Providing a framework for seagrass mapping in United States coastal ecosystems using high spatial resolution satellite imagery.

Seagrasses have been widely recognized for their ecosystem services, but traditional seagrass monitoring approaches emphasizing ground and aerial observations are costly, time-consuming, and lack standardization across datasets. This study leveraged satellite imagery from Maxar's WorldView-2 and WorldView-3 high spatial resolution, commercial satellite platforms to provide a consistent classification approach for monitoring seagrass at eleven study areas across the continental United States, representing geographically, ecologically, and climatically diverse regions. A single satellite image was selected at each of the eleven study areas to correspond temporally to reference data representing seagrass coverage and was classified into four general classes: land, seagrass, no seagrass, and no data. Satellite-derived seagrass coverage was then compared to reference data using either balanced agreement, the Mann-Whitney U test, or the Kruskal-Wallis test, depending on the format of the reference data used for comparison. Balanced agreement ranged from 58% to 86%, with better agreement between reference- and satellite-indicated seagrass absence (specificity ranged from 88% to 100%) than between reference- and satellite-indicated seagrass presence (sensitivity ranged from 17% to 73%). Results of the Mann-Whitney U and Kruskal-Wallis tests demonstrated that satellite-indicated seagrass percentage cover had moderate to large correlations with reference-indicated seagrass percentage cover, indicative of moderate to strong agreement between datasets. Satellite classification performed best in areas of dense, continuous seagrass compared to areas of sparse, discontinuous seagrass and provided a suitable spatial representation of seagrass distribution within each study area. This study demonstrates that the same methods can be applied across scenes spanning varying seagrass bioregions, atmospheric conditions, and optical water types, which is a significant step toward developing a consistent, operational approach for mapping seagrass coverage at the national and global scales. Accompanying this manuscript are instructional videos describing the processing workflow, including data acquisition, data processing, and satellite image classification. These instructional videos may serve as a management tool to complement field- and aerial-based mapping efforts for monitoring seagrass ecosystems.

Impact of Atmospheric Correction on Classification and Quantification of Seagrass Density from WorldView-2 Imagery.

Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors' retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGCseagrass) estimates. This study assessed atmospheric correction's impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (LW), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line height (ELH) and dark-object subtraction (DOS) methods were used for atmospheric correction. DOS left residual brightness in the blue and green bands but had minimal impact on the seagrass classification accuracy. However, the brighter reflectance values reduced LAI retrievals by up to 50% compared to ELH-corrected images and ground-based observations. This study offers a potential correction for LAI underestimation due to incomplete atmospheric correction, enhancing the retrieval of seagrass density and above-ground Blue Carbon from WorldView-2 imagery without in situ observations for accurate atmospheric interference correction.

Photorespiration in eelgrass (Zostera marina L.): A photoprotection mechanism for survival in a CO2-limited world.

Photorespiration, commonly viewed as a loss in photosynthetic productivity of C3 plants, is expected to decline with increasing atmospheric CO2, even though photorespiration plays an important role in the oxidative stress responses. This study aimed to quantify the role of photorespiration and alternative photoprotection mechanisms in Zostera marina L. (eelgrass), a carbon-limited marine C3 plant, in response to ocean acidification. Plants were grown in controlled outdoor aquaria at different [CO2]aq ranging from ~55 (ambient) to ~2121 µM for 13 months and compared for differences in leaf photochemistry by simultaneous measurements of O2 flux and variable fluorescence. At ambient [CO2], photosynthesis was carbon limited and the excess photon absorption was diverted both to photorespiration and non-photochemical quenching (NPQ). The dynamic range of NPQ regulation in ambient grown plants, in response to instantaneous changes in [CO2]aq, suggested considerable tolerance for fluctuating environmental conditions. However, 60 to 80% of maximum photosynthetic capacity of ambient plants was diverted to photorespiration resulting in limited carbon fixation. The photosynthesis to respiration ratio (P E : R D) of ambient grown plants increased 6-fold when measured under high CO2 because photorespiration was virtually suppressed. Plants acclimated to high CO2 maintained 4-fold higher P E : R D than ambient grown plants as a result of a 60% reduction in photorespiration. The O2 production efficiency per unit chlorophyll was not affected by the CO2 environment in which the plants were grown. Yet, CO2 enrichment decreased the light level to initiate NPQ activity and downregulated the biomass specific pigment content by 50% and area specific pigment content by 30%. Thus, phenotypic acclimation to ocean carbonation in eelgrass, indicating the coupling between the regulation of photosynthetic structure and metabolic carbon demands, involved the downregulation of light harvesting by the photosynthetic apparatus, a reduction in the role of photorespiration and an increase in the role of NPQ in photoprotection. The quasi-mechanistic model developed in this study permits integration of photosynthetic and morphological acclimation to ocean carbonation into seagrass productivity models, by adjusting the limits of the photosynthetic parameters based on substrate availability and physiological capacity.

The influence of particle concentration and bulk characteristics on polarized oceanographic lidar measurements.

Oceanographic lidar measurements of the linear depolarization ratio, δ, contain information on the bulk characteristics of marine particles that could improve our ability to study ocean biogeochemistry. However, a scarcity of information on the polarized light-scattering properties of marine particles and the lack of a framework for separating single and multiple scattering effects on δ have hindered the development of polarization-based retrievals of bulk particle properties. To address these knowledge gaps, we made single scattering measurements of δ for several compositionally and morphologically distinct marine particle assemblages. We then used a bio-optical model to explore the influence of multiple scattering and particle characteristics on lidar measurements of δ made during an expedition to sample a mesoscale coccolithophore bloom. Laboratory measurements of linear depolarization revealed a complex dependency on particle shape, size, and composition that were consistent with scattering simulations for idealized nonspherical particles. Model results suggested that the variability in δ measured during the field expedition was driven predominantly by shifts in particle concentration rather than their bulk characteristics. However, model estimates of δ improved when calcite particles were represented by a distinct particle class, highlighting the influence of bulk particle properties on δ. To advance polarized lidar retrievals of bulk particle properties and to constrain the uncertainty in satellite lidar retrievals of particulate backscattering, these results point to the need for future efforts to characterize the variability of particulate depolarization in the ocean and to quantify the sensitivity of operational ocean lidar systems to multiple scattering.

Simulated response of St. Joseph Bay, Florida, seagrass meadows and their belowground carbon to anthropogenic and climate impacts.

Seagrass meadows are degraded globally and continue to decline in areal extent due to human pressures and climate change. This study used the bio-optical model GrassLight to explore the impact of climate change and anthropogenic stressors on seagrass extent, leaf area index (LAI) and belowground organic carbon (BGC) in St. Joseph Bay, Florida, using water quality data and remotely-sensed sea surface temperature (SST) from 2002 to 2020. Model predictions were compared with satellite-derived measurements of seagrass extent and shoot density from the Landsat images for the same period. The GrassLight-derived area of potential seagrass habitat ranged from 36.2 km2 to 39.2 km2, averaging 38.0 ± 0.8 km2 compared to an observed seagrass extent of 23.0 ± 3.0 km2 derived from Landsat (range = 17.9-27.4 km2). GrassLight predicted a mean seagrass LAI of 2.7 m2 leaf m-2 seabed, compared to a mean LAI of 1.9 m2 m-2 estimated from Landsat, indicating that seagrass density in St. Joseph Bay may have been below its light-limited ecological potential. Climate and anthropogenic change simulations using GrassLight predicted the impact of changes in temperature, pH, chlorophyll a, chromophoric dissolved organic matter and turbidity on seagrass meadows. Simulations predicted a 2-8% decline in seagrass extent with rising temperatures that was offset by a 3-11% expansion in seagrass extent in response to ocean acidification when compared to present conditions. Simulations of water quality impacts showed that a doubling of turbidity would reduce seagrass extent by 18% and total leaf area by 21%. Combining climate and water quality scenarios showed that ocean acidification may increase seagrass productivity to offset the negative effects of both thermal stress and declining water quality on the seagrasses growing in St. Joseph Bay. This research highlights the importance of considering multiple limiting factors in understanding the effects of environmental change on seagrass ecosystems.

Vertical artifacts in high-resolution WorldView-2 and WorldView-3 satellite imagery of aquatic systems.

Satellite image artefacts are features that appear in an image but not in the original imaged object and can negatively impact the interpretation of satellite data. Vertical artefacts are linear features oriented in the along-track direction of an image system and can present as either banding or striping; banding are features with a consistent width, and striping are features with inconsistent widths. This study used high-resolution data from DigitalGlobe's (now Maxar) WorldView-3 satellite collected at Lake Okeechobee, Florida (FL), on 30 August 2017. This study investigated the impact of vertical artefacts on both at-sensor radiance and a spectral index for an aquatic target as WorldView-3 was primarily designed as a land sensor. At-sensor radiance measured by six of WorldView-3's eight spectral bands exhibited banding, more specifically referred to as non-uniformity, at a width corresponding to the multispectral detector sub-arrays that comprise the WorldView-3 focal plane. At-sensor radiance measured by the remaining two spectral bands, red and near-infrared (NIR) #1, exhibited striping. Striping in these spectral bands can be attributed to their time delay integration (TDI) settings at the time of image acquisition, which were optimized for land. The impact of vertical striping on a spectral index leveraging the red, red edge, and NIR spectral bands-referred to here as the NIR maximum chlorophyll index (MCINIR)-was investigated. Temporally similar imagery from the European Space Agency's Sentinel-3 and Sentinel-2 satellites were used as baseline references of expected chlorophyll values across Lake Okeechobee as neither Sentinel-3 nor Sentinel-2 imagery showed striping. Striping was highly prominent in the MCINIR product generated using WorldView-3 imagery, as noise in the at-sensor radiance exceeded any signal of chlorophyll in the image. Adjusting the image acquisition parameters for future tasking of WorldView-3 or the functionally similar WorldView-2 satellite may alleviate these artefacts. To test this, an additional WorldView-3 image was acquired at Lake Okeechobee, FL, on 26 May 2021 in which the TDI settings and scan line rate were adjusted to improve the signal-to-noise ratio. While some evidence of non-uniformity remained, striping was no longer noticeable in the MCINIR product. Future image tasking over aquatic targets should employ these updated image acquisition parameters. Since the red and NIR #1 spectral bands are critical for inland and coastal water applications, archived images not collected using these updated settings may be limited in their potential for analysis of aquatic variables that require these two spectral bands to derive.

Temporal Stability of Seagrass Extent, Leaf Area, and Carbon Storage in St. Joseph Bay, Florida: a Semi-automated Remote Sensing Analysis.

Seagrasses are globally recognized for their contribution to blue carbon sequestration. However, accurate quantification of their carbon storage capacity remains uncertain due, in part, to an incomplete inventory of global seagrass extent and assessment of its temporal variability. Furthermore, seagrasses are undergoing significant decline globally, which highlights the urgent need to develop change detection techniques applicable to both the scale of loss and the spatial complexity of coastal environments. This study applied a deep learning algorithmto a 30-year time series of Landsat 5 through 8 imagery to quantify seagrass extent, leaf area index (LAI), and belowground organic carbon (BGC) in St. Joseph Bay, Florida, between 1990 and 2020. Consistent with previous field-based observations regarding stability of seagrass extent throughout St. Joseph Bay, there was no temporal trend in seagrass extent (23 ± 3 km2, τ = 0.09, p = 0.59, n = 31), LAI (1.6 ± 0.2, τ = -0.13, p = 0.42, n = 31), or BGC (165 ± 19 g C m-2, τ = - 0.01, p = 0.1, n = 31) over the 30-year study period. There were, however, six brief declines in seagrass extent between the years 2004 and 2019 following tropical cyclones, from which seagrasses recovered rapidly. Fine-scale interannual variability in seagrass extent, LAI, and BGC was unrelated to sea surface temperature or to climate variability associated with the El Niño-Southern Oscillation or the North Atlantic Oscillation. Although our temporal assessment showed that seagrass and its belowground carbon were stable in St. Joseph Bay from 1990 to 2020, forecasts suggest that environmental and climate pressures are ongoing, which highlights the importance of the method and time series presented here as a valuable tool to quantify decadal-scale variability in seagrass dynamics. Perhaps more importantly, our results can serve as a baseline against which we can monitor future change in seagrass communities and their blue carbon.

Polarized lidar and ocean particles: insights from a mesoscale coccolithophore bloom.

Oceanographic lidar can provide remote estimates of the vertical distribution of suspended particles in natural waters, potentially revolutionizing our ability to characterize marine ecosystems and properly represent them in models of upper ocean biogeochemistry. However, lidar signals exhibit complex dependencies on water column inherent optical properties (IOPs) and instrument characteristics, which complicate efforts to derive meaningful biogeochemical properties from lidar return signals. In this study, we used a ship-based system to measure the lidar attenuation coefficient (α) and linear depolarization ratio (δ) across a variety of optically and biogeochemically distinct water masses, including turbid coastal waters, clear oligotrophic waters, and calcite rich waters associated with a mesoscale coccolithophore bloom. Sea surface IOPs were measured continuously while underway to characterize the response of α and δ to changes in particle abundance and composition. The magnitude of α was consistent with the diffuse attenuation coefficient (Kd), though the α versus Kd relationship was nonlinear. δ was positively related to the scattering optical depth and the calcite fraction of backscattering. A statistical fit to these data suggests that the polarized scattering properties of calcified particles are distinct and contribute to measurable differences in the lidar depolarization ratio. A better understanding of the polarized scattering properties of coccolithophores and other marine particles will further our ability to interpret polarized oceanographic lidar measurements and may lead to new techniques for measuring the material properties of marine particles remotely.

Metabolic Profiling Reveals Biochemical Pathways Responsible for Eelgrass Response to Elevated CO2 and Temperature.

As CO2 levels in Earth's atmosphere and oceans steadily rise, varying organismal responses may produce ecological losers and winners. Increased ocean CO2 can enhance seagrass productivity and thermal tolerance, providing some compensation for climate warming. However, the metabolic shifts driving the positive response to elevated CO2 by these important ecosystem engineers remain unknown. We analyzed whole-plant performance and metabolic profiles of two geographically distinct eelgrass (Zostera marina L.) populations in response to CO2 enrichment. In addition to enhancing overall plant size, growth and survival, CO2 enrichment increased the abundance of Calvin Cycle and nitrogen assimilation metabolites while suppressing the abundance of stress-related metabolites. Overall metabolome differences between populations suggest that some eelgrass phenotypes may be better suited than others to cope with an increasingly hot and sour sea. Our results suggest that seagrass populations will respond variably, but overall positively, to increasing CO2 concentrations, generating negative feedbacks to climate change.

Ebullition of oxygen from seagrasses under supersaturated conditions.

Gas ebullition from aquatic systems to the atmosphere represents a potentially important fraction of primary production that goes unquantified by measurements of dissolved gas concentrations. Although gas ebullition from photosynthetic surfaces has often been observed, it is rarely quantified. The resulting underestimation of photosynthetic activity may significantly bias the determination of ecosystem trophic status and estimated rates of biogeochemical cycling from in situ measures of dissolved oxygen. Here, we quantified gas ebullition rates in Zostera marina meadows in Virginia, U.S.A. using simple funnel traps and analyzed the oxygen concentration and isotopic composition of the captured gas. Maximum hourly rates of oxygen ebullition (3.0 mmol oxygen m-2 h-1) were observed during the coincidence of high irradiance and low tides, particularly in the afternoon when oxygen and temperature maxima occurred. The daily ebullition fluxes (up to 11 mmol oxygen m-2 d-1) were roughly equivalent to net primary production rates determined from dissolved oxygen measurements indicating that bubble ebullition can represent a major component of primary production that is not commonly included in ecosystem-scale estimates. Oxygen content comprised 20-40% of the captured bubble gas volume and correlated negatively with its δ18O values, consistent with a predominance of mixing between the higher δ18O of atmospheric oxygen in equilibrium with seawater and the lower δ18O of oxygen derived from photosynthesis. Thus, future studies interested in the metabolism of highly productive, shallow water ecosystems, and particularly those measuring in situ oxygen flux, should not ignore the bubble formation and ebullition processes described here.

Performance across WorldView-2 and RapidEye for reproducible seagrass mapping.

Satellite remote sensing offers an effective remedy to challenges in ground-based and aerial mapping that have previously impeded quantitative assessments of global seagrass extent. Commercial satellite platforms offer fine spatial resolution, an important consideration in patchy seagrass ecosystems. Currently, no consistent protocol exists for image processing of commercial data, limiting reproducibility and comparison across space and time. Additionally, the radiometric performance of commercial satellite sensors has not been assessed against the dark and variable targets characteristic of coastal waters. This study compared data products derived from two commercial satellites: DigitalGlobe's WorldView-2 and Planet's RapidEye. A single scene from each platform was obtained at St. Joseph Bay in Florida, USA, corresponding to a November 2010 field campaign. A reproducible processing regime was developed to transform imagery from basic products, as delivered from each company, into analysis-ready data usable for various scientific applications. Satellite-derived surface reflectances were compared against field measurements. WorldView-2 imagery exhibited high disagreement in the coastal blue and blue spectral bands, chronically overpredicting. RapidEye exhibited better agreement than WorldView-2, but overpredicted slightly across all spectral bands. A deep convolutional neural network was used to classify imagery into deep water, land, submerged sand, seagrass, and intertidal classes. Classification results were compared to seagrass maps derived from photointerpreted aerial imagery. This study offers the first radiometric assessment of WorldView-2 and RapidEye over a coastal system, revealing inherent calibration issues in shorter wavelengths of WorldView-2. Both platforms demonstrated as much as 97% agreement with aerial estimates, despite differing resolutions. Thus, calibration issues in WorldView-2 did not appear to interfere with classification accuracy, but could be problematic if estimating biomass. The image processing routine developed here offers a reproducible workflow for WorldView-2 and RapidEye imagery, which was tested in two additional coastal systems. This approach may become platform independent as more sensors become available.

Adaptive signatures in thermal performance of the temperate coral Astrangia poculata.

Variation in environmental characteristics and divergent selection pressures can drive adaptive differentiation across a species' range. Astrangia poculata is a temperate scleractinian coral that provides unique opportunities to understand the roles of phenotypic plasticity and evolutionary adaptation in coral physiological tolerance limits. This species inhabits hard-bottom ecosystems from the northwestern Atlantic to the Gulf of Mexico and withstands an annual temperature range of up to 20°C. Additionally, A. poculata is facultatively symbiotic and co-occurs in both symbiotic ('brown') and aposymbiotic ('white') states. Here, brown and white A. poculata were collected from Virginia (VA) and Rhode Island (RI), USA, and exposed to heat (18-32°C) and cold (18-6°C) stress, during which respiration of the coral host along with photosynthesis and photochemical efficiency (Fv/Fm) of Breviolum psygmophilum photosymbionts were measured. Thermal performance curves (TPCs) of respiration revealed a pattern of countergradient variation with RI corals exhibiting higher respiration rates overall, and specifically at 6, 15, 18, 22 and 26°C. Additionally, thermal optimum (Topt) analyses show a 3.8°C (brown) and 6.9°C (white) higher Topt in the VA population, corresponding to the warmer in situ thermal environment in VA. In contrast to respiration, no origin effect was detected in photosynthesis rates or Fv/Fm, suggesting a possible host-only signature of adaptation. This study is the first to consider A. poculata's response to both heat and cold stress across symbiotic states and geography, and provides insight into the potential evolutionary mechanisms behind the success of this species along the East Coast of the USA.

Expected limits on the ocean acidification buffering potential of a temperate seagrass meadow.

Ocean acidification threatens many marine organisms, especially marine calcifiers. The only global-scale solution to ocean acidification remains rapid reduction in CO2 emissions. Nevertheless, interest in localized mitigation strategies has grown rapidly because of the recognized threat ocean acidification imposes on natural communities, including ones important to humans. Protection of seagrass meadows has been considered as a possible approach for localized mitigation of ocean acidification due to their large standing stocks of organic carbon and high productivity. Yet much work remains to constrain the magnitudes and timescales of potential buffering effects from seagrasses. We developed a biogeochemical box model to better understand the potential for a temperate seagrass meadow to locally mitigate the effects of ocean acidification. Then we parameterized the model using data from Tomales Bay, an inlet on the coast of California, USA which supports a major oyster farming industry. We conducted a series of month-long model simulations to characterize processes that occur during summer and winter. We found that average pH in the seagrass meadows was typically within 0.04 units of the pH of the primary source waters into the meadow, although we did find occasional periods (hours) when seagrass metabolism may modify the pH by up to ±0.2 units. Tidal phasing relative to the diel cycle modulates localized pH buffering within the seagrass meadow such that maximum buffering occurs during periods of the year with midday low tides. Our model results suggest that seagrass metabolism in Tomales Bay would not provide long-term ocean acidification mitigation. However, we emphasize that our model results may not hold in meadows where assumptions about depth-averaged net production and seawater residence time within the seagrass meadow differ from our model assumptions. Our modeling approach provides a framework that is easily adaptable to other seagrass meadows in order to evaluate the extent of their individual buffering capacities. Regardless of their ability to buffer ocean acidification, seagrass meadows maintain many critically important ecosystem goods and services that will be increasingly important as humans increasingly affect coastal ecosystems.

Net primary production, growth, and standing crop of Macrocystis pyrifera in Southern California.

Marine macroalgae are believed to be among the most productive autotrophs in the world. However, relatively little information exists about spatial and temporal variation in net primary production (NPP) by these organisms. The data presented here are being collected to investigate patterns and causes of variation in NPP by the giant kelp, Macrocystis pyrifera, which is believed to be one of the fastest growing autotrophs on earth. The standing crop and loss rates of M. pyrifera have been measured monthly in permanent plots at three sites in the Santa Barbara Channel, USA. Collection of these data began in June 2002 and is ongoing. Seasonal estimates of NPP and growth rate are made by combining the field data with a model of kelp dynamics. The purpose of this Data Paper is to make available a time series of M. pyrifera NPP, growth, and standing crop that is appropriate for examining seasonal and interannual patterns across multiple sites. Data on plant density in each plot and censuses of fronds on tagged plants at each site are also made available here. NPP, mass-specific growth rate, and standing crop are presented in four different metrics (wet mass, dry mass, carbon mass, and nitrogen mass) to facilitate comparisons with previous studies of M. pyrifera and with NPP measured in other ecosystems. Analyses of these data reveal seasonal cycles in growth and standing crop as well as substantial differences in M. pyrifera NPP among sites and years.

Top-down impact through a bottom-up mechanism: the effect of limpet grazing on growth, productivity and carbon allocation of Zostera marina L. (eelgrass).

The unusual appearance of a commensal eelgrass limpet [Tectura depicta (Berry)] from southern California at high density (up to 10 shoot-1) has coincided with the catastrophic decline of a subtidal Zostera marina L. meadow in Monterey Bay, California. Some commensal limpets graze the chloroplast-rich epidermis of eelgrass leaves, but were not known to affect seagrass growth or productivity. We evaluated the effect on eelgrass productivity of grazing by limpets maintained at natural densities (8±2 shoot-1) in a natural light mesocosm for 45 days. Growth rates, carbon reserves, root proliferation and net photosynthesis of grazed plants were 50-80% below those of ungrazed plants, but biomass-specific respiration was unaffected. The daily period of irradiance-saturated photosynthesis (H sat) needed to maintain positive carbon balance in grazed plants approached 13.5 h, compared with 5-6 h for ungrazed plants. The amount of carbon allocated to roots of ungrazed plants was 800% higher than for grazed plants. By grazing the chlorophyll-rich epidermis, T. depicta induced carbon limitation in eelgrass growing in an other-wise light-replete environment. Continued northward movement of T. depicta, may have significant impacts on eelgrass production and population dynamics in the northeast Pacific, even thought this limpet consumes very little plant biomass. This interaction is a dramatic example of top-down control (grazing/predation) of eelgrass productivity and survival operating via a bottom-up mechanism (photosynthesis limitation).