Conceptualizations of Environment and Technology in Food Systems

This paper develops three alternative conceptualizations of the interrelationships between the environment, technology, and the food system as a basis for looking at the global dimensions of the food system in context of environmental and technological factors. The three conceptualizations are, respectively, a balance of trade oriented perspective, a human labor oriented perspective and a carrying capacity perspective

Technological Shift: As Related to Technological Learning and Technological Change

It is shown using a simple dynamic model of competition between product lines that the shape of learning curves has a powerful influence on the dynamics of technological substitution. Learning of both production efficiency and marketing efficiency are considered. It is asserted that both types of learning are important and that the two are complementary. It is further speculated that production learning is probably more important for commodities and in situations of low per capita income while market learning gains ascendancy in cases of high income and specialized and diversified product lines. In closing, it is noted that simple competitive models are misleading, firstly because complementarities and coevolutionary processes are probably as important in the overall development of technology as are competitive processes, and secondly because optimization of the technological system's parts does not guarantee improvement of the performance of the system as a whole

Global Modeling and Climate Impact Analysis

A sample of global economic and social system models are examined to ascertain how they might be utilized for climate impact analysis. General values and difficulties of global models as tools for climate impact are discussed. Special note is made of two models whose relatively strong biophysical basises appear to make them particularly compatible with climatological thinking. These and other global models are explored in terms of their time horizon, methods, and substantive focus. Possible contributions toward understanding climate in relation to agriculture, energy, demography, and politics are described. It is concluded that, despite the large number of difficulties with global models, models of some sort are required to investigate quantitative interrelationships of the global system, and that useful results could be extricated from existing models given imagination, critical awareness, and good scientific practice

PLANMKT: An Exploratory Model of the Market Mechanism in a Planned Economy

This paper describes PLANMKT, a simple, general model of the market mechanism in a planned economy. The paper and the model are exploratory. The paper's purpose is to describe the model and its behavior and to ask where they are and are not reasonable. It begins with a description of model structure and proceeds to description of the behavior that emanates from that structure

Technological Shift: A Graphical Exploration of Progress Functions Learning Costs and Their Effects on Technological Substitution

The innovation process, defined here to incorporate the full cycle from invention to full commercialization, is slow. It cannot be encompassed with time horizons of less than 26 years. Many innovations require half a century or more to reach commercial maturity. Management of the innovation process is critical to the management of technology, but the slowness of the process makes it difficult for conventional economists or policy makers, who typically consider 15 years a long-term forecast or plan, to understand or control. The situation, in short, is one in which the absence of theoretical understanding limits the effectiveness of managerial practice. Accordingly one appropriate niche for applied systems analysis in this case is development, application and testing of theoretical models. Toward this end the innovation-task of IIASA's Management and Technology Area is studying the mechanisms of technological substitution. One phase of this work is being conducted through construction and analysis of a series dynamic simulation models, TECH1, TECH2,..., TECH.N. The present working paper is one of a series describing these models. Its purpose is one of clarification, simplification and communication. It attempts, by use of static graphical figures, to make the dynamic process described in the models more understandable. It is complementary to working papers by the same author entitled "Technological Shift: A Cybernetic Exploration", a semi-technical description of TECH1, and "Technological Shift: As Related to Technological Learning and Technological Change", a discussion of some theoretical and philosophical aspects of the structure posed in the TECH models. Later papers in the series will describe TECH2, a variant of TECH restructured to assume a planned economy rather than free market competition, and application of TECH to historically observed technological substitutions. In the first six months of 1980 the entire series of working papers will be collected into a IIASA Research Report. Various parts of the series are being adapted for separate journal publication. The author welcomes comments, questions, criticisms and suggestions on this or any related work

Technological Shift: A Cybernetic Exploration

The innovation process, defined here to incorporate the full cycle from invention to full commercialization, is slow. It cannot be encompassed with time horizons of less than 26 years. Many innovations require half a century or more to reach commercial maturity. Management of the innovation process is critical to the management of technology, but the slowness of the process makes it difficult for conventional economists or policy makers, who typically consider 15 years a long-term forecast or plan, to understand or control. The situation, in short, is one in which the absence of theoretical understanding limits the effectiveness of managerial practice. Accordingly one appropriate niche for applied systems analysis in this case is development, application and testing of theoretical models. Toward this end the innovation-task of IIASA's Management and Technology Area is studying the mechanisms of technological substitution. One phase of this work is being conducted through construction and analysis of dynamic simulation models. The present paper describes TECH1, the first of these models. TECH1 is generic and views technological substitution as the interaction of product and process improvements (learning) and capacity acquisition under circumstances of market competition between an old and a new technology. Accompanying working papers, entitled "Technological Shift: A Graphical Exploration of Progress Functions, Learning Costs and Their Effects on Technological Substitution" and "Technological Shift: as Related to Technological Learning and Technological Change" develop concepts derived from TECH1 in, respectively, graphical and philosophical terms. Discussion of TECH1 with colleagues from socialist countries suggests that the model could be made more descriptive of technological substitution through making price and investment respond in non-smooth fashion to both exogenous policy goals and to extended product delivery waiting times (or inventory pile-ups) resulting from disequilibria of supply and demand. TECH2 will be developed to take these structural features into account and will be described in a later working paper. Another likely extension of this work is case application. If time permits the model will be adapted to describe four historical incidences of technological substitution. In the first six months of 1980 the entire series of working papers will be collected into a IIASA Research Report. Various parts of the series are being adapted for separate journal publication. The author welcomes comments, questions, criticisms and suggestions on this or any related work

Thermoelastic investigation of residual stress: plastic deformation and the change in thermoelastic constant

Plastic deformation causes very small changes in the thermoelastic response of metallic materials; this variation of the thermoelastic constant has the potential to form the basis of a new non-destructive, non-contact, full-field technique for residual stress assessment that is quicker and cheaper than existing methods. The effect of plastic strain on the thermoelastic constant is presented as a potential basis for a calibration methodology that reveals areas of a component that have experienced plastic strain. Establishing this basis provides the initial step in identifying a new approach to residual stress analysis using the thermoelastic response. An evaluation of initial calibration results is presented and the feasibility of applying the methodology to actual components is assessed. As the response to plastic strain is likely to be small it is necessary to identify the effects of the paint coating; experimental work is presented that highlights the importance of repeatable coating approaches

Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation

There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently estimate the posterior probability density function of hydrologic model parameters in complex, high-dimensional sampling problems. This MCMC scheme adaptively updates the scale and orientation of the proposal distribution during sampling and maintains detailed balance and ergodicity. It is then demonstrated how DREAM can be used to analyze forcing data error during watershed model calibration using a five-parameter rainfall-runoff model with streamflow data from two different catchments. Explicit treatment of precipitation error during hydrologic model calibration not only results in prediction uncertainty bounds that are more appropriate but also significantly alters the posterior distribution of the watershed model parameters. This has significant implications for regionalization studies. The approach also provides important new ways to estimate areal average watershed precipitation, information that is of utmost importance for testing hydrologic theory, diagnosing structural errors in models, and appropriately benchmarking rainfall measurement devices

A Framework for Scenario Generation for CO2 Gaming

This Working Paper develops a framework for the generation of integrated scenarios of carbon use and climatic impacts in the computer-based game and for strengthening the design of the board in the board game. The paper also seeks the assistance of readers in the further elaboration of several aspects of game design

Rekindling old friendships in new landscapes: The environment–microbiome–health axis in the realms of landscape research

1. Humans are spending less time in biodiverse environments, and according to the Old Friends and Biodiversity hypotheses, this has led to fewer interactions with diverse immunoregulatory micro‐organisms or ‘old friends’. 2. Non‐communicable diseases such as asthma and inflammatory bowel disease are on the rise, and the development and progression of these ‘modern’ diseases may be attributed in part, to the breakdown of this evolutionary relationship between humans and environmental microbiota. 3. There is a growing interest in the environment–microbiome–health axis as a mechanism to explain some of the health benefits linked to spending time in nature. 4. This may provide a platform for proposing a new, holistic and transdisciplinary approach to public and environmental health. 5. The field of landscape research—which combines social and natural sciences—responds to emerging socioecological issues and can make a significant contribution towards this approach. 6. This paper explores innovative, landscape research‐based approaches to understanding the complex relationships between the environment, the microbiome and human health. 7. Transdisciplinarity will play an important role moving forward. This forms a major discussion point in this paper, along with future research directions, key research questions and novel concepts supported by recent technological advancements. 8. The development of a new field of study—Microbioscape Research as a crossover between microbiome science and landscape research—is also discussed