Phytoplankton biomass and productivity have been continuously monitored from ocean color satellites for over a decade. Yet, the most widely used empirical approach for estimating chlorophyll a (Chl) ...from satellites can be in error by a factor of 5 or more. Such variability is due to differences in absorption and backscattering properties of phytoplankton and related concentrations of colored-dissolved organic matter (CDOM) and minerals. The empirical algorithms have built-in assumptions that follow the basic precept of biological oceanography —namely, oligotrophic regions with low phytoplankton biomass are populated with small phytoplankton, whereas more productive regions contain larger bloom-forming phytoplankton. With a changing world ocean, phytoplankton composition may shift in response to altered environmental forcing, and CDOM and mineral concentrations may become uncoupled from phytoplankton stocks, creating further uncertainty and error in the empirical approaches. Hence, caution is warranted when using empirically derived Chl to infer climate-related changes in ocean biology. The Southern Ocean is already experiencing climatic shifts and shows substantial errors in satellite-derived Chl for different phytoplankton assemblages. Accurate global assessments of phytoplankton will require improved technology and modeling, enhanced field observations, and ongoing validation of our "eyes in space."
The abundance and distribution of plastic debris in natural waters is largely unknown due to limited comprehensive monitoring. Here, optical properties of dry and wet marine-harvested plastic debris ...were quantified to explore the feasibility of plastic debris optical remote sensing in the natural environment. We measured the spectral reflectance of microplastics (<5mm) from the North Atlantic Ocean, macroplastics (>5mm) washed ashore along the USA west coast and virgin plastic pellets over a wavelength range from 350 to 2500nm. Compared to the spectral variability of multi-colored dry macroplastics, the measured dry marine-harvested microplastic reflectance spectra could be represented as a single bulk average spectrum with notable absorption features at ~931, 1215, 1417 and 1732nm. The wet marine-harvested microplastics had similar spectral features to the dry microplastics but the magnitude was lower over the measured spectrum. When spectrally matched to the reference library of typical dry virgin pellets, the mean dry marine-harvested microplastics reflectance had moderate similarities to low-density polyethylene, polyethylene terephthalate, polypropylene and polymethyl methacrylate. This composition was consistent with the subset sampled with the Fourier Transform Infrared (FTIR) spectrometer and what has been reported globally. The absorption features at 1215 and 1732nm were observable through an intervening atmosphere and used to map the distributions of synthetic hydrocarbons at a landfill and on man-made structures from airborne visible-infrared imaging spectrometer (AVIRIS) imagery, indicating the potential to remotely sense dry washed ashore and land-origin plastics. These same absorption features were identifiable on wet marine-harvested microplastics, but the ability to conduct remote sensing of microplastics at the ocean surface layer will require more detailed radiative transfer analysis and development of high signal-to-noise sensors. The spectral measurements presented here provide a foundation for such advances towards remote detection of plastics from various platforms.
•Measure reflectance of marine plastic debris from the visible to shortwave infrared•Establish a mean spectral signal for marine-harvested microplastics•Classify marine plastics using a spectral library of pure virgin pellets•Explore airborne remote sensing of synthetic hydrocarbons
Here, we present a proof-of-concept on remote sensing of ocean plastics using airborne shortwave infrared (SWIR) imagery. We captured red, green, and blue (RGB) and hyperspectral SWIR imagery with ...equipment mounted on a C-130 aircraft surveying the “Great Pacific Garbage Patch” at a height of 400 m and a speed of 140 knots. We recorded the position, size, color, and type (container, float, ghost net, rope, and unknown) of every plastic piece identified in the RGB mosaics. We then selected the top 30 largest items within each of our plastic type categories (0.6–6.8 m in length) to investigate SWIR spectral information obtained with a SASI-600 imager (950–2450 nm). Our analyses revealed unique SWIR spectral features common to plastics. The SWIR spectra obtained (N = 118 items) were quite similar both in magnitude and shape. Nonetheless, some spectral variability was observed, likely influenced by differences in the object optical properties, the level of water submersion, and an intervening atmosphere. Our simulations confirmed that the ∼1215 and ∼1732 nm absorption features have potential applications in detecting ocean plastics from spectral information. We explored the potential of SWIR remote sensing technology for detecting and quantifying ocean plastics, thus provide relevant information to those developing better monitoring solutions for ocean plastic pollution.
Seagrass meadows are important environments for the blue carbon budget and are potential early indicators for environmental change. Remote sensing is a viable monitoring tool for spatially extensive ...meadows but most current approaches are limited by the requirement for in situ calibration data or provide categorical level maps rather than quantitative estimates of direct physiological significance. In this paper we present a method for mapping water depth and the leaf area index (LAI, ratio of leaf area to substrate area) of Thalassia testudinum meadows, based on radiative transfer model inversion using an embedded three-dimensional aquatic canopy model. Variations in reflectance due to leaf length, leaf position, sediment coverage on leaves, water depth and solar zenith angle were included in the model to parameterise uncertainty propagation. The model revealed canopy reflectance as a function of LAI decreases exponentially at all wavelengths up to an LAI around four, beyond which increasing canopy density cannot be determined from reflectance. In addition, sediment coverage on leaves has surprisingly little effect on the reflectance of sparse canopies because shading is also a contributor to darkening.
The capability of the method for image based mapping was assessed through sensitivity analyses and by application to hyperspectral airborne imagery of Florida Bay collected by the Portable Remote Imaging Spectrometer (PRISM), with the uncertainty propagation providing per-pixel confidence intervals on all the estimated parameters. Results were consistent across the sensitivity and image analyses and the agreement with field data was good, given the challenges in validation of submerged pixels at metre scale. Uncertainties were high for LAIs greater than two in water of depth 8m, but lower for sparse canopies and shallower water. For water depths approaching 10m the pixel-to-pixel variation arising from processes at the water surface upwards was greater than the uncertainties arising from the canopy or water column.
The physics-based model inversion approach is readily adaptable to any sensor configuration and to different seagrass species and canopy morphologies. No site-specific in situ data is required and the uncertainty estimates can provide an objective basis for interpreting apparent changes in the distribution of seagrasses over time and space, as revealed by remote sensing techniques.
•A model inversion method for mapping seagrass leaf area index is proposed.•The method requires no in situ data and provides per-pixel uncertainty estimates.•LAI, depth and IOPs were accurately quantified from hyperspectral imagery.•Canopies with leaf area index above four cannot be discriminated by remote sensing.
Ocean acidification, caused by elevated seawater carbon dioxide levels, may have a deleterious impact on energetic processes in animals. Here we show that high PCO(2) can suppress metabolism, ...measured as oxygen consumption, in the pteropod, L. helicina forma antarctica, by ∼20%. The rates measured at 180-380 µatm (MO(2) = 1.25 M(-0.25), p = 0.007) were significantly higher (ANCOVA, p = 0.004) than those measured at elevated target CO(2) levels in 2007 (789-1000 µatm, = 0.78 M(-0.32), p = 0.0008; Fig. 1). However, we further demonstrate metabolic plasticity in response to regional phytoplankton concentration and that the response to CO(2) is dependent on the baseline level of metabolism. We hypothesize that reduced regional Chl a levels in 2008 suppressed metabolism and masked the effect of ocean acidification. This effect of food limitation was not, we postulate, merely a result of gut clearance and specific dynamic action, but rather represents a sustained metabolic response to regional conditions. Thus, pteropod populations may be compromised by climate change, both directly via CO(2)-induced metabolic suppression, and indirectly via quantitative and qualitative changes to the phytoplankton community. Without the context provided by long-term observations (four seasons) and a multi-faceted laboratory analysis of the parameters affecting energetics, the complex response of polar pteropods to ocean acidification may be masked or misinterpreted.
Standard ocean color chlorophyll algorithms, including normalized fluorescence line height algorithms, overestimate summer blooms and often miss large winter blooms in mid-latitude estuaries such as ...Long Island Sound (LIS). Thus, they are unable to accurately determine year-round chlorophyll concentrations. Here, we show that winter phytoplankton blooms cannot be retrieved using MODIS' 667 and 678 nm bands. Although MERIS' equivalent 665 and 681 nm bands are able to better characterize chlorophyll a concentrations at LIS compared to MODIS, we show that it is a red band difference (RBD) algorithm relying on observing the maximum spectral difference between Rrs681nm-Rrs665nm and Rrs709nm-Rrs665nm from the MERIS sensor that is able to successfully capture the seasonal chlorophyll dynamics measured in situ. Such switching algorithms are useful in areas where the shape of the reflectance spectrum changes throughout the seasons associated with changes in the phytoplankton community structure, and provide seamless implementation compared to algorithms based on seasonal tunings. We apply the switching RBD algorithm to the 10 years of available MERIS data, and results reveal important spatial and temporal patterns that cannot be assessed from in situ data alone. These include the observation that the decreasing trend in surface chlorophyll concentrations between 2002 and 2012 is localized, and may be related to changes in the flow of Atlantic waters into the estuary rather than a result of active management against eutrophication. Following from past studies, we demonstrate how high sensitivity red bands are valuable to successfully determine proxies for phytoplankton biomass in coastal areas where optical properties are dominated by dissolved organic matter, and where the fluorescence peak may not accurately capture the dynamics of productive waters. Such switching RBD algorithms applied to data from the Sentinel or PACE missions may allow distribution of near-real time chlorophyll a products for coastal waters across winter and summer seasons.
•MODIS red bands have low sensitivity to detect winter Chl in a midlatitude estuary.•A switching RBD Chl algorithm using MERIS revealed winter and summer blooms.•Climatology retrievals provide effective model validation in complex estuaries.•Future sensors should include sensitive bands in red and near infrared wavelengths.•Decadal analysis of Chl imagery reveal spatial trends useful in coastal management.
Determining the authorship of scientific manuscripts is no easy task in today's world of large co-investigator, interdisciplinary research. The question of first authorship isn't always so ...contentious, but determining who else should be listed as an author is a recurrent challenge. To warrant authorship, an individual must play a substantive role in at least 2 out of 3 of the following tasks: ideas, data and analysis, and writing.
Mats of the pelagic macroalgae Sargassum represent a complex environment for the study of marine camouflage at the air-sea interface. Endemic organisms have convergently evolved similar colors and ...patterns, but quantitative assessments of camouflage strategies are lacking. Here, spectral camouflage of two crab species (Portunus sayi and Planes minutus) was assessed using hyperspectral imagery (HSI). Crabs matched Sargassum reflectance across blue and green wavelengths (400-550 nm) and diverged at longer wavelengths. Maximum discrepancy was observed in the far-red (i.e., 675 nm) where Chlorophyll a absorption occurred in Sargassum and not the crabs. In a quantum catch color model, both crabs showed effective color matching against blue/green sensitive dichromat fish, but were still discernible to tetrachromat bird predators that have visual sensitivity to far red wavelengths. The two species showed opposing trends in background matching with relation to body size. Variation in model parameters revealed that discrimination of crab and background was impacted by distance from the predator, and the ratio of cone cell types for bird predators. This is one of the first studies to detail background color matching in this unique, challenging ecosystem at the air-sea interface.
Current operational approaches to ocean color remote sensing tend to be least accurate in coastal regions with waters rich in terrigenous material. Semi-analytical models can be used to retrieve the ...absorption and backscattering properties of dissolved and suspended materials unique to these environments, and subsequently biogeochemical parameters such as total suspended material (TSM) and chlorophyll (Chl). In this study, optical data collected over several years are used to select and optimize a semi-analytical ocean color algorithm for the dynamic and optically complex Long Island Sound estuary. The most successful algorithm requires a red reflectance channel between 600 and 650nm, which is not included in many current ocean color sensors, but is essential in highly scattering waters. Regional optimization including the use of a dynamic, spectrally variable f/Q, a value related to the bidirectional reflectance distribution function (BRDF), results in an approximately five-fold decrease in retrieval bias in highly backscattering, sediment-laden waters near river outflows. Retrievals of dissolved and particulate spectral absorption, backscattering, dissolved and detrital absorption coefficients and total suspended matter obtained from the optimized algorithm agree well with field observations (r2≥0.90). These parameters are useful for assessing riverine discharge, mixing and residence times of surface waters, as well as assessing the turbidity and light penetration in this estuary. Estimation of Chl remains challenging (r2=0.59) due to the stepwise nature of the algorithm and the relatively high proportion of dissolved and non-algal constituents masking phytoplankton absorption (generally<20% of total absorption at 440nm). Moreover, diverse phytoplankton assemblages throughout the region create variability between spectral absorption and chlorophyll and highlight the benefits of increased spectral resolution of ocean color satellites going forward.
► Optimized algorithm significantly improves IOP and Chl retrievals. ► Reference band between 600 and 650nm critical to algorithm retrievals in turbid waters. ► Spectrally varying f/Q significantly improves algorithm retrievals. ► Chl retrievals hindered by step-wise nature of algorithm and plankton diversity.
Combating the imminent environmental problems associated with plastic litter
requires a synergy of monitoring strategies, clean-up efforts, policymaking
and interdisciplinary scientific research. ...Lately, remote sensing
technologies have been evolving into a complementary monitoring strategy
that might have future applications in the operational detection and
tracking of plastic litter at repeated intervals covering wide geospatial
areas. We therefore present a dataset of Lambertian-equivalent spectral
reflectance measurements from the ultraviolet (UV, 350 nm) to shortwave
infrared (SWIR, 2500 nm) of synthetic hydrocarbons (plastics). Spectral
reflectance of wet and dry marine-harvested, washed-ashore, and virgin
plastics was measured outdoors with a hyperspectral spectroradiometer.
Samples were harvested from the major accumulation zones in the Atlantic and
Pacific oceans, suggesting a near representation of plastic litter in global
oceans. We determined a representative bulk average spectral reflectance for
the dry marine-harvested microplastics dataset available at https://doi.org/10.21232/jyxq-1m66 (Garaba and Dierssen,
2019c). Similar absorption features were identified in the dry samples of
washed-ashore plastics: dataset available at https://doi.org/10.21232/ex5j-0z25 (Garaba and Dierssen,
2019a). The virgin pellets samples consisted of 11 polymer types
typically found in floating aquatic plastic litter: dataset available at
https://doi.org/10.21232/C27H34 (Garaba and
Dierssen, 2017). Magnitude and shape features of the spectral reflectance
collected were also evaluated for two scenarios involving dry and wet
marine-harvested microplastics: dataset available at https://doi.org/10.21232/r7gg-yv83 (Garaba and Dierssen,
2019b). Reflectance of wet marine-harvested microplastics was noted to be
lower in magnitude but had similar spectral shape to that of dry
marine-harvested microplastics. Diagnostic absorption features common in the
marine-harvested microplastics and washed-ashore plastics were identified at
∼931, 1215, 1417 and 1732 nm. In addition, we include metrics
for a subset of the marine-harvested microplastics related to particle
morphology, including sphericity and roundness. These datasets are also
expected to improve and expand the scientific evidence-based knowledge of
optical characteristics of common plastics found in aquatic litter.
Furthermore, these datasets have potential use in radiative transfer
simulations exploring the effects of plastics on ocean colour remote sensing
and developing algorithms applicable to remote detection of floating plastic
litter.
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