Linking inter-annual variation in environment, phenology, and abundance for a montane butterfly community (article)

This is the final version. Available from the Ecological Society of America via the DOI in this record. The dataset associated with this article is located in ORE at: https://doi.org/10.24378/exe.1963Climate change has caused widespread shifts in species’ phenology, but the consequences for population and community dynamics remain unclear because of uncertainty regarding the species-specific drivers of phenology and abundance, and the implications for synchrony among interacting species. Here, we develop a statistical model to quantify inter-annual variation in phenology and abundance over an environmental gradient, and use it to identify potential drivers of phenology and abundance in co-occurring species. We fit the model to counts of 10 butterfly species with single annual generations over a mountain elevation gradient, as an exemplar system in which temporally limited availability of biotic resources and favorable abiotic conditions impose narrow windows of seasonal activity. We estimate parameters describing changes in abundance, and the peak time and duration of the flight period, over ten years (2004–2013) and across twenty sample locations (930–2,050 m) in central Spain. We also use the model outputs to investigate relationships of phenology and abundance with temperature and rainfall. Annual shifts in phenology were remarkably consistent among species, typically showing earlier flight periods during years with warm conditions in March or May–June. In contrast, inter-annual variation in relative abundance was more variable among species, and generally less well associated with climatic conditions. Nevertheless, warmer temperatures in June were associated with increased relative population growth in three species, and five species had increased relative population growth in years with earlier flight periods. These results suggest that broadly coherent interspecific changes to phenology could help to maintain temporal synchrony in community dynamics under climate change, but that the relative composition of communities may vary due to interspecific inconsistency in population dynamic responses to climate change. However, it may still be possible to predict abundance change for species based on a robust understanding of relationships between their population dynamics and phenology, and the environmental drivers of both.Royal SocietyNatural Environment Research Counci

Linking fine-scale sub-arctic vegetation distribution in complex topography with surface-air-temperature modelled at 50-m resolution

Recent studies have shown that the complexities of the surface features in mountainous terrain require a re-assessment of climate impacts at the local level. We explored the importance of surface-air-temperature based on a recently published 50-m-gridded dataset, versus soil variables for explaining vegetation distribution in Swedish Lapland using generalised linear models (GLMs). The results demonstrated that the current distribution of the birch forest and snowbed community strongly relied on the surface-air-temperature. However, temperature alone is a poor predictor of many plant communities (wetland, meadow). Because of diminishing sample representation with increasing altitude, the snowbed community was undersampled at higher altitudes. This results in underestimation of the current distribution of the snowbed community around the mountain summits. The analysis suggests that caution is warranted when applying GLMs at the local level. Copyright © Royal Swedish Academy of Sciences 2012