Quantifying range-wide variation in population trends from local abundance surveys and widespread opportunistic occurrence records J€ orn Pagel 1,2 *, Barbara J. Anderson 3,4 , Robert B. O’Hara 5 , Wolfgang Cramer 6 , Richard Fox 7 , Florian Jeltsch 1 , David B. Roy 8 , Chris D. Thomas 4 and Frank M. Schurr 2,9 1 Plant Ecology and Conservation Biology, University of Potsdam, 14469 Potsdam, Germany; 2 Institut des Sciences de l’Evolution, UMR 5554, Universit  e Montpellier 2, Montpellier, cedex 05, France; 3 Rutherford Discovery Fellow, Landcare Research, Private Bag 1930, Dunedin 9054, New Zealand; 4 Department of Biology (Area 18), University of York, York, YO10 5YW, UK; 5 Biodiversity and Climate Change Research Centre (BIK-F), 60325 Frankfurt am Main, Germany; 6 Institut M editerran een de Biodiversit  e et d’Ecologie Marine et Continentale (IMBE), Aix Marseille Universit  e, CNRS, IRD, Avignon Universit  e, Aix-en-Provence, cedex 04, France; 7 Butterfly Conservation, Manor Yard, East Lulworth, Dorset, BH20 5QP, UK; 8 NERC Centre for Ecology & Hydrology, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB, UK; and 9 Landscape Ecology and Vegetation Science, University of Hohenheim, 70599 Stuttgart, Germany Summary 1. Species’ abundances vary in space and time. Describing these patterns is a cornerstone of macroecology. Moreover, trends in population size are an important criterion for the assessment of a species’ conservation sta- tus. Because abundance trends are not homogeneous in space, we need to quantify variation in abundance trends across the geographical range of a species. A basic difficulty exists in that data sets that cover large geographic areas rarely include population abundance data at high temporal resolution. Whilst both broad-scale geographic distribution data and site-specific population trend data are becoming more widely available, approaches are required which integrate these different types of data. 2. We present a hierarchical model that integrates observations from multiple sources to estimate spatio-tempo- ral abundance trends. The model links annual population densities on a spatial grid to both long-term count data and to opportunistic occurrence records from a citizen science programme. Specific observation models for both data types explicitly account for differences in data structure and quality. 3. We test this novel method in a virtual study with simulated data and apply it to the estimation of abundance dynamics across the range of a butterfly species (Pyronia tithonus) in Great Britain between 1985 and 2004. The application to simulated and real data demonstrates how the hierarchical model structure accommodates various sources of uncertainty which occur at different stages of the link between observational data and the modelled abundance, thereby it accounts for these uncertainties in the inference of abundance variations. 4. We show that by using hierarchical observation models that integrate different types of commonly available data sources, we can improve the estimates of variation in species abundances across space and time. This will improve our ability to detect regional trends and can also enhance the empirical basis for understanding range dynamics. Key-words: atlas data, Bayesian statistics, biogeography, butterflies, citizen science programme, conservation biology, count data, macroecology, state-space model Introduction Species distribution data are of central importance to ecology. Analysing spatial patterns of species’ occurrence is the natural first step of studies that assess global change impacts on biodi- versity and design conservation strategies (Dawson et al. 2011). Including the temporal dimension in macro-ecological data is critical to the development of macro-ecology as a pre- dictive science (Fisher, Frank & Leggett 2010). Indeed, we need data on the spatio-temporal variation of not only occurrence, but also abundance to understand the population demograph- ics that underlie species niches and range dynamics (Schurr et al. 2012) and conservation biogeography (Whittaker et al. 2005). In particular, the detection of abundance trends is an important component of assessing the conservation status of species according to Red List criteria (IUCN Standards & Peti- tions Subcommittee 2011). Because threats are not equally dis- tributed across the geographical range of species, and conservation actions are commonly deployed within adminis- trative units rather than globally, we need to quantify abun- dance trends in different parts of the range. However, *Correspondence author. E-mail: jpagel@uni-potsdam.de © 2014 The Authors. Methods in Ecology and Evolution © 2014 British Ecological Society Methods in Ecology and Evolution 2014, 5, 751–760 doi: 10.1111/2041-210X.12221