Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil.

Abstract:

:Roots of mangrove trees have an important role in depurating water and sediments by retaining metals that may accumulate in different plant tissues, affecting physiological processes and anatomy. The present study aimed to evaluate adaptive changes in root of Rhizophora mangle in response to different levels of chemical elements (metals/metalloids) in interstitial water and sediments from four neotropical mangroves in Brazil. What sets this study apart from other studies is that we not only investigate adaptive modifications in R. mangle but also changes in environments where this plant grows, evaluating correspondence between physical, chemical and biological issues by a combined set of multivariate statistical methods (pattern recognition). Thus, we looked to match changes in the environment with adaptations in plants. Multivariate statistics highlighted that the lignified periderm and the air gaps are directly related to the environmental contamination. Current results provide new evidences of root anatomical strategies to deal with contaminated environments. Multivariate statistics greatly contributes to extrapolate results from complex data matrixes obtained when analyzing environmental issues, pointing out parameters involved in environmental changes and also evidencing the adaptive response of the exposed biota.

journal_name

Chemosphere

journal_title

Chemosphere

authors

Souza Ida C,Morozesk M,Duarte ID,Bonomo MM,Rocha LD,Furlan LM,Arrivabene HP,Monferrán MV,Matsumoto ST,Milanez CR,Wunderlin DA,Fernandes MN

doi

10.1016/j.chemosphere.2014.02.066

subject

Has Abstract

pub_date

2014-08-01 00:00:00

pages

115-24

eissn

0045-6535

issn

1879-1298

pii

S0045-6535(14)00335-X

journal_volume

108

pub_type

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