Moutouama Jacob K, Compagnoni Aldo, Miller Tom E X
Department of BioSciences, Program in Ecology and Evolutionary Biology, Rice University, Houston, TX 77005.
Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale) 06120, Germany.
Proc Natl Acad Sci U S A. 2025 May 27;122(21):e2422162122. doi: 10.1073/pnas.2422162122. Epub 2025 May 20.
Global climate change has triggered an urgent need for predicting the reorganization of Earth's biodiversity. For dioecious species (those with separate sexes), it is unclear how commonly unique climate sensitivities of females and males could influence projections for species-level responses to climate change. We developed demographic models of range limitation, parameterized from geographically distributed common garden experiments, with females and males of a dioecious grass species () throughout and beyond its range in the south-central U.S. We contrasted predictions of a standard female-dominant model with those of a two-sex model that accounts for feedbacks between sex ratio and vital rates. Both model versions predict that future climate change will induce a poleward shift of niche suitability beyond current northern limits. However, the magnitude of the poleward shift was underestimated by the female-dominant model because females have broader temperature tolerance than males but become mate-limited under female-biased sex ratios, which are forecasted to become more common under future climate. Our results illustrate how explicitly accounting for both sexes can enhance population viability forecasts and conservation planning for dioecious species in response to climate change.
全球气候变化引发了预测地球生物多样性重组的迫切需求。对于雌雄异株物种(即具有不同性别的物种),尚不清楚雌性和雄性独特的气候敏感性在多大程度上会影响对物种层面气候变化响应的预测。我们开发了范围限制的人口统计学模型,该模型根据地理分布的共同园实验进行参数化,涵盖了美国中南部一种雌雄异株草本植物()在其分布范围内及范围外的雌性和雄性个体。我们将标准的以雌性为主导的模型预测结果与考虑了性别比例和生命率之间反馈的两性模型的预测结果进行了对比。两个模型版本都预测,未来气候变化将导致生态位适宜性向北移动,超出当前的北部界限。然而,以雌性为主导的模型低估了向北移动的幅度,因为雌性比雄性具有更宽的温度耐受性,但在雌性偏向的性别比例下会受到配偶限制,预计在未来气候条件下这种情况会更加普遍。我们的结果表明,明确考虑两性因素如何能够增强对雌雄异株物种应对气候变化的种群生存能力预测和保护规划。