资源环境科技发展态势分析平台

A new method for analysing change in high-dimensional data is based on nearest-neighbour statistics and is applied here to song dynamics during vocal learning in zebra finches, but could potentially be applied to other biological and artificial behaviours.

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.

Coral records indicate that the variability of the Indian Ocean Dipole over the last millennium is strongly coupled to variability in the El Nino/Southern Oscillation and that recent extremes are unusual but not unprecedented.

The Indian Ocean Dipole (IOD) affects climate and rainfall across the world, and most severely in nations surrounding the Indian Ocean(1-4). The frequency and intensity of positive IOD events increased during the twentieth century(5) and may continue to intensify in a warming world(6). However, confidence in predictions of future IOD change is limited by known biases in IOD models(7) and the lack of information on natural IOD variability before anthropogenic climate change. Here we use precisely dated and highly resolved coral records from the eastern equatorial Indian Ocean, where the signature of IOD variability is strong and unambiguous, to produce a semi-continuous reconstruction of IOD variability that covers five centuries of the last millennium. Our reconstruction demonstrates that extreme positive IOD events were rare before 1960. However, the most extreme event on record (1997) is not unprecedented, because at least one event that was approximately 27 to 42 per cent larger occurred naturally during the seventeenth century. We further show that a persistent, tight coupling existed between the variability of the IOD and the El Nino/Southern Oscillation during the last millennium. Indo-Pacific coupling was characterized by weak interannual variability before approximately 1590, which probably altered teleconnection patterns, and by anomalously strong variability during the seventeenth century, which was associated with societal upheaval in tropical Asia. A tendency towards clustering of positive IOD events is evident in our reconstruction, which-together with the identification of extreme IOD variability and persistent tropical Indo-Pacific climate coupling-may have implications for improving seasonal and decadal predictions and managing the climate risks of future IOD variability.

The front of the Getz Ice Shelf in West Antarctica creates an abrupt topographic step that deflects ocean currents, suppressing 70% of the heat delivery to the ice sheet.

Mass loss from the Antarctic Ice Sheet to the ocean has increased in recent decades, largely because the thinning of its floating ice shelves has allowed the outflow of grounded ice to accelerate(1,2). Enhanced basal melting of the ice shelves is thought to be the ultimate driver of change(2,3), motivating a recent focus on the processes that control ocean heat transport onto and across the seabed of the Antarctic continental shelf towards the ice(4-6). However, the shoreward heat flux typically far exceeds that required to match observed melt rates(2,7,8), suggesting that other critical controls exist. Here we show that the depth-independent (barotropic) component of the heat flow towards an ice shelf is blocked by the marked step shape of the ice front, and that only the depth-varying (baroclinic) component, which is typically much smaller, can enter the sub-ice cavity. Our results arise from direct observations of the Getz Ice Shelf system and laboratory experiments on a rotating platform. A similar blocking of the barotropic component may occur in other areas with comparable ice-bathymetry configurations, which may explain why changes in the density structure of the water column have been found to be a better indicator of basal melt rate variability than the heat transported onto the continental shelf(9). Representing the step topography of the ice front accurately in models is thus important for simulating ocean heat fluxes and induced melt rates.