National scale predictions of contemporary and future blue carbon storage
Creators
- 1. Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Warrnambool Campus, Geelong, VIC 3125 (Australia)
- 2. School of Science and Centre for Marine Ecosystems Research, Edith Cowan University, Joondalup, WA 6027 (Australia)
- 3. Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood Campus, Geelong, VIC 3125 (Australia)
- 4. School of Biological Sciences, The University of Queensland, St. Lucia, QLD 4072 (Australia)
- 5. Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Queenscliff Campus, Geelong, VIC 3125 (Australia)
Description
Highlights: • Vegetated coastal ecosystems store significant amounts of 'blue carbon'. • Environmental and anthropogenic conditions explain the variation in blue carbon. • Spatially explicit maps of blue carbon stocks are developed at a national scale. • Climate projections are used to assess future suitability for blue carbon. • The results help to pinpoint current and future locations for blue carbon projects. To help mitigate the impacts of climate change, many nature-based solutions are being explored. These solutions involve protection and restoration of ecosystems that serve as efficient carbon sinks, including vegetated coastal ecosystems (VCEs: tidal marshes, mangrove forests, and seagrass meadows) also known as 'Blue Carbon' ecosystems. In fact, many nations are seeking to manage VCEs to help meet their climate change mitigation targets through Nationally Determined Contributions (NDCs). However, incorporation of VCEs into NDCs requires national-scale estimates of contemporary and future blue carbon storage, which has not yet been achieved. Here we address this challenge using machine learning approaches to reliably map (with 62–72% accuracy) soil carbon stocks in VCEs based on geospatial data (topography, geomorphology, climate, and anthropogenic impacts), using Australia as a case study. The resulting maps of soil carbon stocks showed that there is a total of 951 Tg (±65 Tg) of carbon stock within Australian VCEs. Strong relationships between soil carbon stocks and climatic conditions (temperature, rainfall, solar radiation) allowed us to project future changes in carbon storage across all RCP scenarios for the years 2050 and 2090 to determine changes in environmental suitability for soil carbon stocks. Results show that soil carbon stocks in mangrove/tidal marsh ecosystems are likely to predominantly experience declines in carbon stocks under predicted climate change scenarios (19% of ecosystems area is predicted to have an increase in soil carbon stocks, while 38% of ecosystems area is predicted to have a decrease in soil carbon stocks), but a majority of seagrass area is likely to have increased soil carbon stocks (56% increase, 7% decrease). This approach is effective for developing robust national blue carbon inventories and revealing the capacity for blue carbon to help meet NDCs. The resulting spatially-explicit maps can also be used to pinpoint areas for successful blue carbon projects both now and in the future.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.scitotenv.2021.149573Additional details
Identifiers
- DOI
- 10.1016/j.scitotenv.2021.149573;
- PII
- S0048969721046489;
Publishing Information
- Journal Title
- Science of the Total Environment
- Journal Volume
- 800
- Journal Page Range
- vp.
- ISSN
- 0048-9697
- CODEN
- STENDL
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 54061343
- Subject category
- S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- BIOLOGICAL RECOVERY; CARBON; CARBON SINKS; CLIMATES; GEOMORPHOLOGY; GREENHOUSE EFFECT; MACHINE LEARNING; MANGROVES; MARSHES; SOILS; SOLAR RADIATION; TOPOGRAPHY
- Descriptors DEC
- ALGORITHMS; AQUATIC ECOSYSTEMS; ARTIFICIAL INTELLIGENCE; CLIMATIC CHANGE; ECOSYSTEMS; ELEMENTS; GEOLOGY; LEARNING; MAGNOLIOPHYTA; MAGNOLIOPSIDA; MATHEMATICAL LOGIC; NONMETALS; PLANTS; RADIATIONS; SINKS; STELLAR RADIATION; TREES; WETLANDS
Optional Information
- Copyright
- Copyright (c) 2021 Elsevier B.V. All rights reserved.