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Are floristic and edaphic patterns in Amazonian rain forests congruent for trees, pteridophytes and Melastomataceae?
- Kalle Ruokolainen, Hanna Tuomisto, Manuel J. Macía, Mark A. Higgins, Markku Yli-Halla
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- Journal:
- Journal of Tropical Ecology / Volume 23 / Issue 1 / January 2007
- Published online by Cambridge University Press:
- 12 January 2007, pp. 13-25
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Studies in western Amazonian forests have found that similarities in soil cation concentration and texture explain floristic similarities between sites, when these are measured using trees, pteridophytes or Melastomataceae. However, it is not known to what extent the three plant groups react to the same soil characteristics, because tree studies have almost always been conducted in different areas than studies on the understorey plant groups. We made inventories in 23 sites representing non-inundated rain forests on clayey to loamy soil in three regions of western Amazonia. Significant Mantel correlations between the floristic patterns of trees and pteridophytes were found in all three regions when floristic differences were measured with species presence–absence data. When species abundance data were used, and when the floristic patterns of trees and Melastomataceae were compared, significant correlations were found in one or two regions. Mantel correlations between plant groups were highest in the two regions where the observed variation in soil characteristics was largest. In all regions, the same soil variables emerged with significant Mantel correlations with trees, pteridophytes and Melastomataceae. Soil calcium and magnesium were most frequently retained in the models of multiple regression on distance matrices. On average, soil differences explained 50% of the variation in floristic differences (range = 14–84%), and geographical distances explained 16% (range = 0–64%). Our results demonstrate that beta diversities of the three plant groups are highly correlated, and that much of this congruence is explained by similar reactions to soil variation. These results support the idea that pteridophytes, and to a lesser degree Melastomataceae, can be used as indicators of general floristic and edaphic patterns in Amazonian rain forests. Since understorey plants are much quicker to inventory than trees, this would make it possible to recognize and map floristic patterns over huge areas of lowland Amazonia within a reasonable time.
Efficient plot-based floristic assessment of tropical forests
- Oliver L. Phillips, Rodolfo Vásquez Martínez, Percy Núñez Vargas, Abel Lorenzo Monteagudo, Maria-Elena Chuspe Zans, Washington Galiano Sánchez, Antonio Peña Cruz, Martin Timaná, Markku Yli-Halla, Sam Rose
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- Journal:
- Journal of Tropical Ecology / Volume 19 / Issue 6 / November 2003
- Published online by Cambridge University Press:
- 24 October 2003, pp. 629-645
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The tropical flora remains chronically understudied and the lack of floristic understanding hampers ecological research and its application for large-scale conservation planning. Given scarce resources and the scale of the challenge there is a need to maximize the efficiency of both sampling strategies and sampling units, yet there is little information on the relative efficiency of different approaches to floristic assessment in tropical forests. This paper is the first attempt to address this gap. We repeatedly sampled forests in two regions of Amazonia using the two most widely used plot-based protocols of floristic sampling, and compared their performance in terms of the quantity of floristic knowledge and ecological insight gained scaled to the field effort required. Specifically, the methods are assessed first in terms of the number of person-days required to complete each sample (‘effort’), secondly by the total gain in the quantity of floristic information that each unit of effort provides (‘crude inventory efficiency’), and thirdly in terms of the floristic information gained as a proportion of the target species pool (‘proportional inventory efficiency’). Finally, we compare the methods in terms of their efficiency in identifying different ecological patterns within the data (‘ecological efficiency’) while controlling for effort. There are large and consistent differences in the performance of the two methods. The disparity is maintained even after accounting for regional and site-level variation in forest species richness, tree density and the number of field assistants. We interpret our results in the context of selecting the appropriate method for particular research purposes.