Assessment of land use impacts on the natural environment: Part 2: Generic characterization factors for local species diversity in Central Europe

Goal, Scope and Background: Land use is an economic activity that generates large benefits for human society. One side effect, however, is that it has caused many environmental problems throughout history and still does today. Biodiversity, in particular, has been negatively influenced by intensive agriculture, forestry and the increase in urban areas and infrastructure. Integrated assessment such as Life Cycle Assessment (LCA), thus, incorporate impacts on biodiversity. The main objective of this paper is to develop generic characterization factors for land use types using empirical information on species diversity from Central Europe, which can be used in the assessment method developed in the first part of this series of paper. Methods: Based on an extensive meta-analysis, with information about species diversity on 5581 sample plots, we calculated characterization factors for 53 land use types and six intensity classes. The typology is based on the CORINE Plus classification. We took information on the standardized α-diversity of plants, moss and mollusks into account. In addition, threatened plants were considered. Linear and nonlinear models were used for the calculation of damage potentials (EDP S). In our approach, we use the current mean species number in the region as a reference, because this determines whether specific land use types hold more or less species diversity per area. The damage potential calculated here is endpoint oriented. The corresponding characterization factors EDP S can be used in the Life Cycle Impact Assessment as weighting factors for different types of land occupation and land use change as described in Part 1 of this paper series. Results: The result from ranking the intensity classes based on the mean plant species number is as expected. High intensive forestry and agriculture exhibit the lowest species richness (5.7-5.8 plant species/m2), artificial surfaces, low intensity forestry and non-use have medium species richness (9.4-11.1 plant species/m2) and low-intensity agriculture has the highest species richness (16.6 plant species/m2). The mean and median are very close, indicating that the skewedness of the distribution is low. Standard error is low and is similar for all intensity classes. Linear transformations of the relative species numbers are linearly transformed into ecosystem damage potentials (EDP linear S ). The integration of threatened plant species diversity into a more differentiated damage function $$EDP_{linear}^{S_{total} }$$ makes it possible to differentiate between land use types that have similar total species numbers, but intensities of land use that are clearly different (e.g., artificial meadow and broad-leafed forest). Negative impact values indicate that land use types hold more species per m2 than the reference does. In terms of species diversity, these land use types are superior (e.g. near-to-nature meadow, hedgerows, agricultural fallow). Discussion: Land use has severe impacts on the environment. The ecosystem damage potential EDP S is based on assessment of impacts of land use on species diversity. We clearly base EDP S factors on α-diversity, which correlates with the local aspect of species diversity of land use types. Based on an extensive meta-analysis of biologists' field research, we were able to include data on the diversity of plant species, threatened plant species, moss and mollusks in the EDP S. The integration of other animal species groups (e.g. insects, birds, mammals, amphibians) with their specific habitat preferences could change the characterization factors values specific for each land use type. Those mobile species groups support ecosystem functions, because they provide functional links between habitats in the landscape. Conclusions: The use of generic characterization factors in Life Cycle Impact Assessment of land use, which we have developed, can improve the basis for decision-making in industry and other organizations. It can best be applied for marginal land use decisions. However, if the goal and scope of an LCA requires it this generic assessment can be complemented with a site-dependent assessment. Recommendations and Perspectives: We recommend utilizing the developed characterization factors for land use in Central Europe and as a reference methodology for other regions. In order to assess the impacts of land use in other regions it would be necessary to sample empirical data on species diversity and to develop region specific characterization factors on a worldwide basis in LCA. This is because species diversity and the impact of land use on it can very much differ from region to regio

Land use impacts on biodiversity in LCA: a global approach

Purpose: Land use is a main driver of global biodiversity loss and its environmental relevance is widely recognized in research on life cycle assessment (LCA). The inherent spatial heterogeneity of biodiversity and its non-uniform response to land use requires a regionalized assessment, whereas many LCA applications with globally distributed value chains require a global scale. This paper presents a first approach to quantify land use impacts on biodiversity across different world regions and highlights uncertainties and research needs. Methods: The study is based on the United Nations Environment Programme (UNEP)/Society of Environmental Toxicology and Chemistry (SETAC) land use assessment framework and focuses on occupation impacts, quantified as a biodiversity damage potential (BDP). Species richness of different land use types was compared to a (semi-)natural regional reference situation to calculate relative changes in species richness. Data on multiple species groups were derived from a global quantitative literature review and national biodiversity monitoring data from Switzerland. Differences across land use types, biogeographic regions (i.e., biomes), species groups and data source were statistically analyzed. For a data subset from the biome (sub-)tropical moist broadleaf forest, different species-based biodiversity indicators were calculated and the results compared. Results and discussion: An overall negative land use impact was found for all analyzed land use types, but results varied considerably. Different land use impacts across biogeographic regions and taxonomic groups explained some of the variability. The choice of indicator also strongly influenced the results. Relative species richness was less sensitive to land use than indicators that considered similarity of species of the reference and the land use situation. Possible sources of uncertainty, such as choice of indicators and taxonomic groups, land use classification and regionalization are critically discussed and further improvements are suggested. Data on land use impacts were very unevenly distributed across the globe and considerable knowledge gaps on cause-effect chains remain. Conclusions: The presented approach allows for a first rough quantification of land use impact on biodiversity in LCA on a global scale. As biodiversity is inherently heterogeneous and data availability is limited, uncertainty of the results is considerable. The presented characterization factors for BDP can approximate land use impacts on biodiversity in LCA studies that are not intended to directly support decision-making on land management practices. For such studies, more detailed and site-dependent assessments are required. To assess overall land use impacts, transformation impacts should additionally be quantified. Therefore, more accurate and regionalized data on regeneration times of ecosystems are neede

Crop diversity and stability of revenue on farms in Central Europe : an analysis of big data from a comprehensive agricultural census in Bavaria

<div><p>Diversity of agricultural landscapes is important to maintain the provision of ecosystem services. In face of decreasing support measures for agricultural markets in the European Union, diversified crop portfolios could also offer a possibility to stabilize revenue at farm level (portfolio effect). We hypothesize that (i) diversity of crop portfolios changes along spatial gradients in the study area (Bavaria, Germany), (ii) the composition of portfolios depends on farm parameters, and (iii) more diverse portfolios on arable land provide higher revenue stability. We analysed agricultural census data comprising all farms (<i>N</i> = 105 314) in the study area and identified 26 typical crop portfolios. We show that portfolio composition is related to farm characteristics (whole farm revenue, farm type, farm size) and location. Currently, diversification of crop portfolios fails to promote stability of portfolio revenue in the study area, where policy still indirectly influences market prices of energy crops. We conclude that the portfolio effect as a natural insurance was less important in recent years due to high market prices for specific crops. This low need for natural insurances probably favoured simplified portfolios leading to decreased agricultural diversity.</p></div

Bayesian modeling of ecosystem services in human enviroment systems.

The adaptive management of ecosystem services requires knowledge about the interdependence of land use decision-making and the ecosystem features in a given landscape; and how this coupled humanenvironment system is influenced by drivers of global change. The problem in this context is, that both decisionmaking processes and the ecosystem changes are subject to large uncertainties and incomplete information. Furthermore, trade-offs between different ecosystem services and biodiversity exist and actors tend to maximize only one feature. The adaptive management of an entire system thus needs to find a solution, which optimizes all ecosystem services given uncertain information. For this purpose, we develop a Bayesian Network BN of the humanenvironment system allowing evaluating simultaneously the effect of different decision-making processes on ecosystem responses and updating the results when better information becomes available. We test the approach in a case study in the Swiss Alps, where we focus on integrating the value of different ecosystem services as a support for landscape planning. Results show that if uncertainties are not explicitly integrated into the modeling framework, the information provided to the decision-makers might be misleading. For a case study in a Costa Rican watershed, we expand the BN with exogenous drivers from market (e.g., change in price for crops), policy (e.g., change in national park border) and climate (e.g., change in frequency of heavy rainfall). Policy instruments like command and control, park zoning and payments for cosystem services can help reaching a more balanced management of a watershed. For the planning of those instruments, however, it is helpful to have a model which shows how the manager of individual land units, takes policy measures, together with expected market changes and climate change into account in his land use decision-making. For each management unit, the prior probability of a specific land use and cover is updated with a posterior probability, when additional information about the management unit (e.g., slope, soil type, governance) is available. This type of model can be used to plan and simulate new policy measures like payments for ecosystem services, because it simultaneously takes the ecosystem, socio-economic system and the policy system into account. The model allows identifying management units with high and low values for each ecosystem services and thus the targeting of available financial funds can be optimized. First working steps show that such a BN provides a robust modeling environment, useful for better informed and participatory decision-making

The Role of Vegetation in Mitigating Urban Land Surface Temperatures : A Case Study of Munich, Germany during the Warm Season

The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area

Towards mapping and assessing antarctic marine ecosystem services – The Weddell Sea case study

This study is the first to quantify and to map the provision of ecosystem core services (ES) – tourism, genetic diversity and carbon sequestration – for a large Antarctic marine area, the Weddell Sea. Additionally, synergies and trade-offs between the ES were explored. The analyses conducted during this study covered both spatial and temporal correlations between pairs of ES, and between individual ES and sea ice coverage. Overall, service delivery in the studied seascape is distinctly heterogeneous, albeit there are areas where multiple benefits are provided simultaneously (“super hotspots”). Our findings indicate that in wide parts of the Weddell Sea, small scale conservation efforts may not achieve their intended goals. They also show that particularly sea ice cover restrains tourism, i.e. this sector may expect strong growth in a future of global warming driven sea ice retreat

Do Consumers of Environmentally Friendly Farming Products in Downstream Areas Have a WTP for Water Quality Protection in Upstream Areas?

In South Korea, the Soyang Lake is an important source of drinking water to the metropolitan areas including Seoul. However, water quality problems in the Soyang Lake have still remained due to chemical contaminations attributed to conventional farming practices in the upstream areas. Based on a downstream consumer survey using a contingent valuation method, this study estimated the expected willingness to pays (WTPs) for water quality improvement through the conversion to environmentally friendly farming (EFF). The results showed that the estimated annual mean WTP is KRW 36,115 per household. The aggregated WTPs of downstream respondents in the Soyang Lake are sufficient to compensate for the income losses of upstream EFF farmers in highland farming areas. In addition, we found that the downstream citizens who recognize the label for EFF products and who intend to purchase EFF products in the future have a significant impact on WTPs for water quality improvement