Abstract
Understanding global patterns of genetic diversity (GD) is essential for describing, monitoring, and preserving life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrates that comprise only a small fraction of Earth’s biodiversity. Here, we construct the first global map of predicted insect GD, derived from open data. We calculate the GD mean (GDM) and evenness (GDE) of insect assemblages across the globe, identify environmental correlates of insect GD, and make predictions. Based on the largest single-locus genetic dataset assembled yet, we find that GDE follows a quadratic latitudinal gradient peaking in the subtropics. Both GDM and GDE correlate with seasonally hot temperatures, as well as climate stability since the LGM. Our models explain 27.9% and 24.0% of the observed variation in GDM and GDE in insects, respectively, making an important step towards understanding global biodiversity patterns in the most diverse animal taxon.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
In summary, we have: -- Clarified the description of the modeling workflow to make it easier to reproduce. -- Added sensitivity analyses for five additional minimum OTU thresholds (>10, >25, >50, >100, >150, >200), which demonstrate qualitatively similar results. -- Added simulation experiments which show that any potential bias due to missing duplicate alleles is negligible across the relevant parameter space of our models. -- Simplified our modeling approach by removing an extra step of model selection, which extends our initial results based on contemporary climate variables to show that the genetic diversity of insect assemblages has also been significantly influenced by historical climate change. -- Revised our previous discussion to place findings in the context of the eco-evolutionary processes underlying Rapoport's rule, varying range sizes, and late Pleistocene population histories. -- Added a discussion on the advantages and limitations of using mtDNA for global macrogenetics studies.
https://github.com/connor-french/global-insect-macrogenetics
