We examined sexual size dimorphism （SSD）, mating pattem, fertilization efficiency and female reproductive traits in two bufonid toads （Bufo gargarizans and Duttaphrynus melanostictus） to test the idea that importa...We examined sexual size dimorphism （SSD）, mating pattem, fertilization efficiency and female reproductive traits in two bufonid toads （Bufo gargarizans and Duttaphrynus melanostictus） to test the idea that importance of male body size for egg fertilization success depends on the mating pattern. Female-biased SSD was evident only in D. melanostictus. Female B. gar- garizans laid fewer larger eggs nearly three months earlier than did female D. melanostictus. Fertilization efficieneies on average were higher in B. gargarizans （95%） than in D. melanostictus （91%）. Though differing in the degree of SSD, body size, breeding season, clutch size, egg size and fertilization efficiency, the two toads were similar in four aspects： （1） both showed size-assortative mating; （2） females did not tradeoff egg size against egg number; （3） male size, clutch size and clutch dry mass were greater in male-larger than in female-larger pairs after accounting for female snout-vent length （SVL）; and （4） the ratio of male to female SVL did not affect fertilization efficiency. Our data show that： （1） a female preference for large males is likely not important in terms of egg fertilization success; （2） a male preference for large females is likely important because larger females are more fecund; and （3） size-assortative mating arises from a male preference for large females. Our study demonstrates that male size is not always important for egg fertilization success in anurans that show size-assortative mating.展开更多
Large-scale empirical data, the sample size and the dimension are high, often exhibit various characteristics. For example, the noise term follows unknown distributions or the model is very sparse that the number of c...Large-scale empirical data, the sample size and the dimension are high, often exhibit various characteristics. For example, the noise term follows unknown distributions or the model is very sparse that the number of critical variables is fixed while dimensionality grows with n. The authors consider the model selection problem of lasso for this kind of data. The authors investigate both theoretical guarantees and simulations, and show that the lasso is robust for various kinds of data.展开更多
文摘We examined sexual size dimorphism （SSD）, mating pattem, fertilization efficiency and female reproductive traits in two bufonid toads （Bufo gargarizans and Duttaphrynus melanostictus） to test the idea that importance of male body size for egg fertilization success depends on the mating pattern. Female-biased SSD was evident only in D. melanostictus. Female B. gar- garizans laid fewer larger eggs nearly three months earlier than did female D. melanostictus. Fertilization efficieneies on average were higher in B. gargarizans （95%） than in D. melanostictus （91%）. Though differing in the degree of SSD, body size, breeding season, clutch size, egg size and fertilization efficiency, the two toads were similar in four aspects： （1） both showed size-assortative mating; （2） females did not tradeoff egg size against egg number; （3） male size, clutch size and clutch dry mass were greater in male-larger than in female-larger pairs after accounting for female snout-vent length （SVL）; and （4） the ratio of male to female SVL did not affect fertilization efficiency. Our data show that： （1） a female preference for large males is likely not important in terms of egg fertilization success; （2） a male preference for large females is likely important because larger females are more fecund; and （3） size-assortative mating arises from a male preference for large females. Our study demonstrates that male size is not always important for egg fertilization success in anurans that show size-assortative mating.
基金supported by the National Natural Science Foundation of China(No.11671059)
文摘Large-scale empirical data, the sample size and the dimension are high, often exhibit various characteristics. For example, the noise term follows unknown distributions or the model is very sparse that the number of critical variables is fixed while dimensionality grows with n. The authors consider the model selection problem of lasso for this kind of data. The authors investigate both theoretical guarantees and simulations, and show that the lasso is robust for various kinds of data.
