Aboveground plant community and species-specific vegetation cover from the Jena Experiment (Main Experiment, year 2008)

This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2008, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2009)

This data set contains aboveground community biomass in 2009 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2009 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in three rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for all biomass measures are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2010)

This data set contains aboveground community biomass in 2010 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2010 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in two rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for all biomass measures are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Aboveground plant community and species-specific vegetation cover from the Jena Experiment (Main Experiment, year 2002)

This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2002, vegetation cover was estimated only once in Septemper just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2002, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.

Aboveground plant community and species-specific vegetation cover from the Jena Experiment (Main Experiment, year 2003)

This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2003, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2003, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.

Aboveground plant community and species-specific vegetation cover from the Jena Experiment (Main Experiment, year 2005)

This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2005, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2005, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.

Aboveground plant community and species-specific vegetation cover from the Jena Experiment (Main Experiment, year 2006)

This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2006, vegetation cover was estimated twice in June and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2006, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.

Aboveground plant community and species-specific vegetation cover from the Jena Experiment (Main Experiment, year 2007)

This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2007, vegetation cover was estimated twice in June and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2007, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.

Aboveground plant community and species-specific vegetation cover from the Jena Experiment (Main Experiment, year 2004)

This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2004, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2004, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.

Financial media, globalisation, and China’s economic integration: comparing narrative construction of the Economist and Caijing

In June 2015, legal frameworks of the Asian Infrastructural Investment Bank were signed by its 57 founding members. Proposed and initiated by China, this multilateral development bank is considered to be an Asian counterpart to break the monopoly of the World Bank and the International Monetary Fund. In October 2015, China’s Central Bank announced a benchmark interest rate cut to combat the economic slowdown. The easing policy coincides with the European Central Bank’s announcement of doubts over US Fed’s commitment to raise interest rates. Global stock markets responded positively to China’s move, with the exception of the indexes from Wall Street (Bland, 2015; Elliott, 2015). In the meantime, China’s ‘One Belt, One Road’ (or New Silk Road Economic Belt) became atopic of discourse in relation to its growing global economy, as China pledged $40 billion to trade and infrastructure projects (Bermingham, 2015). The foreign policy aims to reinforce the economic belt from western China through Central Asia towards Europe, as well as to construct maritime trading routes from coastal China through the South China Sea (Summers, 2015). In 2012, The Economist launched a new China section, to reveal the complexity of the‘meteoric rise’ of China. John Micklethwait, who was then the chief editor of the magazine, said that China’s emergence as a global power justified giving it a section of its own(Roush, 2012). In July 2015, Hu Shuli, the former chief editor of Caijing, announced the launch of a think tank and financial data service division called Caixin Insight Group, which encompasses the new Caixin China Purchasing Managers Index (PMI). Incooperation with with Markit Group, a principal global provider of PMI, the index soon became a widely cited economic indicator. One anecdote from November’s Caixin shows how much has changed: in a high-profile dialogue between Hu Shuli and Kevin Rudd, Hu insisted on asking questions in English; interestingly, the former Prime Minister of Australia insisted on replying in Chinese. These recent developments point to one thing: the economic ascent of China and its increasing influence on the power play between economics and politics in world markets. China has begun to take a more active role in rule making and enforcement under neoliberal frameworks. However, due to the country’s size and the scale of its economy in comparison to other countries, China’s version of globalisation has unique characteristics. The ‘Capitalist-socialist’ paradox is vital to China’s market-oriented transformation. In order to comprehend how such unique features are articulated and understood, there are several questions worth investigating in the realms of media and communication studies,such as how China’s neoliberal restructuring is portrayed and perceived by different types of interested parties, and how these portrayals are de-contextualised and re-contextualised in global or Anglo-American narratives. Therefore, based on a combination of the themes of globalisation, financial media and China’s economic integration, this thesis attempts to explore how financial media construct the narratives of China’s economic globalisation through the deployment of comparative and multi-disciplinary approaches. Two outstanding elite financial magazines, Britain’s The Economist, which has a global readership and influence, and Caijing, China’s leading financial magazine, are chosen as case studies to exemplify differing media discourses, representing, respectively, Anglo-American and Chinese socio-economic and political backgrounds, as well as their own journalistic cultures. This thesis tries to answer the questions of how and why China’s neoliberal restructuring is constructed from a globally-oriented perspective. The construction primarily involves people who are influential in business and policymaking. Hence, the analysis falls into the paradigm of elite-elite communication, which is an important but relatively less developed perspective in studying China and its globalisation. The comparing of characteristics of narrative construction are the result of the textual analysis of articles published over a ten-year period (mid-1998 to mid-2008). The corpus of samples come from the two media outlets’ coverage of three selected events:China becoming a member of the World Trade Organization, its outward direct investment, and the listing of stocks of Chinese companies in overseas exchanges, which are mutually exclusive in sample collection and collectively exhaustive in the inclusion of articles regarding China’s economic globalisation. The findings help to understand that, despite language, socio-economic and political differences, elite financial media with globally-oriented readerships share similar methods of and approaches to agenda setting, the evaluation of news prominence, the selection of frame, and the advocacy of deeply rooted neoliberal ideas. The comparison of their distinctive features reflects the different phases of building up the sense of identity in their readers as global elites, as well as the different economic interests that are aligned with the corresponding readerships. However, textual analysis is only relevant in terms of exploring how the narratives are constructed and the elements they include; textual analysis alone prevents us from seeing the obstacles and the constrains of the journalistic practices of construction. Therefore, this thesis provides a brief discussion of interviews with practitioners from the two media, in order to understand how similar or different narratives are manifested and perceived, how the concept of neoliberalism deviates from and is justified in the Chinese context, and how and for what purpose deviations arise from Western to Chinese contexts. The thesis also contributes to defining financial media in the domain of elite communication. The relevant and closely interlocking concepts of globalisation, elitism and neoliberalism are discussed, and are used as a theoretical bedrock in the analysis of texts and contexts. It is important to address the agenda-setting and ideological role of elite financial media, because of its narrative formula of infusing business facts with opinions,which is important in constructing the global elite identity as well as influencing neoliberal policy-making. On the other hand, ‘journalistic professionalism’ has been redefined, in that the elite identity is shared by the content producer, reader and the actors in the news stories emerging from the much-compressed news cycle. The professionalism of elite financial media requires a dual definition, that of being professional in the understanding of business facts and statistics, and that of being professional in the making sense of stories by deploying economic logic.

Una planta sin clásicos. La berenjena en la farmacología medieval y renacentista

La berenjena (Solanum melongena L.) es una planta solanácea de múltiples variedades, cuyos ancestros salvajes se sitúan en Indochina y el este de África. Su cultivo fue muy temprano en zonas de China e India. Aun así, no se extendió al Occidente antiguo ni apenas se conoció, de ahí su ausencia en los textos clásicos de botánica y farmacología. Fueron los árabes quienes llevaron el cultivo de la planta por el Norte de África y Al-Andalus, de donde pasó ya a Europa. Los primeros testimonios occidentales de la berenjena aparecen en traducciones latinas de textos árabes, para incorporarse luego a la literatura farmacológica medieval y, más tarde ya, a la del Renacimiento, que empezó a tratar de ella por su posible parecido con una especie de mandrágora. Pese a que se le reconocían algunas virtudes medicinales, siempre se la tuvo bajo sospecha por ser de sabor poco agradable, indigesta y causante de algunas afecciones. Solo los botánicos de finales del Renacimiento describirían la planta y sus variedades con criterios más «científicos» y botánicos, ya sin apenas intereses farmacológicos.

Markers for seedling and adult plant crown rot resistance in four partially resistant bread wheat sources

QTL identified for seedling and adult plant crown rot resistance in four partially resistant hexaploid wheat sources. PCR-based markers identified for use in marker-assisted selection. Crown rot, caused by Fusarium pseudograminearum, is an important disease of wheat in many wheat-growing regions globally. Complete resistance to infection by F. pseudograminearum has not been observed in a wheat host, but germplasm with partial resistance to this pathogen has been identified. The partially resistant wheat hexaploid germplasm sources 2-49, Sunco, IRN497 and CPI133817 were investigated in both seedling and adult plant field trials to identify markers associated with the resistance which could be used in marker-assisted selection programs. Thirteen different quantitative trait loci (QTL) conditioning crown rot resistance were identified in the four different sources. Some QTL were only observed in seedling trials whereas others appeared to be adult plant specific. For example while the QTL on chromosomes 1AS, 1BS, and 4BS contributed by 2-49 and on 2BS contributed by Sunco were detected in both seedling and field trials, the QTL on 1DL present in 2-49 and the QTL on 3BL in IRN497 were only detected in seedling trials. Genetic correlations between field trials of the same population were strong, as were correlations between seedling trials of the same population. Low to moderate correlations were observed between seedling and field trials. Flanking markers, most of which are less than 10 cM apart, have now been identified for each of the regions associated with crown rot resistance.

Alternative media for public pedagogy: "Chief" concerns and human agency

To demonstrate how the growing influence of alternative media in civil society correlates with the rise of social movements and their influence on contemporary manifestations of resistance, this research uses critical ethnographic methodologies to document the narratives of alternative media producers in the pro-Indigenous and anti-“Chief” campaigns at the University of Illinois at Urbana-Champaign during the 2006-2007 school year. These narratives demonstrate not only the ways alternative media help transmit dissent by distributing information to diverse populations, but also the manner they facilitate contexts that influence identity formations and strengthen counter-cultural communal practices. Particular lineages of critical social theory are used to situate knowledge construction and social relationships within specific socio-historic contexts to approach issues of subjectivity, human agency, and resistance. These include the Frankfurt School for Social Research, the Birmingham Centre for Contemporary Cultural Studies, and the Brazilian education philosopher Paulo Freire, who emphasize criticality based on the engagement of ideological analysis, as well as developing capacities to critique and resist oppressive social and political relationships. Thus, this study argues for expanding traditional notions of literacy to include the ability to decode and produce media as a critical element of meaningful democratic participation.

Dynamics of a large submersed plant bed in upper Chesapeake Bay

A large SAV bed in upper Chesapeake Bay has experienced several abrupt shifts over the past half-century, beginning with near-complete loss after a record-breaking flood in 1972, followed by an unexpected, rapid resurgence in the early 2000’s, then partial decline in 2011 following another major flood event. Together, these trends and events provide a unique opportunity to study a recovering SAV ecosystem from several different perspectives. First, I analyzed and synthesized existing time series datasets to make inferences about what factors prompted the recovery. Next, I analyzed existing datasets, together with field samples and a simple hydrodynamic model to investigate mechanisms of SAV bed loss and resilience to storm events. Finally, I conducted field deployments and experiments to explore how the bed affects internal physical and biogeochemical processes and what implications those effects have for the dynamics of the system. I found that modest reductions in nutrient loading, coupled with several consecutive dry years likely facilitated the SAV resurgence. Furthermore, positive feedback processes may have played a role in the sudden nature of the recovery because they could have reinforced the state of the bed before and after the abrupt shift. I also found that scour and poor water clarity associated with sediment deposition during the 2011 flood event were mechanisms of plant loss. However, interactions between the bed, water flow, and waves served as mechanisms of resilience because these processes created favorable growing conditions (i.e., clear water, low flow velocities) in the inner core of the bed. Finally, I found that that interactions between physical and biogeochemical processes led to low nutrient concentrations inside the bed relative to outside the bed, which created conditions that precluded algal growth and reinforced vascular plant dominance. This work demonstrates that positive feedbacks play a central role in SAV resilience to both chronic eutrophication as well as acute storm events. Furthermore, I show that analysis of long-term ecological monitoring data, together with field measurements and experiments, can be an effective approach for understanding the mechanisms underlying ecosystem dynamics.

Optimising plant bed performance through adaptive research with the Australian sweetpotato industry

A key driver of Australian sweetpotato productivity improvements and consumer demand has been industry adoption of disease-free planting material systems. On a farm isolated from main Australian sweetpotato areas, virus-free germplasm is annually multiplied, with subsequent 'pathogen-tested' (PT) sweetpotato roots shipped to commercial Australian sweetpotato growers. They in turn plant their PT roots into specially designated plant beds, commencing in late winter. From these beds, they cut sprouts as the basis for their commercial fields. Along with other intense agronomic practices, this system enables Australian producers to achieve worldRSQUOs highest commercial yields (per hectare) of premium sweetpotatoes. Their industry organisation, ASPG (Australian Sweetpotato Growers Inc.), has identified productivity of mother plant beds as a key driver of crop performance. Growers and scientists are currently collaborating to investigate issues such as catastrophic plant beds losses; optimisation of irrigation and nutrient addition; rapidity and uniformity of initial plant bed harvests; optimal plant bed harvest techniques; virus re-infection of plant beds; and practical longevity of plant beds. A survey of 50 sweetpotato growers in Queensland and New South Wales identified a substantial diversity in current plant bed systems, apparently influenced by growing district, scale of operation, time of planting, and machinery/labour availability. Growers identified key areas for plant bed research as: optimising the size and grading specifications of PT roots supplied for the plant beds; change in sprout density, vigour and performance through sequential cuttings of the plant bed; optimal height above ground level to cut sprouts to maximise commercial crop and plant bed performance; and use of structures and soil amendments in plant bed systems. Our ongoing multi-disciplinary research program integrates detailed agronomic experiments, grower adaptive learning sites, product quality and consumer research, to enhance industry capacity for inspired innovation and commercial, sustainable practice change.