Back

Diversity and Functional Roles of Carabid Beetles across Salinity Gradients in Marshlands

Remmers, S.; Dausmann, K. H.

2025-12-05 ecology
10.64898/2025.12.04.692354 bioRxiv
Show abstract

Marsh ecosystems represent ecotones of high ecological significance where terrestrial and aquatic systems converge, governed by strong gradients in salinity and flooding. These environments sustain specialised communities and perform vital ecosystem functions such as carbon sequestration or nutrient cycling. This study examined carabid beetle (Coleoptera: Carabidae) assemblages across freshwater and saltwater marshes along the Elbe estuary in northern Germany to assess how environmental conditions shape patterns of abundance, diversity, and functional traits. Over 17,000 individuals representing 84 species were collected between March and October 2024. Despite similar species richness between marsh types, community composition differed markedly (Bray-Curtis dissimilarity: 0.92), reflecting environmental filtering along the salinity gradient. Freshwater marshes exhibited greater overall functional richness, while saltwater marshes supported more functionally even and divergent trait distributions, indicating stronger niche specialization under saline stress. Seasonal activity was bimodal in both habitats but peaked earlier in freshwater sites. A generalized linear mixed model revealed significant positive relationships between carabid activity abundance and functional richness of both dispersal- and preference-based traits. These findings demonstrate that salinity and flooding regimes drive distinct taxonomic and functional assemblages, with trait diversity underpinning ecosystem resilience and functioning. The study establishes an ecological baseline for future monitoring of marshland biodiversity and highlights the necessity of conserving functionally diverse communities to maintain the ecological integrity of tidal and floodplain marshes under changing environmental conditions.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.