Early effect of no - tillage on land profitability, soil fertility and microbiota: A case study in a tropical ecosystem (altitude plains, Lao PDR)

Early effect of no-tillage on land profitability, soil fertility and microbiota

A case study in a tropical ecosystem (altitude plains, Lao PDR)

Pascal Lienhard, Florent Tivet, Andre Chabanne, Lucien Séguy, Anonh Khamhung, Khamkéo Panyasiri, Pierre-Alain Maron and Lionel Ranjard

5th World Congress on Conservation Agriculture - Brisbane, Australia, 26-29 September 2011

http://www.inra.fr/

CONTENT

Context: Main farming systems and agricultural changes in the Plain of Jars

Material and methods: Experimental site & design, agri-environmental indicators

Results: Impact on farmers’ income, soil fertility evolution and microbiota

Conclusions: global agri-environmental evaluation of agricultural management

CONTENT





Plain of Jars (900-1200m)

3 western districts (Pek, Phoukout and Paxay) of Xieng Khouang province, north -eastern Lao PDR

Plain of Jars (900-1200m)

About 80.000 ha of savannah grasslands with pine trees on hills summit

Main farming system: rice production in paddy fields and extensive livestock production in the hills

Limited possibilities to extend paddy areas Limited agricultural production in the

upland due to soil constraints (low pH, deficiencies in main nutrients, severe aluminium toxicity)

Only 5% of total surface is cultivated, 80% in paddy rice fields

Livestock system: low stocking rate, low investments

Main changes in the uplands Since 1990’s

Reforestation (pine trees) policy and upland rice production attempts based on plowing with disks Since 2000’sAttribution of large concessions to private companies for cash crops production (cassava, corn, jatropha); land preparation based on deep soil plowing Since 2005Conception and promotion of CA-DMC systems as an ecologically-sound alternative to tillage-based agriculture

However, little information regarding agri-environmental

impacts of these practices on soils for such agro-ecology

Study objectives

Early effect (after 3 cropping seasons)

of various agricultural management(conservation vs conventional agriculture)

on profitability(farmers income)

soil fertility (chemical car. and soil aggregate stability)

and microbiota (abundance and diversity)

in a specific agro ecology (tropical climate, mountainous areas)

CONTENT





Ban POA Experimental Site

Soil sampling:PASCVDMC1DMC2DMC3

Ban Poa experimental site (created in 2007)

Land Use Rep DescriptionPAS 17 Savannah grassland dominated by Themeda triandra and Cymbopogon nardus speciesCV 27 Land preparation based on ploughing using discs and burying of crop residuesDMC No-tillage; direct seeding after mechanical and chemical control of cover crops

DMC 1 27 Year 1: "fing+pig", then 3y rotation rice+sty / corn+fing+pig / soy bean +oat+buck

DMC 2 27 Year 1: "fing+sty", then 3y rotation rice+sty / corn+sty / soy bean +oat +buckDMC 3 27 Year 1 "ruzi+pig", then 3-year rotation rice+sty / corn+ruzi / soy bean +oat +buck

Treatments PAS

DMCs CV

Data collection over 2007-2010 periodAll inputs, labor, and yields were

collected to calculate 4y cumulated:– production costs (USD.ha-1)

all inputs + operational costs– gross income (USD.ha-1) crops

yield (kg.ha-1) x unit price (USD.kg-1)

– net income (USD.ha-1 ) gross income – production costs

Calculations are made with constant average price in USD over the 4y-period

Economical data collection

Soil chemical characteristics

– Soil sampling in June 2009– Bulk of 5 soil samples for each treatment – Soil analysis in France (CIRAD SAL)

• pH water (1:5)• Org C (dry combustion)• Total N (dry combustion)• Available P (Olsen)• Effective CEC (cobalt hexamine)• Exchangeable base (Ca, Mg, K, Na)

(cobalt.)

Soil Aggregate Stability

– Yoder method (1936) adapted by different authors (Haynes, 2000; Castro Filho, 2002; Madari et al, 2005)

– 7 size classes of aggregates obtained after wet sieving of soil samples through 6 sieves (mesh of 8, 4, 2, 1, 0.5 and 0.25 mm)

– 3 field replicates per treatment– 4 aggregation parameters:

• Macro (0.25-19mm) and micro (<0.25mm) aggregate content

• Mean Weight Diameter (MWD)• Mean Geometric Diameter (MGD)• Aggregate Stability Index (AS)

The mean-weight diameter (MWD) of aggregates is an estimate of the size of the heaviest aggregate size classes:

where wi is the proportional weight of each aggregate class in relation to the whole and xi is the mean diameter of the considered class (mm).

The Mean geometric diameter (MGD) of aggregates is an estimate of the size of the most frequent aggregate size classes:

where wi is the weight (g) of the aggregates of each size class and ln xi the natural logarithm of the mean diameter of the size class.

The Aggregate stability index (AS) of soils is a measure of the total aggregation of the soil:

where wp25 is the weight (g) of aggregates <0.25 mm and sand is the weight (g) of particles between 53 and 2000 µm. It is expressed in percent.

Soil microbiota

Total microbial community

Principal component

analysis

Molecular fingerprint(B-ARISA)

Genetical structure of bacterial communities

Soil DNA quantification (agarose)= total soil microbial biomass

Bacterial and fungal abundance(qPCR 16 et 18S rDNA)

Adapted from Pascault, 2010 and Ranjard, 2009

– Analysis of microbes abundance and diversity

– Molecular tools

CONTENT





• Economical performances of CA vs CV systems

Letters between brackets indicate significant differences according Kruskal-Wallis test (p<0,05), Bonferroni correction

2007-2010 cumulated data for the following crop sequences:rice 2008, corn 2009, soybean 2010 (2007: cover crops for DMCs and nat past for CV)

Syst cum. prod costs (USD/ha)

cum. labour (wd/ha)

cum. yields (Ton of grains/ha)

cum. gross income (USD/ha)

cum. net income (USD/ha)

CV 1974± 271 [a] 233± 9 [ab] 9,7± 2,8 [a] 2848± 577 [a] 874± 382 [ab]DMC 1 2036± 334 [a] 202± 11 [a] 10,6± 2,3 [a] 3037± 593 [a] 1000± 362 [b]DMC 2 2154± 294 [a] 241± 15 [b] 10,5± 2,7 [a] 2911± 828 [a] 757± 583 [ab]DMC 3 2003± 307 [a] 221± 15 [ab] 8,4± 2,3 [a] 2404± 487 [a] 402± 218 [a]

• Similar cumulated prod. costs over 2007-2010 but…

2007 2008 2009 2010 2011 20120

500

1000

1500

2000

2500Cumulated production costs (USD.ha-1)

CV DMC1 DMC2 DMC3

• Different trends with expected CV prod. costs > DMCs prod costs in 2011





cum. labour (wd/ha)





• Similar grain yields and gross income over 2007-2010, but… …By-products of DMCs systems are not taken into the economical calculation

• 2007: Finger millet and pigeon pea used for pig fattening• 2007: Ruzi grass seeds collected for sale• 2009 & 2010 ruzi grass forage cut and exported for cattle fattening activities





cum. labour (wd/ha)





• Similar cumulated net income (except for ruzi-grass based DMC3)

2007 2008 2009 2010

-800

-600

-400

-200

0

200

400

600

800

1000

1200Cumulated net income (USD.ha-1)

CV DMC1 DMC2 DMC3

•Return on investment after 3 cropping seasons

Land use impact on top soil (0-10cm) aggregate stability

Land Use

Microaggregate (0-0.250 mm) (g. kg-1 soil)

Macroaggregate (0.250-19 mm)

(g. kg-1 soil)MWD (mm) MGD (mm) AS (%)

PAS 47 ± 44 [ab] 953 ± 44 [bc] 8.36 ± 0.58 [a] 4.63 ± 0.83 [b] 91 ± 9 [b]CV 93 ± 38 [c] 907 ± 38 [a] 6.95 ± 1.24 [a] 3.36 ± 0.79 [a] 81 ± 13 [a]DMC 1 48 ± 34 [b] 952 ± 34 [b] 9.43 ± 1.16 [b] 6.18 ± 1.56 [c] 87 ± 13 [b]DMC 2 45 ± 26 [ab] 955 ± 26 [bc] 9.46 ± 1.33 [b] 6.54 ± 1.00 [c] 89 ± 14 [b]DMC 3 33 ± 19 [a] 967 ± 19 [c] 9.70 ± 1.04 [b] 6.75 ± 1.34 [c] 92 ± 7 [b]

MWD = Mean Weight Diameter; MGD = Mean Geometric Diameter; AS = Aggregate Stability IndexLetters between brackets indicate significant differences according Kruskal-Wallis test (p<0,05), Bonferroni correction

• Soil structure stability decrease under CV compared to PAS and DMC• Early macroaggregate disruption process under CV

Higher soil sensitivity to erosion Higher exposition of SOC to microbes and mineralization (since C is physically protected into microaggregates that are formed into macroaggregates, Six et al, 2004)

– Lower Bulk density under CV compared to PAS and DMCs

Land use impact on top soil (0-10cm) chemical characteristics

1 C stock (Mg/ha) = Org C (%) x Da (g.cm-3) x layer depth (cm) x 10; 2 N stock (Mg/ha) = Total N (‰) x Da (g.cm-3) x layer depth (cm)Letters between brackets indicate significant differences according Kruskal-Wallis test (p<0,05), Bonferroni correction

LU Da (g.cm-3) Corg (%) TOC (Mg.ha-1) N tot (‰) Tot N (Mg.ha-1) PAS 1,33 ± 0,10 [ab] 3,38 ± 0,46 [ab] 45 ± 3 [ab] 2,53 ± 0,37 [b] 3,36 ± 0,19 [b] CV 1,31 ± 0,10 [a] 3,15 ± 0,21 [a] 41 ± 5 [a] 2,13 ± 0,24 [a] 2,78 ± 0,47 [a] DMC1 1,39 ± 0,10 [b] 3,36 ± 0,54 [ab] 47 ± 4 [bc] 2,38 ± 0,30 [b] 3,31 ± 0,36 [b] DMC2 1,39 ± 0,11 [b] 3,44 ± 0,46 [b] 48 ± 5 [c] 2,40 ± 0,33 [ab] 3,35 ± 0,53 [b] DMC3 1,40 ± 0,08 [b] 3,44 ± 0,53 [b] 48 ± 5 [c] 2,42 ± 0,36 [b] 3,39 ± 0,44 [b]

– Lower C and N content and stocks under CV– Mean loss of 4 Mg of TOC/ha and 0.5 Mg of TN/ha

under CV after only 3 cropping seasons ! – No losses under DMCs

LU pH H2O (1:5) P Olsen (mg/kg) Σ base (c mol/kg) CEC (c mol/kg)PAS 5,29 ± 0,25 [ab] 3,36 ± 1,01 [a] 0,76 ± 0,33 [a] 2,13 ± 0,81 [a]CV 5,19 ± 0,42 [a] 8,23 ± 2,50 [b] 2,87 ± 0,60 [b] 3,32 ± 0,51 [a]DMC1 5,54 ± 0,24 [b] 10,61 ± 3,90 [b] 4,51 ± 1,47 [c] 4,76 ± 1,61 [b]DMC2 5,44 ± 0,24 [ab] 10,15 ± 3,44 [b] 4,31 ± 1,23 [c] 4,44 ± 1,35 [b]DMC3 5,50 ± 0,25 [b] 9,74 ± 2,50 [b] 4,42 ± 1,45 [c] 4,67 ± 1,64 [b]

Land use impact on top soil chemical characteristics

1 BS = Base saturation= (Ca+Mg+K+Na)×100 / CECLetters between brackets indicate significant differences according Kruskal-Wallis test (p<0,05), Bonferroni correction

• General improvement of soil chemical fertility under fertilized agro-systems (CV and DMCs) compared to native pastureland (PAS) due to lime + thermo phosphate applications



• General improvement of soil chemical fertility under fertilized agro-systems (CV and DMCs) compared to native pastureland (PAS) due to lime + thermo phosphate applications

• But…• Better fertilizer use under DMCs (higher lixiviation rates under CV)

LU pH H2O (1:5) P Olsen (mg/kg) Σ base (c mol/kg) CEC (c mol/kg)PAS 5,29 ± 0,25 [ab] 3,36 ± 1,01 [a] 0,76 ± 0,33 [a] 2,13 ± 0,81 [a]CV 5,19 ± 0,42 [a] 8,23 ± 2,50 [b] 2,87 ± 0,60 [b] 3,32 ± 0,51 [a]DMC1 5,54 ± 0,24 [b] 10,61 ± 3,90 [b] 4,51 ± 1,47 [c] 4,76 ± 1,61 [b]DMC2 5,44 ± 0,24 [ab] 10,15 ± 3,44 [b] 4,31 ± 1,23 [c] 4,44 ± 1,35 [b]DMC3 5,50 ± 0,25 [b] 9,74 ± 2,50 [b] 4,42 ± 1,45 [c] 4,67 ± 1,64 [b]



• Decrease of pH under CV despite lime and thermo phosphate applications

• Might be related to the release of protons (H+) during the oxidation of carbon (C) and nitrogen (N) compounds in soils (tillage)

LU pH H2O (1:5) P Olsen (mg/kg) Σ base (c mol/kg) CEC (c mol/kg) BS (%)PAS 5,29 ± 0,25 [ab] 3,36 ± 1,01 [a] 0,76 ± 0,33 [a] 2,13 ± 0,81 [a] 35 ± 7 [a]CV 5,19 ± 0,42 [a] 8,23 ± 2,50 [b] 2,87 ± 0,60 [b] 3,32 ± 0,51 [a] 86 ± 9 [b]DMC1 5,54 ± 0,24 [b] 10,61 ± 3,90 [b] 4,51 ± 1,47 [c] 4,76 ± 1,61 [b] 95 ± 4 [c]DMC2 5,44 ± 0,24 [ab] 10,15 ± 3,44 [b] 4,31 ± 1,23 [c] 4,44 ± 1,35 [b] 98 ± 6 [c]DMC3 5,50 ± 0,25 [b] 9,74 ± 2,50 [b] 4,42 ± 1,45 [c] 4,67 ± 1,64 [b] 96 ± 6 [c]

Land use impact on top soil (0-10cm) micro biota abundance

Trend of decrease of bacterial and fungal biomasses under CV compared to PAS and DMCs

Land use impact on top soil (0-10cm) micro biota diversity

Effect of texture > effect of land use Similar to Ranjard et al findings (2010): main driving factor

explaining soil microbial distribution related to texture, pH and total org C

For given textural classes: trends of bacterial communities changes observed (DMCs ≠ PAS ≠ CV)

Total soils (n=114), from clay to sandy loam Clay soils (n=66)

PCA of B-ARISA fingerprints

CONTENT




Conclusions: global agri-environmental evaluation of the impact of native land conversion to agriculture

PAS

CVDMCs

Initial situation Extensive grazing on native grass

Early impact of land use conversion on…

Farmers income

Soil structure stability

Soil organic status

Soil nutrients availab.

Soil bulk density

Soil microbiota abundance

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Conclusions

Despite higher global agri-environmental services provided by CA-DMCs, tillage-based systems are still prevailing

Main constraints are related to:₋ financial capital access₋ information₋ and commodity chain

Conclusions (2)

These first observations confirmed the early impact of ploughing on top soil degradation process and the interactions between Soil Organic Matter, soil biota and soil structure as described by Six et al (2002)

Macro aggregates disruption, enhanced soil aeration and mixing of residues into the soil induced changes in microbial biota and C and N losses

Conclusions (3)

These results observed after only 3 years of cultivation also confirmed how fast soil degradation can occur in the tropics (even in altitude-cooler areas)

Thank you for your attention !

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Early effect of no - tillage on land profitability, soil fertility and microbiota: A case study in a tropical ecosystem (altitude plains, Lao PDR)