Semiochemical and physical stimuli involved in host recognition by Telenomus podisi (Hymenoptera: Scelionidae) toward Euschistus heros (Heteroptera: Pentatomidae)

The egg parasitoid, Telenomus podisi, was shown to recognize its host, Euschistus heros, through both chemical and physical cues. These were determined in short-range bioassays. The cues comprised fertile and infertile host eggs, egg extracts, crude extracts of adult males and females and successive dilutions of the synthetic racemic mixture of methyl 2,6,10-trimethyltridecanoate, a male-produced pheromone of E. heros. Some of the treatments used induced a selection process in T. podisi, through host recognition behaviour, indicating a consistent response of this species to E. heros. The possibility that some of these compounds could be exploited as long-range kairomones, by T. podisi, is discussed. Using GC analysis, an unidentified compound (Rt 24.8 min), possibly from the egg adhesive material, was detected from E. heros egg extracts. Its retention time compared to the methyl 2,6,10-trimethyltridecanoate showed a lower volatility, suggesting that the egg adhesive may act as a short-range kairomone. Physical cues appeared to be an important component in the host selection process by T. podisi. The parasitoid discriminated infertile eggs which are differently shaped and smaller than fertile eggs.     

Time allocation of the parasitoidAphidius colemani (Hymenoptera: Aphidiidae) foraging forAphis gossypii (Homoptera: Aphidae) on cucumber leaves

The time allocation of individualAphidius colemani female parasitoids foraging forAphis gossypii nymphs on cucumber leaves has been investigated. Apart from experiences on the current leaf (such as density of hosts on the current leaf, density of hosts on a neighboring leaf and encounters with hosts on the current leaf), the effect of previous leaf visits on the time allocation was studied. Behavioral records were analyzed by means of the proportional hazards model, to determine the tendency of leaving the current leaf. The leaving tendency decreased only on leaves with a high host density (100 aphids), thus increasing the giving up time since the latest encounter. Rejection of aphids had no influence on the leaving tendency. To assess the effect of the number of hosts encountered on the leaving tendency, we considered three classes: 0–30 encounters, 31–100 encounters, and 100 or more encounters with hosts. The effect of the number of hosts encountered differed at different aphid densities. When fewer than 10 aphids were present the leaving tendency was much greater after 30 encounters than beforehand. At a density of 100 aphids the leaving tendency was lower than at the other aphid densities and increased only after 100 encounters. The density of hosts on a neighboring leaf, ranging from 0 to 100 hosts, had a negligible effect on the leaving tendency. Repeated visits to leaves with 10 unparasitized aphids resulted in an increase in the leaving tendency after 10 visits. It is argued that the parasitoids have some innate expectancy of host availability and that they concentrate on high-density patches.     

Time matching between grooming partners: Do methodological distinctions between short versus long‐term reciprocation matter?

Primatologists have long focused on grooming exchanges to examine aspects of social relationships, co‐operation, and social cognition. One particular interest is the extent to which reciprocating grooming partners time match, and the time frame over which they do so. Conclusions about time matching vary across species. Generally, researchers focus on the duration of pauses between grooming episodes that involve a switch in partner roles and choose a cut‐off point to distinguish short from longer‐term reciprocation. Problematically, researchers have made inconsistent choices about cut‐offs. Such methodological variations are potentially concerning, as it is unclear whether inconsistent conclusions about short‐term time matching are attributable to species/ecological differences, or are due in part to methodological inconsistency. We ask whether various criteria for separating short versus long‐term reciprocation influence conclusions about short‐term time matching using data from free‐ranging rhesus ( Macaca mulatta) and captive‐crested macaques ( Macaca nigra). We compare several commonly used cut‐offs to ones generated by the currently preferred approach—survival analysis. Crested macaques displayed a mild degree of time matching regardless of the cutoff used. For rhesus macaques, whereas most cut‐offs yielded similar degrees of time matching as the one derived from survival analysis, very short ones significantly underestimated both the degree of time matching and the influence of rank distance on time matching. Although researchers may have some flexibility in their choice of cut‐offs, we suggest that they employ caution by using survival analysis when possible, and when not possible, by avoiding very short time windows.     

Comparison of methods for analysis of selective genotyping survival data

Survival traits and selective genotyping datasets are typically not normally distributed, thus common models used to identify QTL may not be statistically appropriate for their analysis. The objective of the present study was to compare models for identification of QTL associated with survival traits, in particular when combined with selective genotyping. Data were simulated to model the survival distribution of a population of chickens challenged with Marek disease virus. Cox proportional hazards (CPH), linear regression (LR), and Weibull models were compared for their appropriateness to analyze the data, ability to identify associations of marker alleles with survival, and estimation of effects when all individuals were genotyped (full genotyping) and when selective genotyping was used. Little difference in power was found between the CPH and the LR model for low censoring cases for both full and selective genotyping. The simulated data were not transformed to follow a Weibull distribution and, as a result, the Weibull model generally resulted in less power than the other two models and overestimated effects. Effect estimates from LR and CPH were unbiased when all individuals were genotyped, but overestimated when selective genotyping was used. Thus, LR is preferred for analyzing survival data when the amount of censoring is low because of ease of implementation and interpretation. Including phenotypic data of non-genotyped individuals in selective genotyping analysis increased power, but resulted in LR having an inflated false positive rate, and therefore the CPH model is preferred for this scenario, although transformation of the data may also make the Weibull model appropriate for this case. The results from the research presented herein are directly applicable to interval mapping analyses.