Ecological MethodologyEcological Methodology, Second Edition provides a balance of material on animal and plant populations, and teaches students of ecology how to design efficient tests in order to obtain maximum precision with minimal work. |
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Page 150
... Morisita's Index of Dispersion Morisita ( 1962 ) developed an index of dispersion that has some of the desirable attributes of an index : Id = n Σ x2 - ( Σ x ) - Σ x Σχ ( 4.26 ) where Id = Morisita's index of dispersion n = Sample size ...
... Morisita's Index of Dispersion Morisita ( 1962 ) developed an index of dispersion that has some of the desirable attributes of an index : Id = n Σ x2 - ( Σ x ) - Σ x Σχ ( 4.26 ) where Id = Morisita's index of dispersion n = Sample size ...
Page 151
Charles J. Krebs. 1. Calculate the Morisita index of dispersion using equation ( 4.26 ) . 2. Calculate the two significance points for the Morisita index from the following formulas : 2 x2975 - n + Σ xi Uniform index = Mu = ( Σ x ) - 1 ...
Charles J. Krebs. 1. Calculate the Morisita index of dispersion using equation ( 4.26 ) . 2. Calculate the two significance points for the Morisita index from the following formulas : 2 x2975 - n + Σ xi Uniform index = Mu = ( Σ x ) - 1 ...
Page 306
... Morisita's index . ( From Wolda , 1981. ) λι = - Σ " [ X1j ( Xij − 1 ) ] Nj ( N , - 1 ) λ2 = Σ " [ Xik ( Xik - 1 ) ] Nk ( Nk - 1 ) ( 9.12 ) ( 9.13 ) The Morisita index is most easily interpreted as a probability : * one } Probability ...
... Morisita's index . ( From Wolda , 1981. ) λι = - Σ " [ X1j ( Xij − 1 ) ] Nj ( N , - 1 ) λ2 = Σ " [ Xik ( Xik - 1 ) ] Nk ( Nk - 1 ) ( 9.12 ) ( 9.13 ) The Morisita index is most easily interpreted as a probability : * one } Probability ...
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abundance aphids Appendix assumptions bias calculations capture Caughley census zone Chapter chi-square clumped coefficient of variation confidence interval confidence limits defined density estimate distance ecological ecologists END-OF-FILE Enter equal catchability equation estimate of population estimate population example Figure finite population FORMAT 2X formula frequency distribution index of dispersion line transect mark-recapture marked animals method n₁ nearest neighbor negative binomial distribution niche breadth niche overlap normal distribution null hypothesis Number of animals Number of individuals number of quadrats number of samples number of species observed obtained parameters Petersen plot Poisson distribution population density population estimate problem Program proportion quadrat counts random points random sampling ratio READ recaptures regression sample size sample sizes sampling unit Schnabel Seber second sample simple random sampling spatial pattern standard error statistical statistical population stratum study area survival rate Table techniques Total number transformation variable variance