Abstract

Abstract. The interface between climate and ecosystem structure and function is incompletely understood, partly because few ecological records start before the recent warming phase. Here, we analyse an exceptional 100-yr long record of the great tit (Parus major) population in Switzerland in relation to climate and habitat phenology. Using structural equation analysis, we demonstrate an uninterrupted cascade of significant influences of the large-scale atmospheric circulation (North-Atlantic Oscillation, NAO, and North-sea – Caspian Pattern, NCP) on habitat and breeding phenology, and further on fitness-relevant life history traits within great tit populations. We then apply the relationships of this analysis to reconstruct the circulation-driven component of fluctuations in great tit breeding phenology and productivity on the basis of new seasonal NAO and NCP indices back to 1500 AD. According to the structural equation model, the multi-decadal oscillation of the atmospheric circulation likely led to substantial variation in habitat phenology, productivity and consequently, tit population fluctuations with minima during the "Maunder Minimum" (∼ 1650–1720) and the Little Ice Age Type Event I (1810–1850). The warming since 1975 was not only related with a quick shift towards earlier breeding, but also with the highest productivity since 1500, and thus, the impact of the NAO and NCP has contributed to an unprecedented increase of the population. A verification of the structural equation model against two independent data series (1970–2000 and 1750–1900) corroborates that the retrospective model reliably depicts the major long-term NAO/NCP impact on ecosystem parameters. The results suggest a complex cascade of climate effects beginning at a global scale and ending at the level of individual life histories. This sheds light on how large-scale climate conditions substantially affect major life history parameters within a population, and thus influence key ecosystem parameters at the scale of centuries.

Highlights

  • Assessing the mechanisms of long-term, large-scale ecological consequences of climate fluctuations requires quantification of causal pathways, from conditions at a continental scale down to fine-scale processes such as trophic interactions within ecosystems (e.g. Parmesan, 2006; Meehl et al, 2007; IPCC, 2007)

  • We demonstrate an uninterrupted cascade of significant influences of the large-scale atmospheric circulation (North-Atlantic Oscillation, NAO, and North-sea – Caspian Pattern, NCP) on habitat and breeding phenology, and further on fitness-relevant life history traits within great tit populations

  • According to the structural equation model, the multi-decadal oscillation of the atmospheric circulation likely led to substantial variation in habitat phenology, productivity and tit population fluctuations with minima during the “Maunder Minimum” (∼ 1650–1720) and the Little Ice Age Type Event I (1810–1850)

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Summary

Introduction

Assessing the mechanisms of long-term, large-scale ecological consequences of climate fluctuations requires quantification of causal pathways, from conditions at a continental scale down to fine-scale processes such as trophic interactions within ecosystems (e.g. Parmesan, 2006; Meehl et al, 2007; IPCC, 2007). Due to the scarceness of data, climate impacts have rarely been tracked down to key parameters of population dynamics such as reproductive (Saether et al, 2003) or survival rates (Catchpole et al, 2000; Grosbois et al, 2006) Both the history and future of climate forcing on ecosystem function remain highly debated (Martin, 2007). We reconstructed climate-related ecological responses back to 1500 AD by applying the structural equation model from the 20th-century analysis to new reconstructions of monthly NAO and NCP indices This model was verified using independent data on habitat phenology based on historical plant phenological observations for the period 1750–1900

Great tit breeding phenology and population observations
Large-scale atmospheric circulation data
Model validation data
Statistical analyses
Structural equation model 1901–1999
Independent validation of structural equation model
Retrospective model 1500–2000
Full Text
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