EDGE Angiosperms: integrating phylogenetics and extinction risk data for conservation prioritisation in flowering plants
EDGE Angiosperms: integrating phylogenetics and extinction risk data for conservation prioritisation in flowering plants
批准号:
2744005
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
灭绝的结果不仅是物种的消失,而且是这些物种所代表的独特的进化历史的消失,包括它们可能表现出的不可替代的特征。从进化角度来看,并非所有物种都是平等的;在生命之树上,一个孤立的物种比一个有几个近亲的新进化物种更能代表独特的进化史。物种灭绝还降低了进化潜力,即一群生物生存和适应未来环境变化的能力。维管植物大约有35万种,其中许多是生态系统的主要组成部分,对无数其他物种的生存至关重要。据估计,40%的植物面临灭绝的危险,因此,了解哪些植物濒临灭绝,它们面临哪些威胁,不仅对保护这些物种,而且对保护整个生态系统至关重要。在保护计划中,哪些物种和地区应该优先考虑,这是一个反复出现的问题,但在相当大比例受到威胁的大型生物群体中,更是如此。对于优化保存生命之树的必要性,人们普遍达成了共识。因此,基于进化历史的指标被提出作为实现保护优先级的选择方法。基于系统发育多样性的概念,已经提出了各种方法。进化独特和全球濒危(EDGE)方法根据物种的进化独特性和它们面临的灭绝风险水平对物种进行排名。这种方法被伦敦动物学会采用,并应用于几个动物群体(www.edgeofexistence.org),但尚未广泛应用于开花植物。该博士项目将为一个正在进行的项目做出贡献,该项目的主要目标是根据开花植物的进化独特性和全球濒危程度,制定一份全球优先保护名单,并确定这些物种在哪里的浓度最高。该项目包括编制所有被子植物物种的合成系统发育树,并根据保护评估直接或间接地估计每个物种面临的灭绝风险。半自动化管道的开发将允许定期重新计算这些进化指标,并提供监测保护工作有效性的客观手段。该项目将需要开发几种新的方法和方法来处理所涉及的大量数据。它还将为我们的合作伙伴On The Edge Conservation提供实习机会,参与他们支持保护和政策的各种活动。我们鼓励学生在最适合他们个人兴趣的方向上发展他们的项目,包括系统发育、大规模数据挖掘、空间分析和机器学习,但很可能包括上述内容的组合。
英文摘要
Extinction results not only in species loss, but also in loss of the unique evolutionary history that these species represent, including the irreplaceable features they may exhibit. Not all species are equal in evolutionary terms; an isolated species on the tree of life represent more unique evolutionary history than a recently evolved species with several close relatives. Species extinction also reduces evolutionary potential, the ability of a group of organisms to survive and adapt to future environmental changes.There are around 350,000 species of vascular plants, many of which are dominant ecosystem components and vital for the survival of countless other species. With 40% of plants estimated to be at risk of extinction, obtaining an overview of which ones are these and which threats they face is central to protecting not only these species, but entire ecosystems. Which species and areas should be prioritised in conservation programmes is a recurrent question, but even more so in large groups of organisms where a sizeable proportion is threatened. There is generally a consensus regarding the need to optimise the preservation of the tree of life. Thus, metrics based on evolutionary history have been proposed as approaches of choice to implement prioritization in conservation. Various methods based on the concept of phylogenetic diversity have been proposed. The Evolutionarily Distinct and Globally Endangered (EDGE) approach ranks species according to their evolutionary distinctiveness and the level of extinction risk they face. This approach was adopted by the Zoological Society of London and applied to several animal groups (www.edgeofexistence.org) but has not been as widely used in flowering plants. This PhD project will contribute to an ongoing programme which main objective is to produce a global priority conservation list for flowering plants based on their evolutionary distinctiveness and global endangerment and determine where these species are found in the highest concentrations. The project involves the compilation of a synthetic phylogenetic tree for all angiosperm species and an estimate of the extinction risk faced by each species, based directly or indirectly on conservation assessments. The development of a semi-automated pipeline will allow a regular re-calculation of these evolutionary metrics and provide objective means of monitoring the effectiveness of conservation efforts. The project will require the development of several novel approaches and methodologies to handle the large amount of data involved. It will also offer an internship with our partner On The Edge Conservation on various activities around their work supporting conservation and policy. The student will be encouraged to develop their project in the direction that best suits their personal interests, including phylogenetics, large scale data mining, spatial analysis, and machine learning, but will most likely comprise a combination of the above.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
海外基金