Wei Fang - Böcker

This book argues for the explanatory autonomy of the biological sciences. It does so by showing that scientific explanations in the biological sciences cannot be reduced to explanations in the fundamental sciences such as physics and chemistry and by demonstrating that biological explanations are advanced by models rather than laws of nature. To maintain the explanatory autonomy of the biological sciences, the author argues against explanatory reductionism and shows that explanation in the biological sciences can be achieved without reduction. Then, he demonstrates that the biological sciences do not have laws of nature. Instead of laws, he suggests that biological models usually do the explanatory work. To understand how a biological model can explain phenomena in the world, the author proposes an inferential account of model explanation. The basic idea of this account is that, for a model to be explanatory, it must answer two kinds of questions: counterfactual-dependence questions that concern the model itself and hypothetical questions that concern the relationship between the model and its target system. The reason a biological model can answer these two kinds of questions is due to the fact that a model is a structure, and the holistic relationship between the model and its target warrants the hypothetical inference from the model to its target and thus helps to answer the second kind of question.The Explanatory Autonomy of the Biological Sciences will be of interest to researchers and advanced students working in philosophy of science, philosophy of biology and metaphysics.

This book argues for the explanatory autonomy of the biological sciences. It does so by showing that scientific explanations in the biological sciences cannot be reduced to explanations in the fundamental sciences such as physics and chemistry and by demonstrating that biological explanations are advanced by models rather than laws of nature. To maintain the explanatory autonomy of the biological sciences, the author argues against explanatory reductionism and shows that explanation in the biological sciences can be achieved without reduction. Then, he demonstrates that the biological sciences do not have laws of nature. Instead of laws, he suggests that biological models usually do the explanatory work. To understand how a biological model can explain phenomena in the world, the author proposes an inferential account of model explanation. The basic idea of this account is that, for a model to be explanatory, it must answer two kinds of questions: counterfactual-dependence questions that concern the model itself and hypothetical questions that concern the relationship between the model and its target system. The reason a biological model can answer these two kinds of questions is due to the fact that a model is a structure, and the holistic relationship between the model and its target warrants the hypothetical inference from the model to its target and thus helps to answer the second kind of question.The Explanatory Autonomy of the Biological Sciences will be of interest to researchers and advanced students working in philosophy of science, philosophy of biology and metaphysics.

Giving a full description of the simulation techniques used in the greenhouse industry, this text includes information on different environments from mulching to greenhouses. Another important topic discussed at length is the relationship between plants and the environment. An emphasis is put on the relationship between quantitative phenomena and qualitative analyses. Most of the phenomena involved are non-linear and non-steady-state. In this second edition we describe these phenomena with an approach called System Dynamics and mathematical models developed in the simulation languages MATLAB and SIMULINK. These models can be easily adapted to the specific requirements of the readers, and the environments in which they work. In general, the subjects covered in this book should be relevant to graduate students, scientists and researchers in the agricultural and biological sciences.