Scaling in geology: landforms and earthquakes.

Landforms and earthquakes appear to be extremely complex; yet, there is order in the complexity. Both satisfy fractal statistics in a variety of ways. A basic question is whether the fractal behavior is due to scale invariance or is the signature of a broadly applicable class of physical processes. Both landscape evolution and regional seismicity appear to be examples of self-organized critical phenomena. A variety of statistical models have been proposed to model landforms, including diffusion-limited aggregation, self-avoiding percolation, and cellular automata. Many authors have studied the behavior of multiple slider-block models, both in terms of the rupture of a fault to generate an earthquake and in terms of the interactions between faults associated with regional seismicity. The slider-block models exhibit a remarkably rich spectrum of behavior; two slider blocks can exhibit low-order chaotic behavior. Large numbers of slider blocks clearly exhibit self-organized critical behavior.

Spectral diffusion and the energy landscape of a protein

We present a novel type of spectral diffusion experiment in the millikelvin range to characterize the energy landscape of a protein as compared with that of a glass. We measure the time evolution of spectral holes for more than 300 hr after well-defined initial nonequilibrium conditions. We show that the model of noninteracting two-level systems can describe spectral diffusion in the glass, but fails for the protein. Our results further demonstrate that randomness in the energy landscape of a protein shows features of organization. There are “deep minimum” states separated by barriers, the heights of which we are able to estimate. The energy landscape of a glass is featureless by comparison.

Computational method to reduce the search space for directed protein evolution

We introduce a computational method to optimize the in vitro evolution of proteins. Simulating evolution with a simple model that statistically describes the fitness landscape, we find that beneficial mutations tend to occur at amino acid positions that are tolerant to substitutions, in the limit of small libraries and low mutation rates. We transform this observation into a design strategy by applying mean-field theory to a structure-based computational model to calculate each residue's structural tolerance. Thermostabilizing and activity-increasing mutations accumulated during the experimental directed evolution of subtilisin E and T4 lysozyme are strongly directed to sites identified by using this computational approach. This method can be used to predict positions where mutations are likely to lead to improvement of specific protein properties.

Human-modified ecosystems and future evolution

Our global impact is finally receiving the scientific attention it deserves. The outcome will largely determine the future course of evolution. Human-modified ecosystems are shaped by our activities and their side effects. They share a common set of traits including simplified food webs, landscape homogenization, and high nutrient and energy inputs. Ecosystem simplification is the ecological hallmark of humanity and the reason for our evolutionary success. However, the side effects of our profligacy and poor resource practices are now so pervasive as to threaten our future no less than that of biological diversity itself. This article looks at human impact on ecosystems and the consequences for evolution. It concludes that future evolution will be shaped by our awareness of the global threats, our willingness to take action, and our ability to do so. Our ability is presently hampered by several factors, including the poor state of ecosystem and planetary knowledge, ignorance of human impact, lack of guidelines for sustainability, and a paucity of good policies, practices, and incentives for adopting those guidelines in daily life. Conservation philosophy, science, and practice must be framed against the reality of human-dominated ecosystems, rather than the separation of humanity and nature underlying the modern conservation movement. The steps scientists can take to imbed science in conservation and conservation in the societal process affecting the future of ecosystems and human well-being are discussed.

Protein evolution on partially correlated landscapes.

We extend an earlier model of protein evolution on a rugged landscape to the case in which the landscape exhibits a variable degree of correlation (i.e., smoothness). Correlation is introduced by assuming that a protein is composed of a set of independent blocks or domains and that mutation in one block affects the contribution of that block alone to the overall fitness of the protein. We study the statistical structure of such landscapes and apply our theory to the evolution by somatic hypermutation of antibody molecules composed of framework and complementarity-determining regions. We predict the expected number of replacement mutations in each region.