Toward systems agroecology: Design and control of intercropping.

In view of changing climatic conditions and disappearing natural resources such as fertile soil and water, exploring alternatives to today's industrial monocrop farming becomes essential. One promising farming practice is intercropping (IC), in which two or more crop species are grown together. Many experiments have shown that, under certain circumstances, IC can decrease soil erosion and fertilizer use, improve soil health and land management, while preserving crop production levels.

A theoretical perspective on Waddington's genetic assimilation experiments.

Genetic assimilation is the process by which a phenotype that is initially induced by an environmental stimulus becomes stably inherited in the absence of the stimulus after a few generations of selection. While the concept has attracted much debate after being introduced by C. H.

Evolutionary dynamics, evolutionary forces, and robustness: A nonequilibrium statistical mechanics perspective.

SignificanceEvolution through natural selection is an overwhelmingly complex process, and it is not surprising that theoretical approaches are strongly simplifying it. For instance, population genetics considers mainly dynamics of gene allele frequencies. Here, we develop a complementary approach to evolutionary dynamics based on three elements-organism reproduction, variations, and selection-that are essential for any evolutionary theory.

Nongenetic individuality, changeability, and inheritance in bacterial behavior.

Isogenic populations often display remarkable levels of phenotypic diversity even in constant, homogeneous environments. Such diversity results from differences between individuals ("nongenetic individuality") as well as changes during individuals' lifetimes ("changeability"). Yet, studies that capture and quantify both sources of diversity are scarce.

Bacterial Growth Control Mechanisms Inferred from Multivariate Statistical Analysis of Single-Cell Measurements.

Analysis of single-cell measurements of bacterial growth and division often relied on testing preconceived models of cell size control mechanisms. Such an approach could limit the scope of data analysis and prevent us from uncovering new information. Here, we take an "agnostic" approach by applying regression methods to multiple simultaneously measured cellular variables, which allow us to infer dependencies among those variables from their apparent correlations.