Centennial relationships between ocean temperature and Atlantic puffin production reveal shifting decennial trends.

The current warming of the oceans has been shown to have detrimental effects for a number of species. An understanding of the underlying mechanisms may be hampered by the non-linearity and non-stationarity of the relationships between temperature and demography, and by the insufficient length of available time series. Most demographic time series are too short to study the effects of climate on wildlife in the classical sense of meteorological patterns over at least 30 years. Here we present a harvest time series of Atlantic puffins (Fratercula arctica) that goes back as far as 1880. It originates in the world's largest puffin colony, in southwest Iceland, which has recently experienced a strong decline. By estimating an annual chick production index for 128 years, we found prolonged periods of strong correlations between local sea surface temperature (SST) and chick production. The sign of decennial correlations switches three times during this period, where the phases of strong negative correlations between puffin productivity and SST correspond to the early 20th century Arctic warming period and to the most recent decades. Most of the variation (72%) in chick production is explained by a model in which productivity peaks at an SST of 7.1°C, clearly rejecting the assumption of a linear relationship. There is also evidence supporting non-stationarity: The SST at which puffins production peaked has increased by 0.24°C during the 20th century, although the increase in average SST during the same period has been more than three times faster. The best supported models indicate that the population's decline is at least partially caused by the increasing SST around Iceland.

Spatial synchrony in sub-arctic geometrid moth outbreaks reflects dispersal in larval and adult life cycle stages.

Spatial synchrony in population dynamics can be caused by dispersal or spatially correlated variation in environmental factors like weather (Moran effect). Distinguishing between these mechanisms is challenging for natural populations, and the study of dispersal-induced synchrony in particular has been dominated by theoretical modelling and laboratory experiments. The goal of the present study was to evaluate the evidence for dispersal as a cause of meso-scale (distances of tens of kilometres) spatial synchrony in natural populations of the two cyclic geometrid moths Epirrita autumnata and Operophtera brumata in sub-arctic mountain birch forest in northern Norway. To infer the role of dispersal in geometrid synchrony, we applied three complementary approaches, namely estimating the effect of design-based dispersal barriers (open sea) on synchrony, comparing the strength of synchrony between E. autumnata (winged adults) and the less dispersive O. brumata (wingless adult females), and relating the directionality (anisotropy) of synchrony to the predominant wind directions during spring, when geometrid larvae engage in windborne dispersal (ballooning). The estimated effect of dispersal barriers on synchrony was almost three times stronger for the less dispersive O. brumata than E. autumnata. Inter-site synchrony was also weakest for O. brumata at all spatial lags. Both observations argue for adult dispersal as an important synchronizing mechanism at the spatial scales considered. Further, synchrony in both moth species showed distinct anisotropy and was most spatially extensive parallel to the east-west axis, coinciding closely to the overall dominant wind direction. This argues for a synchronizing effect of windborne larval dispersal. Congruent with most extensive dispersal along the east-west axis, E. autumnata also showed evidence for a travelling wave moving southwards at a speed of 50-80 km/year. Our results suggest that dispersal processes can leave clear signatures in both the strength and directionality of synchrony in field populations, and highlight wind-driven dispersal as promising avenue for further research on spatial synchrony in natural insect populations.

Seasonal dependent suitability of physical parameterizations to simulate precipitation over the Himalayan headwater.

The Himalayan ecosystem is fragile and needs robust management strategies for sustainability of natural resources such as water and vegetation. Therefore, reliable precipitation estimation becomes quite important from operational and regulation standpoints. It is crucial for numerous activities including policy/planning, agriculture, reservoir operations, disaster management, and others. In addition, reliable information on temporal variability of precipitation is also crucial for various applications such as agricultural and hydrological. The western Himalaya receives two distinct weather systems during summer and winter. Summer is responsible (largely) for rainfall and winter is for snowfall. Therefore, we hypothesize that there may not be a single set of parameterization schemes that can represent well both the weather systems. To investigate, we set up the WRF modeling system and performed six experiments with a combination of three microphysics (MP3, MP3, and WSM6) and two cumulus schemes (KF, and BMJ). It was found that the precipitation along the Himalayan foothills (near to basin terminal) is underestimated in four out of six experiments. Only experiments with BMJ cumulus scheme along with WSM6 and MP8 microphysics were able to show a considerable amount of precipitation along these foothills. It was noted that all six experiments showed high precipitation in the upstream region and over the mountain peaks and ridges in North-Western Himalaya. For DJF, each experiment was found to have large biases and none of them represented the observation with high confidence. However, the selection of observation reference data itself is a challenging task because of data paucity in this region. Therefore, the closest experiment to the most appropriate observation was selected as the reliable configuration (MP8_KF: MP8 microphysics and KF cumulus scheme) for DJF precipitation simulation. In this study we have, for the first time, reported the role of seasonal sensitivity for the climate scale simulations as we found that different schemes were suitable for different weather systems.