body’s physiology . In general, cells are treated with parent compounds, disregarding potential host and microbial metabolism between consumption and the moment compounds reach the target organ . Cells are also not always treated with amounts representative of physiological concentrations in the body, which can be low due to the limited absorption of polyphenols . They are relatively simple to access and maintain, and provide insights into the cellular mechanisms of the studied compounds . Although blueberry phytochemicals may impact a multitude of health-related mechanisms, we focused on 2 intrinsically related systems , the regulation of which are central to health, and when dysregulated, underlie many disease outcomes. The objective of this narrative review is to discuss observations related to the modulatory role of blueberry phytochemicals on key pathways implicated in systems, and to consider the results from a physiological perspective.Search queries containing the keywords “inflammation”, “anti-inflammatory”, “oxidative stress”, “cell culture”, “in vitro”, and “berry” were conducted in the PubMed and Science Direct databases. The search was conducted for articles through to August 2021. Duplicates, reviews, articles written in languages other than English, and studies using animal models or human participants were excluded with the caveat that studies focusing on animals and/or humans but containing complementary cell-based experiments were included and an evaluation of the cell model findings used in the current review. From all studies on berries and cell culture-based models retrieved, only studies using blueberries were included. In this article, the term “blueberry” encompasses fruits from the Vaccinium genus described as blueberries, including V. angustifolium, V. corymbosum, V. ashei, V. uliginosum, and the European blueberry also referred to as bilberry,V. myrtillus. In addition, relevant references from earlier reviews were manually entered. A total of 70 articles related to blueberry and cell culture models of inflammation, oxidative stress, and related conditions were included.Inflammation is the innate immune system reaction to a stimulus generated by pathogens, damaged cells, carcinogens, toxic compounds, changes in concentrations of reactive oxygen species , and some foods or metabolites . General response mechanisms of inflammation have been extensively reviewed elsewhere . In brief, the NF-κB and mitogen-activated protein kinase [MAPK, subdivided into extracellular-signal-regulated kinase , c-Jun Nterminal kinase , and p38] inflammatory pathways are activated following an external stimulus and/or by proinflammatory cytokines . Their activation generates the production of proinflammatory cytokines, including TNF-α, IL-1β, and IL-6, which upon release mobilize immune cells . Abnormal activation of inflammation-associated proteins, including NADPH oxidase , inducible NO synthase , and cyclooxygenase -2 , and failure to resolve the infection or injury can lead to chronic inflammation linked to diseases and cardiometabolic dysfunction.

Coinfection by two genetically different isolates together in the same plant has been documented before , and there are reports of artificial mixed infection of a vector and of a single vector being able to transmit all four subspecies of X. fastidiosa . Moreover, it was shown that isolates from two different subspecies can cause disease in a single host . Hence, the possibility that two different X. fastidiosa strains may encounter one another and exchange DNA, as shown by MLST analyses, exists in nature. Donor DNA may be derived from dead cells or may be secreted by a type IV secretion system, as shown in N. gonorrhoeae . Moreover, the experiment with heat-killed donor cells suggests that recombination is possible if homologous DNA fragments are present in the environment. Although the majority of recombination events will not be beneficial to the recipient cell, some may have adaptive advantages and increased virulence, among other phenotypes under selective pressure. For example, the relatively recent emergence of citrus variegated chlorosis and coffee leaf scorch in South America is proposed to be due to intersubspecific recombination between a X. fastidiosa subsp. multiplex donor and an unidentified native recipient based on MLST .

In addition, strains that are classi- fied in the newly proposed subspecies, Xylella fastidiosa subsp. morus, that infects mulberry, nft channel have been suggested to be generated by recombination between an X. fastidiosa subsp. fastidiosa donor and an X. fastidiosa subsp. multiplex recipient . A similar mechanism may have resulted in strains that infect blueberry and blackberry . The recombination events observed in this study are based on horizontal acquisition of antibiotic resistance markers , which represent a small fraction of the genome of X. fastidiosa. Since the natural competence experiments were performed under conditions without any selective pressure, recombination events should be expected to have occurred at other regions of the genome as well but were not detected due to the experimental approach used here. Under the simplistic assumption that gene exchange occurs randomly throughout the genome and with similar frequencies at all loci, the recombination frequencies reported in this study for one locus could be as much as 2.5 103 higher, considering the size of the X. fastidiosa genome . In summary, X. fastidiosa is naturally competent with a high rate of recombination when cultured under the liquid flow conditions of the MC system, which mimics plant xylem vessels and the insect vector foregut. Natural competence in the MCs was maintained even when the medium was supplemented with grapevine xylem sap, suggesting that the natural habitat of X. fastidiosa supports natural competence.

Moreover, habitats and media that favored increased biofilm growth and increased twitching motility showed increased rates of recombination. This study advances the characterization of the phenomenon of natural competence in X. fastidiosa that needs to be further studied to understand the evolution and adaptation of this important plant pathogen.To identify data sets suitable to address our research questions, we performed a search in the ISI Web of Science and SCOPUS . To minimise potential publication bias and to maximise the number of relevant data sets we also searched for unpublished data by contacting potential data holders through researcher networks. Data sets had to meet the following requirements to be included in the analysis: pollination and/or pest control services in crops were measured in both crop fields adjacent to floral plantings and control fields without planting; the replication at the field level was ≥ six fields per study . We contacted data holders fulfilling these requirements and requested primary data on plant species richness of plantings, time since establishment, landscape context and crop yield in addition to measured pollination and pest control services. Overall, we analysed data from 35 studies. We here define a study as a dataset collected by the same group of researchers for a particular crop species and ecosystem service in a particular region during one or several sampling years.

We collected 18 pest control service and 17 pollination service studies, representing a total of 868 service-site-year combinations across 529 sites . In eight of these studies both crop pollination and pest control services were measured .As different studies used different methods and measures to quantify pollination services, pest control services and crop yield, we standardised data prior to statistical analysis using z-scores . The use of z-scores has clear advantages compared with other transformations or standardisation approaches because average z-scores follow a normal distribution, and the variability present in the raw data is not constrained as in other indices that are bound between 0 and 1 . Pollination services were measured as seed set , fruit set , pollen deposition rate and, in one study, flower visitation rate . If available, differences in pollination service measures of open pollinated flowers and flowers from which pollinators were excluded were analysed. Measures of pest control services were quantified as pest parasitism , pest predation , population growth or crop damage by pests or pest densities . Whenever possible, the pest control index based on population growth proposed by Gardiner et al. was calculated and analysed . Note that standardised values of pest density and crop damage were multiplied by
1 because lower values of these measures reflect an increased pest control service . Crop yield was only considered for the analysis if a direct measure of final crop yield was available. Too few studies assessed crop quality which was therefore not considered further. Yield was measured as crop mass or number of fruits produced per unit area. Due to a lack of studies measuring crop yield in fields with and without adjacent hedgerows, the analysis of crop yield focused on effects of flower strips. Crop yield measures were available from a total of 11 flower strip studies and 194 fields .Flower strips are here defined as strips or other areas of planted wild native and/or non-native flowering herbaceous plants. Hedgerows are defined as areas of linear shape planted with native and/or non-native at least partly flowering woody plants and typically also herbaceous flowering plants. For hedgerows, information about the exact time since establishment and number of plant species was not available for most studies. The analyses of these drivers therefore focus on flower strip effects on pollination and pest control services. Information on plant species richness was available in 12 out of 18 pest control studies and 10 out of 17 pollination studies. Whenever available, the species richness of flowering plants was used. Otherwise, for some flower strip studies, the number of sown, potentially flowering plant species was used. Time since establishment of flower strips, that is the time span between seeding or planting and data sampling, was available for all studies ranging from 3 to 122 months. The proportional cover of arable crops was available and analysed as a proxy for landscape simplification in 11 pest control and 12 pollination studies. Proportional cover of arable crops was calculated in circular sectors of 1 km radius around focal crops, or 750 m or 500 m radius .We used a mixed effect-modelling approach to address our research questions. In all models, hydroponic nft study was included as a random intercept to account for the hierarchical structure of the data with field measures nested within study. To assess whether flower strips and hedgerows enhanced pollination and pest control services in adjacent crops linear mixed-effect models with planting were separately fitted for flower strips and hedgerows for the response variables pollination service and pest control service. To test how the effects on service provisioning change with distance from plantings and with landscape simplification these explanatory variables and their interactions with the fixed effects described earlier were included in the models. Exploratory analyses showed that neither distance nor landscape simplification effects differed between flower strips and hedgerows; that is no significant interactive effects of planting type with any of the tested fixed effects.

We therefore pooled flower strip and hedgerow data in the final models, excluding planting type and its two or three-way interactions as fixed effects. In addition to linear relationships we tested for an exponential decline of measured response variables from the border of the field by fitting log10 in the linear mixed-effect models described earlier. In this case, field nested within study was included as a random effect. To test the intermediate landscape complexity hypothesis, we tested for linear as well as hump-shaped relationships between landscape context, and its interaction with local floral plantings by fitting landscape variables as a quadratic fixed predictor in the models described earlier . To present the ranges covered by the agricultural landscape gradients, we did not standardise measures of landscape simplification within studies . To examine how pollination and pest control service provisioning relates to flower strip plant diversity and time since establishment plant species richness and log10 were included as fixed effects in models with study as a random effect. Plant species richness and time since establishment of flower strips were not correlated . Only 10 studies measured services in several years since establishment , and we included only data from the last sampling year. To assess how the presence of plantings affected the agronomic yield of adjacent crops , we fitted a linear mixed-effect model with the same fixed and random structure as described for question 1, but with crop yield as the response variable. Statistical analyses for different models and response variables differed in sample sizes as not all studies measured crop yield in addition to pollination or pest control services . In all models we initially included planting area as a co-variate in an explorative analysis, but removed it in the final models, as it did not explain variation in any of the models and did not improve model fit . Effect sizes provided in the text and figures are model estimates of z-transformed response variables. For statistical inference of fixed effects we used log-likelihood ratio tests recommended for testing significant effects of a priori selected parameters relevant to the hypotheses . For all models, assumptions were checked according to the graphical validation procedures recommended by Zuur et al. . All statistical analyses were performed in R version 3.5.2 using the R-package lme4 .The provisioning of pest control services in crop fields adjacent to flower strips was enhanced by 16% on average compared to fields without flower strips. On average, pest control services were also increased in crops adjacent to hedgerows, but effects were more variable and overall not statistically significant . Pest control services declined exponentially with distance from the field edge, but the slopes of the distance functions between fields with and without adjacent floral plantings did not differ . Crop pollination effects were more variable across studies and overall not significantly different between crops with or without adjacent floral planting across all studies and within- field distances . However, effects of distance to field edge differed for fields with floral plantings compared with control fields . Pollination services were increased near floral plantings and decreased exponentially with increasing distance from plantings, while no such effect of distance to field edge was detected for control fields . The fitted distance curves for fields with or without floral plantings intersected at 43 m .Crop pollination services, but not pest control services, tended to increase with flowering plant species richness of the adjacent flower strip . Crop pollination services also tended to increase with time since establishment of the adjacent flower strip, but showed a positive saturating relationship .Pollination services increased by 27% in 2 year old strips compared with the youngest plantings , while the additional predicted increase from 2 to 4 years or older strips was approximately 5% on average . Pest control services in crops adjacent to flower strips did not increase with flower strip age .Our quantitative synthesis demonstrates a generally positive effect of flower strips on pest control services but these effects did not consistently translate into higher yields. Although in most cases beneficial effects of plantings were also found for crop pollination services, effects on crop pollination and final crop yield were variable and overall not significant. The effect of wildflower strips on pollination services increased with age and species-richness suggesting that the quality of such plantings plays a pivotal role in effective service provision. Moreover, crop pollination declined with increasing distance to floral plantings .

Linking to these chemical databases provides a more in-depth source of information on the compounds and their physical and chemical properties. In summary, PMN is a broad resource for plant metabolism and continues to be under active development and expansion. The large number of predicted databases in PMN 15 allows us to evaluate the quality of the predictions quantitatively. To estimate the extent of incorrectly-predicted pathways in the PMN databases, and to measure the overall accuracy of the computational predictions, both alone and in conjunction with manual curation, we evaluated the prediction of 120 randomly selected pathways on both the released single-species databases in Pathway Tools and naïve prediction versions generated using only computational prediction . Biocurators evaluated the pathway assignments to the 126 organisms currently in PMN, round garden pot and classified them as “Expected” , “Broader” , “Narrower” , or as NonPMN Pathways .

In the naïve prediction databases, only 15% of selected pathways were predicted within the phylogenetic ranges expected from the literature, and 58% were NPPs. In the released PGDBs, however, 78% of evaluated pathways were predicted as expected . In addition to correcting the prediction for 94% of all NPPs of the surveyed pathways, incorporating curated information also reduced the percent of pathways predicted beyond their expected phylogenetic ranges from 13% to 4%. Thus, the application of phylogenetic information and manual curation drastically improves the quality of pathway prediction throughout PMN databases over the use of computational prediction alone.To determine whether different groups of plants can be differentiated solely by their metabolic capacity, we performed multiple correspondence analysis , a type of dimension reduction analysis that is similar to principal component analysis but can be used for categorical data . MCA was carried out using presence-absence matrices for pathways, reactions, and compounds . Reactions were considered present only if at least one enzyme in the species was annotated as catalyzing the reaction. Independently, the plants were categorized according to phylogenetic groups.

Dimensions 1 and 3 of the pathway and compound MCA, and dimensions 1 and 2 of the reaction MCA, separated the species into several phylogenetic groups . Phylogenetic groups that clearly cluster together and away from other groups include algae, non-flowering plants, Brassicaceae, and Poaceae . Dimension 1 separates the chlorophytes from land plants and dimension 3 separates certain angiosperm families such as the Brassicaceae and Poaceae well. No clear separation was observed among other eudicot groups. In addition, dimension 2 of the pathway and compound MCA mostly separated a small number of highly curated species from all the rest . Overall, the MCA clustering shows that some groups of plants can be readily differentiated based on their metabolic information in PMN, while other groups cannot, suggesting that further curation of species in these groups may be beneficial. We next asked which metabolic pathways drive the separation of the taxonomic groups on each dimension . Seventy percent of the variance in dimension 1 was described by 109 pathways, all of which were predicted to be either embryophyte-specific pathways or present in a larger proportion of embryophytes than chlorophytes. This mirrors the separation of the Chlorophyta cluster in dimension 1 of the MCA plot .

Similarly, 70% of the variance along dimension 3 was captured by 150 pathways, of which 81 were associated more strongly with Poaceae and 69 were associated more strongly with Brassicaceae . The pathways that contributed 95% of the variance in dimension 1, which separates chlorophytes from embryophytes, were enriched for hormone metabolism . Hormone metabolism may have helped support the increased complexity of land plants compared to their algal ancestors . In contrast, pathways responsible for clustering along dimension 3 were enriched for specialized metabolism , which is more lineage-specific than other domains of metabolism and can help distinguish between clades of angiosperms . Thus, it appears that metabolic data in PMN can effectively differentiate groups of species not only by the presence or absence of specific pathways and reactions, but also by the types of metabolic processes which are related to their evolutionary divergence.One of the major advantages of PMN 15 is the ability to quantitatively and qualitatively analyze omics data in the context of global metabolism for the 126 species represented in the resource. Here we demonstrate two applications of integrating omics data with PMN 15 to gain novel insights about plant metabolism. Pathway Tools’ Omics Dashboard allows users to visualize omics data across experimental time points and conditions across a broad range of cellular subsystems and at multiple scales of resolution . To demonstrate the utility of the Omics Dashboard within a metabolic context, we used a transcriptomic survey of two sorghum cultivars, RTx430 and BTx642, subjected to drought stress . RTx430 is tolerant to pre-flowering drought, whereas BTx642 is tolerant to post-flowering drought. To see if there was any difference in metabolic gene expression between the two cultivars in response to post-flowering drought, we examined differentially expressed genes in droughted plants compared to well-watered plants from the last week of watering to the first two weeks of post-flowering drought . We observed a consistent down-regulation of biosynthetic activity from root tissues in the post-flowering drought sensitive cultivar RTx430 compared to relatively stable expression in the post-flowering drought tolerant cultivar BTx642 . This observation is consistent with the authors’ findings that BTx642 demonstrated higher levels of redox balancing and likely experienced lower levels of reactive oxygen species stress, compared to RTx430, as a result of drought. By analyzing expression patterns of all metabolic genes, we observed a widespread metabolic down regulation in RTx430 root tissue, which was not reported previously . Drought-responsive DEGs were enriched in metabolic genes among both leaf and root tissues. However, contrary to the clear cultivar-specific trends shown in the root DEGs , there was no clear trend in expression patterns of metabolic genes in the leaves of either cultivar as a result of drought . To determine whether the consistent reduction of metabolic gene expression observed in RTx430 roots in response to drought was a global trend in the transcriptome or specific to metabolic genes, we compared relative expression levels of all non-metabolic root DEGs to all metabolic root DEGs in both cultivars during the same 3-week period. While the average relative expression decreased each week among both metabolic and non-metabolic genes in RTx430, the down regulation was greater among metabolic genes at both time points . In contrast, BTx642 roots showed no difference in expression among both metabolic and non-metabolic genes in response to drought , suggesting a global metabolic homeostasis in sorghum drought tolerance. By comparing the patterns of expression among DEGs in root and leaf tissues, rather than solely the number of DEGs, analysis via the Omics Dashboards revealed that roots exhibited stronger genotype-specific responses to drought than leaves, which was not observed previously . In addition to offering a visual overview of metabolism via the Omics Dashboard, PMN’s analytical toolkit allows researchers to easily conduct enrichment analyses among a set of genes or compounds of interest.

From within a SmartTable, users can view the pathways associated with a set of genes or compounds, large round plant pots and can then ask whether those genes or compounds are enriched for specific pathways. Broader metabolic classifications can also be added to the list of enriched pathways to better understand which area of metabolism are most enriched. For example, among the set of drought-responsive DEGs in RTx430 roots, we observed an enrichment in various domains of carbohydrate and amino acid biosynthesis and degradation, in addition to chitin degradation, consistent with the authors’ observation of drought-induced responsiveness of biotic defense genes . Thus, by combining PMN’s analytical capabilities with its broad set of metabolic data, users can find additional means of supporting existing hypotheses, uncovering novel insights, and finding new avenues for exploration in their own research. PMN 15 data can also be integrated with other cutting-edge datasets to investigate novel biological questions. As an example, we integrated A. thaliana root single-cell RNA-seq datasets from five independent studies to examine celltype specificity of metabolic domains and pathways . We define cell type-specific metabolic domains as those whose constituent genes show significantly higher expression levels in certain cell types compared to their average expression level in total cells. Different metabolic domains showed overlapping as well as distinct cell type specificity . First, epidermal and cortex cells were most metabolically active throughout the various domains of metabolism . This is consistent with previous observations that the major groups of metabolites detected in Arabidopsis roots, including glucosinolates, phenylpropanoids, and dipeptides, were highly abundant in the cortex . In contrast, maturing xylem showed relatively low metabolic activity as the major roles of these cells are structural support and water/soluble transport . Viewed from the level of metabolic domains, this analysis demonstrates a diverse range of metabolic activity across unique cell types in Arabidopsis roots. We next probed cell-type specificity of individual pathways. Among the 198 pathways associated with at least 10 genes, 40 pathways showed specificity in at least one cell type compared to their background gene expression levels represented by the average expression level of the pathway across all cell types . For example, in actively dividing cells, such as meristematic xylem cells, pathways involved in pyrimidine, histidine, arginine, and lysine biosynthesis showed high activity . These pathways are involved in essential metabolism, which are critical for maintaining cell division and growth. On the other hand, hormone biosynthesis pathways, such as cytokinin glucoside and gibberellin,showed high activity in the cortex. This is consistent with current understanding that the cortex is one of the predominant cell types that synthesizes these two hormones in the Arabidopsis root . By elucidating cell type-level activity of metabolic pathways, we can begin to map metabolism at cellular and tissue levels, which will be instrumental in understanding how metabolism affects plant development and responses to the environment as well as enabling effective engineering strategies. Similar to cell-type specificity, the concept of pathway divergence at the individual cell level can also be explored using single-cell transcriptomics data. To probe this question, we asked whether isozymes catalyzing the same reaction are more likely to be expressed in different cells compared to enzymes catalyzing different reactions in the same pathway. Isozymes are defined as enzymes encoded by different genes catalyzing the same reaction, which are usually the result of gene duplication events. We computed Spearman’s correlation coefficient to measure gene expression pattern similarity between a pair of enzymes across Arabidopsis root cells. The coefficients computed based on single cell data were generally lower than that generated by bulk RNA-seq, which may be due to the sparseness of single cell transcriptomic profiles or high heterogeneity of gene expression across cells. Nonetheless, metabolic genes in the same pathway showed higher correlation than randomly sampled metabolic genes , which suggests functional coordination between genes involved in the same pathway at the cellular level. Isozymes were much less correlated than enzyme pairs catalyzing different reactions in the same pathway. This indicates that isozymes may have evolved divergent expression patterns in root cells . Since isozymes are often the results of gene duplication events, this diversified expression between isozymes may contribute to retaining duplicated genes through sub-functionalization or neofunctionalization and fine-tuning metabolic pathways at the cellular level .PMN 15 is an extensive and regularly-updated database of compounds, pathways, reactions, and enzymes for 126 plant and green algae species and subspecies as well as a pan-species reference database called PlantCyc. We examined the quality of the data contained in the databases by assessing the accuracy of pathway prediction via manual validation of a randomly-selected subset of predicted pathways. Using two publicly available transcriptomics datasets, we demonstrated how PMN resources can be leveraged to characterize and gain insights from omics data. The present work demonstrates that the Plant Metabolic Network can be a useful tool for various analyses of plant metabolism across species.PMN 15 differs from other metabolic pathway databases in several ways: the quantity of curated and computational information, its comprehensive set of tools, and its specific focus on plants. Other, comparable databases include KEGG , Plant Reactome , and WikiPathways . Like PMN, these databases contain metabolic pathways along with their associated reactions, compounds, and enzymes.

The accumulation in Parlier was greatest for the remainder of the season and was closely followed by Wilmington. Salem accumulation was the least of the three regions presented in the US. In Salem, accumulation followed a similar pattern in 2012 compared to 2013, but the total number of degree-day degree-days was less in 2012 compared to 2013 . In Italy during 2013, the accumulation was greatest in Riva del Garda, followed by Pergine, and then Sant’Orsola . In Pergine, accumulation followed a broadly similar pattern in 2012 compared to 2013. Greater early-season degree-day accumulation in 2012 allowed a highe rseason-long total in 2012 compared to 2013 .In this study, we demonstrated how temperature-dependent fecundity and survival data could be integrated into a matrix population model to describe relative D. suzukii population increase and age structure according to environmental conditions in four environmentally-distinct fruit production regions. We found that the environment had major effects on how populations of D. suzukii behaved over a season in the different regions and that the population trends had implications for management. We also found that the different environments affected population stage-structure, black plastic planting pots and that stage structure also related to management of this pest.

To see if independent measures would support population predictions, we used trap and fruit infestation data as well as degree-day estimates for comparison. In general, we found some corroboration of population trends with trap data, and to a limited extent with fruit infestation data. We found that degree day accumulations did not reflect population predictions, and had limited capabilities to predict phenology or voltinism of this pest. The trap counts in our data are from either treated or untreated crops or crops that are unsuitable for D. suzukii population buildup. We realize that data from the traps placed in our study in some cases may, aside from other shortcomings, not provide an accurate early reflection of D. suzukii population levels. The environment had important implications for when populations of D. suzukii were a threat for crops. When comparing predicted population trends from Wilmington, Parlier and Salem, it is apparent that in cooler regions such as Salem, early-ripening fruits would escape D. suzukii attack because early season temperatures are unsuitable for early population increase. In warmer regions such as Parlier and Wilmington, management of D. suzukii should begin as soon as susceptible fruits start to ripen, as favorability of early-season temperatures mean that populations of D. suzukii are high at the beginning of the season. In interiorareas of California and lower elevations of Italy, there is a midseason decrease in pest pressure as temperatures become very hot and less suitable to D. suzukii. This was true to a lesser extent in North Carolina and Riva del Garda in 2013, where mid-season populations declined only slightly.

An implication of these predicted population trends is that management of D. suzukii during these periods could be less important relative to earlier and later periods when populations peak. Clear differences in stage-specific population structure were found between Wilmington, Parlier and Salem. Temperatures appeared to be better suited for all life stage activities and survival in Wilmington throughout the calendar year, followed by Parlier and then Salem. Stability of population structure was highest in Wilmington, followed by Parlier and then Salem. The period characterized by the highest stability in population structure generally coincides with the period when fruit is harvested in some regions. This suggests that that there can be consistent pressure on the crop during harvest, which is a period when allowable pest management activity may be restricted. Stage-specific population structure was generally characterized by a small percentage of adults compared to immature stages in the D. suzukii population. This may explain why traps are such a poor indicator of fruit infestation. For pest management, the only life stage targeted currently is the adult stage. Unfortunately, the implications of the predicted age structure are that only a small percentage of the population is affected. This could help explain why frequent spray intervals are required to minimize crop damage from D. suzukii. Unless immature stages can be specifically targeted in future management, it will likely remain challenging to manage this pest with scheduled spray intervals in a way that breaks the life cycle of the insect. While we were able to corroborate population projections with independent trap and fruit infestation data, we do not consider these data to be reliable or validating of early D. suzukii pest pressure.

The level of precision for fruit infestation data from sampling is unknown. Previous literature indicates that action thresholds for fruit infestation demand fruit samples in far greater quantities of the numbers of fruit collected in the current study. In order to get a 5% error rate for a sample containing 0.5% infested fruit, at least 600 fruits need to be collected and searched externally and internally through dissection. Given these limitations and the limited number of fruit that were collected in this study, fruit infestation could have happened earlier than observed. Erratic trap catches in Wilmington may have reflected yeast activity in monitoring traps used there. In the cases where we had trap and fruit infestation data, the first trap counts were observed during approximately the same period as when the first infested fruit was found. These findings illustrate the fact that traps cannot be seen as an early warning tool. Our predictions of stage structure in populations of D. suzukii illustrate the challenge of discerning distinct generations or predicting important life events in any useful way using a traditional degree-day model. Degree-day accumulations also did not directly reflect pest pressure as predicted by the population model, nor did the degree-day trajectories capture the subtlety in population fluctuations. When comparing estimations of population levels between years at Salem, there were clear differences in risk. Temperatures were more suitable for population buildup in Salem during the early portion of the season in 2013 compared to 2012. In Salem during May 2013, D. suzukii population projections were ten-fold higher compared to 2012, indicating the greater potential of crop losses for early-ripening crops. Assessing degree-day accumulations alone, differences between 2012 and 2013 were small and provided limited insight into the far higher early season risk in 2013 compared to 2012. For the annual comparison in Pergine, temperatures were within the optimal range for longer periods during 2013 compared to 2012, and D. suzukii population pressure was projected to be higher. In Pergine, the differences in population are not clearly reflected by degreeday estimations, because lower degree-day accumulation was measured in 2013 compared to 2012. For all production regions, D. suzukii population estimation has application for use as a virtual laboratory where ‘what-if’ statements can be raised and answered prior to management action, plant plastic pots by simulating population changes as typically achieved during pesticide intervention, Wolbachia infection, or biological control. Age-structured population models can be used to simulate mortality on specific life stages to predict how different management strategies affect D. suzukii pressure. These strategies can then be validated by field implementation. Population estimation in this study was not aimed at simulating the behavior of individuals or populations of D. suzukii as found in other more complex models for insects of medical importance [20,24–26,48]. Winter survival, availability of suitable host medium, nutrient sources, humidity and suitable host plant environments were not taken into consideration in this study. These factors can have strong effects population densities. It is clear that behavior of D. suzukii is important. The migration of flies to track favorable environmental conditions and host suitability was also not taken into consideration when making these estimates. The mechanisms of D. suzukii thermal extreme tolerance are not well documented and need further investigation in order to determine potential adaptation or behavioral mitigation to temperature extremes. Existing literature on Drosophila indicates that mechanisms of thermal tolerance may be influenced by the gene expression of heat shock proteins.

These mechanisms have not been studied in D. suzukii but data from future studies on the influence of these factors would benefit population models such as presented here. Other refinements of our model could potentially account for met apopulation dynamics, host availability, and overwintering survival, and density dependence. Like all models, ours necessarily makes assumptions and presents a simplified representation of complex ecosystems, ignoring some factors that may influence D. suzukii population levels. However, temperature is clearly one of the most important factors for D. suzukii population growth. This model has clear application for predicting relative pressure from D. suzukii in crops, and can be used as a temperature-related and physiology based comparative risk tool for pending larval infestation. Further application of the population projections would be to extend them into the future based on weather forecasts. Validation of this model will require controlled experiments on D. suzukii to test hypotheses about survival and fecundity based on model output in response to environmental conditions. For example, caged populations of a known size could be subjected to temperature simulations over intervals of time to assess population trajectories and age structures for comparison with model predictions. Additional validation studies could also include passive or live traps to capture flies over the season to be reared in field cages for assessment of survival and reproductions. We believe that the model described here is useful to approximate population levels, to more clearly define the age structure of populations, and to provide additional information that may aid in decision-making for D. suzukii. Given the many complexities in predicting populations, we argue that absolute precision is not necessary to identify effective management interventions or to improve understanding of this pest. We recognize the limitations of our projection model but believe that it represents a novel technique and a potentially powerful tool for management and research on D. suzukii and other damaging insects.Plant disease has always been a significant concern in agriculture since it results in reduction of crop quality and production . Image-based auto-diagnosing method is very accessible and economical for farmers. It is especially friendly to those farmers who are in remote areas or on a small scale. In recent years, deep learning methods are widely used in image-based recognition . Many networks have achieved excellent performance when trained with relevant large-scale datasets. As we know, the performance of deep learning network relies on data. As the network gets deeper, the number of trainable parameters becomes larger and the demand for data increases. Insufficient data can easily lead to overfitting . In plant disease recognition, the existing data resources are limited. Meanwhile, creating a large-scale plant disease dataset is difficult due to: the number of species and diseases are very huge; disease identification and annotation requires expert involvement; some diseases are too rare to collect sufficient samples. The long-tailed distribution of data is common in nature and it is difficult to be used to train a balanced model. In brief, creating large-scale dataset of plant disease is a time consuming and exhausting work . Generally, there are three ways to alleviate the problems caused by data shortages. Data augmentation, as the most common solution, augments instances by image scaling, rotation, affine transformation, etc. Transfer learning method delivers prior knowledge from source domain to target domain and adapts to the target domain by a small amount of data. But the two solutions cannot generalize to new categories in test, which means that the classes in test must have been learned in training. In addition to these two solutions, meta-learning, an approach that mimics human learning mechanisms, has been proposed in recent years. The objective of this solution is not to learn knowledge, but to learn to learn. Different from the conventional classification methods, few-shot learning is a kind of meta-learning method which can quickly generalize to unseen categories with the supports of few samples. One branch of FSL is metric-based method . The principle is that the features of samples belonging to the same category are close to each other, while the features of samples belonging to different categories are far from each other. The earliest representative work is Siamese Network, which is trained with positive or negative sample pairs . Vinyals et al. proposed the Matching Networks, and they borrowed the concept “seq2seq+attention” to train an end-to-end nearest neighbor classifier.

Additionally, relationships between traits and evolutionary history also result in mutual correlation among traits; thus, we also constructed a Spearman rank correlation matrix of traits . In constructing nested linear models and the correlation matrix, lecty was converted from a categorical variable into a quantitative variable corresponding to diet niche breadth to aid in model fitting.Across two years of sampling, we found that study plots in fragments harbored bee assemblages with reduced plot-level functional diversity and distinct functional composition compared to those in reserves. Changes in functional diversity and composition were closely related to declines and shifts in taxonomic diversity and composition. While we found strong evidence for non-random patterns of species loss, such patterns of loss was insufficient to cause landscape-level taxonomic or functional homogenization in the fragments. Null model analyses and correlational analyses also demonstrate that the loss of bee functional diversity can be explained by loss of bee taxonomic diversity. Taken together, these findings suggest that ecological filtering contributes to the restructuring of bee assemblages, large plastic gardening pots but is not the main driving force of bee diversity loss in habitat fragments in our system.

The strongest support for the importance of ecological filtering in our system is the detection of multiple indicator species and functional groups that appear particularly susceptible to fragmentation, typical of “winner-loser” dynamics found in modified landscapes . Also typical of “winner-loser” dynamics, we found a number of species that are present at all study plots, most of which are eusocial species in the tribe Halictini, which are known to be tolerant of habitat fragmentation . However, unlike systems where small numbers of “winner” taxa or functional groups dominate modified landscapes , indicator analyses revealed no such “winner” species or functional groups associated with fragments. Our finding only indicator taxa associated with reserves suggests that ecological filtering indeed leads to the exclusion of certain “loser” taxa and functional groups from fragments, but not to such an extent that the bee assemblages become numerically dominated by groups of disturbance-tolerant species that thrive in altered habitats. In fact, the loss of “loser” taxa seems to largely underlie the detected directional shifts in both taxonomic and functional measures of assemblage composition; simply removing the 12 indicator species from the analyses nullifies the significant differences detected between reserves and fragments with respect to both taxonomic and functional composition .

Evaluating differences between bee faunas in reserves and fragments one trait at a time revealed several differences between reserves and fragments, but only two that remained statistically significant after correction for multiple comparisons . Preferential loss of specialists in modified environments has been documented in many taxa , including bees . The increased relative abundance of late-season active bees observed in the present study has also been reported in at least one other system in which bees in modified landscapes have enhanced access to anthropogenic sources of floral resources during periods of relative resource dearth . In our system, it is likewise plausible that late-season bees in fragments are able to thrive by foraging on floral resources in the irrigated urban matrix surrounding fragments. The increase in average range size of bees inhabiting fragments also reveals the role of ecological filtering in structuring bee assemblages our system. Range size is not a functional trait per se, but it does serve as a proxy for an important ecological function that remains difficult to quantify: overall niche breadth . While many studies on bees focus on lecty as the main metric for niche breadth , selectivity of nesting substrates , phenological flexibility , and physiological tolerance to abiotic conditions may all influence how bee species respond to the addition of novel ecological filters. Our results suggest that bees in fragments tend to be those that are capable of surviving in a greater number of ecological contexts compared to bees in reserves, consistent with the view ecological filters present in habitat fragments exclude species that are more narrowly adapted to the unique local ecosystems.

Such replacement of endemics by geographically widespread species has been observed in other systems impacted by habitat alterations , and may be an important force driving reductions in ecological complexity across large spatial scales. Given that bee assemblages in fragments exhibited strong reductions in both taxonomic and functional alpha diversity as well as distinct taxonomic and functional composition compared to reserves, it is noteworthy that reserves and fragments did not differ with respect to either taxonomic or functional beta diversity. Reduced beta diversity is associated with biotic homogenization, which is a hallmark of ecological filtering resulting from anthropogenic disturbance . Biotic homogenization resulting from land use change has been found across many taxa , including pollinators . However, unlike other systems in which anthropogenic impact is dominant and pervasive, such as in cases where intensive agriculture generated highly simplified landscapes , the habitat fragments we selected in our study were comparable to our natural reserve sites with respect to both the diversity and the composition of native, insect-pollinated plant assemblages, at least at the scale of our one-hectare study plots . Thus, given that our fragment plots retained relatively intact plant assemblages, it is perhaps unsurprising that bee assemblages therein had not converged to a subset of taxa that thrive in altered habitats . As with the findings of , robust beta diversity among fragments may result from underlying heterogeneity in the habitat characteristics of our fragment plots. Taxonomic and functional diversity are often positively related to each other , but the two measures of diversity are related to each other in complex ways and may be independently impacted by habitat modifications . These complex relationships may explain our null model analysis, wherein the reduction in functional diversity in fragments did not differ from expectation under stochastic species loss despite our detecting multiple “loser” functional groups that suffer declines in fragments. While the parallel declines in taxonomic and functional diversity we detected in fragments via both null model and correlation analysis may indeed indicate stochastic loss of species , such a pattern could also arise from non-random loss of species whose functional traits have dispersions comparable to those lost due to random removal of species in the null model. Our finding that the “loser” species and functional groups associated with reserves varied with respect to every functional trait measured lends support to the latter mechanism. Alternatively, the apparent non-uniformity in the functional traits of “loser” taxa may result from our not measuring some other functional traits that may be shared among these taxa. For example, if dispersal is the main driver of bee assemblage composition in fragments, a functional trait that strongly influences the likelihood of dispersal across the urban matrix may be largely responsible for interspecific variation in likelihood of local extirpation from fragments. Irrespective of the mechanism underlying the parallel declines in taxonomic and functional diversity, our null model and correlational analysis results suggest that in our system, managing habitats in such a way as to preserve taxonomic diversity may be an effective way to preserve functional diversity . We uncovered significant phylogenetic conservatism in the functional traits we measured , large plastic growing pots which likely contributed to the numerous correlations detected among traits , a pattern also reported in other studies involving bee functional traits .

Given that phylogenetic conservatism in functional traits can shape the ecology and distribution of bee species in a landscape , our findings must be interpreted in the context of fragmentation impacting bees at the level of higher taxa. However, since analyses at the level of genera yielded qualitatively similar results , the overall patterns we report are unlikely to be driven by a few species-rich groups that respond especially strongly to fragmentation. The detection of indicator species belonging to three families and indicator functional group members belonging to five families also suggests that impacts of fragmentation are not limited to certain clades of bees. Phylogenetic relationships among bee taxa are a subject of ongoing research, even at the level of higher taxa . Once accepted phylogenies become available for bee taxa occurring in our system, it would be instructive to quantify the extent to which evolutionary relationships among taxa contribute to our findings, and the implications fragmentation may have on the evolutionary trajectory of bee faunas as time progresses.The maintenance of both taxonomic and functional beta diversity in our studied fragments argues for the preservation of each individual fragments of CSS habitat, despite the fact that fragments as a whole share the absence of sensitive “loser” bee taxa and functional groups. Our results suggest that each fragment preserves its own distinctive subset of the bee faunas formerly present in the regional species pool, and thus by extension, their ecological interactions with other taxa such as plants, parasitic or commensal invertebrates , and microbes . High levels of heterogeneity in assemblage composition among fragmented habitat remnants have also been documented in other systems ; in such systems, the cumulative species pool of compositionally divergent fragments may equal or exceed the species pools of unfragmented habitat. Beta diversity as a result of habitat heterogeneity is a strong driver of local and regional diversity of pollinators and organisms in general . In our system, bee faunas occupying habitat fragments embedded in a heterogeneous landscape do not exceed or equal those in larger natural reserves with respect to taxonomic or functional diversity, but nevertheless represent valuable units of conservation that may each exhibit unique community-level evolutionary trajectories with time if properly preserved. In fact, of the 216 species collected in the study , 40 were unique to fragments , while 74 were unique to reserves . That said, the decrease in plot-level functional diversity in habitat fragments still represents a conservation challenge with respect to both the functionality and the resilience of bee faunas , highlighting the importance of preserving large, intact areas of scrub habitat.We demonstrated that ecological filtering in fragmented scrub habitats caused shifts in the taxonomic and functional composition of bee faunas as a result of a loss of sensitive bee taxa and an increase in the relative abundance of geographically widespread bee species. However, filtering was not sufficiently strong to reduce functional diversity beyond that expected under random species loss, and bee faunas in fragments retained taxonomic and functional beta diversity among plots. Future studies that can quantitatively partition the relative contribution of deterministic and stochastic processes in driving taxonomic and functional diversity loss will shed light on the factors influencing community reassembly in structurally intact but isolated fragments of well preserved natural habitat.Animal-mediated pollination of angiosperms represents a vital ecosystem function in terrestrial ecosystems . Thus, reported declines in pollinator abundance and diversity worldwide could harm the integrity of terrestrial ecosystems. For this reason, documenting how environmental change impacts the structure and function of plant-pollinator interactions has been identified as an important research priority . In the last two decades, the bipartite network approach has become widely favored for examining interactions between communities of flower visiting animals and plants. To construct plant-pollinator interaction networks, researchers document the frequency with which each pollinator species visits each plant species within a predefined area. The resulting topology of interaction patterns provides information regarding the manner in which species are connected to one another, and the number of interactions documented between two species is often used as a surrogate for the strength of the relationship between the two putative mutualists with respect to pollination services or food provision . While studies on the structure of plant-pollinator interaction networks provide no direct information on the fitness of organisms involved, general patterns in network structure across plant and pollinator communities have shed light on the function of these networks. For example, nestedness and asymmetry , two properties common to most networks studied, result from the presence of groups of numerically abundant, ubiquitous generalist species that interact with large numbers of partner taxa. Having such generalized species at the “core” of networks may cause the ecological function of these networks to be robust to the loss of species and habitat . However, if network structure indeed predicts the resiliency of ecological relationships between plants and pollinators, then perturbations to network structure resulting from anthropogenic impacts may have strong consequences on ecological function Given the link between network structure and ecological function, a number of studies have investigated how plant-pollinator interaction networks are impacted by different sources of anthropogenic impact such as habitat fragmentation , land use intensification , grazing , and biological invasions .