Nat Commun2026Article

众包生物多样性监测弥补了全球植物性状图谱的空白

Crowdsourced biodiversity monitoring fills gaps in global plant trait mapping

Daniel Lusk · Sophie Wolf · Daria Svidzinska · Carsten F. Dormann · Jens Kattge · Helge Bruelheide · Francesco Maria Sabatini · Gabriella Damasceno · Álvaro Moreno Martínez · Cyrille Violle · Daniel Hending · Georg J. A. Hähn · Solana Tabeni · Shyam Phartyal · Fernando Gonçalves · Holger Kreft · Marco Schmidt · Han Chen · Behlül Güler · Jiri Dolezal · Remigiusz Pielech · Anaclara Guido · Ciara Dwyer · Francesca Napoleone · Jacob Willie · André Luís Gasper · Manuel J. Macía · Milan Chytry · Jonathan Lenoir · Dinesh Thakur · Jürgen Dengler · Sebastian Świerszcz · Jan Altman · Ladislav Mucina · Ashish N. Nerlekar · Kaoru Kakinuma · Pravin Rawat · Zvjezdana Stančić · Riccardo Testolin · Mohamed Z. Hatim · Flávio Rodrigues · Jürgen Homeier · Marcia C. M. Marques · James K. McCarthy · M. A. El-Sheikh · Kirill Korznikov · Kilian Gerberding · Teja Kattenborn

1. 信息

DOI10.1038/s41467-026-68996-y

期刊Nature Communications / Nat Commun

类型Article

发表2026-01-30 （online）

卷期页17(1): 1203

收录2026-10-03

被浏览…

关键词plant functional traits citizen science vegetation survey trait measurement Earth observation data spatial transferability ecosystem functioning biogeochemical processes conservation

标签—

2. 摘要

植物功能性状是生态系统动态和地球系统过程的基础，但其全球特征受限于可用的实地调查和性状测量。近年来，生物多样性数据聚合的扩展——包括植被调查、公民科学观测和性状测量——为克服这些限制提供了新机遇。在这里，我们证明将这些多样化的数据源与高分辨率地球观测数据相结合，能够以高达 1 公里 (2) 分辨率的精度对关键植物性状进行建模。我们的方法实现了高达 0.63 的相关性（31 种性状中有 15 种超过 0.50），并提高了空间可转移性，有效地弥补了欠采样区域的空白。通过捕捉具有高空间覆盖率的广泛性状，这些图谱可以增强对植物群落特性和生态系统功能的理解，同时作为建模全球生物地球化学过程和指导保护工作的工具。我们的框架突出了众包生物多样性数据在解决全球植物性状建模中长期存在的推演挑战方面的强大作用，随着数据收集和遥感技术的持续进步，将进一步提升对生物圈性状特征的理解。

原文摘要（English）

Plant functional traits are fundamental to ecosystem dynamics and Earth system processes, but their global characterization is limited by available field surveys and trait measurements. Recent expansions in biodiversity data aggregation—including vegetation surveys, citizen science observations, and trait measurements—offer new opportunities to overcome these constraints. Here we demonstrate that combining these diverse data sources with high-resolution Earth observation data enables accurate modeling of key plant traits at up to 1 km 2 resolution. Our approach achieves correlations up to 0.63 (15 of 31 traits exceeding 0.50) and improved spatial transferability, effectively bridging gaps in under-sampled regions. By capturing a broad range of traits with high spatial coverage, these maps can enhance understanding of plant community properties and ecosystem functioning, while serving as tools for modeling global biogeochemical processes and informing conservation efforts. Our framework highlights the power of crowdsourced biodiversity data in addressing longstanding extrapolation challenges in global plant trait modeling, with continued advancements in data collection and remote sensing poised to further refine trait-based understanding of the biosphere.

3. 图表

4. 引用

Lusk D, Wolf S, Svidzinska D, et al. Crowdsourced biodiversity monitoring fills gaps in global plant trait mapping[J]. Nature Communications, 2026, 17(1): 1203. DOI: 10.1038/s41467-026-68996-y.

查看 BibTeX

@article{lusk2026,
  author = {Daniel Lusk and Sophie Wolf and Daria Svidzinska and Carsten F. Dormann and Jens Kattge and Helge Bruelheide and Francesco Maria Sabatini and Gabriella Damasceno and Álvaro Moreno Martínez and Cyrille Violle and Daniel Hending and Georg J. A. Hähn and Solana Tabeni and Shyam Phartyal and Fernando Gonçalves and Holger Kreft and Marco Schmidt and Han Chen and Behlül Güler and Jiri Dolezal and Remigiusz Pielech and Anaclara Guido and Ciara Dwyer and Francesca Napoleone and Jacob Willie and André Luís Gasper and Manuel J. Macía and Milan Chytry and Jonathan Lenoir and Dinesh Thakur and Jürgen Dengler and Sebastian Świerszcz and Jan Altman and Ladislav Mucina and Ashish N. Nerlekar and Kaoru Kakinuma and Pravin Rawat and Zvjezdana Stančić and Riccardo Testolin and Mohamed Z. Hatim and Flávio Rodrigues and Jürgen Homeier and Marcia C. M. Marques and James K. McCarthy and M. A. El-Sheikh and Kirill Korznikov and Kilian Gerberding and Teja Kattenborn},
  title = {Crowdsourced biodiversity monitoring fills gaps in global plant trait mapping},
  journal = {Nature Communications},
  year = {2026},
  volume = {17},
  number = {1},
  pages = {1203},
  doi = {10.1038/s41467-026-68996-y},
  publisher = {Springer Science and Business Media LLC},
}

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