Information theory and ecological diversity

2005 ◽  
pp. 290-303 ◽  
Author(s):  
David Lurié ◽  
Jorge Wagensberg
Keyword(s):  
Information Theory ◽  
Ecological Diversity

scholarly journals The Introduction of Entropy and Information Methods to Ecology by Ramon Margalef

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 794 ◽  
Author(s):  
William B Sherwin ◽  
Narcis Prat i Fornells
Keyword(s):  
Information Theory ◽  
Environmental Variables ◽  
Alpha Diversity ◽  
Ecosystem Processes ◽  
Ecological Diversity ◽  
100Th Birthday ◽  
Accessible Form

In ecology and evolution, entropic methods are now used widely and increasingly frequently. Their use can be traced back to Ramon Margalef’s first attempt 70 years ago to use log-series to quantify ecological diversity, including searching for ecologically meaningful groupings within a large assemblage, which we now call the gamma level. The same year, Shannon and Weaver published a generally accessible form of Shannon’s work on information theory, including the measure that we now call Shannon–Wiener entropy. Margalef seized on that measure and soon proposed that ecologists should use the Shannon–Weiner index to evaluate diversity, including assessing local (alpha) diversity and differentiation between localities (beta). He also discussed relating this measure to environmental variables and ecosystem processes such as succession. Over the subsequent decades, he enthusiastically expanded upon his initial suggestions. Finally, 2019 also would have been Margalef’s 100th birthday.

Conditional and Weighted Measures of Ecological Diversity

2003 ◽  
Vol 11 (03) ◽  
pp. 283-300 ◽  
Author(s):  
Radu Cornel Guiaşu ◽  
Silviu Guiaşu
Keyword(s):  
Information Theory ◽  
Shannon Entropy ◽  
Supplementary Information ◽  
Conservation Value ◽  
Ecological Diversity ◽  
Simpson Index ◽  
Global Measure ◽  
Absolute Abundance ◽  
Economic Significance ◽  
Respective Species

Shannon's entropy and Simpson's index are the most used measures of species diversity. As the Simpson index proves to be just an approximation of the Shannon entropy, conditional Simpson indices of diversity and a global measure of interdependence among species are introduced, similar to those used in the corresponding entropic formalism from information theory. Also, since both the Shannon entropy and the Simpson index depend only on the number and relative abundance of the respective species in a given ecosystem, the paper generalizes these indices of diversity to the case when a numerical weight is attached to each species. Such a weight could reflect supplementary information about the absolute abundance, the economic significance, or the conservation value of the species.

Network Information Theory

2011 ◽  
Author(s):  
Abbas El Gamal ◽  
Young-Han Kim
Keyword(s):  
Information Theory ◽  
Network Information Theory ◽  
Network Information

Information Theory and Coding by Example

2009 ◽  
Author(s):  
Mark Kelbert ◽  
Yuri Suhov
Keyword(s):  
Information Theory

Constructing and Deconstructing Concepts

2016 ◽  
Vol 63 (5) ◽  
pp. 249-262 ◽  
Author(s):  
Charles A. Doan ◽  
Ronaldo Vigo
Keyword(s):  
Information Theory ◽  
Model Performance ◽  
Unsupervised Classification ◽  
Family Resemblance ◽  
Category Membership ◽  
Formal Models ◽  
Human Beings ◽  
One Dimensional ◽  
Relational Patterns ◽  
Optimal Classification

Abstract. Several empirical investigations have explored whether observers prefer to sort sets of multidimensional stimuli into groups by employing one-dimensional or family-resemblance strategies. Although one-dimensional sorting strategies have been the prevalent finding for these unsupervised classification paradigms, several researchers have provided evidence that the choice of strategy may depend on the particular demands of the task. To account for this disparity, we propose that observers extract relational patterns from stimulus sets that facilitate the development of optimal classification strategies for relegating category membership. We conducted a novel constrained categorization experiment to empirically test this hypothesis by instructing participants to either add or remove objects from presented categorical stimuli. We employed generalized representational information theory (GRIT; Vigo, 2011b , 2013a , 2014 ) and its associated formal models to predict and explain how human beings chose to modify these categorical stimuli. Additionally, we compared model performance to predictions made by a leading prototypicality measure in the literature.

Test of the Information Theory of Secondary Reinforcement

1968 ◽  
Author(s):  
John D. Davis ◽  
Constance Oliphant
Keyword(s):  
Information Theory ◽  
Secondary Reinforcement
Sign in / Sign up

Export Citation Format

Share Document