base (biomes of australian soil environments) - andrew bissett

Andrew Bissett, Andrew Young, Kelly Hamonts & Kristen Williams

BASE – Biomes of Australian Soil Environments

Presentation Outline

Introduction to BASE

Methodology

Progress to date– Environmental sampling

– Amplicon sequencing

– Metagenome sequencing

– Modeling

BASE: Biomes of Australian Soil Environments | Andrew Young2 |

Future steps

Sampling

Sequence Analysis

Modeling

Data Management

INTRODUCTION TO BASE

3 | BASE: Biomes of Australian Soil Environments | Andrew Young

BASE: Biomes of Australian Soil Environments

Aim of BASE is to develop a National Framework Data set of Australian soil microbial diversity

Combines metagenomics of environmental samples with soil“contextual” data and modelling at continental scale

TO present a publically available database of soil related diversity information

What is BASE?


Why BASE?

Very little is known about the identity, abundance or distribution of soil microbial communities. Yet they are ecologically very important.

They: Mediate key ecological processes e.g.

nutrient cycling, carbon cycling, water purification

Form crucial symbiotic associations with plants e.g. nitrogen fixation

Play roles in bioregulation e.g. disease suppressive soils

Etc.


Soil bacteria

Soil fungi

What will BASE do?

Measure and map microbial community diversity and composition, edaphic and other site specific variables across Australia

Model relationships between microbial community structure and soil environment, vegetation composition and climate

Provide a publically available research database (a National Framework Dataset) for exploration of soil biological diversity and function


What will BASE do?

Test biogeographical and evolutionary hypotheses regarding microbial ecology and plant-microbe co-evolution

Explore relationships between Australia’s microbial diversity and that of the rest of the world

Examine effects of land management

Inform restoration and management of soil diversity and ecosystem services


Who is involved in BASE?

BioPlatforms Australia

CSIRO

VicDPI

DOTE and DECWA• Atlas of Living Australia

• Australian Antarctic Division

• Australian National Data Service (ANDS)

• Department of Agriculture, Forestry and Fisheries

• Department of Sustainability Environment Water Population and Communities (SEWPAC)

• Grains Research and Development Corporation

• La Trobe University

• Science and Industry Endowment Fund (SIEF)

• South Australian Research and Development Institute (SARDI)

• Tasmanian Land Conservancy

• Terrestrial Ecosytem Research Network (TERN)

• Monash University

• University of Adelaide

• University of New South Wales

• University of Queensland

• University of Western Australia

• University of Western Sydney


METHODOLOGY


Environmental sampling 600+ sampling points in intact natural biomes

across the continent⁻ Stratified by soil type, vegetation composition and

climate

⁻ Mainly National reserve system thus far

25mx25m quadrats⁻ 9 soil cores split into 0-10cm and >20cm depth

⁻ Cores bulked, mixed and stored for soil chemistry and DNA analysis

⁻ Site specific data recorded (Vegetation, slope, aspect, etc.)


Amplicon sequencing

Amplicon sequencing (Illumina)- Bacteria –16S

- Fungi –ITS

- Archaea – 16S

- Euk – 18S

Bioinformatics pipeline:- BASE database - EMP protocol of closed

reference OTU picking

- Specifc analysis pathways for specifcprojects/questions


Metagenome sequencing

Use amplicon sequencing data to: Identify “interesting” samples for metagenomic

sequencing

Indentify likely samples for differential binning matches

Similar compositions, different abundances

HiSeq

Incorporate metagenomic information into models Metabolic diversity turnover

Functional distribution models


Sampling – data –sampling workflow

Quantify diversity and abundance of microbial communities

Model abundance and composition in relation to environmental parameters measured at each site

Model against continental environmental data “surfaces”

Extrapolate to continental scale

Undertake environmental gap analysis

Add new samples and refine model


PROGRESS TO DATE


Soil chemistry and vegetation data

Edaphic variables– all samples have data for: Soil moisture, Texture, Ammonium, Nitrate,

Nitrogen, Phosphorus, Potassium, Sulphur, Total Carbon, Organic Carbon, Conductivity, pH, Copper, Iron, Manganese, Zinc, Exc. Aluminium, Exc. Calcium, Exc. Magnesium, Exc. Potassium, Exc. Sodium, Boron, Grain Size (% gravel, sand, silt, clay), project specific data (minerology, MIR, biogeochemical rates,……..).

Non-edaphic/climate/site– all samples have data for: Overlying plant cover (% and identity), slope,

aspect, location, elevation, land-use history, land-management history.

Data for first 400 samples are available online (BPA website), ALA


Amplicon sequencing

Sequenced 100 samples using 454 pyrosequencing with bacterial and fungal tags Data available online via BPA (although not in such a useful format)

Illumina reads for first 600 samples due next week


Metagenome sequencing

HiSeq data generated for 6 sites (12 samples)

Test whether amplicon data can inform suitability for sample analysis, binning etc.

Sequences generated from both 350bp and 550bp fragments to assess efficacy of both

Data being analysed now


BASE database

Developed an offline (access) relational database that allows searching of sequence and contextual data

Currently migrating this to online tool, with AAD, ALA and Centre for Comparative Genomics (BPA)

Raw Sequence data available via BPA data store


SOME RESULTS


Model – using site contextual data

20 |

Model (3 & 9)

5778 site pairs

% Deviance

Explained# predictors Main predictor

Presence/

Absence73.0 13 Conductivity

Abundance 74.1 14 Conductivity

BASE: Biomes of Australian Soil Environments | Andrew Young

Exploratory models compared OTU presence/absence and abundance

using soil chemistry data (common between sites) using data from first 98

sites for which all data were available

Presentation title | Presenter name22 |

Antarctica

Xmas Island

Minerology sites

NRS

TERN supersites

Trend transect


Bacteria Fungi

• Edaphic and spatial components were significant in explaining community structure for

both bacterial and fungal communities

• pH and conductivity most important

• Communities at different soils depths were significantly different

only for bacteria

NEXT STEPS…


Extended environmental sampling

Add Temporal component to sampling Long term monitoring sites

Sites with biogeochemical rate data

Sites identified as containing residual information

Sites with NO residual information (to test model)

More metagenomic samples (as guided by amplicon data)


Agricultural sampling

Cropping, grazing, horticulture⁻ Stratified soil type and by production

system

Measure same parameters as environmental sites


Modeling

Extend Generalised Dissimilarity modelling to include PhlogeneticDistance metrics

Create species distribution models

Incorporate temporal aspect into models

Test models


Database availability development


The BASE Team:CSIRO: Andrew Bissett, Leon Court, Kelly Hamonts,

Shamsul Hoque, Kristen Williams, Andrew Young

Bioplatforms Australia: Anna Fitzgerald, John

Stephens and Catherine Zhang

University of Adelaide: Frank Reith

DEC WA: Margaret Byrne and David Coates

DSEWPaC: Belinda Brown and Parks field staff at:

Kakadu, Christmas Is, Booderee, Uluru

TERN: Supersites

SIEF: Strategic resourcing

Others: Vic DPI, Gondwana Link, Bushblitz, Antarctic

Division


base (biomes of australian soil environments) - andrew bissett

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