Establishing macroecological trait datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide
Establishing macroecological trait datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide
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DOI：
10.1002/ece3.1136
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发表时间：
2014-07-01
影响因子：
2.6
通讯作者：
Svenning, Jens-Christian
中科院分区：
文献类型：
--
作者：
Kissling, Wilm Daniel;Dalby, Lars;Svenning, Jens-Christian
生态性状数据对于了解生物多样性的大尺度分布及其对全球变化的响应至关重要。对于动物来说，饮食代表了物种进化适应、生态和功能角色以及营养相互作用的一个基本方面。然而，饮食对宏观进化和宏观生态动力学的重要性仍然很少被探索，部分原因是缺乏全面的性状数据集。我们编制并评估了一个全面的全球哺乳动物饮食偏好数据集（“MammalDIET”）。从两个全球和全谱系的数据源对饮食信息进行数字化，并评估多个数据记录者的数据输入错误。然后，我们开发了一种分层外推程序来填补缺失信息的物种的饮食信息。缺失的数据用其他分类水平（属、同一属或科内的其他物种）的信息进行外推，并随后在内部（使用对已编译的物种水平饮食数据应用的折刀法）和外部（使用来自全大陆综合数据源的独立物种水平饮食信息）验证这种外推。最后，我们将哺乳动物物种划分为营养等级和饮食行会，并在全球范围内绘制了这些饮食类别的物种丰富度及其占总丰富度的比例，得到了较好的验证结果。正确数字化数据的成功率为94%，说明多台记录仪数据录入一致性高。数据来源提供了总共2033种（占IUCN分类的5364种陆生哺乳动物的38%）的物种水平的饮食信息。其余3331种的饮食信息主要来自属水平的外推（占所有陆生哺乳动物种类的48%），很少来自同一属的其他物种（6%）或科水平（8%）。内部和外部验证表明：(1)外推法在主要食品项目上最可靠；(2)“动物”、“哺乳动物”、“无脊椎动物”、“植物”、“种子”、“水果”和“叶子”等几个饮食类别的正确预测比例较高；(3)正确推断特定饮食类别的潜力在进化支内部和进化支之间都是不同的。全球物种丰富度和比例图显示营养水平之间的一致性，但饮食行业之间也存在实质性差异。MammalDIET为全世界所有陆生哺乳动物提供了一个全面、独特和免费的饮食偏好数据集。它可以对特定营养水平和饮食行会进行大规模的分析，并在全球范围内首次评估哺乳动物饮食偏好的性状保守性。数字化、外推和验证程序可以转移到其他性状数据和分类群。
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.