Using strong inference to falsify differential equation models of sugar maple height growth---Discussion

作者

  • Boris Zeide Professor Emeritus, University of Arkansas, USA

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critical thinking##common.commaListSeparator## growth equations##common.commaListSeparator## Popper##common.commaListSeparator## simple and complex problems##common.commaListSeparator## strong inference

摘要

Leary and Johannsen (2010; Leary and Johannsen. 2010. Using strong inference to falsify differential equation models of sugar maple height growth. MCFNS 2:1-11) envision growth modeling as a search for a single precise line like those depicting the laws of physics. However, it is unlikely that such a complex process as tree growth can be captured by our simple, usually empirical models. Instead of carrying out the experiment so as to get a clean result, it may be more realistic to start with enclosing the field of growth trajectories between two boundary lines representing the two opposite explanations of a studied relationship. Understanding complex process is more likely by combining opposites rather than falsifying one of them. Then, the modules delineating the boundaries can be joint in a single model that describes a more complex and fluid central tendency.  MCFNS 2(1):12-14.

##submission.citations##

Guttenberg, A.R. von 1915. Growth and yield of spruce in Hochgebirge. Franz Deuticke, Wien. 153 p. [In German] [Cited from Zeide, 1993]

Leary, R.A., V.K. Johannsen. 2010. Using strong inference to falsify differential equation models of sugar maple height growth. MCFNS 2(1):1-11.

Platt, J. 1964. Strong inference. Science 146:347-353.

Popper, K.R. 1983. Realism and the aim of science. W. W. Bartley (Editor). Rowman and Littlefield, Totowa, N.J. 464p.

Zeide, B. 1993. Analysis of growth equations. For. Sci. 39(3):594-616.

Zeide, B. 2008. The science of forestry. Journal of Sustainable Forestry 27(4): 345-473.

出版日期

2010-02-18

期號

分類

Mathematical Modeling

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