Refereed journal article or data article (A1)
Revealing floristic variation and map uncertainties for different plant groups in western Amazonia
List of Authors: Zuquim Gabriela, Tuomisto Hanna, Chaves Pablo P, Emilio Thaise, Moulatlet Gabriel M, Ruokolainen Kalle, Van Doninck Jasper, Balslev Henrik
Publisher: WILEY
Publication year: 2021
Journal: Journal of Vegetation Science
Journal name in source: JOURNAL OF VEGETATION SCIENCE
Journal acronym: J VEG SCI
Article number: ARTN e13081
Volume number: 32
Number of pages: 12
ISSN: 1100-9233
eISSN: 1654-1103
DOI: http://dx.doi.org/10.1111/jvs.13081
URL: https://onlinelibrary.wiley.com/doi/10.1111/jvs.13081
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/67967121
Questions: Understanding spatial variation in floristic composition is crucial to quantify the extent, patchiness and connectivity of distinct habitats and their spatial relationships. Broad-scale variation in floristic composition and the degree of uniqueness of different regions remains poorly mapped and understood in several areas across the globe. We here aim to map vegetation heterogeneity in Amazonia. Location Middle Jurua river region, Amazonas State, Brazil.
Methods: We mapped four plant groups by applying machine learning to scale up locally observed community composition and using environmental and remotely sensed variables as predictors, which were obtained as GIS layers. To quantify how reliable our predictions were, we made an assessment of model transferability and spatial applicability. We also compared our floristic composition map to the official Brazilian national-level vegetation classification.
Results: The overall performance of our floristic models was high for all four plant groups, especially ferns, and the predictions were found to be spatially congruent and highly transferable in space. For some areas, the models were assessed not to be applicable, as the field sampling did not cover the spectral or environmental characteristics of those regions. Our maps show extensive habitat heterogeneity across the region. When compared to the Brazilian vegetation classification, floristic composition was relatively homogeneous within dense forests, while floristic heterogeneity in rainforests classified as open was high.
Conclusion: Our maps provide geoecological characterization of the regions and can be used to test biogeographical hypotheses, develop species distribution models and, ultimately, aid science-based conservation and land-use planning.
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