scholarly journals Taylor’s power law and its decomposition in urban facilities

2019 ◽  
Vol 6 (3) ◽  
pp. 180770 ◽  
Author(s):  
Liang Wu ◽  
Chi Gong ◽  
Xin Yan

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 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 complementary services (e.g. restaurants).

2019 ◽  
Vol 24 (1) ◽  
pp. 43-52
Author(s):  
He-Ping Wei ◽  
Feng Wang ◽  
Rui-Ting Ju

Taylor’s power law and Iwao’s patchiness regression were used to describe the dispersion patterns for overwintering and wandering stages of Corythucha ciliata on the London plane trees, Platanus x acerifolia (Ait.) Willd. Both Taylor’s and Iwao’s tests fit the distribution data for the overwintering stage. The overwintering adults were spatially aggregated. In the wandering stage, Taylor’s power law consistently fit the data, whereas the fit of Iwao’s patchiness regression was erratic. Both Iwao’s and Taylor’s indices indicated a clumped distribution pattern for eggs, nymphs, and wandering adults. Trunk was identified as the best sampling target for the overwintering stage whereas twig was the best for the wandering stage. In order to determine the sample size for evaluating whether the population has reached the control threshold, the sampling of 35 and 7 trunks for the overwintering stage and 32 and 8 twigs per tree for the wandering stage would provide 0.5- and 0.25-precision levels, respectively.


Oikos ◽  
1992 ◽  
Vol 65 (3) ◽  
pp. 538 ◽  
Author(s):  
Joe N. Perry ◽  
Ian P. Woiwod

2019 ◽  
Vol 19 ◽  
pp. e00657 ◽  
Author(s):  
Peijian Shi ◽  
Lei Zhao ◽  
David A. Ratkowsky ◽  
Karl J. Niklas ◽  
Weiwei Huang ◽  
...  

1988 ◽  
Vol 28 (2) ◽  
pp. 279 ◽  
Author(s):  
PG Allsopp ◽  
S Iwao ◽  
LR Taylor

Counts of adults of mixed populations of Nysius vinitor Bergroth and N. clevelandensis Evans on preflowering and postflowering sunflowers did not conform to the Poisson distribution because of overdispersion. Preflowering samples did not conform to the negative binomial model, but postflowering samples did with a common k of 3.78. Both sets of samples fitted significantly (P<0.01) Iwao's patchiness regression and Taylor's power law, but with significantly (P<0.01) different intercepts and slopes, respectively. Relationships to determine sample sizes for fixed levels of precision and fixed-precision-level stop lines are developed for both stages of crop development using Taylor's power law. Sequential decision plans based on Iwao's regression are developed for use in the management of Nysius spp. on preflowering and postflowering sunflowers.


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