Soil Carbon Stocks Vary Across Geomorphic Settings in Australian Temperate Tidal Marsh Ecosystems

Gorham, Connor; Lavery, Paul; Kelleway, Jeffrey J.; Salinas, Cristian; Serrano, Óscar

doi:10.1007/s10021-020-00520-9

Cited by 31 publications

(20 citation statements)

References 59 publications

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“…Soil C org stocks along the depth profile were estimated by multiplying the C org density by the slice thickness. Soil C org stocks in 30‐cm thick soil deposits were estimated as the sum of C org stock along the decompressed depth profile estimated using the compression factor, recorded during sampling by measuring the difference in surface soil elevation inside and outside the coring device (Gorham et al., 2021).…”

Section: Methodsmentioning

confidence: 99%

Factors Determining Seagrass Blue Carbon Across Bioregions and Geomorphologies

Mazarrasa

Lavery

Duarte

et al. 2021

Global Biogeochemical Cycles

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Seagrass meadows rank among the most significant organic carbon (Corg) sinks on earth. We examined the variability in seagrass soil Corg stocks and composition across Australia and identified the main drivers of variability, applying a spatially hierarchical approach that incorporates bioregions and geomorphic settings. Top 30 cm soil Corg stocks were similar across bioregions and geomorphic settings (min‐max: 20–26 Mg Corg ha−1), but meadows formed by large species (i.e., Amphibolis spp. and Posidonia spp.) showed higher stocks (24–29 Mg Corg ha−1) than those formed by smaller species (e.g., Halodule, Halophila, Ruppia, Zostera, Cymodocea, and Syringodium; 12–21 Mg Corg ha−1). In temperate coastal meadows dominated by large species, soil Corg stocks mainly derived from seagrass Corg (72 ± 2%), while allochthonous Corg dominated soil Corg stocks in meadows formed by small species in temperate and tropical estuarine meadows (64 ± 5%). In temperate coastal meadows, soil Corg stocks were enhanced by low hydrodynamic exposure associated with high mud and seagrass Corg contents. In temperate estuarine meadows, soil Corg stocks were enhanced by high contributions of seagrass Corg, low to moderate solar radiation, and low human pressure. In tropical estuarine meadows formed by small species, large soil Corg stocks were mainly associated with low hydrodynamic energy, low rainfall, and high solar radiation. These results showcase that bioregion and geomorphic setting are not necessarily good predictors of soil Corg stocks and that site‐specific estimates based on local environmental factors are needed for Blue Carbon projects and greenhouse gases accounting purposes.

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Section: Methodsmentioning

confidence: 99%

Factors Determining Seagrass Blue Carbon Across Bioregions and Geomorphologies

Mazarrasa

Lavery

Duarte

et al. 2021

Global Biogeochemical Cycles

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“…Tidal salt marshes store so‐called “blue carbon” (Nellemann et al., 2009) in high quantities relative to their land area (Chmura et al., 2003; Duarte et al., 2008, 2013) and could be used to mitigate climate change (Howard et al., 2017; IPCC, 2014; Macreadie et al., 2021; Serrano et al., 2019), but we are just beginning to understand C dynamics in these complex ecosystems. Most blue C studies focus on the distribution of C in the soil profile (Berthelin et al., 2022; Chmura et al., 2003; Gorham et al., 2021; Hinson et al., 2017; Spivak et al., 2019; Sun et al., 2019; J. Yu et al., 2014; Van De Broek et al., 2016) or vertical trace gas fluxes (Abdul‐Aziz et al., 2018; Capooci et al., 2019; Capooci & Vargas, 2022a; Diefenderfer et al., 2018; O’Connor et al., 2020; Tong et al., 2020; Vázquez‐Lule & Vargas, 2021; Wollenberg et al., 2018). Few studies focus on the lateral C flux, which is the inorganic and organic C imported and exported via tidal channels (Santos et al., 2021; Trifunovic et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Physiochemical Controls on the Horizontal Exchange of Blue Carbon Across the Salt Marsh‐Tidal Channel Interface

Fettrow,

Jeppi,

Wozniak

et al. 2023

JGR Biogeosciences

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Tidal channels are biogeochemical hotspots that horizontally exchange carbon (C) with marsh platforms, but the physiochemical drivers controlling these dynamics are poorly understood. We hypothesized that C‐bearing iron (Fe) oxides precipitate and immobilize dissolved organic carbon (DOC) during ebb tide as the soils oxygenate, and dissolve into the porewater during flood tide, promoting transport to the channel. The hydraulic gradient physically controls how these solutes are horizontally exchanged across the marsh platform‐tidal channel interface; we hypothesized that this gradient alters the concentration and source of C being exchanged. We further hypothesized that trace soil gases (i.e., CO2, CH4, dimethyl sulfide) are pushed out of the channel bank as the groundwater rises. To test these hypotheses, we measured porewater, surface water, and soil trace gases over two 24‐hr monitoring campaigns (i.e., summer and spring) in a mesohaline tidal marsh. We found that Fe2+ and DOC were positively related during flood tide but not during ebb tide in spring when soils were more oxidized. This finding shows evidence for the formation and dissolution of C‐bearing Fe oxides across a tidal cycle. In addition, the tidal channel contained significantly (p < 0.05) more terrestrial‐like DOC when the hydraulic gradient was driving flow toward the channel. In comparison, the channel water was saltier and contained significantly (p < 0.05) more marine‐like DOC when the hydraulic gradient reversed direction. Trace gas fluxes increased with rising groundwater levels, particularly dimethyl sulfide. These findings suggest multiple physiochemical mechanisms controlling the horizontal exchange of C at the marsh platform‐tidal channel interface.

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“…For example, Gholizadeh et al (2018) used 18 different satellite band indices to predict SOC in agricultural sites. Marsh morphology, floristic composition, and microclimate will likely vary from site to site (Gorham et al, 2021), therefore optimum covariates are likely to be marsh-specific (Guevara et al, 2018). Nevertheless, accurate SOC stock calculations can still be achieved when taking the weighted average of multiple regression models even when built on poorly correlated covariates.…”

Section: Discussionmentioning

confidence: 99%