should be no less stringent than one would demand of a creationist. If evolutionary science is to move forward, the standards of the field should be set no lower than in any other area of inquiry.

The field of population genetics is technically demanding, and it is well known that most biologists abhor all things mathematical. However, the details do matter in the field of evolutionary biology. As discussed above, many aspects of biology that superficially appear to have adaptive roots almost certainly owe their existence in part to nonadaptive processes. Such conclusions would be difficult to reach without a formal population-genetic framework, but they equally rely on observations from molecular, genomic, and cell biology. Such conclusions also raise significant challenges. If complexity, modularity, evolvability, and/or robustness are entirely products of adaptive processes, then where is the evidence? What are the expected patterns of evolution of such properties in the absence of selection, and what types of observations would be acceptable as a falsification of a null, nonadaptive hypothesis?

This tone of dissent is not meant to be disrespectful. The development of a mature field of evolutionary biology requires the participation of not just population geneticists, but molecular, cell, and developmental biologists. However, the integration of these fields needs to be a two-way street. Because the forces of mutation, recombination, and genetic drift are now readily quantifiable in multiple species, there is no longer any justification for blindly launching suppositions about adaptive scenarios without an evaluation of the likelihood of nonadaptive alternatives. Moreover, if the conclusion that nonadaptive processes have played a central role in driving evolutionary patterns is correct, the origins of biological complexity should no longer be viewed as extraordinarily low-probability outcomes of unobservable adaptive challenges, but expected derivatives of the special population-genetic features of DNA-based genomes. A similar point has been made previously by Kauffman (1993), although his conclusions were derived from models far removed from mainstream population genetics.

Helpful input has been provided by E. Haag, M. Hahn, H. Malik, S. Otto, A. Stoltzfus, G. Wray, and the two reviewers. This work was supported by the National Institutes of Health and National Science Foundation.