Assessing the multidimensional complexity of biodiversity using a globally standardized approach

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Authors

Robert M McElderry , Camille Fournier de Lauriere , Charbel El Khoury, Priyanka Chaudhary, Shivakumara Manu, Felix Specker, Ian Brettell, Johan van den Hoogen , Daniel Maynard, Carolina Bello Lozano, Lalasia Bialic-Murphy, Camille S Delavaux, Daisy H Dent, Thomas Elliott, Laura G van Galen, Thomas Lauber, Andrea Paz Velez, Gabriel Smith, Leland K Werden, Constantin M Zohner, Thomas W Crowther

Abstract

Quantifying biodiversity across the globe is critical for transparent reporting and assessment under the Kunming-Montreal Global Biodiversity Framework. Understanding the complexity of biodiversity requires consideration of the variation of life across genes, species, and ecosystems. Achieving this in a standardized way remains a key challenge for creating an equitable nature positive future. Here, we present the Sustainable Ecology and Economic Development (SEED) framework, which assesses the dimensions that structure biodiversity patterns worldwide (genetics, species, and ecosystems) across plants, animals, and microbial taxa, and consolidates this into a single measure of biocomplexity at every location, relative to a ‘reference’ ecosystem with minimal human disturbance. We describe the SEED methodology and highlight its features, which include seven novel measures of biodiversity intactness that are integrated into the SEED biocomplexity index. SEED will continuously integrate new datasets and maps to provide up-to-date estimates of local biocomplexity across the planet, providing a tool for decision makers to assess and improve the global state of nature.  

DOI

https://doi.org/10.32942/X2689N

Subjects

Biodiversity, Life Sciences

Keywords

Biocomplexity, Biodiversity Monitoring, biodiversity intactness, genetic diversity, species diversity, ecosystem diversity

Dates

Published: 2023-08-25 17:46

Last Updated: 2024-11-12 13:14

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License

CC BY Attribution 4.0 International

Additional Metadata

Language:
English

Data and Code Availability Statement:
Open data/code are not available with this preprint.

Conflict of interest statement:
The Restor platform (Restor Eco AG) was founded by and spun out from the Crowther Lab at ETH Zurich, and is wholly owned and financed by the Restor Foundation. None of the authors own any shares in Restor. TCW is the President of the Council of the Restor Foundation and a member of Restor’s Science Advisory Council.