Aim Understanding patterns in the abundance of species across thermal ranges can give useful insights into the potential impacts of climate change. The abundant‐centre hypothesis suggests that species will reach peak abundance at the centre of their thermal range where conditions are optimal, but evidence in support of this hypothesis is mixed and limited in geographical and taxonomic scope. We tested the applicability of the abundant‐centre hypothesis across a range of intertidal organisms using a large, citizen science‐generated data set. Location UK. Methods Species' abundance records were matched with their location within their thermal range. Patterns in abundance distribution for individual species, and across aggregated species abundances, were analysed using Kruskal–Wallis tests and quantile general additive models. Results Individually, invertebrate species showed increasing abundances in the cooler half of the thermal range and decreasing abundances in the warmer half of the thermal range. The overall shape for aggregated invertebrate species abundances reflected a broad peak, with a cool‐skewed maximum abundance. Algal species showed little evidence for an abundant‐centre distribution individually, but overall the aggregated species abundances suggested a hump‐backed abundance distribution. Main Conclusions Our study follows others in showing mixed support for the abundant‐centre hypothesis at an individual species level, but demonstrates an increased predictability in species responses when an aggregated overall response is considered.

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Citizen science represents an effective means of collecting ecological data; however, the quality/reliability of these data is often questioned. Quality assurance procedures are therefore important to determine the validity of citizen science data and to promote confidence in conclusions. Here, data generated by a marine citizen science project conducted at 12 sites across the United Kingdom was used to investigate whether the use of a simple, low-taxonomic-resolution field-monitoring protocol allowed trained citizen scientists to generate data comparable to those of professional scientists. To do this, differences between field estimates of algal percentage cover generated by different observer units (i.e., trained citizen scientists, professional scientists, and combined units), and digitally derived baseline estimates were examined. The results show that in the field, citizen scientists generated data similar to those of professional scientists, demonstrating that training, coupled with the use of a simple, low-taxonomic-resolution protocol can allow citizen scientists to generate robust datasets in which variability likely represents ecological variation/change as opposed to observer variation. The results also show, irrespective of observer unit, that differences between field and digital baseline estimates of algal percentage cover were greatest in plots with medium levels of algal cover, highlighting that additional/enhanced training for all participants could be beneficial in this area. The approach presented can serve as a guide for existing and future projects with similar protocols to assess their data quality, to strengthen participant training/protocols, and ultimately to promote the incorporation of robust citizen science datasets into environmental research and management.