Tag: 30 plant pot

The final component of the agreement was a set of three non-binding accompanying measures

The portion of land affected varied by type of production. Financial support for the rest of the land would come as before, via a system of guaranteed prices. In other words, direct income payments were only partially decoupled from production. The third component of the agreement was a mandatory land set-aside program, to remove land from production with the objectives of reducing output and improving the health of the land. Reducing output would also in the long run reduce CAP expenditures, as costs for storage and dumping would decrease. While long-term savings was an oft-repeated refrain of the reforms, details of exactly when these savings would come and how much they would be were murky at best. Contrary to the stipulations of the initial proposal, in the final agreement, land that was required to be set aside was eligible for compensatory payments for price cuts.These measures sought to improve the environmental health of the land via a series of programs, including agri-environmental initiatives, afforestation, and early retirement. These measures were significantly watered down from the initial proposal circulated by Agricultural Commissioner Ray MacSharry. A fifth major proposal, modulation, which would redirect money from the biggest CAP beneficiaries to the smallest farmers, was defeated and thus did not make it into the final agreement. Table 3.1 below presents the initial and final form of each key measure included in the agreement. Not only were price cuts much smaller than initially proposed, but compensation was extended further. Specifically set-aside land,blueberry plant container which was not supposed to be eligible for a compensation payment, was included in that scheme.

Beyond having smaller than proposed pricecuts and a broader extension of compensation, beef and dairy producers benefited from an additional, hidden form compensation in that price cuts to cereals lowered their input costs related to animal feed. In addition, efforts to redirect additional compensation to small farmers and to reduce the payments of the largest CAP beneficiaries via modulation were completely thwarted. As a Financial Times editorial noted, “the more muscular reform that MacSharry had originally envisioned was sapped by the fierce outcry of the EC’s farm lobbies, echoed and targeted by their agricultural ministers” . The MacSharry Reform fits a broader pattern observable across CAP reforms. Changes to CAP policies and programs rarely if ever take money away from farmers; instead, they change how farmers are paid. In the case of the MacSharry Reform, price cuts did not ultimately take money away from farmers. While EU farmers had previously been supported by the CAP through a system of high prices, that support was transitioning to a direct income support system. In the end, farmers were still being paid the same money; it was merely coming from a new pot. This pattern holds up across other CAP reforms. In CAP reform, there is never direct retrenchment, only recalibration. In other words, spending is not cut, but the operation of the program, including how funds are delivered, is reformed. Of the twin goals of lowering spending and reducing production levels and overall output, most progress was made toward achieving the latter. Mandatory set asides removed land from production, a direct initiative to counteract out of control commodity production. The introduction of partial decoupling through a system of price cuts and compensatory payments also worked to reduce at least the incentives for production. It replaced a system that previously encouraged and rewarded farmers for extracting as much as they could from the land. While the reforms included major strides toward reducing production, the MacSharry Reform failed to decrease overall spending.

Although the reform was undertaken with a major objective of reducing CAP expenditure, and proposals were written with this goal in mind, the end result was a reform that actually increased CAP costs in the short run and, due to the lagged implementation of price cuts, would not actually deliver cheaper prices to consumers until the mid-to-late 1990s . On top of the lack of savings related to smaller price cuts and the broader than anticipated extension of compensation, the accompanying measures targeted for early retirement, rural development, and other agri-environmental concerns added an additional 6 billion ECU to CAP spending. The failure to include modulation in the final agreement, which would have limited the maximum payment earnable by the largest farmers, and thus reduced total payment output levels, added another 6 billion ECU in CAP spending. Savings could be expected only in the long term as production levels fell and the EU would no longer have to finance the purchase, storage, and dumping of vast stocks of excess goods.The CAP reform agreed to in March of 1999 was one part of the EU-wide Agenda 2000 initiative. The scheme, formally called “Agenda 2000: For a Stronger and Wider Europe” was intended to prepare the EU for the new millennium, including the adoption of a common currency, the Euro, enlargement towards Eastern and Central Europe, and challenges related to globalization and the continued spread and development of new technologies. The Commission intended for Agenda 2000 to consider “how to develop the European mode of society in the 21st century and how to best respond to the major concerns of citizens” including unemployment, social exclusion, and the environment . In specific reference to agriculture, the report acknowledged that the 1992 CAP reform had been successful but suggested that “the time has come to deepen the reform and to take further movement towards world market prices coupled to direct income aids” . More broadly, the Commission’s guiding document for the Agenda 2000 reforms suggested that the EU had to modernize and reorganize its structures while also concentrating on the essentials and those areas where Europe could provide real added value.

Despite the ambitious agenda, the end result was a CAP reform whose major proposals were either defeated outright, or, at best, made optional for member states to adopt. A key factor explaining the failure to adopt meaningful reform is that there were no major crises that exerted pressure on the CAP. The next round of the WTO had yet to commence. Enlargement was still several years down the road, and the formal terms of CAP accession had not yet been determined. CAP spending was running high, as was normal, but there was no major spending threat, especially since the MacSharry reforms, combined with global price and production yields, seemed to be achieving their intended goal of reducing production. Ultimately,30 plant pot there was no powerful crisis that could credibly be used to justify truly dramatic change or to force an agreement. Unlike his predecessor Ray MacSharry, Agricultural Commissioner Franz Fischler was leading this reform during politics as usual conditions. Fischler thus had little mandate for reform. The purpose of this chapter is to account for the content of the 1999 Agenda 2000 CAP reform and to explain why the reform proposals were largely gutted. The Agenda 2000 CAP agreement contained no landmark reform. Instead previous reforms were preserved and the Commission’s major initiatives in the areas of greening and balancing payments were either made optional or entirely defeated. First, decoupling was preserved and further extended through a series of market reforms to the three most important areas of production: arable goods, beef, and dairy. The cuts were overall somewhat smaller and slower and with greater compensation than reformers had hoped. Beef prices, for example would be cut by 20% as opposed to the 30% proposed and price cuts for milk would be delayed by 6 years, beginning in 2006 instead of 2000 as the Commission hoped. More importantly, these cuts were expected as part of the agreement reached in 1992 to move to decouple the CAP; they do not constitute a new change to CAP policy. Second, the new environmental measure, called cross-compliance, that sought to link direct payments to good environmental practices was made optional instead of mandatory with the member states given virtually complete discretion over if and how to implement the program. If a member state actually chose to participate, it would also be allowed to use its own environmental standards. Modulation, a program to account for payment imbalances across member states by redistributing CAP funds, was likewise made entirely voluntary. Finally, a cap on farmer income payments over 100k ECU was entirely rejected. To the extent that any change was made, CAP reform mirrored the process of welfare state retrenchment, with reformers employing a variety of tactics to slip through any reform possible and hopefully position themselves to achieve more substantial retrenchment in the future. While the environmental programs introduced under Agenda 2000 were voluntary, their inclusion in the CAP agreement positioned policymakers to make more significant reforms in that direction in the future. In this way, the path of these environmental reforms is quite similar to how systemic reforms occur in the process of welfare state retrenchment.

As is typical, the final package included a number of side payments, concessions, and exemptions in order to facilitate the agreement. For example, the measures to cut prices and further decouple payment from production included smaller cuts than initially proposed, with implementation delayed by a number of years and substantial income supports provided to farmers.Agenda 2000 illustrates the importance of disruptive politics for achieving meaningful CAP reform. It demonstrates what reform efforts look like when there are no crises to drive forward major change: major proposals are substantially watered down, made optional, or entirely defeated. The far-reaching reforms that bookended Agenda 2000 were driven by disruptive politics: failing trade negotiations and a CAP system that would be unsustainable in a newly enlarged Europe. In these cases, disruptive politics allowed for fundamental change to CAP programs. The situation surrounding the Agenda 2000 reform was vastly different, with Fischler attempting to lead negotiations during politics as usual. While at first glance it might seem that enlargement, a powerful source of disruptive politics might be at play in the Agenda 2000 reform, a closer look at the circumstances reveals that no such pressure was brought by enlargement. In 2004, ten new member states were scheduled to join the EU. All the new member states, Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia, and Slovenia, were from Central and Eastern Europe, and were comparatively poorer and less developed than the existing member states. In addition, these countries had agricultural sectors that were much larger and less efficient than the current member states. For this reason, it was projected that it would be difficult and expensive to transition the new Central and Eastern European countries into the CAP. One, albeit narrow, area where enlargement did exert some pressure on reformers was in the domain of price supports. Studies conducted suggested that, without price cuts, the costs of integrating the new member states to the CAP would be “unacceptably high” . Specifically, a 1997 DGVI study estimated that the accession of the ten new Central and East European countries to the CAP would cost between 10-12 billion ECU, with roughly half of that, or 5-6 billion ECU needed to cover direct payments . The study suggested that, if the CAP remained unreformed, these costs could even increase further, as the new member states would exacerbate existing stock build up problems. In addition, if existing EU prices were not brought closer to the lower levels in the new member states, analysts warned that these prices might trigger a new surplus problem, which the MacSharry Reform had worked sohard to combat, and could also result in higher domestic food prices, which would place further financial strain on a population that was already comparatively poorer . Enlargement was ultimately not a significant pressure for reform, however, because member states and the Commission were operating under the assumption that farmers in the new member states would not be eligible for the direct income payments introduced under the MacSharry Reform. Their exclusion was based on the grounds that farmers in these countries had not faced the price cuts for which the direct payment scheme compensated and were actually likely to see prices for their goods increase .

Further confounding the issue is the existence of large spatial variability among cornand cotton-growing states

Additionally, diversion of corn to ethanol production essentially reduces food supply, which may lead farmers worldwide to convert natural land to new cropland in order to compensate for the diverted grain . This indirect LUC would generate the same net effects as that of direct LUC as discussed above, although its estimation is much more complicated for the difficulty and uncertainty involved in quantifying the impacts of US bio-fuel policies on global land and agricultural commodity markets . Studies continue to explore the effect of indirect LUC of bio-fuels with refined modeling methodologies , improved understanding of agricultural and food systems around the world , and extended assessment to non-GHG impacts . Yet, there is another consequence of corn ethanol expansion to which relatively less attention has been paid. In conjunction with rising corn prices, substantial land cover shift from cotton to corn has been observed—particularly between 2005 and 2009—through both direct expansion of corn into cotton and indirect expansion of corn into soybean, then of soybean into cotton . This observation is supported by farm-level data, which reveal that as growing corn became more profitable, some farmers reacted by reducing cotton land for growing corn . Furthermore, the National Agricultural Statistics Service Cropland Data Layer provides high-resolution maps derived from satellite imagery clearly demonstrating that land shifts from cotton to corn occurred in several states . Overall, between 2006 and 2009 when corn prices increased substantially relative to cotton prices , cotton area harvested reduced by 40 % , while corn area in the cotton growing states expanded by 1.3 million ha . Despite the potential large-scale land shift from cotton to corn,black plastic nursery pots there have been few studies on associated environmental impacts. Here, we address this knowledge gap.

We note that corn displacing cotton was only part of the complex land use dynamics in the past “ethanol decade” that involved also land shift from, for example, soybeans and hay to corn, cotton to soybeans, and natural vegetations to corn . The reason we focus only on cotton to corn here is that environmental impacts of land shift between cotton to corn, both high-input crops, are less clear than that between relatively low-input crops and high-input crops . In a recent study, Wallander et al. stated that “When acreage shifts from one high-input crop to another , however, ethanol induced changes may be negligible or could even reduce environmental externalities.” In this study, we seek to test the validity of this statement, focusing on regional environmental issues along with a growing body of literature on the non-GHG consequences of bio-fuels expansion . A land shift from one crop to the other can alter both direct, or on-site, and indirect, or offsite, environmental effects. For example, increased use of nitrogen fertilizers as a result of the land shift not only can elevate N related emissions such as NOx and N runoff but also requires more energy and material inputs in the process of fertilizer production. The system boundary of the study, therefore, was drawn to cover both direct and indirect emissions. In particular, we paid a special attention to direct environmental emissions from crop production given their significance relative to indirect emissions . We calculated indirect emissions embodied in input materials that take place along supply chains, using the Ecoinvent database . In our data compilation, we placed an emphasis on the crop growth and agricultural input structures at the state level, as previous studies showed that national, average data may fall short in capturing the environmental impacts of crop production at a regional level . This is because agricultural systems display high degrees of variability across regions in terms of input structure due primarily to differences in geography, weather patterns, soil type, and management practices .

Also, data on major agricultural inputs such as fertilizers and pesticides collected by the US Department of Agriculture are only available at the state level . The reference year of this study is 2005 given that cotton area experienced a substantial decline between 2005 and 2009. Major inputs in crop growth include fertilizers, pesticides, energies, and irrigation water. We obtained relevant state-level data from several USDA surveys and censuses reflecting cotton and corn farming practices around 2005 and then compiled a set of state-specific inventories. Not all inputs data, however, are available for every state that grows cotton and corn. The USDA Farm and Ranch Irrigation survey, for example, includes more states than surveys of energy and agrichemical use. Nevertheless, the states for which all inputs data are available capture the majority of US cotton and corn production. Specifically, the inventories we compiled cover 19 corn growing states, which account for 95 % of domestic corn production in 2005, and 9 cotton growing states, which account for 88 % of domestic cotton production in 2005. Due to use of agricultural inputs like fertilizers and pesticides, crop production contributes to an array of environmental impacts from acidification, eutrophication, water scarcity to human and ecological toxicity . To best capture these impacts associated with US cotton and corn growth, we estimated all potential onsite environmental emissions based on various databases, models, and literature . The emissions data compiled cover >100 different substances, the majority of which are pesticides and volatile organic compound emissions. Numerical information on all emission factors used in this study can be found in the Table S1–S6 . After compiling emissions data for cotton and corn, we evaluated their environmental impacts using characterization factors from life cycle impact assessment . Reflecting the relative significance of an emission or resource, characterization factors are used to aggregate emission results, usually including a large number of different substances, into a dozen of impact category scores that enable better comparison between alternatives . In this study, we focused on regional environmental aspects of cotton and corn, and based on our previous study , we selected eight impact categories to which cotton and corn production potentially contribute.

These impact categories are acidification, eutrophication, smog formation, freshwater ecotoxicity, and water use as well as human health cancer, non-cancer, and respiratory effects. Characterization factors for all categories except water use are taken from the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts developed for the USA by the EPA . Characterization factors for water use were based on the ReCiPe model . Note that TRACI 2.0, compared with its original version , has incorporated the recently developed USEtox model for the ecotoxicty, human health cancer, and non-cancer impact categories .For comparison between the two crops, results are organized on the basis of per hectare produced. Figure 2.1 shows the average environmental impacts, weighted by state area harvested, of corn relative to that of cotton in 2005 in the USA. For most impact categories, corn and cotton per hectare show roughly similar environmental impacts, with relative magnitude ranging from 1.4 for acidification and 0.9 for human health cancer. For freshwater ecotoxicity, however, corn shows about one third of impact by cotton per hectare, and corn’s water use is less than half that of cotton. Above all,greenhouse pot most of the environmental impacts associated with cotton and corn production are due to on-site environmental emissions rather than that embodied in input materials like fertilizers and pesticides. Their acidification effect is due in large part to application of nitrogen fertilizers and diesel combustion . Although N intensity of corn is much larger than that of cotton , corn farming uses much less diesel . Overall, the acidification impact of corn per hectare is 1.4 times that of cotton. The same can be said about smog formation. Not surprisingly, the two crops’ eutrophication impact is caused mainly by use of N and phosphate fertilizers. Although corn has higher nutrient application intensities than cotton, its average N and P leaching and runoff rates are lower ; thus, the two crops have a comparable eutrophication impact. Water use by cotton and corn comes primarily from irrigation: about 400 m3 is applied per hectare corn produced as opposed to 940 m3 applied per hectare cotton produced. Freshwater ecotoxicity for both crops is due in large part to pesticide use, and cotton per hectare has a freshwater ecotoxicity about three times that of corn. This is partly because pesticide application intensity of cotton is approximately twice as much as that of corn . Also, many of the pesticides such as cyfluthrin, lamb dacyhalothrin, and cypermethrin used in cotton growth generally show higher toxicity-related characterization factors than the major ones used in corn growth. The two crops’ potential human health respiratory impacts are comparable, although that of cotton is slightly higher. The respiratory effect is mainly caused by diesel combustion, application of N fertilizers, and emissions embodied in P fertilizers. Human health cancer and non-cancer impacts of corn per hectare are slightly larger than that of cotton.

Heavy metals contained in phosphate constitute the major contributor to both crops’ non-cancer effect, but use of acephate, an insecticide, is also another important source of non-cancer impact for cotton. This is why corn’s relative magnitude of non-cancer effect is not as large as that of phosphate application intensity . The two crops’ potential human health cancer impact is due to a number of factors including diesel combustion and heavy metals brought about by phosphate as well as the cancer impact embodied in fertilizers. The results above indicate that corn and cotton grown per hectare in the USA on average generate roughly comparable impacts for most of the impact categories except for water use and freshwater ecotoxicity, where cotton shows lower impacts. The results seem consistent with the view of a recent USDA study , “When acreage shifts from one high-input crop to another , however, ethanolinduced changes may be negligible or could even reduce environmental externalities.” We argue that, however, the average results as shown in Fig. 2.1 are inadequate to capture the net environmental impacts associated with land cover change from cotton to corn that took place in the USA. First, Fig. 2.1 is largely a portrait of corn and cotton growth in different regions and, weighted by state crop area, mainly represents the major crop-growing states where respective crops are likely the most suitable to grow. But, when land shifts from cotton to corn growth, it happens in cotton-growing areas in the South. Lands in these areas can be by and large considered marginal lands for corn in both geographic and economic senses as they are generally less suitable for corn growth than the Corn Belt.The range of spatial variation in cotton growth is two to threefold for acidification, smog formation, eutrophication, human health non-cancer, and respiratory effects and four to sixfold for freshwater ecotoxicity and human health cancer effect. The range of spatial variation in corn growth is about two to threefold for acidification, smog formation, human health cancer, non-cancer, and respiratory effects and fourfold for eutrophication. Water use can vary by orders of magnitude for both crops as some states use little irrigation water while some rely heavily on irrigation . In short, the results for average corn and cotton as reflected in Fig. 2.1 fall short of representing the environmental performance of marginal corn in cotton-growing states and, therefore, should not be used for evaluating environmental impacts of land use change from cotton to corn or vice versa. Comparing Fig. 2.2 with Fig. 2.1 reveals that corn and cotton growths in 2005 at the state level can be quite different from the average situation. Land shift from cotton to corn in Georgia and Texas would likely aggravate all of the impact categories except freshwater ecotoxicity. For North Carolina, however, the land shift would increase water withdraw and aggravate eutrophication impact, but would not cause substantial changes to human health effects. For TX, land shift from cotton to corn would especially aggravate acidification and smog formation impacts. This is because TX, as the major producer of cotton in the US, applies far less nutrients per hectare cotton produced than per hectare corn produced there .

Urban and peri-urban agriculture is growing as urbanized areas expand

Urban agriculture occurs within and near the built environment, with high proportions of surrounding impervious surfaces such as buildings and roads . Urbanization fragments habitats and reduces the abundance and diversity of organisms . Many of the affected organisms are beneficial to urban agriculture and the provision of ecosystem services such as pollination and biological control services . Biological control of pest insects is an important ecosystem service for urban farmers due to pesticide use regulation in cities and rejection of chemical management practices for health and environmental reasons. In the absence of chemical controls, agroecological pest management practices are frequently adopted. Agroecological pest management is a proactive ecosystem services based approach that aims to reduce pest abundance and crop damage by increasing natural enemy populations through agroecosystem diversification . However, landscape fragmentation and surrounding imperviousness can often negatively affect the regulatory ecosystem services APM relies upon . While most off-farm landscape effects are not within the control of urban farmers, on-farm diversification practices are. Substantial research and published literature have investigated the impact of diversification practices to increase biological control of pest insects on rural farms, but less attention has been focused on the effects of diversification in the fragmented landscapes innate to urban agroecosystems . This chapter focuses on the effects of floral provisioning on parasitic Hymenoptera and the ubiquitous cabbage aphid , specifically,30 plant pot the impact of floral provisioning on PH populations vis-a-vis the enemies hypothesis and the nectar provision hypothesis .

The nectar provision hypothesis was proposed to explore the effects of floral-based diversification schemes on the contributions made by PH to biological control services. Heimpel and Jervis posit that with increased accessibility to nectar-producing plants, PH should respond with increased fitness, resulting in elevated levels of localized biological control . Many PH species have been documented feeding on a wide variety of flowers . Nectar, pollen, and extrafloral nectar are essential sources of carbohydrates, proteins, lipids, and minerals for PH . Nectar provisioning has been shown to play an important role in increasing parasitoid longevity, fecundity , abundance, and diversity , as well as increase rates of parasitism . Despite documented positive outcomes for parasitoid fitness and increased rates of biological control, floral provisioning does not always result in improved biological control services from PH . In response to confounding results regarding floral manipulations, researchers have proposed several concepts to explain these inconsistencies: 1. PH may utilize floral resources but then disperse to reduce the risk of hyper- or super-parasitism, other mortality, and inbreeding among offspring ; 2. parasitoids may already have enough local floral resources, and floral manipulations may not be introducing a limited resource ; 3. pest insects utilize floral resources more effectively than parasitoids ; 4. diversification strategies might make it difficult for parasitoids to find hosts in increasingly heterogeneous landscapes ; and lastly, 5. many factors determine the ability of PH to use floral resources, including wasp body size, mouthpart morphology, floral structure, and nutritional value . A disconnect between plant species and parasitoid feeding characteristics may limit the opportunity of PH to utilize these floral resources . The extent to which these conditions affect PH in urban areas is still being explored.

Generally speaking, the inclusion of flowers into urban agroecosystems to supply nectar for PH should yield effective results in the context of APM. However, inconsistent results regarding the nectar provisioning hypothesis and effects on biological control services have complicated the implementation of floral provisioning practices for farmers. Of all potential remedies for inconsistency regarding effects of floral provisioning, the concept of functional biodiversity has been championed for its potential to influence habitat manipulations that are targeted toward specific ecosystem services or to particular natural enemies. Understanding the linkages between potential PH feeding preferences and specific agroecosystem components could help farmers “fine-tune” their production systems to maximize biological control services. Morphology, bloom time, floral area, and the amount of pollen and nectar resources provided by a given plant species have all been shown to either positively or negatively impact natural enemy populations . Gaining a better understanding of the range of flowers most likely to be utilized by and positively affect PH populations and biological control services may enable practitioners to tailor management practices . To better understand the effects of floral provisioning on PH richness and abundance and potential feeding preferences, we conducted an in-situ flower survey using an improvised D-vac insect vacuum fitted with a lined and filtered five-gallon bucket that wholly covered flowering plant inflorescences. Each sampled plant was visually assessed for spatial relationships regarding other herbaceous cover and was only sampled if it was standing free of additional herbaceous cover and flowering plants. In addition, each plant was visually assessed for pest infestations and was not sampled if pest infestations were visible. We vacuumed three plants of each flowering plant species present at a farm location. Multiple samples were collected during a farm visits, but varied due to available specimens.

Sampling occurred once every thirty days during the same time intervals during each visit. Results from the 2018 survey informed flowering plant selection for the 2019 sampling season. Each plant species that yielded very few or no PH during the 2018 sampling period was excluded from sampling in the following year; 13 flowering plant species were sampled . Each sample was stored in a deep freeze until processed by extracting all PH and identifying them to sub-family as per previous literature . Parasitic Hymenoptera identification was accomplished using Goulet et al., for all groups and Gibson et al. for Chalcidoidea and Dangerfield et al., for Braconidae. Collected specimens that were damaged were identified to morphosubfamily.Aphid abundance, parasitism, and plant damage observations were performed over two growing seasons on commonly grown brassica cultivars: kale, broccoli, collards, and tree collards. Individual plants were randomly selected and identified to cultivar. If possible, we only observed plants that had not been heavily harvested. The major insect pests of interest were cabbage aphids , a common agricultural pest of Brassicaceae. Aphid abundance was measured on each plant by selecting three leaves and recording the number of apterous, alate, and parasitized aphids . The percent of mummified aphids per leaf was used as a measure of biological control services by parasitoid wasps. A qualitative assessment of pest damage on brassicas was completed using a high, medium, and low scale based on familiar concepts of marketability. High damage corresponded to a leaf that would be unmarketable, medium damage had some damage but would still be purchased by a consumer, and low damage had little to no visible damage. Two agroecological practices that increase on-farm diversification, floral provisioning,30 planter pot and crop richness were measured three times: early-season , mid-season , and late-season . Crop richness was measured by using 8m transects across cropping systems. Any crop plant that touched the transect line was considered, including different cultivars of the same species . Three transects were completed on small farms, six on medium farms, and nine on large farms. We collected data for crop richness three times during the growing season over the two years of the study. Floral richness was recorded seasonally, similar to crop richness. Every on-farm, non-crop flowering plant was recorded and identified to genus. Generalized linear mixed models were constructed for each of the following response variables: Total parasitic Hymenopteran abundance, super-family, family, and subfamily abundance, and total PH diversity. Selected fixed effect explanatory variables included: floral richness, floral species, year by season, and site as a random intercept. Using the fitdistrplus package in R, parasitic Hymenoptera count data were plotted and examined to determine the best probabilistic distribution for the GLMM modeling; a Poisson distribution with a log link function . Models that had response variables significantly affected by floral species were further analyzed using the non-parametric KruskalWallis test with posthoc Dunn’s test to determine floral species that had the most significant influence on the response variable . Aphid data were analyzed to test for differences in aphid abundance, parasitism rates, and crop damage.

Explanatory variables examined were year and season, floral richness?Aphid count data were assessed using the fitdistrplus package in R to determine the best probabilistic distribution for the GLMM modeling; a negative binomial distribution with a log link function . The final GLMM was constructed with glmer.nb using crop and floral richness, date and year as fixed effects and site as the random effect. We constructed mixed-effects models using the lme4 package in R . After fitting a series of GLMMs based on predictors expected to affect response variables, the model with the lowest Akaike Information Criterion score was selected. All GLMM model residuals were simulated from the fitted model using the simulate Residuals function in the package DHARMa to test for dispersion and model fit . Using the effects package in R, a partial regression plot was constructed for each predictor variable included in the final GLMMs . To better understand the nectar provision hypothesis and the effectiveness of floral-based habitat manipulations, we used PH abundance and richness on flowering plants to indicate parasitoid feeding preferences. Our results showed that floral species were not a strong indicator of increased abundance or richness at any measured scale of PH. Only one PH family, the pteromalids, was found in more significant quantities on nettles. Using a non-parametric test, PH diversity was shown to increase on marigolds and nettles, a response documented by previous floral provisioning research . Laboratory experiments have shown floral feeding preferences in parasitoids , but in-situ results have been less clear . Our results show that our collected PH had a very weak response to floral species, and in some cases showed a negative relationship to floral richness. Several factors may singularly, or in aggregate, explain this absence of floral preference in situ: 1. floral resources incorporated into urban gardens and farms are not selected for their functional diversity but that of other traits, such as attractiveness and availability ; 2. in-situ food resources may present a greater variety of acceptable foods unlike no-choice feeding trials; and 3. some sampling bias may have occurred when using the vacuum on inflorescences as the vacuum may be more likely to capture smaller parasitoids which may be able to exploit a broader range of nectaries or may be feeding on other food items such as honeydew . Many parasitoids also feed on the same plant as their host, which may bias visitation by family and sub-family. A negative PH abundance response to increased floral richness may be a result of dispersion to reduce the risk of hyper- or super-parasitism, other mortality, and inbreeding among offspring . Our research showed a weak relationship between increased PH richness on marigolds and nettles and an increased abundance response with pteromalids on nettles compared to other PH taxa. Marigolds have a history of being utilized as a beneficial flower in the gardening community and are grown for cultural and aesthetic reasons. Nettles are not typically grown intentionally, and in the few location’s nettles were sampled, they were unintentional but preserved in non-crop areas. Nettles, in this case, may be an example of a non-selected floral species with a higher level of ecosystem function than species selected for other traits. Additionally, aphid parasitoids, specifically Aphidius, have been found in higher abundance on nettles due to the occurrence of the stinging nettle aphid, Microlophiurn carnosum . It is unclear what connection pteromalids may have in this ecology. It is possible that nettles sampled had infestations of aphids that remained obscured due to the obstacles associated with close inspection of stinging nettles. Despite these findings, anecdotal relationships between floral species and specific PH species indicate these relationships should continue to be explored to better understand parasitoid feeding preferences, floral occupancy, and farm scape mediated biological control. To assess the second criterion of the nectar provision hypothesis, a demonstratable reduction in pest impacts, we looked at aphid abundance, rates of parasitism, and overall crop damage on brassicas. Our results show that farms with increased floral richness have lower aphid counts per plant. We did not record a reduction in crop damage nor an increase in aphid parasitism with increased floral richness.