Although the effects of climate change on biodiversity are increasingly evident by the shifts in species ranges across taxonomical groups, the underlying mechanisms affecting individual species are still poorly understood. The power of climate envelopes to predict future ranges has been seriously questioned in recent studies. Amongst others, an improved understanding of the effects of current weather on population trends is required. We analysed the relation between butterfly abundance and the weather experienced during the life cycle for successive years using data collected within the framework of the Dutch Butterfly Monitoring Scheme for 40 species over a 15-year period and corresponding climate data. Both average and extreme temperature and precipitation events were identified, and multiple regression was applied to explain annual changes in population indices. Significant weather effects were obtained for 39 species, with the most frequent effects associated with temperature. However, positive density-dependence suggested climatic independent trends in at least 12 species. Validation of the short-term predictions revealed a good potential for climate-based predictions of population trends in 20 species. Nevertheless, data from the warm and dry year of 2003 indicate that negative effects of climatic extremes are generally underestimated for habitat specialists in drought-susceptible habitats, whereas generalists remain unaffected. Further climatic warming is expected to influence the trends of 13 species, leading to an improvement for nine species, but a continued decline in the majority of species. Expectations from climate envelope models overestimate the positive effects of climate change in northwestern Europe. Our results underline the challenge to include population trends in predicting range shifts in response to climate change.Electronic supplementary materialThe online version of this article (doi:10.1007/s00442-011-2007-z) contains supplementary material, which is available to authorized users.

Optimality theory states that whole-tree carbon gain is maximized when leaf N and photosynthetic capacity profiles are distributed along vertical light gradients such that the marginal gain of nitrogen investment is identical among leaves. However, observed photosynthetic N gradients in trees do not follow this prediction, and the causes for this apparent discrepancy remain uncertain. Our objective was to evaluate how hydraulic limitations potentially modify crown-level optimization in Sequoiadendron giganteum (giant sequoia) trees up to 90 m tall. Leaf water potential (Ψ l ) and branch sap flow closely followed diurnal patterns of solar radiation throughout each tree crown. Minimum leaf water potential correlated negatively with height above ground, while leaf mass per area (LMA), shoot mass per area (SMA), leaf nitrogen content (%N), and bulk leaf stable carbon isotope ratios (δ(13)C) correlated positively with height. We found no significant vertical trends in maximum leaf photosynthesis (A), stomatal conductance (g s), and intrinsic water-use efficiency (A/g s), nor in branch-averaged transpiration (E L), stomatal conductance (G S), and hydraulic conductance (K L). Adjustments in hydraulic architecture appear to partially compensate for increasing hydraulic limitations with height in giant sequoia, allowing them to sustain global maximum summer water use rates exceeding 2000 kg day(-1). However, we found that leaf N and photosynthetic capacity do not follow the vertical light gradient, supporting the hypothesis that increasing limitations on water transport capacity with height modify photosynthetic optimization in tall trees.