ASSESSING THE ENVIRONMENTAL EXTERNALITIES OF AGROFORESTRY: IMPROVEMENTS IN FARM-SAFE Silvestre Garcia de Jalon, Anil Graves, Kristina J. Kaske, Joao Palma, Josep Crous-Duran and Paul J. Burgess 3 rd European Agroforestry Conference Montpellier, France May 25 th, 2016
Farm-SAFE Intro Farm-SAFE: A Microsoft Excel-based spreadsheet model to evaluate the costs and benefits of arable, forestry and agroforestry systems (Graves et al. 2007; 2011) Developed in SAFE project (Dupraz et al. 2005) Intensive agriculture has led to negative environmental externalities (e.g. soil degradation, GHG emissions, nonpointsource pollution, a reduction of landscape and recreation values) Agroforestry provides an opportunity to reduce them In AgForward (Burgess et al. 2015), Farm-SAFE is been adapted to evaluate environmental externalities e.g.: GHG emissions and sequestration Soil erosion losses by water Nonpoint-source pollution from fertiliser use
Cumulative Net Margin ( ha -1 ) Cumulative Net Margin ( ha -1 ) Financial results of Farm-SAFE: Cumulative Net Margin Grants can determine the land-use profitability Bedfordshire, UK 10000 With grants 10000 Without grants 8000 8000 6000 4000 2000 0-2000 -4000 0 5 10 15 20 25 30 6000 4000 Arable 2000 Forestry Agroforestry 0 0 5 10 15 20 25 30-2000 -4000-6000 Years -6000 Years 10 20 30 Arable: wheat-wheat-barley-oilseed Forestry: hybrid poplar Agroforestry: hybrid poplar with wheat-wheat-barley-oilseed
Cumulative Net Margin ( / ha) Cumulative Net Margin ( / ha) Financial results of Farm-SAFE: Cumulative Net Margin Grants can determine the land-use profitability Extremadura, Spain With grants Without grants 3500 3000 2500 2000 1500 1000 500 0-500 -1000-1500 0 10 20 30 40 50 60 20 40 60 Years 3500 3000 2500 2000 1500 Arable 1000 Forestry 500 Agroforestry 0 0 10 20 30 40 50 60-500 -1000-1500 Years Arable: oat-grassland Forestry: holm oak Agroforestry: dehesa with holm oak and grassland
Evaluating externalities in Farm-SAFE: GHG emissions A life-cycle based data were used The model was adapted for GHG emissions and sequestration in aboveground biomass The resources and energy used in the production system (input) and the emissions released into the environment (output) were included in the economic analysis The carbon price used for the calculations was 7.63 t CO 2-1 which is being achieved in the UK (www.forestry.goc.uk/carboncode)
System boundary for the Life Cycle Assessment (LCA) in Farm-SAFE Manufacture and delivery of machinery and buildings Fuel for farm machinery Manufacture and delivery of fertilisers and pesticides Fertilisers Pesticides Vehicle and machinery operations Sub-soiling Ploughing Cultivation Seeds Straw Reduced tillage Direct drilling Fertiliser application Pesticide application Chemical application Crop production Grains, seeds and straw Farm Gate Harvest Harvest Baling Adapted from Kaske (2015)
Fuel consumption (L ha-1) Work rate (hours ha-1) Farm-SAFE allows users to change the tractor size and soil type For some operations, these factors are associated with the fuel consumption and work rate GHG emissions Equations of these relationships were calculated and used to interpolate values a) Ploughing with four furrows b) Subsoiling of tramlines (3 leg sub-soiler) 50 2.0 40 1.6 y = 0.0052x + 1.0029 30 20 y = 0.2149x + 23.621 1.2 0.8 10 0.4 0 0 25 50 75 100 Proportion of clay in soil (%) 0.0 0 25 50 75 100 Proportion of clay in soil (%) Assumed relationship of the effect of soil clay content on fuel consumption for ploughing, and the work rate of sub-soiling
Annually emitted carbon by machinery and agrochemicals manufacturing and field operations 3.500 Bedfordshire, UK Anual carbon emissions (t CO2eq ha -1 3.000 2.500 2.000 1.500 1.000 0.500 Arable Forestry Agroforestry - 0 5 10 15 20 25 30 Years
Carbon emissions (t CO2eq / ha) Carbon emissions (t CO2eq / ha) Cumulative emitted carbon by machinery and agrochemicals manufacturing and field operations Bedfordshire, UK Schwarzbubenland, Switzerland 140.0 140.0 120.0 120.0 100.0 100.0 80.0 60.0 80.0 Series1 60.0 Series2 40.0 Series3 40.0 20.0 20.0-0 5 10 15 20 25 30 Years - 0 10 20 30 40 50 60 Years Arable Forestry Agroforestry
Equivalent Annual Value (EAV) in Bedfordshire, UK (t = 30 years, i = 5%) Arable 1 Silvoarable 2 Forestry 3 EAV of CO 2 eq emissions ( ha -1 year -1 ) -40-21 -8 EAV of CO 2 eq seq. ( ha -1 year -1 ) 0 64 88 EAV with grants ( ha -1 year -1 ) 548 342 467 EAV with grants and GHG exter. ( ha -1 year -1 ) 508 385 546 EAV without grants ( ha -1 year -1 ) 302 82 23 EAV without grants and GHG exter. ( ha -1 year -1 ) 262 125 103 Not including the grants, the inclusion of GHG emissions reduced the difference between the arable and the silvoarable system from 220 ha -1 to 137 ha -1 Including environmental costs can change the societal advantage of the land uses 1 arable system: a rotation of wheat, wheat, barley and oilseed rape 2 silvoarable system: same rotation as the arable system with poplar hybrids planted at 113 trees ha -1 3 forestry system: hybrid poplars planted at a density of 156 trees ha -1
Soil erosion losses by water The Revised Universal Soil Loss Equation (RUSLE) is used in Farm- SAFE to calculate the annual soil loss (tons ha -1 year -1 ) A = R * K * LS * C * P Where A is the estimated average soil loss, R rainfall-runoff erosivity, K soil erodibility, L slope length, S slope steepness, C cover-management, P support practice When comparing in the same geographical area, the R, K, and LS factors were considered constant to compare soil loss in arable, forestry and silvoarable systems Only changes in C and P factors are used to evaluate landuse differences
K-factor in the EU (used in Farm-SAFE) 30 0'0"W 20 0'0"W 10 0'0"W 0 0'0" 10 0'0"E 20 0'0"E 30 0'0"E 40 0'0"E 50 0'0"E K-factor Value High : 0.0766097 Low : 0.00469355 60 0'0"N 60 0'0"N K-factor Value High : 0.0766097 50 0'0"N 50 0'0"N Low : 0.00469355 40 0'0"N 40 0'0"N 10 0'0"W 0 0'0" 10 0'0"E 20 0'0"E Source: Data obtained from the European Soil Data Centre (ESDAC)
C-factor C-factor values based on the literature review Different values for each species For trees, C-factor is dynamically calculated it decreases proportionally to tree growth (height and canopy area) For agroforestry systems (based on Palma et al. 2007): C = [Cov c * C c ] + [Cov f * C f ] Where C is the C-factor of an agroforestry system, Cov c the land cover fraction of the crop component, C c the C-factor of the crop component + Cov f the land cover fraction of the tree component, and C f the C-factor of the tree component Cov c and Cov f depend on the distance between trees and the canopy growth
Soil erosion losses (t ha -1 year -1 ) Annual soil erosion losses by water in Bedfordshire, UK The C-factor decreases as the canopy area and tree height increase Soil erosion losses are reduced 0.6 0.5 0.4 0.3 0.2 Arable Forestry Agroforestry 0.1 0.0 0 5 10 15 20 25 30 Years 20 30 Arable: wheat-wheat-barley-oilseed Forestry: hybrid poplar Agroforestry: hybrid poplar with wheat-wheat-barley-oilseed
Cumulative soil erosion losses (t ha- 1 ) Cumulative soil erosion losses by water in Bedfordshire, UK In the first years there is no great difference compared to the arable system The effect of trees on reducing soil erosion starts around year 10 12.0 10.0 8.0 6.0 4.0 Arable Forestry Agroforestry 2.0 0.0 0 5 10 15 20 25 30 Years Arable: wheat-wheat-barley-oilseed Forestry: hybrid poplar Agroforestry: hybrid poplar with wheat-wheat-barley-oilseed
Next steps in Farm-SAFE Adding more regulating services and improving accuracy Nitrogen and Phosphorous leaching Air quality Cultural services Recreation services Incorporating PPGIS in Farm-SAFE? Landscape diversity
Conclusions Financial analyses can quantify the benefits and costs of different land management practices from a farmer s perspective this does not necessarily reflect the full benefits and costs to society Including environmental externalities helps identify the most appropriate land use decisions from a societal perspective Compared to arable, including GHG emissions (and most services) increased the relative value of agroforestry and forestry The ecosystem services provision evolves as trees grow Farm-SAFE allows a dynamic assessment of ecosystem services More case studies and model improvements to assess ecosystem services are being developed within the AGFORWARD project
Thank you Silvestre Garcia de Jalon s.garcia-de-jalon@cranfield.ac.uk We acknowledge support of the European Commission through the AGFORWARD FP7 research project (contract 613520). The views and opinions expressed in this presentation are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission.
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