Germany’s Agricultural Land Footprint and the Impact of Import Pattern Allocation

Footprints are powerful indicators for evaluating the impacts of a country’s bioeconomy on environmental goods, both domestic and abroad. We apply a hybrid approach combining a multi-regional input-output model and land use modelling to compute the agricultural land footprint (aLF). Furthermore, we added information on land-use change to the analysis and allocated land conversion to specific commodities. Using Germany as a case study, we show that the aLF abroad is 2.5 to 3 times larger compared to impacts within the country. When allocating land conversion of natural and semi-natural land-cover types in 2005 and 2010 to import increases by Germany, conversion rates were found to be 2.5 times higher than for the global average. Import increases to Germany slowed down in 2015 and 2020, reducing land conversion attributed to the German bioeconomy as well. Our results indicate that looking at a static import pattern is not sufficient to draw a realistic picture of the land footprint of a country. For a more detailed assessment that also considers temporal dynamics and impacts of biomass use and trade, our newly developed set of indicators also captures changes of import patterns over time. The case study shows that our enhanced land footprint provides clear and meaningful information for policymakers and other stakeholders.

A predictive model of fractional land use

Land use change leads to shifts in species ranges and declines in biodiversity across the world. By mapping likely future land use under projections of socio-economic change, these ecological changes can be predicted to inform conservation decision-making.We present a land use modelling approach that enables ecologists to map changes in land use under various socio-economic scenarios at fine spatial resolutions. Its predictions can be used as a direct input to virtually all existing spatially-explicit ecological models.The most commonly used land use modelling approaches provide binary predictions of land use. However, continuous representations of land use have been shown to improve ecological models. Our approach maps the fractional cover of land use within each grid cell, providing higher information content than discrete classes at the same spatial resolution.When parametrized using data from 1990, the method accurately reproduced land use patterns observed in the Amazon from 1990 until 2018. Predictions were accurate in terms of the fractional amounts allocated across the landscape and the correct identification of areas with declines and increases in different land uses. A small case study showcases the successful application of our model to reproduce patterns of agricultural expansion and habitat decline.The model source code is provided as an open-source R package, making this new, open method available to ecologists to bridge the gap between socio-economic, land use and biodiversity modelling.

A Review of Methodological Integration in Land-Use Change Models

Global change research communities are paying increasing attention to answering critical questions related to land-use change, questions which are at the root of many pressing socio-economic and environmental issues. In this regard, a huge number of models have been developed to support future land-use planning and environmental impact assessments of land-use change activities. Within land-use change models, methodological integration is recognized as an essential feature for a complete model, which can help to combine the strength of single modelling methods/techniques without inherent weaknesses. Despite the potential and remarkable growth of methodological integration in land-use change models, limited attention has been paid to this aspect of integration. In response to this, the authors' paper summarizes the current major land-use modelling methods/techniques, and explains the co-integration of these methods/techniques. In addition, they summarize the achievements, limitations and future trends in the use of the methodological integration approach in land-use change models.