Male-biased sexual selection, but not sexual dichromatism, predicts speciation in birds

• Main Authors: Cally, Justin, Stuart-Fox, Devi, Holman, Luke, Dale, James, Medina, Iliana
• Format: Dataset
• Language: English
• Published: Dryad 2021
• Subjects: Selection - Sexual; FOS Biological sciences; Arctic; Random Point; Lynx
• Online Access: https://dx.doi.org/10.5061/dryad.573n5tb6n; http://datadryad.org/stash/dataset/doi:10.5061/dryad.573n5tb6n

Sexual selection is thought to shape phylogenetic diversity by affecting speciation or extinction rates. However, the net effect of sexual selection on diversification is hard to predict, because many of the hypothesised effects on speciation or extinction have opposing signs and uncertain magnitudes. Theoretical work also suggests that the net effect of sexual selection on diversification should depend strongly on ecological factors, though this prediction has seldom been tested. Here, we test whether variation in sexual selection can predict speciation and extinction rates across passerine birds (up to 5,812 species, covering most genera) and whether this relationship is mediated by environmental factors. Male-biased sexual selection, and specifically sexual size dimorphism, predicted two of the three measures of speciation rates that we examined. The link we observed between sexual selection and speciation was independent of environmental variability, though species with smaller ranges had higher speciation rates. There was no association between any proxies of sexual selection and extinction rate. Our findings support the view that male-biased sexual selection, as measured by frequent predictors of male-male competition, has shaped diversification in the largest radiation of birds. : We obtained estimates of species range size using expert range maps (BirdLife International and Handbook of the Birds of the World 2017). The names of 1,230 species in the Birdlife database (Hoyo and Collar 2016) have been recently changed, so we manually matched these taxa with the names used in the sexual dichromatism dataset (Hoyo and Collar 2016). For each species’ range, we obtained estimates of climatic conditions by extracting 1,000 random point samples of each bioclimatic variable. We extracted 19 present-day bioclimatic variables (representing a variety of biologically relevant annual trends in temperature and precipitation) with 30-second (~1 km2) spatial resolution (Fick and Hijmans 2017). From the 1000 values of each bioclimatic variable, we obtained means and standard deviations for each species. Using the same spatial sampling, we extracted means and standard deviations of bioclimatic variables from the paleoclimate during the last interglacial (LIG; 120,000 - 140,000 years ago) (Otto-Bliesner et al. 2006). To estimate variability in the energy available to species, we obtained the mean and standard deviation of net primary productivity (NPP) values between 2000 - 2015 across each species distribution. Estimates of NPP had 30-second resolution and were obtained through MODIS (Moderate Resolution Imaging Spectroradiometer) primary production products stage 3 (MOD17A3) (Zhao et al. 2005). References BirdLife International and Handbook of the Birds of the World. 2017. Bird species distribution maps of the world. http://datazone.birdlife.org/species/requestdis. Fick, S. E., and R. J. Hijmans. 2017. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37:4302–4315. Hoyo, J. del, and N. J. Collar. 2016. HBW and birdlife international illustrated checklist of the birds of the world. Lynx Edicions; BirdLife International. Otto-Bliesner, B. L., S. J. Marshall, J. T. Overpeck, G. H. Miller, A. Hu, and. 2006. Simulating arctic climate warmth and icefield retreat in the last interglaciation. Science 311:1751–1753. Zhao, M., F. A. Heinsch, R. R. Nemani, and S. W. Running. 2005. Improvements of the modis terrestrial gross and net primary production global data set. Remote Sensing of Environment 95:164–176. : The data, with relevant code relating to its usage and analysis is available on Github: https://github.com/JustinCally/SexualSelection_Speciation