| Contents Notes |
Questioning Chance -- Chance in Living Systems -- Lessons for Managing Living Systems -- The Contribution of Models and Modelling: Some Examples -- Biodiversity and Ecological Theories -- Chance and Evolution -- Evaluating Biodiversity: The Example of French Guiana -- Conclusion. What are the origins of chance? Although its existence has long been accepted as a fact, the theory of probability only allows us to examine the random events produced by chance without enabling us to determine what creates it - and this despite knowing that living systems (from the cell to organisms, populations, communities and ecosystems) need chance to survive. In this book on living systems, we identify two origins: one external, coming from the environment, and the other, internal, produced by biological mechanisms that are molecular as well as cellular, demographic and ecological. These internal mechanisms - veritable "biological roulettes" - are similar to the mechanical devices that bring about "physical chance". They are at once the products and the engines of evolution and they also generate biodiversity, often in response to the vagaries of the environment. By creating biodiversity, these biological roulettes act as a kind of a life insurance that, on an evolutionary scale, ensure that life will continue after great upheaval: within the wide variety of organisms, there are some that are potentially adapted to new environmental conditions. From among those that survive, a new living world will grow and diversify. By examining biodiversity at all scales and all levels, this book seeks to evaluate the breadth of our knowledge on this topical subject; to propose an integrated look at living things; and to assess the role of chance in the dynamics of biodiversity, from populations to ecosystems and the biosphere, and more generally in evolutionary processes. Finally, it suggests that by simultaneously examining the mechanisms of diversification, maintenance and extinction, we can model the dynamics of biodiversity to better understand it and predict its variations and, thus, to foresee the practical aspects for managing living systems. |
