Structural change in macroeconomic time series: A complex systems perspective

We demonstrate that the process of generating smooth transitions Call be viewed as a natural result of the filtering operations implied in the generation of discrete-time series observations from the sampling of data from an underlying continuous time process that has undergone a process of structural change. In order to focus discussion, we utilize the problem of estimating the location of abrupt shifts in some simple time series models. This approach will permit its to address salient issues relating to distortions induced by the inherent aggregation associated with discrete-time sampling of continuous time processes experiencing structural change, We also address the issue of how time irreversible structures may be generated within the smooth transition processes. (c) 2005 Elsevier Inc. All rights reserved.

A complex systems approach to the value of ecological resources

A theory of value sits at the core of every school of economic thought and directs the allocation of resources to competing uses. Ecological resources complicate the modem neoclassical approach to determining value due to their complex nature, considerable non-market values and the difficulty in assigning property rights. Application of the market model through economic valuation only provides analytical solutions based on virtual markets, and neither the demand nor supply-side techniques of valuation can adequately consider the complex set of biophysical and ecological relations that lead to the provision of ecosystem goods and services. This paper sets out a conceptual framework for a complex systems approach to the value of ecological resources. This approach is based on there being both an intrinsic quality of ecological resources and a subjective evaluation by the consumer. Both elements are necessary for economic value. This conceptual framework points the way towards a theory of value that incorporates both elements, so has implications for principles by which ecological resources can be allocated. (c) 2005 Elsevier B.V. All rights reserved.

Why is economics not a complex systems science?

The article argues that economics will have to become a complex systems science before economists can comfortably incorporate institutionalist and evolutionary economics into mainstream theory. The article compares the complex adaptive system of John Foster with that of standard economic theory and illustrates the difference through an examination of familiar production function. The place of neoclassical, Keynesian economics in complex systems is considered. The article concludes that convincing, multiple models have been made possible by the increase in widely available computing power available.

Patterns in complex systems modeling

The design, development, and use of complex systems models raises a unique class of challenges and potential pitfalls, many of which are commonly recurring problems. Over time, researchers gain experience in this form of modeling, choosing algorithms, techniques, and frameworks that improve the quality, confidence level, and speed of development of their models. This increasing collective experience of complex systems modellers is a resource that should be captured. Fields such as software engineering and architecture have benefited from the development of generic solutions to recurring problems, called patterns. Using pattern development techniques from these fields, insights from communities such as learning and information processing, data mining, bioinformatics, and agent-based modeling can be identified and captured. Collections of such 'pattern languages' would allow knowledge gained through experience to be readily accessible to less-experienced practitioners and to other domains. This paper proposes a methodology for capturing the wisdom of computational modelers by introducing example visualization patterns, and a pattern classification system for analyzing the relationship between micro and macro behaviour in complex systems models. We anticipate that a new field of complex systems patterns will provide an invaluable resource for both practicing and future generations of modelers.

Transcriptional network dynamics in macrophage activation

Transcriptional regulatory networks govern cell differentiation and the cellular response to external stimuli. However, mammalian model systems have not yet been accessible for network analysis. Here, we present a genome-wide network analysis of the transcriptional regulation underlying the mouse macrophage response to bacterial lipopolysaccharide (LPS). Key to uncovering the network structure is our combination of time-series cap analysis of gene expression with in silico prediction of transcription factor binding sites. By integrating microarray and qPCR time-series expression data with a promoter analysis, we find dynamic subnetworks that describe how signaling pathways change dynamically during the progress of the macrophage LPS response, thus defining regulatory modules characteristic of the inflammatory response. In particular, our integrative analysis enabled us to suggest novel roles for the transcription factors ATF-3 and NRF-2 during the inflammatory response. We believe that our system approach presented here is applicable to understanding cellular differentiation in higher eukaryotes. (c) 2006 Elsevier Inc. All rights reserved.

Pattern-based reuse of successful designs: usability ofsafety-critical systems

Users of safety-critical systems are expected to effectively control or monitor complex systems, with errors potentially leading to catastrophe. For such systems, safety is of paramount importance and must be designed into the human-machine interface. While many case studies show how inadequate design practice led to poor safety and usability, concrete guidance on good design practices is scarce. The paper argues that the pattern language paradigm, widely used in the software design community, is a suitable means of documenting appropriate design strategies. We discuss how typical usability-related properties (e.g., flexibility) need some adjustment to be used for assessing safety-critical systems, and document a pattern language, based on corresponding "safety-usability" principles

Additional signalling compounds are required to orchestrate plant development

Plants are necessarily complex systems that require monitoring of multiple environmental signals and, in response to those signals, coordination of differentiation and development of an extensive array of cell types at multiple locations. This coordination must rely on integration of long-distance signals that provide a means of communication among different plant parts. We propose that the relatively well-characterized classical phytohormones must act with several other long-distance signals to achieve this level of organization with dynamic yet measured responses. This is supported by observations that classical phytohormones: (i) operate in complex yet experimentally unresolved networks involving cross-talk and feedback, (ii) are generally multifunctional and nonspecific and hence must rely on other long-distance cues or pre-set conditions to achieve specificity and (iii) are likely to mask roles of other long-distance signals in several experimental contexts. We present evidence for involvement of novel long-distance signals in three developmental processes-branching, flowering and nodulation, and discuss the possible identities of novel signalling molecules.

Inherent size constraints on prokaryote gene networks due to "accelerating" growth

Networks exhibiting accelerating growth have total link numbers growing faster than linearly with network size and either reach a limit or exhibit graduated transitions from nonstationary-to-stationary statistics and from random to scale-free to regular statistics as the network size grows. However, if for any reason the network cannot tolerate such gross structural changes then accelerating networks are constrained to have sizes below some critical value. This is of interest as the regulatory gene networks of single-celled prokaryotes are characterized by an accelerating quadratic growth and are size constrained to be less than about 10,000 genes encoded in DNA sequence of less than about 10 megabases. This paper presents a probabilistic accelerating network model for prokaryotic gene regulation which closely matches observed statistics by employing two classes of network nodes (regulatory and non-regulatory) and directed links whose inbound heads are exponentially distributed over all nodes and whose outbound tails are preferentially attached to regulatory nodes and described by a scale-free distribution. This model explains the observed quadratic growth in regulator number with gene number and predicts an upper prokaryote size limit closely approximating the observed value. (c) 2005 Elsevier GmbH. All rights reserved.

Accounting for uncertainty in marine reserve design

Ecosystems and the species and communities within them are highly complex systems that defy predictions with any degree of certainty. Managing and conserving these systems in the face of uncertainty remains a daunting challenge, particularly with respect to developing networks of marine reserves. Here we review several modelling frameworks that explicitly acknowledge and incorporate uncertainty, and then use these methods to evaluate reserve spacing rules given increasing levels of uncertainty about larval dispersal distances. Our approach finds similar spacing rules as have been proposed elsewhere - roughly 20-200 km - but highlights several advantages provided by uncertainty modelling over more traditional approaches to developing these estimates. In particular, we argue that uncertainty modelling can allow for (1) an evaluation of the risk associated with any decision based on the assumed uncertainty; (2) a method for quantifying the costs and benefits of reducing uncertainty; and (3) a useful tool for communicating to stakeholders the challenges in managing highly uncertain systems. We also argue that incorporating rather than avoiding uncertainty will increase the chances of successfully achieving conservation and management goals.