scholarly journals Spatial distribution and sampling of Corythucha ciliata (Hemiptera: Tingidae) in London plane trees

2019 ◽  
Vol 24 (1) ◽  
pp. 43-52
Author(s):  
He-Ping Wei ◽  
Feng Wang ◽  
Rui-Ting Ju
Keyword(s):  
Spatial Distribution ◽  
Distribution Pattern ◽  
Power Law ◽  
Distribution Data ◽  
Taylor’S Power Law ◽  
Control Threshold ◽  
Dispersion Patterns ◽  
Plane Trees ◽  
Taylor's Power Law ◽  
London Plane

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.

SAMPLING PLANS FOR ESTIMATING ACHENE DAMAGE BY THE RED SUNFLOWER SEED WEEVIL (COLEOPTERA: CURCULIONIDAE)

1995 ◽  
Vol 127 (1) ◽  
pp. 7-14 ◽  
Author(s):  
Chengwang Peng ◽  
Gary J. Brewer
Keyword(s):  
Sample Size ◽  
Distribution Pattern ◽  
Power Law ◽  
Sunflower Seed ◽  
Management Strategies ◽  
Economic Injury Level ◽  
Taylor’S Power Law ◽  
Precision Level ◽  
Taylor's Power Law ◽  
The Mean

AbstractA sampling plan for the estimation of the number of achenes damaged by the red sunflower seed weevil, Smicronyx fulvus LeConte, is useful in evaluating the efficiency of weevil management strategies. The objective of this study was to determine the distribution pattern of the damaged achenes that would allow the development of a fixed-sample-size plan for estimation of the damaged achenes. Taylor’s power law and Iwao’s patchiness regression were used to analyze the distribution pattern of the damaged achenes. Slopes from both models were >1, indicating an aggregated spatial pattern. The intercepts and slopes from both models were used to calculate the minimal mean number of damaged achenes per sunflower head that can be estimated for a given sample size and precision level. If the mean number of damaged achenes per head is low (<20), the plan developed using the parameters of Taylor’s power law requires significantly more samples than the plan using the parameters of Iwao’s patchiness regression to estimate the same density of damaged achenes. If the mean number of damaged achenes per head is high (>30), the two plans give similar results. If both low and high damage situations are considered, Taylor’s plan is preferred to Iwao’s plan. At the 0.10 precision level, Taylor’s plan requires approximately 40 samples (heads) to estimate a mean of about 200 damaged achenes per head (≈ current economic injury level).

SPATIAL DISTRIBUTION AND SAMPLING PLANS WITH FIXED LEVELS OF PRECISION FOR CEREAL APHIDS (HOMOPTERA: APHIDIDAE) INFESTING SPRING WHEAT

1998 ◽  
Vol 130 (1) ◽  
pp. 67-77 ◽  
Author(s):  
Philip J. Boeve ◽  
Michael Weiss
Keyword(s):  
Spatial Distribution ◽  
Power Law ◽  
Spring Wheat ◽  
Rhopalosiphum Padi ◽  
Aphid Population ◽  
Management Decision ◽  
Cereal Aphids ◽  
Sampling Plans ◽  
Taylor’S Power Law ◽  
Taylor's Power Law

AbstractThree cereal aphids, Rhopalosiphum padi (L.), Schizaphis graminum (Rondani), and Sitobion avenae (F.), invade wheat fields in the northern Great Plains each spring, and populations occasionally reach economic levels. The first objective of this study was to describe the spatial distribution of three species of cereal aphids infesting hard red spring wheat (Triticum aestivum L.). The second objective was to develop two sampling plans for cereal aphids using individual stems as the sampling unit, a sampling plan with fixed levels of precision and a sequential sampling decision plan based on total numbers of aphids present. Aphid population estimates were collected from 47 eastern North Dakota spring wheat fields during 1993–1995. The number of aphids per stem were counted on 100–350 stems per field. Taylor’s power law and Iwao’s patchiness regression were used to analyze the spatial distribution of the aphids. Rhopalosiphum padi and S. avenae exhibited an aggregated distribution, whereas S. graminum was distributed randomly in the field. Taylor’s power law provided a better fit to the data than Iwao’s patchiness regression. Sample size requirements for precision levels of 0.10, 0.15, and 0.25 were estimated with Taylor’s regression coefficients. Required sample sizes increased with decreased aphid populations and increased levels of precision. The two sampling plans presented should be useful for research on cereal aphid population dynamics and pest management decision making in spring wheat.

Variation and Consistency in Spatial Distribution as Measured by Taylor's Power Law

1998 ◽  
Vol 27 (2) ◽  
pp. 191-201 ◽  
Author(s):  
R.A.J. Taylor ◽  
R. K. Lindquist ◽  
J. L. Shipp
Keyword(s):  
Spatial Distribution ◽  
Power Law ◽  
Taylor’S Power Law ◽  
Taylor's Power Law

Distribution pattern of benthic invertebrates in Danish estuaries: The use of Taylor's power law as a species-specific indicator of dispersion and behavior

2013 ◽  
Vol 77 ◽  
pp. 70-78 ◽  
Author(s):  
Erik Kristensen ◽  
Matthieu Delefosse ◽  
Cintia O. Quintana ◽  
Gary T. Banta ◽  
Hans Christian Petersen ◽  
...  
Keyword(s):  
Distribution Pattern ◽  
Power Law ◽  
Benthic Invertebrates ◽  
Taylor’S Power Law ◽  
Taylor's Power Law ◽  
Species Specific ◽  
And Behavior

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
Keyword(s):  
Power Law ◽  
Distribution Data ◽  
Specific Factor ◽  
Observation Window ◽  
Quadrat Size ◽  
Taylor’S Power Law ◽  
Urban Service ◽  
Taylor's Power Law ◽  
Taylor’S Law ◽  
Function Relationship

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).

Nematode spatial distribution and the frequency of zeros in samples

Nematology ◽  
2017 ◽  
Vol 19 (3) ◽  
pp. 263-270 ◽  
Author(s):  
Robin A.J. Taylor ◽  
Sun-Jeong Park ◽  
Parwinder S. Grewal
Keyword(s):  
Spatial Distribution ◽  
Life History ◽  
Longitudinal Study ◽  
Density Dependence ◽  
Power Law ◽  
Life History Strategy ◽  
Taylor’S Power Law ◽  
Rare Taxa ◽  
Large Samples ◽  
Taylor's Power Law

In the first longitudinal study of nematode spatial distribution with sufficiently large samples to estimate Taylor’s power law (TPL), we concluded that TPL is sensitive to life history strategy. We also observed that the value of TPL slope b was generally higher for more widespread and abundant taxa. We deduce that removal of empty samples increases b and discuss the results in relation to known causes of bias in estimating TPL. Only one cause might explain an increase in b with removal of empty quadrats: the underestimation of variance. Although bias cannot be ruled out in rare taxa, the consistency of the pattern with very abundant genera suggests a different explanation. TPL appears sensitive to the number of samples in a survey that do not contain the taxon of interest. We conclude that TPL measures the space between individuals as well as the density-dependence of the numerical distribution of abundance.

Spatial Distribution of Scale Insects: Comparative Study Using Taylor's Power Law

1995 ◽  
Vol 24 (3) ◽  
pp. 506-512 ◽  
Author(s):  
David Nestel ◽  
Hadass Cohen ◽  
Nitza Saphir ◽  
Michal Klein ◽  
Zvi Mendel
Keyword(s):  
Spatial Distribution ◽  
Comparative Study ◽  
Power Law ◽  
Scale Insects ◽  
Taylor’S Power Law ◽  
Taylor's Power Law
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