Wells, L.H., Dexter, K.G., Pennington, R.T. et al. (5 more authors) (2025) Satellite remote sensing can operationalise the IUCN Global Ecosystem Typology in the biome-diverse North-East of Brazil. Frontiers of Biogeography, 18. e145498. ISSN 1948-6596
Abstract
Accurate biome delineation is difficult where biomes occupy the same climatic space, as is the case for tropical dry forest and savanna. The resulting confusion limits our ability to understand and manage impacts of global change on these biomes. To address this, we developed an unsupervised, repeatable method to delineate biomes and their component functional ecosystems, based on landscape-level vegetation structure measured using remote sensing and an understanding of the ecology of the region. This approach contrasts with previous definitions, based on climate differences amongst savanna, dry forest and rain forest.
Using the heterogeneous north-east Brazil, where several biomes interdigitate, as a case study, a hierarchical functional ecosystem classification is proposed that aligns with both the IUCN Global Ecosystem Typology (GET) and previous work. Based on fuzzy clustering of remotely sensed vegetation attributes, seven groups were found, identified as rain forest, cerrado (savanna) and five caatinga vegetation groups. These groups broadly align with the literature, for example, sedimentary and arboreal caatinga. These groups align with three ‘Ecosystem Functional Groups’ (EFGs) described by the IUCN GET and, additionally, suggest there is a new, fourth EFG in the region: non-pyric shrublands. Random Forest models showed soil pH was the most important environmental variable distinguishing these vegetation groups.
These results suggest a remotely sensed structure-based approach is an effective method for operationalising the IUCN GET. North-East Brazil – where many EFGs are interdigitated – serves as a challenging case study and, therefore, we hope our approach will have generality for other regions globally.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Ⓒ Lucy H. Wells et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Keywords: | Biome; Brazil; caatinga; IUCN; remote sensing; soil; vegetation structure |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Mar 2025 21:33 |
Last Modified: | 17 Mar 2025 21:33 |
Status: | Published |
Publisher: | Pensoft Publishers |
Identification Number: | 10.21425/fob.18.145498 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:224452 |