InterJournal Complex Systems, 457
Status: Submitted
Manuscript Number: [457]
Submission Date: 1127
Comment on manuscript revision number 32586
Referee report on MS # 371
Author(s): Guy Hoelzer

Subject(s): CX.34, CX.19, CX.67

Category: Brief Article

Abstract:

This paper by Parrott and Kok presents a clear description of a new, object-based simulation platform for exploring patterns and processes of community structure. Like all such approaches, it has certain advantages over traditional reductionistic/analytical models; specifically, this approach adds flexibility in the assumption set, and the potential to reveal the emergence of system-wide behavior caused by complex interactions among system components. Limitations of this approach include the idiosyncratic behavior of each simulation, which raise concerns about the potential for induction. Nevertheless, I believe that this approach provides an important complement to the traditional approach, and one that has been lacking until now due to limitations of computational power. I recommend that this paper be accepted for publication. If the authors are to revise the paper, I have the following specific comments for consideration. p. 2, top: "Natural ecosystems have been shown to exhibit a wide variety of structural and dynamical features that are commonly attributed to the complex system..." I would attribute these features to "system complexity". p. 2, top: "...including self-organization, emergence of spatial and temporal patterns, efficient information processing, and effectively unpredictable behaviour." This is an interesting list. I am personally interested in the claim of "efficient information processing", but it would be worthwhile for the authors to provide references for each of these features, or for the set as a whole. p. 2, top: "As a result, there has recently been a shift away from the use of conventional “top-down” analytical models to “bottom-up” object-based approaches, in which ecosystems are portrayed at a high level of resolution as networks of many interacting components" Most, if not all of the analytical models refered to here are what I consider reductionistic (bottom-up), because they are mean field approximations of the system from the perspective of individual system components. If they were top-down models, then emergent system behavior could be recognized. I think the authors and I agree on the history here, but we would use opposing terminology to describe it. I do not want to impose my terminology on the authors, but they should appreciate the alternative description and modify this decription to avoid confusion. p. 2, middle: "In contrast, the authors have developed an object-based ecosystem model that is of a wide scope, including all of the major biotic and abiotic components of an ecosystem" This is too strongly stated. While the authors did an admirable job of including the factors that have been identified as having potential influence over community structure, we cannot know if their list includes ALL possible influential factors. p. 9, middle: "One of the most salient characteristics of a complex system is the presence of dissimilar spatial and temporal features at different scales." This seems to contradict my understanding of scale invariance (sensu Brown and West) under the sorts of power law distributions expected from complex systems. The authors should explain the meaning of this statement in this regard. Is this a true contradiction, or is their view consistent with what Brown and West refer to as scale invariance? Despite these minor concerns, I think this is an excellent paper that makes a good contribution to the InterJournal.

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