What can we learn from amino acids about oceanic organic matter cycling and degradation?

Abstract

Abstract. Amino acids (AAs) mainly bound in proteins are major constituents of living biomass and non-living organic material in the oceanic particulate and dissolved organic matter pool. Uptake and cycling by heterotrophic organisms lead to characteristic changes in AA composition so that AA-based biogeochemical indicators are often used to elucidate processes of organic matter cycling and degradation. We analyzed particulate AA in a large sample set collected in various oceanic regions covering sinking and suspended particles in the water column, sediment samples, and dissolved AA from water column and pore water samples. The aim of this study was to test and improve the use of AA-derived biogeochemical indicators as proxies for organic matter sources and degradation and to better understand particle dynamics and interaction between the dissolved and particulate organic matter pools. A principal component analysis (PCA) of all data delineates diverging AA compositions of sinking and suspended particles with increasing water depth. A new sinking particle and sediment degradation indicator (SDI) allows a fine-tuned classification of sinking particles and sediments with respect to the intensity of degradation, which is associated with changes of stable isotopic ratios of nitrogen (δ15N). This new indicator is furthermore sensitive to sedimentary redox conditions and can be used to detect past anoxic early diagenesis. A second indicator emerges from the AA spectra of suspended particulate matter (SPM) in the epipelagic and that of the meso- and bathypelagic ocean and is a residence time indicator (RTI). The characteristic changes in AA patterns from shallow to deep SPM are recapitulated in the AA spectra of the dissolved organic matter (DOM) pool, so that deep SPM is more similar to DOM than to any of the other organic matter pools. This implies that there is equilibration between finely dispersed SPM and DOM in the deep sea, which may be driven by microbial activity combined with annealing and fragmentation of gels. As these processes strongly depend on physico-chemical conditions in the deep ocean, changes in quality and degradability of DOM may strongly affect the relatively large pool of suspended and dissolved AA in the ocean that amounts to 15 Pg amino acid carbon (AAC) and 89 ± 29 Pg AAC, respectively.

Burial of Organic Carbon in Swedish Fjord Sediments: Highlighting the Importance of Sediment Accumulation Rate in Relation to Fjord Redox Conditions

“…The Ox/Anox index is based on the reactivities of individual amino acids under oxic and anoxic conditions and is calculated with the following equation using molar % of each compound: $$$\frac{\text{Ox}}{\text{Anox}}=\frac{\text{Asp}+\text{Glu}+\text{BALA}+\text{GABA}+\text{Lys}}{\text{Ser}+\text{Met}+\text{Ile}+\text{Leu}+\text{Tyr}+\text{Phe}}$$$ where, Ox/Anox ratios ≥1.5 are indicative of degradation under oxic conditions and Ox/Anox ratios ≤1 are indicative of degradation under anoxic conditions (Menzel et al., 2013, 2015). While this ratio was initially applied to study redox in lacustrine systems, it has been used in numerous coastal studies (Gaye et al., 2022; Mai‐Thi et al., 2017).…”

“…where, Ox/Anox ratios ≥1.5 are indicative of degradation under oxic conditions and Ox/Anox ratios ≤1 are indicative of degradation under anoxic conditions (Menzel et al, 2013(Menzel et al, , 2015. While this ratio was initially applied to study redox in lacustrine systems, it has been used in numerous coastal studies (Gaye et al, 2022;Mai-Thi et al, 2017).…”

“…While amino acids are not source specific, they are useful to study OC degradation as they are relatively reactive (Cowie & Hedges, 1992a, 1992b, 1994; Dauwe & Middelburg, 1998). In particular, the amino acid degradation index along with non‐protein amino acids are widely used in coastal and estuarine systems as indices of lability and degradation (Dauwe et al., 1999; Gaye et al., 2022). For example, amino acids have been used to study changes in OC reactivity resulting from diagenetic processes in fjord water column and sediments (Alkhatib et al., 2012; Cowie et al., 1992; Haugen & Lichtentaler, 1991).…”

Metabolic alkalinity release from large port facilities (Hamburg, Germany) and impact on coastal carbon storage

“…The river discharge uncertainty was 5 % (Léonard et al, 2000) and was added to the error in the end. The analytical measurement precision of POC and PON was 0.05 % and 0.005 %, respectively (Gaye et al, 2022), calculated from the average box 1 values. We calculated the analytical errors with the following equation per parameter and box:…”

Metabolic alkalinity release from large port facilities (Hamburg, Germany) and impact on coastal carbon storage

“…The river discharge uncertainty was 5 % (Léonard et al, 2000) and was added to the error in the end. The analytical measurement precision of POC and PON was 0.05 % and 0.005 %, respectively (Gaye et al, 2022), calculated from the average box 1 values. The analytical errors were calculated with the following equation per parameter and box:…”