Ecological interactions in Aedes species on Reunion Island

Two invasive, container‐breeding mosquito species, Aedes aegypti (Stegomyia aegypti) and Aedes albopictus (Stegomyia albopicta) (Diptera: Culicidae), have different distribution patterns on Reunion Island. Aedes albopictus occurs in all areas and Ae. aegypti colonizes only some restricted areas already occupied by Ae. albopictus. This study investigates the abiotic and biotic ecological mechanisms that determine the distribution of Aedes species on Reunion Island. Life history traits (duration of immature stages, survivorship, fecundity, estimated finite rate of increase) in Ae. aegypti and Ae. albopictus were compared at different temperatures. These fitness measures were characterized in both species in response to competitive interactions among larvae. Aedes aegypti was drastically affected by temperature, performing well only at around 25 °C, at which it achieved its highest survivorship and greatest estimated rate of increase. The narrow distribution of this species in the field on Reunion Island may thus relate to its poor ability to cope with unfavourable temperatures. Aedes aegypti was also more negatively affected by high population densities and to some extent by interactions with Ae. albopictus, particularly in the context of limited food supplies. Aedes albopictus exhibited better population performance across a range of environmental conditions. Its ecological plasticity and its superior competitive ability relative to its congener may further enhance its invasion success on Reunion Island.     

Non‐pollinating cheater wasps benefit from seasonally poor performance of the mutualistic pollinating wasps at the northern limit of the range of Ficus microcarpa

1. Species interactions in tightly bound ecological mutualisms often feature highly specialised species' roles in which competitive exclusion may preclude multi‐species coexistence. Among the 800 fig (Ficus) species, it was originally considered that each was pollinated by their own wasp (Agaonidae). However, recent investigations show that this ‘one‐to‐one’ rule often breaks down, as fig species regularly host multiple agaonids but in ways suggesting that competitive processes still mediate biodiversity outcomes. 2. A phenological survey was conducted of the fig–fig wasp pair, Ficus microcarpa and its associated pollinating wasp, alongside its sister species, the cheating wasp, in Xishuangbanna, China. 3. Reproductive output underwent extreme seasonal variation. Seed and pollinator production fell markedly during cooler, drier months, although high levels of fig production continued. However, this resource was predominantly utilised by the cheater species, which offers no pollination services. Pollinators and cheaters rarely co‐occur, suggesting that temporal coexistence is constrained by competition for access to figs. 4. The overall findings indicate periodic rearrangements of mutualism dynamics, probably resulting from a strongly seasonal environment. Sympatric co‐occurrence may result from a window of opportunity for a functionally divergent agaonid, potentially due to constraints on the main pollinator in adapting to variable year‐round conditions that prevent competitive exclusion.     

Starvation and the Mating Success of Wild Male Mediterranean Fruit Flies (Diptera: Tephritidae)

Recent evidence suggests that the nutritional state of male Mediterranean fruit flies, Ceratitis capitata (Wied.) (medfly), is an important influence on various components of their reproductive biology, including mating success. The objective of the present study was to examine experimentally the effect of temporary starvation on the mating success of wild male C. capitata. Males were maintained on protein–sugar or sugar-only diets, and for each diet we compared the mating success of continuously fed males versus males starved for 18 or 24 h immediately before testing. In trials conducted on field-caged, host trees, males starved for 24 h obtained only about half as many matings as fed males for both diets. However, when the starvation period was 18 h, starved males reared on the protein–sugar diet mated significantly less frequently than fed males, whereas starved males reared on sugar mated as often as fed males. Measurements of male pheromone calling and female attraction revealed that reduced mating success likely reflected the decreased signaling activity of starved males.     

Social status and reproductive success of male Macaca fascicularis

Dominant males of nonseasonally breeding species should have more opportunity than seasonal breeders to monopolize access to estrous females and thus enhance their reproductive success. They may also use other strategies for maximizing reproductive success such as producing offspring by relatively high ranking females. To test these hypotheses, the paternity of 35 (80%) of 44 Macaca fascicularis offspring, born over a 28-month period, was established using electrophoretically and serologically defined genetic markers. The social ranks of each of the seven potential fathers and 26 potential mothers were determined by recording outcomes of dyadio agonistic interactions. No evidence could be found to support either hypothesis. Further, in view of previously reported significant, positive correlations between male social rank and sexual activity rates in this study group, sexual activity rates do not appear to predict the number of offspring a male sires in this species.     

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.