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Addresses of All Authors

Institute for Creation Research

1806 Royal Lane

Dallas, TX 75229

Author's Biography

Leo (Jake) Hebert, III earned a B.S. from Lamar University, an M.S. from Texas A&M University, and a Ph.D. from the University of Texas at Dallas (all in physics). His Ph.D. work involved cutting-edge research on a possible connection between cosmic rays, solar activity, and weather and climate. He has had a strong interest in creationism since he was a teenager. He is now a research scientist at the Institute for Creation Research in Dallas, TX, where he has been employed since 2011.

Presentation Type

Full Paper Presentation

Proposal

Within the creationist community, there has been recent interest in applying engineering principles to the study of living things. Engineers routinely attempt to maximize certain qualities, such as efficiency and durability, while minimizing others, such as cost of construction, within certain design limits or constraints. Biologists have long suspected that living things are in some sense “optimized” and there is a long history of attempting to understand biological systems in terms of this optimization. This is strong prima facie evidence of intelligent design, yet evolutionists attribute this optimization to evolution and natural selection.

Biological optimization is closely related to allometry, the study of the manner in which biological variables scale with body size. A large body of literature suggests that observable biological characteristics are often proportional to an organism’s mass raised to some power, often a simple multiple of 1/4. Some of these variables include lifespan, heart rate, and the radii of tree trunks and the mammalian aorta. One particularly well-known example was discovered by agricultural scientist Max Kleiber. He observed that for birds and many mammals, basal (resting) metabolic rate is proportional to body mass raised to the 3/4 power. This surprised biologists, as they were expecting, based on simple geometrical reasoning, an exponent of 2/3, rather than 3/4.

In 1997 physicist Geoffrey West and biologists Brian Enquist and James Brown (WEB) published a theoretical explanation for Kleiber’s Law. WEB modeled a biological nutrient supply network as levels of interconnected, diverging pipes. The highest level of the network consisted of one single large pipe, which diverged into multiple pipes at the second and subsequent levels. The number of new branches (the branching ratio) at each junction was a constant, and pipes in subsequent levels decreased in size in a regular, predictable manner. The resulting pipe network was a self-similar fractal. WEB assumed that biological systems are designed to minimize the amount of energy needed to transport nutrients to the entire organism, given “volume filling” and other constraints. They used Lagrange multipliers to find optimal values (in terms of branching ratios) for pipe lengths and pipe cross-sectional areas in subsequent levels of the network. Their model did a reasonably good job of accounting for 16 features of the mammalian circulatory system and 17 characteristics of plant vascular systems.

Nevertheless, the WEB theory has been the subject of controversy, with some questioning the empirical validity of Kleiber’s Law, as well as whether it is truly universal. Nevertheless, the WEB model reignited interest in using engineering principles to understand living things, inspiring others to propose other optimization models. Although some of these are quite impressive, none are universally successful, probably because some of the model constraints are too strong, whereas in many cases, additional constraints need to be added. This suggests that the optimization of living things is very sophisticated, involving the “balancing” of multiple different design considerations against one another. In fact, other researchers have already suggested design considerations that might perhaps need to be included in future models. Clearly, living things are designed according to optimization principles, and any creationist theory of biological design should make use of them. Yet surprisingly, these optimization/allometric theories seem to have received little attention in the creationist community.

This paper is divided into four parts. Part 1 provides an overview of allometry and earlier attempts to apply optimization principles to biology. Part 2 provides an overview of the WEB theory, as it is perhaps the best known optimization theory currently in existence. I lay out the theory’s basics, filling in details which may not be obvious to newcomers, especially the “volume filling” requirement, which was not clearly explained by WEB. Part 3 discusses both successes and failures of the theory, as well as possible reasons for the failures. Part 4 discusses ways in which creationists could improve upon the WEB theory. I provide examples of how flowchart logic might be helpful in improving upon these models, as could observations and deductions from Scripture.

This area is “wide open” for creation researchers. Although the WEB and other models are quite impressive, they are still relatively crude, as evidenced by their inability to explain all observations. Creationists have a real opportunity to improve on existing models to obtain a more comprehensive and successful theory of biological design.

Disciplines

Biology

Keywords

Metabolic scaling, allometry, longevity, scaling laws, WBE theory, optimization, design, giantism

DOI

10.15385/jpicc.2023.9.1.12

Disclaimer

DigitalCommons@Cedarville provides a publication platform for fully open access journals, which means that all articles are available on the Internet to all users immediately upon publication. However, the opinions and sentiments expressed by the authors of articles published in our journals do not necessarily indicate the endorsement or reflect the views of DigitalCommons@Cedarville, the Centennial Library, or Cedarville University and its employees. The authors are solely responsible for the content of their work. Please address questions to dc@cedarville.edu.

Submission Type

paper

Included in

Biology Commons

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