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6 results for “Taylor's Law”
High-frequency light attenuation measurements in 35 lakes: companion data from "Coefficients in Taylor’s Law increase with the time scale of water clarity measurements in a global suite of lakes"
Identifying the scaling rules describing ecological patterns across time and space is a central challenge in ecology. Taylor’s Law of fluctuation scaling, which states that the variance of a population is proportional to a positive power of the mean, has been widely observed in population dynamics and characterizes variability in multiple scientific domains. However, it is unclear if this phenomenon accurately describes ecological patterns across many orders of magnitude in time, and therefore links otherwise disparate observations. This dataset uses light attenuation observations from 10,531 days of high-frequency measurements in 35 globally distributed lakes to test this unknown. We focus on water clarity as an integrative ecological characteristic that responds to both biotic and abiotic drivers. We provide documentation that variations in ecological measurements across diverse sites and temporal scales exhibit variance patterns consistent with Taylor’s Law, and that model coefficients increase in a predictable yet non-linear manner with decreasing observation frequency.
Dataset 'Yeast facilitates the multiplication of Drosophila bacterial symbionts but has no effect on the form or parameters of Taylor's law'
<p>Dataset from the manuscript 'Yeast facilitates the multiplication of <em>Drosophila </em>bacterial symbionts but has no effect on the form or parameters of Taylor’s law' (2020)</p> <p>Each line corresponds to a single experimental unit.</p>
Data from: Biological and statistical processes jointly drive population aggregation: using host–parasite interactions to understand Taylor's power law
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Data from: Taylor's Power Law and its decomposition in urban facilities
As one of the few generalities in ecology, Taylor's power law admits a power function relationship $V=aM^{b}$ between the variance $V$ and mean number $M$ of organisms in a quadrat. We examine the spatial distribution data of seven urban service facilities in 37 major cities in China, and find that Taylor's law is validated among all types of facilities. Moreover, Taylor's law is robust if we shift the observation window or vary the size of the quadrats. The exponent $b$ increases linearly with the logarithm of the quadrat size, i.e., $b(s) = b_0 + A\log(s)$. Furthermore, the ANOVA test indicates that $b$ takes distinct values for different facilities in different cities. We decompose $b$ into two different factors, a city-specific factor (CSF) and a facility-specific factor (FSF). variations in $b$ can be explained to a large extent by the differences between cities and types of facilities. Facilities are more evenly distributed in larger and more developed cities. Competitive interchangeable facilities (e.g. pharmacy), with larger FSFs and smaller $b$s, are less aggregated than complimentary services (e.g., restaurants).
Data from: Taylor's Power Law and its decomposition in urban facilities
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Data from: A process-independent explanation for the general form of Taylor’s Law
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