194 CATALYZING INQUIRY
Among the fundamental questions in the study of evolution are those that seek to know the relative
strengths of natural selection, genetic drift, dispersal processes, and genetic recombination in shaping
the genome of a population—essentially the forces that provide genetic variability in a species. Both
ecologists and evolutionary biologists want to know how these forces lead to morphological changes,
speciation, and ultimately, survival over time. The fields seek theory, models, and data that can account
for genetic changes over time in large heterogeneous populations in which genetic information is
exchanged routinely in an environment that also exerts its influence and changes over time.
In addition to interest in genetic variability and fitness within a single species, the two fields are
interested in relationships between multiple species. In ecology, this manifests itself in questions of how
the individual forces of variability within and between species affect their relative ability to compete for
resources and space that leads to their survival or extinction—in other words, forces that determines the
biodiversity of an ecosystem (i.e., a set of biological organisms interacting among themselves and their
environment). Ecologists want to understand what determines the minimum viable population size for
a given population, the role of keystone species in determining the diversity of the ecosystem, and the
role of diversity in preservation of the ecosystem.
For evolutionary biologists, questions regarding relationships between species focus on trying to
understand the flow of genetic information over long periods of time as a measure of the relatedness of
different species and the effects of selection on the genetic contribution to phenotypes. Among the great
mysteries for evolutionary biologists is whether and how evolution relates to organismal development,
an interaction for which no descriptive language currently exists.
How will ecologists and evolutionary biologists answer these questions? These fields have had few
tools to monitor interactions in real time. But new opportunities have emerged in areas from genomics
to satellite imaging and in new capabilities for the computer simulation of complex models.
5.4.8.2 Examples from Evolution
A plethora of genomic data is beginning to help untangle the relationship between traits, genes,
developmental processes, and environments. The data will serve as the substrate from which new
statistical conclusions can be drawn, for example, new methods for identifying inherited gene se-
quences such as those related to disease. To answer question about the process of genome rearrange-
ment, the possibility of comparing gene sequences from multiple organisms provides the basis for
testing tools that discern repeatable patterns and elucidate linkages.
As more detailed DNA and protein sequence information is compiled for more genes in more
organisms, computational algorithms for estimating parameters of evolution have become extremely
complex. New techniques will be needed to handle the likelihood functions and produce satisfactory
statistics in a reasonable amount of time. Studies of the role of environmental and genetic plasticity in
trait development will involve large-scale simulations of networks of linked genes and their interacting
products. Such simulations may well suggest new approaches to such old problems as the nature-
nurture dichotomy for human behaviors.
New techniques and the availability of more powerful computers have also led to the development
of highly detailed models in which a wide variety of components and mechanisms can be incorporated.
Among these are individual unit models that attempt to follow every individual in a population over
time, thereby providing insight into dynamical behavior (Box 5.22).
Levin argues that such models are “imitation[s] of reality that represent at best individual realiza-
tion of complex processes in which stochasticity, contingency, and nonlinearity underlie a diversity of
possible outcomes.”^109 From the collective behaviors of individual units arise the observable dynamics
(^109) S.A. Levin, B. Grenfell, A. Hastings, and A.S. Perelson, “Mathematical and Computational Challenges in Population Biology
and Ecosystems Science,” Science 275(5298):334-343, 1997.