Unknown

Dataset Information

0

Species-specific model to predict amphibian metamorphosis.


ABSTRACT: Exploring the timing of life-history transitions has been a pivotal focus in the field of evolutionary ecology. Studies on amphibian metamorphosis are well suited to investigate this aspect. We propose a species-specific model to predict the optimal metamorphosis point for frog individuals with different larval growth trajectories. Because overall fitness will be determined throughout both aquatic and terrestrial stages, we included growth and survival rates of aquatic and terrestrial stages in the fitness equation. Then we conducted a rearing experiment on a brown frog, Rana ornativentris, as an example to obtain the size at metamorphosis, larval period, and larval growth trajectory. Based on these results, we determined the model's parameters to fit the actual metamorphosis patterns. Because the parameters are supposed to be evolutionarily maintained, our data-driven approach enabled obtaining fundamental ecological information (evolutionally-based life-history parameters) of the target species. Comparing the parameters among species will allow us to understand the mechanisms in determining life-history transition more deeply.

SUBMITTER: Iwai N 

PROVIDER: S-EPMC10545764 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

altmetric image

Publications

Species-specific model to predict amphibian metamorphosis.

Iwai Noriko N   Tachiki Yuuya Y  

Scientific reports 20231002 1


Exploring the timing of life-history transitions has been a pivotal focus in the field of evolutionary ecology. Studies on amphibian metamorphosis are well suited to investigate this aspect. We propose a species-specific model to predict the optimal metamorphosis point for frog individuals with different larval growth trajectories. Because overall fitness will be determined throughout both aquatic and terrestrial stages, we included growth and survival rates of aquatic and terrestrial stages in  ...[more]

Similar Datasets

| S-EPMC8362105 | biostudies-literature
| S-EPMC6530347 | biostudies-literature
| S-EPMC9554713 | biostudies-literature
| S-EPMC3569864 | biostudies-literature
| S-EPMC4507497 | biostudies-literature
| S-EPMC5680631 | biostudies-literature
| S-EPMC3512013 | biostudies-literature
| S-EPMC5413923 | biostudies-literature
| S-EPMC1198380 | biostudies-other
2012-11-01 | E-GEOD-37135 | biostudies-arrayexpress