ALBERT

Description: 〈div data-abstract-type="normal"〉〈p〉A fine-grained, up to 3-m-thick tephra bed in southwestern Saskatchewan, herein named Duncairn tephra (Dt), is derived from an early Pleistocene eruption in the Jemez Mountains volcanic field of New Mexico, requiring a trajectory of northward tephra dispersal of ~1500 km. An unusually low CaO content in its glass shards denies a source in the closer Yellowstone and Heise volcanic fields, whereas a Pleistocene tephra bed (LSMt) in the La Sal Mountains of Utah has a very similar glass chemistry to that of the Dt, supporting a more southerly source. Comprehensive characterization of these two distal tephra beds along with samples collected near the Valles caldera in New Mexico, including grain size, mineral assemblage, major- and trace-element composition of glass and minerals, paleomagnetism, and fission-track dating, justify this correlation. Two glass populations each exist in the Dt and LSMt. The proximal correlative of Dt1 is the plinian Tsankawi Pumice and co-ignimbritic ash of the first ignimbrite (Qbt1g) of the 1.24 Ma Tshirege Member of the Bandelier Tuff. The correlative of Dt2 and LSMt is the co-ignimbritic ash of Qbt2. Mixing of Dt1 and Dt2 probably occurred during northward transport in a jet stream.〈/p〉〈/div〉

Description: Abstract Global warming has advanced the timing of biological events, potentially leading to disruption across trophic levels. The potential importance of phenological change as a driver of population trends has been suggested. To fully understand possible impacts, there is a need to quantify the scale of these changes spatially and according to habitat type. We studied the relationship between phenological trends, space and habitat type between 1965 to 2012 using an extensive UK dataset comprising 269 aphid, bird, butterfly and moth species. We modelled phenologies using generalized additive mixed models that included covariates for geographical (latitude, longitude, altitude), temporal (year, season) and habitat terms (woodland, scrub, grassland). Model selection showed that a baseline model with geographical and temporal components explained the variation in phenologies better than either a model in which space and time interacted or a habitat model without spatial terms. This baseline model showed strongly that phenologies shifted progressively earlier over time, that increasing altitude produced later phenologies and that a strong spatial component determined phenological timings, particularly latitude. The seasonal timing of a phenological event, in terms of whether it fell in the first or second half of the year, did not result in substantially different trends for butterflies. For moths, early season phenologies advanced more rapidly than those recorded later. Whilst temporal trends across all habitats resulted in earlier phenologies over time, agricultural habitats produced significantly later phenologies than most other habitats studied, probably because of non‐climatic drivers. A model with a significant habitat‐time interaction was the best‐fitting model for birds, moths and butterflies, emphasising that the rates of phenological advance also differ among habitats for these groups. Our results suggest the presence of strong spatial gradients in mean seasonal timing, and non‐linear trends towards earlier seasonal timing that varies in form and rate among habitat types. This article is protected by copyright. All rights reserved.