El papel de la familia en la religiosidad del niño

HASHEMI F.1_{, OLESEN J.E.}1_{, DALGAARD T.}1_{, BØRGESEN C.D.}1

1 _{Department of Agroecology, Aarhus University, Blichers Allé 20, 8830 Tjele, Denmark}

INTRODUCTION

Denmark is one of the largest contributors of agricultural nitrogen (N) discharges to the Baltic Sea measured in terms of N-load per hectare. Many N mitigation measures have already been implemented in Denmark since the 1980s, but this has been insufficient to meet the environmental objectives without adversely affecting agricultural production. To this end, a combination of innovative methods to reduce discharges to recipient waters is needed. One such innovative strategy is spatially differentiated N mitigation in agriculture to replace the currently uniform regulation in Denmark and to exploit the fact that there is significant spatial variation in natural groundwater and surface water N-reduction (removal by biogeochemical processes or sedimentation).

MATERIAL AND METHODS

A review of 130 published articles was carried out with scenario-based modelling of methods for reducing the nutrient load to the aquatic environment (Hashemi et al., 2016). Based on this overview, new methods developed for scenario analysis in two Danish catchments (Norsminde and Odense) based on spatially differentiated aspects of groundwater N-reduction considering spatial constraints (farm boundary and soil type) and two different scales for N-reduction maps(Hashemi et al., 2018a). Ten scenarios were defined using cover crops within the crop rotation, set-aside on high N-load areas and N-leaching relocation based on spatial variation in N-reduction to reach N-load reduction targets of 20% or 40%. Furthermore, the potential of farm-scale measures versus landscape measures for reducing N-loads was investigated in the Odense catchment through a combination of farm and landscape measures to reach the required N-load reduction target of 38% (Hashemi et al., 2018c). This resulted in 17 scenarios by reducing N-leaching at farm (changing to crop rotation and application of cover crops) and landscape scales (set-aside application on high N-load areas) and enhancing N- reduction at landscape scale (wetlands). Scenario analyses for were performed using a map-based N- load model to achieve N-load reduction targets with least effect on agricultural production. Using information on variation in groundwater N-reduction maps for construction of spatially differentiated scenarios in the Norsminde catchment provided a basis for exploring the uncertainty in the estimated results (Hashemi et al., 2018b). To reduce the uncertainty in the estimated N-load reductions, three different methods for targeting the set-aside were developed. These methods included application of set-aside based on each individual N-reduction map compared to a mean of 15 randomly chosen N- reduction maps, using the spatial frequency of high N-load and using the spatial frequency of low N- reduction. The efficiency of using different methods was compared in terms of set-aside area required for a 50 or 80% probability of achieving the 20% N-load reduction.

RESULTS AND DISCUSSION

The scenario analysis showed that the highest reduction in catchment N-load and in set-aside area were achieved where there was the least constraint for N-leaching relocation. The greatest reductions in N-load and set-aside for the spatially differentiated method were achieved using the high-resolution rather than the low-resolution N-reduction maps. The results also showed that a combination of land use, soil type, spatial variation in N-reduction and cropping conditions within each catchment affect the reduction in excessive N-loadings and required set-aside area. Using a combination of measures showed that it was possible to achieve the N-load reduction target without need for set-aside. The potential gain of farm-scale measures was affected by farm type, soil type and the N-reductions possible, while the feasibility of using wetlands to reduce N-load depends on the availability of landscape features that can be used for the establishment of wetlands. In relation to uncertainty

analysis, the results showed that that using ensembles of N-reduction maps rather than individual N- reduction maps could improve the efficiency of spatially differentiated strategies. Using a frequency map of high N-load areas compared to set-aside maps based on average N-reduction map and a spatial frequency of low N-reduction is more effective in terms of N-load and set-aside reduction.

CONCLUSION

It was found that spatially differentiated strategies for N reduction and using combination of measures can significantly reduce the N load with low impact on agricultural production, and this potential gain varies considerably between catchments, depending on spatial variation in groundwater N reduction and land use. However, the potential benefit of the N-load reduction strategies resulting from a combination of measures at both farm and landscape scale is limited by farm type and the potential area available for the application of measures. In addition, it will be difficult to exploit the full potential in practice due to the current agricultural structure and the uncertainty associated with higher resolution of groundwater N-reduction maps. Despite the higher uncertainty of estimated N-load reductions based on fine-scale compared to coarse-scale N-reduction maps, we suggest using grid- scale N-reduction maps for spatially differentiated strategies since the benefits in terms of the smaller set-aside area required at this scale outweighs the higher uncertainty. Developing new methods for reducing the uncertainty in the estimated results of N-load reductions showed the benefit of using a frequency of high N-load areas for targeting set-aside compared to the other two methods.

Acknowledgements: This work was carried out in the BONUS SOILS2SEA project (www.Soils2Sea.eu), which received funding from BONUS (Art 185), funded jointly by the EU and Innovation Fund Denmark, The Swedish Environmental Protection Agency, The Polish National Centre for Research and Development, The German Ministry for Education and Research, and The Russian Foundation for Basic Research (RFBR). This study was further supported by The NitroPortugal Project and the Innovation Fund Denmark (contract number 0603- 00517B) through the dNmark Research Alliance (http://dnmark.org) supported by the Danish Council for Strategic Research (Ref. 12-132421).

REFERENCES

Review of scenario analyses to reduce agricultural nitrogen and phosphorus loading to the aquatic environment. Hashemi, F., Olesen, J. E., Dalgaard, T., & Børgesen, C. D. Science of the Total Environment, 2016. 573, 608-626.

Spatially differentiated strategies for reducing nitrate loads from agriculture in two Danish catchments. Hashemi, F., Olesen, J. E., Hansen, A. L., Børgesen, C. D., & Dalgaard, T. Journal of environmental management, 2018a. 208, 77-91.

Reducing uncertainty of estimated nitrogen load reductions to aquatic systems through spatially targeting agricultural mitigation measures using groundwater nitrogen reduction. Hashemi, F., Olesen, J. E., Jabloun, M., & Hansen, A. L. Journal of environmental management special Issues, 2018b.218, 451–464.

Potential benefits of farm scale measures versus landscape measures for reducing nitrate loads in a Danish catchment. Hashemi, F., Olesen, J. E., Børgesen, C. D., Tornbjerg, H., Thodsen, H., & Dalgaard, T. Science of the Total Environment, 2018c.637-638, 318-335.

20th _{Nitrogen Workshop}

Coupling C-N-P-S cycles

June 25-27, 2018

Le Couvent des Jacobins, Rennes – France