Severino G. Salmo III, Sean Paul B. Manalo, Precious B. Jacob, Maria Elisa B. Gerona-Daga, Camila Frances P. Naputo, Mareah Wayne A. Maramag, Mohammad Basyuni, Frida Sidik, Richard MacKenzie
{"title":"利用本地化有机质-有机碳方程改进菲律宾红树林土壤碳估算","authors":"Severino G. Salmo III, Sean Paul B. Manalo, Precious B. Jacob, Maria Elisa B. Gerona-Daga, Camila Frances P. Naputo, Mareah Wayne A. Maramag, Mohammad Basyuni, Frida Sidik, Richard MacKenzie","doi":"10.1186/s13021-024-00276-y","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Southeast Asian (SEA) mangroves are globally recognized as blue carbon hotspots. Methodologies that measure mangrove soil carbon stock (SCS) are either accurate but costly (i.e., elemental analyzers), or economical but less accurate (i.e., loss-on-ignition [LOI]). Most SEA countries estimate SCS by measuring soil organic matter (OM) through the LOI method then converting it into organic carbon (OC) using a conventional conversion equation (%C<sub>org</sub> = 0.415 * % LOI + 2.89, R<sup>2</sup> = 0.59, n = 78) developed from Palau mangroves. The local site conditions in Palau does not reflect the wide range of environmental settings and disturbances in the Philippines. Consequently, the conventional conversion equation possibly compounds the inaccuracies of converting OM to OC causing over- or under-estimated SCS. Here, we generated a localized OM-OC conversion equation and tested its accuracy in computing SCS against the conventional equation. The localized equation was generated by plotting % OC (from elemental analyzer) against the % OM (from LOI). The study was conducted in different mangrove stands (natural, restored, and mangrove-recolonized fishponds) in Oriental Mindoro and Sorsogon, Philippines from the West and North Philippine Sea biogeographic regions, respectively. The OM:OC ratios were also statistically tested based on (a) stand types, (b) among natural stands, and (c) across different ages of the restored and recolonized stands. Increasing the accuracy of OM-OC conversion equations will improve SCS estimates that will yield reasonable C emission reduction targets for the country’s commitments on Nationally Determined Contributions (NDC) under the Paris Agreement.</p><h3>Results</h3><p>The localized conversion equation is %OC = 0.36 * % LOI + 2.40 (R<sup>2</sup> = 0.67; n = 458). The SOM:OC ratios showed significant differences based on stand types (<i>x</i><sup>2</sup> = 19.24; P = 6.63 × 10<sup>–05</sup>), among natural stands (F = 23.22; p = 1.17 × 10<sup>–08</sup>), and among ages of restored (F = 5.14; P = 0.03) and recolonized stands (F = 3.4; P = 0.02). SCS estimates using the localized (5%) and stand-specific equations (7%) were similar with the values derived from an elemental analyzer. In contrast, the conventional equation overestimates SCS by 20%.</p><h3>Conclusions</h3><p>The calculated SCS improves as the conversion equation becomes more reflective of localized site conditions. Both localized and stand-specific conversion equations yielded more accurate SCS compared to the conventional equation. While our study explored only two out of the six marine biogeographic regions in the Philippines, we proved that having a localized conversion equation leads to improved SCS measurements. Using our proposed equations will make more realistic SCS targets (and therefore GHG reductions) in designing mangrove restoration programs to achieve the country’s NDC commitments.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"19 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-024-00276-y","citationCount":"0","resultStr":"{\"title\":\"Improving soil carbon estimates of Philippine mangroves using localized organic matter to organic carbon equations\",\"authors\":\"Severino G. Salmo III, Sean Paul B. Manalo, Precious B. Jacob, Maria Elisa B. Gerona-Daga, Camila Frances P. Naputo, Mareah Wayne A. 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Here, we generated a localized OM-OC conversion equation and tested its accuracy in computing SCS against the conventional equation. The localized equation was generated by plotting % OC (from elemental analyzer) against the % OM (from LOI). The study was conducted in different mangrove stands (natural, restored, and mangrove-recolonized fishponds) in Oriental Mindoro and Sorsogon, Philippines from the West and North Philippine Sea biogeographic regions, respectively. The OM:OC ratios were also statistically tested based on (a) stand types, (b) among natural stands, and (c) across different ages of the restored and recolonized stands. Increasing the accuracy of OM-OC conversion equations will improve SCS estimates that will yield reasonable C emission reduction targets for the country’s commitments on Nationally Determined Contributions (NDC) under the Paris Agreement.</p><h3>Results</h3><p>The localized conversion equation is %OC = 0.36 * % LOI + 2.40 (R<sup>2</sup> = 0.67; n = 458). The SOM:OC ratios showed significant differences based on stand types (<i>x</i><sup>2</sup> = 19.24; P = 6.63 × 10<sup>–05</sup>), among natural stands (F = 23.22; p = 1.17 × 10<sup>–08</sup>), and among ages of restored (F = 5.14; P = 0.03) and recolonized stands (F = 3.4; P = 0.02). SCS estimates using the localized (5%) and stand-specific equations (7%) were similar with the values derived from an elemental analyzer. In contrast, the conventional equation overestimates SCS by 20%.</p><h3>Conclusions</h3><p>The calculated SCS improves as the conversion equation becomes more reflective of localized site conditions. Both localized and stand-specific conversion equations yielded more accurate SCS compared to the conventional equation. While our study explored only two out of the six marine biogeographic regions in the Philippines, we proved that having a localized conversion equation leads to improved SCS measurements. 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Improving soil carbon estimates of Philippine mangroves using localized organic matter to organic carbon equations
Background
Southeast Asian (SEA) mangroves are globally recognized as blue carbon hotspots. Methodologies that measure mangrove soil carbon stock (SCS) are either accurate but costly (i.e., elemental analyzers), or economical but less accurate (i.e., loss-on-ignition [LOI]). Most SEA countries estimate SCS by measuring soil organic matter (OM) through the LOI method then converting it into organic carbon (OC) using a conventional conversion equation (%Corg = 0.415 * % LOI + 2.89, R2 = 0.59, n = 78) developed from Palau mangroves. The local site conditions in Palau does not reflect the wide range of environmental settings and disturbances in the Philippines. Consequently, the conventional conversion equation possibly compounds the inaccuracies of converting OM to OC causing over- or under-estimated SCS. Here, we generated a localized OM-OC conversion equation and tested its accuracy in computing SCS against the conventional equation. The localized equation was generated by plotting % OC (from elemental analyzer) against the % OM (from LOI). The study was conducted in different mangrove stands (natural, restored, and mangrove-recolonized fishponds) in Oriental Mindoro and Sorsogon, Philippines from the West and North Philippine Sea biogeographic regions, respectively. The OM:OC ratios were also statistically tested based on (a) stand types, (b) among natural stands, and (c) across different ages of the restored and recolonized stands. Increasing the accuracy of OM-OC conversion equations will improve SCS estimates that will yield reasonable C emission reduction targets for the country’s commitments on Nationally Determined Contributions (NDC) under the Paris Agreement.
Results
The localized conversion equation is %OC = 0.36 * % LOI + 2.40 (R2 = 0.67; n = 458). The SOM:OC ratios showed significant differences based on stand types (x2 = 19.24; P = 6.63 × 10–05), among natural stands (F = 23.22; p = 1.17 × 10–08), and among ages of restored (F = 5.14; P = 0.03) and recolonized stands (F = 3.4; P = 0.02). SCS estimates using the localized (5%) and stand-specific equations (7%) were similar with the values derived from an elemental analyzer. In contrast, the conventional equation overestimates SCS by 20%.
Conclusions
The calculated SCS improves as the conversion equation becomes more reflective of localized site conditions. Both localized and stand-specific conversion equations yielded more accurate SCS compared to the conventional equation. While our study explored only two out of the six marine biogeographic regions in the Philippines, we proved that having a localized conversion equation leads to improved SCS measurements. Using our proposed equations will make more realistic SCS targets (and therefore GHG reductions) in designing mangrove restoration programs to achieve the country’s NDC commitments.
期刊介绍:
Carbon Balance and Management is an open access, peer-reviewed online journal that encompasses all aspects of research aimed at developing a comprehensive policy relevant to the understanding of the global carbon cycle.
The global carbon cycle involves important couplings between climate, atmospheric CO2 and the terrestrial and oceanic biospheres. The current transformation of the carbon cycle due to changes in climate and atmospheric composition is widely recognized as potentially dangerous for the biosphere and for the well-being of humankind, and therefore monitoring, understanding and predicting the evolution of the carbon cycle in the context of the whole biosphere (both terrestrial and marine) is a challenge to the scientific community.
This demands interdisciplinary research and new approaches for studying geographical and temporal distributions of carbon pools and fluxes, control and feedback mechanisms of the carbon-climate system, points of intervention and windows of opportunity for managing the carbon-climate-human system.
Carbon Balance and Management is a medium for researchers in the field to convey the results of their research across disciplinary boundaries. Through this dissemination of research, the journal aims to support the work of the Intergovernmental Panel for Climate Change (IPCC) and to provide governmental and non-governmental organizations with instantaneous access to continually emerging knowledge, including paradigm shifts and consensual views.