In a recent book review in Science of the book “From Populations to Ecosystems” by Michel Loreau, Tadashi Fukami emphasizes the message from the publication: the unfeasibility (and undesirability) to find a unified theory for ecology. Instead, he argues that it is a much better approach to deal with multilayer information, trying to find the links between different levels of organization.
Such problem arises also in other disciplines dealing with multiscale simulations. The unability of finding a unified model for a complete biological problem, for example, from the molecule to the organism, relies not in the difficulty of the mathematical approaches to be merged, but in the obvious difference in scales one faces. Thus, it is well known that it is by no means justified to include short time and small scale details that are not going to affect long time and big scale events, and applied mathematics is able to handle with the different problems by, let’s say, using stochastic to deterministic approaches. A solution in these cases is typically identifying those parameters for the large scale modelling that can be obtained aside from more detailed scale simulations.
Now that it seems that philosophy is menaced by our increasing knowledge of Nature (from the origin of the universe to the birth of conscience in our brain), scientists are falling in the danger to solely look at finding unified visions, while not realizing the power of applying what is already known has on our daily life. Finding a good combination of planning big answers to big questions while touching the ground and integrating what is already around us is the challenge for science in this next years. And multiscale simulations are in their way in many disciplines.
