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BCCVL Chinese Academy of Sciences Workshop Hamish Holewa, Program Manager, Biodiversity and Climate Change Virtual Laboratory, Griffith University P - +61 400027653 [email protected]
BCCVL Chinese Academy of Sciences Workshop
Hamish Holewa, Program Manager, Biodiversity and Climate Change Virtual Laboratory, Griffith University
P - +61 400027653
WeChat ID: hholewa
Australian Virtual Laboratories and eReseach Initiatives
Australian Collaborative
eResearch Infrastructure
38,000+ cores Multi-petabyte storage Education network Data management programs
Virtual Laboratories
• Formed around engaged research communities
• Built on existing research capabilities
• Support research workflows
• Easier access to data and analysis tools
• Facilitate sharing of data and results
• Provide platform for collaboration and contributions
Australian Virtual Labs
National eResearch Collaboration Tools And Resources
1. All Sky Virtual Lab (Astronomy)
2. Virtual Geophysics Laboratory
3. Humanities Network Infrastructure
4. Marine Virtual Laboratory
5. Genomics Virtual Lab
6. Industrial Ecology Virtual Lab
7. Climate & Weather Science Virtual Lab
8. Virtual Hazards, Impact and Risk VL
9. Microbial Genomics Virtual Lab
10. Characterization Virtual Lab
11. ALVEO (Human Communication)
12. Endocrine Genomics Virtual Lab
13. Biodiversity and Climate Change VL
Virtual Laboratories uptake
• NeCTAR Virtual Laboratories are:
– Demonstrably successful in:
• Supporting research communities across the breadth of
Australian research
• Harnessing sector co-investment to sustain the infrastructure
– Increasingly supporting key NCRIS domain capabilities
• Eg. Genomics, characterisation,, climate and weather science,
astronomy, biodiversity and climate change
• In future, Virtual Lab program should:
– Improve strategic alignment with NCRIS domain
investments
• While continuing to address broad needs across the Australian
research sector
7
Continuing growth in uptake: • Over 10,000 registered research users
Aggregating and processing research data: • Over 120,000 datasets uploaded
Over 250 TeraBytes Uploaded
The Biodiversity and Climate Change
Virtual Laboratory
A big collaborative effort…
08
Prof Brendan Mackey
Climate Change
Griffith University
Prof Emeritus Henry Nix AO
Climate Change
A/Prof Shawn Laffan
Geospatial analysis/ Biodiversity
University of New South Wales
A/Prof Jeremy VanderWal
Ecology
James Cook University
Dr Linda Beaumont
Climate Ecology
Macquarie University
Our Experts
A/Prof Sama Low Choy
Statistics
Griffith University
A/Prof Fabiana Santana
Computer Science
University of Canberra
Mr Lee Belbin
Ecology
Atlas of Living Australia
A/Prof Mark Kennard
Freshwater ecology
Griffith University
How?
Access to data
Photo: © Shane Ruming
Species occurrence data
Annual precipitation 30 arcsec (~1 km resolution)
Max temperature warmest month 30 arcsec (~1 km resolution)
Major vegetation groups 3 arcsec (~90 m resolution)
Gross Primary Productivity 9 arcsec (~250 m resolution)
> 4000 Climate data layers
– Current and future climate
– Range of climate change scenarios and global climate models
> 300 Environmental data layers
(soil, vegetation, run off, GPP, fPAR etc)
Access to data
Advanced modelling capability
Potential distribution of species under current climatic
and/or environmental conditions
Species Distribution Experiment
Multi-Species Distribution Experiment
Effect of environment on
species traits
Species Trait Experiment
Advanced modelling capability
Effect of climate change on predicted species
distributions
Thorny devil, 2045 RCP 8.5 ‘business as usual’
Thorny devil, 2085 RCP 8.5 ‘business as usual’
Climate Change Projection
Analysis of biodiversity, species richness, rarity,
endemism
Biodiverse Experiment
Combine model outputs to reduce uncertainty
Mean
Min
Max
Ensemble Analysis
Results
Bioclim 01 (annual mean temperature)
Bioclim 12 (annual precipitation)
Advanced modelling capability
Education topics Our users do cool things!
Supporting forest managers in finding pre-
adapted tree populations to
mitigate climate impacts in Hungary
Education topics Our users do cool things!
Local government mapping raptor nests to inform management decisions
Current 2085
Education topics Our users do cool things!
Modelling species of interest in Tanzania
Matilda’s Horn Viper
Kipunji Monkey
Education topics Our users do cool things!
Education topics Our users do cool things!
Modelling hotspots of richness for
>500 acacia species
3 months – 1 hour
Education topics Our users do cool things!
Refining models at the click of a button
Noxious weed
Education topics Our users do cool things!
Undergraduate curriculum
assessment item
• Data types
• Providers
• Licensing
• Data cleaning
• Data generation
• Spatial interpolation
• Scale
• Resolution
Data
BCCVL
Education topics Education topics
• Purpose
• Problem definition
• Experimental design
• Underlying principles
• Model assumptions/
limitations
• Algorithms
• Taxonomy
• Statistics
• Model evaluation
Science
Knowledge Base
Education tools
This content downloaded from 132.234.251.230 on Tue, 22 Sep 2015 02:05:02 UTCAll use subject to JSTOR Terms and Conditions
Education tools
1 – Intro to Species Distribution Modelling
2 – Ecological theory of SDMs
3 – Data
4 – Designing a SDM
5 – Presence only models
6 – Statistical regression models
7 – Machine learning models
8 – Model evaluation
9 – SDMs and climate change projections
10 – Case studies in the BCCVL
Online Open Course
Education tools Education tools
Workshops
• BCCVL & ALA workshop
• Different audiences – Undergraduate
– Academic
– Industry
• 24 workshops run = 723 participants
Education tools Education tools
Champions Program
Outcomes Outcomes - reach
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.gmail etc.
.org
.gov.au (Government)
.edu (University)
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Supporting Infrastructure
• National Research Cloud • 38,000 Cores • Multi-petabyte storage • Openstack Cloud Platform
Computation and Data Infrastructure
• National User Support Network • National Help Desk
• Phone Number • Chat • Email
• Training Programs
• Software Carpentry • Champions Program
Support and Education Infrastructure
• Computation • 400 workers • Scalable
• Storage • Object Storage • API Access to external data
• Software
• R-Server • Rabbit MQ • Plone
• Management
• Containers/ Kubernetes • Github
BCCVL Infrastructure
Scalable - Servers can be in Australia, New Zealand, China - Capacity can be increased quickly and easily
Benefits
Data - Data can be stored in locally - Restrict access to users or groups - Access external data easily
Customise and expand - Experiments and analysis added
Latest technology - Quick setup and operation - Run on any Cloud - Repeatable
• Computation • 400 Cloud Computers • Expandable
• Storage
• Limitless (Cloud based) • Access to external data
• Software
• R-Server • GIS • Python
• Management
• Containers/ Kubernetes • Github
BCCVL Infrastructure
Scalable - Servers can be in Australia, New Zealand, China - Capacity can be increased quickly and easily - Doesn’t use own laptop
Benefits
Data - Data can be stored in locally - Restrict access to users or groups - Access external data easily
Customise and expand - Experiments and analysis added easily - Tailor for use - Publishable workflows
Latest technology - Quick setup and operation - Run on any Cloud - Repeatable
Enabling – General Modelling Platform
New Zealand Specific Environmental and
Climate
NZ - BCCVL M- BCCVL
?? BCCVL
Marine SDM and Traits
Marine Data
Country
Domain
Methods
Future Programs and Opportunities
Data Challenges
• Access to Dynamic Data
• Weather data
• High resolution, country specific data
• Environmental, climate, biological
• Combine traits, genomics, phenology data
• Vector based data (e.g. Biosecurity threats)
• Shipping lanes, people, movement
Potential Research Programs
• Invasive Species
• China/ Australia have similar land area
• Similar amount of identified invasive species
• Migratory Modelling
• Australia/ China Migratory Bird Agreement
• Integrating current and future land cover and land use change into SDM/ Climate Change Models
• Trait expression as a function of time and space
Potential Research Programs
• Invasive Species
• China/ Australia have similar land area
• Similar amount of identified invasive species
• Migratory Modelling
• Australia/ China Migratory Bird Agreement
• Integrating current and future land cover and land use change into SDM/ Climate Change Models
• Trait expression as a of environmental correlates
Localisation
• Chinese specific datasets
• Environmental
• Biodiversity (Occurrence)
• Language
• Internet Explorer
• Authentication
Future Data Challenges
• Access to Dynamic Data
• Weather data
• High resolution, country specific data
• Environmental, climate, biological
• Combine traits, genomics, phenology data
• Vector based data (e.g. Biosecurity threats)
• Shipping lanes, people, movement
Opportunities
Data • Dynamic Data – Daily
Interpolated weather data • Trait Data – Environmental/
Genetic • Anthropogenic and urban
layers • International datasets
Models • Species Trait - Function of
Time and Space • Mechanist/ Functional • Self-calibrating models • Data preparation (NicheA?)
Training • Industry targeted • Micro accreditation
Prediction Services • Constantly updated models
(when new data available) • Self calibrating models • Environmental prediction
services
Proposal #1 China-Australia
collaboration on developing
Biodiversity & Climate Change
Modeling Platforms (Virtual Labs) and
Data Hubs
Collaboration & Resource Sharing
• Exchange of existing platforms and knowhow
• Co-development of these platforms functionality
• Sharing and linking for collaborative research purposes of existing and new biological, climate and environmental data
• Co-development of new tools, techniques and experiments
• Collaborate on training and teaching materials and activities.
Proposal #2 International network of
modeling platforms (Virtual Labs) and
Data Hubs?
Broader international collaboration, e.g. Asia-Pacific network
Sharing access to modeling and data platforms
Access (with permission) international high resolution country specific data;
Share and iteratively develop best practice models;
Develop new tools, techniques and experiments;
Share and collaborate on training and teaching materials.
