Collective foraging decision in a gregarious insect

Group foraging by eusocial insects implies sophisticated recruitment processes that often result in collective decisions to exploit the most profitable sources. These advanced levels of cooperation, however, remain limited to a small range of species, and we still know little about the mechanisms underlying group foraging behaviours in the great mass of animals exhibiting lower levels of social complexity. In this paper, we report, for the first time in a gregarious insect, the cockroach Blattella germanica (L.), a collective foraging decision whereby the selection of food sources is reached without requiring active recruitment. Groups of cockroaches given a binary choice between identical food sources exhibited exploitation asymmetries whose amplitude increases with group size. By coupling behavioural observations to computer simulations, we demonstrate that selection of food sources relies uniquely on a retention effect of feeding individuals on newcomers without comparison between available opportunities. This self-organised pattern presents similarities with the foraging dynamics of eusocial species, thus stressing the generic dimension of collective decision-making mechanisms based on social amplification rules despite fundamental differences in recruitment processes. We hypothesise that such parsimony could apply to a wide range of species and help understand the emergence of collective behaviours in simple social systems.     

Cerebro-costo-mandibular syndrome in a father and a female fetus: early prenatal ultrasonographic diagnosis and autosomal dominant transmission

Ultrasonography in a female fetus revealed cystic cervical hygroma, severe micrognathia, and vertebral and upper limb anomalies suggestive of cerebro-costo-mandibular syndrome (CCMS) which was diagnosed ultrasonographically at 16 weeks' gestation. The father is affected and presents with a Pierre Robin sequence, short stature and typical costovertebral anomalies. CCMS is a rare and severe disorder. The high frequency of sporadic cases, vertical transmission, and the excess of sibs affected via horizontal transmission suggest dominant autosomal mutation with possible germinal mosaicism. The vertical familial case detailed in the present report is a reminder of the high risk when one parent or one sibling is affected and the extreme variability of phenotype and costal ossification. Early prenatal ultrasound diagnosis is possible in a severely affected fetus. Copyright © 2001 John Wiley & Sons, Ltd.     

Sampling for weed spatial distribution mapping need not be adaptive

Weeds are species of interest for ecologists because they are competitors of the crop for resources but they also play an important role in maintaining biodiversity in agroecosystems. To study their spatial distribution at the field scale, only sampled observations are available due to the cost of sampling. Weeds sampling strategies are static. However, in the domain of spatial sampling, adaptive strategies have also been developed with, for some of them, an important on-line or off-line computational cost. In this article we provide answers to the following question: Are the current adaptive sampling methods efficient enough to motivate a wider use in practice when sampling a weed species at a field scale? We provide a comparison of the behaviour of 8 static strategies and 3 adaptive ones on four criteria: density class estimation, map restoration, spatial aggregation estimation, and sampling duration. From two weeds data sets, we estimated six contrasted Markov Random Field (MRF) models of weed density class spatial distribution and a model for sampling duration. The MRF models were then used to compare the strategies on a large set of simulated maps. Our main finding was that there is no clear gain in using adaptive sampling strategies rather than static ones for the three first criteria, and adaptive strategies were associated to longer sampling duration. This conclusion points out that for weed mapping, it is more important to build a good model of spatial distribution, than to propose complex adaptive sampling strategies.     

The performance of state-of-the-art modelling techniques depends on geographical distribution of species

We explored the effects of prevalence, latitudinal range and clumping (spatial autocorrelation) of species distribution patterns on the predictive accuracy of eight state-of-the-art modelling techniques: Generalized Linear Models (GLMs), Generalized Boosting Method (GBM), Generalized Additive Models (GAMs), Classification Tree Analysis (CTA), Artificial Neural Network (ANN), Multivariate Adaptive Regression Splines (MARS), Mixture Discriminant Analysis (MDA) and Random Forest (RF). One hundred species of Lepidoptera, selected from the Distribution Atlas of European Butterflies, and three climate variables were used to determine the bioclimatic envelope for each butterfly species. The data set consisting of 2620 grid squares 30′ × 60′ in size all over Europe was randomly split into the calibration and the evaluation data sets. The performance of different models was assessed using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Observed differences in modelling accuracy among species were then related to the geographical attributes of the species using GAM. The modelling performance was negatively related to the latitudinal range and prevalence, whereas the effect of spatial autocorrelation on prediction accuracy depended on the modelling technique. These three geographical attributes accounted for 19–61% of the variation in the modelling accuracy. Predictive accuracy of GAM, GLM and MDA was highly influenced by the three geographical attributes, whereas RF, ANN and GBM were moderately, and MARS and CTA only slightly affected. The contrasting effects of geographical distribution of species on predictive performance of different modelling techniques represent one source of uncertainty in species spatial distribution models. This should be taken into account in biogeographical modelling studies and assessments of climate change impacts.     

A framework for testing meso‐mediational relationships in Organizational Behavior

We advance a framework for testing mediational relationships that traverse levels of analysis. We differentiate mediation that functions within levels, as well as different forms of meso‐mediation that operate downward across levels of analysis. We discuss the preconditions and evidential basis for these meso‐mediational type relationships. We then provide an empirical example that illustrates the different types of mediation and conclude with recommendations and extensions for studying more complex meso‐mediational organizational phenomena. Copyright © 2007 John Wiley & Sons, Ltd.     

How floral odours are learned inside the bumblebee (Bombus terrestris) nest

Recruitment in social insects often involves not only inducing nestmates to leave the nest, but also communicating crucial information about finding profitable food sources. Although bumblebees transmit chemosensory information (floral scent), the transmission mechanism is unknown as mouth-to-mouth fluid transfer (as in honeybees) does not occur. Because recruiting bumblebees release a pheromone in the nest that triggers foraging in previously inactive workers, we tested whether this pheromone helps workers learn currently rewarding floral odours, as found in food social learning in rats. We exposed colonies to artificial recruitment pheromone, paired with anise scent. The pheromone did not facilitate learning of floral scent. However, we found that releasing floral scent in the air of the colony was sufficient to trigger learning and that learning performance was improved when the chemosensory cue was provided in the nectar in honeypots; probably because it guarantees a tighter link between scent and reward, and possibly because gustatory cues are involved in addition to olfaction. Scent learning was maximal when anise-scented nectar was brought into the nest by demonstrator foragers, suggesting that previously unidentified cues provided by successful foragers play an important role in nestmates learning new floral odours.