Predicting environmental gradients with fern species composition in Brazilian Amazonia
Aim: A major problem for conservation in Amazonia is that species distribution maps are inaccurate. Consequently, conservation planning needs to be based on other information sources such as vegetation and soilmaps, which are also inaccurate. We propose and test the use of biotic data on a common an...
| Autor principal: | Zuquim, Gabriela |
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| Outros Autores: | Tuomisto, Hanna, Jones, Mirkka M., Prado, J., Figueiredo, Fernando Oliveira Gouvêa, Moulatlet, Gabriel M., Costa, Flávia Regina Capellotto, Quesada, Carlos Alberto, Emilio, Thaise |
| Grau: | Artigo |
| Idioma: | English |
| Publicado em: |
Journal of Vegetation Science
2020
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| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/17732 |
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Aim: A major problem for conservation in Amazonia is that species distribution maps are inaccurate. Consequently, conservation planning needs to be based on other information sources such as vegetation and soilmaps, which are also inaccurate. We propose and test the use of biotic data on a common and relatively easily inventoried group of plants to infer environmental conditions that can be used to improvemaps of floristic patterns for plants in general. Location: Brazilian Amazonia. Methods: We sampled 326 plots of 250 m × 2 m separated by distances of 1-1800 km. Terrestrial fern individuals were identified and counted. Edaphic data were obtained from soil samples and analysed for cation concentration and texture. Climatic data were obtained from Worldclim. We used a multivariate regression tree to evaluate the hierarchical importance of soils and climate for fern communities and identified significant indicator species for the resultant classification. We then tested how well the edaphic properties of the plots could be predicted on the basis of their floristic composition using two calibration methods, weighted averaging and k-nearest neighbour estimation. Results: Soil cation concentration emerged as the most important variable in the regression tree, whereas soil textural and climatic variation played secondary roles. Almost all the plot classes had several fern species with high indicator values for that class. Soil cation concentration was also the variablemost accurately predicted on the basis of fern community composition (R2 = 0.65-0.75 for log-transformed data). Predictive accuracy varied little among the calibration methods, and was not improved by the use of abundance data instead of presence-absence data. Conclusions: Fern species composition can be used as an indicator of soil cation concentration, which can be expected to be relevant also for other components of rain forests. Presence-absence data are adequate for this purpose, which makes the collecting of additional data potentially very rapid. Comparison with earlier studies suggests that edaphic preferences of fern species have good transferability across geographical regions within lowland Amazonia. Therefore, species and environmental data sets already available in the Amazon region represent a good starting point for generating better environmental and floristic maps for conservation planning. © 2014 International Association for Vegetation Science. |