In fall, Myzus persicae (Sulzer) (Homoptera: Aphididae) may exhibit population resurgence in winter oilseed rape in France. This resurgence may arise from pyrethroid treatments against Coleoptera ( Psylliodes chrysocephala L.) that either kill parasitoids present during treatment or prevent recolonization by off-crop parasitoids. We studied the impact of Diaeretiella rapae (M’Intosh) (Hymenoptera: Braconidae) on populations of M. persicae when parasitoids were introduced on deltamethrin-treated plants at increasing intervals after treatment. Parasitoids were introduced 1, 2, 7, or 14 d posttreatment on individually caged plants infested with established populations of M. persicae . Aphids were counted 7, 14 and 21 d after parasitoid introduction. First, we observed that both the pesticide and the parasitoid reduced aphid population growth and that their effects were additive. Second, there was no mortality of parasitoids exposed to treated leaves in a device with a refuge area, and only 20% of mortality without the refuge area. Furthermore, deltamethrin residues had no effect on the reproduction of D. rapae females. Compared with the known toxicity of deltamethrin to D. rapae on glass, this low mortality may have been due to both the high liposolubility of deltamethrin (leading to a rapid diffusion of residues in the oilseed rape leaf cuticle) and to the existence of a refuge area. This work suggests that D. rapae could limit populations of M. persicae in the fall, even after pyrethroid treatment, because the presence of deltamethrin residues had little impact on the parasitoid.

In recent years, considerable research interest in behavioral ecology has focused on characterizing and understanding individual differences in behavior that are consistent over time and across contexts, termed animal “personalities,” and correlations between various behaviors across contexts, termed behavioral syndromes. Although there is some evidence that differences in personality among individuals within populations can be genetically based and adaptive, when and how individual personality differences emerge in a population is not well understood, but of considerable general interest. Here, using juveniles of the convict cichlid ( Amatitlania siquia ) as a model system, we investigated in the laboratory whether individuals consistently differ in their personalities and whether behavioral syndromes are apparent at an early developmental stage and, if so, whether distinct personality traits are heritable. Under standardized laboratory conditions and using sibling analysis, we quantified interindividual differences in their boldness behavior under potential predation threat and their exploratory activity in a novel environment, 2 ecologically important behaviors, as our focal personality traits and estimated their respective repeatability and heritability. We report for the first time consistent (repeatable) and heritable individual differences in boldness and exploratory behaviors, and a boldness–exploration behavioral syndrome, in young convict cichlids. Bolder fish were more exploratory than relatively timid ones. These results provide novel evidence for the emergence in early life history of consistent individual differences in personality traits and behavioral syndromes in this species and suggest that genetic variation for boldness and exploratory behaviors, and thus potential for selection on these traits, exists in our study population.

9 pagesInternational audienceDiscriminant function analysis (DFA) based on morphological measurements is a quick, inexpensive, and efficient method for sex determination in field studies on cryptically monomorphic bird species. However, behind the apparent standardization and relative simplicity of DFA lie subtle differences and pitfalls that have been neglected in some studies. Most of these concerns directly affect assessment of the discriminant performance, a parameter of crucial importance in practice because it provides a measure of the quality of an equation that may be used in later field studies. Using results from 141 published studies and simulations based on a large data set collected on adult Zenaida Doves (Zenaida aurita), we assessed the effects of sexual dimorphism, sample size, and validation methods on discrimination rates. We compared the three most common methods used to estimate the proportion of correctly classified males and females by DFA: resubstitution, jackknife, or sample splitting. Results from simulations indicate that these procedures may lead to opposite conclusions, especially when the sample size is small. In particular, the resubstitution techniques appear to be overoptimistic, and we therefore recommend that DFA accuracy be estimated by the jackknife cross-validation procedure. In addition, we show that most previous studies failed to present DFA accuracy with 95% confidence intervals, which hampers comparisons among studies. Finally, our results suggest that large sample sizes should be preferred over repeated measurements of the same individuals, because random measurement error is likely to have only a weak effect on the accuracy of the discriminant rate

Many animals nest or roost colonially. At the start of a potential foraging period, they may set out independently or await information from returning foragers. When should such individuals act independently and when should they wait for information? In a social insect colony, for example, information transfer may greatly increase a recruit's probability of finding food, and it is commonly assumed that this will always increase the colony's net energy gain. We test this assumption with a mathematical model. Energy gain by a colony is a function both of the probability of finding food sources and of the duration of their availability. A key factor is the ratio of pro-active foragers to re-active foragers. When leaving the nest, pro-active foragers search for food independently, whereas re-active foragers rely on information from successful foragers to find food. Under certain conditions, the optimum strategy is totally independent (pro-active) foraging because potentially valuable information that re-active foragers may gain from successful foragers is not worth waiting for. This counter-intuitive outcome is remarkably robust over a wide range of parameters. It occurs because food sources are only available for a limited period. Our study emphasizes the importance of time constraints and the analysis of dynamics, not just steady states, to understand social insect foraging.

In a previous article, we advocated against using the sum of Akaike weights (SW) as a metric to distinguish between genuine and spurious variables in Information Theoretic (IT) statistical analyses. A recent article (Giam & Olden, Methods in Ecology and Evolution, 2016, 7, 388) criticises our finding and instead argues in favour of SW. It points out that (1) we performed a biased data‐generation procedure and (2) we erroneously evaluated SW on its capacity to estimate the proportion of variance in the data explained by a variable. We here respond to these points. Giam and Olden's first concern is unfounded. When using the data‐generating code they proposed, SW remains very imprecise. To respond to their second concern, we first list the meanings taken by a variable's importance in the context of IT. Although, SW is presented as an estimate of variable relative importance in methodological textbooks (i.e. a variable's rank in importance or its relative contribution to the variance in the data), it is also used as a metric of variable absolute importance (i.e. a variable's absolute effect size or its statistical significance). We then compare SW to alternative metrics on its ability to estimate variable absolute or relative importance. SW values have low repeatability across analyses. As a result, based on SW, it is hard to distinguish between variables with weak and large effects. For estimations of variable absolute importance, experimenters should prefer model‐averaged parameter estimates and/or compare nested models based on evidence ratios. Sum of Akaike weights is also a poor metric of variable relative importance. We showed that correct variable ranking in importance was generally more frequent when using model‐averaged standardised parameter estimates, than when using SW. To avoid recurrent errors in ecology and evolution, we therefore warn against the use of SW for estimations of variable absolute and relative importance and we propose that experimenters should instead use model‐averaged standardised parameter estimates for statistical inferences.