A generic model of hierarchy for systems analysis and simulation

Abstract Problems of global change and sustainable agriculture have motivated systems analyses that span increasing numbers of hierarchical levels. The reuse of existing simulation models in these expanded analyses is appealing, though experience with crop models shows that the design of the models can limit their reuse. In order to avoid these design problems, a new framework for systems analysis was developed based on hierarchy theory. The framework formalizes a metaphor used to define hierarchy: each hierarchical object (holon) is analyzed and modeled with two faces, named up and down, through which the object can communicate data; up is a portal for data exchange with the next higher level and down provides data exchange with the object's subsystems, which are also holons. This generic model of hierarchy was coded in object-oriented computer languages and was developed into a programming framework named JanuSys. JanuSys organizes communications between modeled holons and provides an orderly sequence to their simulation. The framework permits dynamic creation of a user-defined number of hierarchical levels, containing user-defined numbers of subsystems in each holon. These capabilities, combined with the generic model of hierarchy, are required for testing basic theories of hierarchy and systems evolution. If hierarchy theories are correct, JanuSys will provide a more successful foundation for systems analysis than non-hierarchic approaches.

[1]  William R. Taylor,et al.  Connection topology of proteins , 1993, Comput. Appl. Biosci..

[2]  J. D. Kabuga.  Social relationships in N'dama cattle during supplementary feeding , 1992 .

[3]  P. Hocking,et al.  Effects of body weight at sexual maturity and the degree and age of restriction during rearing on the ovarian follicular hierarchy of broiler breeder females. , 1993, British poultry science.

[4]  C. Pahlwostl,et al.  The Influence of a Hierarchy in Time Scales on the Dynamics of, and the Coexistence within, Ensembles of Predator-Prey Pairs , 1993 .

[5]  F. D. Panetta,et al.  Emex australis and the Competitive Hierarchy of a Grazed Annual Pasture , 1993 .

[6]  R. N. Kickert,et al.  Applied plant growth models for grazinglands, forests, and crops. , 1987 .

[7]  J. D. Hesketh,et al.  Current models and methods , 1987 .

[8]  Charles Francis,et al.  Exploring the role of diversity in sustainable agriculture. , 1995 .

[9]  Bjarne Stroustrup,et al.  C++ Programming Language , 1986, IEEE Softw..

[10]  James Hansen,et al.  Simulation of multiple cropping systems with CropSys , 1993 .

[11]  F. K. van Evert,et al.  CropSyst: a collection of object-oriented simulation models of agricultural systems , 1994 .

[12]  N. D. Stone,et al.  Object-oriented simulation: plant growth and discrete organ to organ interactions , 1991 .

[13]  Felix Müller,et al.  Hierarchical approaches to ecosystem theory , 1992 .

[14]  J. Amir,et al.  A model of the temperature and solar-radiation effects on spring wheat growth and yield , 1991 .

[15]  James W. Jones,et al.  Global climate change and US agriculture , 1990, Nature.

[16]  J. Bronowski.  The Ascent of Man , 1973 .

[17]  A. Nyerges,et al.  The Ecology of Wealth‐in‐People: Agriculture, Settlement, and Society on the Perpetual Frontier , 1992 .

[18]  William E. Lorensen,et al.  Object-Oriented Modeling and Design , 1991, TOOLS.

[19]  E. Odum,et al.  Input Management of Production Systems , 1989, Science.

[20]  Rebecca Wirfs-Brock,et al.  Designing object-oriented software , 1990 .

[21]  Herman H. Shugart,et al.  Scale, Synthesis, and Ecosystem Dynamics , 1988 .

[22]  C. J. Crosby,et al.  A simulation modeling tool for nitrogen dynamics using object-oriented progamming. , 1990 .

[23]  James Lowenberg-DeBoer,et al.  Simulation of yield distributions in millet-cowpea intercropping , 1991 .

[24]  W. Mcallister,et al.  Hierarchy of base-pair preference in the binding domain of the bacteriophage T7 promoter. , 1993, Journal of molecular biology.

[25]  T. Hodges.  Predicting Crop Phenology , 1990 .

[26]  Thomas B. Starr,et al.  Hierarchy: Perspectives for Ecological Complexity , 1982 .

[27]  R. O'Neill,et al.  FUNCTIONAL COMPLEXITY AND ECOSYSTEM STABILITY , 1980 .

[28]  Glyn M. Rimmington,et al.  A model of the effect of interspecies competition for light on dry-matter production , 1984 .

[29]  Jerry W. Stuth,et al.  Decision support systems for the management of grazing lands: emerging issues , 1993 .

[30]  R. O'Neill.  A Hierarchical Concept of Ecosystems. , 1986 .

[31]  C. A. Francis,et al.  Ecological framework for multiple cropping research. , 1986 .

[32]  William Silvert,et al.  Object-oriented ecosystem modelling , 1993 .

[33]  Richard Lowrance,et al.  A hierarchical approach to sustainable agriculture , 1986 .

[34]  HERBERT A. SIMON,et al.  The Architecture of Complexity , 1991 .

[35]  Grady Booch,et al.  Object-Oriented Design with Applications , 1990 .

[36]  D. Nullet,et al.  Local differences in soil temperature and soil moisture regimes on a mountain slope, Hawaii. , 1990 .

[37]  Carlo C. Maley,et al.  Implementing i-state configuration models for population dynamics: an object-oriented programming approach , 1993 .

[38]  Veerana Sinsawat,et al.  Growth of florets of sunflower (Helianthus annuus L.) in relation to their position in the capitulum, shading and nitrogen supply , 1993 .

[39]  Charles Francis,et al.  Multiple Cropping Systems , 1986 .

[40]  Robert F. Grant,et al.  Simulation of competition between barley and wild oats under different managements and climates , 1994 .

[41]  A Koestler,et al.  Ghost in the Machine , 1970 .

[42]  Paul Teng,et al.  Systems approaches for agricultural development , 1993, Systems Approaches for Sustainable Agricultural Development.

[43]  P A Johnson,et al.  Characterization of a source and levels of plasma immunoreactive inhibin during the ovulatory cycle of the domestic hen. , 1993, Biology of reproduction.

[44]  C. S. Holling.  Cross-Scale Morphology, Geometry, and Dynamics of Ecosystems , 1992 .