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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Oecologia 86 (1991), S. 484-491 
    ISSN: 1432-1939
    Keywords: Regulation ; Random walk ; Density dependence ; Survival time ; Fluctuation pattern ; Log-Range
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary It is often claimed that the fluctuation of numbers in field populations is fundamentally different from random walks of densities, in that population size is kept between certain positive limits. To test this hypothesis patterns of fluctuation in field populations were compared with random walks of density of about the same duration. It was found that the boundaries (Log-Range) between which numbers fluctuate in field populations increase with time to about the same extent as in comparable random walks of density. Moreover, deviations of the trend of numbers over years (Average lnR) from zero trend in populations of 62 (carabid) species were just those expected for simulated random walk runs, with the median value of Var(lnR), and different values for mean population size that cover the possible range of “survival times” for these species. This means that the null hypothesis that in the field numbers would fluctuate as random walks of densities could not be rejected. Although it is not very probable that field populations fluctuate exactly like random walks of densities, random walk models appear to mimic the fluctuation patterns of field populations sufficiently closely to explain what happens in nature, and to deny the need for regulation. The same conclusion was drawn in earlier studies where statistical tests were applied to fluctuation patterns of field populations (Den Boer and Reddingius 1989; Den Boer 1990a). Random walks of densities do not exclude the possibility that local populations can persist for some centuries.
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Oecologia 79 (1989), S. 143-149 
    ISSN: 1432-1939
    Keywords: Density dependence ; Census data ; Trends ; Regulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary When testing for regulation of population numbers, rather than using Bulmer's second test in cases where population numbers are estimated instead of measured, we prefer to correct Bulmer's first test for estimation error. A correction method is expounded, discussed, and applied to two series of census data: the pine looper of Klomp and the garden chafer of Milne. In neither case the tentative conclusion from using the uncorrected test was changed after correction. Therefore, in practice Bulmer's first test without correction can be used well as a first orientation. Twelve long series (more than 10 years) of census data of both univoltine and semelparous (a necessary condition) insects were tested for significant density dependence in the fluctuations of numbers with the randomization test of Pollard et al. None of the series, all we could find to meet the necessary condition as well as being longer than 10 years, showed significant density dependence at the 0.05 level, though the pine looper of Klomp did so at the 0.1 level. Next, the same series were tested for regulation in the sense of “keeping density within limits” with both the first test of Bulmer and the permutation test of Reddingius and Den Boer. Onky Klomp's pine looper population at “Hoge Veluwe” scored significantly. In a following paper this population will be considered more closely, in order to enable understanding of this test result.
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Oecologia 75 (1988), S. 161-168 
    ISSN: 1432-1939
    Keywords: Winter moth ; Density dependence ; Regulation ; Limits of density ; Key-factor
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary Latto and Hassell (1987) disagree with the conclusion of Den Boer (1986), that the winter moth population at Wytham Wood, studied by Varley and Gradwell, was not regulated. They attempt to demonstrate regulation by means of a simulation model. In the present paper the validity of this model is tested step by step. The fixing of the initial and final densities, as practised by Den Boer and rejected by Latto and Hassell, did not prevent population explosions and extinctions, as was assumed by Latto and Hassell. It is shown that the deterministic formulation of the density dependence of pupal predation, as used by Latto and Hassell, deviates systematically from the field data. Replacing the values of the key-factor (k1) by random values drawn from a normal distribution (Latto and Hassell) affects the dynamics such that the ability of pupal predation to govern density is improved in the model. Changing mortalities other than the key-factor does not significantly influence the pattern of fluctuations nor the limits of density. Models should leave intact the essentials of the reality under study, while removing distracting elements (Levins 1968). As both the timing of the key-factor, and its correlation with pupal predation are essential features of the winter moth population at Wytham Wood between 1950 and 1968, the model of Latto and Hassell does not apply to this population. By simply changing log10 (eggs/female) it is shown that the power of the density dependence of pupal predation to govern possible trends in density of the winter moth population at Wytham Wood is weak. On the other hand, the model of Latto and Hassell gives insight into the conditions that might favour regulation of numbers. Although the model of Poethke and Kirchberg (1987) preserves more features of the pertinent winter moth population than that of Latto and Hassell (1987) it still deviates in one essential aspect: the succession in time of both the (coupled) mortalities and the deviations from the deterministic density dependence are taken at random. Therefore, also this model is still too far from the field population to be a sound base for the statistical speculation proposed by Poethke and Kirchberg.
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Oecologia 78 (1989), S. 1-8 
    ISSN: 1432-1939
    Keywords: Density dependence ; Regulation ; Stabilization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary It is tried to remove some misunderstandings about the “regulation” of animal numbers by density-dependent processes. Staying between limits is called “stabilization”, and only when this results from density-dependent processes it is considered “regulation”. We discuss two tests that may be used to detect the existence of regulation: the parametric tests of Bulmer and a nonparametric “permutation” test. The powers of these tests are compared. The first test of Bulmer and the permutation test do not differ very much in power, but the second test of Bulmer has hardly any power and therefore cannot be used in cases where densities were only estimated. The arguments from which Bulmer's second test is derived are critically discussed and found not to be very convincing. We propose, rather than using Bulmer's second test, to correct the test statistic of his first test for estimation error, and present a possible solution for this. In a following paper this method will be applied to some long series of population counts of univoltine insects, for, a basic assumption of all regulation-tests is, that the sequence of population counts is a realization of a piece of first-order Markov chain. This highly restricts the usefulness of regulation-tests. Some other recent attempts to construct such tests are discussed within the present context
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Oecologia 83 (1990), S. 38-46 
    ISSN: 1432-1939
    Keywords: Density dependence ; Regulation ; Closed populations ; Stabilization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary When testing census data of insect populations for regulation, and/or for overall density dependence in the course of numbers over years, certain conditions, which follow from the testing models, should be fulfilled. Even if the series of densities may be considered a piece of first-order Markov chain (a necessary condition) significant test results need not obviously point to regulation of numbers by dominant density-dependent processes. Such a case is presented by the pine looper population at “Hoge Veluwe” studied by Klomp. A drastic drop in density from 1952 to 1953, which takes 78–97% of the log-density range (LR) over all years, most probably wrongly causes significant test results. This is supported by some simulation experiments. Moreover, we cannot be sure that the population was sufficiently isolated, i.e. that dispersal of adults from surrounding populations did not importantly influence population numbers. Among 6 Panolis-populations studied by Schwerdtfeger during 17 years a single one scored significantly with all tests. This resulted, however, from such a drastic drop in density that it covered the entire log-density range (LR=9.39), which therefore is wider than in any of the other (non-significant) populations. Another Panolis-population that maintained itself during 60 years, and which also scored significantly, most probably was kept within limits by supplementation of very low densities with immigrants, on the one hand, and by restriction of high densities by defoliation caused by other species, on the other. It is discussed whether this can be considered “regulation”, or results from spreading of risk. It is concluded that the range stability of particular populations must be considered generally to be the result of stabilization by both internal and external processes among which both density-dependent and density-independent processes play a significant part, and from which the contribution of the density-dependent processes need not be separated. The most interesting aspect of the stabilization of animal numbers is its relationship with the expected survival time of the population.
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