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Until now the main instrument to counteract the loss of biodiversity and landscape quality in the European countryside has been agri-environment schemes (AES), which offer short-term payments for performing prescribed environmental management behaviors. In our opinion this approach is, in its current set-up, not a sustainable way of enhancing biodiversity and landscape quality. Here we will argue that conservation in agricultural areas is also a social challenge. To change farmers' behaviors toward more sustainable conservation of farmland biodiversity, instruments should aim to influence individual farmer's motivation and behavior. We should aim to place farmland biodiversity "in the hands and minds of farmers."

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PurposeAs capture fishery production has reached its limits and global demand for aquatic products is still increasing, aquaculture has become the world’s fastest growing animal production sector. In attempts to evaluate the environmental consequences of this rapid expansion, life cycle assessment (LCA) has become a frequently used method. The present review of current peer-reviewed literature focusing on LCA of aquaculture systems is intended to clarify the methodological choices made, identify possible data gaps, and provide recommendations for future development within this field of research. The results of this review will also serve as a start-up activity of the EU FP7 SEAT (Sustaining Ethical Aquaculture Trade) project, which aims to perform several LCA studies on aquaculture systems in Asia over the next few years.MethodsFrom a full analysis of methodology in LCA, six phases were identified to differ the most amongst ten peer-reviewed articles and two PhD theses (functional unit, system boundaries, data and data quality, allocation, impact assessment methods, interpretation methods). Each phase is discussed with regards to differences amongst the studies, current LCA literature followed by recommendations where appropriate. The conclusions and recommendations section reflects on aquaculture-specific scenarios as well as on some more general issues in LCA.ResultsAquaculture LCAs often require large system boundaries, including fisheries, agriculture, and livestock production systems from around the globe. The reviewed studies offered limited coverage of production in developing countries, low-intensity farming practices, and non-finfish species, although most farmed aquatic products originate from a wide range of farming practices in Asia. Apart from different choices of functional unit, system boundaries and impact assessment methods, the studies also differed in their choice of allocation factors and data sourcing. Interpretation of results also differed amongst the studies, and a number of methodological choices were identified influencing the outcomes.Conclusions and recommendationsEfforts should be made to increase transparency to allow the results to be reproduced, and to construct aquaculture related database(s). More extensive data reporting, including environmental flows, within the greater field of LCA could be achieved, without compromising the focus of studies, by providing supporting information to articles and/or reporting only ID numbers from background databases. More research is needed into aquaculture in Asia based on the latest progress made by the LCA community.Electronic supplementary materialThe online version of this article (doi:10.1007/s11367-011-0369-4) contains supplementary material, which is available to authorized users.

In response to growing awareness of climate change, requests to establish product carbon footprints have been increasing. Product carbon footprints are life cycle assessments restricted to just one impact category, global warming. Product carbon footprint studies generate life cycle inventory results, listing the environmental emissions of greenhouse gases from a product’s lifecycle, and characterize these by their global warming potentials, producing product carbon footprints that are commonly communicated as point values. In the present research we show that the uncertainties surrounding these point values necessitate more sophisticated ways of communicating product carbon footprints, using different sizes of catfish (Pangasius spp.) farms in Vietnam as a case study. As most product carbon footprint studies only have a comparative meaning, we used dependent sampling to produce relative results in order to increase the power for identifying environmentally superior products. We therefore argue that product carbon footprints, supported by quantitative uncertainty estimates, should be used to test hypotheses, rather than to provide point value estimates or plain confidence intervals of products’ environmental performance.

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To develop a multimetal toxicity model requires insight into the relationships between the composition of metal mixtures and their toxicological effects on organisms. As a first step in developing such a model, quantitative data from binary and higher mixture studies of Cu, Cd, and Zn were compiled and used to assess trends in toxicological effects on various organisms. The findings of this meta-analysis show relatively little occurrence of additive effects compared with antagonistic and synergistic effects. This observation held true irrespective of test species, environmental compartment, or metal concentrations in the mixture. However, the type of effect was significantly correlated with the metal combination tested and the selected toxicological endpoint. It was also found that different methods were used for assessing deviation from additivity in the various individual studies. For robust comparison, standardization on this point is required. Toxicological responses of organisms to metal mixtures were shown to be hard to predict and were often slightly less than or slightly more than additive. The interactions observed could not be explained by metal-metal interactions alone. We therefore conclude that with current scientific knowledge it is not yet possible to predict responses to metal mixtures in individual cases; at best this is possible only in terms of general patterns. Nevertheless, in the context of environmental risk policy, the assumption of additivity produces a conservative prediction of toxicity, because toxicity of a metal mixture will be either predicted correctly or overpredicted by default in approximately 75% of all cases. The use of models based on noninteraction is satisfactory from this regulatory perspective.