A hydrogen isoscape for tracing the migration of herbivorous lepidopterans across the Afro-Palearctic range

Abstract

Rationale: Many insect species undertake multigenerational migrations in the Afro-tropical and Palearctic ranges, and understanding their migratory connectivity remains challenging due to their small size, short life span and large population sizes. Hydrogen isotopes (δ² H) can be used to reconstruct the movement of dispersing or migrating insects, but applying δ² H for provenance requires a robust isotope baseline map (i.e. isoscape) for the Afro-Palearctic.

Methods: We analyzed the δ² H in the wings (δ² H_wing ) of 142 resident butterflies from 56 sites across the Afro-Palearctic. The δ² H_wing values were compared to the predicted local growing-season precipitation δ² H values (δ² H_GSP ) using a linear regression model to develop an insect wing δ² H isoscape. We used multivariate linear mixed models and high-resolution and time-specific remote sensing climate and environmental data to explore the controls of the residual δ² H_wing variability.

Results: A strong linear relationship was found between δ² H_wing and δ² H_GSP values (r² = 0.53). The resulting isoscape showed strong patterns across the Palearctic but limited variation and high uncertainty for the Afro-tropics. Positive residuals of this relationship were correlated with dry conditions for the month preceding sampling whereas negative residuals were correlated with more wet days for the month preceding sampling. High intra-site δ² H_wing variance was associated with lower relative humidity for the month preceding sampling and higher elevation.

Conclusion: The δ² H_wing isoscape is applicable for tracing herbivorous lepidopteran insects that migrate across the Afro-Palearctic range but has limited geolocation potential in the Afro-tropics. The spatial analysis of uncertainty using high-resolution climatic data demonstrated that many African regions with highly variable evaporation rates and relative humidity have δ² H_wing values that are less related to δ² H_GSP values. Increasing geolocation precision will require new modeling approaches using more time-specific environmental data and/or independent geolocation tools.