Max Planck Institute for Biogeochemistry, Jena, Germany.
German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Glob Chang Biol. 2020 Jan;26(1):119-188. doi: 10.1111/gcb.14904. Epub 2019 Dec 31.
Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
植物性状——植物的形态、解剖、生理、生化和物候特征——决定了植物如何对环境因素做出反应，影响其他营养级，影响生态系统的性质及其对人类的益处和危害。因此，植物性状数据是从进化生物学、群落和功能生态学，到生物多样性保护、生态系统和景观管理、恢复、生物地理学和地球系统建模等广泛研究领域的基础。自 2007 年成立以来，TRY 植物性状数据库不断发展。它现在根据开放获取数据政策提供前所未有的数据覆盖范围，是全球研究界使用的主要植物性状数据库。TRY 数据库越来越支持基于性状的植物研究的新前沿，包括确定数据差距以及随后调动或测量新数据。为了支持这一发展，本文评估了 TRY 中编译的性状数据的范围，并分析了数据覆盖范围和代表性的新兴模式。分类性状的最佳物种覆盖率最高——几乎完全涵盖“植物生长形式”。然而，与生态学和植被建模相关的大多数性状都具有连续的种内变异和性状-环境关系。这些性状必须在其各自的环境中对个体植物进行测量。尽管数据覆盖范围前所未有，但我们观察到，在许多方面，这些连续性状的完整性和代表性都令人谦卑地缺乏。因此，我们得出结论，减少 TRY 数据库中的数据差距和偏差仍然是一个关键挑战，需要协调一致的方法来调动数据和进行性状测量。这只能通过与其他倡议合作来实现。
