Evolution is certainly a tricky word.

For a creationist, it’s clear as day why. There are two equivocal definitions being used which blur the lines and convolute any attempt at productive dialogue.

“Change in allele frequencies in a population over time.”

The breakdown: Alleles represent versions of genes in which a part of the gene is different, which often makes the overall functional outcome in some way different.

The frequencies in a population are the ratio of members with or without an allele.

Finally, the premise of this definition is that the number of organisms in a population with a certain trait can grow or diminish over time.

This seems to me a very uncontroversial thing to hold to. Insofar as evolution could be a fact, this is certainly hard to deny.

All that is needed for this first definition is mechanisms for sorting and redistribution of existing variation.

However, what is commonly inferred from the term is an altogether separate conception:

“All living things are descended from a common ancestor.”

This is clearly different. An evolutionist may agree, but argue that these are merely differences in degree (or scale). But is that the case?

The only way to know whether the one definition flows seamlessly into the next or whether this is a true equivocation is to understand the underlying mechanism. For instance, let’s talk about movement.

South America and Asia are roughly four times further apart than Australia and Antarctica. Yet, I could say, rightly, that I could walk from South America to Asia, but I could not say the same about Australia and Antarctica. Why is this? If I can walk four times the distance in one instance, why should I be thus restricted?

The obvious reason is this: Australia and Antarctica are separated by the entire width of the deep, open Southern Ocean and the Tasman Sea. I should not expect that I can traverse, by walking, two places with no land betwixt them.

The takeaway is this: My extrapolation is only good so long as my mechanism is sufficient. Walking is only possible with land bridges. Without land bridges, it doesn’t matter the distance; you’re not going to make it.

This second definition requires mechanisms for sorting and redistribution of existing variation as well as creation of new biological information and structures.

With that consideration, let us now take this lesson and apply it to the mechanisms of change which evolutionists espouse.

There are many, but we will quickly narrow our search.

Natural Selection: This is any process that acts as a culling from the environment (which can be ecology, climate, niche, etc).

Gene Flow: This is the reproductive isolation of populations.

Genetic Drift/Draft: This is any process that causes fluctuations in alleles due to a lack of selection pressures.

Sexual Selection/Non-Random Mating: This is the process by which organisms preferentially choose phenotypes.

The point of this exercise is to observe that these are all mechanisms of sorting and redistribution of existing variation, but they are not the mechanisms that create that variation in the first place. Any mechanism that lacks creative power is insufficient to account for our second definition.

The mechanism that is left is, you might have guessed, mutation.

Here’s the problem: mutation is its own conflation. We need to unravel the many ways in which DNA can change. There are many kinds of mutations, and what’s true for one may not be true for another. For example, it is often said that mutations are:

1. Copying errors
2. Creative
3. Random with respect to fitness

However, this is hardly the case for many various types of phenomena that are classified as mutations.

For instance, take recombination.

Recombination is not a copy error. It is a very particular and facilitated meiotic process that requires deliberate attention and agency.

Recombination is not creative. Although it can technically cause a change in allele frequencies (as a new genotype is being created), so can every other non-creative process. It can no more create new genetic material than a card shuffler can create new cards.

Recombination is not random with respect to fitness. Even with recombination, like a card shuffler, being random in one sense, there is a telos about particular random processes that make them constitute something not altogether random. If we take a card shuffler, it is not random with respect to the “fitness” of the card game. In fact, it is specifically designed to make a fairer and balanced game night. Likewise, recombination, particularly homologous recombination (HR), is fundamentally a high-fidelity DNA repair pathway. It is designed to prevent the uninterrupted spread of broken or worse genes within a single genotype. Like the card shuffler, the mechanism of recombination has no foresight, but it has an explicit function nonetheless.

Besides recombination, there are many discrete ways in which mutations can happen. On the small scale, we see things like Single Nucleotide Polymorphisms (SNPs) and Insertions and Deletions (Indels). Zooming out, we also find mutations such as duplications & deletions of genes or multiple genes (e.g., CNVs), exon shuffling, and transposable elements. On the grand scale, we see events such as whole genome duplications and epigenetic modifications as well.

On the small scale, Single Nucleotide Polymorphisms (SNPs) and Insertions and Deletions (Indels) are the equivalent of typos or missing characters within an existing blueprint. While a typo can certainly change the meaning of a sentence, it cannot generate a completely new architectural plan. It modifies the existing instruction set; it does not introduce a novel concept or function absent in the original text. These are powerful modifiers, but their action is always upon pre-existing information.

It is also the case that these mutations can never rightly be called evolution. They are not creative; they are only destructive mechanisms. Copy errors create noise, not clarity, in information systems.

Further, these small-scale mutations happen within the context of the preexisting structure and integrity of the genome. So that, even those which are said to be beneficial are preordained to be so by some higher design principles. For instance, much work has been done to show that nucleosomes protect DNA from damage and structural variants stabilize regions where they emerge:

“Structural variants (SVs) tend to stabilize regions in which they emerge, with the effect most pronounced for pathogenic SVs. In contrast, the effects of chromothripsis are seen across regions less prone to breakages. We find that viral integration may bring genome fragility, particularly for cancer-associated viruses.” (Pflughaupt et al.)

“Eukaryotic DNA is organized in nucleosomes, which package DNA and regulate its accessibility to transcription, replication, recombination, and repair… living cells nucleosomes protect DNA from high-energy radiation and reactive oxygen species.” (Brambilla et al.)

Moving to the medium scale, consider duplications and deletions (CNVs) and exon shuffling. Gene duplication, often cited as a source of novelty, is simply copying an entire, functional module—a paragraph or even a full chapter. This provides redundancy. It is often supposed that this allows one copy to drift while the original performs its necessary task. But gene duplications are not simply ignored by the genome or selective processes. They are often immediately discarded if they don’t infer a use, or otherwise, they are incorporated in a certain way.

“Gene family members may have common non-random patterns of origin that recur independently in different evolutionary lineages (such as monocots and dicots, studied here), and that such patterns may result from specific biological functions and evolutionary needs.” (Wang et al.)

Here we see that there is often a causal link between the needs of the organism and the duplication event itself. Further, we observe a highly selective process of monitoring post-duplication:

“Recently, a nonrandom process of gene loss after these different polyploidy events has been postulated [12,31,38]. Maere et al. [12] have shown that gene decay rates following duplication differ considerably between different functional classes of genes, indicating that the fate of a duplicated gene largely depends on its function.” (Casneuf et al.)

Even if the function conferred was redundancy, redundancy is not creation; it is merely an insurance policy for existing information. Where, precisely, is the mechanism that takes that redundant copy and molds it into a fundamentally new structure or process—say, turning a light-sensing pigment gene into a clotting factor? What is the search space that will have to be traversed? Indels and SNPs are not sufficient to modify a duplication into something entirely novel. Novel genes require novel sequences for coding specific proteins and novel sequences for regulation. Duplication at best provides a scratch pad, which is highly sensitive to being tampered with.

Exon shuffling, similarly, is a process of reorganization, splicing together pre-existing functional protein domains. This is the biological equivalent of an editor cutting and pasting sentences from one section into another. The result can be a new combination, but every word and grammatical rule was already present. It is the sorting and redistribution of parts.

Further, exon shuffling is a highly regulated process that has been shown to be constrained by splice frame rules and mediated by TEs in introns.

“Exon shuffling follows certain splice frame rules. Introns can interrupt the reading frame of a gene by inserting a sequence between two consecutive codons (phase 0 introns), between the first and second nucleotide of a codon (phase 1 introns), or between the second and third nucleotide of a codon (phase 2 introns).” (Wikipedia Contributors)

This Wikipedia article gives you a taste for the precision and intense regulation, prerequisite and premeditated, in order to perform what are essentially surgical operations to create specialized proteins for cellular operation. One of the reasons it is such a delicate process is portrayed in this journal article:

“Successful shuffling requires that the domain in question is bordered by introns that are of the same phase, that is, that the domain is symmetrical in accordance with the phase-compatibility rules of exon shuffling (Patthy 1999b), because shuffling of asymmetrical exons/domains will result in a shift of the reading frame in the downstream exons of recipient genes.” (Kaessmann)

In the same way, transposable elements are constrained by the epigenetic and structural goings-on of the genome. Research shows that transposase recognizes DNA structure at insertion sites, and there are physical constraints caused by chromatin:

“We show that all four of these measures of DNA structure deviate significantly from random at P element insertion sites. Our results argue that the donor DNA and transposase complex performing P element integration may recognize a structural feature of the target DNA.” (Liao Gc et al.)

Finally, we look at the grand scale. Whole Genome Duplication (WGD) is the ultimate copy-paste—duplicating the entire instructional library. Again, this provides massive redundancy but offers zero novel genetic information. This is not creative in any meaningful sense, even at the largest scale.

As for epigenetic modifications, these are critical regulatory mechanisms that determine when and how existing genes are expressed. They are the rheostats and switches of the cell, changing the output and timing without ever altering the source code (the DNA sequence). They are regulatory, not informational creators.

The central issue remains: The second definition of evolution requires the creation of new organizational blueprints and entirely novel biological functions.

The mechanism of change relied upon—mutation—is, across all its various types, fundamentally a system of copying, modification, deletion, shuffling, or regulation of existing, functional genetic information. None of these phenomena, regardless of their scale, demonstrates the capacity to generate the required novel information (the “land bridge”) necessary to traverse the vast gap between one kind of organism and another. Again, they are really great mechanisms for change over time, but they are pitiable creative mechanisms.

Therefore, the argument that the two definitions of evolution are merely differences of scale falls apart. The extrapolation from observing a shift in coat color frequency (Definition 1) to positing a common ancestor for all life (Definition 2) is logically insufficient. It requires a creative mechanism that is qualitatively different from the mechanisms of sorting and modification we observe. Lacking that demonstrated, information-generating mechanism, we are left with two equivocal terms, where one is an undeniable fact of variation and the other is an unsupported inference of mechanism—a proposal to walk across the deep, open ocean with only the capacity to walk on land.

Works Cited

Brambilla, Francesca, et al. “Nucleosomes Effectively Shield DNA from Radiation Damage in Living Cells.” Nucleic Acids Research, vol. 48, no. 16, 10 July 2020, pp. 8993–9006, pmc.ncbi.nlm.nih.gov/articles/PMC7498322/, https://doi.org/10.1093/nar/gkaa613. Accessed 30 Oct. 2025.

Casneuf, Tineke, et al. “Nonrandom Divergence of Gene Expression Following Gene and Genome Duplications in the Flowering Plant Arabidopsis Thaliana.” Genome Biology, vol. 7, no. 2, 2006, p. R13, https://doi.org/10.1186/gb-2006-7-2-r13. Accessed 7 Sept. 2021.

Kaessmann, H. “Signatures of Domain Shuffling in the Human Genome.” Genome Research, vol. 12, no. 11, 1 Nov. 2002, pp. 1642–1650, https://doi.org/10.1101/gr.520702. Accessed 16 Jan. 2020.

Liao Gc, et al. “Insertion Site Preferences of the P Transposable Element in Drosophila Melanogaster.” Proceedings of the National Academy of Sciences of the United States of America, vol. 97, no. 7, 14 Mar. 2000, pp. 3347–3351, https://doi.org/10.1073/pnas.97.7.3347. Accessed 1 Dec. 2023.

Pflughaupt, Patrick, et al. “Towards the Genomic Sequence Code of DNA Fragility for Machine Learning.” Nucleic Acids Research, vol. 52, no. 21, 23 Oct. 2024, pp. 12798–12816, https://doi.org/10.1093/nar/gkae914. Accessed 8 Nov. 2025.

Wang, Yupeng, et al. “Modes of Gene Duplication Contribute Differently to Genetic Novelty and Redundancy, but Show Parallels across Divergent Angiosperms.” PLoS ONE, vol. 6, no. 12, 2 Dec. 2011, p. e28150, https://doi.org/10.1371/journal.pone.0028150. Accessed 20 Dec. 2021.

Wikipedia Contributors. “Exon Shuffling.” Wikipedia, Wikimedia Foundation, 31 Oct. 2025, en.wikipedia.org/wiki/Exon_shuffling.