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母体风险管理通过自然选择阐明了鲨鱼生殖适应性的进化。

Maternal risk-management elucidates the evolution of reproductive adaptations in sharks by means of natural selection.

机构信息

University of South Florida, St. Petersburg Campus, St. Petersburg, FL, 33701, USA.

University of Miami, Miami, FL, 33124, USA.

出版信息

Sci Rep. 2024 Aug 29;14(1):20088. doi: 10.1038/s41598-024-70677-z.

DOI:10.1038/s41598-024-70677-z
PMID:39209898
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11362299/
Abstract

Maternal investment theory is the study of how breeding females allocate resources between offspring size and brood size to achieve reproductive success. In classical trade-off models, r/K-selection and bet-hedging selection, the primary predictors of maternal investments in offspring are population density and resource stability. In crowded, stable environments, K-selected females invest in large offspring at an equivalent cost in brood size. In uncrowded, unstable environments, r-selected females invest in large broods at an equivalent cost in offspring size. In unpredictable resource environments, bet-hedging females invest moderately in brood size and offspring size. The maternal risk-management model represents a profound departure from classical trade-off models. Maternal investments in offspring size, brood size, and brood number are shaped independently by autonomous risk factors: the duration of gaps in resources during seasonal cycles, rates of predation, and unpredictable catastrophic events. To date, no single model has risen to a position of preeminence. Here in sharks, we show that maternal investments within and across species do not agree with the predictions of trade-off models and instead agree with the predictions of the maternal risk-management model. Within and across shark species, offspring size and brood size were independent maternal investment strategies. The risk of starvation favored investments in larger offspring. The risk of predation favored investments in larger broods. If empirical studies continue to confirm its predictions, maternal-risk management may yet emerge as a unifying model of diverse reproductive adaptations by means of natural selection.

摘要

母体投资理论是研究繁殖雌性如何在后代大小和窝仔大小之间分配资源以实现生殖成功的理论。在经典的权衡模型中,r/K 选择和避险选择,母体对子代投资的主要预测因子是种群密度和资源稳定性。在拥挤、稳定的环境中,K 选择的雌性以相当的窝仔大小成本投资于大的后代。在不拥挤、不稳定的环境中,r 选择的雌性以相当的后代大小成本投资于大的窝仔。在资源不可预测的环境中,避险雌性以中等的窝仔大小和后代大小投资。母体风险管理模型代表了对经典权衡模型的深刻背离。母体对子代大小、窝仔大小和窝仔数量的投资是由自主风险因素独立塑造的:季节性周期中资源缺口的持续时间、捕食率和不可预测的灾难性事件。到目前为止,还没有一个单一的模型占据优势地位。在这里,我们在鲨鱼中表明,物种内和物种间的母体投资与权衡模型的预测不一致,而与母体风险管理模型的预测一致。在鲨鱼物种内和物种间,后代大小和窝仔大小是独立的母体投资策略。饥饿的风险有利于投资于更大的后代。捕食的风险有利于投资于更大的窝仔。如果实证研究继续证实其预测,那么母体风险管理可能会作为一种通过自然选择实现多样化生殖适应的统一模型出现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/e77d32739bd6/41598_2024_70677_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/fdeb2eb6c0e3/41598_2024_70677_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/b048f2d22c67/41598_2024_70677_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/0397bcb1671b/41598_2024_70677_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/a97d7b9856a1/41598_2024_70677_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/abb4b3720739/41598_2024_70677_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/e77d32739bd6/41598_2024_70677_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/fdeb2eb6c0e3/41598_2024_70677_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/898062ce6e1c/41598_2024_70677_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/561f16cafdb8/41598_2024_70677_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/b048f2d22c67/41598_2024_70677_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/0397bcb1671b/41598_2024_70677_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/a97d7b9856a1/41598_2024_70677_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/abb4b3720739/41598_2024_70677_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f2/11362299/e77d32739bd6/41598_2024_70677_Fig8_HTML.jpg

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