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Biodiversity describes the variety of living things at multiple organizational levels: genetic, species and ecosystem diversity. Species diversity includes all branches of the evolutionary tree from single-celled prokaryotic organisms, bacteria, and archaea, to the eukaryotic kingdoms: plants; animals; fungi; and protists. To date, there have been about 1.75 million species identified, and new species are discovered every week.
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Dealing with bio- and ecological complexity: Challenges and opportunities.

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Control engineering faces challenges in biological and ecological systems. Dynamic modeling and control advance understanding and methods in these complex domains.

Keywords:
AgricultureBiomedical systemsBiotechnologyControl systemsEcologyEnvironmental systemsModelling

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Area of Science:

  • Control Engineering
  • Biological Systems
  • Ecological Systems

Background:

  • Biological and ecological systems present complex dynamic processes challenging for control engineers.
  • Dynamic modeling and control have significantly improved the understanding of these complexities over decades.
  • These systems serve as crucial test-beds, revealing limitations and driving advancements in control methodologies.

Purpose of the Study:

  • To explore the opportunities and achievements in applying dynamic modeling and control within bio- and ecological domains.
  • To highlight the synergistic relationship between complex biological/ecological systems and control engineering advancements.

Main Methods:

  • Review and synthesis of existing literature on dynamic modeling and control in bio- and ecological contexts.
  • Analysis of how these systems act as platforms for developing and testing novel control strategies.
  • Examination of the impact of control engineering applications on understanding biological and ecological dynamics.

Main Results:

  • Demonstration of successful applications of dynamic modeling and control in understanding complex biological and ecological phenomena.
  • Identification of specific areas where control engineering has catalyzed methodological innovation.
  • Evidence of the iterative process where system complexities drive control theory advancements.

Conclusions:

  • The application of dynamic modeling and control continues to offer significant opportunities in biological and ecological sciences.
  • Methodological advancements in control engineering are spurred by the challenges inherent in these complex systems.
  • Further integration of control engineering principles is essential for deeper insights into bio- and ecological dynamics.