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Predicting the impact of global climat echange on the biosphere has become one of the most important efforts in ecology. Ecosystems worldwide are changing rapidly as a consequence of global warming, yet our understanding of the consequences of these changes on populations is limited. The North Atlantic Oscillation (NAO) has been used as a proxy for “climate” in several ecological studies, but this index may not always explain the patterns of variation in populations examined. Other techniques to study the relationship between ecological time series and climate are therefore needed. A standard method used in climatology is to work with point maps, where point correlation, point regression or other techniques are used to identify hot spots of regions that can explain the variability observed in the time series. These hotspots may be part of a teleconnection, which is an atmospheric mode of variability that affects remote regions around the globe. The NAO is one type of teleconnection, but not all climate variability can be explained through it. In the present study we have used climate-related techniques and analyzed the yearly variation in the population growth of a Common Guillemot Uria aalge colony in the Barents Sea area spanning 30 years. We show that the NAO does not explain this variation, but that point analysis can help identify indices that can explain a significant part of it. These indices are related to changes of mean sea level pressure in the Barents Sea via the Pacific—forming a teleconnection-type pattern. The dynamics are as follows: in years when the population growth rate is higher, the patterns observed are that of an anomalous low-pressure system in the Barents Sea. These low-pressure systems are a source of heat transport into the region and they force upwelling mixing in the ocean, thus creating favorable conditions for a more successful survival and breeding of the Common Guillemot

frontiers in ecology and evolution

There is more to climate than the North Atlantic Oscillation: a new perspective from climate dynamics to explain the variability in population growth rates of a long-lived seabird