NSFDEB-NERC: Collaborative Research: Informing population models with evolutionary theory to infer species' conservation status

NSFDEB-NERC：合作研究：利用进化理论为种群模型提供信息以推断物种的保护状态

• 批准号: 1556779
• 负责人: Holly Kindsvater
• 金额: $ 74.94万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2019-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1556779&HistoricalAwards=false
• 关键词: NSFDEB; NERC; Collaborative; Research; Informing

Marine species are very hard to census. This is especially true of large, high value fishes that are vulnerable to overfishing because of their biology. For example, one third of shark and ray species are known to have declined in recent history, but it is unknown whether most of the remaining two-thirds are also declining, or if they are stable. Likewise, population sizes of predatory fishes such as groupers and tuna have decreased substantially due to intense fishing, yet little is known about the extent of decline and risk of extinction for some of these species. This project uses the evolutionary history of well-studied related species to provide estimates of basic demographic properties of little-studied species of fisheries and conservation importance. This knowledge provides important information to guide management efforts, such as limits on catch and trade, until more direct research can be carried out. The researchers will also engage in educational outreach on mathematical biology for undergraduates and on marine biodiversity science for the general public. Scientists often have some knowledge of individual traits such as reproductive behavior, lifespan, and metabolic rates of many related fish species, even in the absence of population-level information. Evolutionary theory can predict the co-evolution of these unique trait combinations of various groups. This theory can be used to infer demographic rates and project species' status, but previous efforts have not incorporated the unique details of each species' biology. This project will develop comprehensive theory linking the evolution of these traits to species status projections for tunas, groupers, and sharks and rays. Modern statistical methods will allow information from models of data-rich species, which have formal assessments, to be shared with poorly studied species in similar habitats, or with relatives. With this new understanding of population trajectories, the team will produce recommendations for use by organizations like the International Union for Conservation of Nature, as well as managers and scientists.

海洋物种很难普查。对于大型、高价值的鱼类来说尤其如此，因为它们的生物学特性很容易受到过度捕捞的影响。例如，已知三分之一的鲨鱼和鳐物种在近代历史上已经减少，但尚不清楚其余三分之二的物种是否也在减少，或者它们是否稳定。同样，石斑鱼和金枪鱼等掠食性鱼类的种群数量也因密集捕捞而大幅减少，但对其中一些物种的减少程度和灭绝风险知之甚少。该项目利用经过充分研究的相关物种的进化历史，对很少研究的渔业和养护重要性物种的基本人口特征进行估计。这些知识提供了重要的信息，以指导管理工作，如限制渔获量和贸易，直到可以进行更直接的研究。研究人员还将为本科生开展数学生物学教育推广活动，为公众开展海洋生物多样性科学教育推广活动。科学家通常对许多相关鱼类的个体特征有一些了解，如生殖行为，寿命和代谢率，即使在缺乏种群水平信息的情况下。进化理论可以预测不同群体的这些独特性状组合的共同进化。这一理论可以用来推断人口统计率和项目物种的地位，但以前的努力没有纳入每个物种的生物学的独特细节。该项目将发展综合理论，将这些特征的进化与金枪鱼、石斑鱼、鲨鱼和鳐的物种地位预测联系起来。现代统计方法将允许从数据丰富的物种模型中获得信息，这些模型有正式的评估，可以与相似栖息地中研究不足的物种或亲属共享。有了对种群轨迹的新理解，该团队将提出建议，供国际自然保护联盟等组织以及管理人员和科学家使用。