Bioclimatic envelope model of climate change impacts on blanket peatland distribution in Great Britain

Blanket peatlands are rain-fed mires that cover the landscape almost regardless of topography. The geographical extent of this type of peatland is highly sensitive to climate. We applied a global process-based bioclimatic envelope model, PeatStash, to predict the distribution of British blanket peatlands. The model captures the present areal extent (Kappa = 0.77) and is highly sensitive to both temperature and precipitation changes. When the model is run using the UKCIP02 climate projections for the time periods 2011–2040, 2041–2070 and 2071–2100, the geographical distribution of blanket peatlands gradually retreats towards the north and the west. In the UKCIP02 high emissions scenario for 2071–2100, the blanket peatland bioclimatic space is ~84% smaller than contemporary conditions (1961–1990); only parts of the west of Scotland remain inside this space. Increasing summer temperature is the main driver of the projected changes in areal extent. Simulations using 7 climate model outputs resulted in generally similar patterns of declining aereal extent of the bioclimatic space, although differing in degree. The results presented in this study should be viewed as a first step towards understanding the trends likely to affect the blanket peatland distribution in Great Britain. The eventual fate of existing blanket peatlands left outside their bioclimatic space remains uncertain.

Decision theory and real estate development: a note on uncertainty

Real estate development appraisal is a quantification of future expectations. The appraisal model relies upon the valuer/developer having an understanding of the future in terms of the future marketability of the completed development and the future cost of development. In some cases the developer has some degree of control over the possible variation in the variables, as with the cost of construction through the choice of specification. However, other variables, such as the sale price of the final product, are totally dependent upon the vagaries of the market at the completion date. To try to address the risk of a different outcome to the one expected (modelled) the developer will often carry out a sensitivity analysis on the development. However, traditional sensitivity analysis has generally only looked at the best and worst scenarios and has focused on the anticipated or expected outcomes. This does not take into account uncertainty and the range of outcomes that can happen. A fuller analysis should include examination of the uncertainties in each of the components of the appraisal and account for the appropriate distributions of the variables. Similarly, as many of the variables in the model are not independent, the variables need to be correlated. This requires a standardised approach and we suggest that the use of a generic forecasting software package, in this case Crystal Ball, allows the analyst to work with an existing development appraisal model set up in Excel (or other spreadsheet) and to work with a predetermined set of probability distributions. Without a full knowledge of risk, developers are unable to determine the anticipated level of return that should be sought to compensate for the risk. This model allows the user a better understanding of the possible outcomes for the development. Ultimately the final decision will be made relative to current expectations and current business constraints, but by assessing the upside and downside risks more appropriately, the decision maker should be better placed to make a more informed and “better”.

Attribution of climate change: a methodology to estimate the potential contribution to increases in potato yield in Scotland since 1960

Maincrop potato yields in Scotland have increased by 3035 similar to t similar to ha-1 since 1960 as a result of many changes, but has changing climate contributed anything to this? The purpose of this work was to answer this question. Daily weather data for the period 19602006 were analysed for five locations covering the zones of potato growing on the east coast of Scotland (between 55.213 and 57.646 similar to N) to determine trends in temperature, rainfall and solar radiation. A physiologically based potato yield model was validated using data obtained from a long-term field trial in eastern Scotland and then employed to simulate crop development and potential yield at each of the five sites. Over the 47 similar to years, there were significant increases in annual air and 30 similar to cm soil temperatures (0.27 and 0.30 similar to K similar to decade-1, respectively), but no significant changes in annual precipitation or in the timing of the last frost in spring and the first frost of autumn. There was no evidence of any north to south gradient of warming. Simulated emergence and canopy closure became earlier at all five sites over the period with the advance being greater in the north (3.7 and 3.6 similar to days similar to decade-1, respectively) than the south (0.5 and 0.8 similar to days similar to decade-1, respectively). Potential yield increased with time, generally reflecting the increased duration of the green canopy, at average rates of 2.8 similar to t similar to ha-1 decade-1 for chitted seed (sprouted prior to planting) and 2.5 similar to t similar to ha-1 decade-1 for unchitted seed. The measured warming could contribute potential yield increases of up to 13.2 similar to t similar to ha-1 for chitted potato (range 7.119.3 similar to t similar to ha-1) and 11.5 similar to t similar to ha-1 for unchitted potato (range 7.115.5 similar to t similar to ha-1) equivalent to 3439% of the increased potential yield over the period or 2326% of the increase in actual measured yields.

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target.

Demonstrating the importance of criteria and sub-criteria in building assessment methods

Building assessment methods have become a popular research field since the early 1990s. An international tool which allows the assessment of buildings in all regions, taking into account differences in climates, topographies and cultures does not yet exist. This paper aims to demonstrate the importance of criteria and sub-criteria in developing a new potential building assessment method for Saudi Arabia. Recently, the awareness of sustainability has been increasing in developing countries due to high energy consumption, pollution and high carbon foot print. There is no debate that assessment criteria have an important role to identify the tool’s orientation. However, various aspects influence the criteria and sub-criteria of assessment tools such as environment, economic, social and cultural to mention but a few. The author provides an investigation on the most popular and globally used schemes: BREEAM, LEED, Green Star, CASBEE and Estidama in order to identify the effectiveness of the different aspects of the assessment criteria and the impacts of these criteria on the assessment results; that will provide a solid foundation to develop an effective sustainable assessment method for buildings in Saudi Arabia. Initial results of the investigation suggest that each country needs to develop its own assessment method in order to achieve desired results, while focusing upon the indigenous environmental, economic, social and cultural conditions. Keywords: Assessment methods, BREEAM, LEED, Green Star, CASBEE, Estidama, sustainability, sustainable buildings, Environment, Saudi Arabia.

The simulation of the opposing fluxes of latent heat and CO2 over various land-use types: coupling a gas exchange model to a mesoscale atmospheric model

A mesoscale meteorological model (FOOT3DK) is coupled with a gas exchange model to simulate surface fluxes of CO2 and H2O under field conditions. The gas exchange model consists of a C3 single leaf photosynthesis sub-model and an extended big leaf (sun/shade) sub-model that divides the canopy into sunlit and shaded fractions. Simulated CO2 fluxes of the stand-alone version of the gas exchange model correspond well to eddy-covariance measurements at a test site in a rural area in the west of Germany. The coupled FOOT3DK/gas exchange model is validated for the diurnal cycle at singular grid points, and delivers realistic fluxes with respect to their order of magnitude and to the general daily course. Compared to the Jarvis-based big leaf scheme, simulations of latent heat fluxes with a photosynthesis-based scheme for stomatal conductance are more realistic. As expected, flux averages are strongly influenced by the underlying land cover. While the simulated net ecosystem exchange is highly correlated with leaf area index, this correlation is much weaker for the latent heat flux. Photosynthetic CO2 uptake is associated with transpirational water loss via the stomata, and the resulting opposing surface fluxes of CO2 and H2O are reproduced with the model approach. Over vegetated surfaces it is shown that the coupling of a photosynthesis-based gas exchange model with the land-surface scheme of a mesoscale model results in more realistic simulated latent heat fluxes.

Emotional arousal amplifies the effects of biased competition in the brain

The arousal-biased competition model predicts that arousal increases the gain on neural competition between stimuli representations. Thus, the model predicts that arousal simultaneously enhances processing of salient stimuli and impairs processing of relatively less-salient stimuli. We tested this model with a simple dot-probe task. On each trial, participants were simultaneously exposed to one face image as a salient cue stimulus and one place image as a non-salient stimulus. A border around the face cue location further increased its bottom-up saliency. Before these visual stimuli were shown, one of two tones played: one that predicted a shock (increasing arousal) or one that did not. An arousal-by-saliency interaction in category-specific brain regions (fusiform face area for salient faces and parahippocampal place area for non-salient places) indicated that brain activation associated with processing the salient stimulus was enhanced under arousal whereas activation associated with processing the non-salient stimulus was suppressed under arousal. This is the first functional magnetic resonance imaging study to demonstrate that arousal can enhance information processing for prioritized stimuli while simultaneously impairing processing of non-prioritized stimuli. Thus, it goes beyond previous research to show that arousal does not uniformly enhance perceptual processing, but instead does so selectively in ways that optimizes attention to highly salient stimuli.

Climate impact research: beyond patchwork

Despite significant progress in climate impacts research, the narratives that science can presently piece together of a 2-, 3-, 4-, or 5-degree warmer world remain fragmentary. Here we briefly review past undertakings to comprehensively characterize and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to systematically compare impacts models across sectors and scales, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impacts knowledge through integrated cross-sectoral assessments, and that the climate impacts community is now in a favourable position to do so.

Assessing the sensitivities of a distributed snow model to forcing data resolution

Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.

A Variance-Minimizing Filter for Large-Scale Applications

A truly variance-minimizing filter is introduced and its per for mance is demonstrated with the Korteweg– DeV ries (KdV) equation and with a multilayer quasigeostrophic model of the ocean area around South Africa. It is recalled that Kalman-like filters are not variance minimizing for nonlinear model dynamics and that four - dimensional variational data assimilation (4DV AR)-like methods relying on per fect model dynamics have dif- ficulty with providing error estimates. The new method does not have these drawbacks. In fact, it combines advantages from both methods in that it does provide error estimates while automatically having balanced states after analysis, without extra computations. It is based on ensemble or Monte Carlo integrations to simulate the probability density of the model evolution. When obser vations are available, the so-called importance resampling algorithm is applied. From Bayes’ s theorem it follows that each ensemble member receives a new weight dependent on its ‘ ‘distance’ ’ t o the obser vations. Because the weights are strongly var ying, a resampling of the ensemble is necessar y. This resampling is done such that members with high weights are duplicated according to their weights, while low-weight members are largely ignored. In passing, it is noted that data assimilation is not an inverse problem by nature, although it can be for mulated that way . Also, it is shown that the posterior variance can be larger than the prior if the usual Gaussian framework is set aside. However , i n the examples presented here, the entropy of the probability densities is decreasing. The application to the ocean area around South Africa, gover ned by strongly nonlinear dynamics, shows that the method is working satisfactorily . The strong and weak points of the method are discussed and possible improvements are proposed.

Exploring the impact of social axioms on firm reputation: a stakeholder perspective

This study proposes a model of how deeply held beliefs, known as ‘social axioms, moderate the interaction between reputation, its causes and consequences with stakeholders. It contributes to the stakeholder relational field of reputation theory by explaining why the same organizational stimuli lead to different individual stakeholder responses. The study provides a shift in reputation research from organizational-level stimuli as the root causes of stakeholder responses to exploring the interaction between individual beliefs and organizational stimuli in determining reputational consequences. Building on a conceptual model that incorporates product/service quality and social responsibility as key reputational dimensions, the authors test empirically for moderating influences, in the form of social axioms, between reputation-related antecedents and consequences, using component-based structural equation modelling (n = 204). In several model paths, significant differences are found between responses of individuals identified as either high or low on social cynicism, fate control and religiosity. The results suggest that stakeholder responses to reputation-related stimuli can be systematically predicted as a function of the interactions between the deeply held beliefs of individuals and these stimuli. The authors offer recommendations on how strategic reputation management can be approached within and across stakeholder groups at a time when firms grapple with effective management of diverse stakeholder expectations.

Participatory crop improvement: the challenges of and opportunities for institutionalisation in the Indian public research sector

This thesis considers Participatory Crop Improvement (PCI) methodologies and examines the reasons behind their continued contestation and limited mainstreaming in conventional modes of crop improvement research within National Agricultural Research Systems (NARS). In particular, it traces the experiences of a long-established research network with over 20 years of experience in developing and implementing PCI methods across South Asia, and specifically considers its engagement with the Indian NARS and associated state-level agricultural research systems. In order to address the issues surrounding PCI institutionalisation processes, a novel conceptual framework was derived from a synthesis of the literatures on Strategic Niche Management (SNM) and Learning-based Development Approaches (LBDA) to analyse the socio-technical processes and structures which constitute the PCI ‘niche’ and NARS ‘regime’. In examining the niche and regime according to their socio-technical characteristics, the framework provides explanatory power for understanding the nature of their interactions and the opportunities and barriers that exist with respect to the translation of lessons and ideas between niche and regime organisations. The research shows that in trying to institutionalise PCI methods and principles within NARS in the Indian context, PCI proponents have encountered a number of constraints related to the rigid and hierarchical structure of the regime organisations; the contractual mode of most conventional research, which inhibits collaboration with a wider group of stakeholders; and the time-limited nature of PCI projects themselves, which limits investment and hinders scaling up of the innovations. It also reveals that while the niche projects may be able to induce a ‘weak’ form of PCI institutionalisation within the Indian NARS by helping to alter their institutional culture to be more supportive of participatory plant breeding approaches and future collaboration with PCI researchers, a ‘strong’ form of PCI institutionalisation, in which NARS organisations adopt participatory methodologies to address all their crop improvement agenda, is likely to remain outside of the capacity of PCI development projects to deliver.

Morpho-physical Recording of Bovine Conceptus (Bos indicus) and Placenta from Days 20 to 70 of Pregnancy

The study is based on 141 pregnant Bos indicus cows, from days 20 to 70 post-insemination. First, special attention was given to the macroscopically observable phenomena of attachment of the conceptus to the uterus, i.e. the implantation, from about days 20 to 30 post-insemination up to day 70, and placentome development by growth, vascularization and increase in the number of cotyledons opposite to the endometrial caruncles. Secondly, as for the conceptuses, semiquantitative, statistical analyses were performed of the lengths of chorio-allantois, amnion and yolk sac; and the different parts of the centre and two extremes of the yolk sacs were also analysed. Thirdly, the embryos/foetuses corresponding to their membranes were measured by their greatest length and by weight, and described by the appearance of external developmental phenomena during the investigated period like neurulation, somites, branchial arcs, brain vesicles, limb buds, C-form, pigmented eye and facial grooves. In conclusion, all the data collected in this study from days 20 to 70 of bovine pregnancy were compared extensively with corresponding data of the literature. This resulted in an `embryo/foetal age-scale`, which has extended the data in the literature by covering the first 8 to 70 days of pregnancy. This age-scale of early bovine intrauterine development provides model for studies, even when using slaughtered cows without distinct knowledge of insemination or fertilization time, through macroscopic techniques. This distinctly facilitates research into the cow, which is now being widely used as `an experimental animal` for testing new techniques of reproduction like in vitro fertilization, embryo transfer and cloning.

Densities and Viscosities of vegetable oils of nutritional value

Densities and viscosities of five vegetable oils (Babassu oil, Buriti oil, Brazil nut oil, macadamia oil, and grape seed oil) and of three blends of Buriti oil and soybean oil were measured as a function of temperature and correlated by empirical equations. The estimation capability of two types of predictive methodologies was tested using the measured data. The first group of methods was based on the fatty acid composition of the oils, while the other was based on their triacylglycerol composition, as a multicomponent system. In general, the six models tested presented a good representation of the physical properties considered in this work. A simple method of calculation is also proposed to predict the dynamic viscosity of methyl and ethyl ester biodiesels, based on the fatty acid composition of the original oil. Data presented in this work and the developed model can be valuable for designing processes and equipment for the edible oil industry and for biodiesel production.