Entry Deutschman:2000:RVU from siggraph2000.bib

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BibTeX entry

@Article{Deutschman:2000:RVU,
  author =       "Douglas H. Deutschman and Catherine Devine and Linda
                 A. Buttel",
  title =        "The role of visualization in understanding a complex
                 forest simulation model",
  journal =      j-COMP-GRAPHICS,
  volume =       "34",
  number =       "1",
  pages =        "51--55",
  month =        feb,
  year =         "2000",
  CODEN =        "CGRADI, CPGPBZ",
  DOI =          "https://doi.org/10.1145/604446.604452",
  ISSN =         "0097-8930",
  bibdate =      "Wed Oct 7 09:18:19 MDT 2009",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/siggraph2000.bib",
  abstract =     "Ecological research is changing as scientists confront
                 the complexities of natural and human-influenced
                 ecosystems. Early ecological research was dominated by
                 the concepts of equilibrium and determinism [30].
                 Ecosystems were thought to be stable 'super-organisms,'
                 fine-tuned by thousands of years of mutual adaptation.
                 In such a world, ecosystems can be completely described
                 with static measures of equilibrium population
                 densities. Although this view has been challenged since
                 its inception, it is only in the past 25 years that it
                 has been displaced as the dominant paradigm in ecology.
                 Today, ecologists describe ecosystems as a dynamic
                 collection of individuals responding in different ways
                 to local interactions, broad-scale environmental change
                 and frequent accidents of history [18, 23, 30].
                 Although the behavior of the ecosystem is partially
                 understandable from population densities, ecosystem
                 dynamics are variable and complex. Ecologists use an
                 increasingly sophisticated toolbox of techniques to
                 characterize these complex dynamics. Field surveys and
                 laboratory experiments measure the responses of
                 individuals under varied conditions. Thus the mean
                 response as well as the variance in response can be
                 estimated. Improved statistical analyses allow
                 ecologists to describe spatial structure, temporal
                 dynamics and complex spatio-temporal patterns. Finally,
                 mathematical models are being developed that can
                 simulate the complex local interactions of thousands of
                 individuals in a dynamic, heterogeneous environment [9,
                 17, 34].Improvements in computer hardware and software
                 have facilitated this shift toward increasing
                 complexity. Today, ecologists are seldom limited by
                 hardware, and software to acquire, store and analyze
                 data has improved dramatically in the past decade. In
                 addition, computational models of ecological systems
                 are becoming common [14]. Models are tools to express
                 our understanding of mechanisms governing the structure
                 and function of ecological communities [20]. Models can
                 also be used to make predictions, determine the
                 robustness of these predictions, reveal system
                 properties and highlight weaknesses in our knowledge
                 [8, 25]. Complex ecological models have several
                 important drawbacks including the need for huge amounts
                 of input data, propagation of errors and difficulty
                 interpreting the often voluminous model output [10, 11,
                 13]. As a result, increased model complexity and detail
                 may not lead to increased understanding [10, 16, 22].",
  acknowledgement = ack-nhfb,
  fjournal =     "Computer Graphics",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J166",
}

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