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Título : Revealing floristic variation and map uncertainties for different plant groups in western Amazonia
Autor : Zuquim, Gabriela
Tuomisto, Hanna
Thaise, Emilio
Perez, Pablo
Ruokolainen, Kalle
Massaine Moulatlet, Gabriel
Van doninck, Jasper
Balslev, Henrik
Palabras clave : Plant community
Área of applicability
Remote sensing
Vegetation mapping,
Tropical forests,
Species-environmental relationships
Niche,
Juruá river,
Machine learning
Amazonian biogeography
Ferns
Palms
Melastomataceae
Zingiberales
Fecha de publicación : 2021
Editorial : Scopus
Citación : Zuquim, Gabriela & Tuomisto, Hanna & Perez, Pablo & Emilio, Thaise & Moulatlet, G. & Ruokolainen, Kalle & Van doninck, Jasper & Balslev, Henrik. (2021). Revealing floristic variation and map uncertainties for different plant groups in western Amazonia. Journal of Vegetation Science. 32. 10.1111/jvs.13081.
Citación : PRODUCIÓN CIENTIFICA- ARTÍCULOS CIENTÍFICOS;A-IKIAM-000290
Resumen : 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 Juruá 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 remote 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.
URI : http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/524
ISSN : DOI:10.1111/jvs.13081
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