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Establishing macroecological trait datasets: digitalization extrapolation and validation of diet preferences in terrestrial mammals worldwide

机译:建立宏观生态特征数据集:全球陆生哺乳动物的数字化外推法和饮食偏好验证

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摘要

Ecological trait data are essential for understanding the broad-scale distribution of biodiversity and its response to global change. For animals, diet represents a fundamental aspect of species’ evolutionary adaptations, ecological and functional roles, and trophic interactions. However, the importance of diet for macroevolutionary and macroecological dynamics remains little explored, partly because of the lack of comprehensive trait datasets. We compiled and evaluated a comprehensive global dataset of diet preferences of mammals (“MammalDIET”). Diet information was digitized from two global and cladewide data sources and errors of data entry by multiple data recorders were assessed. We then developed a hierarchical extrapolation procedure to fill-in diet information for species with missing information. Missing data were extrapolated with information from other taxonomic levels (genus, other species within the same genus, or family) and this extrapolation was subsequently validated both internally (with a jack-knife approach applied to the compiled species-level diet data) and externally (using independent species-level diet information from a comprehensive continentwide data source). Finally, we grouped mammal species into trophic levels and dietary guilds, and their species richness as well as their proportion of total richness were mapped at a global scale for those diet categories with good validation results. The success rate of correctly digitizing data was 94%, indicating that the consistency in data entry among multiple recorders was high. Data sources provided species-level diet information for a total of 2033 species (38% of all 5364 terrestrial mammal species, based on the IUCN taxonomy). For the remaining 3331 species, diet information was mostly extrapolated from genus-level diet information (48% of all terrestrial mammal species), and only rarely from other species within the same genus (6%) or from family level (8%). Internal and external validation showed that: (1) extrapolations were most reliable for primary food items; (2) several diet categories (“Animal”, “Mammal”, “Invertebrate”, “Plant”, “Seed”, “Fruit”, and “Leaf”) had high proportions of correctly predicted diet ranks; and (3) the potential of correctly extrapolating specific diet categories varied both within and among clades. Global maps of species richness and proportion showed congruence among trophic levels, but also substantial discrepancies between dietary guilds. MammalDIET provides a comprehensive, unique and freely available dataset on diet preferences for all terrestrial mammals worldwide. It enables broad-scale analyses for specific trophic levels and dietary guilds, and a first assessment of trait conservatism in mammalian diet preferences at a global scale. The digitalization, extrapolation and validation procedures could be transferable to other trait data and taxa.
机译:生态特征数据对于理解生物多样性的广泛分布及其对全球变化的响应至关重要。对于动物而言,饮食代表着物种进化适应,生态和功能角色以及营养相互作用的基本方面。然而,饮食对于宏观进化和宏观生态动力学的重要性仍然很少被探索,部分原因是缺乏综合性状数据集。我们编译并评估了哺乳动物饮食偏好的综合全球数据集(“ MammalDIET”)。饮食信息从两个全球性和进化范围的数据源中数字化,并评估了多个数据记录器的数据输入错误。然后,我们开发了一种层次外推程序,以针对缺少信息的物种填写饮食信息。缺失的数据可以用其他分类学级别(属,同一属或家族中的其他物种)的信息进行推断,随后,这种推断在内部(对所汇编的物种水平饮食数据应用千斤顶刀方法)和外部都得到了验证。 (使用来自整个洲际数据源的独立物种级饮食信息)。最后,我们将哺乳动物物种分为营养水平和饮食行会,并且针对这些饮食类别在全球范围内绘制了其物种丰富度及其在总丰富度中的比例,并获得了良好的验证结果。正确数字化数据的成功率为94%,表明多个记录器之间数据输入的一致性很高。数据来源提供了总共2033种物种的物种级饮食信息(根据IUCN分类法,在所有5364种陆生哺乳动物物种中占38%)。对于其余的3331种,饮食信息大部分是从属水平的饮食信息(占所有陆生哺乳动物的48%)中推断出来的,很少是从同属其他物种(6%)或家庭水平(8%)中推断的。内部和外部验证表明:(1)外推法对主要食品最为可靠; (2)几种饮食类别(“动物”,“哺乳动物”,“无脊椎动物”,“植物”,“种子”,“水果”和“叶”)具有正确预测的饮食等级比例; (3)正确推断特定饮食类别的潜力在进化枝内部和进化枝之间有所不同。全球物种丰富度和比例图显示营养水平之间的一致性,但饮食行会之间也存在实质性差异。 MammalDIET为全球所有陆栖哺乳动物提供了饮食偏好的全面,独特且免费的数据集。它可以对特定营养水平和饮食行会进行大规模分析,并且可以在全球范围内对哺乳动物饮食偏好中的特质保守性进行首次评估。数字化,外推和验证程序可以转移到其他性状数据和分类中。

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