Preamble - Allocation Outcomes
About Allocation Outcomes for 2026 (click to view)
National Computational Merit Allocation Scheme (NCMAS)
The National Computational Merit Allocation Scheme (NCMAS) provides access to Australia’s national high‑performance computing (HPC) facilities through competitive peer review grounded in research and computational merit. Within this framework, the Scientific Advisory Committee (SAC) has an overriding responsibility: to allocate resources at levels that make the proposed meritorious research feasible, rather than dilute allocations across more projects at the cost of viability.
The 2026 round occurred under an unprecedented surge in demand. Across NCI and Pawsey, the call attracted roughly 245 proposals, and aggregate demand substantially exceeded the NCMAS allocation envelope. The pressure was especially acute in areas of rapidly escalating computational intensity—including large‑scale simulation, data‑driven discovery, and AI‑enabled workflows.
This round made visible a structural trend that has developed over several years: requests for HPC resources are growing far faster than Australia’s publicly funded national compute capacity. Between the NCMAS 2023 and 2026 rounds, demand rose by ~68%, while the resource envelope expanded by only ~6%. Specifically with respect to the NCMAS 2026 round, the annual demand grew by ~24%, while the resource envelope shrank by 4%. This widening gap between demand for HPC and available resource envelope to NCMAS is the central context for the 2026 outcomes, which reflects an increasingly urgent national vulnerability: Australia’s publicly funded research HPC is not scaling with the computational and simulation requirements of modern science and engineering and is not fit for purpose to take advantage of the opportunities that HPC and simulations bring to Australian Science, Engineering and the Economy.
Evidence snapshot (NCMAS requests vs available capacity of NCMAS)
Facility |
Available 2023 (kSU) |
Available 2026 (kSU) |
Requested 2023 (kSU) |
Requested 2026 (kSU) |
Oversub. 2023 |
Oversub. 2026 |
|
NCI/Gadi |
330,000 |
350,000 |
770,866 |
1,246,722 |
2.34× |
3.56× |
|
Pawsey/Setonix CPU |
295,000 |
325,000 |
390,033 |
611,675 |
1.32× |
1.88× |
|
Pawsey/Setonix GPU |
160,000 |
160,000 |
172,341 |
384,420 |
1.08× |
2.40× |
Total (Gadi+Setonix) |
785,000 |
835,000 |
1,333,240 |
2,242,817 |
1.70× |
2.69× |
Note: The NCMAS 2023 round was already oversubscribed by 1.70×, with NCI Gadi
leading with an oversubscription of 2.34×, which by the current NCMAS 2026 round has ballooned to an oversubscription of 3.56×.
Key changes since the NCMAS 2023 round:
- Total requests increased by 68% while total available capacity increased by 6% (oversubscription increased by 58%).
- Gadi requests increased by 62% vs Gadi capacity +6%.
- Setonix‑GPU requests increased by 123% while Setonix‑GPU capacity remained flat over the same period.
- By 2026, aggregate requested service units reached 2,242,817 kSU against an available envelope of 835,000 kSU (≈ 2.69x oversubscribed).
NOTE
This preamble is intended to provide context for the 2026 outcomes and to support clear communication with applicants and stakeholders. It does not replace the published NCMAS guidelines, Terms of Reference, or the outcome communication.
This mismatch has immediate consequences for a merit‑based process. As oversubscription intensifies, the SAC's ability to "fund the tail" diminishes. Allocation thresholds rise sharply; proposals competitive in prior years become unfundable; and partial allocations—already common across the last four NCMAS rounds—can push otherwise meritorious projects below the minimum level needed to remain feasible or internationally competitive. These outcomes are disruptive not only to research teams but also to national science programs and publicly funded grants that hinge on access to scalable HPC.
The SAC acknowledges community concerns regarding the 2026 outcomes—particularly perceptions of: fairness, transparency, disciplinary balance, and the concentration of resources. The committee emphasises, however, that its assessment and allocation process has not changed. It remains grounded in expert domain‑specific assessment of research and computational merit, informed—but not dictated — by facility technical advice. Yet in a year of severe oversubscription, even a consistent process may produce community‑level outcomes that appear abrupt, because proposals cluster tightly in score while the envelope is exhausted earlier.
Critically, constrained national capacity not only reduces the number of funded projects, but it also increases the likelihood that funded programs become delayed, de‑scoped, or rendered unfeasible and uncompetitive internationally. This risk is most acute in computationally and simulation-intensive national priority areas—including climate and environmental science, renewable energy and critical materials, transport, advanced manufacturing, medical and health research, and AI‑enabled research.
Against this backdrop, the SAC considers it essential to be candid: the 2026 outcomes are not the result of any procedural change or shift away from merit. They are the outcome of a structural shortfall in national HPC investment. Without sustained growth in HPC capacity—and the workforce and data infrastructure required to support it—future NCMAS rounds will remain volatile, with increasing risks to research feasibility and community confidence in the allocation process.
This structural challenge is not unique to NCMAS. The Australian Academy of Science has recently highlighted the national risk created by the absence of a long‑term HPC strategy and the urgent need for major investment, including at least one exascale‑class capability to sustain sovereign research capacity. The Academy’s February 2024 brief ("The future computing needs of the Australian science sector") provides detailed evidence of the scale and urgency of this issue and is available here:
https://www.science.org.au/sites/default/files/Publication/document/brief-1-hpcd-in-australia.pdf
Outcomes
Allocations displayed below were determined in a meeting of the NCMAS Scientific Advisory Committee.
- All values are kilo-service units (kSU). 1 service unit (SU) does not necessarily equal 1 cpu-hour. Please refer to each facility's documentation for more information on their charging rates.
| Project ID | Lead CI | Institution | Project Title | Allocations (kSU) | ||||
|---|---|---|---|---|---|---|---|---|
| Gadi | Setonix CPU | Setonix GPU | Setonix Q Pilot | Total | ||||
| NCMAS- |
Fengwang Li | University of Sydney | Advanced Computational Frameworks for Accurate DFT Simulations of Electrocatalytic Reactions | 1,100 | 1,100 | |||
| NCMAS- |
Haoxin Mai | Royal Melbourne Institute of Technology | Halide Perovskite Optoelectronics Developed by Integrated Synthesis, Calculation and Artificial Intelligence Methods | 1,000 | 1,000 | |||
| NCMAS- |
Matthew Field | James Cook University | Developing Bioinformatics Capability to Diagnose Infectious Diseases using Clinical Metagenomics | 2,200 | 2,200 | |||
| NCMAS- |
Zhenhai Xia | University of NSW | COMPUTATIONAL DISCOVERY OF NOVEL CARBON CATALYSTS FOR GREEN CHEMICAL PRODUCTION | 6,800 | 6,800 | |||
| NCMAS- |
David Edwards | University of Western Australia | Analysis of complex genomes | 4,000 | 300 | 4,300 | ||
| NCMAS- |
Min Hong | University of Southern Queensland | Computationally driven high-performance thermoelectric materials and devices | 1,000 | 1,000 | 2,000 | ||
| NCMAS- |
Jared Cole | Royal Melbourne Institute of Technology | The materials science of next generation quantum devices. | 1,500 | 1,500 | |||
| NCMAS- |
Jason Evans | University of NSW | Regional Climate Modelling in Australia | 7,300 | 2,900 | 10,200 | ||
| NCMAS- |
Abhirup Dikshit | University of NSW | Flash Drought & Fires | 1,000 | 1,000 | |||
| NCMAS- |
Eduardo Eyras | Australian National University | A scalable computational pipeline for molecular design | 1,900 | 1,900 | |||
| NCMAS- |
Adrian Pudsey | Royal Melbourne Institute of Technology | Aerothermodynamics of High Speed Flight and Enabling Technologies | 5,100 | 2,400 | 7,500 | ||
| NCMAS- |
Liam Scarlett | Curtin University of Technology | Atomic and Molecular Collision Theory | 4,500 | 24,600 | 9,700 | 38,800 | |
| NCMAS- |
Ravi Jagadeeshan | Monash University | Sticky polymers in flow: Nexus between microscopic and macroscopic dynamics | 4,500 | 4,500 | |||
| NCMAS- |
Tanveer Hussain | University of New England | Computational Design of Electrode Additives for Sodium-Based Batteries | 1,000 | 1,000 | 2,000 | ||
| NCMAS- |
Julian Gale | Curtin University of Technology | Atomistic Simulation for Geochemistry and Nanoscience | 2,900 | 9,600 | 4,800 | 17,300 | |
| NCMAS- |
Tilo Ziehn | CSIRO | Exploring climate and carbon cycle uncertainties through large ensemble simulations with ACCESS-ESM1.6 | 10,188 | 10,188 | |||
| NCMAS- |
Zhigang Chen | Queensland University of Technology | Design thermoelectric materials using first-principle calculation and machine learning | 3,900 | 3,900 | |||
| NCMAS- |
Andrew Christofferson | Royal Melbourne Institute of Technology | Optimizing liquid systems for catalytic, biomolecular, and nanomedicine applications | 2,000 | 500 | 3,400 | 5,900 | |
| NCMAS- |
Catherine Stampfl | University of Sydney | First-Principles Investigations of Processes and Properties in Catalysis, Coatings, and Devices | 7,600 | 7,000 | 14,600 | ||
| NCMAS- |
Julio Soria | Monash University | Investigation of the structure, evolution and transport properties of turbulent wall-bounded shear flows using direct numerical simulations | 10,000 | 31,200 | 41,200 | ||
| NCMAS- |
Steven Sherwood | University of NSW | Improving atmospheric modelling across scales | 2,500 | 2,500 | |||
| NCMAS- |
Riddhi Gupta | University of Queensland | Quantum computing algorithms for biomedicine | 1,000 | 1,000 | |||
| NCMAS- |
Tongliang Liu | University of Sydney | Machine Learning Interatomic Potentials for Transition State Modeling | 1,000 | 1,000 | |||
| NCMAS- |
Christoph Federrath | Australian National University | From Interstellar Turbulence to the Formation of Stars | 8,800 | 24,000 | 800 | 33,600 | |
| NCMAS- |
Liangzhi Kou | Queensland University of Technology | Data-Driven Exploration of 2D Functional Materials for Physical and Chemical Applications | 3,200 | 3,400 | 6,600 | ||
| NCMAS- |
Michelle Spencer | Royal Melbourne Institute of Technology | Modelling Nanoscale Materials for Catalysis, Sensing and Device Applications | 3,900 | 8,900 | 12,800 | ||
| NCMAS- |
Kiet Tieu | University of Wollongong | Numerical Modelling of MXenes Nanoparticles in Lubrications | 2,800 | 2,800 | |||
| NCMAS- |
Junxian Liu | Queensland University of Technology | Electrocatalytic C−N Coupling for Sustainable Urea and Formamide Synthesis | 1,000 | 1,000 | |||
| NCMAS- |
Zhe Liu | University of Melbourne | Integrated Computational Materials Engineering for Energy Materials | 6,900 | 19,000 | 2,000 | 27,900 | |
| NCMAS- |
Christoph Arns | University of NSW | Multi-scale multi-physics modelling for geostorage applicatons | 7,400 | 7,400 | |||
| NCMAS- |
Steven Armfield | University of Sydney | Large Scale Natural Convection Boundary Layers with Variable Fluid Properties | 1,100 | 2,600 | 3,700 | ||
| NCMAS- |
Lars Goerigk | University of Melbourne | Theoretical and Computational Quantum Chemistry Including Development of Computational Methods and Computational Materials Science | 1,100 | 1,100 | |||
| NCMAS- |
Jack Evans | University of Adelaide | Simulations of materials for gas separations and heterogeneous catalysis | 1,400 | 1,400 | |||
| NCMAS- |
Ha Bui | Monash University | Modelling gravity-induced rock fracture and fragmentation flow in cave mining: bridging laboratory and field scales | 3,100 | 3,100 | |||
| NCMAS- |
Ben Corry | Australian National University | Molecular simulation of membrane channels, transporters and receptors | 5,800 | 12,300 | 18,100 | ||
| NCMAS- |
Katrin Meissner | University of NSW | Abrupt climate change events in the past, present and future | 7,000 | 7,000 | |||
| NCMAS- |
Chao Xiong | University of Western Sydney | How climate extremes shape microbiome functions and plant disease | 1,000 | 1,000 | |||
| NCMAS- |
Giuseppe Barca | Australian National University | High-Accuracy, AI- and Quantum-Driven Digital Drug Design | 10,100 | 12,500 | 22,600 | ||
| NCMAS- |
David Pontin | University of Newcastle | Probing the origins of the Solar Wind with global-scale MHD simulations | 1,500 | 1,500 | |||
| NCMAS- |
Rhodri Davies | Australian National University | Revealing the 4-D Evolution of Earth's Engine | 8,300 | 6,300 | 14,600 | ||
| NCMAS- |
Leon Chan | University of Melbourne | Numerical simulations of rough-wall boundary layers | 3,300 | 3,500 | 1,800 | 8,600 | |
| NCMAS- |
Nicolas Flament | University of Wollongong | The influence of mantle dynamics on the evolution of complex life | 1,000 | 1,000 | |||
| NCMAS- |
Luke Bennetts | University of Melbourne | Assessing wave–sea ice interactions in a coupled ocean–sea ice–wave model | 3,400 | 3,400 | |||
| NCMAS- |
Fangbao Tian | UNSW Canberra | Bio-inspired Unmanned/Micro Aerial Vehicles and Aerodynamics on Mars | 6,600 | 6,600 | |||
| NCMAS- |
Bishakhdatta Gayen | University of Melbourne | The role of convection and turbulent mixing in ocean circulation | 2,700 | 11,000 | 13,700 | ||
| NCMAS- |
Tyler Rohr | University of Tasmania | mCDrive: Marine Carbon Dioxide Removal Impact and Validation Experiments | 3,100 | 3,100 | |||
| NCMAS- |
Santiago Badia | Monash University | Towards large-scale forward and inverse solvers for multiphysics problems with moving interfaces | 1,300 | 1,300 | |||
| NCMAS- |
Charlotte Petersen | University of Melbourne | Predictive Modelling of Metallic Nanoglasses: Structure, Dynamics, and Machine-Learned Glass Formability | 1,000 | 1,000 | |||
| NCMAS- |
Nicholas Chilton | Australian National University | Nanoscale magnetic memory elements | 2,800 | 2,800 | |||
| NCMAS- |
Susanna Guatelli | University of Wollongong | Development and use of Monte Carlo particle transport simulations for medical physics applications | 4,300 | 4,300 | |||
| NCMAS- |
Haibo Yu | University of Wollongong | Computer simulations of molecular systems and computer-aided molecular design | 4,000 | 7,300 | 7,200 | 18,500 | |
| NCMAS- |
Yan Jiao | University of Adelaide | Design Clean Energy Conversion and Storage Materials by Molecular Modelling | 8,800 | 1,200 | 1,200 | 11,200 | |
| NCMAS- |
Mark Krumholz | Australian National University | Star Formation and Feedback in a Turbulent Interstellar Medium | 10,000 | 12,300 | 22,300 | ||
| NCMAS- |
Daniel Chung | University of Melbourne | Direct numerical simulation of wall-bounded and buoyancy-driven turbulent flows | 1,600 | 25,000 | 700 | 27,300 | |
| NCMAS- |
Nikhil Medhekar | Monash University | Nanoscale Materials: From Atomic Structure to Functional Properties | 9,600 | 9,800 | 19,400 | ||
| NCMAS- |
Ekaterina Pas | Monash University | Development of Next-Generation Density Functional Theory | 7,400 | 1,000 | 8,400 | ||
| NCMAS- |
Rajib Rana | Australian University | Closing the Causality Gap: A Computational Framework for Validating Allosteric Drug Mechanisms | 1,000 | 1,000 | |||
| NCMAS- |
Jessica Jein White | CSIRO | Quantum vs Classical: Investigating Geochemically Relevant Small Molecules on Setonix-Q | 1,000 | 1,000 | |||
| NCMAS- |
Amir Karton | University of New England | AI-Driven Discovery for Regional Australia: Predictive Quantum Chemistry for Energy and Water Solutions | 2,000 | 2,000 | |||
| NCMAS- |
Lisa Alexander | University of NSW | Extreme rainfall in regional climate model simulations | 2,900 | 2,900 | |||
| NCMAS- |
Lei Wang | Griffith University | LiteMotion: Learning Efficient and Scalable Video Motion Representations | 2,400 | 2,400 | |||
| NCMAS- |
Simon Ringer | University of Sydney | Exploring structure-property correlations in advanced materials: Nexus between computational simulation and atomic resolution microscopy | 7,000 | 1,500 | 8,500 | ||
| NCMAS- |
Hrvoje Tkalčić | Australian National University | Seismological Studies of Earthquakes and Earth’s Internal Structure at a Plate Boundary | 4,000 | 4,000 | |||
| NCMAS- |
Luca Casagrande | Australian National University | Modelling the Evolution and Spectra of Stars: 3D Magneto-Hydrodynamic Stellar Atmosphere, Non-Equilibrium Radiative Transfer, and Machine Learning Generative Models | 8,500 | 8,500 | |||
| NCMAS- |
Karen Wilson | Griffith University | Elucidating CO2-to-Organonitrogen Conversion via Enhanced Sampling Simulations with Machine-Learned Interatomic Potentials | 2,500 | 2,500 | |||
| NCMAS- |
Andrew Ooi | University of Melbourne | Fluid Mechanics in Environmental Sustainability: Numerical Simulations, Data-Driven Insights and Mathematical Models | 5,100 | 9,800 | 7,200 | 22,100 | |
| NCMAS- |
Angli Xue | Garvan Institute of Medical Research | Identifying and characterising gene regulatory networks of autoimmune diseases at single-cell resolution | 1,000 | 1,000 | |||
| NCMAS- |
Francesco Campaioli | Royal Melbourne Institute of Technology | Controlling the relaxation rate of Rydberg atom arrays | 1,000 | 1,000 | |||
| NCMAS- |
Gordon Qian | University of Sydney | Exploring the biological foundations of mRNA splicing through artificial intelligence | 1,400 | 1,400 | |||
| NCMAS- |
Huijun Li | University of Wollongong | Accelerating Single Atomic Catalyst Design for CO2 Electrochemical Reduction through Synergy of Advanced Computational Machine Learning Techniques | 1,700 | 1,700 | |||
| NCMAS- |
Claire Vincent | University of Melbourne | Clouds, rain and Climate: Mapping a hierarchy of cloud, ocean feedbacks and rainfall processes to our global climate system. | 5,100 | 5,100 | |||
| NCMAS- |
Nehad Elsalamouny | University of Wollongong | Computer Simulations of Biomolecular Systems: Unveiling Mechanisms and Functions | 400 | 600 | 1,000 | ||
| NCMAS- |
Christopher Leonardi | University of Queensland | Direct numerical simulation of multiphase flows in complex geometries | 1,000 | 1,000 | |||
| NCMAS- |
Xiaotian WANG | University of Wollongong | Topological phonons in solids | 1,000 | 1,000 | |||
| NCMAS- |
Tiffany Walsh | Deakin University | Development and application of nano interfacial simulations | 2,300 | 2,300 | |||
| NCMAS- |
Mark Thompson | Monash University | Transition, stability and control of bluff body flows and wakes | 1,800 | 1,800 | |||
| NCMAS- |
Edward Doddridge | University of Tasmania | Antarctic systems and future change | 9,000 | 9,000 | |||
| NCMAS- |
Junming Ho | University of NSW | Accelerating the Design of Novel Catalysts and Drugs through Computational Chemistry | 3,700 | 600 | 5,400 | 9,700 | |
| NCMAS- |
Matthew England | University of NSW | Past, present and future climate variability and change in the Southern Ocean | 9,700 | 9,700 | |||
| NCMAS- |
James Zanotti | University of Adelaide | Quantum chromodynamics in focus: hadron structure and high-precision tests | 6,200 | 11,500 | 12,300 | 1,000 | 31,000 |
| NCMAS- |
Alan Mark | University of Queensland | From molecules to cells: Probing the structural, dynamic and quantum dynamic properties of cellular components at an atomic level. | 4,900 | 14,600 | 9,800 | 29,300 | |
| NCMAS- |
Judy Hart | University of NSW | Design and development of photoactive and catalytic materials for efficient solar conversion | 2,500 | 2,500 | |||
| NCMAS- |
Adele Morrison | Australian National University | The Ocean’s role in the climate system: from kilometres to global scales, from weeks to centuries | 9,200 | 9,200 | |||
| NCMAS- |
Stephan Rachel | University of Melbourne | Testing a next-generation quantum computer under real-world conditions | 2,200 | 2,200 | |||
| NCMAS- |
Anna Trigos | Peter MacCallum Cancer Centre | High performance compute for better personalised medicine for cancer patients | 1,700 | 1,700 | 3,400 | ||
| NCMAS- |
Joanna Achinger-Kawecka | University of Adelaide | Establishing the Regulatory Function of Transposable Elements in Cancer | 1,000 | 1,000 | |||
| NCMAS- |
Richard Sandberg | University of Melbourne | High-fidelity simulations of turbulent flows in power generation and transport | 5,000 | 9,000 | 12,800 | 6,000 | 32,800 |
| NCMAS- |
Cheong Xin Chan | University of Queensland | Comparative and Evolutionary Genomics of Microbes from Diverse Marine Environments | 7,300 | 7,300 | |||
| NCMAS- |
Vincent Wheatley | University of Queensland | Advancing the Science of Hypersonic Propulsion and Aerothermodynamics | 11,200 | 11,200 | |||
| NCMAS- |
Michelle Coote | Flinders University | Computer-aided Chemical Design of Catalysts and Control Agents | 9,100 | 9,100 | |||
| NCMAS- |
Xiaoguang Duan | University of Adelaide | Molecular Insights into Single Atom Catalysis for Water Decontamination | 1,000 | 1,000 | |||
| NCMAS- |
Robert Edwards | Flinders University | Combining metagenomics and AI to discover and understand novel bacteriophages and viruses | 3,300 | 12,600 | 15,900 | ||
| NCMAS- |
Ben Woodcroft | Queensland University of Technology | Large scale reconstruction of novel microbial genomes | 4,400 | 4,400 | |||
| NCMAS- |
Fatemeh Vafaee | University of NSW | AI-Driven Precision Medicine and Drug Discovery | 2,000 | 2,000 | |||
| NCMAS- |
Rajib Rahman | University of NSW | Multiscale Multiphysics Simulations of Silicon Quantum Information Processing Units | 8,800 | 8,800 | |||
| NCMAS- |
Evatt Hawkes | University of NSW | Direct Numerical Simulations of Turbulent Combustion | 5,500 | 17,700 | 12,600 | 35,800 | |
| NCMAS- |
Kasimir Gregory | University of New England | GPU-Accelerated Molecular Simulations for Circular-Economy Photovoltaics | 1,000 | 1,000 | |||
| NCMAS- |
Emilio Echevarria | CSIRO | Hybrid Modelling of Coastal Hazards Using Synthetic Tropical Cyclones and Machine Learning Surrogate Models | 1,000 | 1,000 | |||
| NCMAS- |
Toby Allen | Royal Melbourne Institute of Technology | Mechanisms of ion channel function and modulation. | 1,000 | 1,000 | |||
| NCMAS- |
Debra Bernhardt | University of Queensland | Molecular systems out of equilibrium: theory, simulation and application | 2,000 | 8,000 | 2,700 | 12,700 | |
| NCMAS- |
Olga Zinovieva | UNSW Canberra | High performance process-structure-property-performance simulations for advanced manufacturing | 1,000 | 1,000 | |||
| NCMAS- |
Mohsen Talei | University of Melbourne | Developing predictive tools for cleaner combustion | 4,000 | 7,600 | 11,600 | ||
| NCMAS- |
Megan O'Mara | University of Queensland | Multiscale Simulations for Precision Biotechnology: Molecular Self-Assembly in Dynamic Environments | 7,700 | 7,500 | 6,400 | 21,600 | |
| NCMAS- |
Albert Henry | Garvan Institute of Medical Research | DINGO: Drug Target Identification using Next-Generation Omics | 1,000 | 1,000 | |||
| NCMAS- |
Hongwei An | University of Western Australia | Advanced numerical modelling for developing safer and more efficient ocean infrastructure | 1,000 | 1,000 | |||
| NCMAS- |
Carla Verdi | University of Queensland | First-principles design and characterisation of materials for quantum technologies, clean energy and spintronics | 3,500 | 3,200 | 6,700 | ||
| NCMAS- |
Mathew Lipson | University of NSW | Urban-enabled global ACCESS climate simulations | 1,000 | 1,000 | |||
| NCMAS- |
Bram Hoex | University of NSW | Agentic Multimodal Large-Language-Model Framework for Autonomous De Novo Inorganic Crystal Design | 1,000 | 1,000 | |||
| NCMAS- |
Alexander Heger | Monash University | 3D Simulations of Core-Collapse Supernovae | 6,300 | 7,400 | 13,700 | ||
| NCMAS- |
Gemma Galbraith | James Cook University | Resolving Depth-Dependent Connectivity | 1,000 | 1,000 | |||
| Total | 387,288 | 325,000 | 160,000 | 12,000 | 884,288 | |||

