How do processes interact across levels of biological organization?

Abstract

Biological systems are organized in a size-hierarchy, from sub-molecular, via cells, tissues, and organisms to ecosystems and biomes. Different entities within each level of organization interact at varying spatial and temporal scales, and their interactions determine static as well as dynamic properties of the system. However, interactions occurring within a given level influence, and are influenced by, interactions that occur at many other levels of organization, and these together determine the emergent properties of biological systems. For example, the introduction of rabbits to Australia and sub-Antarctic islands in the 1800s had cascading effects across multiple scales throughout the ecosystem [1]. Similarly, but at different scales, muscle stretch injury has cascading effects that, in combination with organismal behavior, environmental factors [2], and drug therapies might determine the susceptibility of muscle once recovered to re-injury [3]. Such examples illustrate the complex cascading effects of cross-level interactions that occur up and down levels of biological organization. Improved understanding of complex interactions among levels would facilitate predictions with better accuracy of wide-scale effects that result from relatively simple perturbations at a single level (e.g. an injury, a simple mutation, a species introduction). Given our capacity for complex modeling and the explosion of big data science usually used within each level of biological organization, the time has come to push for the integration of these methods to provide more nuanced modeling of cascading interactions across levels of biological organization.