Carbon Removal Using Coastal Blue Carbon Ecosystems Is Uncertain and Unreliable, With Questionable Climatic Cost-Effectiveness

Mangrove forests, seagrass meadows and tidal saltmarshes are vegetated coastal ecosystems that accumulate and store large quantities of carbon in their sediments. Many recent studies and reviews have favorably identified the potential for such coastal “blue carbon” ecosystems to provide a natural climate solution in two ways: by conservation, reducing the greenhouse gas emissions arising from the loss and degradation of such habitats, and by restoration, to increase carbon dioxide drawdown and its long-term storage. The focus here is on the latter, assessing the feasibility of achieving quantified and secure carbon removal (negative emissions) through the restoration of coastal vegetation. Seven issues that affect the reliability of carbon accounting for this approach are considered: high variability in carbon burial rates; errors in determining carbon burial rates; lateral carbon transport; fluxes of methane and nitrous oxide; carbonate formation and dissolution; vulnerability to future climate change; and vulnerability to non-climatic factors. Information on restoration costs is also reviewed, with the conclusion that costs are highly uncertain, with lower-range estimates unrealistic for wider application. CO2 removal using coastal blue carbon restoration therefore has questionable cost-effectiveness when considered only as a climate mitigation action, either for carbon-offsetting or for inclusion in Nationally Determined Contributions. Many important issues relating to the measurement of carbon fluxes and storage have yet to be resolved, affecting certification and resulting in potential over-crediting. The restoration of coastal blue carbon ecosystems is nevertheless highly advantageous for climate adaptation, coastal protection, food provision and biodiversity conservation. Such action can therefore be societally justified in very many circumstances, based on the multiple benefits that such habitats provide at the local scale

S.O.S. « océan en détresse »

Il y a une quinzaine d’années encore, l’absorption de 30 % du dioxyde de carbone rejeté dans l’atmosphère par les activités humaines était considérée comme bénéfique car limitant la concentration de CO2 dans l’atmosphère. C’était sans prendre en compte les conséquences de cette absorption sur la chimie de l’océan et sur les organismes et les écosystèmes marins. Les océanographes tirent à présent la sonnette d’alarme

Changes in freshwater bacterial community composition during measurements of microbial and community respiration

The respiration rates of a pelagic community and of its microbial fraction (< 1.2 μm) were measured at two depths in the oxic layer of a meromictic alpine lake (Cadagno, Switzerland) using the oxygen technique. The duration of the incubations were 12, 24 and 55 h. Bacterioplankton abundance (DAPI counts) and composition (whole cell hybridization using 11 group-specific rRNA-targeted oligonucleotide probes) were measured during the incubations. Respiration generally increased with time, especially in the microbial fraction, or remained similar. This result was not always consistent with changes in bacterial abundance and cell volume. The composition of the community also changed during the incubations. The abundance of β-Proteobacteria increased during the course of all the experiments. These results extend the previous conclusions drawn in marine environments to fresh waters and demonstrate that, in addition to changes in bacterial abundance, cell volume and biomass, changes in the taxonomic composition of the bacterial community can occur during discrete incubations of freshwater planktonic communitie

Closure threat to key museum research facility

As leading representatives of the environmental and Earth science communities, we are gravely concerned about the proposed closure of the micropalaeontology research group at London's Natural History Museum ( see http://go.nature.com/KCppCe)

Ocean acidification reshapes the otolith-body allometry of growth in juvenile seabream

International audienceThe effects of elevated CO2 partial pressure (pCO2) on otolith calcification and on the coupling between the somatic and otolith growth were investigated in juvenile gilthead seabream Sparus aurata. Six-month old individuals were raised during seven weeks under four pCO2 conditions set according to projected future ocean acidification scenarios. Body and otolith biometric parameters were measured throughout the experiment along with the otolith biomineralization monitored using a radiotracer technique based on 45Ca incorporation. Seabream exhibited somatic growth resilience to all treatments. In contrast, increased growth rate and shape complexity of otoliths were observed with a pHT drop from 8.1 to 7.5. Hypercalcification was observed under lowered pH, with a rate of calcium incorporation increasing by up to 18% between pHT 8.1 and pHT 7.7. This work highlighted an uncoupling of otolith and body growth of juvenile seabream within 40 d at pHT 7.9 projected to be reached by the end of the century. As the otolith is an essential tool used in reconstructing fish life history, this work suggests that information resulting from otolith studies should be interpreted with caution with respect to the potential impacts that ocean acidification projected modifications could have on otolith biomineralization

Early life stages of a Mediterranean coral are vulnerable to ocean warming and acidification

The ability of coral populations to recover from disturbance depends on larval dispersion and recruitment. While ocean warming and acidification effects on adult corals are well documented, information on early life stages is comparatively scarce. Here, we investigate whether ocean warming and acidification can affect the larval and juvenile development of the Mediterranean azooxanthellate coral Astroides calycularis. Larvae and juveniles were raised for 9 months at ambient (23 &deg;C) and warm (26 &deg;C) temperatures and ambient (8.0) and low pH (7.7, on the total scale). The timing of the larvae metamorphosis, growth of the juvenile polyp, and skeletal characteristics of the 9-month-old polyps were monitored. Settlement and metamorphosis were more successful and hastened under a warm temperature. In contrast, low pH delayed the metamorphosis and affected growth of the recruits by reducing the calcified area of attachment to the substrate, as well as by diminishing the skeleton volume and the number of septa. However, skeleton density was higher under low pH and ambient temperature. The warm temperature and low pH treatment had a negative impact on the survival, settlement, and growth of recruits. This study provides evidence of the threat that represents ocean warming and acidification for the larval recruitment and the growth of recruits of A. calycularis.</p

The potential for ocean-based climate action: negative emissions technologies and beyond

The effectiveness, feasibility, duration of effects, co-benefits, disbenefits, cost effectiveness and governability of four ocean-based negative emissions technologies (NETs) are assessed in comparison to eight other ocean-based measures. Their role in revising UNFCCC Parties' future Nationally Determined Contributions is discussed in the broad context of ocean-based actions for both mitigation and ecological adaptation. All measures are clustered in three policy-relevant categories (Decisive, Low Regret, Concept Stage). None of the ocean-based NETs assessed are identified as Decisive at this stage. One is Low Regret (Restoring and increasing coastal vegetation), and three are at Concept Stage, one with low to moderate potential disbenefits (Marine bioenergy with carbon capture and storage) and two with potentially high disbenefits (Enhancing open-ocean productivity and Enhancing weathering and alkalinization). Ocean-based NETs are uncertain but potentially highly effective. They have high priority for research and development

An Alternative to Static Climatologies: Robust Estimation of Open Ocean CO2 Variables and Nutrient Concentrations From T, S, and O2 Data Using Bayesian Neural Networks

This work presents two new methods to estimate oceanic alkalinity (AT), dissolved inorganic carbon (CT), pH, and pCO2 from temperature, salinity, oxygen, and geolocation data. “CANYON-B” is a Bayesian neural network mapping that accurately reproduces GLODAPv2 bottle data and the biogeochemical relations contained therein. “CONTENT” combines and refines the four carbonate system variables to be consistent with carbonate chemistry. Both methods come with a robust uncertainty estimate that incorporates information from the local conditions. They are validated against independent GO-SHIP bottle and sensor data, and compare favorably to other state-of-the-art mapping methods. As “dynamic climatologies” they show comparable performance to classical climatologies on large scales but a much better representation on smaller scales (40–120 d, 500–1,500 km) compared to in situ data. The limits of these mappings are explored with pCO2 estimation in surface waters, i.e., at the edge of the domain with high intrinsic variability. In highly productive areas, there is a tendency for pCO2 overestimation due to decoupling of the O2 and C cycles by air-sea gas exchange, but global surface pCO2 estimates are unbiased compared to a monthly climatology. CANYON-B and CONTENT are highly useful as transfer functions between components of the ocean observing system (GO-SHIP repeat hydrography, BGC-Argo, underway observations) and permit the synergistic use of these highly complementary systems, both in spatial/temporal coverage and number of observations. Through easily and robotically-accessible observations they allow densification of more difficult-to-observe variables (e.g., 15 times denser AT and CT compared to direct measurements). At the same time, they give access to the complete carbonate system. This potential is demonstrated by an observation-based global analysis of the Revelle buffer factor, which shows a significant, high latitude-intensified increase between +0.1 and +0.4 units per decade. This shows the utility that such transfer functions with realistic uncertainty estimates provide to ocean biogeochemistry and global climate change research. In addition, CANYON-B provides robust and accurate estimates of nitrate, phosphate, and silicate. Matlab and R code are available at https://github.com/HCBScienceProducts/

Estimates of Water-Column Nutrient Concentrations and Carbonate System Parameters in the Global Ocean: A Novel Approach Based on Neural Networks

A neural network-based method (CANYON: CArbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network) was developed to estimate water-column (i.e., from surface to 8,000 m depth) biogeochemically relevant variables in the Global Ocean. These are the concentrations of three nutrients [nitrate (NO3−), phosphate (PO43−), and silicate (Si(OH)4)] and four carbonate system parameters [total alkalinity (AT), dissolved inorganic carbon (CT), pH (pHT), and partial pressure of CO2 (pCO2)], which are estimated from concurrent in situ measurements of temperature, salinity, hydrostatic pressure, and oxygen (O2) together with sampling latitude, longitude, and date. Seven neural-networks were developed using the GLODAPv2 database, which is largely representative of the diversity of open-ocean conditions, hence making CANYON potentially applicable to most oceanic environments. For each variable, CANYON was trained using 80 % randomly chosen data from the whole database (after eight 10° × 10° zones removed providing an “independent data-set” for additional validation), the remaining 20 % data were used for the neural-network test of validation. Overall, CANYON retrieved the variables with high accuracies (RMSE): 1.04 μmol kg−1 (NO3−), 0.074 μmol kg−1 (PO43−), 3.2 μmol kg−1 (Si(OH)4), 0.020 (pHT), 9 μmol kg−1 (AT), 11 μmol kg−1 (CT) and 7.6 % (pCO2) (30 μatm at 400 μatm). This was confirmed for the eight independent zones not included in the training process. CANYON was also applied to the Hawaiian Time Series site to produce a 22 years long simulated time series for the above seven variables. Comparison of modeled and measured data was also very satisfactory (RMSE in the order of magnitude of RMSE from validation test). CANYON is thus a promising method to derive distributions of key biogeochemical variables. It could be used for a variety of global and regional applications ranging from data quality control to the production of datasets of variables required for initialization and validation of biogeochemical models that are difficult to obtain. In particular, combining the increased coverage of the global Biogeochemical-Argo program, where O2 is one of the core variables now very accurately measured, with the CANYON approach offers the fascinating perspective of obtaining large-scale estimates of key biogeochemical variables with unprecedented spatial and temporal resolutions. The Matlab and R codes of the proposed algorithms are provided as Supplementary Material