Sensitivity analysis of the aquatic pesticide fate models in SYNOPS and their parametrization for Switzerland.

The model SYNOPS was developed to calculate national risk indicators for assessing the aquatic and terrestrial risk potential of pesticides in Germany. For Switzerland, a national aquatic risk indicator is currently being developed based on SYNOPS. It aims at evaluating long-term trends in aquatic risks based on changing pesticide usage and risk mitigation measures. In a first step, parameters of the fate models of SYNOPS were parametrized for the Swiss geographical context. Apart from data about pesticides and their specific usage, SYNOPS requires information about climate, soil and site-specific properties and crop stage. Based on these inputs, SYNOPS calculates the predicted environmental concentrations (PEC) of pesticides in water bodies and the associated exposure-toxicity-ratios (i.e., risks). To consider the effects of risk mitigation measures in risk indicators, a realistic representation of the contribution of different routes of entry (run-off, erosion, drainage, drift) is essential. To parametrize SYNOPS, a sensitivity analysis of the aquatic transport and fate models of SYNOPS was conducted: realistic ranges of Swiss-specific parameters and their combinations were defined and used as input for the sensitivity analysis. The impacts of input parameters on total PEC values and on the contribution of different routes of entry were analyzed. The sensitivity analysis revealed that slope and KOC were the parameters with the highest impact on pesticide concentration and that run-off was the dominant route of entry in most tested scenarios. From over 40,000 tested environmental scenarios, a reduced set of 75-113 environmental scenarios was finally selected, which predicted similar PEC values and comparable contributions of different routes of entry compared with the full set. With the parametrization and reduction of used environmental scenarios, fate calculations became more efficient and realistic for Swiss conditions. The findings of this study provide a solid basis for developing a national aquatic risk indicator using SYNOPS.

Quantifying Land Use Impacts on Biodiversity: Combining Species-Area Models and Vulnerability Indicators.

Habitat degradation and subsequent biodiversity damage often take place far from the place of consumption because of globalization and the increasing level of international trade. Informing consumers and policy makers about the biodiversity impacts "hidden" in the life cycle of imported products is an important step toward achieving sustainable consumption patterns. Spatially explicit methods are needed in life cycle assessment to accurately quantify biodiversity impacts of products and processes. We use the Countryside species-area relationship (SAR) to quantify regional species loss due to land occupation and transformation for five taxa and six land use types in 804 terrestrial ecoregions. Further, we calculate vulnerability scores for each ecoregion based on the fraction of each species' geographic range (endemic richness) hosted by the ecoregion and the IUCN assigned threat level of each species. Vulnerability scores are multiplied with SAR-predicted regional species loss to estimate potential global extinctions per unit of land use. As a case study, we assess the land use biodiversity impacts of 1 kg of bioethanol produced using six different feed stocks in different parts of the world. Results show that the regions with highest biodiversity impacts differed markedly when the vulnerability of species was included.

Harmonizing the assessment of biodiversity effects from land and water use within LCA.

Addressing biodiversity impacts in life cycle assessment (LCA) has recently been significantly improved. Advances include the consideration of several taxa, consideration of vulnerability of species and ecosystems, global coverage and spatial differentiation. To allow a comparison of biodiversity impacts of different stressors (e.g., land and water use), consistent approaches for assessing and aggregating biodiversity impacts across taxa are needed. We propose four different options for aggregating impacts across taxa and stressors: equal weight for species, equal weight for taxa and two options with special consideration of species' vulnerability. We apply the aggregation options to a case study of coffee, tea and sugarcane production in Kenya for the production of 1 kg of crop. The ranking between stressors (land vs water use) within each crop and also of the overall impact between crops (coffee>sugarcane>tea) remained the same when applying the different aggregation options. Inclusion of the vulnerability of species had significant influence on the magnitude of results, and potentially also on the spatial distribution of impacts, and should be considered.

High-resolution assessment of land use impacts on biodiversity in life cycle assessment using species habitat suitability models.

Agricultural land use is a main driver of global biodiversity loss. The assessment of land use impacts in decision-support tools such as life cycle assessment (LCA) requires spatially explicit models, but existing approaches are either not spatially differentiated or modeled at very coarse scales (e.g., biomes or ecoregions). In this paper, we develop a high-resolution (900 m) assessment method for land use impacts on biodiversity based on habitat suitability models (HSM) of mammal species. This method considers potential land use effects on individual species, and impacts are weighted by the species' conservation status and global rarity. We illustrate the method using a case study of crop production in East Africa, but the underlying HSMs developed by the Global Mammals Assessment are available globally. We calculate impacts of three major export crops and compare the results to two previously developed methods (focusing on local and regional impacts, respectively) to assess the relevance of the methodological innovations proposed in this paper. The results highlight hotspots of product-related biodiversity impacts that help characterize the links among agricultural production, consumption, and biodiversity loss.

Land use in life cycle assessment: global characterization factors based on regional and global potential species extinction.

Land use is one of the main drivers of biodiversity loss. However, many life cycle assessment studies do not yet assess this effect because of the lack of reliable and operational methods. Here, we present an approach to modeling the impacts of regional land use on plants, mammals, birds, amphibians, and reptiles. Our global analysis calculates the total potential damage caused by all land uses within each WWF ecoregion and allocates this total damage to different types of land use per ecoregion. We use an adapted (matrix-calibrated) species-area relationship to model the potential regional extinction of nonendemic species caused by reversible land use and land use change impacts. The potential global extinction of endemic species is used to assess irreversible, permanent impacts. Model uncertainty is assessed using Monte Carlo simulations. The impacts of land use on biodiversity varied strongly across ecoregions, showing the highest values in regions where most natural habitat had been converted in the past. The approach is thus retrospective and was able to highlight the impacts in highly disturbed regions. However, we also illustrate how it can be applied to prospective assessments using scenarios of future land use. Uncertainties, modeling choices, and validity are discussed.

Two-step sensitivity testing of parametrized and regionalized life cycle assessments: methodology and case study.

Comprehensive sensitivity analysis is a significant tool to interpret and improve life cycle assessment (LCA) models, but is rarely performed. Sensitivity analysis will increase in importance as inventory databases become regionalized, increasing the number of system parameters, and parametrized, adding complexity through variables and nonlinear formulas. We propose and implement a new two-step approach to sensitivity analysis. First, we identify parameters with high global sensitivities for further examination and analysis with a screening step, the method of elementary effects. Second, the more computationally intensive contribution to variance test is used to quantify the relative importance of these parameters. The two-step sensitivity test is illustrated on a regionalized, nonlinear case study of the biodiversity impacts from land use of cocoa production, including a worldwide cocoa products trade model. Our simplified trade model can be used for transformable commodities where one is assessing market shares that vary over time. In the case study, the highly uncertain characterization factors for the Ivory Coast and Ghana contributed more than 50% of variance for almost all countries and years examined. The two-step sensitivity test allows for the interpretation, understanding, and improvement of large, complex, and nonlinear LCA systems.

Toward meaningful end points of biodiversity in life cycle assessment.

Halting current rates of biodiversity loss will be a defining challenge of the 21st century. To assess the effectiveness of strategies to achieve this goal, indicators and tools are required that monitor the driving forces of biodiversity loss, the changing state of biodiversity, and evaluate the effectiveness of policy responses. Here, we review the use of indicators and approaches to model biodiversity loss in Life Cycle Assessment (LCA), a methodology used to evaluate the cradle-to-grave environmental impacts of products. We find serious conceptual shortcomings in the way models are constructed, with scale considerations largely absent. Further, there is a disproportionate focus on indicators that reflect changes in compositional aspects of biodiversity, mainly changes in species richness. Functional and structural attributes of biodiversity are largely neglected. Taxonomic and geographic coverage remains problematic, with the majority of models restricted to one or a few taxonomic groups and geographic regions. On a more general level, three of the five drivers of biodiversity loss as identified by the Millennium Ecosystem Assessment are represented in current impact categories (habitat change, climate change and pollution), while two are missing (invasive species and overexploitation). However, methods across all drivers can be greatly improved. We discuss these issues and make recommendations for future research to better reflect biodiversity loss in LCA.