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: 1555729
• 负责人: Marc Mangel
• 金额: $ 17.6万
• 依托单位: University of California-Santa Cruz
• 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 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1555729&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.

海洋物种很难统计。对于大型、高价值的鱼来说尤其如此，因为它们的生物学特性很容易受到过度捕捞。例如，已知有三分之一的鲨鱼和射线物种在近代史上有所下降，但尚不清楚其余三分之二的物种是否也在下降，或者它们是否稳定。同样，由于密集捕捞，石斑鱼和金枪鱼等捕食性鱼类的种群数量大幅减少，但对其中一些物种的下降程度和灭绝风险知之甚少。该项目利用经过充分研究的近缘物种的进化史来估计鲜有研究的渔业物种的基本人口统计特性和养护重要性。在开展更直接的研究之前，这些知识为指导管理工作提供了重要信息，例如对渔获量和贸易的限制。研究人员还将为本科生开展数学生物学方面的教育推广活动，并为普通公众开展海洋生物多样性科学方面的教育活动。即使在缺乏种群水平的信息的情况下，科学家也往往对许多相关鱼类的生殖行为、寿命和代谢率等个体特征有一定的了解。进化论可以预测不同群体的这些独特特征组合的共同进化。这一理论可以用来推断人口统计比率和预测物种的地位，但以前的努力并没有纳入每个物种生物学的独特细节。该项目将开发综合理论，将这些特征的进化与金枪鱼、石斑鱼、鲨鱼和射线的物种状况预测联系起来。现代统计方法将允许来自数据丰富的物种模型的信息与类似生境中研究较少的物种或亲属共享，这些模型有正式的评估。有了对人口轨迹的新理解，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。