Krasilnikov global soil security
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Transcript of Krasilnikov global soil security
Economics of land degradation contribution to soil security in
Eurasia Pavel Krasilnikov, Oleg Makarov, Alexey Sorokin,
Alisher Mirzabaev, Anton Strokov, Sergey Kiselev Moscow State University
Global food security is jeopardized by the increasing land degradation, which is especially dangerous in the
poorest countries of the world
Evident hotspots are recognized in Africa, South-Eastern Asia and Central America
Northern Eurasia has been considered as a relatively stable territory with minor impact of land degradation
However, soil degradation is active in Russia, as it is driven by a complex of natural and socio-economic factors
Processes of degradation Area, million ha Water erosion and deflation ~ 70 Various degrees of salinity > 40 Excessive stoniness 12 Desertification > 1 Low organic carbon content 56 Gullies 1.7 Wind-blown sands 6.3
Processes of soil degradation in Russia
USSR • Economical situation: low
productivity , residual principle of finding
• Social situation: discrimination of rustic population, poor rural infrastructure
• Technological situation: weakness of technology, low priority of agrotechnology for the state
• Economical situation: economic freedom, weakness of producers, “wild market”
• Social situation: social freedom, weak social protection, “social desertification”
• Technological situation: dependence on imported technologies, the loss of scientific background; some promising “growth points”
Land use in the USSR and nowadays Russia
Russian Federation
Economics of Land Degradation initiative
21 of September 2011 the European Commission, the German government and the UNCCD Secretary launched the initiative on the Economics of land Degradation (ELD)
Conceptual scheme for the assessment of costs/benefits under action vs. inaction scenarios
Bases and methodology
Methodology: cost of land degradation
• Following Nkonya et al. (2014), we calculated the costs of land degradation due to land-use and land-cover change (LUCC) through:
(1)
• where CLUCC = cost of land degradation due to LUCC; a1= land area of biome 1 being replaced by biome 2; P1 and P2 are the total economic value (TEV) of biomes 1 and 2, respectively.
Methodology: the cost of action • The cost of taking action against land degradation due to LUCC is
given by: (2) • where CTAi = cost of restoring high value biome i; ρt = discount
factor of land user; Ai = area of high value biome i that was replaced by low value biome j; zi = cost of establishing high value biome I; xi = maintenance cost of high value biome i until it reaches maturity; xj = productivity of low value biome j per hectare; pj = price of low value biome j per unit (e.g. ton); t = time in years and T = planning horizon of taking action against land degradation. The term pjxj represents the opportunity cost of foregoing production of the low value biome j being replaced.
Methodology: the cost of inaction
• The cost of inaction will be the sum of annual losses due to land degradation
(3) • where CIi = cost of not taking action against
degradation of biome i.
Methodology: cost of action without land use change
• The social cost and benefit of action against land degradation and inaction is given by the net present value (NPV) for taking action against land degradation in year t for the land users planning horizon T:
(4) • Where πc
t = NPV; Yct = production of direct use provisioning services
when using SLM practices; P= unit price of Yct; IVt = indirect use
value; NUt = on-site non-use value; bct = off-site positive benefit of
SLM practices ρt = 1+r, r = land user’s discount rate; lmct = cost of
SLM practices; cct = direct costs of production other than land
management; τct = off-site costs of SLM – including use and non-
use costs.
Methodology: cost of inaction without land use change
• If land user does not take action against land degradation, the corresponding NPV is given by
(5) • Where πd
t = NPV when land user uses land degrading practices. All other variables are as defined in above but with superscript d indicating land degrading practices.
• The benefit of taking action against land degradation is given by
Federal districts of Russian Federation
Far East
Siberian Ural
North-west Central
Volga Southern
North Caucasus
Federal districts of Russia and European countries
Rural population density, person/km2
Area of arable lands, mln ha
Share of arable lands in the territory, %
Availability of arable lands, ha/person
Share of employment in agriculture of rural population, %
Northern FD 1.4 2.4 1.6 1.2 18.9
Finland 5.8 2.3 6.7 1.1 6.0
Central FD 11.0 20.1 32.0 2.9 18.7
Poland 45.6 12.5 38.6 0.8 15.8
Southern FD 16.7 20.4 35.0 2.1 16.7
France 26.0 18.5 33.6 1.3 5.4
Some characteristics of rural lands and agriculture of Federal districts of Russia and European countries with respectively
similar bioclimatic conditions
Based on Nefedova (2013)
Indicators 1991-1995 2003-2007
Application of organic fertilizers, mln t (t/ha)
150.1 (1.7) 51.8 (0.9)
Supply of mineral fertilizers, mln t
4.5 1.5
Application of mineral fertilizers, kg/ha
35 28
Melioration of acidic soils, thousand ha
2733 314
Application of phosphorous fertilizers, thousand ha
1021 39.1
Melioration of Solonetz, thousand ha
66.2 3.2
Processing of Solonetz, thousand ha
84 10.1
Agro-chemicals application in Russia
Gordeeva and Romanenko (2008)
Areas of long-term (1982-2006) NDVI decline (with correction of RF and AF effects and masking saturated NDVI zones) versus
main land cover/use types of the Russian Federation
Federal District
Annual cost of Land Degradation in 2002-2010, in bln USD
Annual cost of land degradation per capita including the value of the loss of ecosystem services, in USD
GDP in 2010, current bln USD
Land degradation as a share of GDP (%), annually
Central 6 157 434 1
Southern 2 144 75 3
Northwestern 17 1232 127 13
Far Eastern 76 11679 68 112
Siberian 61 3111 133 46
Ural 18 1477 165 11
Volga 5 164 184 3
North Caucasian 3 332 29 10
Total 189 1315 1216 16
The costs of land degradation in Federal Districts of Russia through land-use change, including TEV values
Costs of action vs inaction in Federal Districts of Russia, in bln USD
Federal District
GDP in 2010
Annual TEV of LD in 2010 vs. 2002, bln USD
Annual cost of LD in 2010 vs 2002, in USD
Cost of Action (6 years)
Cost of Action (30 years)
The oppor-tunity cost of action
Cost of Inaction (6 years)
Cost of Inaction (30 years)
Ratio of cost of action / inaction
Central 434 6 2 14 14 13 43 93 14%
Southern 75 2 0 5 5 5 15 32 16% North-Western 127 17 16 81 82 75 161 348 22% Far Eastern 68 76 60 279 283 263 720 1 558 17%
Siberian 133 61 44 217 220 201 530 1 147 18%
Ural 165 18 12 77 77 71 164 355 20%
Volga 184 5 2 14 14 12 39 85 15% North Caucasian 29 3 1 7 7 6 21 46 14% Total 1216 189 136 694 702 647 1 693 3 663 18%
Roadmap for the future
• Management: – Searching for adequate
SLM practices (validation of WOCAT database)
– from Agriculture to iGriculture (precision agriculture, landscape-adaptive techniques etc.)
Plant et al. (2000)
Roadmap for the future • Awareness, education,
investment: – Inform the decision-makers
and general public on the economic value of soil degradation
– Include the basics of economics of land degradation in university and extension programs
– Attract investment in SLM using economic arguments
Roadmap for the future
• Research: – Downscaling the results of
the research: higher responsibility for prediction on a farm-scale
– Quantifying soil degradation in an economically sound way
– Establishing monetary value for most ecosystem services
Roadmap for the future
• Information: – Demand for information
on soil dynamics (actual and retrospective monitoring)
– Demand for economic information (not readily available)
– Demand for mapping of ecosystem services related to soils
Conclusions
• All the soil services should be assessed and expressed in monetary equivalent
• Initiatives should feed each other rather than compete
• The approaches developed in the frames of Global Soil Security, Economics of Land Degradation, Global Soil Partnership and many others compliment each other
THANK YOU FOR YOUR ATTENTION
The research was supported by the Russian Science Foundation, project No. 14-38-00023