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MODELING ECOLOGICAL PROCESSES ACROSS SCALES
Author(s) -
Urban Dean L.
Publication year - 2005
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/04-0918
Subject(s) - scaling , scale (ratio) , ecology , process (computing) , task (project management) , computer science , scaling law , focus (optics) , statistical physics , management science , mathematics , geography , biology , engineering , physics , systems engineering , geometry , cartography , optics , operating system
The issue of scaling impinges on every aspect of landscape ecology and much of ecology in general. Consequently, the topic has invited a vast commentary. One result of scaling research is so‐called scaling laws that describe how observations scale (e.g., as power laws). Importantly, such scaling rules seldom derive from a process‐based understanding of why they emerge. Alternatively, the task of scaling is often addressed via simulation models. This is a scaling operation about which we are somewhat less confident, although recent advances in computing power and computational statistics provide for some promising new solutions. Here, I focus on methods for scaling simulations developed at fine grain and small extent, to their implications over much larger extent. The intent in scaling is to simplify the model while retaining those details essential for larger‐scale applications. This approach should lead to scaling rules that are well founded in fine‐scale ecological process and yet useful for making predictions at the larger scales of management and environmental policy.