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title = "Multifractals in ecology using R" |
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date = 2017-11-28T10:48:00-05:00 |
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tags = ["real-examples", "math", "equations"] |
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draft = false |
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author = "Leonardo A. Saravia" |
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source = "https://github.com/lsaravia/MultifractalsInR/blob/master/Curso3.md" |
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- **Disclaimer:** This post is from the [link](https://github.com/lsaravia/MultifractalsInR/blob/master/Curso3.md) posted by GitHub user |
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[**lsaravia**](https://github.com/lsaravia) in [this comment](https://github.com/gohugoio/hugo/issues/234#issuecomment-347532166). All credits for this post |
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go to the original author. |
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|
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--- |
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{{<figure src="/images/MultifractalsInR/fractal-ice.jpg">}} |
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## Multifractals {#multifractals} |
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- Many natural systems cannot be characterized by a single number such |
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as the fractal dimension. Instead an infinite spectrum of dimensions |
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must be introduced. |
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{{<figure src="/images/MultifractalsInR/C3_Clouds.png">}} |
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## Multifractal definition {#multifractal-definition} |
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- Consider a given object \\(\Omega\\), its multifractal nature is |
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practically determined by covering the system with a set of boxes |
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\\(\{B\_i(r)\}\\) with \\((i=1,..., N(r))\\) of side lenght \\(r\\) |
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- These boxes are nonoverlaping and such that |
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\\[\Omega = \bigcup\_{i=1}^{N(r)} B\_i(r)\\] |
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This is the box-counting method but now a measure \\(\mu(B\_n)\\) for each |
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box is computed. This measure corresponds to the total population or |
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biomass contained in \\(B\_n\\), in general will scale as: |
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\\[\mu(B\_n) \propto r^\alpha\\] |
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## Box counting {#box-counting} |
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{{<figure src="/images/MultifractalsInR/C3_BoxCounting.png">}} |
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## The generalized dimensions {#the-generalized-dimensions} |
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- The fractal dimension \\(D\\) already defined is actually one of an |
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infinite spectrum of so-called correlation dimension of order \\(q\\) or |
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also called Renyi entropies. |
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\\[D\_q = \lim\_{r \to 0} \frac{1}{q-1}\frac{log \left[ \sum\_{i=1}^{N(r)}p\_i^q \right]}{\log r}\\] |
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where \\(p\_i=\mu(B\_i)\\) and a normalization is assumed: |
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\\[\sum\_{i=1}^{N(r)}p\_i=1\\] |
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- For \\(q=0\\) we have the familiar definition of fractal dimension. To see |
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this we replace \\(q=0\\) |
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\\[D\_0 = -\lim\_{r \to 0}\frac{N(r)}{\log r}\\] |
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## Generalized dimensions 1 {#generalized-dimensions-1} |
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- It can be shown that the inequality \\(D\_q' \leq D\_q\\) holds for |
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\\(q' \geq q\\) |
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- The sum |
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\\[M\_q(r) = \sum\_{i=1}^{N(r)}[\mu(B\_i(r))]^q = \sum\_{i=1}^{N(r)}p\_i^q\\] |
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is the so-called moment or partition function of order \\(q\\). |
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- Varying q allows to measure the non-homogeneity of the pattern. The |
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moments with larger \\(q\\) will be dominated by the densest boxes. For |
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\\(q<0\\) will come from small \\(p\_i\\)'s. |
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- Alternatively we can think that for \\(q>0\\), \\(D\_q\\) reflects the scaling |
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of the large fluctuations and strong singularities. In contrast, for |
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\\(q<0\\), \\(D\_q\\) reflects the scaling of the small fluctuations and weak |
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singularities. |
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## Exercise {#exercise} |
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- Calculate the partition function for the center and lower images of |
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the figure: |
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{{<figure src="/images/MultifractalsInR/C3_BoxCounting.png">}} |
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## Two important dimensions {#two-important-dimensions} |
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- Two particular cases are \\(q=1\\) and \\(q=2\\). The dimension for \\(q=1\\) is |
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the Shannon entropy or also called by ecologist the Shannon's index of |
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diversity. |
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\\[D\_1 = -\lim\_{r \to 0}\sum\_{i=1}^{N(r)} p\_i \log p\_i\\] |
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and the second is the so-called correlation dimension: |
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\\[D\_2 = -\lim\_{r \to 0} \frac{\log \left[ \sum\_{i=1}^{N(r)} p\_i^2 \right]}{\log r} \\] |
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the numerator is the log of the Simpson index. |
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## Application {#application} |
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- Salinity stress in the cladoceran Daphniopsis Australis. Behavioral |
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experiments were conducted on individual males, and their successive |
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displacements analyzed using the generalized dimension function \\(D\_q\\) |
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and the mass exponent function \\(\tau\_q\\) |
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{{<figure src="/images/MultifractalsInR/C3_Cladoceran.png">}} |
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both functions indicate that the successive displacements of male D. |
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australis have weaker multifractal properties. This is consistent with |
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and generalizes previous results showing a decrease in the complexity |
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of behavioral sequences under stressful conditions for a range of |
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organisms. |
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- A shift between multifractal and fractal properties or a change in |
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multifractal properties, in animal behavior is then suggested as a |
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potential diagnostic tool to assess animal stress levels and health. |
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## Mass exponent and Hurst exponent {#mass-exponent-and-hurst-exponent} |
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- The same information contained in the generalized dimensions can be |
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expressed using mass exponents: |
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\\[M\_q(r) \propto r^{-\tau\_q}\\] |
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This is the scaling of the partition function. For monofractals |
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\\(\tau\_q\\) is linear and related to the Hurst exponent: |
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\\[\tau\_q = q H - 1\\] |
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For multifractals we have |
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\\[\tau\_q = (q -1) D\_q\\] |
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Note that for \\(q=0\\), \\(D\_q = \tau\_q\\) and for \\(q=1\\), \\(\tau\_q=0\\) |
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## Paper {#paper} |
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1. Kellner JR, Asner GP (2009) Convergent structural responses of |
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tropical forests to diverse disturbance regimes. Ecology Letters 12: |
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887--897. <10.1111/j.1461-0248.2009.01345.x>. |
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