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 130
... example , for the cricket data given above ( with Σ r2 = 136.78 ) : x2 = 2 ( 3.14159 ) ( 0.08621 ) ( 136.78 ) ... example at a = .05 we have two decision rules : 1. If observed x2 is less than x295 ( 59.0 in this example ) we have evidence ...
... example , for the cricket data given above ( with Σ r2 = 136.78 ) : x2 = 2 ( 3.14159 ) ( 0.08621 ) ( 136.78 ) ... example at a = .05 we have two decision rules : 1. If observed x2 is less than x295 ( 59.0 in this example ) we have evidence ...
Page 203
... example , the total number of Solidago individuals in the entire 100 - ha study field . 2. Mean = x , for example , the average number of Solidago per m2 . 3. Ratio of two totals = R = x / y ; for example , the number of Solidago per ...
... example , the total number of Solidago individuals in the entire 100 - ha study field . 2. Mean = x , for example , the average number of Solidago per m2 . 3. Ratio of two totals = R = x / y ; for example , the number of Solidago per ...
Page 238
... example , the number of pink bollworms per cotton plant may be counted , and after each plant is counted a decision can be made whether the population is dense ( i.e. , spray pesticide ) or sparse ( do not spray ) . If you do not sample ...
... example , the number of pink bollworms per cotton plant may be counted , and after each plant is counted a decision can be made whether the population is dense ( i.e. , spray pesticide ) or sparse ( do not spray ) . If you do not sample ...
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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