国际应用系统分析研究所的生物圈项目

国际应用系统分析研究所座落于奥地利维也纳城近郊。在美国和苏联倡议下它创建于1972年10月,现有16个工业化国家是该所的成员国。它是一个非官方、多学科综合性研究所。笔者于1988年5月16日来到这里工作访问三天,主要內容是该所的环境计划和高级计算机应用实验室芯克.H.Pry先生介绍了环境计划的主要研究项目,即生物圈的生态持续稳定发展(简称生物圈项目)、酸雨和大型国际河流管理的决策支持系统。     

Agro-biology for bioregenerative Life Support Systems in long-term Space missions: General constraints and the Italian efforts

Abstract

Future Space stations and Space habitats/outposts should be envisioned as self-sufficient ecological closed or semi-closed systems. The Italian Space Agency (ASI) projects have involved many research groups from complementary areas with a final goal of designing a facility for plant cultivation in Space. It has been critical to (i) identify, for this particular environment, highly productive species able to optimize O₂ production/CO₂ consumption, and (ii) develop high-tech controlled environments. Research activities have included seedling production in simulated microgravity and in Space with the two-fold objective of (i) integrating the crew diet with fresh food, and (ii) studying specific biological phenomena. Another research topic concerned pollen biology as a critical component for seed-to-seed cycles but also for gametophytic selection. In this context, a review of the main scientific topics on plant Space biology and of the Italian efforts on agro-biology for bioregenerative Life Support Systems will be presented and discussed in this paper.     

A Stochastic Approach to Model Dynamic Systems in Life Cycle Assessment

This article presents a framework to evaluate emerging systems in life cycle assessment (LCA). Current LCA methods are effective for established systems; however, lack of data often inhibits robust analysis of future products or processes that may benefit the most from life cycle information. In many cases the life cycle inventory (LCI) of a system can change depending on its development pathway. Modeling emerging systems allows insights into probable trends and a greater understanding of the effect of future scenarios on LCA results. The proposed framework uses Bayesian probabilities to model technology adoption. The method presents a unique approach to modeling system evolution and can be used independently or within the context of an agent‐based model (ABM). LCA can be made more robust and dynamic by using this framework to couple scenario modeling with life cycle data, analyzing the effect of decision‐making patterns over time. Potential uses include examining the changing urban metabolism of growing cities, understanding the development of renewable energy technologies, identifying transformations in material flows over space and time, and forecasting industrial networks for developing products. A switchgrass‐to‐energy case demonstrates the approach.     

Biopolymers: Model Systems

A selection of World Wide Web sites relevant to papers published in this issue of Current Opinion in Chemical biology.     

Adaptation in Cones: A General Model

Three features appear to characterize steady-state light adaptation in vertebrate cone photoreceptors: (a) the shape of the “log intensity-response” curve at different levels of adaptation is the same, the only change with adaptation is in the position of the point on the curve about which the cones operate; (b) at high adapting intensities the operating point becomes fixed in position; (c) this fixed position is at the steepest point of the log intensity-response curve. These three features can be described by a mathematical model.     

Systems Biology: The elements and principles of Life

Systems Biology has a mission that puts it at odds with traditional paradigms of physics and molecular biology, such as the simplicity requested by Occam’s razor and minimum energy/maximal efficiency. By referring to biochemical experiments on control and regulation, and on flux balancing in yeast, we show that these paradigms are inapt. Systems Biology does not quite converge with biology either: Although it certainly requires accurate ‘stamp collecting’, it discovers quantitative laws. Systems Biology is a science of its own, discovering own fundamental principles, some of which we identify here.     

Measures of Variation at DNA Repeat Loci under a General Stepwise Mutation Model

Polymorphisms at tandem repeat loci are caused by mutations with allele sizes occasionally altered by more than one repeat unit in both forward and backward directions. Such mutational changes may occur with asymmetric probabilities. Therefore, a one-step symmetric stepwise mutation model may not be appropriate for studying the population dynamics at all repeat loci. In this work, we evaluated the expectation and variance of the within-population variance of the allele size distribution in a finite population, and the expected homozygosity at a locus by the coalescence approach under a general stepwise mutation model, where mutational transitions of allele sizes can be arbitrary, including being asymmetric. Under the special cases of symmetric one-step, two-step, and multi-step geometric distributions of mutations, our general results reduce to the corresponding results obtained by earlier investigators. The general results indicate that in a finite population, which has reached a steady state under the (general stepwise) mutation and drift balance, the within-population variance of allele sizes has a simple expectation (i.e., proportional toNν, the product of the mutation rate,ν, and effective population size,N). However, its stochastic variance is a quadratic function of this composite parameter,Nν. Furthermore, this second-order variance does not decay with the number of alleles sampled from a population. Application of this theory to data on allele size distributions in unrelated Caucasians from the CEPH pedigree (obtained from the Genome Data Base) shows that the relationship of the variance and mean of within-population variance of allele sizes at tandem repeat loci, grouped by their chromosomal assignment, has a trend compatible with the theory. However, there is an indication that the second-order variance is generally underestimated. One reason for this departure might be that the CEPH sample may not represent a single homogeneous population that reached equilibrium at all tandem repeat loci.     

Microbial Astronauts: Assembling Microbial Communities for Advanced Life Support Systems

Extension of human habitation into space requires that humans carry with them many of the microorganisms with which they coexist on Earth. The ubiquity of microorganisms in close association with all living things and biogeochemical processes on Earth predicates that they must also play a critical role in maintaining the viability of human life in space. Even though bacterial populations exist as locally adapted ecotypes, the abundance of individuals in microbial species is so large that dispersal is unlikely to be limited by geographical barriers on Earth (i.e., for most environments everything is everywhere given enough time). This will not be true for microbial communities in space where local species richness will be relatively low because of sterilization protocols prior to launch and physical barriers between Earth and spacecraft after launch. Although community diversity will be sufficient to sustain ecosystem function at the onset, richness and evenness may decline over time such that biological systems either lose functional potential (e.g., bioreactors may fail to reduce BOD or nitrogen load) or become susceptible to invasion by human-associated microorganisms (pathogens) over time. Research at the John F. Kennedy Space Center has evaluated fundamental properties of microbial diversity and community assembly in prototype bioregenerative systems for NASA Advanced Life Support. Successional trends related to increased niche specialization, including an apparent increase in the proportion of nonculturable types of organisms, have been consistently observed. In addition, the stability of the microbial communities, as defined by their resistance to invasion by human-associated microorganisms, has been correlated to their diversity. Overall, these results reflect the significant challenges ahead for the assembly of stable, functional communities using gnotobiotic approaches, and the need to better define the basic biological principles that define ecosystem processes in the space environment.     

Ego-Resiliency Reloaded: A Three-Component Model of General Resiliency

Ego-resiliency (ER) is a capacity that enables individuals to adapt to constantly changing environmental demands. The goal of our research was to identify components of Ego-resiliency, and to test the reliability and the structural and convergent validity of the refined version of the ER11 Ego-resiliency scale. In Study 1 we used a factor analytical approach to assess structural validity and to identify factors of Ego-resiliency. Comparing alternative factor-structures, a hierarchical model was chosen including three factors: Active Engagement with the World (AEW), Repertoire of Problem Solving Strategies (RPSS), and Integrated Performance under Stress (IPS). In Study 2, the convergent and divergent validity of the ER11 scale and its factors and their relationship with resilience were tested. The results suggested that resiliency is a double-faced construct, with one function to keep the personality system stable and intact, and the other function to adjust the personality system in an adaptive way to the dynamically changing environment. The stability function is represented by the RPSS and IPS components of ER. Their relationship pattern is similar to other constructs of resilience, e.g. the Revised Connor-Davidson Resilience Scale (R-CD-RISC). The flexibility function is represented by the unit of RPSS and AEW components. In Study 3 we tested ER11 on a Hungarian online representative sample and integrated the results in a model of general resiliency. This framework allows us to grasp both the stability-focused and the plasticity-focused nature of resiliency.