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Measurement and modelling of primary sex ratios for species with temperature-dependent sex determination.

Melanie Duc Bo MasseySarah K HoltRonald J BrooksNjal Rollinson
Published in: The Journal of experimental biology (2019)
For many oviparous animals, incubation temperature influences sex through temperature-dependent sex determination (TSD). Although climate change may skew sex ratios in species with TSD, few available methods predict sex under natural conditions, fewer still are based on mechanistic hypotheses of development, and field tests of existing methods are rare. We propose a new approach that calculates the probability of masculinization (PM) in natural nests. This approach subsumes the mechanistic hypotheses describing the outcome of TSD, by integrating embryonic development with the temperature-dependent reaction norm for sex determination. Further, we modify a commonly used method of sex ratio estimation, the constant temperature equivalent (CTE), to provide quantitative estimates of sex ratios. We test our new approaches using snapping turtles (Chelydra serpentina). We experimentally manipulated nests in the field, and found that the PM method is better supported than the modified CTE, explaining 69% of the variation in sex ratios across 27 semi-natural nests. Next, we used the PM method to predict variation in sex ratios across 14 natural nests over 2 years, explaining 67% of the variation. We suggest that the PM approach is effective and broadly applicable to species with TSD, particularly for forecasting how sex ratios may respond to climate change. Interestingly, we also found that the modified CTE explained up to 64% of variation in sex ratios in a Type II TSD species, suggesting that our modifications will be useful for future research. Finally, our data suggest that the Algonquin Park population of snapping turtles possesses resilience to biased sex ratios under climate change.
Keyphrases
  • climate change
  • air pollution
  • particulate matter
  • heavy metals
  • machine learning
  • risk assessment