Harmonizing plant metabarcoding pipelines in Europe to support monitoring activities in the field of plants and their functional organismic networks

植物作为自养生物，是陆地生态系统的驱动力。据估计，每五种植物中就有两种面临灭绝的威胁，这可能也会影响其他生物。植物元生物编码(用于分类鉴定的环境DNA(EDNA)分析)可以标准化和自动化，适合大规模、高通量、长期监测，并能够以以前无法达到的规模和精度进行生物多样性调查。欧洲所有的保护倡议都是以物种出现为基础的，而指示物种构成了保护决策的基础。然而，公共和私营部门的利益相关者需要快速、准确和具有成本效益的方法来监测植物生物多样性。跨国和跨学科的METAPLANTCODE项目将测试、优化和提供关于植物变种编码的泛欧洲案例研究的最佳做法建议，优化物种识别的分析管道，并开发易于使用的参考数据库，以便在欧洲和各国的基础设施中实施。将确定并具体说明差距。将与BioSCAN Europe、ELEXIR社区和其他组织合作，出版和组织关于在GBIF和INSDC数据库中公平发布植物元码数据的最佳实践文件。通过使用人工智能，将在独立的元编码分析的新工具中实施多模式DL模型，与Elxir基础设施兼容，以利用多个数据源进行物种级别的识别(序列数据、文本数据、分类数据集和生态分析)。我们将通过GBIF数据集和元数据(GBIF、EUNIS、Biolflor)提高物种鉴定的准确性，并通过Col Checklist Bank将区域、国家和国际植物分类清单、红色名录和植物区系动员到生命目录(COL)中进行物种水平鉴定。分类和植物区系文献将通过新的实体识别和关系提取模块在语义上得到丰富，以支持通过特定领域的描述性/表型特征(例如，生境、特征、土壤特征、生物相互作用)对物种进行优化的元码编码识别。提供接口以将分类名称链接到处理、标识同音异义词和同义词，例如用于植物区系、红色清单和生态处理的转换和注释。在项目结束时，所有METAPLANTCODE产品将公平+可用。从项目开始，将促进与参与伙伴和利益攸关方的知识转移。将确定相关利益攸关方，确定优先事项，建立、监测和根据需要修订沟通渠道。我们将加大努力，让利益攸关方参与进来，并进行培训和推广，以确保植物元生物编码在未来欧洲和其他地区被用作生物多样性监测的常规标准。

Plants, as autotrophs, are the drivers of terrestrial ecosystems. It is estimated that two out of five plant species are threatened with extinction, which probably also affects other organisms. Plant metabarcoding (the analysis of environmental DNA (eDNA) for taxonomic identification) can be standardized and automated, suits large-scale, high-throughput, long-term monitoring, and enables biodiversity surveys at a scale and accuracy previously unattainable. All European conservation initiatives are based on species occurrence, and indicator species form the basis for conservation decision-making. However, public and private sector stakeholders need rapid, accurate, and cost-effective methods to monitor plant biodiversity. The transnational and transdisciplinary METAPLANTCODE project will test, optimize and provide best practice recommendations for pan-European case studies on plant metabarcoding, optimize analysis pipelines for species identification and develops easy-to-use reference databases to be implemented in European and national infrastructures. Gaps will be identified and specified. In collaboration with BIOSCAN Europe, ELIXIR communities and others, best practice documents on FAIR publication of plant metabarcode data in GBIF and INSDC databases will be published and organized. Through the use of AI, multimodal DL models will be implemented in novel tools for stand-alone metabarcoding analyses, compatible with the ELIXIR infrastructure, to leverage multiple data sources for species-level identification (sequence data, text data, taxonomic classification datasets, and ecological analyses). We will improve the accuracy of species identification through GBIF datasets and metadata (GBIF, EUNIS, Biolflor) and incorporate regional, national, and international botanical taxonomic checklists, Red Lists, and floras for species level identification by mobilization to the Catalogue of Life (COL) through COL ChecklistBank. The taxonomic and floristic literature will be semantically enriched with new entity recognition and relationship extraction modules to support optimized metabarcoding identification of species by domain-specific descriptive/phenotypic features (e.g., habitats, features, soil characteristics, biotic interactions). An interface is provided to link taxonomic names to treatments, identify homonyms and synonyms, e.g., for conversion and annotation of flora, red lists, and ecological treatments. At project end, all METAPLANTCODE products will be FAIR+ available. From project start on knowledge transfer with participating partners and stakeholders will be fostered. Relevant stakeholders will be identified, priorities set, communication channels established, monitored and revised as needed. We will increase efforts to engage stakeholders and conduct training and outreach to ensure that plant metabarcoding is routinely used as a standard for biodiversity monitoring in Europe and beyond in the future.