Estimating acridid densities in grassland habitats: a comparison between presence-absence and abundance sampling designs

Sampling methods to estimate acridid density per surface area unit in grassland habitats were compared using presence-absence data and count data. Sampling plans based on 6 yr of surveys were devised to estimate the density of Chorthippus spp., Euchorthippus spp., and Calliptamus italicus L. These acridids represented >90% of species in the study area. Sampling plans based on count data provided a reasonable tool when densities were >1/m(2) and when the level of precision was 0.20-0.30. A binomial sampling plan can be used to estimate C. italicus density with a level of precision >or=0.28. Sampling characteristics, i.e., estimated mean, actual precision, and sample size, were established on validation data sets with bootstrapping analysis. Sampling costs were also calculated according to density-dependent functions. Comparison between binomial sampling and enumerative sampling of C. italicus showed that binomial sampling required less time than enumerative sampling when densities were <or=2/m(2) and when fixed precision was >0.35. Plot area had no significant effect on sample variances of counts.

Species interactions can explain Taylor's power law for ecological time series

One of the few generalities in ecology, Taylor's power law, describes the species-specific relationship between the temporal or spatial variance of populations and their mean abundances. For populations experiencing constant per capita environmental variability, the regression of log variance versus log mean abundance gives a line with a slope of 2. Despite this expectation, most species have slopes of less than 2 (refs 2, 3-4), indicating that more abundant populations of a species are relatively less variable than expected on the basis of simple statistical grounds. What causes abundant populations to be less variable has received considerable attention, but an explanation for the generality of this pattern is still lacking. Here we suggest a novel explanation for the scaling of temporal variability in population abundances. Using stochastic simulation and analytical models, we demonstrate how negative interactions among species in a community can produce slopes of Taylor's power law of less than 2, like those observed in real data sets. This result provides an example in which the population dynamics of single species can be understood only in the context of interactions within an ecological community.

Spatial and temporal distribution of Anopheles gambiae s.l. (Diptera: Culicidae) in two Tanzanian villages: implication for designing mosquito sampling routines

This paper describes the spatial and temporal distribution of Anopheles gambiae s.l. Giles in two Tanzanian villages based on data collected from a five-month intensive mosquito sampling programme and analysed using Taylor's power law. The degree of spatial aggregation of female A. gambiae in each village was similar to its corresponding temporal aggregation, indicating that in designing sampling routines for estimating the abundance of mosquitoes, sampling effort should be allocated equally to houses (spatial) and nights (temporal). The analysis also showed that for a given amount of sampling effort, estimates of village-level mosquito abundance are more precise when sampling is carried out in randomly selected houses, than when the same houses are used on each sampling occasion. Also, the precision of estimating parous rates does not depend on whether mosquito sampling is carried out in the same or a random selection of houses. The implications of these findings for designing sampling routines for entomological evaluation of vector control trials are discussed.

Scaling in the growth of geographically subdivided populations: invariant patterns from a continent-wide biological survey

We consider statistical patterns of variation in growth rates for over 400 species of breeding birds across North America surveyed from 1966 to 1998. We report two results. First, the standard deviation of population growth rates decays as a power-law function of total population size with an exponent beta = 0.36 +/- 0.02. Second, the number of subpopulations, measured as the number of survey locations with non-zero counts, scales to the 3/4 power of total number of birds counted in a given species. We show how these patterns may be related, and discuss a simple stochastic growth model for a geographically subdivided population that formalizes the relationship. We also examine reasons that may explain why some species deviate from these scaling laws.

The temporal variability of animal abundances: measures, methods and patterns

From first principles, the temporal variability of a time series of abundances can be defined as the average deviation of values from a mean value on a proportional scale. In this paper we review: (i) the different kinds of temporal variability; (ii) the different ways in which it can be measured; (iii) the design of appropriate sampling schemes; (iv) methods of analysing variability; and (v) patterns in temporal variability. We emphasize that some commonly applied measures are not appropriate, that several do not measure the desired feature of time series, and the importance of considerations of trend and sampling error. A number of suggestions are made for the improvement of the basis for comparative analyses of levels of variability, and some of the potential pitfalls are identified. Given the serious faults in many previous analyses of ecological patterns in the temporal variability of animal abundances, emphasis is laid on the theoretical basis for different patterns, and hence a set of hypotheses for testing is generated.

Density dependence, regulation and variability in animal populations

This paper reviews a series of approaches to the study of density dependence, regulation and variability in terrestrial animals, by using single-species, multispecies and life table time series data. Special emphasis is given to the degree of density dependence in the level of variability, which is seldom discussed in this context, but which is conceptually related to population regulation. Broad patterns in density dependence, regulation and variability in vertebrates and arthropods are described, with some more specific results for moths and aphids. Vertebrates have generally less variable populations than arthropods, which is the only well documented, consistent pattern in population variability. The degree of density dependence of variability is negatively correlated with the average level of variability, suggesting that generally the more regulated populations are less variable. Most population studies, especially on insects, have involved outbreak species with complex dynamics, which may explain the common failures to detect density dependence in natural populations. In British moths, density dependence is less obvious in the more abundant species. The study of uncommon and rare species remains a major challenge for population ecology.