Detection and mapping of Posidonia oceanica dead matte by high-resolution acoustic imaging

Adaptive stacked species distribution modelling: Novel approaches to large scale quantification of blue carbon to support marine management

This study introduces a novel concept of 'Adaptively Stacked' Species Distribution Models (AS-SDMs) to predict blue carbon habitat distribution, abundance, carbon stocks, and carbon sequestration potential in Orkney. AS-SDMs are built from Weighted Boosted Regression Trees (WBRTs) that adaptively stack blue carbon sediment thickness, sediment carbon content, and sequestration potential to predicted abundance. A novel method to describe substrate types by relative inputs of mud, sand, and gravel is detailed that better characterises the determining factors of seagrass, maerl, and horse mussel abundance. This study also introduces a novel use of indexes to mitigate double counting issues of mixed species distribution models. Seagrass, maerl, horse mussel, and mixed seagrass and maerl (SGM) habitats are estimated to cover a maximum area of 657 km2 in Orkney, have a total sediment carbon stock of 16 Mt. C, and sequester 6000 t C yr-1. Applying a conservative threshold of 50 % abundance to habitat predictions, six key potential areas of blue carbon offset projects are identified. These areas cover just over 9 km2, have a total carbon stock of 330,000 t C, and sequester 330 t C yr-1. When applied to UK carbon credit value, assuming integration with voluntary markets and compliance with accreditation criteria, the habitats in these areas have a potential value of £24.5 million. If applied as annual values, these areas have carbon stocks with a potential value of £0.93 million yr-1 and a carbon sequestration potential value of £24,000 yr-1.

A multi-approach inventory of the blue carbon stocks of Posidonia oceanica seagrass meadows: Large scale application in Calvi Bay (Corsica, NW Mediterranean)

In Mediterranean, Posidonia oceanica develops a belowground complex structure ('matte') able to store large amounts of carbon over thousands of years. The inventory of blue carbon stocks requires the coupling of mapping techniques and in situ sediment sampling to assess the size and the variability of these stocks. This study aims to quantify the organic (C_org) and inorganic (C_inorg) carbon stocks in the P. oceanica matte of the Calvi Bay (Corsica) using sub-bottom profiler imagery and biogeochemical analysis of sediment cores. The matte thicknesses map (average ± SD: 2.2 m ± 0.4 m) coupled with marine benthic habitat cartography allows to estimate matte volume at 12 473 352 m³. The cumulative stocks were assessed at 20.2-50.3 kg C_org m^-2 and 26.6-58.7 kg C_inorg m^-2 within the first meter of depth on matte (3632 ± 486 cal yr BP). The data contributed to estimate the overall carbon stocks at 389 994 t C_org and 615 558 t C_inorg, offering a new insight of the heterogeneity of blue carbon stocks in seagrass meadows. Variability of carbon storage capacity of matte influenced by substrate is discussed.

Sizing the carbon sink associated with Posidonia oceanica seagrass meadows using very high-resolution seismic reflection imaging

Among blue carbon ecosystems, seagrass meadows have been highlighted for their contribution to the ocean carbon cycle and climate change mitigation derived from their capacity to store large amounts of carbon over long periods of time in their sediments. Most of the available estimates of carbon stocks beneath seagrass meadows are based on the analysis of short sediment cores in very limited numbers. In this study, high-resolution seismic reflection techniques were applied to obtain an accurate estimate of the potential size of the organic deposit underlying the meadows of the Mediterranean seagrass Posidonia oceanica (known as 'matte'). Seismic profiles were collected over 1380 km of the eastern continental shelf of Corsica (France, Mediterranean Sea) to perform a large-scale inventory of the carbon stock stored in sediments. The seismic data were ground-truthed by sampling sediment cores and using calibrated seismo-acoustic surveys. The data interpolation map highlighted a strong spatial heterogeneity of the matte thickness. The height of the matte at the site was estimated at 251.9 cm, being maximum in shallow waters (10-20 m depth), near river mouths and lagoon outlets, where the thickness reached up to 867 cm. Radiocarbon dates revealed the presence of seagrass meadows since the mid-Holocene (7000-9000 cal yr BP). Through the top meter of soil, the matte age was estimated at 1656 ± 528 cal yr BP. The accretion rate showed a high variability resulting from the interplay of multiple factors. Based on the surface area occupied by the meadows, the average matte thickness underneath them and the carbon content, the matte volume and total C_org stock were estimated at 403.5 ± 49.4 million m³ and 15.6 ± 2.2 million t C_org, respectively. These results confirm the need for the application of large-scale methods to estimate the size of the carbon sink associated with seagrass meadows worldwide.

Performance Assessment of Posidonia oceanica (L.) Delile Restoration Experiment on Dead matte Twelve Years after Planting—Structural and Functional Meadow Features

Following the restoration of natural conditions by reducing human pressures, reforestation is currently considered a possible option to accelerate the recovery of seagrass habitats. Long-term monitoring programs theoretically represent an ideal solution to assess whether a reforestation plan has produced the desired results. Here, we report on the performance of a 20 m2 patch of Posidonia oceanica transplanted on dead matte twelve years after transplantation in the Gulf of Palermo, northwestern Sicily. Photo mosaic performed in the area allowed us to detect 23 transplanted patches of both regular and irregular shape, ranging from 0.1 to 2.7 m2 and an overall surface close to 19 m2. Meadow density was 331.6 ± 17.7 shoot m−2 (currently five times higher than the initial value of 66 shoots m−2), and it did not show statistical differences from a close by natural meadow (331.2 ± 14.9). Total primary production, estimated by lepidochronology, varied from 333.0 to 332.7 g dw m2/year, at the transplanted and natural stand, respectively. These results suggest that complete restoration of P. oceanica on dead matte is possible in a relatively short time (a decade), thus representing a good starting point for upscaling the recovery of the degraded meadows in the area.

Seismic interval velocity in the matte of Posidonia oceanica meadows: Towards a non-destructive approach for large-scale assessment of blue carbon stock

High-resolution seismic reflection data have been used over the last decades to estimate the thickness of the long-term Blue Carbon sink associated to the below-ground sediment deposit (matte) of the Posidonia oceanica meadows. Time-to-depth conversion of these geophysical datasets was usually performed assuming a sound velocity in this structure, but appropriate seismic interval velocity measurements is necessary to achieve accurate calibration. This study describes the first methodology to estimate the seismic interval velocity in the matte. This approach performed on the eastern continental shelf of Corsica island (France, NW Mediterranean) is based on measurements of the vertical matte profile from high-resolution seismic reflection profiles (s TWTT) and from seafloor morpho-bathymetric DTM (multibeam echosounders - MBES and Light Detection and Ranging - LiDAR surveys) calibrated with ground-truthing data. A biogeosedimentological analysis of horizontal cores sampled in vertical matte escarpments has been undertaken to identify the potential relationship of sediment and environmental parameters with sound velocity. The cross-comparison and the data intercalibration show significant correlation of MBES (R² = 0.872) and LiDAR datasets (R² = 0.883) with direct underwater measurements. Seismic interval velocities (n = 367) have been found to range between 1631.9 and 1696.8 m s^-1 (95% confidence interval) and are estimated on average at 1664.4 m s^-1, which is similar to the literature for unconsolidated marine sediments. The prediction map provided by the ordinary kriging method emphasized, however, a high variability of sound velocity within the study area. The results showed that changes in sound velocity in the matte are positively and strongly correlated with sand and gravel content and environmental factors such as distance to coastal river mouths and coastline. However, it was found that a negative relationship linked sound velocity with total and coarse organic content of matte deposits.

Assessing Fine-Scale Distribution and Volume of Mediterranean Algal Reefs through Terrain Analysis of Multibeam Bathymetric Data. A Case Study in the Southern Adriatic Continental Shelf

In the Mediterranean Sea, crustose coralline algae form endemic algal reefs known as Coralligenous (C) build-ups. The high degree of complexity that C can reach through time creates notable environmental heterogeneity making C a major hotspot of biodiversity for the Mediterranean basin. C build-up can variably modify the submarine environment by affecting the evolution of submerged landforms, although its role is still far from being systematically defined. Our work proposes a new, ad-hoc semi-automated, GIS-based methodology to map the distribution of C build-ups in shallow coastal waters using high-resolution bathymetric data, collected on a sector of the southern Apulian continental shelf (Southern Adriatic Sea, Italy). Our results quantitatively define the 3D distribution of C in terms of area and volume, estimating more than 103,000 build-ups, covering an area of roughly 305,200 m2, for a total volume of 315,700 m3. Our work firstly combines acoustic survey techniques and geomorphometric analysis to develop innovative approaches for eco-geomorphological studies. The obtained results can contribute to a better definition of the ocean carbon budget, and to the monitoring of local anthropogenic impacts (e.g., bottom trawling damage) and global changes, like ocean warming and acidification. These can affect the structural complexity and total volume of carbonate deposits characterizing the Mediterranean benthic environment.

Quantifying and modelling the carbon sequestration capacity of seagrass meadows--a critical assessment

Seagrasses are among the planet's most effective natural ecosystems for sequestering (capturing and storing) carbon (C); but if degraded, they could leak stored C into the atmosphere and accelerate global warming. Quantifying and modelling the C sequestration capacity is therefore critical for successfully managing seagrass ecosystems to maintain their substantial abatement potential. At present, there is no mechanism to support carbon financing linked to seagrass. For seagrasses to be recognised by the IPCC and the voluntary C market, standard stock assessment methodologies and inventories of seagrass C stocks are required. Developing accurate C budgets for seagrass meadows is indeed complex; we discuss these complexities, and, in addition, we review techniques and methodologies that will aid development of C budgets. We also consider a simple process-based data assimilation model for predicting how seagrasses will respond to future change, accompanied by a practical list of research priorities.