This is what some call microevolution and nobody debates it. The real issue is macroevolution - whether major changes in organisms can occur through the proposed mechanisms of neo-darwinian theory. That is the issue. Both sides of this issue have been debated at length at asa3.org the American Scientific Affiliation, a fellowship of Christians in the sciences. So although there is nothing wrong with your assertions about single-celled life evolving, that is not the issue anybody disagrees with.
The left hand column of the table you quoted defines the drivers for both macro and microevolution. Macroevolution is the accumulation of microevolution events over geological timescales which is the mainstream view of evolution.
My response was to a creationist who probably gets his information from creationist sites such as AIG and ICR not the American Scientific Affiliation.
AIG and ICR are renowned for their dishonest portrayals of mainstream science, the subjects of macro and microevolution are no exception, their rejection of the connection between the two is not based on any science but on the false dichotomy that no connection automatically validates creationism.
DennisF:
Egad, if you know anything from science you know that nonlinear systems are modeled at a given point - an operating-point - in their nonlinear functions and that incremental changes around that point are how they are linearized so that linear systems theory can be applied to describe their behavior around that point. Physicists call it perturbation theory. Electronics engineers call it small-signal or incremental modeling. This not only applies to transistors but also to evolutionary development.
(The Santa Fe Institute has put plenty of work into this. Have you even heard of them?)
As the extrapolation of differentials from the op-pt increases, the validity of the model diminishes. Once the evolutionary changes being considered are too large, the bacteria-level model no longer has validity.
With regards to your response to
@Hans Blaster, Hans happens to be a physicist and your transistor analogy has a fundamental problem as to have a perturbation you need a fixed or equilibrium starting point around which perturbation occurs. While this is not a problem with transistors, there are no fixed or equilibrium points in evolution as the starting point for evolution namely mutations are by their very nature random.
While the Santa Fe Institute does challenge the mainstream view of the connection between macroevolution and microevolution it is not an endorsement for creationism and provides an alternate hypothesis at bacterial levels where bacteria are modelled as large population networks. It however does not refute the mainstream model at bacterial levels.
| Aspect | Mainstream Evolutionary Biology | Santa Fe Institute (Complex Systems Approach) |
|---|
| Core Model | Population genetics: allele frequency changes under selection, drift, mutation, and gene flow | Complex adaptive systems: interaction networks, feedback, emergent properties |
| Mutation Role | Random mutations drive variation; modeled with fixation probabilities | Mutations interact with dynamic systems; may trigger emergent behaviors |
| Selection | Acts on genetic variants within a fixed environment | Acts within a co-evolving, possibly shifting environment (e.g., phages, hosts) |
| Adaptation | Gradual changes in traits based on fitness advantages | Nonlinear adaptation through system-level restructuring and feedback |
| Horizontal Gene Transfer (HGT) | Treated as an exception or special case | Central mechanism for network rewiring and innovation |
| Biofilms / Communities | Often modeled as individual strains in competition | Viewed as distributed, interactive systems with emergent cooperation or specialization |
| Modeling Tools | Wright-Fisher models, mutation-selection balance, molecular evolution theory | Fitness landscapes (e.g., NK models), agent-based models, network theory |
| Innovation (e.g., antibiotic resistance) | Stepwise accumulation of beneficial mutations, or plasmid acquisition | Innovation emerges from modularity, recombination, and network plasticity |
| Fitness Landscapes | Fixed or slowly changing; individuals climb fitness peaks over time | Rugged, dynamic landscapes; organisms may explore, jump, or be driven across valleys |
| Equilibrium View | Populations may stabilize under selective pressures | Systems are dynamic, far-from-equilibrium, with ongoing restructuring |
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