TY - JOUR
T1 - A spatially explicit hierarchical approach to modeling complex ecological systems
T2 - Theory and applications
AU - Wu, Jianguo
AU - David, John L.
N1 - Funding Information:
We thank Darrel Jenerette, Habin Li, Matt Luck and Thomas Meyer for their comments on this paper. Darrin Thome and Hoski Schaasfma helped with the development of the spatial multi-species population dynamics model. JW would like to acknowledge the support for his research in hierarchical patch dynamics from US Environmental Protection Agency grant R827676-01-0 and US National Science Foundation grant DEB 97-14833 (CAP-LTER). Although the research described in this paper has been funded in part by the above mentioned agencies, it has not been subjected to the Agencies' required peer and policy review and therefore does not necessarily reflect the views of the agencies and no official endorsement should be inferred.
PY - 2002/7/15
Y1 - 2002/7/15
N2 - Ecological systems are generally considered among the most complex because they are characterized by a large number of diverse components, nonlinear interactions, scale multiplicity, and spatial heterogeneity. Hierarchy theory, as well as empirical evidence, suggests that complexity often takes the form of modularity in structure and functionality. Therefore, a hierarchical perspective can be essential to understanding complex ecological systems. But, how can such hierarchical approach help us with modeling spatially heterogeneous, nonlinear dynamic systems like landscapes, be they natural or human-dominated? In this paper, we present a spatially explicit hierarchical modeling approach to studying the patterns and processes of heterogeneous landscapes. We first discuss the theoretical basis for the modeling approach - the hierarchical patch dynamics (HPD) paradigm and the scaling ladder strategy, and then describe the general structure of a hierarchical urban landscape model (HPDM-PHX) which is developed using this modeling approach. In addition, we introduce a hierarchical patch dynamics modeling platform (HPD-MP), a software package that is designed to facilitate the development of spatial hierarchical models. We then illustrate the utility of HPD-MP through two examples: a hierarchical cellular automata model of land use change and a spatial multi-species population dynamics model.
AB - Ecological systems are generally considered among the most complex because they are characterized by a large number of diverse components, nonlinear interactions, scale multiplicity, and spatial heterogeneity. Hierarchy theory, as well as empirical evidence, suggests that complexity often takes the form of modularity in structure and functionality. Therefore, a hierarchical perspective can be essential to understanding complex ecological systems. But, how can such hierarchical approach help us with modeling spatially heterogeneous, nonlinear dynamic systems like landscapes, be they natural or human-dominated? In this paper, we present a spatially explicit hierarchical modeling approach to studying the patterns and processes of heterogeneous landscapes. We first discuss the theoretical basis for the modeling approach - the hierarchical patch dynamics (HPD) paradigm and the scaling ladder strategy, and then describe the general structure of a hierarchical urban landscape model (HPDM-PHX) which is developed using this modeling approach. In addition, we introduce a hierarchical patch dynamics modeling platform (HPD-MP), a software package that is designed to facilitate the development of spatial hierarchical models. We then illustrate the utility of HPD-MP through two examples: a hierarchical cellular automata model of land use change and a spatial multi-species population dynamics model.
KW - Complex systems modeling
KW - Hierarchical modeling
KW - Hierarchical patch dynamics
KW - Scaling
KW - Urban landscape ecology
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U2 - 10.1016/S0304-3800(01)00499-9
DO - 10.1016/S0304-3800(01)00499-9
M3 - Article
AN - SCOPUS:0037099993
SN - 0304-3800
VL - 153
SP - 7
EP - 26
JO - Ecological Modelling
JF - Ecological Modelling
IS - 1-2
ER -