Literature DB >> 11459353

Information theory in ecology.

R E Ulanowicz1.   

Abstract

The application of information theory (IT) to ecology has occurred along two separate lines: (1) it has been used to quantify the distribution of stocks and numbers of organisms; and (2) it has been employed to quantify the pattern of interactions of trophic processes. By and large, the first endeavor has resulted in relatively few insights into ecosystem dynamics and has generated much ambiguity and disappointment, so that most ecologists remain highly skeptical about the advisability of applying IT to ecology. By contrast, the second, and less well-known application has shed light on the possibility that ecosystem behavior is the most palpable example of a purely natural 'infodynamics' that transcends classical dynamics, but remains well within the realm of quantitative description.

Entities:  

Mesh:

Year:  2001        PMID: 11459353     DOI: 10.1016/s0097-8485(01)00073-0

Source DB:  PubMed          Journal:  Comput Chem        ISSN: 0097-8485


  13 in total

1.  Illuminating a plant's tissue-specific metabolic diversity using computational metabolomics and information theory.

Authors:  Dapeng Li; Sven Heiling; Ian T Baldwin; Emmanuel Gaquerel
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-07       Impact factor: 11.205

2.  A supplementary tool to existing approaches for assessing ecosystem community structure.

Authors:  Matthew E Hopton; Arunprakash T Karunanithi; Ahjond S Garmestani; Denis White; Jerry R Choate; Heriberto Cabezas
Journal:  Ecol Modell       Date:  2017-07-10       Impact factor: 2.974

3.  Diversity and survival of artificial lifeforms under sedimentation and random motion.

Authors:  Nicolas Glade; Olivier Bastien; Pascal Ballet
Journal:  Theory Biosci       Date:  2017-07-18       Impact factor: 1.919

4.  Connections between classical and parametric network entropies.

Authors:  Matthias Dehmer; Abbe Mowshowitz; Frank Emmert-Streib
Journal:  PLoS One       Date:  2011-01-05       Impact factor: 3.240

5.  Novel topological descriptors for analyzing biological networks.

Authors:  Matthias M Dehmer; Nicola N Barbarini; Kurt K Varmuza; Armin A Graber
Journal:  BMC Struct Biol       Date:  2010-06-17

6.  Applying factor analysis combined with kriging and information entropy theory for mapping and evaluating the stability of groundwater quality variation in Taiwan.

Authors:  Guey-Shin Shyu; Bai-You Cheng; Chi-Ting Chiang; Pei-Hsuan Yao; Tsun-Kuo Chang
Journal:  Int J Environ Res Public Health       Date:  2011-04-08       Impact factor: 3.390

7.  Interrelations of graph distance measures based on topological indices.

Authors:  Matthias Dehmer; Frank Emmert-Streib; Yongtang Shi
Journal:  PLoS One       Date:  2014-04-23       Impact factor: 3.240

8.  Information theory tests critical predictions of plant defense theory for specialized metabolism.

Authors:  Dapeng Li; Rayko Halitschke; Ian T Baldwin; Emmanuel Gaquerel
Journal:  Sci Adv       Date:  2020-06-10       Impact factor: 14.136

9.  Mutual Information as a General Measure of Structure in Interaction Networks.

Authors:  Gilberto Corso; Gabriel M F Ferreira; Thomas M Lewinsohn
Journal:  Entropy (Basel)       Date:  2020-05-07       Impact factor: 2.524

10.  A large scale analysis of information-theoretic network complexity measures using chemical structures.

Authors:  Matthias Dehmer; Nicola Barbarini; Kurt Varmuza; Armin Graber
Journal:  PLoS One       Date:  2009-12-15       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.