Open Access Open Badges Research article

Forgotten forests - issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study

Tiina Särkinen1*, João RV Iganci2, Reynaldo Linares-Palomino3, Marcelo F Simon4 and Darién E Prado5

Author affiliations

1 Department of Botany, Natural History Museum, Cromwell Road, London SW7 5BD, UK

2 Universidade Federal do Rio Grande do Sul, Programa de Pós-Graduação em Botânica, Av. Bento Gonçalves, 9500 - Prédio 43433, Bloco 4 - Sala 214, Campus do Vale, Porto Alegre- RS 91501-970, Brazil

3 Herbario Forestal MOL, Universidad Nacional Agraria La Molina, Apartado 456, Lima 1, Peru

4 Embrapa Recursos Genéticos e Biotechnologia, PqEB, Caixa Postal 02372, Brasilia-DF 70770-917, Brazil

5 Facultad de Ciencias Agrarias, Universidad Nacional de Rosario. P.O. Box N°14, S2125ZAA Zavalla, Argentina

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Citation and License

BMC Ecology 2011, 11:27  doi:10.1186/1472-6785-11-27

Published: 24 November 2011



South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF) biome using herbarium data of habitat specialist species.


Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1) poor spatial resolution, and (2) poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM) approach where georeferenced herbarium data is used in conjunction with bioclimatic data.


Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in biome mapping, and could be particularly useful for mapping poorly known, fragmented, or degraded vegetation. We wish to highlight that biome delimitation is not an exact science, and that transparency is needed on how biomes are used as study units in macroevolutionary and ecological research.