Quantifying pigment content in crustose coralline algae using hyperspectral imaging: A case study with Tethysphytum antarcticum (Ross Sea, Antarctica).

Crustose coralline algae (CCA) are a highly diverse group of habitat-forming, calcifying red macroalgae (Rhodophyta) with unique adaptations to diverse irradiance regimes. A distinctive CCA phenotype adaptation, which allows them to maximize photosynthetic performance in low light, is their content of a specific group of light-harvesting pigments called phycobilins. In this study, we assessed the potential of noninvasive hyperspectral imaging (HSI) in the visible spectrum (400-800 nm) to describe the phenotypic variability in phycobilin content of an Antarctic coralline, Tethysphytum antarcticum (Hapalidiales), from two distinct locations. We validated our measurements with pigment extractions and spectrophotometry analysis, in addition to DNA barcoding using the psbA marker. Targeted spectral indices were developed and correlated with phycobilin content using linear mixed models (R2 = 0.64-0.7). Once applied to the HSI, the models revealed the distinct phycoerythrin spatial distribution in the two site-specific CCA phenotypes, with thin and thick crusts, respectively. This study advances the capabilities of hyperspectral imaging as a tool to quantitatively study CCA pigmentation in relation to their phenotypic plasticity, which can be applied in laboratory studies and potentially in situ surveys using underwater hyperspectral imaging systems.

Life beneath the ice: jellyfish and ctenophores from the Ross Sea, Antarctica, with an image-based training set for machine learning.

BACKGROUND: Southern Ocean ecosystems are currently experiencing increased environmental changes and anthropogenic pressures, urging scientists to report on their biodiversity and biogeography. Two major taxonomically diverse and trophically important gelatinous zooplankton groups that have, however, stayed largely understudied until now are the cnidarian jellyfish and ctenophores. This data scarcity is predominantly due to many of these fragile, soft-bodied organisms being easily fragmented and/or destroyed with traditional net sampling methods. Progress in alternative survey methods including, for instance, optics-based methods is slowly starting to overcome these obstacles. As video annotation by human observers is both time-consuming and financially costly, machine-learning techniques should be developed for the analysis of in situ /in aqua image-based datasets. This requires taxonomically accurate training sets for correct species identification and the present paper is the first to provide such data. NEW INFORMATION: In this study, we twice conducted three week-long in situ optics-based surveys of jellyfish and ctenophores found under the ice in the McMurdo Sound, Antarctica. Our study constitutes the first optics-based survey of gelatinous zooplankton in the Ross Sea and the first study to use in situ / in aqua observations to describe taxonomic and some trophic and behavioural characteristics of gelatinous zooplankton from the Southern Ocean. Despite the small geographic and temporal scales of our study, we provided new undescribed morphological traits for all observed gelatinous zooplankton species (eight cnidarian and four ctenophore species). Three ctenophores and one leptomedusa likely represent undescribed species. Furthermore, along with the photography and videography, we prepared a Common Objects in Context (COCO) dataset, so that this study is the first to provide a taxonomist-ratified image training set for future machine-learning algorithm development concerning Southern Ocean gelatinous zooplankton species.

Rapid Manipulation in Irradiance Induces Oxidative Free-Radical Release in a Fast-Ice Algal Community (McMurdo Sound, Antarctica).

Sea ice supports a unique assemblage of microorganisms that underpin Antarctic coastal food-webs, but reduced ice thickness coupled with increased snow cover will modify energy flow and could lead to photodamage in ice-associated microalgae. In this study, microsensors were used to examine the influence of rapid shifts in irradiance on extracellular oxidative free radicals produced by sea-ice algae. Bottom-ice algal communities were exposed to one of three levels of incident light for 10 days: low (0.5 µmol photons m-2 s-1, 30 cm snow cover), mid-range (5 µmol photons m-2 s-1, 10 cm snow), or high light (13 µmol photons m-2 s-1, no snow). After 10 days, the snow cover was reversed (either removed or added), resulting in a rapid change in irradiance at the ice-water interface. In treatments acclimated to low light, the subsequent exposure to high irradiance resulted in a ~400× increase in the production of hydrogen peroxide (H2O2) and a 10× increase in nitric oxide (NO) concentration after 24 h. The observed increase in oxidative free radicals also resulted in significant changes in photosynthetic electron flow, RNA-oxidative damage, and community structural dynamics. In contrast, there was no significant response in sea-ice algae acclimated to high light and then exposed to a significantly lower irradiance at either 24 or 72 h. Our results demonstrate that microsensors can be used to track real-time in-situ stress in sea-ice microbial communities. Extrapolating to ecologically relevant spatiotemporal scales remains a significant challenge, but this approach offers a fundamentally enhanced level of resolution for quantifying the microbial response to global change.

Mapping the in situ microspatial distribution of ice algal biomass through hyperspectral imaging of sea-ice cores.

Ice-associated microalgae make a significant seasonal contribution to primary production and biogeochemical cycling in polar regions. However, the distribution of algal cells is driven by strong physicochemical gradients which lead to a degree of microspatial variability in the microbial biomass that is significant, but difficult to quantify. We address this methodological gap by employing a field-deployable hyperspectral scanning and photogrammetric approach to study sea-ice cores. The optical set-up facilitated unsupervised mapping of the vertical and horizontal distribution of phototrophic biomass in sea-ice cores at mm-scale resolution (using chlorophyll a [Chl a] as proxy), and enabled the development of novel spectral indices to be tested against extracted Chl a (R2 ≤ 0.84). The modelled bio-optical relationships were applied to hyperspectral imagery captured both in situ (using an under-ice sliding platform) and ex situ (on the extracted cores) to quantitatively map Chl a in mg m-2 at high-resolution (≤ 2.4 mm). The optical quantification of Chl a on a per-pixel basis represents a step-change in characterising microspatial variation in the distribution of ice-associated algae. This study highlights the need to increase the resolution at which we monitor under-ice biophysical systems, and the emerging capability of hyperspectral imaging technologies to deliver on this research goal.