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This article documents the addition of 283 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Agalinis acuta; Ambrosia artemisiifolia; Berula erecta; Casuarius casuarius; Cercospora zeae-maydis; Chorthippus parallelus; Conyza canadensis; Cotesia sesamiae; Epinephelus acanthistius; Ficedula hypoleuca; Grindelia hirsutula; Guadua angustifolia; Leucadendron rubrum; Maritrema novaezealandensis; Meretrix meretrix; Nilaparvata lugens; Oxyeleotris marmoratus; Phoxinus neogaeus; Pristomyrmex punctatus; Pseudobagrus brevicorpus; Seiridium cardinale; Stenopsyche marmorata; Tetranychus evansi and Xerus inauris. These loci were cross-tested on the following species: Agalinis decemloba; Agalinis tenella; Agalinis obtusifolia; Agalinis setacea; Agalinis skinneriana; Cercospora zeina; Cercospora kikuchii; Cercospora sorghi; Mycosphaerella graminicola; Setosphaeria turcica; Magnaporthe oryzae; Cotesia flavipes; Cotesia marginiventris; Grindelia Xpaludosa; Grindelia chiloensis; Grindelia fastigiata; Grindelia lanceolata; Grindelia squarrosa; Leucadendron coniferum; Leucadendron salicifolium; Leucadendron tinctum; Leucadendron meridianum; Laodelphax striatellus; Sogatella furcifera; Phoxinus eos; Phoxinus rigidus; Phoxinus brevispinosus; Phoxinus bicolor; Tetranychus urticae; Tetranychus turkestani; Tetranychus ludeni; Tetranychus neocaledonicus; Tetranychus amicus; Amphitetranychus viennensis; Eotetranychus rubiphilus; Eotetranychus tiliarium; Oligonychus perseae; Panonychus citri; Bryobia rubrioculus; Schizonobia bundi; Petrobia harti; Xerus princeps; Spermophilus tridecemlineatus and Sciurus carolinensis.
2. We present a hierarchical model that integrates observations from multiple sources to estimate spatio-temporal 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.