The seasonal dynamics of Copidodiaptomus numidicus (Gurney, 1909) and Thermocyclops dybowskii (Lande, 1890) in Castelo-do-Bode Reservoir

We investigated the population dynamics of Copidodiaptomus numidicus (Copepoda: Calanoida) and Thermocyclops dybowskii (Copepoda: Cyclopoida) in Castelo-do-Bode Reservoir (Portugal). Both species in the reservoir were regulated mainly by food availability during the summers of 1993 and 1994. C. numidicus was always more abundant than T. dybowskii in the reservoir. C. numidicus produced two generations during the sampling period of both years whereas T. dybowskii produced two and three generations in 1993 and 1994, respectively. Because of high temperatures and low rainfall in 1994, the reservoir was more eutrophic than in 1993. Higher clutch size and a higher percentage of ovigerous females suggest that both species were benefiting from better feeding conditions in 1994. Despite this, population growth was reduced in 1994 relatively to 1993. Vertebrate predation and predation by copepods seem to have been minor factors in explaining this decline. However, the presence of Mesostoma sp. in the reservoir may have contributed to the reduction of both copepod populations during specific periods in 1994 although the calanoid was more affected than the cyclopoid by this predation.     

An Efficient Regression Type Estimator in Survey Sampling

For the estimation of population mean in simple random sampling, an efficient regression-type estimator is proposed which is more efficient than the conventional regression estimator and hence than mean per unit estimator, ratio and product estimators and many other estimators proposed by various authors. Some numerical examples are included for illustration.     

Semiparametric Regression in Size-Biased Sampling

Summary .  Size-biased sampling arises when a positive-valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size-biased outcomes. In our proposed model, the regression parameters of covariates are of major interest, while the distribution of random errors is unspecified. Under the proposed model, we discover that regression parameters are invariant regardless of size-biased sampling. Following this invariance property, we develop a simple estimation procedure for inferences. Our proposed methods are evaluated in simulation studies and applied to two real data analyses.     

Confidence Intervals for the Risk Ratio in Cohort Studies under Inverse Sampling

Three simple interval estimates for the risk ratio in inverse sampling are considered. The first two interval estimates are derived on the basis of Fieller's Theorem and the delta method with the logarithmic transformation, respectively. The third interval estimate is derived on the basis of an F-test statistic proposed by BENNETT (1981) for testing equal probabilities of a disease between two comparison groups when the disease is rare. To evaluate the performance of these three methods, a Monte Carlo simulation is used to compare the actual coverage probability with the nominal confidence level for each method and to estimate the expected length of the corresponding confidence interval in a variety of situations. On the basis of the results found in the simulation, we have concluded that the method with the logarithmic transformation is either equivalent to or better than the other two methods for all situations considered here.     

Does Mother Nature really prefer rare species or are log‐left‐skewed SADs a sampling artefact?

Intensively sampled species abundance distributions (SADs) show left‐skew on a log scale. That is, there are too many rare species to fit a lognormal distribution. I propose that this log‐left‐skew might be a sampling artefact. Monte Carlo simulations show that taking progressively larger samples from a log‐unskewed distribution (such as the lognormal) causes log‐skew to decrease asymptotically (move towards ?∞) until it reaches the level of the underlying distribution (zero in this case). In contrast, accumulating certain types of repeated small samples results in a log‐skew that becomes progressively more log‐left‐skewed to a level well beyond the underlying distribution. These repeated samples correspond to samples from the same site over many years or from many sites in 1 year. Data from empirical datasets show that log‐skew generally goes from positive (right‐skewed) to negative (left‐skewed) as the number of temporally or spatially replicated samples increases. This suggests caution when interpreting log‐left‐skew as a pattern that needs biological interpretation.     

Sampling Atriplex bladders: a comparison of methods

Abstract. A major objection to the convenient sampling of Chenopodiacean bladders by brushing in aqueous solutions is the suspected leakage of ions from the leaf blade. To overcome this problem, a new method of sampling bladder hair is described, which also achieves rapid and quantitative separation and, at the same time, yields bladder samples of undoubtedly high purity. Leakage is stopped by the aid of liquid nitrogen. Comparison of this method to removal of bladders by brushing in aquenous solutions effectively confirm the validity of the customary method beyond dispute.