African Journal of EcologyEcologyPeer-reviewed journal article
Elevational patterns in two groups of micromoths (Lepidoptera: Pterophoridae, Alucitidae) in tropical forests of Mount Cameroon
Fernando P. GaonaiD, Sylvain DelabyeiD, Vincent MaicheriD, P. Ya. UstjuzhaniniD, Vasily N. KovtunovichiD, Štěpán JanečekiD, Mercy Murkwe, Pavel PotockýiD, Szabolcs SáfiániD, Robert TropekiD
Abstract
Tropical elevational gradients offer unique insights into ecological processes shaping biodiversity, although micromoths remain severely understudied, especially in the Afrotropics. We analysed species richness, community composition, and functional traits (elevational range size and wingspan) of two micromoth families, many-plumed moths (Alucitidae) and plume moths (Pterophoridae), along a complete forest gradient on Mount Cameroon, an Afrotropical biodiversity hotspot. Alucitidae exhibited a distinct mid-elevation diversity peak, mirroring common patterns in tropical butterflies and moths, whereas Pterophoridae showed an uncommon upslope increase in species richness. Both families demonstrated clear elevational turnover in community composition, indicative of strong environmental filtering. Additionally, community-weighted elevational range size and wingspan increased consistently with elevation, supporting Rapoports rule and Bergmanns cline, respectively. These patterns likely reflect interactions among climatic factors and environmental complexity, though the underlying mechanisms remain unresolved. Our findings reveal the unique communities of both mid- and high-elevation forests, as well as the distinctiveness of species-poor lowland assemblages. This elevational differentiation underscores the need for conservation across the full gradient and the vulnerability of endemic highland taxa to climate-driven range contractions. Comprehensive research on neglected tropical insect groups is urgently needed to better anticipate biodiversity responses to environmental change.
- research focus: ecology & biodiversity
- research focus: clustering
- research focus: differential expression
- research focus: spatial domain detection
- approach: statistical model
- Citations
- 1
- FWCI
- 0.59
- Field percentile
- top 31%
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