A multi-isotope (δ13C, δ15N, δ34S, δ2H) approach to establishing migratory connectivity in lesser snow geese: Tracking an overabundant species

Expanding populations of North American midcontinent lesser snow geese (Anser caerulescens caerulescens) have potential to alter ecosystems throughout the Arctic and subarctic where they breed. Efforts to understand origins of harvested lesser snow geese to better inform management decisions have traditionally required mark-recapture approaches, while aerial photographic surveys have typically been used to identify breeding distributions. As a potential alternative, isotopic patterns that are metabolically fixed within newly grown flight feathers following summer molting could provide inferences regarding geographic breeding origin of individuals, without the need for prior capture. Our objective was to assess potential to use four stable isotopes (δ13C, δ15N, δ34S, δ2H) from feather material to determine breeding origins. We obtained newly grown flight feathers from individuals during summer banding at three Arctic and two subarctic breeding colonies in 2014 (n = 56) and 2016 (n = 45). We used linear discriminant analyses to predict breeding origins from models using combinations of stable isotopes as predictors and evaluated model accuracy when predicting colony, subregion, or subpopulation levels. We found a strong inverse relationship between δ2H values and increasing latitude (R2 = 0.83), resulting in differences (F4, 51 = 90.41, P \u3c 0.0001) among sampled colonies. No differences in δ13C or δ15N were detected among colonies, although δ34S in Akimiski Island, Baffin Island, and Karrak Lake were more enriched (F4, 51 = 11.25, P \u3c 0.0001). Using δ2H values as a predictor, discriminant analyses improved accuracy in classification level as precision decreased [model accuracy = 67% (colony), 88% (subregion), 94% (subpopulation)]. Application of the isotopic methods we describe could be used to provide an alternative monitoring method of population metrics, such as overall breeding population distribution, region-specific productivity and migratory connectivity that are informative to management decision makers and provide insight into cross-seasonal effects that may influence migratory behavior

Report on the 1st SPARC Stratospheric Network for the Assessment of Predictability (SNAP). April 24-26 April 2013, Reading, UK

Stratospheric Network for the Assessment of Predictability (SNAP), 24-26 April 2013, Reading, UKThe first SPARC Stratospheric Network for the Assessment of Predictability (SPARC-SNAP) workshop was organized in the Department of Meteorology, University of Reading, UK, from 24 to 26 April 2013. This was a joint workshop with 3rd SPARC Dynamical Variability (SPARC-DynVar) (Manzini et al., this issue) workshop 22-24 April with the 24th April as a joint day. The joint workshop was well attended and had around 100 participants (http://www.met.reading.ac.uk/~pn904784/DynVar_SNAP_Workshop/participant.html) from 16 countries in Europe, Asia, Africa, Australia, North America, and South America (Participants figure). In the SNAP part of workshop (including the joint day) there were two keynote address, nine invited talks, six contributory talks and 24 posters.The authors are grateful to the Natural Environment Research Council and WCRP-SPARC for their financial support

The influence of stratospheric vortex displacements and splits on surface climate

A strong link exists between stratospheric variability and anomalous weather patterns at the earth’s surface. Specifically, during extreme variability of the Arctic polar vortex termed a “weak vortex event,” anomalies can descend from the upper stratosphere to the surface on time scales of weeks. Subsequently the outbreak of cold-air events have been noted in high northern latitudes, as well as a quadrupole pattern in surface temperature over the Atlantic and western European sectors, but it is currently not understood why certain events descend to the surface while others do not. This study compares a new classification technique of weak vortex events, based on the distribution of potential vorticity, with that of an existing technique and demonstrates that the subdivision of such events into vortex displacements and vortex splits has important implications for tropospheric weather patterns on weekly to monthly time scales. Using reanalysis data it is found that vortex splitting events are correlated with surface weather and lead to positive temperature anomalies over eastern North America of more than 1.5 K, and negative anomalies over Eurasia of up to −3 K. Associated with this is an increase in high-latitude blocking in both the Atlantic and Pacific sectors and a decrease in European blocking. The corresponding signals are weaker during displacement events, although ultimately they are shown to be related to cold-air outbreaks over North America. Because of the importance of stratosphere–troposphere coupling for seasonal climate predictability, identifying the type of stratospheric variability in order to capture the correct surface response will be necessary

FPGA Implementations of SHA-3 Candidates:CubeHash, Grøstl, L{\sc ane}, Shabal and Spectral Hash

Abstract: Hash functions are widely used in, and form an important part of many cryptographic protocols. Currently, a public competition is underway to find a new hash algorithm(s) for inclusion in the NIST Secure Hash Standard (SHA-3). Computational efficiency of the algorithms in hardware will form one of the evaluation criteria. In this paper, we focus on five of these candidate algorithms, namely CubeHash, Grøstl, L{\sc ane}, Shabal and Spectral Hash. Using Xilinx Spartan-3 and Virtex-5 FPGAs, we present architectures for each of these hash functions, and explore area-speed trade-offs in each design. The efficiency of various architectures for the five hash functions is compared in terms of throughput per unit area. To the best of the authors\u27 knowledge, this is the first such comparison of these SHA-3 candidates in the literature

Galaxy Zoo: dust lane early-type galaxies are tracers of recent, gas-rich minor mergers

We present the second of two papers concerning the origin and evolution of local early-type galaxies exhibiting dust features. We use optical and radio data to examine the nature of active galactic nucleus (AGN) activity in these objects, and compare these with a carefully constructed control sample. We find that dust lane early-type galaxies are much more likely to host emission-line AGN than the control sample galaxies. Moreover, there is a strong correlation between radio and emission-line AGN activity in dust lane early-types, but not the control sample. Dust lane early-type galaxies show the same distribution of AGN properties in rich and poor environments, suggesting a similar triggering mechanism. By contrast, this is not the case for early-types with no dust features. These findings strongly suggest that dust lane early-type galaxies are starburst systems formed in gas-rich mergers. Further evidence in support of this scenario is provided by enhanced star formation and black hole accretion rates in these objects. Dust lane early-types therefore represent an evolutionary stage between starbursting and quiescent galaxies. In these objects, the AGN has already been triggered but has not as yet completely destroyed the gas reservoir required for star formation.Comment: 11 pages, 18 figures, 4 tables, MNRAS (Accepted for publication- 2012 January 19

100 years of progress in understanding the stratosphere and mesosphere

The stratosphere contains ~17% of Earth’s atmospheric mass, but its existence was unknown until 1902. In the following decades our knowledge grew gradually as more observations of the stratosphere were made. In 1913 the ozone layer, which protects life from harmful ultraviolet radiation, was discovered. From ozone and water vapor observations, a first basic idea of a stratospheric general circulation was put forward. Since the 1950s our knowledge of the stratosphere and mesosphere has expanded rapidly, and the importance of this region in the climate system has become clear. With more observations, several new stratospheric phenomena have been discovered: the quasi-biennial oscillation, sudden stratospheric warmings, the Southern Hemisphere ozone hole, and surface weather impacts of stratospheric variability. None of these phenomena were anticipated by theory. Advances in theory have more often than not been prompted by unexplained phenomena seen in new stratospheric observations. From the 1960s onward, the importance of dynamical processes and the coupled stratosphere–troposphere circulation was realized. Since approximately 2000, better representations of the stratosphere—and even the mesosphere—have been included in climate and weather forecasting models. We now know that in order to produce accurate seasonal weather forecasts, and to predict long-term changes in climate and the future evolution of the ozone layer, models with a well-resolved stratosphere with realistic dynamics and chemistry are necessary

Stratosphere‐troposphere coupling and annular mode variability in chemistry‐climate models

The internal variability and coupling between the stratosphere and troposphere in CCMVal‐2 chemistry‐climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the models’ annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a well‐simulated stratosphere can improve simulation of tropospheric intraseasonal variability