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A randomization procedure is proposed which allows statistical tests to be combined into a single test to maintain specified and acceptable levels of false detection. This method was applied to the problem of detecting density dependence in 135 unpublished time-series (of ≥10 generations) from insect populations, and to simulated density-dependent and density-independent data, so that the correctness of observed levels of detection from the published data could be verified. To allow the application of the randomization procedure to Bulmer's (1975) tests and Varley and Gradwell's (1960) test, these were recast as randomization tests. The randomization procedure was tested with 39 combinations of tests for density dependence (and limitation/attraction); it generally producedcombined tests with levels of detection that were intermediate between detection levels of the constituent tests (and hence was limite by these). The specified rate of false detection (5%) was never exceeded (by more than 1%) when combined tests were applied to time-series from a random-walk model. Two different combinations of tests produced levels of detection from the published time-series which were slightly greater than their constituent tests when they were combined into single tests. These were the randomized form of Bulmer's (1975) first test with the tests of Pollard et al. (1987) and Reddingius and den Boer (1989) with the randomized form of Bulmer's second test. The combination of Bulmer's first and Pollard et al.'s test produced a greater level of detection (21.5%) than any other single test or combination of tests. These results were confirmed by the analysis of modelled density dependent data. Although the increase in power of combinations of tests over single tests is small with the data we used, the combined tests (listed above) had rates of detection that were less influenced by the form of data (of two forms of density-dependent data) than were their constituent tests. Hence, it appears that the combined tests are of greater generality than single test statistics. The method presented here for combining several statistical tests into a single randomization test is applicable in many other areas of ecology where we wish to apply several tests and take the most probable result of these; and if the tests being conducted are, or can be expressed as, randomization tests.

By analogy with deterministic stability, the stability of stochastic ecological systems can be viewed as a tendency for population densities to avoid dynamic boundaries (i.e. boundedness) or to approach a dynamic attractor (i.e. attraction). At the population level, these two views generate predictions consistent with density dependence. I therefore devised two new statistical tests of attraction, the “random-walk attraction test” and the “randomized attraction test”; I then used them successfully, along with randomization techniques that detect boundedness and two autocorrelation methods, to test for density dependence in published sequences of population densities. The attraction tests identify the apparent attractor, the band of densities toward which density tends to shift between generations. Locating the apparent attractor can generate a prediction of the next direction of density change; for data from a dragonfly assemblage, about 80% of these predictions were correct. From the single-population tests, I also developed two multispecies tests of attraction (the multispecies random-walk and randomized attraction tests) and two multispecies tests of boundedness (the multispecies permutation and randomization tests). These detected attraction and boundedness in the dragonfly assemblage and attraction in a collection of laboratory fruitfly populations. An evaluation of the statistical power of the new density attraction tests indicates a strong dependence on the sequence length n and on the number of populations m: power increases with n and particularly with m. Nevertheless, detecting attraction becomes likely even in populations with strong linear density-dependence only with n>30 or for shorter sequences in multispecies assemblages.

Using 12 years of monthly sweep-net data from 9-12 permanent sampling stations, we evaluated the variability and stability of the dragonfly assemblage in Bays Mountain Lake (northeastern Tennessee, USA). To do this, we adopted the view that a stable assemblage (i.e. one capable of recovering quickly from disturbances) should have low variability (i.e. high persistence of taxa, relatively constant densities, and high rank concordance), except with disturbances more intense and frequent than those in this system. Moreover, a stable assemblage should contain populations that exhibit density dependence and should tend to remain within a restricted range of densities (boundedness), shifting toward a narrow density interval between generations (attraction). To test some specific predictions derived from these views, we analyzed 12-year sequences of larval population sizes just before the onset of emergence for the 13 dominant dragonfly taxa in the lake. Most but not all of the 13 dominant taxa persisted during the 12-year period. Variabilities of taxon densities, measured as standard deviations across generations of log-transformed population sizes, were representative of the broad range for other invertebrates but somewhat higher than those of terrestrial vertebrates. There were fewer than three significant abundance trends over the 12-year period, and rank concordance between generations was high (W=0.716). Density dependence was detected among some of the dragonfly density sequences by five different methods. Using techniques presented in the companion paper, we found strong indications of both boundedness and attraction in the whole assemblage. We conclude tentatively that an assemblage consisting of at least 11 of the 13 dominant dragonfly taxa at Bays Mountain Lake has low-to-moderate variability and is stable, but that the complete 29-species assemblage is probably not stable at the scale of this single lake. We emphasize the need for coupling such long-term descriptive analyses with studies of responses to experimental disturbances.

In seed plants, the proximate causes of spatial segregation of the sexes (SSS) and its association with environmental variation are thought to be linked to sex-specific morphological and physiological variation. To address the general question of linkage among SSS, plant traits and environmental gradients, Marchantia inflexa was used, for which male plants are found under more open tree canopy than females. We hypothesized that males are adapted to higher light intensity and are better able to tolerate water stress than females, as is the case with seed plants. We tested for sex-specific habitat and trait relationships by quantifying plant traits (morphological and physiological) and estimates of the light conditions (percent canopy openness and light intensity) in the field. Using path analysis, we found that edge pore density in both sexes was negatively correlated with canopy openness, while in males, edge pore density had a weak but positive relationship to light intensity. These responses suggest that canopy openness and light intensity have opposing effects on edge pore density in males and that males might be more responsive to water stress than females. Additionally, the greater importance of female support tissue, which functions as storage, in explaining and being explained by other variables in the path analysis, relative to male support tissue, may reflect sex-specific allocation differences related to resources needed for female function.

This study focuses on ways that the size distribution of individuals influences the types and intensities of competitive interactions within a population of aquatic arthropod predators. Three field experiments and one laboratory experiment were designed to test for feeding interference, interference mortality, and dispersal effects within and between larval size classes of the primarily semivoltine dragonfly Tetragoneuria cynosura in Bays Mountain Lake. One field experiment documented the temporal pattern of colonization of large-mesh cylinders by the small, first-year-class larvae during a 30-day period; the results are consistent with passive (density-independent) colonization. A second field experiment examined the effect of large, second-year-class larvae at densities of 1 or 3 per cylinder (14 or 42 m-2) on colonization by small larvae; this colonization was inhibited at the high density of large larvae. In the laboratory experiment, when larvae of the two size-classes were together in the same aquarium, small larvae moved around less than when by themselves (dispersal inhibition). Thus the inhibition of colonization observed in the field may result from interference mortality, rather than from a flight response to the presence of larger conspecifics.

Ecosystems distributed in space have an effective size, reflecting both their absolute size (extent) and their fine-scale physical structure (viscosity). In this paper, a general mathematical model of a predator-prey interaction is presented via the phase-plane graphs of Rosenzweig and MacArthur (1963) to show one reason why ecosystems of larger effective size should persist longer than smaller ones: oscillations of population densities tend to be displaced farther from extinction thresholds—even in spatially homogeneous systems. Experimental results obtained by Gause and Luckinbill with protozoa and Huffaker with mites are interpreted in this context.