Australia’s ecosystems are globally significant, yet the lack of a nationally consistent classification system has hindered effective environmental reporting and policy development. The adoption of the IUCN Global Ecosystem Typology offers an opportunity to standardise ecosystem classification across the country, enabling coherent reporting, data integration, and informed decision-making.

This globally recognized framework provides a scientifically robust and hierarchically structured typology that can be applied across terrestrial, freshwater, and marine environments. Its implementation in Australia will support a wide range of environmental reporting needs, including the development of environmental indicators, ecosystem condition assessments, and environmental-economic accounts aligned with the UN System of Environmental-Economic Accounting (SEEA).

By providing a consistent basis for ecosystem identification and comparison, the typology facilitates comparability of data across jurisdictions and internationally. The systematic framework also promotes transparency of data availability and can help identify critical data gaps, guiding future data collection and monitoring efforts. This strengthens Australia’s ability to meet international reporting obligations.

Challenges remain in operationalising the typology nationally, including reconciling existing regional classifications, ensuring compatibility with Indigenous ecological knowledge, and fostering cross-sector uptake. Addressing these challenges requires collaboration and input from governments, scientists, Indigenous communities, and other stakeholders. The hierarchical structure of the IUCN GET provides an opportunity to produce Australia specific ecosystem types that can benefit from existing classification schemes and establish a clear link between local knowledge and the needs of international reporting. The production of these Australian ecosystem types will be the focus of a project coordinated by Environment Information Australia and led by the lead author of the GET, Dr David Keith.

Moving forward, integrating the IUCN Global Ecosystem Typology into Australia’s environmental reporting systems will provide a foundation for more transparent, consistent, and actionable insights into ecosystem health and change.

Australia’s biodiversity and ecosystem resilience depend on high-quality, spatially and temporally consistent vegetation data. The National Vegetation Information System (NVIS), maintained by the Department of Climate Change, Energy, the Environment and Water (DCCEEW), is the nation’s authoritative platform for collating and disseminating native vegetation information. NVIS underpins a wide range of ecological and policy applications, including species distribution modelling, bushfire recovery planning, the Nature Repair Market, and State of the Environment reporting.

Despite its foundational role, NVIS faces several limitations: data gaps, inconsistent classification standards across jurisdictions, infrequent updates, and limited accessibility for researchers and the public. These challenges constrain its utility in addressing urgent environmental issues and supporting evidence-based decision-making.

In response, the NVIS Roadmap (2024) outlines a staged transformation to modernise the system and enhance its relevance across ecological disciplines. Key priorities include establishing a regular update cycle, integrating remote sensing and machine learning to detect vegetation change and improve consistency, data accuracy, and expanding access through streamlined digital platforms. The Roadmap also emphasises collaboration with state and territory agencies to ensure national interoperability and alignment with emerging data standards.

This presentation will highlight the strategic vision of the NVIS Roadmap and its potential to elevate Australia’s vegetation data information, showcasing both the successes of this national-level collaboration and the ongoing challenges in achieving the Roadmap’s key objectives. By addressing long-standing limitations and embracing technological innovation, NVIS is poised to become a more dynamic, accessible, and policy-relevant resource—critical to supporting biodiversity conservation, climate adaptation, and sustainable land management in a rapidly changing environment.

Systematic field observations (plot samples) increasingly underpin the development of systematic and comprehensive vegetation classification systems world-wide. However, the distribution of samples across Australia’s major environmental gradients is uneven, with many gaps. This is problematic for the deployment of clustering algorithms typically used to elucidate patterns in vegetation data, because they are insensitive to variation in sample density. Here we propose an approach to leveraging the available plot data in the development of a continent-wide classification system. Key components of the workflow include i) Australia’s first comprehensive and integrated of ecosystems, which facilitates an incremental, thematic approach by sorting existing plots into ecological functional groups; and ii) network theory which can inform an a priori diagnosis of noise in the data and support the elucidation of clusters of variable shape and density. To illustrate the process, we present case studies addressing rainforest and forested wetland ecosystems in southeast Australia.

Vegetation classification has an important, but often unrecognised role to play in understanding, managing, and conserving Australian ecosystems. Classification systems are often hierarchical and typically reliant on vegetation plot data. The most recent continental classification system in Australia is the National Vegetation Information System (NVIS), a structural-physiognomic system designed for vegetation mapping. The NVIS framework can also be applied at the plot level for describing vegetation types. It is a six-level hierarchical classification with the broadest level identified by the dominant growth form, to the detailed level six describing up to five dominant species and structural formations for a maximum of nine substrata. Differences in jurisdictional vegetation mapping datasets are resolved by compiling data into the NVIS vegetation hierarchy and further generating NVIS major vegetation groups and subgroups to create a seamless coverage of vegetation types across Australia.
Vegetation plot data is increasingly recognised for input to classification and validation of various regional and national scale vegetation data products. However, consistent national or internationally recognised typologies have not been applied to vegetation plot data. In recognising this gap, the Terrestrial Ecosystem Research Infrastructure (TERN) Ecosystem Surveillance Capability, developed a pilot to automate the NVIS vegetation hierarchy to over 900 monitoring plots representative of Australia’s major biomes. TERNs national network of plots captures the core field attributes required to characterise and describe vegetation at the plot level, including vegetation structure and composition (structure: height and cover, growth form and floristics).
This presentation will explain the rulesets applied to the quantitative vegetation data to generate the NVIS vegetation hierarchy across TERNs plot network. Limitations and future requirements, such as autogenerating major vegetation groups and subgroups, and examples of national scale applications and future end uses will be discussed.

Biocrusts—communities of mosses, lichens, microbes and other little things that grow on the soil surface—can be found in most terrestrial ecosystems. They play a range of functional roles relating to soil stability, nutrient cycling and hydrology. Somewhat worryingly, global models suggest that they might decline in cover by as much as 40 % in the next half century under climate change. Yet there are no detailed maps of biocrust cover in Australia, which hinders any efforts to conserve biocrusts or track range shifts in the future. Here, we used an extensive replicated survey (397 sites) to 1) model biocrust cover across 1.7 million km2 of south-eastern Australia, 2) identify particular hot and cold spots, and 3) quantify land-use conflicts. Our models estimate that average biocrust cover in the region is 13 %, with the highest cover occurring in semi-arid and arid drylands. Biocrusts were largely absent from flood-prone areas and wet forests, but showed distinctive hot-spots in central New South Wales and the arid plains west of the Flinders Ranges. Land use conflicts were widespread in the semi-arid zone, and our results indicate that 36,000 km2 of present-day cropland would have been occupied by biocrusts prior to European colonisation. From a land management perspective, our findings suggest that efforts to conserve and restore biocrusts should focus on dryland regions with stable well-drained soils and minimal ongoing livestock disturbance. More broadly, our study provides crucial baseline information to monitor biocrusts and facilitate range-shifting in a warming world.

Freshwater wetlands have a dynamic interconnected relationship between surface water and groundwater. In the Anthropocene, wetlands are facing extraordinary pressures due to episodic climate events, the impacts of climate change, over allocation of surface water and groundwater resources and declining water quality. Yet, for many wetland ecosystems, the connectivity between surface and groundwater and the ecological response to those hydrological processes is poorly understood. This project aimed to identify critical hydrological exchange processes that may influence important ecological functions (e.g. vegetative habitat provisioning) in wetlands of the Lower Murray River, South Australia. Hydrological regimes (including an Environmental watering event) were monitored over 12 months. Continuous water level, temperature, specific electrical conductivity (salinity) monitoring, and episodic field data collection (water quality; plant health (uptake of Na+ and K+)) was undertaken to investigate the temporal changes compared with remote sensing plant cover data (NDVI). We found that wetland plants responded to surface-and groundwater derived influxes, and drying processes was an influencing factor on functional plant group growth and heath. Additionally, we found that plants responded according to the perturbations of surface-and ground-water hydrology that was unique to each wetland. With an ever-increasing likelihood that more regular episodic flow and drought events will happen under climate change, we need to understand the response of important habitat-forming ecological communities (such as plants) in wetlands that are supported by surface-and ground-water fluxes. This research provides some insights into plant functional group responses to surface water and groundwater regimes, which will be key knowledge for managing the resilience of these habitat-formers in the Anthropocene.

Habitat mapping underpins biodiversity assessment, land-use planning, and ecological monitoring—but most continental, or national vegetation maps, including Australia’s NVIS, are model-driven, poorly ground-truthed, and uncertain at fine scales. This project explores the potential for bird assemblages to serve as an independent validation layer for mapped vegetation classes.

Using 100 randomly selected locations from across Australia—each with an associated bird list sourced from eBird—we compared the observed vegetation to classifications from three systems: NVIS Major Vegetation Subgroups (MVS), state-based classifications (e.g. REDD, PCT, EVC), and the Habitats of the World (HotW) system. We then applied a custom-built “Bird Assemblage Habitat Program” (BAHP), which predicts the most likely habitat based on indicator-weighted bird species.

We found that BAHP predictions were more likely to match the observed vegetation than any of the three mapping systems alone. More importantly, when the BAHP habitat prediction agreed with a mapped classification, the likelihood that the map was correct increased significantly. In effect, bird assemblages act as a probabilistic validator, greatly improving confidence in existing mapping wherever species data are available.

This study demonstrates that bird assemblages can enhance habitat mapping without replacing existing systems. The method is scalable, leverages citizen science, and bridges remote sensing with ecological ground-truthing. Our results suggest that birds are not only indicators of ecological condition—but also powerful tools for validating the maps that guide conservation action.