Modeling and interpreting bioavailability of organic contaminant mixtures in subsurface environments

Bioavailability often controls the fate of organic contaminants in surface and subsurface aquatic environments. Bioavailability can be limited by sorption, mass transfer, and intrinsic biodegradation potential and can be further altered by the presence of other compounds. This paper reviews current perspectives on the processes influencing subsurface contaminant bioavailability, how these processes are modeled, and how the relative role of the various processes can be assessed through bioavailability indices. Although these processes are increasingly well understood, the use of sophisticated models and indices often are precluded by an inability to estimate the many parameters that are associated with complex models. Nonetheless, the proper representation of sorption, mass transfer, biodegradation, and co-solute effects can be critical in predicting bio-attenuation. The influence of these processes on contaminant fate is illustrated with numerical simulations for the simultaneous degradation of toluene (growth substrate) and trichloroethylene (nongrowth cometabolite) in hypothetical, aerobic, solid-water systems. The results show how the relative impacts on contaminant fate of the model's various component processes depends upon system conditions, including co-solute concentrations. Slow biodegradation rates increase the inhibition effects of a cometabolite and suppress the rate enhancement effects of a growth substrate. Irrespective of co-solute effects, contaminant fate is less sensitive to biodegradation processes in systems with strong sorption and slow desorption rates. Bioavailability indices can be used to relate these findings and to help identify appropriate modeling simplifications. In general, however, there remains a need to redefine such indices in order that bioavailability concepts can be better incorporated into site characterization, remediation design, and regulatory oversight.     

Herbivores and variation in the composition of specific phenolics of boreal coniferous trees: a search for patterns

Coniferous trees of different species, or of the same species growing at different locations, vary in the extent to which they are attacked by various herbivores and pathogens. Plant secondary metabolites might be a key to understanding some of this variation. At the site level, we investigated if there was an intra- or interspecies pattern for individual compounds (or for groups of compounds) and their relationship to indices of plant nitrogen and plant productivity. For example, do plants exhibit similar covariance in defence compounds when evaluated across a number of sites varying in productivity? Here, we concentrated on the phenolic profile of Pinus sylvestris, Picea abies, Juniperus communis and Pinus contorta. Our results indicate striking differences in secondary chemistry profiles of the twigs including needles of the trees and in the inter-relationships amongst individual compounds and groups of compounds. Flavonols occurred in high variety in P. sylvestris and were highly correlated with each other, differing from P. contorta. But the results of the factor analyses indicate an underlying pattern for flavonols of the coumaroyl type for P. contorta. In contrast, the compounds of the other tree species showed a low degree of inter-correlation. Co-occurring phenolics of different tree species were not correlated. Overall, our analysis of site indices indicated that plant productivity was not a useful predictor for the concentration of specific phenolics. The relationship amongst plant nitrogen and specific phenolics might be the result of two defence strategies (one related and the other not related to nitrogen content). This might enable the plant to shift its defences against attacks with a high degree of flexibility.     

Evaporites and continental drift

The Science of Nature -     

Protecting biodiversity and economic returns in resource-rich tropical forests

In pursuit of socioeconomic development, many countries are expanding oil and mineral extraction into tropical forests. These activities seed access to remote, biologically rich areas, thereby endangering global biodiversity. We examined how protection of biodiversity and economic revenues can be balanced in biologically valuable regions. Using spatial data on oil profits and predicted species and ecosystem extents, we optimized the protection of 741 terrestrial species and 20 ecosystems of the Ecuadorian Amazon across a range of opportunity costs (i.e., sacrifices of extractive profit). We also applied spatial statistics to remotely sensed, historic deforestation data to focus the optimization on areas most threatened by imminent forest loss. Giving up 5% of a year's oil profits (US$221 million) allowed for a protected area network that retained an average of 65% of the extent of each species and ecosystem. This performance far exceeded that of the network produced by simple optimization for land area (which required a sacrifice of approximately 40% of annual oil profits [US$1.7 billion]) and used only marginally less land to achieve equivalent levels of ecological protection. We identified what we call emergency conservation targets: regions that are essential components of a cost-effective conservation reserve network but at imminent risk of destruction, thus requiring urgent and effective protection. Governments can use our methods when evaluating extractive-led development options to responsibly manage the associated ecological and economic trade-offs and protect natural capital.