Colony expansion model for describing the spatial distribution of populations

Population Ecology

Volumn 42, Issue 2, 2000, Pages 161-169

  Yamamura, K ^a  

^a NATIONAL INSTITUTE FOR AGRO ENVIRONMENTAL SCIENCES   (Japan)

Author keywords

Iwao's m m regression; Kono Sugino relation; Taylor's power law

Indexed keywords

COLONIZATION; POPULATION DYNAMICS; POPULATION ECOLOGY; SPATIAL DISTRIBUTION;

EID: 0034484970     PISSN: 14383896     EISSN: None     Source Type: Journal    
DOI: 10.1007/PL00011995     Document Type: Article

References (57)

1. Variability in the abundance of animal and plant species
2. The statistical analysis of insect counts based on the negative binomial distribution
3. Robustness in empirically based binomial decision rules for integrated pest management
4. Statistical problems in estimating populations of Japanese beetle larvae
5. Fitting the negative binomial distribution to biological data
6. Negative binomial distribution with a common k
7. Aggregation of plant parasitic nematodes and Taylor's power law
8. Incidence counts for estimating densities of Rhopalosiphum padi (Homoptera: Aphididae)
9. Spatial distribution and sampling plans for four species of cereal aphids (Homoptera: Aphididae) infesting spring wheat in southwestern Idaho
10. Binomial sampling plans for the English grain aphid, Sitobion avenae (Homoptera: Aphididae) based on an empirical relationship between mean density and proportion of tillers with different tally thresholds of aphids
11. Density estimation of corn rootworm egg populations based upon frequency of occurrence
12. On fixed precision level sequential sampling
13. Cross-correlation in population dynamics and the slope of spatial variance-mean regressions
14. The importance of non-linearity: A comment on the view of Taylor
15. A new regression method for analyzing the aggregation pattern of animal populations
16. A new method of sequential sampling to classify populations relative to a critical density
17. Relation of frequency index to population density and distribution pattern
18. Use of the regression of mean crowding on mean density for estimating sample size and the transformation of data for the analysis of variance
19. An approach to the analysis of aggregation pattern in biological populations
20. Families of discrete distributions satisfying Taylor's power law
21. A probabilistic model for the variance to mean power law in ecology
22. On the estimation of the density of rice stems infested by the rice stem borer
23. A new method of sequential sampling to obtain the population estimates with a fixed level of precision
24. Multi-stage sampling for population estimation
25. Evaluation of statistical precision and design of efficient sampling for the population estimation based on frequency of occurrence
26. Sampling and analysis of insect populations
27. Taylor's power law and the measurement of variation in the size of population in space and time
28. Case studies in binary dispersion
29. Mean crowding
30. Information and area-wide control in agricultural ecology
31. Distribution, abundance, and sampling of fall armyworm (Lepidoptera: Noctuidae) in South-central Louisiana cornfields
32. Estimates of mean population density and spatial distribution of Tetranychus urticae (Acarina: Tetranychidae) and Phytoseiulus persimilis (Acarina: Phytoseiidae) based upon the proportion of empty sampling units
33. Binomial sequential classification sampling plans for European red mite (Acari: Tetranychidae) with special reference to performance criteria
34. Taylor's power law for dependence of variance on mean in animal populations
35. Some models for spatial variability of animal species
36. Chaotic dynamics can generate Taylor's power law
37. Fitting Taylor's power law
38. Taylor's power law re-examined
39. Estimating potato tuberworm (Lepidoptera: Gelechiidae) damage in stored potatoes in Tunisia
40. Introduction to sampling theory
41. Simulation studies of binomial sampling: A new variance estimator and density predictor, with special reference to the Russian wheat aphid (Homoptera: Aphididae)
42. Detecting differences in arthropod aggregation by comparing the proportion of occupied sample units
43. Patterns of variations in the numbers of animal populations and the biological foundations of Taylor's law of the mean
44. Aggregation, variance and the mean
45. Assessing and interpreting the spatial distribution of insect populations
46. Aggregation, migration and population mechanics
47. The density-dependence of spatial behaviour and the rarity of randomness
48. Variance and the large scale spatial stability of aphids, moths and birds
49. Behavioural dynamics
50. Clumping patterns of fruit and arthropods in cotton, with implications for binomial sampling
51. Sampling scale dependence of Taylor's power law
52. Optimality in the spatial leaf distribution of the weed Portulaca oleracea L.