scholarly journals Spatial distribution, sampling efficiency and Taylor's power law. 2. Interpreting density‐dependent sampling efficiency

2020 ◽  
Author(s):  
R. A. J. Taylor
Keyword(s):  
Spatial Distribution ◽  
Power Law ◽  
Sampling Efficiency ◽  
Taylor’S Power Law ◽  
Density Dependent ◽  
Taylor's Power Law

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.

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.

Temporal and spatial patterns in pheromone-trap catches of Helicoverpa spp. (Lepidoptera: Noctuidae) in cotton-growing areas of Australia

1989 ◽  
Vol 79 (1) ◽  
pp. 145-161 ◽  
Author(s):  
G. P. Fitt ◽  
M. P. Zalucki ◽  
P. Twine
Keyword(s):  
Power Law ◽  
Pheromone Trap ◽  
Environmental Stochasticity ◽  
Spatial And Temporal Variation ◽  
Small Scale ◽  
Taylor’S Power Law ◽  
Density Dependent ◽  
Taylor's Power Law ◽  
Trap Catches ◽  
The Relationship

AbstractHelicoverpa armigera (Hübner) and H. punctigera (Wallengren) are major pests of cotton and other field crops in Australia. Using data on then abundance of males in pheromone traps at many sites over three seasons, the spatial and temporal variation in trap catch of both species were examined using Taylor's power law and spatial autocorrelation. The distribution of both species was highly clumped, both temporally and spatially. Regression Coefficients for the relationship of spatial mean to variance (bs) were similar to those for noctuids in general, while similarly derived temporal values (bt) for H. armigera fell towards the upper end of the noctuid range and those for H. punctigera well above the range given by Taylor & Woiwood (1980). Taylor and colleagues suggested that patterns of dispersion are species-specific and that they reflect density-dependent patterns of movement towards and away from centres of abundance. Although the relationship between variance and mean abundance for both spatial and temporal aspects of trap catches of Helicoverpa is well fitted by Taylor's power law, it is argued that these patterns of dispersion are a consequence of demographic and environmental stochasticity. Little need is to invoke specific density-dependent behaviours as the major factor responsible in this case. In addition, while Taylor's power law indicated both species had a similar clumped distribution, limited autocorrelation analysis suggested a random dispersion of pheromone-trap catches for H. armigera and small scale patchiness (over distances of 1–2 km) in trap catches of H. punctigera.

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

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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