Carbon Storage in the Coastal Swamp Oak Forest Wetlands of Australia

Kelleway, Jeffrey J.; Adame, María Fernanda; Gorham, Connor; Bratchell, Jennifer; Serrano, Óscar; Lavery, Paul; Owers, Christopher J.; Rogers, Kerrylee; Nagel-Tynan, Zachary; Saintilan, Neil

doi:10.1002/9781119639305.ch18

Cited by 7 publications

(5 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The approach for estimating changes in SOC stocks was based on the mass of organic carbon and accumulation rates in soils from a national collation of SOC sequestration rates in coastal wetlands (Serrano et al 2019) updated to include recently published and unpublished datasets, including those for supratidal forests (Adame et al 2020; Jones et al 2019; Kelleway et al 2021) and sparsely vegetated saltmarshes or salt flats (Brown et al 2021) (Table S1).…”

Section: Methodsmentioning

confidence: 99%

An Australian blue carbon method to estimate climate change mitigation benefits of coastal wetland restoration

Lovelock

Adame

Bradley

et al. 2022

Restoration Ecology

Self Cite

View full text Add to dashboard Cite

Restoration of coastal wetlands has the potential to deliver both climate change mitigation, called blue carbon, and adaptation benefits to coastal communities, as well as supporting biodiversity and providing additional ecosystem services. Valuing carbon sequestration may incentivize restoration projects; however, it requires development of rigorous methods for quantifying blue carbon sequestered during coastal wetland restoration. We describe the development of a blue carbon accounting model (BlueCAM) used within the Tidal Restoration of Blue Carbon Ecosystems Methodology Determination 2022 of the Emissions Reduction Fund (ERF), which is Australia's voluntary carbon market scheme. The new BlueCAM uses Australian data to estimate abatement from carbon and greenhouse gas sources and sinks arising from coastal wetland restoration (via tidal restoration) and aligns with the Intergovernmental Panel for Climate Change guidelines for national greenhouse gas inventories. BlueCAM includes carbon sequestered in soils and biomass and avoided emissions from alternative land uses. A conservative modeled approach was used to provide estimates of abatement (as opposed to on-ground measurements); and in doing so, this will reduce the costs associated with monitoring and verification for ERF projects and may increase participation in blue carbon projects by Australian landholders. BlueCAM encompasses multiple climate regions and plant communities and therefore may be useful to others outside Australia seeking to value blue carbon benefits from coastal wetland restoration.

show abstract

Section: Methodsmentioning

confidence: 99%

An Australian blue carbon method to estimate climate change mitigation benefits of coastal wetland restoration

Lovelock

Adame

Bradley

et al. 2022

Restoration Ecology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Deviated original vegetation floristic structure and landform descriptors shown by the XAI-SHAP deviations, were grassland, heathland and mangrove. These are all coastal ecosystems and differ from vineforest, open woodlands and forest shown to be proxy indicators of DIN dynamics for gauged catchments 30 While data transfer from existing gauged catchments to the four coastal catchments is not supported by our study, our method can instead be used to inform where new water quality monitoring and gauging sites could have the greatest value to represent all DIN regimes 12 , 47 , 56 – 58 . New monitoring and gauging sites are recommended in each of the four coastal catchment groups to collect data representative of all DIN regimes, which could facilitate data transfer for modelled DIN predictions across all ungauged Great Barrier Reef catchments.…”

Section: Discussionmentioning

confidence: 80%

Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef

O’Sullivan,

Deo,

Ghahramani

2023

Sci Rep

View full text Add to dashboard Cite

Transfer of processed data and parameters to ungauged catchments from the most similar gauged counterpart is a common technique in water quality modelling. But catchment similarities for Dissolved Inorganic Nitrogen (DIN) are ill posed, which affects the predictive capability of models reliant on such methods for simulating DIN. Spatial data proxies to classify catchments for most similar DIN responses are a demonstrated solution, yet their applicability to ungauged catchments is unexplored. We adopted a neural network pattern recognition model (ANN-PR) and explainable artificial intelligence approach (SHAP-XAI) to match all ungauged catchments that flow to the Great Barrier Reef to gauged ones based on proxy spatial data. Catchment match suitability was verified using a neural network water quality (ANN-WQ) simulator trained on gauged catchment datasets, tested by simulating DIN for matched catchments in unsupervised learning scenarios. We show that discriminating training data to DIN regime benefits ANN-WQ simulation performance in unsupervised scenarios ( p< 0.05). This phenomenon demonstrates that proxy spatial data is a useful tool to classify catchments with similar DIN regimes. Catchments lacking similarity with gauged ones are identified as priority monitoring areas to gain observed data for all DIN regimes in catchments that flow to the Great Barrier Reef, Australia.

show abstract

“…Casuarina forests have 143 Mg of carbon per ha, with a standard error of 61, for aboveground and 241 Mg of carbon per ha, with a standard error of 136, for belowground stocks (at a 1 meter depth; Kelleway et al. 2022 ). Cypress swamps and mixed ( Nyssa, Fraxinus, Alnus ) forest stands have 115 and 560 Mg of carbon per ha for aboveground and belowground stocks, respectively, with respective standard errors of 20 and 125 (1.4 meter depth; Krauss et al.…”

Section: Tidal Wetlands Have Long-term Storage Of Fixed Carbon Dioxidementioning

confidence: 99%

“… 2019b ), Casuarina (Kelleway et al. 2022 ), cypress and mixed forests (Krauss et al. 2018 ), P. aquatica (Adame et al 2015 ), Picea (Kauffman et al.…”

Section: Tidal Wetlands Have Long-term Storage Of Fixed Carbon Dioxidementioning

confidence: 99%

All tidal wetlands are blue carbon ecosystems

Adame,

Kelleway,

Krauss

et al. 2024

BioScience

View full text Add to dashboard Cite

Managing coastal wetlands is one of the most promising activities to reduce atmospheric greenhouse gases, and it also contributes to meeting the United Nations Sustainable Development Goals. One of the options is through blue carbon projects, in which mangroves, saltmarshes, and seagrass are managed to increase carbon sequestration and reduce greenhouse gas emissions. However, other tidal wetlands align with the characteristics of blue carbon. These wetlands are called tidal freshwater wetlands in the United States, supratidal wetlands in Australia, transitional forests in Southeast Asia, and estuarine forests in South Africa. They have similar or larger potential for atmospheric carbon sequestration and emission reductions than the currently considered blue carbon ecosystems and have been highly exploited. In the present article, we suggest that all wetlands directly or indirectly influenced by tides should be considered blue carbon. Their protection and restoration through carbon offsets could reduce emissions while providing multiple cobenefits, including biodiversity.

show abstract

Carbon Storage in the Coastal Swamp Oak Forest Wetlands of Australia

Cited by 7 publications

References 58 publications

An Australian blue carbon method to estimate climate change mitigation benefits of coastal wetland restoration

An Australian blue carbon method to estimate climate change mitigation benefits of coastal wetland restoration

Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef

All tidal wetlands are blue carbon ecosystems

Contact Info

Product

Resources

About