There is burgeoning investment in national and global scale ecological monitoring infrastructure. These ecosystem observatories are critical for detecting and responding to ecological change in an era of rapid land use and environmental change (Borer et al. 2014; Caddy-Retalic et al. 2017; Cleverly et al. 2019; Loescher et al. 2022; Thorpe et al. 2016). Such infrastructure and networks aim to unify sampling methodologies and support regular data collection, particularly towards detection of national and global scale trends in the state of biodiversity and ecosystems. Here, we aim to highlight the additional importance of regional scale outcomes of such networks, through an introduction to the Great Western Woodlands TERN SuperSite, part of Australia’s national ecosystem observatory known as the Terrestrial Ecosystem Research Network (TERN). We describe the core infrastructure and partnerships involved in the Great Western Woodlands TERN SuperSite, and highlight science learnings to date from a subset of this infrastructure: three gradient plot networks as examples of regional scale outcomes.

TERN SuperSites are temporally intensive long term ecosystem observatories, that aim to facilitate a mechanistic understanding of ecosystem processes and how they are changing over time. There are currently 16 SuperSites established in core biomes across Australia. TERN SuperSites aim to include: (1) a core field site representing an Australian biome, with flux tower and base station; (2) at least one gradient transect (topographical or ecological); and (3) affiliated studies, including student projects (Karan et al. 2016). The Great Western Woodlands TERN SuperSite was established in 2012, centred on a 160,000 km² region in south-western Australia known as the Great Western Woodlands (Fig. 1).

Figure 1. The Great Western Woodlands (GWW) TERN (Terrestrial Ecosystem Research Network) SuperSite. Scope of the Great Western Woodlands TERN SuperSite (yellow circle), including parts of the intact Great Western Woodlands landscapes and fragmented Western Australian (WA) wheatbelt. SuperSite monitoring infrastructure shown: core flux tower site in the north-east (green circle) and five associated plot networks (Nutrient Network [yellow bullseye] and Drought-Net [blue bullseye]) experiments, Mulga-line transect (pink circles), South West Australian Transitional Transect (SWATT, yellow diamonds), Gimlet fire-age plots (orange circles). Map from Google Earth.

The Great Western Woodlands are globally significant in supporting largely intact, diverse landscapes including the world’s largest extant Mediterranean-climate woodland, in mosaic with mallee (lignotuber-resprouting eucalypt shrublands), highly diverse sandplain shrublands, ironstone and greenstone ranges and salt lakes (Watson et al. 2008). The region is bound to the north by a transition to the Acacia dominated rangelands (mulga), to the east by the Nullarbor (treeless) Plain, and to the south and west by the extensively cleared agricultural Western Australian (WA) wheatbelt. The eucalypt woodlands of the Great Western Woodlands are unusual in that they grow to over 20 m tall at mean annual rainfall at as low as 220 mm (Prober et al. 2012). Unlike most eucalypts, the dominant eucalypts in these woodlands are non-resprouters, and take hundreds of years to regrow from dense seedling recruitment following stand-killing fires (Gosper et al. 2018; Yates et al. 1994). The old-growth woodlands are highly valued by Indigenous and non-Indigenous communities, and managing impacts of climate change and the apparently increasing extent of large, intense fires are major ecological management challenges (Prober et al. 2012).

The Great Western Woodlands TERN SuperSite is strategically placed to contribute standardised data to national ecological data streams from a remote, semi-arid environment, at the same time as informing key management challenges within this globally significant area. Major regional scale goals include detecting temporal ecological change, characterising and managing fire regimes and facilitating adaptation of biodiversity and ecosystems in the Great Western Woodlands to a changing climate. The Great Western Woodlands TERN SuperSite also crosses into the adjacent WA wheatbelt, to enable contrasts between the relatively intact Great Western Woodlands, and the adjacent, highly cleared and degraded landscapes of otherwise similar ecosystems in the WA wheatbelt.

The SuperSite includes a core flux tower site with associated monitoring infrastructure near the northern eucalypt woodland boundary, a major ecotone between eucalypt woodlands and Mulga (Acacia) woodlands. This location was chosen as representative of an extensive, relatively intact old-growth eucalypt woodland landscape, and in the expectation that it might be an early sentinel of impacts of climate change. Around this core site is a series of six long-term plot networks falling mostly within the circle of 200 km radius that defines the SuperSite (Fig. 1). The core flux tower and plot network infrastructure has helped to concentrate associated research projects in the Supersite (e.g., Andrew and Fox 2020; De Kauwe et al. 2019; Gosper et al. 2019a, 2019b; Prober et al. 2013, 2016; Raiter et al. 2017, 2018a, 2018b; Zanne et al. 2022), helping to fulfill the three core goals of SuperSites.

To support research at the core flux tower site, we partnered with the WA Department of Biodiversity, Conservation and Attractions (DBCA) to establish the 36 m eddy-covariance flux tower (measuring exchanges of carbon, water and energy between the vegetation and atmosphere, Fig. 2), a Field Studies Centre and accommodation facility and other infrastructure on the Credo Proposed Conservation Reserve (hereafter Credo). This former pastoral lease is now managed for conservation by DBCA.

Figure 2. Long-term monitoring infrastructure at the flux tower site on Credo Proposed Conservation Reserve. (A) 36 m tall flux tower, (B) regularly-monitored core one hectare Eucalyptus salmonophloia AusPlot adjacent to flux tower, (C) litter traps and dendrometer bands in the core one hectare E. salmonophloia AusPlot, (D) soil pit (to 1.4 m deep) at flux tower site.

The Credo flux tower site (35 km from accommodation facilities) has a mean annual rainfall and temperature of 260 mm and 19°C, and occurs on relatively flat terrain (draining very gently to the east). The regolith beneath the eucalypt woodlands in the region is deeply (>40 m) weathered (Anand and Paine 2002) and a deep (>20 m), hypersaline, acidic water table is present (Gray 2001). In much of the area, the in-situ weathered regolith is overlain by sediments of massive, structureless red clays, often calcareous in the upper 0.5–2.0 m (Anand and Paine 2002). The soil sampled at the flux tower soil pit (Fig. 2) is a colluvial red sandy clay loam at the surface, grading to clay at approximately 70 cm. The vegetation in a five-kilometre radius surrounding the flux tower is predominantly open eucalypt woodland dominated by the obligate-seeder eucalypt species Eucalyptus salmonophloia (salmon gum), Eucalyptus salubris (gimlet) and Eucalyptus transcontinentalis (redwood), with patches of Eucalyptus clelandiorum (blackbutt) woodland on occasional greenstone bands, and occasional small patches of Acacia spp. (mulga) woodland and treeless chenopod shrubland where soils become shallow (Figs. 2 and 3).

Figure 3. Vegetation types included in the plot networks associated with the Great Western Woodlands TERN (Terrestrial Ecosystem Research Network) SuperSite. (A) Nutrient Network site including herbivore exclosure in cleared grassy woodland at Mt Caroline in the Western Australian wheatbelt, (B) Drought-Net site with rain-out shelters in chenopod shrubland at Credo, (C) Eucalyptus salmonophloia (salmon gum) and (D) Acacia spp. (mulga) woodlands of the Mulga-line transect, (E) sandplain shrublands of the SWATT (South West Australian Transitional Transect) transect and (F) long-unburnt E. salubris (gimlet) woodland of the Gimlet fire-age plots (estimated time since fire 260– 300 years, Gosper et al. 2013a).

As well as eddy-covariance flux instruments, the flux tower site includes a suite of additional monitoring infrastructure and measurements (Fig. 2), including 30-minute weather, soil temperature and soil moisture data, bioacoustics recordings, phenocam images, digital cover photography, field vegetation measurements and depth to water table, as summarised in Table 1 (Bissett et al. 2016; Bloomfield et al. 2018; White et al. 2012; Wiehl et al. 2023; Zanne et al. 2022). The flux data sets have been downloaded more than 3,800 times via the global FLUXNET portal alone since 2016 (https://fluxnet.org/sites/siteinfo/AU-GWW#data-use-log), and the broader data sets have contributed to over 100 publications worldwide that the authors are aware of.

Table 1 . Long-term monitoring infrastructure at or near the Great Western Woodlands TERN SuperSite flux tower^a.

Measure	Measurement details	Period of measurement
Continuous to 30 min
Bioacoustics	1. 2 SM2+ Songmeters from Wildlife Acoustics, Inc. installed at two locations (recordings for 6 hours around sunrise and sunset daily) 2. 4 Bioacoustic recorders (Frontier Labs) installed in pairs (close and distant to waterway) (recording constantly)	1. 2012–2020 2. 2020–present
Flux instruments	1. Open-path gas analyser (Licor 7500A/RS @36 m) 2. 3D sonic anemometer (CSA CSAT3B @36 m)	2012–present
Weather data	1. Wind direction (WINDSONIC4 @36 m) 2. Temperature and humidity (Vaisala HMP155 @3 m and 36 m) 3. Upwelling and downwelling longwave and shortwave radiation (Kipp and Zonen CNR4 @36 m) 4. Net radiation (Kipp and Zonen NR Lite 2 @36 m) 5. Rainfall (RIMCO RIM-7499-BOM)	2012–present
Soil heat flux	Three heat flux plates (Hukseflux HFP01) Two averaging soil thermocouple probes (CSA TCAV)	2012–present
Soil moisture and temperature	1. Soil moisture in two pits at 5, 10, 20, 30, 50, 70, 90 cm (CSA CS616) 2. Soil temperature at 5, 10, 20, 30, 50 cm (CSA 107 temperature probe)	2012–present
Phenocams	1. Timelapse cameras 2. Outdoor Observation and Surveillance Field Camera (CSA CCFC @36 m)	1. 2012–2018 2. 2021–present (daylight only)
Tree diameter increment	Logging Band Dendrometer (ICT DBL60). 7 Eucalyptus salmonophloia, 4 E. salubris, 4 E. transcontinentalis, 4 E. clelandiorum	2015–present
Photosynthetically active radiation (PAR)	Incoming and reflected PAR (LI-190R Quantum Sensor @36 m)	2020–present
Twice yearly
Leaf area index, crown and foliage cover	Digital cover photography at E. salmonophloia plot: 81 images on a 10 × 10 m grid	2013–present
Depth to water table	Sampled from bores at the E. salmonophoia and E. clelandiorum plots	2014–present
Birdlife Australia bird monitoring	Up to twice yearly surveys across 26 sites on Credo, including core flux site TERN AusPlots. Data collected and managed by Birdlife Australia, using Birdlife Australia 2 ha 20 min standard survey methodology	2014–2024
Litter accumulation	15 Litter traps in each of four 1 ha plots (E. salmonophloia plot, E. salubris plot, E. transcontinentalis plot, E. clelandiorum plot)	2013–present
Annual
Vegetation composition and structure	Standard TERN AusPlot vegetation method (White et al. 2012), September each year at E. salmonophloia TERN AusPlot	2013–present
Occasional
Tree diameter and height	All trees in four TERN AusPlots tagged and measured at least 5 yearly: E. salmonophloia (2012, 2018, 2023), E. salubris (2012, 2023), E. transcontinentalis (2018, 2023), E. clelandiorum (2013)	2012–present
Baseline soil pit and chemical sample	Soil physical and chemical description to 1.4 m	2012
AusPlots soil chemistry samples	Standard TERN AusPlot method (White et al. 2012); samples stored	2013
AustPlots soil biological samples	Standard TERN AusPlot method (White et al. 2012); samples stored	2013
BASE soil biological and chemical samples	Soil chemistry and genomics at 0–10 cm and 20+ cm (data available from Biomes of Australian Soil Environments (BASE) soil microbial diversity database, Bissett et al. (2016)	2013
Leaf physiology	Leaf traits leaf nitrogen, phosphorus, leaf mass-per-area, and photosynthetic parameters on multiple species Bloomfield et al. 2018)	2013–2014
Standardised wood decomposition rate	Pine blocks deployed in E. salmonophloia AusPlot, collected at 12 and 24 months post deployment (Zanne et al. 2022)	2016–2018
Standardised teabag decomposition rate	Decomposition rate measured on two teabag types over 36 months (Keuskamp et al. 2013)	2018–2021
Ant composition	Sampled in E. salmonophloia AusPlot using TERN Australian SuperSites monitoring protocols (Wiehl et al. 2023)	2011–2012 and 2015
Airborne LiDAR coverage	Airborne laser scanning over 5 × 5 km grid centred over flux tower	2012, 2021

TERN: Terrestrial Ecosystem Research Network.

^aData and meta-data variously available from TERN Data Portal (https://portal.tern.org.au/), as cited, or from the authors.

The plot networks of the Great Western Woodlands TERN SuperSite (Table 2) (Borer et al. 2014; Gibson et al. 2017; Gosper et al. 2013a; Yahdjian et al. 2021) have been established in partnership with a range of organisations, including Australia’s Commonwealth Scientific and Industrial Research Organisation (CSIRO), TERN, DBCA, the WA Departments of Jobs, Tourism, Science and Innovation (DJTSI) and Primary Industries, Innovation and Regional Development, the University of Western Australia, Murdoch University, James Cook University, Edith Cowan University, Birdlife Australia and the Ngadju Conservation Aboriginal Corporation. In addition to the six 1 ha plots at the core SuperSite, the plot networks include two plot networks that are part of global experimental networks. These are a Nutrient Network experiment assessing outcomes of nutrient enrichment and grazing exclusion in grassy woodlands of the wheatbelt edge of the SuperSite (Fig. 3A), and a Drought-Net experiment in chenopod shrubland assessing impacts of imposed drought (Fig. 3B). Data from these global networks have now contributed to over 50 science publications.

Table 2 . Plot network infrastructure associated with Great Western Woodlands TERN SuperSite.

Plot network	Key partnerships	Plot and measurement details	Period of measurement
Core SuperSite
Hectare plots	TERN, CSIRO, DBCA	6 standard 1 ha TERN AusPlotsa in vegetation types surrounding flux tower (Eucalyptus salmonophloia, Eucalyptus salubris, Eucalyptus transcontinentalis, and Eucalyptus clelandiorum woodland, chenopod shrubland, Acacia woodland), biannual to 5 yearly measures on eucalypt woodland plots as Table 1	2013–present
Global networks
Nutrient Network	Global NutNet consortium, CSIRO, Mt Caroline property owners	Standardised experimental design and monitoring following Nutrient Network protocols (Borer et al. 2014) Includes annual measurement of floristic composition and biomass, irregular soil and other measures	2008–present
Drought-Net	Global Drought-Net consortium, DBCA, CSIRO, TERN, Murdoch University	Standardised experimental design and monitoring following Drought-Net protocols (Yahdjian et al. 2021). Includes annual measurement of floristic composition and biomass, irregular soil and other measures	2015–present
Gradient plots
South West Australian Transitional Transect	DBCA, TERN, CSIRO	Four standard TERN 1 ha AusPlots with nested 20 × 20 plots at each of 10 locations along the 1,200 km transect (total 160 plots)	Measured in 2013, 1 ha plots repeated in 2022
Mulga-line transect	CSIRO, TERN, DBCA, DJTSI, University of Western Australia, James Cook University, Edith Cowan University, Ngadju Conservation Aboriginal Corporation	12 standard 1 ha TERN AusPlots along a 700 km transect along an aridity gradient and crossing the ecotone between eucalypt and Acacia dominated woodland. Additional annual monitoring of vegetation, soil microbes, and ants	2022–present
Gimlet fire-age plots	CSIRO, TERN, DBCA, Ngadju Conservation Aboriginal Corporation, DPIIRD, Birdlife Australia	76 × 0.25 ha plots across a gradient of times since stand-replacement fire in woodlands dominated by E. salubris. Base measures include vegetation floristics, cover and structure, with visual Vesta fuel assessment, 20-min 2-ha bird survey, ants, drone- and airborne-based LiDAR, plant biomass at a sub-set of plots	First established 2010–2012, various measures since, ongoing

TERN: Terrestrial Ecosystem Research Network; CSIRO: Commonwealth Scientific and Industrial Research Organisation; DBCA: Department of Biodiversity, Conservation and Attractions; DJTSI: Department of Jobs, Tourism, Science and Innovation, DPIIRD: Department of Primary Industries, Innovation and Regional Development.

^aTERN AusPlots are standard 1 ha plots using methodology described in White et al. (2012).

The remaining three plot networks involve three gradient transects. Transects that traverse climatic or other ecological gradients are recognised as effective platforms for climate change or other ecological research (Caddy-Retalic et al. 2017). The gradient plot networks of the Great Western Woodlands TERN SuperSite capture a fire age gradient in E. salubris (gimlet) woodlands, and aridity gradients in sandplains (South West Australian Transitional Transect, SWATT) and woodlands (Mulga-line transect).

Mulga-line transect

The Mulga-line transect was established in 2022, as one of three TERN transects in WA supported by TERN, DJTSI, CSIRO, DBCA, Ngadju Conservation Aboriginal Corporation, University of Western Australia, James Cook University and Edith Cowan University, that aim to pilot temporal biodiversity monitoring (i.e. regular monitoring each year) across major climate gradients. These aim to create temporal and spatial datasets along major climate gradients to (1) provide an initial characterisation of spatial climate patterns on three biodiversity groups–plants, ants and soil microbes, and (2) build up temporal data streams to detect change in vegetation and biodiversity over time. The Mulga-line transect has been designed not only to capture an aridity gradient–ranging from c. 17°C mean annual temperature and 300 mm mean annual rainfall in the south to 21°C and 255 mm in the north–but also to cross the Mulga-line. Hence, seven plots are in E. salmonophloia (salmon gum) woodland (Fig. 3C) and five in Acacia spp. (mulga) woodland (Fig. 3D). We are particularly interested to detect any evidence that the Mulga-line might start to move southwards as the climate warms, as is predicted by ecological modelling, or any other ecological change attributable to climate change (Prober et al. 2012).

South West Australian Transitional Transect

The establishment of the SWATT transect (Gibson et al. 2017) was led by Prof. Stephen van Leeuwen and Dr. Neil Gibson then based at DBCA, as part of the then TERN Australian Transect Network. It was designed to include six sets of plots in the sandplain shrublands (Fig. 3E) of Great Western Woodlands TERN SuperSite, as well as capturing two sandplains in the mesic far south-west and two desert sites in the north east. The SWATT extends for over 1,200 km and covers a rainfall gradient of 1,235 mm. It has a unique design developed to test rates of species turnover in sandplains, which are known to be extremely diverse. To achieve this there are sixteen plots at different distances apart at each of ten locations, i.e. 160 plots altogether. This transect similarly aims to characterise spatial change with climate, and in particular, whether species turnover rates vary with aridity. Monitoring has included plants and soils, with key results demonstrating (1) a very high rate of complete effective plant species turnovers (Whittaker’s βW-1, averaging 2.5 every 10 km); (2) consistent high rates of turnover at all locations along the transect, i.e. independent of the aridity gradient or edaphic factors (Gibson et al. 2017). From a management perspective these results indicate that reserve-based conservation strategies are unlikely to effectively conserve species in the south-western Australian sandplains. Rather, they emphasise the importance of off-reserve management and for minimising disturbance footprints in intact landscapes, especially given projected climate change.

Gimlet fire-age plots

The third set of gradient plots were established by CSIRO, DBCA, and TERN in response to increasing recognition of the significance of the Great Western Woodlands as the world’s largest extant temperate woodland, the value of old-growth stands to Indigenous and non-Indigenous communities, and the significant emerging threat of increases in intense fires (Prober et al. 2012). In contrast to other semi-arid eucalypt woodland communities, the dominant Great Western Woodlands woodland eucalypts are obligate-seeders with fires being stand-replacing. Hence, old-growth woodland values are potentially being degraded through a recent spate of large wildfires likely linked to climate change (Prober et al. 2012; Yates et al. 1994).

The 76 permanently-marked Gimlet fire-age plots (e.g. Fig. 3F) were established across a time since fire chronosequence in woodlands dominated by E. salubris (gimlet). A key early achievement was establishment of a method for ageing individual trees and stands, via a tree size-age model calibrated by growth ring counts and satellite imagery (Gosper et al. 2013a). This established that old-growth stands had a time of origin (last stand-replacement fire) up to 450 years previously. The early goals of the plot network were to understand changes in biodiversity and ecosystem processes over exceptionally long timeframes, and hence potential impacts of increases in fire under climate change.

Vascular flora, birds and ants have been sampled on the Gimlet fire-age plots. Key findings were that (1) some species and functional groups of biota were associated with specific periods of time since fire; (2) post-fire changes in the composition of communities extends over multi-century time frames; (3) for birds and flora, species richness peaked in old-growth woodlands (woodland age is continuous, but here we refer to old-growth as being >~140 years); and (4) for birds most species of conservation significance were associated with old-growth woodlands (Gosper et al. 2013c, 2015, 2019a, 2019b). An important implication of these studies is that old-growth woodlands have greater conservation value and that once burnt, recovery of these values is not feasible over a meaningful management timeframe, emphasising the importance of minimising fire in currently old-growth stands.

Measurements of vegetation structure and flammable fuels have revealed that dense regrowth stands (~30 to 120 years since fire) have greater surface litter cover, shrub cover and tree cover (Gosper et al. 2013b, 2014). Thus intermediate-aged stands are likely to be more flammable than either recently-burnt or old-growth woodlands, which is consistent with independent calculations of hazard of burning from remotely-sensed imagery (O’Donnell et al. 2011). The higher flammability of intermediate-aged woodlands is important because it means that once they burn, regenerating woodlands are more likely to burn again, and need to get through that fire trap before fuels become more spatially disjunct over the course of centuries in transition to old growth woodlands. Prior fire interval has a large bearing on standing dead tree and coarse woody debris piece size. Larger pieces, which provide greater habitat value for fauna and retain greater carbon stocks, occur after longer fire intervals (i.e. when old-growth woodlands are burnt; Gosper et al. 2019c).

A collaboration with Ngadju Conservation Aboriginal Corporation and the University of Bristol has leveraged the on-ground data of the Gimlet fire-age plots to map woodland size and age-class distribution across the Great Western Woodlands. The Gimlet fire-age plots were augmented with a larger temporary plot network at which tree size and density data were collected. These field data were linked across three scales of LiDAR–drone- and airborne-based LiDAR flown over a subset of the field plots, and LiDAR data from the GEDI satellite, to effectively extrapolate field-based tree measures across the Great Western Woodlands (Jucker et al. 2023). The spatial data on woodland age class structure has informed just how much fire there has been in the last half century–nearly 40% of woodland area has burnt at least once–while focussing attention on the ~41% of the area still covered in old growth woodlands. This spatial product is now assisting land managers (including State and Indigenous) in targeting fire management to reduce fires in priority old-growth woodlands.

Finally, we are now using the gimlet and other woodland plots and the subsequent age-class mapping work to explore options for a carbon methodology based on reducing the amount of fire in the Great Western Woodlands. Preliminary data indicates there is a substantial increase in biomass carbon along the sequence from young to old-growth woodland, as would be expected. If economically significant quantities of carbon can be sequestered or retained in woodlands with changes in fire regimes, and fire management can successfully shift fire regimes in a desirable direction, it could provide a pathway to fund fire management, provide employment opportunities and support biodiversity and cultural values.

This paper for the first time introduces the suite of ecological monitoring infrastructure and data streams of the Great Western Woodlands TERN SuperSite. This includes standardised core monitoring at an eddy covariance flux tower, and series of plot networks using standardised monitoring methodologies. Our synthesis showed that gradient plots, designed to capture spatial gradients (in fire age and aridity) represent an effective monitoring design, enabling shorter term outcomes informed by spatial gradients whilst building up longer-term data streams to detect temporal change. We emphasise that all research infrastructure and data described are available for collaborative research, including data accessible from the TERN Data Portal (https://portal.tern.org.au/).

An important but often overlooked element of ecological monitoring observatories is their regional scale outcomes and partnerships. Here we demonstrated how infrastructure can be designed to inform nested scales, from regional to national and global, through applying globally or nationally consistent methodologies to regional scale questions, and building regional partnerships. This led to positive outcomes informing conservation planning in the highly diverse WA sandplains, and better outcomes for fire management in fire sensitive old growth woodlands, with knowledge relevant to climate adaptation management expected as results from the Mulga-line transect become available. These regional-scale outcomes include generalisable insights (e.g. LiDAR applications, long-term ecology of woodlands dominated by obligate-seeders, conservation implications in highly biodiverse landscapes) and contribute to the >150 regional to global scale publications known to have included data from the Great Western Woodlands TERN SuperSite infrastructure.

The research described involved many individuals in addition to the authors, including Dr Margaret Byrne and Mr Nigel Wessels (DBCA), Dr Neil Gibson, Mr Ian Kealley OAM and Dr Rachel Meissner (previously DBCA), Prof. Stephen van Leeuwen (Curtin University), Prof. Jason Beringer and Dr Caitlin Moore (University of Western Australia), Dr Richard Silberstein (Edith Cowan University), Prof. Will Edwards (James Cook University) and Dr Rachel Standish (Murdoch University). The Great Western Woodlands TERN SuperSite includes the traditional lands of a number of First Nations peoples including Ngadju, Wongi and Noongar Nations Peoples.

TERN: Terrestrial Ecosystem Research Network

WA: Western Australia

DBCA: Department of Biodiversity, Conservation and Attractions

CSIRO: Commonwealth Scientific and Industrial Research Organisation

DJTSI: Department of Jobs, Tourism, Science and Innovation

DPIIRD: Department of Primary Industries, Innovation and Regional Development

SWATT: South West Australian Transitional Transect

The Great Western Woodlands TERN SuperSite was initiated by SMP and CM, with flux tower and instrumentation oversight by CM and other core flux site data overseen by GW and SMP; CRG led establishment of the Gimlet fire-age plots with contributions from SMP and GW; LS and HL led collaborations with Ngadju Conservation Aboriginal Corporation; SMP led the writing of this manuscript with significant contributions from all co-authors.

The Great Western Woodlands TERN SuperSite has been supported by the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS)-enabled Terrestrial Ecosystem Research Network (TERN) and a range of other organisations, including CSIRO, the Ngadju Conservation Aboriginal Corporation, and the Western Australian Government Departments of Biodiversity Conservation and Attractions; Primary Industries, Innovation and Regional Development; and Jobs, Tourism, Science and Innovation.

The datasets described in this paper are available on the TERN data portal (https://portal.tern.org.au/), in cited publications or from the corresponding author on reasonable request.

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