Sampling bias masks cross-taxon congruence in Iberian insect species richness patterns

Abstract

Accurate species distribution data are essential for effective conservation planning; however, they are often incomplete or spatially biased. Such limitations may obscure real biodiversity patterns and undermine the reliability of cross-taxon congruence analyses. Here, we assess how data quality and sampling effort influence estimates of cross-taxon congruence in insect species richness patterns across the Iberian Peninsula and the Balearic Islands. Using a large, curated georeferenced database (> 845,000 records comprising 1,808 species) covering four insect groups (butterflies, moths, dung beetles, and water beetles), we evaluated inventory completeness with species accumulation curves and identified well-surveyed cells (≥ 70% completeness and final slope ≤ 0.1) under four scenarios representing progressively higher levels of information reliability. Species richness patterns showed clear geographical structure, with richness hotspots generally associated with major mountain systems, although their specific locations differed among taxonomic groups. Across all dataset scenarios, cross-taxon correlations in species richness were generally positive but moderate. Importantly, congruence tended to decline, as analyses were progressively restricted to well-surveyed cells, suggesting that low-quality data may artificially inflate the apparent agreement among taxa. The strongest congruence was observed between taxonomic groups belonging to the same order (Coleoptera or Lepidoptera), whereas relationships between orders were markedly weaker. Overall, our results suggest that apparent cross-taxon congruence in insect species richness is strongly influenced by data quality and taxonomic relatedness. These findings highlight the need for multi-taxon approaches and for explicitly accounting for sampling bias when using surrogate taxa in biodiversity assessments and conservation planning.

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