TY - JOUR
T1 - Implementing i-state configuration models for population dynamics
T2 - an object-oriented programming approach
AU - Maley, Carlo C.
AU - Caswell, Hal
N1 - Funding Information:
This researchw as supportedb y NSF Grant OCE-8900231a nd DOE Grant DE-FG02-89ER60882to HC, and by a WHOI SummerS tudent Fellowshipa nd MarshallS cholarshipto CM. We thankS olangeB raultfor helpful discussionds uringthe developmenotf the models.W oods Hole OceanographIincs titutionC ontribution8 332.
PY - 1993/7
Y1 - 1993/7
N2 - Demographic models describe population dynamics in terms of the distribution of individuals among categories (e.g., age or size classes); such models are called i-state distribution models. In contrast, i-state configuration models describe population dynamics by simulating the birth, development, and eventual death of each individual in the population. Such models (also referred to, less precisely, as individual-based models) are necessary when interactions among individuals make the assumptions of i-state distribution models untenable. The basic components of an i-state configuration model are a set of individuals (each characterized by its i-state), an interaction structure, and an environment. Each of these components changes dynamically as a function of the others. The implementation of i-state distribution models is familiar; here we present a general framework, based on object-oriented programming (OOP), for the numerical implementation of i-state configuration models. The individuals, interaction structure, and environment are all defined as objects. A special object called the simulator transfers information among these objects as needed. The properties of OOP (data protection, inheritance, polymophism, modularity) lend themselves naturally to i-state configuration simulations.
AB - Demographic models describe population dynamics in terms of the distribution of individuals among categories (e.g., age or size classes); such models are called i-state distribution models. In contrast, i-state configuration models describe population dynamics by simulating the birth, development, and eventual death of each individual in the population. Such models (also referred to, less precisely, as individual-based models) are necessary when interactions among individuals make the assumptions of i-state distribution models untenable. The basic components of an i-state configuration model are a set of individuals (each characterized by its i-state), an interaction structure, and an environment. Each of these components changes dynamically as a function of the others. The implementation of i-state distribution models is familiar; here we present a general framework, based on object-oriented programming (OOP), for the numerical implementation of i-state configuration models. The individuals, interaction structure, and environment are all defined as objects. A special object called the simulator transfers information among these objects as needed. The properties of OOP (data protection, inheritance, polymophism, modularity) lend themselves naturally to i-state configuration simulations.
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U2 - 10.1016/0304-3800(93)90109-6
DO - 10.1016/0304-3800(93)90109-6
M3 - Article
AN - SCOPUS:0027843581
SN - 0304-3800
VL - 68
SP - 75
EP - 89
JO - Ecological Modelling
JF - Ecological Modelling
IS - 1-2
ER -