Modeling Organic Carbon Accumulation Rates and Residence Times in Coastal Vegetated Ecosystems

Abstract

Coastal vegetated "blue carbon" ecosystems can store large quantities of organic carbon (OC) within their soils; however, the importance of these sinks for climate change mitigation depends on the OC accumulation rate (CAR) and residence time. Here we evaluate how two modeling approaches, a Bayesian age-depth model alone or in combination with a two-pool OC model, aid in our understanding of the time lines of OC within seagrass soils. Fitting these models to data from Posidonia oceanica soil cores, we show that age-depth models provided reasonable CAR estimates but resulted in a 22% higher estimation of OC burial rates when ephemeral rhizosphere OC was not subtracted. This illustrates the need to standardize CAR estimation to match the research target and time frames under consideration. Using a two-pool model in tandem with an age-depth model also yielded reasonable, albeit lower, CAR estimates with lower estimate uncertainty, which increased our ability to detect among-site differences and seascape-level trends. Moreover, the two-pool model provided several other useful soil OC diagnostics, including OC inputs, decay rates, and transit times. At our sites, soil OC decayed quite slowly both within fast cycling (0.028 ± 0.014 yr −1 ) and slow cycling (0.0007 ± 0.0003 yr −1 ) soil pools, resulting in OC taking between 146 and 825 yr to transit the soil system. Further, an estimated 85% to 93% of OC inputs enter slow-cycling soil pools, with transit times ranging from 891 to 3,115 yr, substantiating the importance of P. oceanica soils as natural, long-term OC sinks.

The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy

“…These represent 48,870 depth increments, and 126,629 individual measurements, from 64 countries (Figures 3 and 4). Overall there were 305 studies represented in the database, related to 299 bibliographic entities (Abbott, Elsey‐Quirk, & DeLaune, 2019; Abbott, Quirk, & Delaune, 2019; Abed‐Navandi & Dworschak, 2005; Abino et al., 2014; Adame et al., 2013, 2015; Agawin et al., 1996; Ajonina et al., 2014; Allen et al., 2007, 2021, 2022; Alongi, 1996; Alongi et al., 1999, 2001, 2004, 2005; Alongi, Tirendi, Clough, 2000; Alongi, Tirendi, Trott, et al., 2000; Alongi, Trott, Rachmansyah, et al., 2008; Alongi, Trott, Undu, et al., 2008; Al‐rousan et al., 2005; Amon & Herndl, 1991; Andreetta et al., 2014, 2016; Arias‐Ortiz, Masqué, et al., 2021; Arias‐Ortiz, Oikawa, et al., 2021; Arriola & Cable, 2017; Ashton & Macintosh, 2002; Banerjee et al., 2012; Barrón et al., 2004; Baustian, Stagg, Perry, Moss, & Carruthers, 2021; Baustian, Stagg, Perry, Moss, Carruthers, et al., 2021; Belshe et al., 2019a, 2019b; Bernhardt et al., 2018; Borg et al., 2010; Boschker et al., 2000; Bouillon et al., 2003; Boyd, 2012; Boyd et al., 2017, 2019; Boyd & Sommerfield, 2016; Breithaupt et al., 2014, 2017, 2019, 2020; Brunskill et al., 2002, 2004; Buffington et al., 2020; Bukoski et al., 2017; Bulmer et al., 2016; Burden et al.,…”

Exploring controls of timber stock residence times in storage after severe storm events

“…The enterprises have different forest areas. According to Backhaus et al (2016), cases involving larger sampling areas contribute more heavily to the regression function than cases involving smaller sampling areas. Consequently, we use the underlying sampling areas to weight the cases of the sample.…”

“…We thus utilize an approach for systems characterized by a single input pulse and continuous output signals originating from chemical sciences: residence time distributions of chemical reactors as described by Danckwerts (1953) and also Levenspiel (1972). The Gamma distribution is a commonly used distribution to quantify residence time dynamics in environmental systems such as wetlands (e.g., Kadlec 1994) and groundwater aquifers (e.g., Maloszewski and Zuber 1982;Gilmore et al 2016) or carbon storage in ecosystems (e.g., Belshe et al 2019;Oberle et al 2019).…”

Do global change variables alter mangrove decomposition? A systematic review

“…A systematic assessment of the factors driving mangrove litter decomposition, which includes roots, leaves, and wood, is necessary to better characterize how blue C storage will be modified as ecosystems are altered by global change. Further, decomposition rates are often used in models to calculate C storage (Belshe et al, 2019; Dai et al, 2018) and better parameterization of the modelled potential of blue C requires an improved quantification of mangrove litter decomposition.…”

“…Further, decomposition rates are often used in models to calculate C storage (Belshe et al, 2019;Dai et al, 2018) (Contreras et al, 2017;Yang et al, 2018) given our inclusion criteria. Therefore, we investigated the relationships between decay rate and proxies of global change (i.e., latitude, season, nutrient loading and inundation level) through a systematic review approach using data that could be extracted from relevant research papers.…”