Bees in two-armed bandit situations: foraging choices and possible decision mechanisms

In multi-armed bandit situations, gamblers must choose repeatedlybetween options that differ in reward probability, withoutprior information on the options' relative profitability. Foragingbumblebees encounter similar situations when choosing repeatedlyamong flower species that differ in food rewards. Unlike proficientgamblers, bumblebees do not choose the highest-rewarding optionexclusively. This incomplete exclusiveness may reflect an adaptivesampling strategy. A cost—benefit analysis predicts decreasedsampling levels with increasing differences in mean profitability between the available food sources. We simulated two-armed banditsituations in laboratory experiments to test this prediction.Bumblebees (Bombus terrestris L.) made 300 foraging visitsto blue and yellow artificial flowers that dispensed sucrosesolution according to seven probabilistic reward schedules.Reward schedules varied in profitability differences between the two feeding options. As predicted, the bees specializedmore on the higher-rewarding food type (and thus sampled thealternative less) when the mean reward difference between thefeeding options was larger. Choice ratios of individual beeswere linearly related to the reward ratios they had experienced.It has been suggested that the behavioral mechanism underlying incomplete exclusiveness may involve simple rules of thumb thatdo not require long-term memory. However, the bees' responseto recent foraging experience (rewarded and non-rewarded visits)differed between the beginning and the end of observation sessionsand between treatments. Simulations of the Rescorla-Wagnerdifference learning rule reproduced the main trends of the results. These findings suggest that the observed incompleteexclusiveness results from associative learning involving long-termmemory.     

Mark Twain: how to fathom the depth of your pet proteome

The present review highlights recent progresses in the technique of combinatorial peptide ligand libraries (CPPL), a methodology that has much to offer for the detection of low- to very-low abundance proteins (nanograms/mL scale and below) in any proteome. In particular, advances in exploration of the urinary, plasma and tissue proteomes are discussed and evaluated. It is shown that when treating biological fluids, such as plasma, with CPLLs, the detection sensitivity, which in the control only reaches 10 ng/mL, can be enhanced to as high as 10 pg/mL, with an increment of sensitivity of three orders of magnitude. The possibility of using CPLLs as a two-dimensional pre-fractionation of any proteome is also evaluated: on the charge axis, CPLL capture can be implemented at no less than three different pH values (4.0, 7.2 and 9.3), thus permitting a capture of proteinaceous analytes bearing a net positive or net negative charge, respectively. When capture is performed in the absence of salts or at high levels of salts (of the Hofmeister series), one can favor the capture of hydrophilic vs. hydrophobic proteins, respectively. This would thus be a genuine 2D protocol, working on orthogonal separation principles (charge vs. hydrophobicity). As the horizon of CPLLs is expanding and its use is exponentially growing, we expect major breakthroughs in, e.g., biomarker discovery, a field that has suffered a decade of failures.     

It’s all in your head: antifungal immunity in the brain

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Getting out alive: how predators affect the decision to metamorphose

Metamorphosis has intrigued biologists for a long time as an extreme form of complex life cycles that are ubiquitous in animals. While investigated from a variety of perspectives, the ecological focus has been on identifying and understanding the ecological factors that affect an individual’s decision on when, and at what size, to metamorphose. Predation is a major factor that affects metamorphic decisions and a recent review by Benard (Annu Rev Ecol Evol Syst 35:651–673, 2004)) documented how predator cues induce metamorphic changes relative to model predictions. Importantly, however, real predators affect larval prey via several mechanisms beyond simple induction. In this paper, I contrast the leading models of metamorphosis, provide an overview of the multiple ways that predators can directly and indirectly affect larval growth and development (via induction, thinning, and selection), and identify how each process should affect the time to and size at metamorphosis. With this mechanistic foundation established, I then turn to the well-studied model system of larval amphibians to synthesize studies on: (1) caged predators (which cause only induction), and (2) lethal predators (which cause induction, thinning, and selection). Among the caged-predator studies, the chemical cues emitted by predators rarely induce a smaller size at metamorphosis or a shorter time to metamorphosis, which is in direct contrast to theoretical predictions but in agreement with Benard’s (Annu Rev Ecol Evol Syst 35:651–673, 2004) review based on a considerably smaller dataset. Among the lethal-predator studies, there is a diversity of outcomes depending upon the relative importance of induction versus thinning with the relative importance of the two processes appearing to change with larval density. Finally, I review the persistent effects of larval predators after metamorphosis including both phenotypic and fitness effects. At the end, I outline a number of future directions to allow researchers to continue gaining insight into how predators affect the metamorphic decisions of their prey. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Weathering the storm: how lodgepole pine trees survive mountain pine beetle outbreaks

Climate change leads to phenology shifts of many species. However, not all species shift in parallel, which can desynchronize interspecific interactions. Within trophic cascades, herbivores can be top–down controlled by predators or bottom–up controlled by host plant quality and host symbionts, such as plant-associated micro-organisms. Synchronization of trophic levels is required to prevent insect herbivore (pest) outbreaks. In a common garden experiment, we simulated an earlier arrival time (~2 weeks) of the aphid Rhopalosiphum padi on its host grass Lolium perenne by enhancing the aphid abundance during the colonization period. L. perenne was either uninfected or infected with the endophytic fungus Epichloë festucae var. lolii. The plant symbiotic fungus produces insect deterring alkaloids within the host grass. Throughout the season, we tested the effects of enhanced aphid abundance in spring on aphid predators (top–down) and grass–endophyte (bottom–up) responses. Higher aphid population sizes earlier in the season lead to overall higher aphid abundances, as predator occurrence was independent of aphid abundances on the pots. Nonetheless, after predator occurrence, aphids were controlled within 2 weeks on all pots. Possible bottom–up control of aphids by increased endophyte concentrations occurred time delayed after high herbivore abundances. Endophyte-derived alkaloid concentrations were not significantly affected by enhanced aphid abundance but increased throughout the season. We conclude that phenology shifts in an herbivorous species can desynchronize predator–prey and plant–microorganism interactions and might enhance the probability of pest outbreaks with climate change.     

It's all in your head: the role of quantity estimation in sperm competition

The study of animal cognition has provided valuable data throughout the years, yet its reliance on laboratory work leaves some open questions. The main question is whether animals employ cognition in daily decision-making. The following discussion uses sperm competition (SC) as a test case for demonstrating the effect of cognition on routine choices, in this case, sexual selection. Cognition is manifested here by males' ability to represent the number of rivals competing with them. I claim that response to SC is driven by quantity estimation and the ability to assess competition magnitude cognitively. Hence, cognition can determine males' response to SC, and consequentially it can be selected within this context. This supports the argument that cognition constitutes an integral part of an individual's toolbox in solving real-life problems, and shows that physical and behavioural phenomena can expose cognition to selection and facilitate its evolution.     

Craniofacial growth in a whole rat head transplant: how does a non-functional head grow?

To evaluate factors intrinsic to the regulation of craniofacial bone growth, we have developed a new experimental model in which the whole head of an infant rat is transplanted to the body of an isohistogenic rat by means of microvascular anastomosis. In our model, the transplanted head has neither scars nor any moving soft tissue that could modify growth around facial bones. Using this model, we evaluated the growth pattern of the craniofacial complex by means of serial roentgenographic cephalometrics. Ten transplantations were performed using 10-day-old rats as donors and 8-week-old rats as recipients. Cephalograms were taken from the lateral direction at 10, 20, 30, and 40 days after transplantation. Several reference points were selected to analyze the growth pattern. In the present study, we conclude that the size and form of the bony complex are mainly determined genetically. There is craniofacial skeletal growth in the absence of muscle function and brain growth. Further, both the nasal cartilage and the sutures appear to be autonomous growth centers having intrinsic growth potential. Genetic or epigenetic information plays an important role at the skeletal level, but it also affects the muscles through the medium of the muscular tonus responsible for posture and other related phenomena.     

Learning to see the wood for the trees: machine learning,decision trees,and the classification of isolated theropod teeth

Taxonomic identification of fossils based on morphometric data traditionally relies on the use of standard linear models to classify such data. Machine learning and decision trees offer powerful alternative approaches to this problem but are not widely used in palaeontology. Here, we apply these techniques to published morphometric data of isolated theropod teeth in order to explore their utility in tackling taxonomic problems. We chose two published datasets consisting of 886 teeth from 14 taxa and 3020 teeth from 17 taxa, respectively, each with five morphometric variables per tooth. We also explored the effects that missing data have on the final classification accuracy. Our results suggest that machine learning and decision trees yield superior classification results over a wide range of data permutations, with decision trees achieving accuracies of 96% in classifying test data in some cases. Missing data or attempts to generate synthetic data to overcome missing data seriously degrade all classifiers predictive accuracy. The results of our analyses also indicate that using ensemble classifiers combining different classification techniques and the examination of posterior probabilities is a useful aid in checking final class assignments. The application of such techniques to isolated theropod teeth demonstrate that simple morphometric data can be used to yield statistically robust taxonomic classifications and that lower classification accuracy is more likely to reflect preservational limitations of the data or poor application of the methods.     

Differential response of trees and shrubs to browsing and pruning: the effects on Pistacia growth and gall-inducing aphids

The effects of long term browsing on growth and morphology of P. atlantica trees and P. palaestina shrubs, and on the colonization of these hosts by their respective gall-inducing aphid guilds, were studied in natural vegetation pastures in Israel. To simulate apical dominance release by browsing, trees and shrubs were pruned and observed one year later. P. atlantica responded strongly to browsing, producing a crown of dense and sharp dry branches and thorn-like shoots, and pruning, compensating or overcompensating for the lost biomass in the studied morphological variables. Morphological responses of P. palaestina were less evident: we found no compensation in most variables. Three species of aphids produced more galls on browsed than on control shoots of P. atlantica. Two species induced more galls on pruned shoots. The five aphid species on P. palaestina colonized browsed and unbrowsed shoots equally, and produced fewer galls on pruned shoots. The role of apical dominance in architectural responses of trees and shrubs to browsing and pruning, as related to resource availability and timing, is discussed. This revised version was published online in June 2006 with corrections to the Cover Date.     

Modelling extinction risk in multispecies data sets: phylogenetically independent contrasts versus decision trees

Many recent studies of extinction risk have attempted to determine what differences exist between threatened and non-threatened species. One potential problem in such studies is that species-level data may contain phylogenetic non-independence. However, the use of phylogenetic comparative methods (PCM) to account for non-independence remains controversial, and some recent studies of extinction have recommended other methods that do not account for phylogenetic non-independence, notably decision trees (DTs). Here we perform a systematic comparison of techniques, comparing the performance of PCM regression models with corresponding non-phylogenetic regressions and DTs over different clades and response variables. We found that predictions were broadly consistent among techniques, but that predictive precision varied across techniques with PCM regression and DTs performing best. Additionally, despite their inability to account for phylogenetic non-independence, DTs were useful in highlighting interaction terms for inclusion in the PCM regression models. We discuss the implications of these findings for future comparative studies of extinction risk.     

Getting your head around Hex and Hesx1: forebrain formation in mouse

An increasing amount of evidence suggests that in mouse there are two signalling centres required for the formation of a complete neural axis: the anterior visceral endoderm (AVE), and the node and its derivatives. Embryological and genetic studies suggest that the AVE has a head-inducing activity. In contrast, the node appears to act first as a head inducer in synergy with the AVE initiating anterior neural patterning at early stages of mouse development, and later, node derivatives are necessary for maintenance and embellishment of anterior neural character. Hex and Hesx1 are homeobox genes that are expressed in relevant tissues involved in anterior patterning. The analysis of the Hex and Hesx1 mutant mice has revealed that the lack of these genes has little or no effect on the early steps of anterior neural induction. However, both genes are required subsequently for the proper expansion of the forebrain region. We suggest that disturbance in the specification of an Fgf8 signalling centre in the anterior neural ridge may account for the anterior defects observed in these mutants.     

Socioeconomic determinants of menarche in rural Polish girls using the decision trees method

The aim of this study was to assess the usefulness of the decision trees method as a research method of multidimensional associations between menarche and socioeconomic variables. The article is based on data collected from the rural area of Choszczno in the West Pomerania district of Poland between 1987 and 2001. Girls were asked about the appearance of first menstruation (a yes/no method). The average menarchal age was estimated by the probit analysis method, using second grade polynomials. The socioeconomic status of the girls' families was determined using five qualitative variables: fathers' and mothers' educational level, source of income, household appliances and the number of children in a family. For classification based on five socioeconomic variables, one of the most effective algorithms CART (Classification and Regression Trees) was used. In 2001 the menarchal age in 66% of examined girls was properly classified, while a higher efficiency of 70% was obtained for girls examined in 1987. The decision trees method enabled the definition of the hierarchy of socioeconomic variables influencing girls' biological development level. The strongest discriminatory power was attributed to the number of children in a family, and the mother's and then father's educational level. Using this method it is possible to detect differences in strength of socioeconomic variables associated with girls' pubescence before 1987 and after 2001 during the transformation of the economic and political systems in Poland. However, the decision trees method is infrequently applied in social sciences and constitutes a novelty; this article proves its usefulness in examining relations between biological processes and a population's living conditions.     

Cannot see the random forest for the decision trees: selecting predictive models for restoration ecology

Improving predictions of restoration outcomes is increasingly important to resource managers for accountability and adaptive management, yet there is limited guidance for selecting a predictive model from the multitude available. The goal of this article was to identify an optimal predictive framework for restoration ecology using 11 modeling frameworks (including machine learning, inferential, and ensemble approaches) and three data groups (field data, geographic data [GIS], and a combination thereof). We test this approach with a dataset from a large postfire sagebrush reestablishment project in the Great Basin, U.S.A. Predictive power varied among models and data groups, ranging from 58% to 79% accuracy. Finer‐scale field data generally had the greatest predictive power, although GIS data were present in the best models overall. An ensemble prediction computed from the 10 models parameterized to field data was well above average for accuracy but was outperformed by others that prioritized model parsimony by selecting predictor variables based on rankings of their importance among all candidate models. The variation in predictive power among a suite of modeling frameworks underscores the importance of a model comparison and refinement approach that evaluates multiple models and data groups, and selects variables based on their contribution to predictive power. The enhanced understanding of factors influencing restoration outcomes accomplished by this framework has the potential to aid the adaptive management process for improving future restoration outcomes.     

Involving the motor system in decision making

The control of behaviour is usually understood in terms of three distinct components: sensory processing, decision making and movement control. Recently, this view has been questioned on the basis of physiological and behavioural data, blurring the distinction between these three stages. This raises the question to what extent the motor system itself can contribute to the interpretation of behavioural situations. To investigate this question we use a neural model of sensory motor integration applied to a behaving mobile robot performing a navigation task. We show that the population response of the motor system provides a substrate for the categorization of behavioural situations. This categorization allows for the assessment of the complexity of a behavioural situation and regulates whether higher-level decision making is required to resolve behavioural conflicts. Our model lends credence to an emerging reconceptualization of behavioural control where the motor system can be considered as part of a high-level perceptual system.