Potential for Return on Investment in Rehabilitation-Oriented Blue Carbon Projects: Accounting Methodologies and Project Strategies

被引:10
作者
Duncan, Clare [1 ,2 ]
Primavera, Jurgenne H. [3 ,4 ]
Hill, Nicholas A. O. [5 ,6 ]
Wodehouse, Dominic C. J. [7 ]
Koldewey, Heather J. [1 ,4 ]
机构
[1] Univ Exeter, Ctr Ecol & Conservat Biosci, Coll Life & Environm Sci, Penryn, England
[2] Zool Soc London, Inst Zool, London, England
[3] Zool Soc London Philippines, Iloilo, Philippines
[4] Zool Soc London, Conservat & Policy, London, England
[5] Coast 4C, Cronulla, NSW, Australia
[6] Univ Technol Sydney, Climate Change Cluster, Ultimo, NSW, Australia
[7] Mangrove Act Project MAP, Port Angeles, WA USA
关键词
mangroves; carbon emissions reduction; rehabilitation; natural regeneration; blue carbon; remote sensing; ECOSYSTEM SERVICES; VEGETATION INDEX; MANGROVE FORESTS; PANAY ISLAND; RATES; SEQUESTRATION; RESILIENCE; STOCKS; STATE; COST;
D O I
10.3389/ffgc.2021.775341
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Opportunities to boost climate change mitigation and adaptation (CCMA) and sustainable conservation financing may lie in enhancing blue carbon sequestration, particularly in developing nations where coastal ecosystems are extensive and international carbon markets offer comparatively attractive payments for environmental stewardship. While blue carbon is receiving increased global attention, few credit-generating projects are operational, due to low credit-buyer incentives with uncertainty in creditable emissions reductions and high project costs. Little empirical guidance exists for practitioners to quantify return-on-investment (ROI) and viability of potential projects, particularly for rehabilitation where multiple implementation options exist with diverse associated costs. We map and model drivers of mangrove natural regeneration (NR) using remote sensing (high-resolution satellite imagery segmentation and time-series modeling), and subsequent carbon sequestration using field- and literature-derived data, across abandoned aquaculture ponds in the Philippines. Using project-specific cost data, we then assess ROI for a hypothetical rehabilitation-focused mangrove blue carbon project at a 9.68 ha abandoned pond over a 10-year timeframe, under varied rehabilitation scenarios [NR vs. assisted natural regeneration (ANR) with planting], potential emissions reduction accreditation methodologies, carbon prices and discount rates. NR was faster in lower-lying ponds with lower tidal exposure (greater pond dike retention). Forecasted carbon sequestration was 3.7- to 5.2-fold and areal "greenbelt" regeneration 2.5- to 3.4-fold greater in our case study under ANR than NR. Variability in modeled sequestration rates drove high uncertainty and credit deductions in NR strategies. ROI with biomass-only accreditation was low and negative under NR and ANR, respectively. ROI was greater under ANR with inclusion of biomass and autochthonous soil carbon; however, neither strategy was highly profitable at current voluntary market carbon prices. ANR was the only scenario that fulfilled coastal protection greenbelt potential, with full mangrove cover within 10 years. Our findings highlight the benefits of ANR and soils inclusion in rehabilitation-oriented blue carbon projects, to maximize carbon sequestration and greenbelt enhancement (thus enhance pricing with potential bundled credits), and minimize forecasting uncertainty and credit-buyers' perceived risk. An ANR rehabilitation strategy in low-lying, sea-facing abandoned ponds with low biophysical intervention costs may represent large blue carbon CCMA opportunities in regions with high aquaculture abandonment.
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页数:18
相关论文
共 88 条
  • [1] SLIC Superpixels Compared to State-of-the-Art Superpixel Methods
    Achanta, Radhakrishna
    Shaji, Appu
    Smith, Kevin
    Lucchi, Aurelien
    Fua, Pascal
    Suesstrunk, Sabine
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 34 (11) : 2274 - 2281
  • [2] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION
    AKAIKE, H
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) : 716 - 723
  • [3] [Anonymous], 2021, Markets in Motion: State of the Voluntary Carbon Markets, Installment 1
  • [4] Mangrove diversity enhances plant biomass production and carbon storage in Hainan island, China
    Bai, Jiankun
    Meng, Yuchen
    Gou, Ruikun
    Lyu, Jiacheng
    Dai, Zheng
    Diao, Xiaoping
    Zhang, Hongsheng
    Luo, Yiqi
    Zhu, Xiaoshan
    Lin, Guanghui
    [J]. FUNCTIONAL ECOLOGY, 2021, 35 (03) : 774 - 786
  • [5] Windows of opportunity: thresholds to mangrove seedling establishment on tidal flats
    Balke, Thorsten
    Bouma, Tjeerd J.
    Horstman, Erik M.
    Webb, Edward L.
    Erftemeijer, Paul L. A.
    Herman, Peter M. J.
    [J]. MARINE ECOLOGY PROGRESS SERIES, 2011, 440 : 1 - 9
  • [6] Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping
    Baloloy, Alvin B.
    Blanco, Ariel C.
    Ana, Raymund Rhommel C. Sta
    Nadaoka, Kazuo
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2020, 166 : 95 - 117
  • [7] The cost and feasibility of marine coastal restoration
    Bayraktarov, Elisa
    Saunders, Megan I.
    Abdullah, Sabah
    Mills, Morena
    Beher, Jutta
    Possingham, Hugh P.
    Mumby, Peter J.
    Lovelock, Catherine E.
    [J]. ECOLOGICAL APPLICATIONS, 2016, 26 (04) : 1055 - 1074
  • [8] Beeston M., 2020, Blue Carbon: Mind the Gap.
  • [9] Bivand R., 2019, RGEOSINTERFACE GEOME
  • [10] Blue Ventures, 2019, TAH HONK COMM MANGR