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 needed.

In this article, we develop a modelling approach which examines selected drivers of ecosystem functioning and agricultural productivity. In particular, we develop linkages between land use and biodiversity and between biodiversity and agricultural productivity. We review the literature for quantitative estimates of key relationships and their parameters for modelling human consumption, land use, energy use, and greenhouse gas emissions on biodiversity and agricultural productivity. We assemble these specifications into an iterative causal model and carry out a number of scenario projections of country-level consumption, production, land use, energy use, greenhouse gas emissions, species diversity, and agricultural production up to 2050. Finally, we dissect the projections into key drivers using structural decomposition and sensitivity analyses.

By addressing the trade-offs between food production and biodiversity conservation at landscape and ecoregion scales, the land sparing/sharing debate has made a significant contribution to land use science. However, as global population and food consumption grow, and urbanization and transnational trade intensify, land use trade-offs need to be analyzed at broader scales. These analyses should specifically consider the role of environmental heterogeneity on biodiversity distribution and agricultural suitability, the costs and benefits transferred far away from the focal land use, institutional and economic factors influencing stability and resilience, technology-related factors as mediators of agriculture suitability, and bundles of different environmental services. In addition, land use strategies to balance agriculture and biodiversity conservation must consider local socioeconomic constraints and trade-offs.

In this paper we describe a methodology to model the impacts of policy measures within the Common Agricultural Policy (CAP) on farm production, income and prices, and on farmland biodiversity. Two stylised scenarios are used to illustrate how the method works. The effects of CAP measures, such as subsidies and regulations, are calculated and translated into changes in land use and land-use intensity. These factors are then used to model biodiversity with a species-based indicator on a 1 km scale in the EU27. The Common Agricultural Policy Regionalised Impact Modelling System (CAPRI) is used to conduct the economic analysis and Dyna-CLUE (Conversion of Land Use and its Effects) is used to model land use changes. An indicator that expresses the relative species richness was used as the indicator for biodiversity in agricultural areas. The methodology is illustrated with a baseline scenario and two scenarios that include a specific policy. The strength of the methodology is that impacts of economic policy instruments can be linked to changes in agricultural production, prices and incomes, on the one hand, and to biodiversity effects, on the other – with land use and land-use intensity as the connecting drivers. The method provides an overall assessment, but for detailed impact assessment at landscape, farm or field level, additional analysis would be required.

This project focused on mapping the delivery of three ecosystems services each in one case study area in Scotland and then identify how the Scottish policies such as woodland expansion biodiversity, conservation and food production affect the land use. Scenarios for a future land use change were presented to show how the provision of the ecosystem services could change towards this different land use. In Glengarry, was shown how the delivery of timber could change from the current situation and a future management that enhance biodiversity. As it was difficult to map biodiversity, habitat networks which show connectivity between habitats such as woodlands were used to examine how woodland expansion can support biodiversity in South Mull. Delivery of water quality in Clyde Valley was mapped with GIS and potential woodland sites were identified in order for a possible reduces of pollution, and hence flooding. Food production would play a decisive role as a Scottish policy for the imminent land use in this case study area.

International audience | Question: Can we predict where forest regrowth caused by abandonment of agricultural activities is likely to occur? Can we assess how it may conflict with grassland diversity hotspots? Location: Western Swiss Alps (400–3210 ma.s.l.). Methods: We used statistical models to predict the location of land abandonment by farmers that is followed by forest regrowth in semi-natural grasslands of the Western Swiss Alps. Six modelling methods (GAM, GBM, GLM, RF, MDA, MARS) allowing binomial distribution were tested on two successive transitions occurring between three time periods. Models were calibrated using data on land-use change occurring between 1979 and 1992 as response, and environmental, accessibility and socio-economic variables as predictors, and these were validated for their capacity to predict the changes observed from 1992 to 2004. Projected probabilities of land-use change from an ensemble forecast of the six models were combined with a model of plant species richness based on a field inventory, allowing identification of critical grassland areas for the preservation of biodiversity. Results: Models calibrated over the first land-use transition period predicted the second transition with reasonable accuracy. Forest regrowth occurs where cultivation costs are high and yield potential is low, i.e. on steeper slopes and at higher elevations. Overlaying species richness with land-use change predictions, we identified priority areas for themanagement and conservation of biodiversity at intermediate elevations. Conclusions: Combining land-use change and biodiversity projections, we propose applied management measures for targeted/identified locations to limit the loss of biodiversity that could otherwise occur through loss of open habitats. The same approach could be applied to other types of land-use changes occurring in other ecosystems.

Agriculture has a large impact on the environment and retailers increasingly stimulate their suppliers to reduce the environmental impact of agricultural production. The environmental impact resulting from producing a commodity can be measured with a life cycle analysis (LCA) but performing an LCA is costly and time-consuming. In the first paper of this series a practical and general method to identify hotspot areas in crop production on a global scale was developed. The method was implemented for potatoes. The objective of the work reported here was to evaluate the tool and to identify improvement opportunities for each of seven indicators: yield, erosion risk, nitrogen surplus, depletion of water reserves, biocide use, carbon footprint, and impact on biodiversity. The tool produces realistic outputs that can be used to target improve-ment efforts and thus improves the use efficiency of limited resources. The tool can be expanded to produce similar results for other crops; methods to improve the resolution of the tool are discussed.

Land use change is a major driver of ecosystem service change. Urbanization and agricultural activities play substantial roles in altering the state of ecosystem services. This study examined impact of land use change on ecosystem services in a typical agricultural watershed in northwest Arkansas. Biodiversity and ecosystem services – carbon storage, water yield, nutrient cycling – were mapped and quantified for a typical small dairy farm and its watershed for predevelopment (1800) and current (2006) land-use scenarios. Field-level impacts showed that dairy operations resulted in reduced land use change on ecosystem service loss, compared with the overall watershed. The results also indicated substantial change in carbon storage, water yield, and biodiversity; while nutrient cycling showed a low net change. The methodology illustrates the utility of evaluating impact of land management scenarios (historic, current, potential) on ecosystem services at the field and watershed scale, and the need for standard metrics across landscapes.

CITATION: Stuckenberg, T., Munch, Z. & Van Niekerk, A. 2013. Multi-temporal remote sensing land-cover change detection for biodiversity assessment in the Berg River catchment. South African Journal of Geomatics, 2(3):189-205. | The original publication is available athttp://www.sajg.org.za | Due to the intimate relationship that exists between land cover and biodiversity it is possible to draw inferences on the current state of the biodiversity of an area, assess the likely future pressures and plan accordingly based on an analysis of land-cover change. As a means of assessing the state of biodiversity in the Cape Floristic Region, two land-cover maps (1986/7 and 2007) were developed and demonstrated for the Berg River catchment in the Western Cape province of South Africa using multispectral Landsat Thematic Mapper (TM) data. The land-cover maps were produced to an accuracy of 85% using an object-orientated nearest neighbour supervised classification. The existing vegetation types of South Africa data set were superimposed on the newly classified remnants of natural vegetation to model changes in biodiversity. It was found that the area occupied by natural vegetation increased by more than 14%, suggesting an increase in biodiversity from 1986/7 to 2007. Considerable variation between vegetation types was, however, recorded. The land cover mapping, change analysis and biodiversity modelling methods employed by this study show that land-cover change analysis provides an ideal platform from which to initiate more intensive analyses of biodiversity change and conservation. Some limitations to the use of Landsat imagery for biodiversity monitoring are discussed. | http://www.sajg.org.za/index.php/sajg/article/view/85 | Publisher's version

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.