COMP6037 Seminar 23 10 13: Science, knowledge and technology

Set readings 1. Sismondo S. (2009). The Kuhnian revolution. In An introduction to science and technology studies. p12-22 2. Ben-David J, Sullivan T. (1975) Sociology of science. Annual Review of Sociology p203-21 3. Clarke A, Star SL. (2008) The social worlds framework: a theory/methods package. In Hackett EJ et al. The handbook of science and technology studies. Cambridge MA: MIT Press p113-137 Bonus paper (read if you have time) 4. Mitroff I. (1974). Norms and Counternorms in a Select Group of Apollo Moon Scientists. American Sociological Review 39:79-95 • Aim to ensure that you understand the core arguments of each paper • Look up/note any new terminology (and questions you want to ask) • Think about your critical appraisal of the paper (what are the merits/demerits of the argument, evidence etc) In the seminar we will spend about 5 minutes talking about each paper, and then - building on the two lectures - discuss how these ideas might be used to think about the Web and Web Science. At the end there will be some time for questions and a chance to note your key learning points.

Genotype x environment interaction in the uptake of Cs and Sr from soils by plants

The soil-plant transfer factors for Cs and Sr were analyzed in relationship to soil properties, crops, and varieties of crops. Two crops and two varieties of each crop: lettuce (Lactuca sativa L.), cv. Salad Bowl Green and cv. Lobjoits Green Cos, and radish (Raphanus sativus L.), cv. French Breakfast 3 and cv. Scarlet Globe, were grown on five different soils amended with Cs and Sr to give concentrations of 1 mg kg(-1) and 50 mg kg(-1) of each element. Soil-plant transfer coefficients ranged between 0.12-19.10 (Cs) and 1.48-146.10 (Sr) for lettuce and 0.09-13.24 (Cs) and 2.99-93.00 (Sr) for radish. Uptake of Cs and Sr by plants depended on both plant and soil properties. There were significant (P less than or equal to 0.05) differences between soil-plant transfer factors for each plant type at the two soil concentrations. At each soil concentration about 60% of the variance in the uptake of the Cs and Sr was due to soil properties. For a given concentration of Cs or Sr in soil, the most important factor effecting soil-plant transfer of these elements was the soil properties rather than the crops or varieties of crops. Therefore, for the varieties considered here, soil-plant transfer of Cs and Sr would be best regulated through the management of soil properties. At each concentration of Cs and Sr, the main soil properties effecting the uptake of Cs and Sr by lettuce and radish were the concentrations of K and Ca, pH and CEC. Together with the concentrations of contaminants in soils, they explained about 80% of total data variance, and were the best predictors for soil-plant transfer. The different varieties of lettuce and radish gave different responses in soil-plant transfer of Cs and Sr in different soil conditions, i.e. genotype x environment interaction caused about 30% of the variability in the uptake of Cs and Sr by plants. This means that a plant variety with a low soil-plant transfer of Cs and Sr in one soil could have an increased soil-plant transfer factor in other soils. The broad implications of this work are that in contaminated agricultural lands still used for plant growing, contaminant-excluding crop varieties may not be a reliable method for decreasing contaminant transfer to foodstuffs. Modification of soil properties would be a more reliable technique. This is particularly relevant to agricultural soils in the former USSR still affected by fallout from the Chernobyl disaster.

Effects of biosolids from tomato processing on soil fertility and wheat growth in a Greek alfisol

The effects of biosolids from tomato processing on soil properties and wheat growth were investigated in an Alfisol from central Greece. Biosolids were mixed with soil from the surface (Ap) or subsurface (Bt) horizon in plastic containers at rates of 1%, 5%, and 10% by dry weight (d.w.; equivalent to 10, 50, and 100 Mg ha–1). Biosolid treatments were compared to an NH4Cl application (50 mg N kg–1) and an untreated control in (1) a 102 d incubation experiment at 28°C to determine biosolid nitrification potential and (2) a 45 d outdoor experiment to evaluate effects on soil fertility and wheat growth. Mineralization of biosolids in the incubation experiment resulted in accumulation of nitrate-N and indicated that biosolids were able to supply N that was in excess of crop needs in treatments of 5% and 10%. After 45 d of wheat growth, available soil nutrients (N, P) and P uptake by wheat were distinctly lower in the Bt than in the Ap horizon. However, soil pH, electrical conductivity, organic matter, total N, nitrate-N, extractable P, and exchangeable K increased with increasing rate of biosolid application in both soils. These were followed by corresponding increases in wheat nutrient uptake and biomass production, thus demonstrating the importance of this organic material for sustaining production in soils of low immediate fertility. Compared to the NH4Cl treatment (50 kg N ha–1 equivalent), biosolid application rates of 5% and 10% had higher available soil nutrients, similar or higher nutrient uptake and higher wheat biomass. But only an application of 10% biosolids provided sufficient N levels for wheat in the surface soil, and even higher applications were required for providing sufficient N and P in the Bt horizon.

Apparent digestibility and nitrogen utilization of diets based on maize silage harvested at three stages of maturity and fed to steers

Advancing maize crop maturity is associated with changes in ear-to-stover ratio which may have consequences for the digestibility of the ensiled crop. The apparent digestibility and nitrogen retention of three diets (Early, Mid and Late) containing maize silages made from maize of advancing harvest date [dry matter (DM) contents of the maize silages were 273, 314 and 367 g kg(-1) for the silages in the Early, Mid and Late diets respectively], together with a protein supplement offered in sufficient quantities to make the diets isonitrogenous, were measured in six Holstein-Friesian steers in an incomplete Latin square design with four periods. Dry-matter intake of maize silage tended to be least for the Early diet and greatest for the Medium diet (P=0(.)182). Apparent digestibility of DM and organic matter did not differ between diets. Apparent digestibility of energy was lowest in the Late diet (P = 0(.)057) and the metabolizable energy concentrations of the three silages were calculated as 11(.)0, 11(.)1 and 10(.)6 MJ kg(-1) DM for the Early, Medium and Late diets respectively (P = 0(.)068). No differences were detected between diets in starch digestibility but the number of undamaged grains present in the faeces of animals fed the Late diet was significantly higher than with the Early and Mid diets (P = 0(.)006). The apparent digestibility of neutral-detergent fibre of the diets reduced significantly as silage DM content increased (P = 0(.)012) with a similar trend for the apparent digestibility of acid-detergent fibre (P = 0(.)078). Apparent digestibility of nitrogen (N) was similar for the Early and Mid diets, both being greater than the Late diet (P = 0(.)035). Nitrogen retention did not differ between diets. It was concluded that delaying harvest until the DM content is above 300 g kg(-1) can negatively affect the nutritive value of maize silage in the UK.

Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.