Regional databases demonstrate macroecological patterns less clearly than systematically collected field data

• Published in: Ecography (Copenhagen) Vol. 2025; no. 6
• Main Authors: Kerr, Matthew R., Currie, Nicole, Kosnik, Matthew A., Alroy, John
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.06.2025; John Wiley & Sons, Inc
• Subjects: Biodiversity; biodiversity data; Biogeography; bioregionalisation; bivalves; Datasets; Field study; global biodiversity information facility; Information systems; latitudinal diversity gradient; Mollusks; Shellfish; Taxonomy; Trends; Australia
• ISSN: 0906-7590; 1600-0587
• DOI: 10.1111/ecog.07355

The analysis of macroecological patterns has necessitated the use of large, composite datasets recording local‐scale species occurrences distributed across the globe. These datasets, however, have various spatial and temporal biases, including taxonomic under sampling, range gaps for many species, and geographic uncertainty. They have rarely been compared to data collected in the field across large spatial gradients. In this paper we use two datasets built from online repositories plus standardised field collections of death assemblages to reconstruct macroecological patterns for marine bivalves along the eastern coastline of Australia – spanning over 20° of latitude and the transition between tropical and temperate regions. We test the strength of the latitudinal diversity gradient using four diversity measures and identify a biogeographical boundary. The field collection demonstrates a strong latitudinal gradient, but results from the composite datasets were varied. Adding observation‐based records to the composite dataset obscured the latitudinal gradient. The location of the biogeographic boundary was the same in all datasets, and the location mirrored two previously published bioregionalisations. Although broad patterns seen in the field can be uncovered from composite macroecological datasets, care both in dataset construction and choice of methods is needed to ensure robust results.