Sightseeing Around the Single Cosinor

Misuses of the single cosinor analysis are numerous. We give three rules of thumb, providing guidelines as to whether results obtained from this analysis are dubious. This short note avoids mathematical development so as to be comprehensible to the nonspecialist. However, a few endnotes, give some technical comments.     

A comparison of three sampling techniques to estimate the population size of caterpillars in trees

Three sampling techniques commonly used to estimate the population size of caterpillars and sawfly larvae in trees (branch samples, frass production, water basins), were compared with respect to sampling error and economic costs. At the level of tree populations (e.g. forests), on an arbitrary date, the mean caterpillar intensity per tree (expressed in numbers of larvae or their biomass per 100 shoots) was predicted from the mean frass production per tree (expressed in mg frass per m² forest floor per day). At the level of the single tree, the frass production on an arbitrary date was related to the population intensity, but, due to the large sampling error, did not provide an accurate prediction. Summing the frass produced over the whole season reduced this error and predicted the seasonal abundance of larvae in single trees, estimated as their maximum intensity or their density (numbers of larvae or their biomass per m² forest floor). The maximum population intensity was not related to the population density. The sampling techniques suffer from large errors unrelated to larval abundance. The main sources of error (i.e. weather or predation of the larvae) usually cause an underestimation of population size. Labour, the main cause of high costs, was low in the basin technique and high in the frass production technique. Possible ways of reducing errors and applications of the three techniques are discussed.     

Primary production of four dominant salt-marsh angiosperms in the SW Netherlands

Results of a one-year evaluation of aboveground production of four dominant salt-marsh angiosperms show a distinctly higher level of production as compared with reported results for similar studies of salt-marsh vegetations in The Netherlands.Net aboveground production estimates based on production of both living and dead matter varied considerably depending on how the data were computed: Spartina anglica: 1162 to 1649 g m² yr¹; Triglochin maritima: 568 to 783 g m² yr¹; Halimione portulacoides: 790 to 1434 g m² yr¹; Elytrigía pungens: 474 to 878 g m² yr¹. Aboveground production estimates, using a paired plot method, are also strongly dependent on the computation of the data and ranged for Spartina anglica from 2139 to 2659 g m² yr¹ and for Elytrigia pungens from 1416 to 1787 g m² yr¹. Evaluation of the results of the production estimates suggested that the actual aboveground production is best approached using a paired plot method.Nomenclature follows Heukels-van Ooststroom (1977), Flora van Nederland, 19th ed. Wolters-Noordhoff, Groningen.Thanks are due to Dr P. Ketner (Wageningen) for his valuable comments and to Dr A. G. Vlasblom (Yerseke) for providing statistical advice.Communication No. 252.     

An Improved Class of Estimators for Finite Population Mean in Sample Surveys

This paper proposes a class of estimators for estimating the finite population mean -Y of a study variate y using information on two auxiliary variates, one of which is positively and the other negatively correlated with the study variate y. An “asymptotically optimum estimator” (AOE) in the class is identified with its bias and mean square error formulae. It is observed that the proposed AOE is more efficient than Srivastava (1965), Srivastava (1974), Prasad (1989) and Gandge , Varghese , and Prabhu-Ajgaonkar (1993) estimators.     

Living krill, zooplankton and experimental investigations: a discourse on the role of krill and their experimental study in marine ecology

Krill occupy critical positions in a many marine ecosystems and have been the subject of a number of concerted studies yet there are large areas of their biology that still remain a mystery. Most species of krill are open ocean animals, which makes direct observation and sampling difficult. Krill also exhibit a number of physiological and behavioural attributes which frustrate attempts to understand their life history. Krill are conceptually difficult to come to terms with; they are obviously different from larger marine organisms such as squid, fish, whales and fish yet they are also quite distinct from those animals classed as zooplankton such as copepods. Despite these differences they have most often been grouped with zooplankton and have been studied using techniques developed for animals which are orders of magnitude smaller than they. This mismatch has affected our view of their interactions with the physical world and also affects their perceived trophic interactions. Their size and mobility also interferes with our ability to sample them effectively and thus to develop our appreciation of their true role in the marine ecosystem. Understanding how intermediate-sized animals, such as krill, function in aquatic ecosystem is critical to better management of the marine environment.     

Ecological time-series analysis through structural modelling with latent constructs: concepts, methods and applications

Time-series analyses in ecology usually involve the use of autoregressive modelling through direct and/or delayed difference equations, which severely restricts the ability of the modeler to structure complex causal relationships within a multivariate frame. This is especially problematic in the field of population regulation, where the proximate and ultimate causes of fluctuations in population size have been hotly debated for decades. Here it is shown that this debate can benefit from the implementation of structural modelling with latent constructs (SEM) to time-series analysis in ecology. A nonparametric bootstrap scheme illustrates how this modelling approach can circumvent some problems posed by the climate-ecology interface. Stochastic Monte Carlo simulation is further used to assess the effects of increasing time-series length and different parameter estimation methods on the performance of several model fit indexes. Throughout, the advantages and limitations of the SEM method are highlighted.     

Sampling frequencies and measurement error for linear and temporal gait parameters in primate locomotion

Quantitative analyses of animal motion are increasingly easy to conduct using simple video equipment and relatively inexpensive software packages. With careful use, such analytical tools have the potential to quantify differences in movement between individuals or species and to allow insights into the behavioral consequences of morphological differences between taxa. However, as with any other type of measurement, there are errors associated with kinematic measurements. Because normative kinematic data on human and nonhuman primate locomotion are used to model aspects of gait of fossil hominins, errors in the extant data influence the accuracy of fossil gait reconstructions. The principal goal of this paper is to illustrate the effect of camera speeds (frame rates) on kinematic measurement errors, and to demonstrate how these errors vary with subject size, movement velocity, and sample size. Kinematic data for human walking and running (240 Hz), as well as data for primate quadrupedal walking and running (180 Hz) were used as inputs for a simulation of the measurement errors associated with various linear and temporal kinematic variables. Measurement errors were shown to increase as camera speed, subject body size, and interval duration all decrease, and as movement velocity increases. These results have implications for the methods used to calculate subject velocity and suggest that using a moving marker to measure the linear displacements of the body is preferable to the use of a stationary marker. Finally, while slower camera speeds will always result in higher measurement errors than do faster camera speeds, this effect can be moderated to some extent by collecting sufficiently large samples of data.     

Pitfall trapping for ants (Hymenoptera,Formicidae) in mesic Australia: the influence of trap diameter

Catches of ants in the two most commonly-used forms of pitfall trap (‘test-tube’ traps, ca 18 mm diameter; ‘coffee cup’ traps, ca. 70 mm diameter) are compared from samples in open grassy woodland in southern Victoria, Australia. The 25 morphospecies found in the narrower traps were all represented among the 31 morphospecies collected in the larger traps. Either pattern is adequate to collect samples for broad inter-treatment comparisons and documentation of the more typical and representative fauna, but larger traps may have some advantage if more complete inventory is sought.     

Is a biology of rarity in primates yet possible?

If we lack data on the biology of rare species, then understanding of the biology of rarity will be incomplete at best, biased at worst. However, the extent of potential under-study is mostly unknown. We therefore ask for primates, one of the better known orders of mammals, whether data are lacking on rare species. The measure used is published data on a crucial aspect of biology, namely density. Rare species are here defined as those with both geographic range sizes and habitat breadths less than the median for primates; common species are at or above the median for those two measures. Globally, nearly half, 47%, of the 32 rare species lack data on their density, compared to only 10% of the 83 common species (²corr. = 17.1, p < 0.001). Within realms, Asia and Madagascar show a particularly strong bias, missing density data for over 50% of their rare species. Thus, rare species are indeed severely under-studied compared to common species, even in this well-studied mammalian taxon.