Foraging Habitat and Chick Diets of Roseate Tern, Sterna dougallii, Breeding on Country Island, Nova Scotia

Breeding seabirds are threatened by human activities that affect nesting and foraging habitat. In Canada, one of the seabirds most at risk of extirpation is the Roseate Tern, Sterna dougallii. Although critical nesting habitat has been identified for the Roseate Tern in Canada, its foraging locations and the diet of its chicks are unknown. Therefore, our goal was to determine the foraging locations and diet of chicks of Roseate Tern breeding on Country Island, Nova Scotia, which is one of Canada's two main breeding colonies. In 2003 and 2004, we radio-tracked the Roseate Tern by plane to locate foraging areas and conducted feeding watches to determine the diet of chicks. Roseate Tern foraged approximately 7 km from the breeding colony over shallow water < 5 m deep. In both years, sand lance, Ammodytes spp., was the most common prey item delivered to chicks, followed by hake, Urophycis spp. Our results are consistent with previous work at colonies in the northeastern United States, suggesting that throughout its range, this species may be restricted in both habitat use and prey selection. The reliance on a specific habitat type and narrow range of prey species makes the Roseate Tern generally susceptible to habitat perturbations and reductions in the availability of prey.

Reproductive Consequences of Nest Site Use in Fork-tailed Storm-Petrels in the Aleutian Islands, Alaska: Potential Lasting Effects of an Introduced Predator

We examined the reproductive consequences of differential nest site use in Fork-tailed Storm-Petrels (Oceanodroma furcata) in the Aleutian Islands, Alaska, where birds on islands where foxes were introduced nest in rocky substrate rather than in typical soil habitat. We investigated how physical and microclimatic nest site characteristics influenced storm-petrel breeding success 20 years after fox removal. We then examined whether those nest site characteristics that affected success were related to the amount of rock that composed the nest. In both years of our study, nest temperature had the strongest influence on chick survival and overall reproductive success, appearing in all the top models and alone explaining 14–35% of the variation in chick survival. The relationship between reproductive success and nest temperature was positive in both years, with higher survival in warmer nests. In turn, the best predictor of nest temperature was the amount of rock that composed the site. Rockier nests had colder average temperatures, which were driven by lower daily minimum temperatures, compared to nests with more soil. Thus, the rockiness of the nest site appeared to affect chick survival and overall reproductive success through its influence on nest temperature. This study suggests that the use of rocky nest sites, presumed to be a result of historic predation from introduced foxes, could decrease breeding success in this recovering population, and thus be a long-lasting effect of introduced predators.

Effect of ENSO phase on large-scale snow water equivalent distribution in a GCM

Understanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator only

Does the North Atlantic Oscillation show unusual persistence on intraseasonal timescales?

Previous studies have argued that the autocorrelation of the winter North Atlantic Oscillation (NAO) index provides evidence of unusually persistent intraseasonal dynamics. We demonstrate that the autocorrelation on intraseasonal time-scales of 10–30 days is sensitive to the presence of interannual variability, part of which arises from the sampling of intraseasonal variability and the remainder of which we consider to be “externally forced”. Modelling the intraseasonal variability of the NAO as a red noise process we estimate, for winter, ~70% of the interannual variability is externally forced, whereas for summer sampling accounts for almost all of the interannual variability. Correcting for the externally forced interannual variability has a major impact on the autocorrelation function for winter. When externally forced interannual variability is taken into account the intrinsic persistence of the NAO is very similar in summer and winter (~5 days). This finding has implications for understanding the dynamics of the NAO.

Methods and resources for climate impacts research: achieving synergy

The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.