ZusammenfassungDie global steigenden Treibhausgase verändern in zunehmenden Maße auch in Deutschl... more ZusammenfassungDie global steigenden Treibhausgase verändern in zunehmenden Maße auch in Deutschland die klimatischen Verhältnisse. Betroffen sind insbesondere hiesige Agrarlandschaften, die weite Teile Deutschlands umfassen und schon gegenwärtig vielfältige ökologische Probleme aufweisen. Auch wenn die landwirtschaftlichen Nutzungen prägend für Agrarlandschaften sind, so hängt ihre Zukunftsfähigkeit nicht allein von einer Veränderung der Bewirtschaftungsmethoden ab. Die Gestaltung zukunftsfähiger Agrarlandschaften bedarf einer über den einzelnen Schlag hinausgehenden Betrachtung und ist eine gesamtgesellschaftliche Aufgabe, die deutlich über die Verantwortung und Möglichkeiten der einzelnen GrundstückseigentümerInnen und -bewirtschafterInnen hinausreicht. Ausgehend von den bekannten ökologischen Problemen und den im Beitrag ausführlicher dargestellten besonderen Herausforderungen des Klimawandels untersuchen wir daher, was Zukunftsfähigkeit bedeutet und welche gesellschaftlichen Zi...
BirdHab model: bird habitat suitability model applied to input data from the Lossa River Basin in... more BirdHab model: bird habitat suitability model applied to input data from the Lossa River Basin in Central Germany combined with a willingness to pay function for biodiversity. SWAT agronomy model: Calculates contribution margins for crops grown in the Lossa River Basin based on SWAT model output data.
The largest impact of land-use change on catchment hydrology can be linked to deforestation. This... more The largest impact of land-use change on catchment hydrology can be linked to deforestation. This change, driven by exponential population growth, intensified food and industrial production, has resulted in alterations in river flow regimes such as high peaks, reduced base flows, and silt deposition. To reverse this trend more extensive management practices are becoming increasingly important, but can also lead to severe losses in agricultural production. Land-use optimization tools can help catchment managers to explore numerous land-use configurations for the evaluation of trade-offs amongst various uses. In this study, the Soil and water assessment tool (SWAT) model was coupled with a genetic algorithm to identify land-use/management configurations with minimal trade-offs between environmental objectives (reduced sediment load, increased stream low flow) and the crop yields of maize and soybean in Nyangores catchment (Kenya). During the land-use optimization, areas under conventi...
Stream–riparian networks are subject to multiple human pressures that threaten key functions of a... more Stream–riparian networks are subject to multiple human pressures that threaten key functions of aquatic and terrestrial ecosystems, drive habitat and diversity losses, affect riparian connectivity and cause stakeholder conflicts. Designing riparian landscapes in a way that they can simultaneously meet multiple competing demands requires a clear understanding of existing trade‐offs, and a landscape‐scale perspective on the planning of reforestation measures. This study applied a landscape optimization algorithm for allocating riparian forest management measures in the intensively used agricultural catchment of the Zwalm River (Belgium). We optimized forest allocation to improve stream ecological quality (EPT index), functional diversity (diatoms) and riparian carbon processing (cotton‐strip assay), while minimizing losses in agricultural production potential. Regression models were developed to predict the target indicators for 489 segments of the Zwalm riparian corridor, using spati...
Land-use intensification in agroecosystems has led to population declines in many taxonomic group... more Land-use intensification in agroecosystems has led to population declines in many taxonomic groups, especially farmland birds. Two contrasting conservation strategies have therefore been proposed: land sharing (the integration of biodiversity conservation in low-intensity agriculture) and land sparing (the spatial separation of high-yielding agriculture and areas for conservation). Despite the large academic interest in this field, only few studies have taken into account stakeholders’ perspectives of these strategies when assessing conservation implications. We modeled the effects of three land-use scenarios (a business-as-usual, a land-sharing, and a land-sparing scenario), developed together with regional stakeholders, on the habitat area of 13 regionally endangered bird species in the Middle Mulde River Basin (Saxony, Germany). We used random forest models based on environmental variables relating to land-use/cover, climate and soil characteristics, occurrence of linear landscap...
Deliverable 4.1 of BiodivERsA Project TALE (01LC1404A) 'Towards multifunctional agricultural ... more Deliverable 4.1 of BiodivERsA Project TALE (01LC1404A) 'Towards multifunctional agricultural landscapes in Europe: Assessing and governing synergies between biodiversity and ecosystem services'. The TALE project is funded through the 2013-2014 BiodivERsA/FACCE-JPI joint call for research proposals, in this deliverable with the national funders German Federal Ministry of Education and Research (BMBF) and The Austrian Science Fund (FWF).
The data sets contains the major results of the article "Improving information extraction fr... more The data sets contains the major results of the article "Improving information extraction from model data using sensitivity-weighted performance criteria" written by Guse et al. (2020). In this article, it is analysed how a sensitivity-weighted performance criterion improves parameter identifiability and model performance. More details are given the in article. The files of this dataset are described as follows. Parameter sampling: FAST parameter sampling.xlsx: To estimate the sensitivity, the Fourier Amplitude Sensitivity Test (FAST) was used (R-routine FAST, Reusser, 2013). Each column shows the values of the model parameter of the SWAT model (Arnold et al., 1998). All parameters are explained in detail in Neitsch et al. (2011). The FAST parameter sampling defines the number of model runs. For twelve model parameters as in this case, 579 model runs are required. The same parameter sets were used for all catchments. Daily sensitivity time series: Sensitivity_2000_2005.xls...
The acquisition of adequate weather data is the most challenging task when setting up a hydrologi... more The acquisition of adequate weather data is the most challenging task when setting up a hydrologic model. While vegetation, soil and topographic information can be newly assessed if not available, weather data are needed as extensive time series. In our study, we analysed CFSR and WFDEI precipitation data in comparison to rain gauges in the Brazilian territory (n = 2027) for the period 1980-2010 to evaluate which weather reanalysis better represented precipitation in Brazil. Further, we used monthly-based interpolations (and historic monthly averages to fill gaps in time series) to further improve the best data set to measured precipitation. We then applied the interpolated precipitation in the river discharge modelling of the Tocantins Basin with the Soil and Water Assessment Tool (SWAT). Both reanalyses showed better statistics for monthly series than for daily and annual series. WFDEI better represented Brazilian precipitation than CFSR with higher coefficient of determination (R2 = 0.76 vs. 0.50; medians), coefficient of determination multiplied by the coefficient of the regression (bR2 = 0.70 vs. 0.39) and Nash-Sutcliffe coefficient (NS = 0.72 vs. 0.21), but equal percentages of bias (Pbias = 6.9 vs. 3.4). We applied interpolated WFDEI precipitation data in the hydrologic model of the Tocantins Basin with SWAT using 7 river gauges and 3 reservoirs, with an NS > 0.60 for 6 out of 10 stations (NS = 0.19, 0.38, 0.39 and 0.44 for the other 4 stations). Green water flow increased from South-East (640-840 mm) to North-West (1140-1440 mm), while green water storage increased from South (330-1070 mm) to North (2180-3290 mm). Blue water had a less clear pattern, with lower values in the South and central borders of the basin (20-560 mm) and higher values in the central axis and the North (920-1460 mm). Our analysis suggested that WFDEI was an accurate representation of Brazilian precipitation and allowed for the use of reanalysis weather data instead of observational data in hydrologic modelling.
The data set provides the output of a genetic algorithm optimizing a stylized urban region with r... more The data set provides the output of a genetic algorithm optimizing a stylized urban region with respect to three target functions: urban compactness, climate regulation as an exemplary ecosystem service and vascular plant species richness as a measure of biodiversity. The optimisation varies the spatial allocation of three types of land cover blocks in a stylized urban region: high- and low-density and park blocks which consist of green and/or built-up cells. We systematically vary landscape composition at the block level, but keep city size constant. The data set is related to a publication submitted to Frontiers in Environmental Science.
The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the col... more The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors. ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate ...
ZusammenfassungDie global steigenden Treibhausgase verändern in zunehmenden Maße auch in Deutschl... more ZusammenfassungDie global steigenden Treibhausgase verändern in zunehmenden Maße auch in Deutschland die klimatischen Verhältnisse. Betroffen sind insbesondere hiesige Agrarlandschaften, die weite Teile Deutschlands umfassen und schon gegenwärtig vielfältige ökologische Probleme aufweisen. Auch wenn die landwirtschaftlichen Nutzungen prägend für Agrarlandschaften sind, so hängt ihre Zukunftsfähigkeit nicht allein von einer Veränderung der Bewirtschaftungsmethoden ab. Die Gestaltung zukunftsfähiger Agrarlandschaften bedarf einer über den einzelnen Schlag hinausgehenden Betrachtung und ist eine gesamtgesellschaftliche Aufgabe, die deutlich über die Verantwortung und Möglichkeiten der einzelnen GrundstückseigentümerInnen und -bewirtschafterInnen hinausreicht. Ausgehend von den bekannten ökologischen Problemen und den im Beitrag ausführlicher dargestellten besonderen Herausforderungen des Klimawandels untersuchen wir daher, was Zukunftsfähigkeit bedeutet und welche gesellschaftlichen Zi...
BirdHab model: bird habitat suitability model applied to input data from the Lossa River Basin in... more BirdHab model: bird habitat suitability model applied to input data from the Lossa River Basin in Central Germany combined with a willingness to pay function for biodiversity. SWAT agronomy model: Calculates contribution margins for crops grown in the Lossa River Basin based on SWAT model output data.
The largest impact of land-use change on catchment hydrology can be linked to deforestation. This... more The largest impact of land-use change on catchment hydrology can be linked to deforestation. This change, driven by exponential population growth, intensified food and industrial production, has resulted in alterations in river flow regimes such as high peaks, reduced base flows, and silt deposition. To reverse this trend more extensive management practices are becoming increasingly important, but can also lead to severe losses in agricultural production. Land-use optimization tools can help catchment managers to explore numerous land-use configurations for the evaluation of trade-offs amongst various uses. In this study, the Soil and water assessment tool (SWAT) model was coupled with a genetic algorithm to identify land-use/management configurations with minimal trade-offs between environmental objectives (reduced sediment load, increased stream low flow) and the crop yields of maize and soybean in Nyangores catchment (Kenya). During the land-use optimization, areas under conventi...
Stream–riparian networks are subject to multiple human pressures that threaten key functions of a... more Stream–riparian networks are subject to multiple human pressures that threaten key functions of aquatic and terrestrial ecosystems, drive habitat and diversity losses, affect riparian connectivity and cause stakeholder conflicts. Designing riparian landscapes in a way that they can simultaneously meet multiple competing demands requires a clear understanding of existing trade‐offs, and a landscape‐scale perspective on the planning of reforestation measures. This study applied a landscape optimization algorithm for allocating riparian forest management measures in the intensively used agricultural catchment of the Zwalm River (Belgium). We optimized forest allocation to improve stream ecological quality (EPT index), functional diversity (diatoms) and riparian carbon processing (cotton‐strip assay), while minimizing losses in agricultural production potential. Regression models were developed to predict the target indicators for 489 segments of the Zwalm riparian corridor, using spati...
Land-use intensification in agroecosystems has led to population declines in many taxonomic group... more Land-use intensification in agroecosystems has led to population declines in many taxonomic groups, especially farmland birds. Two contrasting conservation strategies have therefore been proposed: land sharing (the integration of biodiversity conservation in low-intensity agriculture) and land sparing (the spatial separation of high-yielding agriculture and areas for conservation). Despite the large academic interest in this field, only few studies have taken into account stakeholders’ perspectives of these strategies when assessing conservation implications. We modeled the effects of three land-use scenarios (a business-as-usual, a land-sharing, and a land-sparing scenario), developed together with regional stakeholders, on the habitat area of 13 regionally endangered bird species in the Middle Mulde River Basin (Saxony, Germany). We used random forest models based on environmental variables relating to land-use/cover, climate and soil characteristics, occurrence of linear landscap...
Deliverable 4.1 of BiodivERsA Project TALE (01LC1404A) 'Towards multifunctional agricultural ... more Deliverable 4.1 of BiodivERsA Project TALE (01LC1404A) 'Towards multifunctional agricultural landscapes in Europe: Assessing and governing synergies between biodiversity and ecosystem services'. The TALE project is funded through the 2013-2014 BiodivERsA/FACCE-JPI joint call for research proposals, in this deliverable with the national funders German Federal Ministry of Education and Research (BMBF) and The Austrian Science Fund (FWF).
The data sets contains the major results of the article "Improving information extraction fr... more The data sets contains the major results of the article "Improving information extraction from model data using sensitivity-weighted performance criteria" written by Guse et al. (2020). In this article, it is analysed how a sensitivity-weighted performance criterion improves parameter identifiability and model performance. More details are given the in article. The files of this dataset are described as follows. Parameter sampling: FAST parameter sampling.xlsx: To estimate the sensitivity, the Fourier Amplitude Sensitivity Test (FAST) was used (R-routine FAST, Reusser, 2013). Each column shows the values of the model parameter of the SWAT model (Arnold et al., 1998). All parameters are explained in detail in Neitsch et al. (2011). The FAST parameter sampling defines the number of model runs. For twelve model parameters as in this case, 579 model runs are required. The same parameter sets were used for all catchments. Daily sensitivity time series: Sensitivity_2000_2005.xls...
The acquisition of adequate weather data is the most challenging task when setting up a hydrologi... more The acquisition of adequate weather data is the most challenging task when setting up a hydrologic model. While vegetation, soil and topographic information can be newly assessed if not available, weather data are needed as extensive time series. In our study, we analysed CFSR and WFDEI precipitation data in comparison to rain gauges in the Brazilian territory (n = 2027) for the period 1980-2010 to evaluate which weather reanalysis better represented precipitation in Brazil. Further, we used monthly-based interpolations (and historic monthly averages to fill gaps in time series) to further improve the best data set to measured precipitation. We then applied the interpolated precipitation in the river discharge modelling of the Tocantins Basin with the Soil and Water Assessment Tool (SWAT). Both reanalyses showed better statistics for monthly series than for daily and annual series. WFDEI better represented Brazilian precipitation than CFSR with higher coefficient of determination (R2 = 0.76 vs. 0.50; medians), coefficient of determination multiplied by the coefficient of the regression (bR2 = 0.70 vs. 0.39) and Nash-Sutcliffe coefficient (NS = 0.72 vs. 0.21), but equal percentages of bias (Pbias = 6.9 vs. 3.4). We applied interpolated WFDEI precipitation data in the hydrologic model of the Tocantins Basin with SWAT using 7 river gauges and 3 reservoirs, with an NS > 0.60 for 6 out of 10 stations (NS = 0.19, 0.38, 0.39 and 0.44 for the other 4 stations). Green water flow increased from South-East (640-840 mm) to North-West (1140-1440 mm), while green water storage increased from South (330-1070 mm) to North (2180-3290 mm). Blue water had a less clear pattern, with lower values in the South and central borders of the basin (20-560 mm) and higher values in the central axis and the North (920-1460 mm). Our analysis suggested that WFDEI was an accurate representation of Brazilian precipitation and allowed for the use of reanalysis weather data instead of observational data in hydrologic modelling.
The data set provides the output of a genetic algorithm optimizing a stylized urban region with r... more The data set provides the output of a genetic algorithm optimizing a stylized urban region with respect to three target functions: urban compactness, climate regulation as an exemplary ecosystem service and vascular plant species richness as a measure of biodiversity. The optimisation varies the spatial allocation of three types of land cover blocks in a stylized urban region: high- and low-density and park blocks which consist of green and/or built-up cells. We systematically vary landscape composition at the block level, but keep city size constant. The data set is related to a publication submitted to Frontiers in Environmental Science.
The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the col... more The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors. ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate ...
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