impact of land use change in the tropics on the dynamics ... · and its relations with greenhouse...

Workshop on Impacts of Global Climate Changeon Agriculture and Livestock

May 27th, 2014

Impact of land use change in the tropics on the dynamics of microbial diversity, composition and distribution

SIU MUI TSAI

[email protected] and Molecular Biology Laboratory

Center for Nuclear Energy in AgricultureUniversity of São Paulo

Brazil

mailto:[email protected]

• Functional redundance supports land use

• Metabolic diversity is the basis of the functional redundanceof the soil

The Resilience of the Soil Microbiome

Microbial Diversity

MetabolicResilience Soil Resilience

FunctionalRedundance

SMT 2013

THE HUMAN MICROBIOME EXAMPLE

Andreote, 2011

The Galapagos

Bacterial Niches

Andreote, 2011

The existing co-occurrance of microbes and their inter-relationships

Barberán et al., 2011

RESEARCH PROJECT

Monitoring the microbial diversity and functional activities in response to land-use changes and deforestation under

soybean and sugarcane cultivations

Proc. FAPESP 2008/58114-3June 2009 – May 2014

FAPESP PROGRAM ON GLOBAL CLIMATE CHANGE

Pristine Forest

Cassava

Pasture

Floresta SecundáriaD

Q5

34

70

3-S

O

DQ148640-SM

0.05

Method – Neighbor-JoiningDistance – Jukes-CantorMatrix PAM (Dayhoff)

Sequences - Reference- Francis et al., 2005- Park et al., 2006

LAND-USE CHANGES IN BENJAMIN CONSTANTAMAZONIAN BORDER (TSBF PROGRAM)

Navarrete et al., 2012

Solo cultivado Solo de floresta

Endophytes

Mycorrhiza

Sustainable Management

(Sugarcane)

• Non-burning–raw cane

• Improvement of 2nd

generation biofuel production

• Below-ground studies

Sugarcane

Bradyrhizobia

Endophytes

MycorrhizaSoybean

Sustainable Management

(Soybean)

• Minimum tillage system

• Genetic improvementfor stress tolerance andbetter root development

THE CONTRIBUTION FROM THE BIOLOGICAL PROCESSES IS HIGHLY SIGNIFICANT IN THE TROPICS

Crop production of grains for biofuel production

Agricultural Residues

CERRI et al., 2008

THE MINIMUM TILLAGE SYSTEM

Increase soil organic matter = improve C storage

CO2

Photosynthesis

Alfa-Diversity = Pasture > Forest

Beta-Diversity = Pasture < Forest

Jan 2013

ÁREAS DE ESTUDO

3

1. Mato Grosso– Sinop

2. Mato Grosso– Campo Verde

3. Mato Grosso– Querência

4. São Paulo– Sta. Rita do Passa Quatro– Pradópolis

5. Mato Grosso Sul– Dourados

2

1

4

VEGETATION

5

Floresta (Sinop-MT)

SojaPastagem (Brachiaria brizantha)

Floresta -Pastagem e Floresta-Soja

Soja e Pastagem

Estrutura das comunidades microbianas do solo sob diferentes usos da terra – Mato Grosso

Acidobacteria and Verrucomicrobia diversity in different land use in the agriculture expansion board on Southwest Amazon

SAMPLING SITES

5th harvest- soybean Adjacent forest Deforested site Pasture

Guanandi Farm

Jaguarúna Farm

1st harvest - soybean Adjacent forest


AMOSTRAGEM

D

C

B

COMPOSITESAMPLE

0 cm

20 cm

0 cm

20 cm

Mesocosms

Microbiological and soil attributes analysis

Am

ost

rage

m d

o s

olo

de

0-4

0 c

m

estr

atif

icad

o a

cad

a 1

0 c

m

BrachiariaGuanandi FarmDeforeste site - soil

SoybeanGuanandi Farm

5th harvet - soil

SoybeanJaguaruna Farm

1st harvest - soil


MESOCOSM EXPERIMENT

Navarrete et al., BAGECO 2013

qPCR 454-PirosequencingT-RFLP Shotgun DNA

T-RFLP (16S rRNA X Soil chemical composition

Soil microbial structure in different land uses on southwest Amazon And its relations with greenhouse gases emission

Forest

Savannah

Pasture

Soybean

Assessing impacts of bio-fuel crop production

Project FAPESP 2011/51749-6:

Functional bio-indicators for soil quality monitoring for sustainable management of

sugarcane biomass production (BIOSQ)

Partners – National and International

• Siu Mui Tsai

• Carlos Cerri• Brigitte Feigl• Acacio Navarrete, Fabiana Cannavan• Lucas Mendes, Clovis Borges, Dennis Göss,

Lucas Palma• Caio Yoshiura, Marcela Arnaldo, Andressa Venturini

• Heitor Cantarella• Raffaella Rossetto

State University of Sao Paulo

• Eliana Lemos• Newton La Scala Jr.• Jackson de Souza• Eliamar Pedrinho

• Eiko Kuramae• Hans van Veen• Wim van der Putten• Paul Bodelier

Instituto Agronomico de Campinas

University of Sao Paulo

•Karoline Faust

• Brendan Bonhannan – UO• Klaus Nüsslein – UMAS• Jorge Rodrigues – UTA• Jizhong (Joe) Zhou - OSU

USA

• MODEL DEVELOPMENT FOR MICROBIOME ASSESSMENT: TAXONOMIC

AND PHYLOGENETIC DIVERSITY

FUNCTIONAL DIVERSITY (C and N CYCLES)


• PLATFORM BASED ON METAGENOMIC AND FUNCTIONAL HIGH

THROUGHPUT DATA, INTEGRATING BIOLOGICAL, CHEMICAL AND PHYSICAL

PARAMETERS.


Phylogenetic approach - Roche 454 GS FLX system

High-throughput pyrosequencing of bacterial

16S rRNA genes (423,145 sequences)

Functional approach - Illumina Hiseq 2000

High-throughput sequencing of soil metagenome (421,182,264 sequences)

Cerrado(Savannah)

No-tillage

Soil Sampling 2011/2012/2013

qPCRIllumina MiSeq

Functional genes

Conventional Tillage

SoilnorBNO

N2O

nosZ

N2

INTEGRATION LIVESTOCK-CROP SYSTEM A SUSTAINABLE MANAGEMENT

Forest

CH4

CH4

pmoA mcrA

consumption

emissions

Functional genesBorges et al. (2011)

Goss et al. (2013)

Quantification of key genes steering the microbial nitrogen cycle in soils under different land-uses in Mato Grosso

Bulk Soil Adjacent Forest

Bulk Soil Deforested Site

Soybean crop field site

Bulk Soil Adjacent Forest

Bulk Soil Deforested Site

Pasture site

Brachiaria brizantha and

Glycine max rhizosphere

N2

NH3

NO2- NO

N2O

nifH

amoA

nirK

norB

nosZ

Nitrogen Cycle

DNA Isolation

Amplification of functional

gene (nitrogen cycle)

qPCR*

*qPCR: Quantitative PCR or Real Time PCR, used to quantify, in number of

copies, gene target from a microbial community.

(A) Two soybean crop fields(B) Five points in each site(C) Mesocosm experiment(D) Rhizosphere and bulk soil (DNA)

AC

B

D C

Rhizosphere Bulk

THE RHIZOSPHERE EFFECT - SOYBEAN

Mendes et al. (2012) ISME14Mendes et al. (2014)

Taxonomical and functional microbial community selection in soybean rhizosphere

Lucas W Mendes, Eiko E Kuramae, Acácio A Navarrete, Johannes A van

Veen and Siu M Tsai

The ISME Journal , (20 February 2014) doi:10.1038/ismej.2014.17

Assembly of the microbial community in the rhizosphere is based

on niche-based processes as a result of the selection power of the

plant and other environmental factors.

RHIZOSPHERE X BULK SOIL

Microbial Taxonomy

Year 1 Year 5Mendes et al. 2013, submitted

RhizosphereBulk Soil

Rhizosphere and bulk soil network analysis based on taxonomic and functional abundance

Bulk Soil Rhizosphere

Total Correlations

310 236

Positive Correlations

191 143

Less Complex

Mendes et al. (2012) ISME14

Mendes et al. 2013, submitted

Mendes et al. (2012) ISME14

NITROGENMETABOLISM

Functional and taxonomic profiles of bulk soil samples (red) and rhizosphere (green) of

nitrogen metabolism, calculated for metagenomes from bulk soil and rhizosphere and

compared to SEED database using a maximum E-value of 1e-5 and a minimum

alignment length of 50 bp.

RHIZOSPHERE X BULK SOIL

Microbial Taxonomy and Functional Diversity

Mendes et al. 2013, submitted

Consequences of Amazon rainforest conversion: metagenomic analysis of soil-borne microbial community and their functional attributes

Lucas W Mendes, Siu M Tsai, Acácio A Navarrete, Mathias de Hollander, Johannes A van Veen, Eiko E Kuramae

• Major differences were observed in community composition: Proteobacteria,Acidobacteria, Verrucomicrobia, Actinobacteria, Chloroflexi, Bacteroidetes,Firmicutes and Planctomycetes.

• Genes related to nutrient cycle, respiration and resistance to stress were foundabundantly in forest.

• The altered soil presented high abundance of genes related to metabolism ofDNA, RNA and Protein. Agriculture soils and pasture were among the mostdiverse taxonomic and functionally. In forest, the ecosystem function ismaintained by the microbial abundance, while in agriculture and pasture ismaintained by high diversity and functional redundancy.

• Land-use change in Amazon forest affects the soil-borne microbial communitiesin both composition and functional attributes.

Cluster dendrograms of taxonomical profile created based on Bray-Curtis similarity for microbial communities of soils from four different land-use systems.

Variation of microbial taxa (a) and functional subsystem (b) among different sites across time. Vertical barsrepresent microbiome samples from 4 land uses type of shotgun data; bars indicate relative abundances colored bymicrobial phyla (a) and functional subsystems (b). Only the most abundant phyla/subsystems are shown.

Redundancy analysis of microbial community patterns and soil characteristics from samples of four different land use systems in the Amazon regions.

(a) Taxonomic analysis using relative abundance based on M5NR database at class level.

(b) Functional analysis using relative abundance based on SEED database at subsystemlevel 1. Analysis of similarity (ANOSIM) is indicated in the upper right of each graph.

(a) Levels of alpha diversity based on Shannon index for the different land use systems across four sampling times.

(b) Linear regression showing differences in alpha diversity levels across different land use systems. X-axis shows taxonomic diversity and Y-axis shows functional diversity, both based on Shannon index.

Box plot showing the distribution inthe proportion of the eight mostabundant phyla assigned to samplesfrom forest, deforested site,agriculture and pasture comprisingall sampling periods.

Trop-FACE

Carlos MartinezUSP-RP

0

20

40

60

80

100

120

1 105 127 146 153 160 167

WF

PS

(%

)

Water-filled pore space Soil temperature

15

17

19

21

23

25

27

29

1 105 127 146 153 160 167

TºC

Control

Elevated CO2

Elevated TºC

Elevated CO2+TºC

Warming+CO2

Water-filled pore space and soil temperature in the Trop-FACE experiment. The vertical bars represent standard error (n=4).

17

18

19

20

21

22

23

146 153 160 167

TºC

Days After Planting

Trop-FACE: Collaboration with Carlos Martinez

Emissions of CH4, CO2 and N2O in the Trop-FACE experiment. The vertical bars represent standard error (n=4).

-0,150

-0,100

-0,050

0,000

0,050

0,100

C-C

H4

(mg

-1m

2h

-1)

50

70

90

110

130

150

170

1 105 127 146 153 160 167

C-C

O2

(mg

-1m

2h

-1)

0

50

100

150

200

250

1 105 127 146 153 160 167

N-N

2O

(µ

g-1

m2

h-1

)

Control

Elevated CO2

Elevated TºC

Elevated CO2+TºC

CH4

N2O

CO2

Warming+CO2

Days After Planting

N2O CO2

Emissions of N2O and CO2 in the Trop-FACE experiment. The vertical bars represent standard error (n=4).

Fallow Grass Grass+warming+CO2

0

20

40

60

80

100

120

Control Elevated CO2 Elevated TºC ElevatedCO2+TºC

N-N

2O

(µ

g-1

m2

h-1

)


0

20

40

60

80

100

120

140

160

180


C-C

O2

(mg

-1m

2h

-1)


0,0E+00

5,0E+08

1,0E+09

1,5E+09

2,0E+09

2,5E+09

Co

py

gen

e 1

6S

bac

teri

ag-1

dry

soil

0,0E+00

5,0E+05

1,0E+06

1,5E+06

2,0E+06

2,5E+06

3,0E+06

3,5E+06

4,0E+06

4,5E+06

5,0E+06

Control Elevated CO2 Elevated T C Elevated CO2 +T C

Co

py

gen

e 1

6S

arch

aea

g-1d

ryso

il

Bacteria

Archaea

0,0E+00

5,0E+08

1,0E+09

1,5E+09

2,0E+09

2,5E+09

Co

py

gen

e 1

6S

g-1d

ryso

il

0,0E+00

5,0E+06

1,0E+07

1,5E+07

2,0E+07

2,5E+07

3,0E+07

3,5E+07

4,0E+07


Co

py

gen

e 1

6S

g-1d

ryso

il

Firmicutes

Verrucomicrobia

qPCR (16S rRNA)

0,0E+00

5,0E+06

1,0E+07

1,5E+07

2,0E+07

2,5E+07

3,0E+07

3,5E+07

4,0E+07

4,5E+07

5,0E+07


Co

py

gen

e A

OA

g-1

dry

soil

0,0E+00

5,0E+05

1,0E+06

1,5E+06

2,0E+06

2,5E+06

3,0E+06

3,5E+06

Co

py

gen

e A

OB

g-1

dry

so

il

0,0E+00

5,0E+06

1,0E+07

1,5E+07

2,0E+07

2,5E+07

3,0E+07

3,5E+07

4,0E+07

Co

py

gen

e n

osZ

g-1d

ryso

il

0,0E+00

2,0E+04

4,0E+04

6,0E+04

8,0E+04

1,0E+05

1,2E+05

1,4E+05

1,6E+05

1,8E+05


Co

py

gen

ep

mo

Ag-1

dry

soil

AOB (Bacteria)

AOA (Archaea) pmoA

nosZ

FUNCTIONAL GENES – N cycle

impact of land use change in the tropics on the dynamics ... · and its relations with greenhouse...

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