This document summarizes a study that quantified and valued the ecosystem services provided by tree-based intercropping systems in Quebec, Canada. The study assessed services like soil quality regulation, food and fiber production, water quality regulation, pollination, wind protection, biological control, air quality regulation, and climate regulation. It used indicators and data to estimate biophysical production of services and economic valuation methods to assign monetary values. The study found that while private agricultural benefits were slightly reduced, the total value of ecosystem services greatly exceeded this and that agroforestry could help limit future climate change impacts on crop yields. It was supported by funding from Ouranos and the Fonds vert of the Quebec government.
The Diagnosis and Recommendation Integrated System (DRIS) method was employed to monitor the nutrients status of onion plants (Allium cepa L.) grown in sandy soil at winter season in the Nubaria, Behira Governorate. DRIS norms were established for various nutrient ratios obtained from high yield group of onion plants. Seventy two samples of bulb were analyzed for N, P, K, Fe, Mn, Zn and Cu content and bulb yield were recorded of onion farms fromNubaria, Behira Governorate. The forms of expression for different nutrients and their norms were selected, based on the highest variance ratio between low and high yielding group. The results showed that the average yield in the high-yielding group was 16.14ton ha-1, while the average yield in the low-yielding group was 11.18ton ha-1. Theselected DRIS norms of onion plants grown in sandy soil wereP/N: 0.154, K/N: 0.348, N/Fe: 83.45, Mn/N: 0.0015, Zn/N: 0.0017, Cu/N: 0.006, P/K: 0.441, P/Fe: 12.74, P/Mn: 106.5, Zn/P: 0.011, Cu/P: 0.004, Fe/K: 0.035, Mn/K: 0.004, Zn/K: 0.005, Cu/K: 0.002,Fe/Mn: 8.382, Fe/Zn: 7.202, Fe/Cu: 20.34, Zn/Mn: 1.164, Cu/Mn:0.413, Cu/Zn: 0.355. The sufficient ranges for N, P and K were 1.987 - 2.769 %, 0.282 - 0.448 % and 0.704 - 0.944 %, respectively. As well as, the sufficient ranges for Fe, Zn, Mn and Cu were 258.3 - 312.7, 29.72 - 38.64, 34.96 - 44.46 and 11.79 - 16.51 ppm, respectively. Determine the optimum values in bulb are an important indicator of the high quality of the bulbs, becausethe relationship between of those nutrientsand all these vehicleswhich are expressive on bulbquality.
Methane in Coastal Blue Carbon EcosystemCIFOR-ICRAF
Presented by Judith A. Rosentreter
(Postdoctoral Researcher Centre for Coastal Biogeochemistry Southern Cross University, Lismore, Australia) on 25 September 2019 at Blue Carbon Regional Workshop, Merida, Yucatan.
The Diagnosis and Recommendation Integrated System (DRIS) method was employed to monitor the nutrients status of onion plants (Allium cepa L.) grown in sandy soil at winter season in the Nubaria, Behira Governorate. DRIS norms were established for various nutrient ratios obtained from high yield group of onion plants. Seventy two samples of bulb were analyzed for N, P, K, Fe, Mn, Zn and Cu content and bulb yield were recorded of onion farms fromNubaria, Behira Governorate. The forms of expression for different nutrients and their norms were selected, based on the highest variance ratio between low and high yielding group. The results showed that the average yield in the high-yielding group was 16.14ton ha-1, while the average yield in the low-yielding group was 11.18ton ha-1. Theselected DRIS norms of onion plants grown in sandy soil wereP/N: 0.154, K/N: 0.348, N/Fe: 83.45, Mn/N: 0.0015, Zn/N: 0.0017, Cu/N: 0.006, P/K: 0.441, P/Fe: 12.74, P/Mn: 106.5, Zn/P: 0.011, Cu/P: 0.004, Fe/K: 0.035, Mn/K: 0.004, Zn/K: 0.005, Cu/K: 0.002,Fe/Mn: 8.382, Fe/Zn: 7.202, Fe/Cu: 20.34, Zn/Mn: 1.164, Cu/Mn:0.413, Cu/Zn: 0.355. The sufficient ranges for N, P and K were 1.987 - 2.769 %, 0.282 - 0.448 % and 0.704 - 0.944 %, respectively. As well as, the sufficient ranges for Fe, Zn, Mn and Cu were 258.3 - 312.7, 29.72 - 38.64, 34.96 - 44.46 and 11.79 - 16.51 ppm, respectively. Determine the optimum values in bulb are an important indicator of the high quality of the bulbs, becausethe relationship between of those nutrientsand all these vehicleswhich are expressive on bulbquality.
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Presented by Judith A. Rosentreter
(Postdoctoral Researcher Centre for Coastal Biogeochemistry Southern Cross University, Lismore, Australia) on 25 September 2019 at Blue Carbon Regional Workshop, Merida, Yucatan.
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Session 3.6 quantification & valuation of eco services
1. Quantification and Valuation of Ecosystem
Services of Tree-Based Intercropping
Systems in Quebec, Canada
Mahbubul Alam, Alain Paquette, Jérôme Dupras,
Jean-Pierre Revéret, Christian Messier, Alain Olivier
3rd
World Agroforestry Conference
February 10-14, 2014 – New Delhi, India
2. Contribution of tree-based intercropping systems to the
adaptation of Québec’s agroecosystems to climate change
Coordination (U Laval)
• Alain Olivier (leader)
• Alain Paquette (coordinator)
Agroforestry ecology (IRBV, UdeM, CEF, UQAM)
• Alain Cogliastro (dir)
• Léa Bouttier (MSc)
• Christian Messier (dir)
• David Rivest (postdoc)
Hydrology (INRS)
• Alain Rousseau (dir)
• Silvio Gumiere (postdoc)
• Dennis Hallema (postdoc)
Biodiversity (CEF, UQAM)
• Tim Work (dir)
• Enrique Doblas (postdoc)
Economics (UQAM)
• Jean-Pierre Revéret (dir)
• Mahbubul Alam (postdoc)
• Jérôme Dupras (PhD)
Modeling (CEF, UQAM)
• Christian Messier (dir)
• Alain Paquette (dir)
• Susy Domenicano (PhD)
• Olivier Taugourdeau (postdoc)
Climate modeling (Ouranos)
• Marie-France Sottile
3. The project objectives
• Growth and interactions
Quantify the effects of agroforestry on trees and crops
• Hydrology
Study the dynamics of soil water in the agroforestry system
• Biodiversity
Measure the effects of agroforestry on soil microarthropods
• Modeling
Model the agroecosystems today in the future in a climate
change context
• Economics
Quantify and monetize ecosystem services provided by
agroforestry
11. Economics
Quantification and monetization of ecosystem
services provided by agroforestry
1. What is the marginal value of ecosystem services
provided by agroforestry systems?
2. Is agroforestry advantageous as a long term
investment, when the "externalities" are internalized in
an environmental cost-benefit analysis?
12. The experimental site of St-Paulin (Mauricie)
Year tree planting: 2004
Intercropping: oats, buckwheat,
canola, etc.
2 sp. of hardwood:
red oak and black
cherry
Two hybrid poplar
clones: DN-3333 et
DN-3570
12 m
D.Rivest
14. Analytical framework
Inventory of EGS associated to agroforestry and short-
listing of the most meaningful in the Quebec context
Quantification of the demand in ecosystem services
Quantification of the production of services (service
providing units, SPU), especially of the components of
biodiversity that support SPU
Value of services
provided by SPU
Value of potential
alternatives
Evaluation of options and extrapolation to appropriate
scale for meaningful policy decision ; determination of
implications for mitigation of and adaptation to CC
Identification
Quantification
Appraisal
15. Supporting Services
Soil Formation
Provisioning Services
Food
Wood and Fiber
Grass
Medicinal products
Regulating Services
Biological control
Pollination
Nitrogen fixation
Protection against wind
Air quality control
Climate regulation
Noise Reduction
Odor control
Soil fertility
Water Quality
Biodiversity habitat
Cultural Services
Aesthetic landscapes
Leisure and recreation
Heritage & Legacy
Spirituality
Education
Inventory and selection of EGS
related to agroforestry
Supporting Services
Provisioning Services
Food
Wood and Fiber
Regulating Services
Biological control
Pollination
Protection against wind
Climate regulation
Odor control
Soil quality
Water Quality
Soil fertility
Air Quality
Cultural Services
16. Ecosystem
Services
Assumptions/Data/Approach
Provision of
timber and
agricultural
products
• Evaluated in terms of provision of agricultural products and
provision of timber
• Rotation on a 20 years period
• Hybrid poplar, soybean, wheat
Air quality Cost of pollution mitigation
Carbon
sequestration
and storage
• Net C-sequestration per ha per year
• Total C sequestered = (Above ground) + (below ground) -
Soil respiration – C leaching
• Economic data: damage cost / social cost of carbon
emission / carbon tax
Abatement of
farm odor
Avoided cost of odour mitigation
Soil quality
regulation
Evaluated in terms of soil formation, addition of SOM, erosion
control, etc.
Valuation framework
17. EGS Assumptions/data/approach
Water quality Cost of decontamination of pollutants
Biological pest
control
Replacement cost approach
Pollination Production Function Approach
Mineralization of
nutrients
Input cost approach
Wind protection Productivity approach
Socio-cultural
services
1. Contingent valuation (Landscape aesthetics)
2. Travel cost (Education)
Valuation framework
18. General Evaluation Model
ESTEV = ∑ES n = ∑ES non-market + ∑ES market
Where, n=1, 2, 3… 10
TEV= Total economic value
∑ES non-market = ∑ES1-8 and
∑ES market = ∑ES9-10
19. Services, indicators and
values of the experimental site
Soil qualitySoil quality
Indicators =
1. Earthworms
2. Invertebrates
Units =
1. 2,5 tons ha-1
y-1
2. 1 ton ha-1
y-1
Values =
1. 125 $ ha-1
y-1
2. 50 $ ha-1
y-1
Sandhu et al 2008; Price, 1999; Pimentel et
al, 1995, 1997
Indicators =
1. Earthworms
2. Invertebrates
Units =
1. 2,5 tons ha-1
y-1
2. 1 ton ha-1
y-1
Values =
1. 125 $ ha-1
y-1
2. 50 $ ha-1
y-1
Sandhu et al 2008; Price, 1999; Pimentel et
al, 1995, 1997
Indicators =
1. Nitrogen inputs
2. Phosphorus inputs
3. Inputs potassium
4. Production change (forestry)
Units =
1. 7 kg ha-1
y-1
2. 11,42 kg ha-1
y-1
3. 21,22 kg ha-1
y-1
4. 0,162 m3
ha-1
y-1
Values =
1. 3,8 $ ha-1
y-1
2. 7,5 $ ha-1
y-1
3. 13,5 $ ha-1
y-1
4. 6,4 $ ha-1
y-1
Thevathasan & Gordon, 2004;
Zhang (1999); Rivest et al (2009)
Toor et al (2012);
USDA
Indicators =
1. Nitrogen inputs
2. Phosphorus inputs
3. Inputs potassium
4. Production change (forestry)
Units =
1. 7 kg ha-1
y-1
2. 11,42 kg ha-1
y-1
3. 21,22 kg ha-1
y-1
4. 0,162 m3
ha-1
y-1
Values =
1. 3,8 $ ha-1
y-1
2. 7,5 $ ha-1
y-1
3. 13,5 $ ha-1
y-1
4. 6,4 $ ha-1
y-1
Thevathasan & Gordon, 2004;
Zhang (1999); Rivest et al (2009)
Toor et al (2012);
USDA
Indicator =
1.Annual yield
Unit =
1. 3,7 tonne ha-1
y-1
Value =
1.784,9 $ ha-1
y-1
Toor et al. 2012
Indicator =
1.Annual yield
Unit =
1. 3,7 tonne ha-1
y-1
Value =
1.784,9 $ ha-1
y-1
Toor et al. 2012
Indicator =
1.Annual yield
Unit =
1.3,5 m3
ha-1
y-1
Value =
1.140 $ ha-1
y-1
Toor et al., 2012
Indicator =
1.Annual yield
Unit =
1.3,5 m3
ha-1
y-1
Value =
1.140 $ ha-1
y-1
Toor et al., 2012
Indicators =
1. Decontamination (nitrogen)
2. Decontamination (phosphorus)
3. Sediment Dredging
Units =
1. 11 kg ha-1
y-1
2. 7,5 kg ha-1
y-1
3. -
Values =
1. 93,5 $ ha-1
y-1
2. 459 $ ha-1
y-1
3. 5,6 ha-1
y-1
Olewiler, 2004; Wilson, 2008
Indicators =
1. Decontamination (nitrogen)
2. Decontamination (phosphorus)
3. Sediment Dredging
Units =
1. 11 kg ha-1
y-1
2. 7,5 kg ha-1
y-1
3. -
Values =
1. 93,5 $ ha-1
y-1
2. 459 $ ha-1
y-1
3. 5,6 ha-1
y-1
Olewiler, 2004; Wilson, 2008
Indicator =
1.Productivity change
Unit =
1. 1,47 ton ha-1
y-1
Value =
1. 24,1 $ ha-1
y-1
Morse and Calderone 2000; Toor et al.
2012
Indicator =
1.Productivity change
Unit =
1. 1,47 ton ha-1
y-1
Value =
1. 24,1 $ ha-1
y-1
Morse and Calderone 2000; Toor et al.
2012
Indicator =
1.Productivity change
Unit =
1. 1,47 ton ha-1
y-1
Value =
1. 117 $ ha-1
y-1
Brandle et al (2004)
Indicator =
1.Productivity change
Unit =
1. 1,47 ton ha-1
y-1
Value =
1. 117 $ ha-1
y-1
Brandle et al (2004)
Indicator =
1.Level of pest
Unit =
1. -
Value =
1. 75 $ ha-1
y-1
Kellermann 2007
Indicator =
1.Level of pest
Unit =
1. -
Value =
1. 75 $ ha-1
y-1
Kellermann 2007
Indicator =
1. Polluant
sequestration
Unit =
1. 1,67 kg/tree
Value =
1. 462 $ ha-1
y-1
Wilson, 2008
Indicator =
1. Polluant
sequestration
Unit =
1. 1,67 kg/tree
Value =
1. 462 $ ha-1
y-1
Wilson, 2008
Indicator =
1. Carbon sequestration
Unit =
1. 8,3 Mg CO2e ha-1
y-1
Value =
1. 356,9 $ ha-1
y-1
Alam et al., 2013
Indicator =
1. Carbon sequestration
Unit =
1. 8,3 Mg CO2e ha-1
y-1
Value =
1. 356,9 $ ha-1
y-1
Alam et al., 2013
Soil fertilitySoil fertility
FoodFood
Wood and
Fiber
Wood and
Fiber
Water
quality
Water
quality
PollinationPollination
Protection
against
wind
Protection
against
wind
Biological
control
Biological
control
Air QualityAir Quality
Climate
regulation
Climate
regulation
20. An example: service climate regulation
produced by agroforestry
Biophysical assessment Economic valuation
NCS = (Bt + Br+ Bl + CR + SOC) – (Cr
+ Cl) + CN2O
where, NCS, Net Carbon Sequestered; Bt,
and Br, Carbon stored in tree trunk
biomass (including branches and leaves)
and roots respectively; Bl, Carbon stored in
litter fall; CR, Carbon stored in crop
residues; SOC, Carbon pool in soil; Cr,
Carbon returned back through soil
respiration; Cl, Carbon lost through
leaching into soil profiles; CN2O, CO2
equivalent avoided emission of N2O.
Where, VADxtT is the present value of all
damage avoided (or additional damage
when negative), due to carbon
sequestration on x land parcel from time
t to T. In the right hand side ΔCx,z,z+1 is
the carbon sequestered over the
rotation period (between time z and
z+1), SCCz+1 is the SCC in year z+1 and
r is the discount rate.
21. Sensitivity analysis of the value of the service of climate
control according to the variation of the social cost of
carbon and of the discount rate
22.
23. Conclusion 1/2
• Private benefits (supply of agricultural products) are
slightly reduced in the studied agroforestry system
• However, the value of non-market ecosystem services
by far exceeds the value of private benefits
• The importance of public benefits should encourage
governments to adopt measures to compensate for
private losses incurred by farmers when switching from
conventional agriculture to agroforestry
24. Conclusion 2/2
• This is even more interesting considering that the results
of our modeling indicate that in 2050, the presence of
trees could help limit crop yield losses that are expected
because of the anticipated climate change, but also
ensure greater stability of yield, a very important element
for the farmer
25. This study was supported by a grant from
Ouranos, the Consortium on Regional
Climatology and Adaptation to Climate
Change, thanks to funding from the Fonds
vert of the ministère du Développement
durable, de l'Environnement, de la Faune et
des Parcs du Québec.