This presentation was presented during the 1 Parallel session on Theme 3.1, Managing SOC in: Soils with high SOC – peatlands, permafrost, and black soils, of the Global Symposium on Soil Organic Carbon that took place in Rome 21-23 March 2017. The presentation was made by Mr. Ivan Vasenev, from Timiryazev Academy – Russian Federation, in FAO Hq, Rome

1. Managing SOC in the
black soils of Russia
Russian Timiryazev State Agricultural University, Moscow
Global Symposium on soil organic carbon-2017
БЕЛГОРОД
ОРЕЛ
ЛИПЕЦК
ТАМБОВ
ВОРОНЕЖ
КУРСК
Мценск
Новосиль
Залегошь
Хомутово
Верховье
Покрвское
Змиевка
Отрадинский
Ливны
Глазуновка
Елец
Лебедянь
Данков
Лев Толстой
Болхов
Хотынец
Нарышкино
Шаблыкино
Крамы
Дмитриевск-Орловский
Знаменка
Малоорхангельск
Колпны
Долгое
Поныри
Железногорск
Первоавгустовский
Дмитриев-Льговский
Фатеж
Золотухино
Хомутовка Конышевка Щигры Черемисиново
Кшенский
Рыльск Льгов
Курчатов
Прямицино
Любимовка
Бол. Солдатская
Суджа
Медвенка
СолнцевоКоренево
Глушково
Обоянь
Кировский
Тим
Касторное
Олымский
Горшечное
Губкин
Старый Оскол
Ивня Прохоровка
Ракитное Яковлево
Томаровка
Борисовка
Грайворон
Октябрьский
Шебекино
Короча
Чернянка
Новый Оскол
Волоконовка
Валуйки
Уразово Вейделевка
Красногвардейское
Алексеевка
Чаплыгин
Доброе
Первомайский
Кочетовка
Мичуринск
Тербуны
Волово
Хлебное
Усмань Добринка
Грязи
Рамонь
Краснолесный
Латная
Стрелица
Хохольский
Нововоронежский
Перелешинский
Панино
Анна
Давыдовка
Бобров
Острогожск
Ольховатка
Россошь
Кантемировка
Богучар
Петропавловка
Таловая
Новохоперск
Поварино
Борисоглебск
Терновка
Шапкино
Мучкапский
Уварово
Мордово
Эртиль
Инжавино
РжаксаНовопокровка
Знаменка
Рассказово
Котовск
Бондари
Сосновка
Грязи
Староюрьево
Кирсанов
Умет
Дмитриевка
Моршанск
Вернадовка
53°20'
34°00'
52°40'
52°00'
51°20'
50°40'
34°00'
50°00'
35°00'
36°00' 37°00'
38°00'
49°20'
39°00' 40°00' 41°00' 42°00'
49°20'
50°00'
43°00'
50°40'
51°20'
52°00'
52°40'
53°20'
44°00'
54°00'
43°00'42°00'41°00'40°00'39°00'38°00'37°00'36°00'
35°00'
54°00'
"Агрофирма Мценская"
Учхоз им. Калинина
Заболотовский лес
Горы Болото Уч."Зоринский"
Стенки-Изгорья
Уч. "Стрелецкий"
Уч. "Казацкий"
ОПХ ВНИИЗиЗПЭ
Уч. "Букреевы Бары"
Уч."Баркаловка"
Парсет
ООО"Горшечное"
Центрально-Черноземный регион
Границы областей
Центрально-Черноземного региона
Объекты исследования
Ivan Vasenev

2. Why we need to do this especially in case of black
soils and Central Chernozemic region of Russia?
• Current high variability of farming systems and
agroecosystem services levels: with winter wheat
yield variability from 2,5 to 7,5 t/ha within one region
• High within-field crop yield variability (40-75% of Max) due
to complicated soil cover patterns resulted by aggregated
soil degradation in frame of the universal land-use zonal
systems application within second half of XX century
• Relatively young and changeable soil cover in
agrolandscapes with n*103 years of modern natural history
and n*101-2 years of modern agricultural one
• Especial attention by successful agricultural business to the
best available agrotechnologies, land agroecological quality
evaluation and crop yield prediction due to sharply
increased input risks value in case of high inputs in farming
• Fast development of applied in RF agrotechnologies and
society interest in organic farming and sustainable land-use

3.  Normative forecasting SOC in the black soils
SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 3
 Managing SOC in the black soils
 Analyzing the black soils and their SOC natural
spatial-temporal variability and sustainability
 Evaluating soil quality dynamics due to SOC
man-made changes in the black soils
 Search forecasting SOC in the black soils in
the principal regions of RF
 Investigating soil forming and degradation
processes rates and potentials in the black soils
with especial attention to their SOC
 Typifying the black soils according to their SOC,
current land-use and its environmental impact
assessment on soil profile, regimes and processes

4. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 4
 Analyzing the black soils and their SOC natural spatial-temporal variability
and sustainability (“RF Soil National Atlas”, 2011):
1:2.5 M Scale
Soil total area – 1595,4 million ha : Black soils – around 188 million ha
Luvic Chernozems + Grey-Luvic Phaeozems – 34,9 million ha
Voronic and Vermic Chernozems – 11,3 million ha
Vorony-Calcic Chernozems – 22,0 million ha
Calcic Chernozems – 17,2 million ha
Haplic and Gypsic Kastanozems – 11,3 million ha …

5. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 5
 Analyzing the black soils and their SOC natural spatial-temporal variability
and sustainability (“RF Soil National Atlas”, 2011):
Soil organic carbon content
Soil organic carbon content
in A horizon
% Level
Very high
High
Average

6. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 6
 Analyzing the black soils and their SOC natural spatial-temporal variability
and sustainability (“RF Soil National Atlas”, 2011):
Soil organic carbon stocks
Soil organic carbon stocks in 1 m:
T/ ha Level
Extremely high
Very high
High
Above average
Average

7. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 7
 Typifying the black soils according to their SOC, current land-use and its
environmental impact assessment on soil profile, regimes and processes:
Data on humus balance in
agricultural area in 1970 – 2001
(“RF Soil National Atlas”, 2011):
• Stable tendency of
dehumification in arable
black soils:
• SOC content in arable soils
have been decreased by
4.4 – 17.1%.
Humus balance in the arable horizon
Negative with annual loss of more than 0,5 t/ha
Negative with annual loss of less than 0,5 t/ha
Positive

8. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 8
 Investigating soil forming and degradation processes rates and potentials in
the black soils with especial attention to their SOC:
1. Bioclimatic zonal and province analysis.
2. Geomorphologic regional and local typification.
3. Ecological and agroecological GIS and DB development.
4. Ecological and agroecological monitoring development
5. Field researches in representative plots with local controls
(native landscapes or less intensive land-use systems).
6. Soil cover patterns studies within chrono- or agro-secuences.
7. The Soil Cover Patterns investigation by the
field catenas, with especial attention to:
(a) their position within meso-relief;
(b) their micro-relief development;
(c) soil profile successions;
(d) soil regimes changes;
(e) soil matrix transformations;
(e) lateral, soil-forming and degradation
processes rates within SCP;
(f) potentials of soil profiles, functions
and services future development.0
20
40
60
80
100
120
140
g kg
-1
Principal Methodology:

9. Soil Agrogenic Successions at the Central Chernozemic Region of
Russia
БЛ
СЛ
ЧОП
ЧВ
ЧТ
ЧТК,
Agrogenic
succession
Agrogenic-erosion
succession
succession
succession
Agrogenic-irrigation
Agrogenic-amelioration
CaCO3
BrLPh
S
GrLF
Ch-C
Ch-V
Ch-V-C
Ch-L

10. SOC Evaluation Logistic functions → DSS development

11. THE MAIN SOIL NATURAL REFERENCE OBJECTS IN THE
CENTRAL CHERNOZEMIC RESERVE
Non-Mowed Steppe
(NMS)
Pasture (PS)
5 year periodically
Mowed Steppe
(P5MS)
Fallow (FL)
Forest (FS)
10 year periodically
mowed steppe
(P10MS)

12. 0
20
40
60
80
100
120
140
g kg
-1
Humus (SOM) dynamics in Chernozems topsoil with different land-use
determines the GHG emission in agrolandscapes
old residual arable lands
rich cultivated arable lands
intensive pastures
temporary pasture, old idle lands
forest, forest-lines
lands with light texture
ChM ChP ChOChTChL
Root CO2
emission
Microbial CO2
emission
Control

13. Erosion as principal factor of microrelief and soil C dynamics
(→Chernozems dehumification and overconsolidation ):
11
7
5
3
1
0
А
В
6,2 t/ha
17,7 t/ha
1-st stage 2-nd stage 3-d stage 4-th stage
C,
%
g
>33% lands have been eroded at
the CChR of Russia

14. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing
1
4
 Typifying the black soils according to their SOC, current land-use and its
environmental impact assessment on soil profile, regimes and processes
IRGA
C02
fluxes

15. Soil CO2 emission in representative plots of cutted
steppe (A), virgin steppe (B), black arable land (C) and
pasture (D), g C m-2 d-1
28,72
22,06
18,46
24,62
5,13
17,95
0,000
5,000
10,000
15,000
20,000
25,000
30,000
35,000
12.06.2012 26.06.2012 10.07.2012 24.07.2012
D
C
B
A
Agrogenic changes of Soil Cover Patterns as
factor of SOC stocks and CO2 emission dynamics

16. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing
1
6
 Investigating soil forming and degradation processes rates and potentials in
the black soils with especial attention to their SOC:
Processes Parameter
Processes Rates in Successions:
Agrogenic Agrogenic-
erosion
Agrogenic-
irrigation
Agrogenic-
ameliorat.
Erosion А+АВ, sm y-1
0,1-0,3 0,3-3,0 0,3-1,2 0,5-1,0
Dehumification Humus - g kg-1
y-1
0,2-1,0 0,3-1,3 0,3-0,5 0,3-1,0
Humification Humus - g kg-1
y-1
0,1-0,3 - 0,1-0,4 0,1-0,5
Overconsolidation Bulk density -g sm-3
y-1
0,01-0,02 0,01-0,05 0,01-0,06 0,01-0,03
Disaggregation  agregates 10-0,25
mm, g kg-1
y-1
1-10 1-18 10-25 8-12
Aggregation 1-10 1-5 1-5 1-5
Season
cementation Crust , sm y-1
0,1-1,0 0,1-2,0
Leaching CaCO3 - kg sm m-2
y-1
0,1-0,3 0,3-1 1-150 1-30
Carbonization CaCO3 - g kg-1
y-1
0,3-1 0,3-1,5 0,5-3,0
Acidification рН y-1
0,01-0,1 0,03-0,1 0,05-0,13 0,03-0,1
Alkalization рН y-1
0,01-0,03 0,05-0,07 0,01-0,03
Na-Salinization Na+
mg kg-1
y-1
5-18
Soil Forming and Degradation Processes Rates in Agrogenic Successions of
Black Soils (Chernozems and Grey-Luvic Phaeozems)

17. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 17
 Investigating soil forming and degradation processes rates and potentials in
the black soils with especial attention to their SOC:
• All cumulative functions in Black
soils were consistently higher than in
Podzoluvisols
--- - Moscow field with Podzoluvisols
– - Pristen field with Chernozems
NEE, Reco, GPP cumulatives

18. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 18
 Investigating soil forming and degradation processes rates and potentials in
the black soils with especial attention to their SOC:
GPP shifted at the seeds
time (0 – point) for EC
station in Moscow (green
triangles) and station in
Kursk (blue diamonds).
Solid lines represent 7-
day running mean values
for station in Moscow
(the red line) and for
station in Kursk (black
line). Vertical lines show
the conventional
boundaries of the stages
of crop development:
0 – seeds,
1- germination,
2 – sprouting, 3- tillering,
4 - leaf tube formation,
5 – milky ripeness, 6- wax
ripeness, 7- complete
ripeness, 8- harvest.
Gross Plant Production, aligned by seeding date (LAMP data)

19. Soil cover
patterns
variability as
factor of A+AB
horizons depth
and SOC stocks:
A) In case of
Grey-Luvic
Phaeozems
B) In case of
Chernozems
Black soil cover patterns and SOC within-field variability due to paleo-
microrelief and agrogenic plough erosion
Soil Cover Patterns at the Key Plots with Luvic and Voronic Chernozems
Field,
Key
plots
Area,
ha
Slopes*
Soils
( 1:10 000
Map)
Soil Cover Patterns
(1:5000 & 1:2000 -
Maps)
А+АВ
Depth,
cm
Carbonates
Depth,
cm
Field -1 53
0-8
(0-3)
ChТ
III ChL

ChL
III, ChТ
II, ChТC
III,
ChТ
IY, ChL
II
70 - 130 15 - 100
KP -1.1 4
0-3
(0-1)
ChТ
III
ChТ
III, ChТC
II, ChL
III,
ChL
II
55 - 100 0 - 105
KP -1.2 4
3-8
(3- 5)
ChL

ChТ
II, ChТC
II, ChL
,
ChТ

42 - 78 0 - 110
Field -2 59
0 -8
(1-5)
ChТ
II ChТ

ChТ

ChТ
IY, ChL
III, ChТC
IY,
ChТC
III, ChТC
II
60 - 180 15 - 120
KP -2.1 4
0-8
(3-5)
ChТ
IY
ChТ
III, ChL
III, ChТC
IY,
ChL
IY, ChТ
II
70 - 195 20 - 150

20. Crop Yield Variability within key Fields & Plots (Experimental Station,
Central Chernozemic Region)
# Key Plot
(KP) or Field
Area, ha Crop Year Weather
Yield,
dt/ha
KP -1.1 4 Barley 1996,
2000,
2004
normal 23-59
KP-1.2 4 Barley 15-64
Field 1 53 Barley 2002,
2005
dry 23-63
Sugar Beat 200-590
KP-2.1 4 Winter Wheat 1998 dry 20-65
Field 2 59 Sugar Beat 1999 normal 242-484
2003 normal 170-546
Barley 2000 normal 21-50
Pea (green food) 2001 normal 100-300
Winter Wheat 2002 dry 38-70
Field 3 53 Barley 1999 normal 25-43
Pea (grain) 22-44

21. Roughness of regression regularities and essential
uncertainty of normative predictions
Current agroecological problem analysis
Soil texture
Soil texture factor for fertilizing doze
N P K
N P K
Soil erosion factor for fertilizing doze
Soil erosion
Barley yield, dt/ha

22. P2О5>250
Yield - 52.5
P2О5<170
Yield - 45.9
K2О >100
Yield - 48.5
K2О<90
Yield - 43.2
Barley Yield
Variability at the
slope, dt ha-1
3<Slope<5
Yield - 46.2
1<Slope<3
Yield- 51.0
8<Slope>9
Yield - 32.7
5<Slope<8
Yield - 38.6
Ch
Yield - 46.1
Ch
Yield - 53.4
ChL
Yield - 50.1
ChV
Yield - 44.1
ChL
Yield - 58.9
ChV
Yield - 48.1
W>28%
Yield - 49.8
W<23%
Yield - 38.4
Crop yield variability as factor of C
sequestration potential assessment
in case of Luvic and Vermic
Chernozems

23. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 23
 Evaluating soil quality dynamics due to SOC man-made changes in black soils:
Within-field winter wheat yield variability due to Luvic and Vermic
Chernozems agrogenic changes ……………
P2О5>250
Yield - 52.5
P2О5<170
Yield - 45.9
K2О >100
Yield - 48.5
K2О<90
Yield - 43.2
Wheat Yield Variability
at the slope
3<Slope<5
Yield - 46.2
1<Slope<3
Yield- 51.0
8<Slope>9
Yield - 32.7
5<Slope<8
Yield - 38.6
Ch
Yield - 46.1
Ch
Yield - 53.4
ChL
Yield - 50.1
ChV
Yield - 44.1
ChL
Yield - 58.9
ChV
Yield - 48.1
W>28%
Yield - 49.8
W<23%
Yield - 38.4

24. Inefficient geostatistical analysis of agroecological problems
within very heterogeneous soil and landscape areas
Soil Cover Patterns at the
Experimental Station (4500 ha)

25. Deficiency of zone standard data and active information
retrieval system
Current agroecological problem analysis
Winter wheat
N
N
P
P
K
K
Available nutrient recoupment by crop yield,
dt/ha per mg/kg
Soil type
NPK usage coefficients
Manure in 1-st year
Mineral fertilizing in 2-nd year
Manure in 2-nd year
Mineral fertilizing in 1-st year

26. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 26
 Managing adaptive to landscape land-use and SOC in the black soils:
Надежда на будущее – 5Традиции российской научной школыFunctional evaluation of soil
cover patterns
Evaluation of agro-ecological problems
within field scale, including SOC
degradation
Quantitative assessment of limiting factors of soil
fertility, crop yield, ecosystem services, farming profits
Annual planning of crop distribution, farming
Meso-relief parameters
Land agroecological
passport of the farm
field
Soil cover patterns
Soil potential fertility
principal parameters
Potential crop yield
prediction mapping
SOC and available
nutrients content in
the soil
IT modules for farming
technologies agro-
ecological optimizing
in the concrete field
Agroecological
assessment of the
relief and precursors
Agroecological
assessment of the
soil cover patterns
Quantitative assess-
ment of the fertility
limiting factors
Crop yield calculation
in concrete PAR and
soil-ecological state
Crop yield calculation
in field with available
nutrient limitations

27. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 27
 Managing SOC in the black soils:
Agroecological DSS development on best available
agrotechnologies including manuring and fertilizing
Manuring and Fertilizing
programming
Economical predictions

28. SOC Managing – Normative Forecasting – LQ Evaluating – Search Forecasting – SF&DP – Soil Typifying – STV Analyzing 28
 Managing SOC in the black soils:
базового
агрогеоинфор-
мационного
обеспечения к
условиям
конкретного
района и
хозяйства ЦЧР.
principal parameters
Potential crop
yield prediction
mapping
SOC and available
nutrients content
in the soil
Quantitative assessment of limiting factors of
soil fertility, crop yield, ecosystem services,
farming profits
Annual planning of crop distribution,
farming systems and technology
applications
Crop yield and SOC
calculation in field
with available
nutrient limitations
Crop yield and SOC
calculation in
concrete PAR and
soil-ecological state
ment of the fertility
limiting factors
Annual planning of the within-field varied fertilizing
Annual planning of crop rotation and
rational distribution in the farm
Fertilizing efficiency
increasing in 20-25%
Farming profitability
increasing in 10-15%
Sharp decreasing of the
environmental risks

29. 5-10%
Farms
15-20%
Farms
30-40%
Farms
20-30%
Farms
In 5 years Crop Y increase in
1,5-2 times :
Sugar Beet - 35→70 t/ha,
Winter Wheat - 5 → 7 t/ha
Dissemination of results (agroecological models, BAAT and DSS)

30. Conclusions
1. The carried out long-term researches of representative natural and rural
landscapes gave us the regional multi-factorial matrix of soil cover patterns (SCP)
with different land-use practices, environmental conditions , SOC dynamics &
sequestration potential.
2.The validation and ranging of the limiting factors of SCP dynamics and
development helped us to understand better the principal regional-typological
forms of SCP, SFP and SOC dynamics & sequestration potential too.
3.The essential amplification of the degradation processes of erosion,
dehumification and out-of-balance CO2 emission, disaggregation and
overcompaction is result of violation of ecologically sound land-use systems and
SOC traditional balances.
4. Due to long-term out-of-balance land-use Russian black soils begin to lose not
only their unique natural features (about 1 m of humus horizon, 4-7% of Corg), but
traditional soil cover patterns, quality of ecosystem services and level of
agroecological functions.
5. Quantitative analysis of land degradation processes in parameters of SOC
dynamics help us in developing the different-scale projects of ecologically sound
rural land-use, taking into attention not only economical benefits but
agroecological functions too .

31. We must work in SOC management together!