Adoption of innovative e-learning support for teaching: A multiple case study at the University of Waikato

In response to recent social, economic, and pedagogical challenges to tertiary-level teaching and learning, universities are increasingly investigating and adopting elearning as a way to engage and motivate students. This paper reports on the first year of a two-year (2009-2010) qualitative multiple case study research project in New Zealand. Using perspectives from activity theory and the scholarship of teaching, the research has the overall goal of documenting, developing, and disseminating effective and innovative practice in which e-learning plays an important role in tertiary teaching. A “snapshot” of each of the four 2009 cases and focused findings within and across cases are provided. This is followed by an overall discussion of the context, “within” and “across” case themes, and implications of the research

Estimating sowing and harvest dates based on the Asian summer monsoon

Sowing and harvest dates are a significant source of uncertainty within crop models, especially for regions where high-resolution data are unavailable or, as is the case in future climate runs, where no data are available at all. Global datasets are not always able to distinguish when wheat is grown in tropical and subtropical regions, and they are also often coarse in resolution. South Asia is one such region where large spatial variation means higher-resolution datasets are needed, together with greater clarity for the timing of the main wheat growing season. Agriculture in South Asia is closely associated with the dominating climatological phenomenon, the Asian summer monsoon (ASM). Rice and wheat are two highly important crops for the region, with rice being mainly cultivated in the wet season during the summer monsoon months and wheat during the dry winter. We present a method for estimating the crop sowing and harvest dates for rice and wheat using the ASM onset and retreat. The aim of this method is to provide a more accurate alternative to the global datasets of cropping calendars than is currently available and generate more representative inputs for climate impact assessments. We first demonstrate that there is skill in the model prediction of monsoon onset and retreat for two downscaled general circulation models (GCMs) by comparing modelled precipitation with observations. We then calculate and apply sowing and harvest rules for rice and wheat for each simulation to climatological estimates of the monsoon onset and retreat for a present day period. We show that this method reproduces the present day sowing and harvest dates for most parts of India. The application of the method to two future simulations demonstrates that the estimated sowing and harvest dates are successfully modified to ensure that the growing season remains consistent with the internal model climate. The study therefore provides a useful way of modelling potential growing season adaptations to changes in future climate

Electron Transport through Disordered Domain Walls: Coherent and Incoherent Regimes

We study electron transport through a domain wall in a ferromagnetic nanowire subject to spin-dependent scattering. A scattering matrix formalism is developed to address both coherent and incoherent transport properties. The coherent case corresponds to elastic scattering by static defects, which is dominant at low temperatures, while the incoherent case provides a phenomenological description of the inelastic scattering present in real physical systems at room temperature. It is found that disorder scattering increases the amount of spin-mixing of transmitted electrons, reducing the adiabaticity. This leads, in the incoherent case, to a reduction of conductance through the domain wall as compared to a uniformly magnetized region which is similar to the giant magnetoresistance effect. In the coherent case, a reduction of weak localization, together with a suppression of spin-reversing scattering amplitudes, leads to an enhancement of conductance due to the domain wall in the regime of strong disorder. The total effect of a domain wall on the conductance of a nanowire is studied by incorporating the disordered regions on either side of the wall. It is found that spin-dependent scattering in these regions increases the domain wall magnetoconductance as compared to the effect found by considering only the scattering inside the wall. This increase is most dramatic in the narrow wall limit, but remains significant for wide walls.Comment: 23 pages, 12 figure

Using climate information to support crop breeding decisions and adaptation in agriculture

Population growth in the next few decades will increase the need for food production, while the yields of major food crops could be impacted by the changing climate and changing threats from pests and pathogens. Crop breeding, both through conventional techniques, and GM assisted breeding could help meet these challenges, if adequately supported by appropriate information on the future climate. We highlight some of the major challenges for crop breeders and growers in the coming decades, and describe the main characteristics of crop breeding techniques and other adaptation options for agriculture. We review recent uses of climate information to support crop breeding decisions and make recommendations for how this might be improved. We conclude that there is significant potential for breeders to work more closely with climate scientists and crop modellers in order to address the challenges of climate change. It is not yet clear how climate information can best be used. Fruitful areas of investigation include: provision of climate information to identify key target breeding traits and develop improved success criteria (e.g. for heat/drought stress); identification of those conditions under which multiple stress factors (for example, heat stress, mid-season drought stress, flowering drought stress, terminal drought stress) are important in breeding programmes; use of climate information to inform selection of trial sites; identification of the range of environments and locations under which crop trials should be performed (likely to be a wider range of environments than done at present); identification of appropriate duration of trials (likely to be longer than current trials, due to the importance of capturing extreme events); and definition of appropriate methods for incorporating climate information into crop breeding programmes, depending on the specific needs of the breeding programme and the strengths and weaknesses of available approaches. Better knowledge is needed on climate-related thresholds important to crop breeders, for example on the frequency and severity of extreme climate events relevant to the product profile, or to help provide tailored climate analyses (particularly for extreme events). The uncertainties inherent in climate and impact projections provide a particular challenge for translating climate science into actionable outcomes for agriculture. Further work is needed to explore relevant social and economic assumptions such as the level and distribution of real incomes, changing consumption patterns, health impacts, impacts on markets and trade, and the impact of legislation relating to conservation, the environment and climate change

Impacts of Climate Change on indirect human exposure to pathogens and chemicals from agriculture

Objective: Climate change is likely to affect the nature of pathogens and chemicals in the environment and their fate and transport. Future risks of pathogens and chemicals could therefore be very different from those of today. In this review, we assess the implications of climate change for changes in human exposures to pathogens and chemicals in agricultural systems in the United Kingdom and discuss the subsequent effects on health impacts. Data sources: In this review, we used expert input and considered literature on climate change ; health effects resulting from exposure to pathogens and chemicals arising from agriculture ; inputs of chemicals and pathogens to agricultural systems ; and human exposure pathways for pathogens and chemicals in agricultural systems. Data synthesis: We established the current evidence base for health effects of chemicals and pathogens in the agricultural environment ; determined the potential implications of climate change on chemical and pathogen inputs in agricultural systems ; and explored the effects of climate change on environmental transport and fate of different contaminant types. We combined these data to assess the implications of climate change in terms of indirect human exposure to pathogens and chemicals in agricultural systems. We then developed recommendations on future research and policy changes to manage any adverse increases in risks. Conclusions: Overall, climate change is likely to increase human exposures to agricultural contaminants. The magnitude of the increases will be highly dependent on the contaminant type. Risks from many pathogens and particulate and particle-associated contaminants could increase significantly. These increases in exposure can, however, be managed for the most part through targeted research and policy changes

What have we learnt from EUPORIAS climate service prototypes?

The international effort toward climate services, epitomised by the development of the Global Framework for Climate Services and, more recently the launch of Copernicus Climate Change Service has renewed interest in the users and the role they can play in shaping the services they will eventually use. Here we critically analyse the results of the five climate service prototypes that were developed as part of the EU funded project EUPORIAS. Starting from the experience acquired in each of the projects we attempt to distil a few key lessons which, we believe, will be relevant to the wider community of climate service developers

Decomposing uncertainties in the future terrestrial carbon budget associated with emission scenarios, climate projections, and ecosystem simulations using the ISI-MIP results

We examined the changes to global net primary production (NPP), vegetation biomass carbon (VegC), and soil organic carbon (SOC) estimated by six global vegetation models (GVMs) obtained from the Inter-Sectoral Impact Model Intercomparison Project. Simulation results were obtained using five global climate models (GCMs) forced with four representative concentration pathway (RCP) scenarios. To clarify which component (i.e., emission scenarios, climate projections, or global vegetation models) contributes the most to uncertainties in projected global terrestrial C cycling by 2100, analysis of variance (ANOVA) and wavelet clustering were applied to 70 projected simulation sets. At the end of the simulation period, changes from the year 2000 in all three variables varied considerably from net negative to positive values. ANOVA revealed that the main sources of uncertainty are different among variables and depend on the projection period. We determined that in the global VegC and SOC projections, GVMs are the main influence on uncertainties (60 % and 90 %, respectively) rather than climate-driving scenarios (RCPs and GCMs). Moreover, the divergence of changes in vegetation carbon residence times is dominated by GVM uncertainty, particularly in the latter half of the 21st century. In addition, we found that the contribution of each uncertainty source is spatiotemporally heterogeneous and it differs among the GVM variables. The dominant uncertainty source for changes in NPP and VegC varies along the climatic gradient. The contribution of GVM to the uncertainty decreases as the climate division becomes cooler (from ca. 80 % in the equatorial division to 40 % in the snow division). Our results suggest that to assess climate change impacts on global ecosystem C cycling among each RCP scenario, the long-term C dynamics within the ecosystems (i.e., vegetation turnover and soil decomposition) are more critical factors than photosynthetic processes. The different trends in the contribution of uncertainty sources in each variable among climate divisions indicate that improvement of GVMs based on climate division or biome type will be effective. On the other hand, in dry regions, GCMs are the dominant uncertainty source in climate impact assessments of vegetation and soil C dynamics

Study of a Class of Four Dimensional Nonsingular Cosmological Bounces

We study a novel class of nonsingular time-symmetric cosmological bounces. In this class of four dimensional models the bounce is induced by a perfect fluid with a negative energy density. Metric perturbations are solved in an analytic way all through the bounce. The conditions for generating a scale invariant spectrum of tensor and scalar metric perturbations are discussed.Comment: 16 pages, 10 figure