(some) Tools available for assessing the environmental needs at EU level

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Tobias Dixon
6 years ago
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1 (some) Tools available for assessing the environmental needs at EU level JM Terres JRC.D5 (F Bouraoui, F Dentener, B Grizzetti, A Leip, E Lugato, P Panagos, ML Paracchini, A de Roo) Best practices addressing environmental and climate needs AGRI-JRC workshop 23/24 March 2017

2 Content The JRC JRC expertise in tools and modelling in agriculture Examples of pan-european bio-physical modelling SOC, soil erosion, water quality, water abstraction, climate change impact Examples of pan-european observation datasets Biodiversity features semi-natural vegetation, woody elements Geospatial analysis for better targeting (ex. risk of farmland abandonment) Farm Level Tools to assess impacts of farming practices on the environment 2

The JRC inside the European Commission the Commission's in-house

Directorate General carrying out direct research Provides EU

whole policy cycle Works in support of other Commission services,

3 The JRC inside the European Commission the Commission's in-house science service 7 directorates in 5 countries Only Commission Directorate General carrying out direct research Provides EU policies with evidence-based scientific support throughout the whole policy cycle Works in support of other Commission services, EU Institutions, and Member States Independent of industry and national interests 3

4 JRC has strong expertise in tools / modelling in agriculture Land characterisation Land evaluation methods, Land quality assessment, Agro-ecological zoning e.g. Methodology for Area with Natural Constraints Bio-physical and geo-spatial modelling e.g. crop modelling (MARS bulletin), pan-european flood model Agro-Economic modelling Quantitative economic analysis (+ linkage to env. & climate assessment) e.g. AgLink (country), CAPRI (region), IFM-CAP (farm) Tools for farming practices impacts assessment Farm Level Tools e.g. Low Carbon Farm, EFA calculator, (SOSTARE) 4

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, et al, 2014 Measured organic carbon content at LUCAS topsoil survey

6 Organic carbon (SOC) in European agricultural soils (model) Source: Lugato E., et al., 2014 Source: de Brogniez D., et al, 2014 Measured organic carbon content at LUCAS topsoil survey (2009) sampling locations The average SOC stock: 64 (arable), 55 (orchard) and 150 (grassland) t/ha of C

7 Soil erosion by water (model) Average rate of soil loss by water erosion in EU28: 2.4 t/ha/year (data 2012) 6.6% of EU28 agricultural area suffers from moderate to severe erosion (>11 t/ha/year). Arable and orchard are more affected (7.4%) than permanent grasslands and pasture (4.2%).

8 Water quality (measurements) Source: EEA WISE WFD database SOER 2015 Shares of river and lake water bodies in different River Basin Districts (RBD) holding less than good ecological status or potential 9

9 Water pollution: agriculture compared to other sources (model) Nitrogen Phosphorus Source: Bouraoui et al 2011, Grizzetti et al 2012 Agriculture contributes significant amount of nutrients into freshwater, impairing their ecological status and leading to eutrophication. European rivers export 4 million tons yearly of N to coastal water, a large share from agriculture Contribution of agriculture to N water pollution can be very important in quantity and share in regions 10 with high livestock density

Source: DG JRC D2 Modelling 2010 Most of agriculture irrigation occurs in areas already

10 Water abstraction: Irrigation for agriculture (model) The Water Exploitation Index (ratio water abstraction / average freshwater resources), indicates areas where water stress occurs Source: DG JRC D2 Modelling 2010 Most of agriculture irrigation occurs in areas already affected by water stress Abstraction for agriculture: Spain (60%), Greece (88%) Source: De Roo et al

on crops Targeting adaptation measures Wheat yield

11 Climate change impact on agricultural production (model) Climate Impacts in Europe The JRC PESETA II Project Impacts on crops Targeting adaptation measures Wheat yield with/without adaptation strategies (% difference under 2 climate scenarii) 12

12 Biodiversity features in agriculture (observations + model) NUTS2 aggregat Share of High Nature Value farmland Share of woody vegetation in agricultural land Semi natural vegetation abundance in agricultural land

13 Geo-spatial assessment - Risk of Farm Land Abandonment Targeting regions with Risk of Farm Land Abandonment Results Composite Index Drivers: land market, income, remoteness Normalised at EU27 level Farm-Type % (CI>0.7) FT4= Specialist Grazing livestock 14

remoteness, investment, farmer age) Normalised at MS level Farm Type 1 2 3

14 Geo-spatial assessment - Risk of Farm Land Abandonment Targeting regions with Risk of Farm Land Abandonment Composite Index (land market, income, remoteness, investment, farmer age) Normalised at MS level Farm Type % Farm Type %

Farm Level Tool: from advice to performance to evaluation Low Carbon Farm To assess farm contribution to GHG emissions, to promote low carbon farming practices (Advisory system) SOSTARE: Assessing

15 Farm Level Tool: from advice to performance to evaluation Low Carbon Farm To assess farm contribution to GHG emissions, to promote low carbon farming practices (Advisory system) SOSTARE: Assessing farm performance EFA calculator to evaluate Ecological Focus Areas potential impacts on the env. Farm level information Calculate the potential impact of EFA features on ecosystem services, biodiversity and management Policy evaluation

16 Questions?

Environmental impact assessment of CAP greening measures using CAPRI model

Environmental impact assessment of CAP greening measures using CAPRI model JM Terres, C. Bulgheroni, A. Leip, ML Paracchini 19 th MARS conference Vilnius Plenary session: Environmental aspects of the CAP