69 research outputs found

    Adaptation of flower and fruit colours to multiple, distinct 1 mutualists

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    Communication in plant–animal mutualisms frequently involves multiple perceivers. A fundamental uncertainty is whether and how species adapt to communicate with groups of mutualists having distinct sensory abilities. We quantified the colour conspicuousness of flowers and fruits originating from one European and two South American plant communities, using visual models of pollinators (bee and fly) and seed dispersers (bird, primate and marten). We show that flowers are more conspicuous than fruits to pollinators, and the reverse to seed dispersers. In addition, flowers are more conspicuous to pollinators than to seed dispersers and the reverse for fruits. Thus, despite marked differences in the visual systems of mutualists, flower and fruit colours have evolved to attract multiple, distinct mutualists but not unintended perceivers. We show that this adaptation is facilitated by a limited correlation between flower and fruit colours, and by the fact that colour signals as coded at the photoreceptor level are more similar within than between functional groups (pollinators and seed dispersers). Overall, these results provide the first quantitative demonstration that flower and fruit colours are adaptations allowing plants to communicate simultaneously with distinct groups of mutualists.Peer reviewe

    A Bayesian framework for emergent constraints: case studies of climate sensitivity with PMIP

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    In this paper we introduce a Bayesian framework, which is explicit about prior assumptions, for using model ensembles and observations together to constrain future climate change. The emergent constraint approach has seen broad application in recent years, including studies constraining the equilibrium climate sensitivity (ECS) using the Last Glacial Maximum (LGM) and the mid-Pliocene Warm Period (mPWP). Most of these studies were based on ordinary least squares (OLS) fits between a variable of the climate state, such as tropical temperature, and climate sensitivity. Using our Bayesian method, and considering the LGM and mPWP separately, we obtain values of ECS of 2.7 K (0.6–5.2, 5th–95th percentiles) using the PMIP2, PMIP3, and PMIP4 datasets for the LGM and 2.3 K (0.5–4.4) with the PlioMIP1 and PlioMIP2 datasets for the mPWP. Restricting the ensembles to include only the most recent version of each model, we obtain 2.7 K (0.7–5.2) using the LGM and 2.3 K (0.4–4.5) using the mPWP. An advantage of the Bayesian framework is that it is possible to combine the two periods assuming they are independent, whereby we obtain a tighter constraint of 2.5 K (0.8–4.0) using the restricted ensemble. We have explored the sensitivity to our assumptions in the method, including considering structural uncertainty, and in the choice of models, and this leads to 95 % probability of climate sensitivity mostly below 5 K and only exceeding 6 K in a single and most uncertain case assuming a large structural uncertainty. The approach is compared with other approaches based on OLS, a Kalman filter method, and an alternative Bayesian method. An interesting implication of this work is that OLS-based emergent constraints on ECS generate tighter uncertainty estimates, in particular at the lower end, an artefact due to a flatter regression line in the case of lack of correlation. Although some fundamental challenges related to the use of emergent constraints remain, this paper provides a step towards a better foundation for their potential use in future probabilistic estimations of climate sensitivity

    A network linking scene perception and spatial memory systems in posterior cerebral cortex

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    The neural systems supporting scene-perception and spatial-memory systems of the human brain are well-described. But how do these neural systems interact? Here, using fine-grained individual-subject fMRI, we report three cortical areas of the human brain, each lying immediately anterior to a region of the scene perception network in posterior cerebral cortex, that selectively activate when recalling familiar real-world locations. Despite their close proximity to the scene-perception areas, network analyses show that these regions constitute a distinct functional network that interfaces with spatial memory systems during naturalistic scene understanding. These “place-memory areas” offer a new framework for understanding how the brain implements memory-guided visual behaviors, including navigation

    On the Functional Significance of the P1 and N1 Effects to Illusory Figures in the Notch Mode of Presentation

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    The processing of Kanizsa figures have classically been studied by flashing the full “pacmen” inducers at stimulus onset. A recent study, however, has shown that it is advantageous to present illusory figures in the “notch” mode of presentation, that is by leaving the round inducers on screen at all times and by removing the inward-oriented notches delineating the illusory figure at stimulus onset. Indeed, using the notch mode of presentation, novel P1and N1 effects have been found when comparing visual potentials (VEPs) evoked by an illusory figure and the VEPs to a control figure whose onset corresponds to the removal of outward-oriented notches, which prevents their integration into one delineated form. In Experiment 1, we replicated these findings, the illusory figure was found to evoke a larger P1 and a smaller N1 than its control. In Experiment 2, real grey squares were placed over the notches so that one condition, that with inward-oriented notches, shows a large central grey square and the other condition, that with outward-oriented notches, shows four unconnected smaller grey squares. In response to these “real” figures, no P1 effect was found but a N1 effect comparable to the one obtained with illusory figures was observed. Taken together, these results suggest that the P1 effect observed with illusory figures is likely specific to the processing of the illusory features of the figures. Conversely, the fact that the N1 effect was also obtained with real figures indicates that this effect may be due to more global processes related to depth segmentation or surface/object perception
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