Assessing the role of agri-environmental measures to enhance the environment in the Veneto Region with a model based-approach Francesco Morari Department of Agronomy Food Natural resources Animals Environment - University of Padova, Italy
Introduction Evaluating the global impact of AEMs on biogeochemical cycles is particularly tricky
Study Site Veneto region: 18400 km 2 (55% alluvial plain) Climate: continental sub-humid T mean 7-15 C; P 700-1400 mm y -1 ET 0 750-1100 mm y -1 Farming covers 57% of regional land, mainly in the plain area (92%) Soils range from silty and sandy-loam in the plain to clay and clay-loam in the mountains and piedomont areas SOM: 1-2% in the plain, up to 4-6% in the mountain
Study Site
Open Questions Do the AEMs improve agro-ecosystems? 11 Are AEMs effective regardless the geographical variability? Is the «action-oriented» approach satisfactory in terms of ecological benefits? AIMS Evaluate the overall effectiveness of AEMs to reduce N pollution across Veneto Region Test a model-gis platform to approach a «spatial targeting» scheme that considers the pedo-climatic and management variability
Diapositiva 5 11 farmers are not paid for the provision of production and outcomes, but for the adoption of land management practices NDF; 21/06/2016
MATERIAL AND METHODS
Methodological Approach MUNICIPAL UNITS DTM Crop and management database Fertilisation database Irrigation database Model-GIS platform integrates management and pedo-climatic information GIS CLIMATE PEDOLOGY Meteorological database Soil profile and horizons database Totally 1341 polygonal units DAYCENT model POLYGONAL UNITS FIELD DATA R C-N-P cycles DAYCENT MODEL Input data Output data R Model validation GIS GHG Emissions Soil quality Water quality Final maps
Model validation N in crop production N leaching N-N 2 O emission
BASELINE scenario Simulated Scenarios Conventional farming practices without the adoption of AEMs Simulated crops across Veneto covering 60% of UAA - maize, wheat, soybean, sugar beet, sunflower, rapeseed, potato, pastures and meadows (permanent or in succession) CLC Veneto Region Arable land Permanent crops Pastures Forests and seminatural areas Artificial surfaces Little / No vegetation
Simulated Scenarios AEM scenario Based on spatial distribution data of AEMs - RDP 2007-2013 BUFFER STRIPT AEMs Main management aspects ID Buffer strips new 6-m wide, no fertilization BUFFER new Woodlands in arable lands new No fertilization, continuous soil WOODLAND new cover Buffer strips maint. (21 yrs) 6-m wide, no fertilization BUFFER maint Woodlands in arable lands maint. (21 yrs) No fertilization, cont. soil cover WOODLAND maint Increase of SOM through farmyard manure input N in = 130 kg ha -1 y -1 FMY in Organic farming new Organic instead of mineral input OF new Organic farming maint. (21 yrs) Organic instead of mineral input MEADOWS OF maint Pastures & permanent meadows maint. (21 yrs) No chemical fertilization PAST-MEAD maint Arable lands to permanent meadows No fertilization MEAD new Conservation agriculture new No till, permanent soil cover, crop rotations CA new Continuous soil cover new Cont. soil cover, green manure CC new Optimization of irrigation Irrigation -25% IRR opt CONSERVATION AGRICULTURE Optimization of fertilization Mineral fertilization -30% FERT opt CONTINUOUS SOIL COVER ORGANIC FERTILIZATIONS
AEMs Performance Soil quality: SOC stock (0-30 cm layer), soil erosion Water quality: total N leaching, P leaching, P runoff GHG emissions: CO2, CH 4, N 2 O Difference between agroecosystems adopting (Y m ) and not adopting (Y 0 ) the AEMs: Absolute Agroecosystem quality AEM effectiveness SOC stock N leaching N-N 2 O (Mg ha -1 ) (kg ha -1 y -1 ) High >65 <10 <1 Medium 40-65 10-35 1-3 Low < 40 >35 >3 Relative
RESULTS
SOC Long-term effect (21 yrs) 40 20 10 0 Permanent soil cover -10 FERT opt IRR opt CC new CA new MEAD new PAST-MEAD maint OF maint OF new FMY in WOODLAND maint BUFFER maint WOODLAND new -20 BUFFER new SOC (Mg ha -1) 30 Median 25%-75% Non-Outlier Range + 15% in the low plain + 45-75% in the piedmont areas
N LEACHING 30 20 Soil cover and water management 0-10 -20-30 Organic inputs Efficient crop systems? -40-50 FERT opt IRR opt CC new CA new MEAD new PAST-MEAD maint OF maint OF new FMY in WOODLAND maint BUFFER maint WOODLAND new -60 BUFFER new N-leaching (kg ha -1 y-1) 10 Median 25%-75% Non-Outlier Range Surplus of N in sandy & silty soils + 0-80%
FERT opt IRR opt CC new CA new MEAD new PAST-MEAD maint OF maint OF new FMY in WOODLAND maint BUFFER maint WOODLAND new -2.0 BUFFER new N-N2O emissions (kg ha -1 y-1) N2O EMISSIONS 2.0 1.0 0.0-1.0 Need to enhance fertilization efficiency -3.0-4.0 Median 25%-75% Non-Outlier Range
16 AEMs effectiveness
Diapositiva 16 16 No carbon stock. Moderate/Low effect on N leaching and GHG emissions. Pedo-climatic conditions reduce yields and therefore less efficient system NDF; 22/06/2016
12 AEMs effectiveness Reduced N mineral input Conservation agriculture
Diapositiva 17 12 No carbon stock. Moderate/Low effect on N leaching and GHG emissions. Pedo-climatic conditions reduce yields and therefore less efficient system NDF; 22/06/2016
14 AEMs effectiveness Organic farming - maintenance Organic farming - new
Diapositiva 18 14 Effects of organic input in the long-term. Short-term highlights no improved soil conditions (low OM) that likely reduced yields, with effects of NUE. NDF; 22/06/2016
15 AEMs effectiveness
Diapositiva 19 15 Effects of organic input in the long-term. Short-term highlights no improved soil conditions (low OM) that likely reduced yields, with effects of NUE. NDF; 22/06/2016
Conclusions DAYCENT is a sensitive model but is not able to represent the total complexity of the agro-ecosystems (e.g. weed effect, soil compaction) The effectiveness of AEMs was different in a spatiotemporal perspective address agro-environmental policies towards a spatial target (result-oriented) approach instead of a generalized support to farmers (action-oriented) Long-term evaluation of AEMs is sometimes required (e.g. organic farming) N fertilizer management (reduced mineral N, change to organic N) is sometimes inefficient unless combined with others Best strategies for N cycle improvement include i) permanent soil cover; ii) minimum soil disturbance
Questions? Acknowledgments: This research was co-financed by the Rural Development Programme for the Veneto 2007-2013 19th Nitrogen Workshop - Skara, Sweden - June 27-29, 2016