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Bacterial community structure as indicator of quality

changes in Brazilian soil: Integrating molecular based soil

microbial diversity data into a soil quality analytical

framework

Alexandre Soares RosadoAlexandre Soares Rosado

InstituteInstitute of of MicrobiologyMicrobiology

UFRJ UFRJ -- BrazilBrazil

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Relevance of microbial based indicators

Soil quality is obviously a concept in constant development, and it is foreseeable that this will remain so for some time to come.

• Since soil quality is strongly influenced by microbe-mediated processes, and function can be related to diversity, it is likely that microbial community structure will have the potential to serve as an early indication of soil degradation or soil improvement.

• Microbial-based indicators of soil quality are believed to be more dynamic than those based on physical and chemical properties. Recent developments in molecular biology based techniques have ledto rapid and reliable tools to characterize microbial community structures.

Does soil biodiversity matter for the future of humankind in its present

form? YES (K. Ritz)

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The rRNA-gene - an ideal molecular marker?

„The molecular clock“

Ubiquitous distribution

Functionally conserved in all forms of life

Regions of different degrees of conservation

Disadvantages

Different number of ribosomal operons

Sequence heterogeneities

A given variable region allows a different resolution for

different taxa

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The use of molecular fingerprinting methods to analyse the

structural composition of microbial communities

Single strand conformation polymorphism (SSCP)

Terminal-restriction fragment length polymorphism (t-RFLP)

Denaturing gradient gel electrophoresis (DGGE)Temperature gradient gel electrophoresis (TGGE)

DNA/RNA

PCR-amplification of 16S or 18S rDNA or rpoB

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Many equally abundant populations (high evenness):patterns with many bands

Few prominent populations (low evenness): patterns with few bands

Molecular fingerprints of microbial communities

Denaturing gradient gel electrophoresis(DGGE, TGGE)

PCR amplification of 16Sor 18S rDNA fragments

„community“ DNA or RNA

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Top-to-bottom analysis:Sequencing of differentiating bandsTaxon-specific primersUse of probes to identify bacterial isolatescorresponding to differentiating bands

Application of molecular fingerprinting techniques to study the

composition and dynamics of soil microbial communities

Cultivation-independent analysis of large numbersof samples

Advantages

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Soil aggregation and bacterial community structure as

affected by tillage and cover cropping in the

Brazilian Cerrados

Peixoto et al., 2006 (in press)

The Cerrados region in central Brazil occupies 22% of the country. It is

characterized by high average temperature (22 - 270C), rainfall (800 - 1600 mm)

and solar radiation (475- 500 Cal/cm2/day).

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L TW1 TW2 T1 T2 NTW1 F2

NT1 NT2 F1 NTW2 L

A

B

L TW1 TW2 T1 T2 NTW1 NTW2 NT1

NT2 F1 F2 L

Linkage Distance

F2/5-10 F1/5-10 F2/0-5 F1/0-5

NT2/5-10NT1/5-10

NTw2/5-10NTw1/5-10

NT2/0-5 NT1/0-5

NTw2/0-5NTw1/0-5

T2/5-10 T1/5-10

Tw2/5-10Tw1/5-10

T2/0-5 T1/0-5

Tw2/0-5 Tw1/0-5

0 2 4 6 8 10

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L TW1 TW2 T1 T2 NTW1 NTW2 NT1

NT2 F1 F2 L

Linkage Distance

F2/5-10 F1/5-10 F2/0-5 F1/0-5

NT1/5-10NTw2/5-10

NT2/5-10 NT2/0-5 NT1/0-5

NTw1/5-10NTw2/0-5NTW1/0-5

Tw2/0-5 T2/5-10 T1/5-10

Tw2/5-10Tw1/5-10

T2/0-5 T1/0-5

Tw1/0-5

0 2 4 6 8 10

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Another experiment using Genus specific primers:

Franco et al.

Tree Diagram for Variables

Unweighted pair-group average

1-Pearson r

0,0 0,2 0,4 0,6 0,8 1,0

Linkage Distance

PC_18

PC_17

PC_16

PC_15

PC_14

PC_13

PD_12

PD_11

PD_10

PD_09

PD_08

PD_07

MT_05

MT_04

MT_06

MT_03

MT_02

MT_010-5cm

Cerrado

No Till

Till

0-5cm

0-5cm

5-20cm

5-20cm

5-20cm

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Soil quality dynamics in a family based shifting cultivation system on a mountainous landscape of the Atlantic Forest, Rio de Janeiro State, Brazil:

Integrating molecular based soil microbial diversity data into a soil quality analytical framework

Aboim et al., in preparation

• The study area is ideal for this type of research since both perennial and short term crops are present, as well as forest fragments at different succession stages.

UxMxL

(Dlin

k/D

ma

x)*

10

0

55

60

65

70

75

80

85

90

95

100

105

M>70

M30

M15

P5

Pa

P3

P1

C3

C2

C1

Ba

Cf

-0,00M>70

0,000,55M30

0,540,81M15

0,770,89P5

0,910,91P3

0,930,79P1

0,860,82C3

0,980,92C2

0,980,89C1

1,000,99Ba

0,910,90Pa

1,000,94Cf

IDM30IDM70

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MDI values for all treatments (MDI = Vdi/Vdmax; where Vdi = distance value between treatment I and the reference treatment, and Vdmax = highest

distance value between all treatments and the reference treatment). Cf: coffee; Pa: pasture; Ba: banana; C1: first year crop; C2: second year crop; C3: third year crop; P1: first year fallow; P3: third year fallow; P5: five year

fallow; M15: 15-20 years old forest fragment; M30: 30–35 years old forest fragment; M70: forest over 70 years old.

Factor Loadings, Factor 1 vs. Factor 2

Rotation: Quartimax raw

Extraction: Principal components

Factor 1

Fa

cto

r 2

pH

Al

Ca_Mg

Ca

Mg

P

K

Na

H_AL %Corg

SB

t

T

V%

Areia_G

Areia_F Areia_T

Silte

Argila

DMP

DMG

IEA

IDM70

IDM30

Micorriza

-1,2

-0,8

-0,4

0,0

0,4

0,8

1,2

-1,2 -0,8 -0,4 0,0 0,4 0,8 1,2

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How BCE can be adapted to the requirements of LCA

framework?

Transformation of the PCR-DGGE data, which is essentially qualitative, into

numerical values (Microbial Diversity Impact, MDI), enabled the integration of bacterial diversity information into a soil quality analytical framework based on multivariate statistics

The underlying assumption for proposing MDI as a surrogate of microbial

diversity in soil quality analysis is that more importantly than assessing whether a specific land use or soil management causes an increase or decrease in microbial diversity, is the knowledge about how different from the original, or reference, situation the microbial diversity becomes.

Essentially, in practical terms, understanding the extent of the impacts suffered by soil microbial communities under different land use scenarios

would aid the development and monitoring of low or reduced impact

agricultural practices.

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General answers to the questions and the case studies suggested

Research initiatives would greatly benefit from soil quality indicatorssensitive enough to enable early prediction of changes in soil due to management.

Different environmental conditions, including soil type, climate, topography, and hydrology, might alter the variables that are more effective in discriminating the different treatments being analysed.

The nature of the treatments themselves can also affect the behavior of different soil quality variables. Therefore we suggest that an exploratory analysis, such as the one presented here, should be carried out prior to the offset of any extensive monitoring project, be it at a plot, watershed, or landscape level.

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Biodiversity and Systematics

Our knowledge of biodiversity needs to be greatly expanded by doubling the rate of taxonomic inventories and species discovery and description by 2015.

This will require a commensurate increase in taxonomic expertise and infrastructure.

The rapidly developing field of informatics and communications technology must be harnessed both to facilitate scientific work and to disseminate taxonomicproducts to all users, including the general public.

Important issues

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Important issues

• Removal of native vegetation in the tropics, and conversion to cropsand pastures have, in most cases, led to degradation of both soil andwater resources, even though high grain yields are being met Fieldand sampling design

• soil quality indicators measured in tropical land still covered bynative vegetation could serve as benchmarks for the development of management to achieve a sustainable agriculture.

• Once background baseline data are established, changes in ecosystem functioning can be detected and management systems developed to protect these systems from irreversible ruin

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Important issues

Due to the limitations of each method the use of a polyphasic

approach is recommended.

To interpret findings baseline data

(the season, the year, the field site ,soil type) are required.

This requires basic knowledge of reference ecosystems, dose-response curves for indicators under human-induced stress, and biodiversity-function relationships.

Comments on Case A, B and CComments on Case A, B and C

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Acknowledgments:

Dr. Raquel Peixoto

MSc. Marcela Aboim

BSc. Natalia Franco

Dr. Heitor Coutinho

- Embrapa Solos, Rio de Janeiro