Plant Family-Specific Impacts of Petroleum Pollution on Biodiversity and Leaf Chlorophyll Content in the Amazon Rainforest of Ecuador.

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.

Variable carbon losses from recurrent fires in drained tropical peatlands.

Tropical peatland fires play a significant role in the context of global warming through emissions of substantial amounts of greenhouse gases. However, the state of knowledge on carbon loss from these fires is still poorly developed with few studies reporting the associated mass of peat consumed. Furthermore, spatial and temporal variations in burn depth have not been previously quantified. This study presents the first spatially explicit investigation of fire-driven tropical peat loss and its variability. An extensive airborne Light Detection and Ranging data set was used to develop a prefire peat surface modelling methodology, enabling the spatially differentiated quantification of burned area depth over the entire burned area. We observe a strong interdependence between burned area depth, fire frequency and distance to drainage canals. For the first time, we show that relative burned area depth decreases over the first four fire events and is constant thereafter. Based on our results, we revise existing peat and carbon loss estimates for recurrent fires in drained tropical peatlands. We suggest values for the dry mass of peat fuel consumed that are 206 t ha(-1) for initial fires, reducing to 115 t ha(-1) for second, 69 t ha(-1) for third and 23 t ha(-1) for successive fires, which are 58-7% of the current IPCC Tier 1 default value for all fires. In our study area, this results in carbon losses of 114, 64, 38 and 13 t C ha(-1) for first to fourth fires, respectively. Furthermore, we show that with increasing proximity to drainage canals both burned area depth and the probability of recurrent fires increase and present equations explaining burned area depth as a function of distance to drainage canal. This improved knowledge enables a more accurate approach to emissions accounting and will support IPCC Tier 2 reporting of fire emissions.

Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images.

The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest.