Magnetic loop emergence within a granule

We investigate the temporal evolution of magnetic flux emerging within a granule in the quiet-Sun internetwork at disk center. We combined IR spectropolarimetry performed in two Fe I lines at 1565 nm with speckle-reconstructed G-band imaging. We determined the magnetic field parameters by a LTE inversion of the full Stokes vector using the SIR code, and followed their evolution in time. To interpret the observations, we created a geometrical model of a rising loop in 3D. The relevant parameters of the loop were matched to the observations where possible. We then synthesized spectra from the 3D model for a comparison to the observations. We found signatures of magnetic flux emergence within a growing granule. In the early phases, a horizontal magnetic field with a distinct linear polarization signal dominated the emerging flux. Later on, two patches of opposite circular polarization signal appeared symmetrically on either side of the linear polarization patch, indicating a small loop-like structure. The mean magnetic flux density of this loop was roughly 450 G, with a total magnetic flux of around 3x10^17 Mx. During the ~12 min episode of loop occurrence, the spatial extent of the loop increased from about 1 to 2 arcsec. The middle part of the appearing feature was blueshifted during its occurrence, supporting the scenario of an emerging loop. The temporal evolution of the observed spectra is reproduced to first order by the spectra derived from the geometrical model. The observed event can be explained as a case of flux emergence in the shape of a small-scale loop.Comment: 10 pages, 13 figures; accepted for Astronomy and Astrophysics; ps and eps figures in full resolution are available at http://www.astro.sk/~koza/figures/aa2009_loop

Born Knowing: Tentacled Snakes Innately Predict Future Prey Behavior

Background: Aquatic tentacled snakes (Erpeton tentaculatus) can take advantage of their prey’s escape response by startling fish with their body before striking. The feint usually startles fish toward the snake’s approaching jaws. But when fish are oriented at a right angle to the jaws, the C-start escape response translates fish parallel to the snake’s head. To exploit this latter response, snakes must predict the future location of the fish. Adult snakes can make this prediction. Is it learned, or are tentacled snakes born able to predict future fish behavior? Methods and Findings: Laboratory-born, naïve snakes were investigated as they struck at fish. Trials were recorded at 250 or 500 frames per second. To prevent learning, snakes were placed in a water container with a clear transparency sheet or glass bottom. The chamber was placed over a channel in a separate aquarium with fish below. Thus snakes could see and strike at fish, without contact. The snake’s body feint elicited C-starts in the fish below the transparency sheet, allowing strike accuracy to be quantified in relationship to the C-starts. When fish were oriented at a right angle to the jaws, naïve snakes biased their strikes to the future location of the escaping fish’s head, such that the snake’s jaws and the fish’s translating head usually converged. Several different types of predictive strikes were observed. Conclusions: The results show that some predators have adapted their nervous systems to directly compensate for the future behavior of prey in a sensory realm that usually requires learning. Instead of behavior selected during their lifetime

Multi-country loss rates of honey bee colonies during winter 2016/2017 from the COLOSS survey

Publication history: Accepted - 5 March 2018; Published online - 8 May 2018.In this short note we present comparable loss rates of honey bee colonies during winter 2016/2017 from 27 European countries plus Algeria, Israel and Mexico, obtained with the COLOSS questionnaire. The 14,813 beekeepers providing valid loss data collectively wintered 425,762 colonies, and reported 21,887 (5.1%, 95% confidence interval 5.0–5.3%) colonies with unsolvable queen problems and 60,227 (14.1%, 95% CI 13.8–14.4%) dead colonies after winter. Additionally we asked for colonies lost due to natural disaster, which made up another 6,903 colonies (1.6%, 95% CI 1.5–1.7%). This results in an overall loss rate of 20.9% (95% CI 20.6–21.3%) of honey bee colonies during winter 2016/2017, with marked differences among countries. The overall analysis showed that small operations suffered higher losses than larger ones (p < 0.001). Overall migratory beekeeping had no significant effect on the risk of winter loss, though there was an effect in several countries. A table is presented giving detailed results from 30 countries. A map is also included, showing relative risk of colony winter loss at regional level.The authors are also grateful to various national funding sources for their support of some of the monitoring surveys [including, in the Republic of Serbia, MPNTR-RS, through grant number III46002]. The authors acknowledge the financial support by the University of Graz for open access publication