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Engineering-Based Models Better Explain the Pattern of Nature than Does Common Ancestry

Brian Miller
Photo credit: Nathan Rupert, via Flickr (cropped).

In previous articles, I have described how engineering principles better explain adaptation than does evolutionary theory (herehereherehere). Now I will explain how engineering-based models also better explain the pattern of similarities and differences between species in the higher taxonomic groups (e.g., phyla, classes, and orders) than does the theory of common ancestry.

Computer scientist Winston Ewert demonstrated that the distribution of the same gene families in diverse species far better fits what he refers to as a dependency graph model than the common ancestry model. His central thesis is that similarities in life represent modules that were implemented in diverse species to achieve similar goals. This prediction has been validated by multiple lines of research over the past few decades.

The Collapse of the Tree of Life

I previously described how evolutionists present the purported tree of life (TOL) as their strongest evidence for common ancestry, and I explained why the TOL is collapsing (See, “BIO-Complexity Presents Better Model than Common Ancestry for Explaining Pattern of Nature.”)

By way of a synopsis, research on the rescaled consistency indexes (RCI) of numerous animal groups demonstrates the shocking inconsistency between the prediction of common ancestry and the actual pattern of similarities in different groups of species. An RCI of 1 indicates that all the data fit with an evolutionary tree. An RCI of 0 indicates that the distribution of similarities no better fits a tree than completely random data.  

To name but a few examples, data on traits in arthropods yielded a RCI of .39. The calculated RCI for therapsids (purported ancestors to mammals) was .42. The RCI for primates and their purported closest relatives was .29. And the RCI for cetaceans (e.g., whales and dolphins) and their purported closest relatives was .24. Evolutionists cite these groups as representing some of the strongest evidence for common ancestry, but their low RCIs testify to the opposite. 

Evolutionists historically predicted that RCI values would fall far closer to 1 than to 0, which they clearly do not. The low values demonstrate that the assumption that similarities in traits reliably imply common ancestry is false. The problem has become so acute for microorganisms that microbiologists Vicky Merhej and Didier Raoult portray attempts to identify the TOL in the most disparaging of terms (Merhej and Raoult, 2012):

None of the seven points laid out in the introduction to this manuscript can be permanently retained, as established by Darwin’s theory, which was at the time a fight against the creationists. This theory cannot be upheld in its entirety. Recent advances from genomics refute the ideas of gradualism, exclusive vertical inheritance, evolution selecting the fittest, a common ancestor and the TOL. Indeed, there may not be any two genes that have the same evolutionary tree. 

Disappointing Results

These disappointing results have forced evolutionists to propose several mechanisms to explain the ubiquitous inconsistencies. Examples include lateral gene transfer (LGT), differential gene loss, incomplete lineage sorting, and convergent evolution. LGT refers to genes passing from one organism to another. This process could theoretically explain how the same genes appear in unrelated species, but the plausibility of widespread LGT in complex organisms has been seriously questioned. Incomplete lineage sorting and gene loss cannot explain complex traits appearing in distantly related organisms. And the claim that complex adaptations can evolve independently multiple times (i.e., convergent evolution) collapses on close examination due to the implausibility of their appearing through undirected processes even once. 

For instance, eyes with lenses are believed to have evolved independently multiple times, but all evolutionary scenarios face insurmountable barriers. The first mutations in the origin of a lens would allocate tissue in front of the photoreceptors. But undifferentiated tissue would hinder light reception, so the first mutations would quickly disappear. The lens would not become beneficial until a complex developmental process coupled to a new gene regulatory network emerged. Yet the available time based on the fossil record is insufficient for even the tiniest amount of required new genetic information to arise (hereherehere).

Engineering Modules

In contrast, engineering-based models well explain the pattern of similarities throughout life. Design architectures often fall into a hierarchical pattern. All transportation vehicles have certain common features such as allocated space for cargo and/or passengers, a propulsion system, and steering. Cars possess all these features plus such components as wheels, breaks, coolants, lubricants, and axles. Toyota Camry models possess all these features plus additional specialized components. The similarities in transportation vehicles would likely fit into a constructed tree at least as well as different groups of species. 

While many features in human creations fit into a hierarchical tree-like pattern, many break that pattern. A police car and an airplane both have two-way radios while two-way radios are absent in most other cars. In addition, the same circuitry is implemented in a wide variety of vehicles to meet similar goals. This pattern reflects how engineers often create modules they implement in diverse contexts. The modules must be designed with the explicit intent of operating in different products, and the products that use the modules must be designed to properly incorporate them into their operations. The same pattern and constraints exist in life. 

Many of the same traits are implemented in diverse creatures to perform similar functions. Different versions of eyes (e.g., compound and camera-like) appear independently multiple times to allow optimal vision in each species’s particular context. And very similar neural and developmental modules appear independently in unrelated species. Neuroscientists Sanes and Zipursky identified in both fly and human visual systems remarkably similar design motifs in the retinas, neural circuits in the brains, and genetic control mechanisms in development even though the different eyes are believed to have evolved independently

“Robust Perfect Adaptation”

Similarly, mathematical biologists Robyn Araujo and Lance Liotta demonstrated that all biological networks that perform “robust perfect adaptation” (RPA) can be decomposed into two distinct classes of modules. The researchers define RPA as “the ability of a system to generate an output that returns to a fixed reference level (its ‘set point’) following a persistent change in input stimulus, with no need for tuning of system parameters.” The same modules appear in systems as diverse as signal transmission, gene regulation, protein interaction networks, sensory systems, and developmental regulation. They are often combined hierarchically to perform more complex functions. 

Of key importance, the base modules operate within exacting constraints:

  • Their constituent components must interconnect according to specific blueprints. 
  • They cannot be subdivided, so they comprise a set of components that are irreducibly complex. 
  • Their operations must solve a local adaptation equation, so reactions or other processes must operate within tight bounds.  
  • The integration of the modules into larger systems must also meet rigid mathematical criteria. 

These constraints imply that the modules’ origin and implementation could not have occurred incrementally through an undirected process since their construction and integration requires coordination, foresight, and goal direction. The authors of System Modeling in Cellular Biology (SMCB) assume evolution must be true as a faith commitment, but they still comment: 

…the concept of “modular design” is borrowed from human engineering and therefore has an essentially forward looking, goal-oriented nature. Complex engines and networks are constructed from modules while the final overall behavior of the system is kept in mind.

p. 44

Between a Submarine and an Airplane

The pattern of nature also corresponds to engineering principles in the distribution of species diversity. In human engineering, many versions of a particular design are often created such as Toyota manufacturing the same car model with different sets of options. But few products would fall outside the larger categories. Vehicles have rarely been designed that would fall part-way between a submarine and an airplane. 

In the same way, many different species exist that represent different versions of the same theme. Several ape-like and human-like creatures have been identified that share various similarities. But the similarities do not fit within a consistent evolutionary tree. And clearly intermediate creatures between primates and other orders of mammals have never been identified. In summary, every aspect of the pattern of similarities in nature contradicts the predictions of common ancestry and fits engineering model expectations.