The impact of the German timber footprint on potential species loss in supply regions.

Previous own assessments have shown that a) Germany has a wood consumption above global average, b) is strongly dependent on imports and c) has a domestic roundwood production that is at the limit of the sustainable harvest potential. Thereby Germany further increases the pressures on global forests which are already stressed by climate-change related impacts and a continuously growing global demand for wood. This leads to negative impacts on the biodiversity in the areas where wood is harvested. This paper aims to show the connection between Germany's timber consumption footprint and the impact on the biodiversity in the regions where the roundwood is sourced. A two-step process is used. In the first step, high-resolution land cover and land use maps are used as a basis for the countryside species-area relationship model, assessing the projected loss of the four taxa amphibians, birds, mammals and reptiles in relation to undisturbed natural ecosystems due to forests occupied for roundwood production. In the second step, roundwood equivalents consumed in Germany in 2015 are traced back to the region of origin using an environmentally-extended input-output analysis and the thereby induced potential species loss is calculated. We show that the highest impact on projected species richness loss caused by roundwood logging is taking place in Oceania (3.34E-03 species/m3), Carribean (1.56E-04 species/m3), and East Asia (1.43E-04 species/m3). German roundwood consumption has the highest projected species loss in the United States (7.4 species), followed by China (7.3 species) and Brazil (4.8 species). From a biodiversity impact perspective, Germany could theoretically reduce its impact by relocating imports to European countries. In view of the planetary boundary of sustainable roundwood consumption, which has already been exceeded, reducing consumption appears to be the only viable long-term option for high-consumption countries such as Germany to reduce negative impacts on global biodiversity.

Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia.

The ongoing trend toward agricultural intensification in Southern Amazonia makes it essential to explore the future impacts of this development on the extent of natural habitats and biodiversity. This type of analysis requires information on future pathways of land-use and land-cover change (LULCC) under different socio-economic conditions and policy settings. For this purpose, the spatially explicit land-use change model LandSHIFT was applied to calculate a set of high-resolution land-use change scenarios for the Brazilian states Para and Mato Grosso. The period of the analysis were the years 2010-2030. The resulting land-use maps were combined with maps depicting vertebrate species diversity in order to examine the impact of natural habitat loss on species ranges as well as the overall LULCC-induced effect on vertebrate diversity as expressed by the Biodiversity Intactness Index (BII). The results of this study indicate a general decrease in biodiversity intactness in all investigated scenarios. However, agricultural intensification combined with diversified environmental protection policies show least impact of LULCC on vertebrate species richness and conservation of natural habitats compared to scenarios with low agricultural intensification or scenarios with less effective conservation policies.

Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.