Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/39264
Title: Plant Family-Specific Impacts of Petroleum Pollution on Biodiversity and Leaf Chlorophyll Content in the Amazon Rainforest of Ecuador.
Authors: Arellano, Paul
Tansey, Kevin
Balzter, Heiko
Tellkamp, M.
First Published: 19-Jan-2017
Publisher: Public Library of Science
Citation: PLoS ONE (2017) 12(1): e0169867.
Abstract: In recent decades petroleum pollution in the tropical rainforest has caused significant environmental damage in vast areas of the Amazon region. At present the extent of this damage is not entirely clear. Little is known about the specific impacts of petroleum pollution on tropical vegetation. In a field expedition to the Ecuadorian Amazon over 1100 leaf samples were collected from tropical trees in polluted and unpolluted sites. Plant families were identified for 739 of the leaf samples and compared between sites. Plant biodiversity indices show a reduction of the plant biodiversity when the site was affected by petroleum pollution. In addition, reflectance and transmittance were measured with a field spectroradiometer for every leaf sample and leaf chlorophyll content was estimated using reflectance model inversion with the radiative tranfer model PROSPECT. Four of the 15 plant families that are most representative of the ecoregion (Melastomataceae, Fabaceae, Rubiaceae and Euphorbiaceae) had significantly lower leaf chlorophyll content in the polluted areas compared to the unpolluted areas. This suggests that these families are more sensitive to petroleum pollution. The polluted site is dominated by Melastomataceae and Rubiaceae, suggesting that these plant families are particularly competitive in the presence of pollution. This study provides evidence of a decrease of plant diversity and richness caused by petroleum pollution and of a plant family-specific response of leaf chlorophyll content to petroleum pollution in the Ecuadorian Amazon using information from field spectroscopy and radiative transfer modelling.
DOI Link: 10.1371/journal.pone.0169867
eISSN: 1932-6203
Links: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0169867
http://hdl.handle.net/2381/39264
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: © 2017 Arellano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Description: Data is available upon request due to legal restriction. The principal author, Dr. Paul Arellano, PhD, is the person that readers may contact to request the data, and a confirmation that data will be available upon request to all interested researchers.
Appears in Collections:Published Articles, Dept. of Geography

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