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

Sherwin, William B.; Fornells, Narcís Prat

doi:10.3390/e21080794

Cited by 36 publications

(21 citation statements)

References 45 publications

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“…This approach has a long tradition in physics, both in statistical me-chanics and information theory. An early maximum entropy approach in ecology derived the biomass pattern of populations [13][14][15] .…”

Section: Department Of Evolutionary Biology and Environmentalmentioning

confidence: 99%

Invariance in ecological pattern

Frank

Bascompte

2019

F1000Res

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The abundance of different species in a community often follows the log series distribution. Other ecological patterns also have simple forms. Why does the complexity and variability of ecological systems reduce to such simplicity? Common answers include maximum entropy, neutrality, and convergent outcome from different underlying biological processes. This article proposes a more general answer based on the concept of invariance, the property by which a pattern remains the same after transformation. Invariance has a long tradition in physics. For example, general relativity emphasizes the need for the equations describing the laws of physics to have the same form in all frames of reference. By bringing this unifying invariance approach into ecology, we show that the log series pattern dominates when the consequences of processes acting on abundance are invariant to the addition or multiplication of abundance by a constant. The lognormal pattern dominates when the processes acting on net species growth rate obey rotational invariance (symmetry) with respect to the summing up of the individual component processes. Recognizing how these invariances connect pattern to process leads to a synthesis of previous approaches. First, invariance provides a simpler and more fundamental maximum entropy derivation of the log series distribution. Second, invariance provides a simple derivation of the key result from neutral theory: the log series at the metacommunity scale and a clearer form of the skewed lognormal at the local community scale. The invariance expressions are easy to understand because they uniquely describe the basic underlying components that shape pattern."It was Einstein who radically changed the way people thought about nature, moving away from the mechanical viewpoint of the nineteenth century toward the elegant contemplation of the underlying symmetry [invariance] principles of the laws of physics in the twentieth century" (ref. 1, p. 153).

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Section: Department Of Evolutionary Biology and Environmentalmentioning

confidence: 99%

Invariance in ecological pattern

Frank

Bascompte

2019

F1000Res

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“…1 of species in quadrats, and recommended that the indices which exhibit homogeneity property under all circumstances perform better. Attempts to measure inter-habitat spatial diversity between two habitats separated by a distance (L), were made by Margalef (1958) with the equation (Sherwin & Prat, 2019),…”

Section: Discussionmentioning

confidence: 99%

Extending the concept of entropy-negentropy for the assessment of ecological dominance and diversity at alpha, beta and gamma levels

Kumar¹,

Thukral

Sharma

et al. 2021

Geology, Ecology, and Landscapes

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Several measures of ecological diversity have been defined at alpha, beta, and gamma levels and less attention has been paid to characterise their ecological dominance. In this paper, we extend the concept of negative entropy (negentropy) for the measurement of ecological dominance and diversity at the three hierarchical levels of community characterization. Negentropy is a measure of energy, and gives a convex curve for binary negentropy function, whereas Shannon's entropy gives a typical concave curve. Similarly, we have defined indices for Simpson's and Brillouin's dominance functions at alpha, beta and gamma levels. The results of diversity indices followed a trend for different sites as: Harike > Beas > Goindwal Sahib, while trend obtained for dominance is Goindwal Sahib > Beas > Harike. The pooled results of both indicated that Harike showed maximum ecological information by the application of Shannon's diversity and Simpson's inverse diversity, while results of Simpson's diversity remain same for all sites.

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“…Leydesdorff and Rafols (2011) explored some of these as citation-based indicators for interdisciplinarity of journals and found Shan--9-manuscript submitted to Water Resources Research non entropy (Shannon, 1948). Shannon entropy is also a classic diversity metric that is used -among many other things -in ecology studies to quantify the diversity of species in a given ecosystem or location (e.g., Harte & Newman, 2014;Sherwin & Prat i Fornells, 2019). Intuitively, articles are analogous to a given ecological site and topics are analogous to species.…”

Section: Measuring Interdisciplinaritymentioning

confidence: 99%