Mapping the spatial distribution of wetlands in Argentina (South America) from a fusion of national databases
Irene Fabricante
A , Priscilla Minotti A and Patricia Kandus A *
+ Author Affiliations
- Author Affiliations
A Laboratorio de Ecología, Teledetección y Ecoinformática (LETyE), Instituto de Investigación e Ingeniería Ambiental (3iA), Universidad Nacional de San Martín (UNSAM), Campus Miguelete, 25 de Mayo y Francia, CP 1650 San Martín, Argentina.
Marine and Freshwater Research - https://doi.org/10.1071/MF22111
Submitted: 24 September 2022 Accepted: 16 October 2022 Published online: 14 November 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing
Abstract
Context: There a large information gap on the spatial distribution and diversity of wetland types in South America.
Aims: We focus on mapping the spatial distribution of broad wetland types in Argentina, based on the integration of open spatial data sources developed by national government agencies.
Methods: We designed a two-tier process, as follows: we filtered broad wetland types described in the attributes of the spatial datasets and created a separate vector layer for each wetland class; we then ensembled the layers by populating a 25-m cell raster template.
Key results: Our WetCarto_AR layer indicates that wetlands cover 13.5% of mainland Argentina, being distributed throughout the country with a greater concentration towards the north-east, but patchy in the rest of the country. Palustrine is the dominant wetlands class followed by Riparian and Lacustrine. Global datasets underestimated wetland coverage, although the same large wetlands are recognised in all.
Conclusions: Our results make visible the known spatial extent of wetlands in Argentina and provide information to feed or validate global models.
Implications: Results stress the importance of existing local databases, which, even when generated for other purposes, can be a starting point for country or region wetland mapping.
Keywords: Argentina, global wetland datasets, local spatial datasets, national databases, spatial dataset integration, spatial distribution of wetlands, wetland mapping, wetland types diversity.
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