We study the strong CO2 ice absorption band at 2.7 μm and the shallower band at 2.35 μm taking advantage of observations across Martian Years 34 and 35 (March 2018 to February 2020), straddling a global dust storm. We obtain latitudinal‐seasonal maps for CO2 ice in both polar regions, in overall agreement with predictions by a general climate model and with the Mars Express/OMEGA spectrometer Martian Years 27 and 28 observations. We find that the narrow 2.35 μm absorption band, spectrally well covered by LNO order 189, offers the most promising potential for the retrieval of CO2 ice microphysical properties. Occurrences of CO2 ice spectra are also detected at low latitudes and we discuss about their interpretation as daytime high altitude CO2 ice clouds as opposed to surface frost. We find that the clouds hypothesis is preferable on the basis of surface temperature, local time and grain size considerations, resulting in the first detection of CO2 ice clouds through the study of this spectral range. Through radiative transfer considerations on these detections we find that the 2.35 μm absorption feature of CO2 ice clouds is possibly sensitive to nm‐sized ice grains.The Nadir and Occultation for MArs Discovery (NOMAD) instrument suite aboard ExoMars/Trace Gas Orbiter spacecraft is mainly conceived for the study of minor atmospheric species, but it also offers the opportunity to investigate surface composition and aerosols properties. We investigate the information content of the Limb, Nadir, and Occultation (LNO) infrared channel of NOMAD and demonstrate how spectral orders 169, 189, and 190 can be exploited to detect surface CO 2 ice detection at high spectral resolution with Trace Gas Orbiter/Nadir and Occultation for MArs DiscoveryMartian surface CO2 ice maps with Mars Express/OMEGA observations and with Mars Climate Database predictionsGeneral good agreement of the seasonal surface CO2 ice clouds detection through the 2.35 micron CO2 ice absorption band, likely sensitive to a population of nm‐sized ice grainsCO Studies of surface ice at higher spectral resolution (resolving power ∼103) have been performed from ground‐based telescopes allowing differentiation of the polar caps' CO2 frost spectral features from those related to gaseous CO2  from space, has not yet been performed.Spectrally wide COExoMars Trace Gas Orbiter (TGO)/Nadir and Occultation for MArs Discovery (NOMAD) is a suite of three spectrometers conceived to study the Martian atmosphere at high spectral resolution Section . The fir2 ice exposed on the surface and its discrimination from surface water ice and clouds. Moreover, we discuss the potential of the CO2 ice 2.35 μm absorption band for the retrieval of the ice grains size and optical depth. This kind of investigation represents a useful framework for more quantitative and extended retrievals of CO2 ice properties, which will be discussed in follow‐up papers  selected on a tunable entrance filter , covering the infrared range 2.2–3.8 μm, working in nadir, limb and solar occultation geometries; SO, working in the range 2.3–4.3 μm and performing dedicated solar occultation measurements . On the other hand, while the Blaze function is well approximated by a Gaussian curve, the AOTF transmission curve includes several secondary peaks  and is better modeled as a combination of a sinus‐cardinal with a Gaussian . Both curves are characterized by strong peaks, whose exact position on the detector is determined differently and changes from one order to the other. The AOTF peak position is tunable through an internal radio frequency generator, whereas the peak width, which defines the nominal spectral range assigned to a given order, is nearly constant , SZA being the Solar Zenith Angle.Once the solar and nadir spectra have been normalized to counts per pixel per second, the reflectance factor conversion is then:The spectral mixing issue due to the AOTF side‐lobes also propagates to the reflectance calibration. In this case, this effect also introduces low‐frequency oscillations in the spectral continuum, making the direct comparison in absolute values between measurements and radiative transfer models complex. For the above reasons, we only deal with the NOMAD intensities close to the center of each spectral order, being less affected by the aforementioned issues, or with relative quantities obtained through normalization and continuum‐removal processing.The main source of noise in LNO observations comes from the thermal background of the instrument itself  are expected . This is achieved by taking advantage of orders 169 and 190  is a more promising feature, since it never saturates and is well covered by LNO order 189. This band is already known to be diagnostic of the presence of CO2 ice on the surface of Mars  tool by Flanner et al. , formerlm Hansen . The modm Hansen , with th3.22 ice clouds is obtained through the MITRA radiative transfer tool  the analysis of the short‐wavelength shoulder of the 2.7 μm band, through orders 169 and 190 investigation (Section Two different approaches were used to identify and map the CO Section  and (b)  Section .4.12 ice on Mars. Moreover, given the band strength, it is also quite sensitive to atmospheric particulate scattering . This test also confirms the Ice Index to be sensitive to H2O ice, measured through the depth of the 1.5 μm band (panel b in the same figure). As expected, the Ice Index has a value of about 1 on non‐icy terrains while it becomes larger for stronger band depths. Since the Ice Index is evaluated on the 2.7 μm band shoulder, different growth regimes versus the band depth are visible, depending on the width and shape of the considered H2O and CO2 ice absorption bands. Its slow growth rate with smaller band depths makes its uncertainty larger in smaller or more dusty ice deposits. Nevertheless, it is evident how, aside from its uncertainty in transition regions, the Ice Index can be reliably used to identify deposits where the ice abundance (and hence the band depth) is large. In the OMEGA case, the possibility to directly measure the band depths, although at moderate spectral resolution, enables each pixel to be flagged as icy or not and consequently to potentially derive threshold values for ice detection based on the actual uncertainty associated with the OMEGA data. However, this approach cannot be extrapolated to the NOMAD data set, since the differences in data acquisition and processing affect the threshold values.This ratio is of course applicable also to other datasets, for example, for OMEGA, that we use here as a benchmark to test its effectiveness in detecting ice. As we can clearly see in Figure R169 and R190, taken at 2.62 and 2.33 μm respectively) in bins of latitude and Ls, by averaging the data at all available longitudes. As a result, we obtain a latitudinal‐seasonal map for each order. As mentioned in Section RX>< and TESX>< are the zonally averaged NOMAD and TES seasonal maps respectively, and X>< denotes the average along the longitudes inside the same latitude/Ls bin of order X. The ratio of the reflectance in the two orders, weighted by TES albedo data, correlates with the amount of ice in the footprint.With NOMAD data we are interested in longitudinally averaging the Ice Index, in order to perform a seasonal study of the ice coverage. To achieve this, we group the reflectance factors taken at the central wavelengths of the selected orders (2 and 104 for OMEGA and NOMAD respectively). This implies that the OMEGA steep short wavelength shoulder of the 2.7 μm band is probably probing different depths of penetration in the ice with respect to NOMAD, due to the wider wavelength range convolved in a single spectral point. All these sources of uncertainty are particularly significant in ice/no‐ice transition regions, and, overall, prevent the definition of an absolute threshold value for ice detection. For this reason, we focus on the global distribution of the Ice Index and its qualitative correlation with regions of interest on the planet. As in the case of OMEGA, in the NOMAD data set Ice index values as low as 1 are found in regions where no large concentrations of ices are expected, for example, at the equator and mid‐latitudes. On the other hand, an Ice Index larger than 2 is found on the polar caps where both H2O and CO2 ices are known to be abundant  embedded in a wider absorption between 2.339 μm  and 2.351 μm . Since the width of the 2.35 μm absorption band is of the same order of the AOTF bandwidth, the measurement of the full band depth is not possible, as the continuum level of the reflectance is hardly determined. Moreover, the SNR at the edges of the order, at wavelengths shorter than 2.337 μm and longer than 2.351 μm drops significantly. The definition of a pseudo‐continuum between 2.339 μm  and 2.351 μm  will allow the measurement of a partial band depth which cannot quantify the amount of CO2 ice (since its continuum is still affected by CO2 ice absorption) but it is qualitatively correlated to its abundance. However, the uncertainties associated with such parameters are still large, since they always deal with the LNO signal measured in few spectral channels.As described in the previous section, the Ice Index is sensitive to both CO4.2.12 ice detection with LNO, we use the Spectral Angle Mapper (SAM) method  and 2.351 μm . As a reference endmember, we adopt a bulk southern polar cap spectrum in which the 2.35 μm CO2 ice absorption band is clearly recognizable and whose spectral shape is in agreement with that expected from radiative transfer models . The resulting map of the SAM similarity index χ is shown in Figure We apply the SAM algorithm to the LNO spectra of order 189 between 2.337 μm  at mid‐latitudes, where the relative errors of the Ice Index and SAM similarity index are maximum and reach 30% and 50% respectively. Nevertheless, we note that the polar caps regions correlate with χ values larger than 0.2  the sublimation of the northern polar cap is observed in both maps, in agreement with MCD simulations. Although fewer observations are available for southern winter (Ls ∼ 90°), we observe some clear detections of the southern polar cap in the Ice Index map. These are in agreement with the presence of both H2O and CO2 ices and, since no coincident detections are available in SAM map, we cannot determine which ice is being probed by the Ice Index. During the southern late winter/spring we observe the sublimation of the southern polar cap both in the Ice Index and SAM maps (140° < Ls < 260°). This solar longitude range is also affected by the 2018 global dust storm , due to the scarce data coverage and poor SNR of order 189 data near the poles in the illumination conditions typical of late winter. During the decay phase of the storm (Ls ∼ 200°–250°) both maps correctly reproduce the sublimation pattern of the ice caps predicted by the MCD.We can now qualitatively compare the seasonal Ice Index Figure  and SAM x Figure  maps wit Figures . In thes Figures . Both thLs > 255°), indicating the condensation and the peak winter phase of the northern polar cap. In this period, ice is identified in both the SAM and Ice Index maps only for Ls > 280°. On the other hand, at Ls ∼ 255° only Ice Index detections are found, suggesting that the parameter is probably probing H2O ice at those solar longitudes. The dichotomy between the SAM and the Ice Index map makes it possible to distinguish the presence of H2O and CO2 ices and is discussed further in Section Finally, a few detections appear during northern autumn and winter Ls > 25°, indic4.32 ice detection approach described in Sections 2 ice spectral features. We verify this assumption by performing radiative transfer simulations with different dust optical depths in the wavelength range covered by orders 169, 189, and 190 . As a consequence, dust lowers the Ice Index value (Section τ2 < 1) can impact the detection of small/thin ice deposits through the Ice Index, but conditions of high dust optical depth can even mask extended icy surfaces. Indeed, with respect to the clear sky case, we estimate a decrease of the Ice Index down to 85% with τ2 = 2. This analysis confirms that, even if it is beyond the scope of this paper  are given in Figure On the other hand, dust has a lesser impact on the CO Section . This is5As described in Section χ index map is higher with respect to the Ice Index map , the Ice Index is probing both H2O and CO2 ices. On the other hand, in the lower Ls clusters in regions C (85° < Ls < 105°) and G (255° < Ls < 320°) only Ice Index derived boundaries appear, suggesting that the parameter is only probing H2O ice there. The estimated cap boundaries show a drift to larger MCD CO2 ice column densities from the peak phase to the sublimation phase of both the North (regions G to A) and the South  polar caps. Such a trend may be related to non‐uniform sublimation processes , possibly yielding an increase of the areal mixing of terrains within the NOMAD footprint, leading to the concept of inner/outer crocus line .On the other hand, OMEGA boundaries  to its decay phase . In this region, its value decreases significantly, while the same does not happen in the SAM similarity index map. A similar behavior is observed at Ls ∼ 190°, during the storm peak phase, where the Ice Index experiences a sudden drop just before the observation gap. This is as expected, as demonstrated in Section τ2 ∼ 0.5. Such an approach indicates that an estimation of the dust abundance through the Ice Index is in principle possible  with very large variations of the CO2 ice effective radius. In this computation, we span from sizes comparable or smaller to those expected for CO2 ice clouds to sizes pertaining to the surface ice regime, up to slabs as large as 100 cm, always keeping constant the optical depth at τ2 = 0.4. From the figure it is evident how for sizes between approximately 100 nm and 1 mm the 2.35 μm band is practically absent. Instead, for both reff < 100 nm and reff > 1 mm the band depth increases. While the band depth increase for large sizes is ascribable to the increasing interaction of the light with the particle volume, the behavior for nanometric sizes is typical of the Rayleigh regime , where the absorption tends to progressively dominate the scattering with the decreasing sizes  in the n et al.  observed2 frost, we find sizes in the range 1–10 cm with optical depths between 0.1 and 1.0.By performing the analysis described above to all detections in Table Of course, the analysis described above cannot be considered as a quantitative retrieval of physical quantities but, as already stressed, provides an estimate of their order of magnitude. A more quantitative approach should rely on a number of assumptions that are still not well assessed, like the detailed instrumental response (e.g., AOTF and blaze functions, see Sections 2 ice 2.35 μm absorption band. Nevertheless, a more conclusive discrimination between the two hypothesis is only achievable through a more comprehensive radiative transfer analysis of the 2.35 μm band as well as other spectral features, whose study is clearly beyond the scope of this paper and will be the subject of a future work (Section 2 ice.Given the above discussion, we suggest that mid‐latitudes ice detections are more likely to be ascribed to clouds than to surface frost for context reasons and band depth estimates, resulting in the first detection of clouds through the study of the CO Section . Neverth62 and H2O ices deposits (Ice Index, Section 2 ice was obtained using the 2.35 μm absorption band, which is well covered by LNO order 189 (Section In this work we explored NOMAD LNO information content of orders 169, 189, and 190 Table  demonstr Section . While t2 ice deposits (Sections We also investigated the impact of the 2018 global dust storm on the ice detection in the Southern polar cap during the spring season. In this case, the high concentration of dust in the atmosphere reduces the number of solar photons reaching the surface and thus back to the NOMAD detector, affecting the capability to spot the surface ice through the Ice Index investigation. On the other hand, we verified that the SAM algorithm is less affected by the presence of dust, making it a robust tool for the detection of spatially homogeneous and abundant COSections  and 5.2 ice detections were also found at mid‐equatorial latitudes, away from the polar regions. CO2 ice has already been detected at these latitudes both as surface ice/frost and high altitude clouds, and the discrimination of these conditions is not easy in nadir‐looking spectra.Through our analysis, CO2 surface ice is known to exist at these latitudes in pole facing slopes remaining in shadow during daytime (Vincendon, 2 ice clouds. Through a grain size analysis (Section 2 ice clouds hypotheses, while the 1–10 nm regime is compatible with fine grains in CO2 ice clouds condensing higher in the atmosphere (Montmessin et al., 2 ice clouds through the 2.35 μm absorption band analysis. This investigation demonstrates how LNO order 189 has large potential to be exploited to retrieve CO2 ice microphysical properties. Moreover, this sets the basis for an in‐depth investigation of the band also in other datasets, like OMEGA and CRISM ones, even if characterized by a lower spectral resolution.While CO Section  we verif Section . The lat2 ice clouds spectra is planned.The analysis presented in this paper sheds some light on the possibility of conducting surface and aerosol science using a data set that is nominally conceived for the study of Martian trace gases, such that of NOMAD LNO, and opens the way for several follow up studies. An analysis of NOMAD UVIS channel information content, focused again on surface studies, is currently being performed as a continuation for the study presented in this paper. A dedicated quantitative radiative transfer analysis for the retrieval of surface ice microphysical and geometrical properties such as grains size, mass density and layers thickness, is already in progress and is the subject for a future paper. Moreover, an investigation focused on ice clouds detection is also being performed. Finally, an in depth radiative transfer analysis of the 2.35 μm feature in CO


Whereas several studies have documented the destructive effects of ice scouring on the seabed and its strong role in structuring benthic communities in Antarctica, none have highlighted the potential of seabed furrows  produced by this disturbance as a novel habitat that is created by the accumulation of drift algae. This work documents the distribution and dimensions of ice pits to evaluate their relationships with the biomass and species composition of the accumulations of drift algae within them. Moreover, the temporal dynamics of algal deposition and advective loss in ice pits over time are assessed. These investigations show that ice pits provide hitherto underestimated ecological subsidies of food and shelter for other benthic organisms. Further research is needed to better understand the role of ice pits in the overall functioning of Antarctic marine benthic ecosystems.2) that would otherwise be transported to deeper water accumulate inside these features, representing an underestimated subsidy. Our work documents the distribution and dimensions of ice pits in Fildes Bay, Antarctica, and evaluates their relationship to the biomass and species composition of algae found within them. It also assesses the rates of deposition and advective loss of algae in the pits. The 17 ice pits found in the study area covered only 4.2% of the seabed but contained 98% of drift algal biomass, i.e., 60 times the density (kg/m2) of the surrounding seabed. Larger ice pits had larger and denser algal accumulations than small pits and had different species compositions. The accumulations were stable over time: experimentally cleared pits regained initial biomass levels after one year, and advective loss was less than 15% annually. Further research is needed to understand the impacts of ice scouring and subsequent algal retention on ecosystem functioning in this rapidly changing polar environment.Ice scouring is one of the strongest agents of disturbance in nearshore environments at high latitudes. In depths, less than 20 m, grounding icebergs reshape the soft-sediment seabed by gouging furrows called ice pits. Large amounts of drift algae (up to 5.6 kg/m The disturbance is one of the most important factors that regulate the structure and functioning of natural communities ,2,3,4,5.Ice, a dominant disturbance agent at high latitudes, is found primarily in two forms: sea ice and icebergs . Sea iceDisturbance from icebergs can shape seabed morphology , reworkiSeveral studies have clearly documented the destructive effects of ice scouring on the benthic communities in Antarctica on both hard and soft bottoms . ExampleOnce algae are detached, their transport is driven mainly by currents , but depending on their structural components and buoyancy, some dislodged algae may float and drift at the ocean surface or water column for long periods of time before accumulating on the shore  or sinkiThe accumulation of macroalgae in ice pits could have multiple implications for the functioning of coastal ecosystems ,64. FirsGiven these potential ecological roles of ice pits and their potentially widespread distribution around Antarctica, further knowledge of their physical and biological characteristics is needed to assess their importance, especially as an ecological subsidy for benthic soft-bottom communities . This inHere we provide a detailed survey of a subtidal site in the West Antarctic Peninsula where we conducted descriptive sampling and experiments to document the distribution and nature of ice pits and drift algae, including species composition and biomass. Specifically, we (1) documented how ice pits are distributed in space, (2) described their physical dimensions, (3) evaluated biomass and species composition of drift algae within ice pits, and (4) determined the temporal dynamics of algal deposition and accumulation in ice pits through time.Adenocystis utricularis (Ochrophyta), Monostroma hariotii (Chlorophyta), and Palmaria decipiens (Rhodophyta) occur. At greater depths, abundant patches of algae attached to rocks appear, mainly the rhodophytes Plocamium cartilagineum, Curdiaea racovitzae, and Palmaria decipiens. The phaeophytes A. utricularis and Himanthorallus grandifolius and the chlorophyte M. hariotii are also present but are less abundant. On the deeper soft bottom, attached algae are not found, except occasionally attached to the shells of the infaunal bivalves Laternula elliptica and Aequiyoldia eightsii or small rocks. In this zone, accumulations of drift algae comprise the overwhelming majority of algal material.The study was conducted in Fildes Bay at a site near the Instituto Antártico Chileno (INACh) Prof. Julio Escudero research station on King George Island, Antarctica . The sitFildes Bay regularly freezes in winter; therefore, field aspects of this study, which spanned 2018–2020, were conducted during the austral summer (January and February) when the bay was ice-free and allowed access for untethered SCUBA diving.2 that ranged in depth from 12 to 20 m. The center of each pit encountered was used to measure the bathymetric depth and the depth of the ice pit  constructed with an auxiliary SCUBA cylinder connected through a BCD hose and an air feed valve to the wall of a 2-m-long, 10-cm-diameter polyvinylchloride (PVC) pipe manipulated by SCUBA divers , which was multiplied by the thickness of the algal layer to calculate the algal density . The total algal biomass for each ice pit was then estimated by multiplying algal density by the calculated algal accumulation volume  ice pits in the study area for logistic reasons . By using the suction technique described above, all the algae in each pit were removed and weighed in January 2018, i.e., at the beginning of the summer sampling season. At the start of the two subsequent summers (January 2019 and 2020), the algal accumulation in each ice pit was again removed and weighed. In addition, during the intervening summers (2018 and 2019), the pits were visited two, four, and six weeks after the major clearing event, and any accumulated algae was removed and weighed. The temporal dynamics of drift algae in ice pits were assessed by two experimental manipulations. In order to estimate rates of algal deposition, drift algae were removed annually in January from five ice pits over three years (2018–2020). The cleared ice pits were randomly selected from among the smaller (≤10 m3), which made them suitable proxies for fragments of drift algae.In order to estimate rates of advective loss of algae from ice pits, ten markers were haphazardly placed on top of the algal layer in seven ice pits and then censused after one month and again after 13 months. The ice pits were randomly selected from among those not used in the clearing experiment. The markers were made of strips of orange-colored straight-line polyvinyl chloride (PVC) flagging tape, each 15 cm long and 2 cm wide. As well as being highly visible for recovery D, the mat-test was used to distinguish the area-specific biomass inside ice pits from that of the surrounding seabed.Pearson’s correlations were used to assess relationships among ice pit dimensions . A Mantel test was used to determine if physical proximity between ice pits  contributed to similarities in ice pit shape . A Welch 2), the algal species richness (S), and diversity (Shannon-Wiener’s H′), were calculated and compared among ice pits. To determine if ice pit dimensions and relative position were good predictors of these metrics, they were modeled using multiple regressions. Environmental variables with relevant interaction terms include bathymetric depth (m), ice pit depth (m), and local coordinates (m). For the latter, latitude and longitude were converted to a meter-based grid within the study area so that all spatial measurements and coefficients were interpreted in meters; locations corresponded to distances east and north of the reference point based on the most southwesterly ice pit “L” and “M”). Initial models for the area-specific biomass, species richness, and H′ diversity also included ice pit length (m), mean width (m), and additional interaction terms. The final models of the four responses were determined by first removing multicollinearity (threshold of VIF = 4.6), then reducing predictors and interaction terms based on a stepwise threshold of ΔAIC of 0.1, and finally, by inspecting model residuals.Biotic metrics, including total algal biomass (kg), the area-specific algal biomass  and the Euclidean distance matrix based on the biomass of each of the 16 algal species. The relationship was also visualized using non-metric Multidimensional Scaling (nMDS) based on Bray-Curtis dissimilarity, which included algal species composition correlated with physical variables .p < 0.05 was used as the significance threshold for all tests.A one-way analysis of variance (ANOVA) was performed to test whether annual algal accumulations measured in 2019 and 2020, each year after being experimentally cleared, differed from the biomass initially observed in the 2018 survey. Annual accumulation values were summed from all removal events, including year-long and short-term  collections. The Bartlett test was used to verify the homogeneity of variances for biomass as a function of observation year, and the Shapiro-Wilks test was used to verify the normality of model residuals. Rates of advective loss of PVC markers were calculated after one and 13 months but were not statistically compared. Analyses were performed using R software , and p = 0.01), whereas ice pit depth was not related to either length  or width . There was almost a 30-fold range in the calculated value for the ice pit area (mean [range]: 9.27 m2 [0.79–21.8]). The Mantel test indicated that spatial autocorrelation did not contribute to the variation in ice pit shape and size  that ran diagonally to the shorelines . Ice pitand size , i.e., st = 7.29, p < 0.001) inside the ice pits (mean ± sd = 2.92 kg/m2 ± 0.19) than outside ice pits (0.05 kg/m2 ± 0.05). Sixteen algal species were found in the samples , and Himantothallus grandifolius , contributed 81.5% of the total biomass  among the 11 ice pits sampled. Not surprisingly, ice pits that were longer and, therefore, larger in the area had greater total algal biomass , but theectively , which vectively  for totaectively , algal dp = 0.001)  also formed a distinct group, separated from the larger ice pits by their geographic location (eastern band of ice pits) and the higher relative abundance of another common species, Curdiea racovitzae.In terms of drift algal diversity, ice pit size  and bathymetric depth both significantly affected species richness, with higher species richness in larger ice pits located in deeper water . No fact= 0.001) . These rdifolius . In contp = 0.92; mean biomass of 2018, 2019, and 2020 = 9.71 kg, 9.2 kg, and 9.36 kg, respectively; Initial biomass values of accumulated drift algae were almost completely restored one year after each experimental removal, with no statistical differences seen among the three years  and the subsequent colonization by associated invertebrates . Our 17 study ice pits were found in a small study area , covering just over 4.2% of the seabed but containing over an estimated 98% of the drift algal biomass. How representative this situation is of other nearshore environments remains unknown, but ice pits are also present at other sites in Fildes Bay  interact to shape ice pits and how they change through time.The relative scarcity of algae outside of ice pits shows that the depression created by an ice pit clearly creates a depositional environment for negatively buoyant drifting algae. However, their dimensions can influence their algal contents, both quantitatively and qualitatively . Not surprisingly, estimates of total biomass increased with ice pit size, but the increase in area-specific biomass with ice pit size was unexpected. While this pattern could be due to thicker layers of algae accumulating in larger ice pits, our measurements of the thickness of the algal layer indicated little variation among ice pits of different sizes. Instead, the relationship between area-specific biomass and ice pit size appears to be related to the density of algal thalli within the algal layer. This layer, a loose mix of algal fragments, was largely composed of water, with algal tissue contributing up to 4% of its volume  and one large brown algal species that do not grow in the immediate area (Desmarestia anceps). The underlying mechanisms producing this pattern are unclear but potentially might be related to the characteristics of the different algal species in terms of rates of deposition  or degradation in ice pits of different dimensions. Smaller ice pits might represent a recent deposition of more ephemeral species, whereas larger pits with larger, more common species may represent more stable assemblages. These findings further bolster the need for additional investigations of the interactions among algal source populations, fragment properties, and the transport of drift algae in this region.Ice pit dimensions also appeared to influence the species composition of accumulated drift algae. Diversity, at least as measured by species richness, differed between ice pits, with larger ice pits in deeper water having more species. This pattern is not surprising as larger pits contained more algal fragments, and there might be less loss of fragments from deeper locations. Species composition also varied among different sizes of ice pits, with different algal species characterizing small, medium, and large ice pits. For example, the three smallest ice pits had distinctly different species compositions than moderate and large ice pits. Despite being in the center of the study area, they lacked some of the species that dominated larger ice pits, including those nearby; instead, they were dominated by two rarely collected red algal species  are less likely to occur then. More likely is the fall, when periods of strong winds and storms would generate waves and currents that could increase hydrodynamic forces that can dislodge algae that have grown during the productive summer season. Spring is another possibility as large quantities of loose sea ice are formed at that time, thus increasing the likelihood of scouring the shallow rocky substrata where algae grow. Regardless, given the substantial annual deposition rates and the lack of advective loss, this system resembles a chemostat with an algal load capacity, which, once reached, remains dynamically stable; excess algae are removed by consumption and decomposition, and these losses are then compensated by seasonal input.Plocamium cartilagineum, Curdiaea racovitzae, Himantothallus grandifolius) were also growing abundantly near the study area, suggesting a local source and limited transport. In support of this idea, other algae, such as Desmarestia anceps, which forms prominent algal forests elsewhere in Fildes Bay, were not well represented in the ice pits. Likewise, the composition of algae in ice pits is not necessarily a snapshot of local algal assemblages. Case in point, the rhodophyte Palmaria decipiens grew in only moderate abundance near the study site, and it was nearly absent in the 2018 data presented in this work (<4 g/m2). However, it was a dominant species in ice pits in the following year  with no readily apparent explanation. These observations emphasize the complex nature of drift algal dynamics.The precise source of drift algae remains unknown. At our site, drift algae in ice pits were composed mainly of red and brown algae, and most species found in ice pits were observed attached to nearby rocky substrata. The most abundant species found in ice pits (The degradation of algal detritus is assumed to be extremely slow in the soft bottom environments of Antarctica ,70 compaAccumulations of drifting algae in ice pits are expected to have different effects on abiotic and biotic conditions within them, depending on the temporal and spatial extent of algal depositions and local hydrodynamic conditions ,67,89. IThis work is a detailed glimpse into a poorly known nearshore habitat and provides a baseline for future observations. It also highlights the important role of ice scouring in Antarctic soft-bottom environments by both dislodging algae and creating ice pits into which much of that drift algae accumulates. Variations in the physical characteristics of ice pits influenced the quantity and species composition of algal accumulations in them, and their biomass appears to be dynamically stable through time. These features provide a unique but underappreciated ecological subsidy for soft-bottom habitats that may be important for structuring the benthic communities.Ice scouring is a key disturbance process in polar regions that will be dramatically altered by climate change. Growing evidence indicates that accelerated warming in the Antarctic will lead to greater iceberg calving and increased production of drift algae. However, relevant information, such as calving rates of glaciers and the size distribution, longevity, and movements of icebergs, is still limited, and further research is required to understand how these factors will combine to affect the benthic assemblages of Antarctic marine ecosystems.


Group II metabotropic glutamate (mGlu) receptors (mGlu2/3) are Gαi/o-coupled receptors and are primarily located on presynaptic axonal terminals in the central nervous system. Like ionotropic glutamate receptors, group II mGlu receptors are subject to regulation by posttranslational phosphorylation. Pharmacological evidence suggests that several serine/threonine protein kinases possess the ability to regulate mGlu2/3 receptors. Detailed mapping of phosphorylation residues has revealed that protein kinase A (PKA) phosphorylates mGlu2/3 receptors at a specific serine site on their intracellular C-terminal tails in heterologous cells or neurons, which underlies physiological modulation of mGlu2/3 signaling. Casein kinases promote mGlu2 phosphorylation at a specific site. Tyrosine protein kinases also target group II receptors to induce robust phosphorylation. A protein phosphatase was found to specifically bind to mGlu3 receptors and dephosphorylate the receptor at a PKA-sensitive site. This review summarizes recent progress in research on group II receptor phosphorylation and the phosphorylation-dependent regulation of group II receptor functions. We further explore the potential linkage of mGlu2/3 phosphorylation to various neurological and neuropsychiatric disorders, and discuss future research aimed at analyzing novel biochemical and physiological properties of mGlu2/3 phosphorylation. Two classes of cell-surface and membrane-bound glutamate receptors are expressed in the mammalian brain. Ionotropic glutamate (iGlu) receptors are a family of ligand-gated ion channels that mediate fast excitatory synaptic transmission . Anotherin vitro and in neurons , protein kinase C (PKC), and G protein-coupled receptor kinases (GRK). Noticeably, mGlu2/3 phosphorylation is a regulated event and is sensitive to changing cellular and synaptic signals. As such, mGlu2/3 phosphorylation levels are altered in an animal model of a neuropsychiatric disease, reflecting a significant adaptive event in the remodeling of excitatory synaptic transmission and plasticity critical for the pathogenesis and symptomatology of the disease.Protein phosphorylation is one of important posttranslational modifications that actively regulate expression, distribution, and function of modified proteins under normal conditions or in response to changing synaptic input. Glutamate receptors are among a pool of synaptic proteins that are subject to vigorous regulation by a phosphorylation-dependent mechanism . Early e neurons . In addiThe GRM2 and GRM3 genes encode human mGlu2 and mGlu3 receptor proteins, respectively  . The amiGroup II receptors have a traditional membrane topology for a class C GPCR: A large extracellular N-terminus, an intracellular C-terminus (CT), and seven transmembrane domains which give rise to three intracellular loops. A schematic topology of the rat mGlu2 receptor is illustrated in mGlu2/3 receptors are diffusely expressed in broad regions of the central nervous system , with mGvia Gβγ release  but not the first intracellular loop. Between two sites (S837 and S843) similar to the PKA consensus phosphorylation motif R/K-R/K-X-S/T (where X represents any amino acid) in mGlu2 CT  in the mGlu3 CT tail  was alsol cortex . Using al cortex . Of notel cortex .Phosphorylation of mGlu2/3 by PKA has significant physiological consequences. Mutation of mGlu2 S843 to alanine (S843A) prevented phosphorylation at this PKA site . This muvia a homologous desensitization process.In addition to second messenger-dependent protein kinases , GRKs phosphorylate and thus regulate GPCRs. GRKs phosphorylate the ligand-activated GPCRs at serine and threonine sites, which facilitates the binding of an arrestin protein to the active receptor. Arrestin binding then interdicts the receptor-G protein coupling, resulting in the agonist-promoted homologous desensitization, one of the most noticeable roles of GRKs. Group I mGlu receptors are among GPCRs that are readily phosphorylated and regulated by several members of the GRK family . mGlu3 rHow GRKs modulate mGlu3 receptors is unclear at present. Traditionally, GRKs could phosphorylate a receptor to initiate a GRK-arrestin process to desensitize the receptor. Alternatively, GRKs could achieve their roles by regulating receptor/G protein interactions without requiring GRK-mediated phosphorylation as has been seen in mGlu1a receptors  or by phin vivo as the mGlu2/3 agonist-induced inhibition of cAMP responses was desensitized in wild-type and mGlu2−/− mice but not in mGlu3−/− mice. Moreover, such resistance was consistently seen in CHO and C6 glioma expression cells and in neurons , casein kinase 1 (CK1) also promotes S843 phosphorylation. Besides serine and threonine, tyrosine represents a site accepting phosphorylation in group II receptors. in vitro. Native PP2C also bound to mGlu3 CT in rat brain cells. Among four brain PP2C isoforms  surveyed, all of them bound to mGlu3 CT, with PP2Cβ showing the highest affinity. Among the CT regions of all mGlu subtypes (mGlu1-8), positive binding of PP2Cα was detected only with mGlu3, indicating that the highly specific nature of the PP2C-mGlu3 interaction. A 20-amino acid region (836–855) in the middle of mGlu3 CT constitutes a minimal domain for the sufficient binding to PP2Cα. This region is noticeably not conserved in mGlu2 CT, even though the amino acid sequences of the group II receptors  are highly homologous in the proximal and distal regions of CT tails , while other serine/threonine phosphatases  did not . Thus, tin vitro and in vivo. GRKs and PKC are also among presynaptic kinases that vigorously regulate mGlu2 and/or mGlu3 receptors. The pharmacologically-defined roles of kinases have been well validated by the ability of kinases to directly phosphorylate mGlu2/3 receptors. In recombinant and native mGlu2/3 proteins respectively expressed in heterologous cells and animal brains, PKA phosphorylates a conserved serine site on mGlu2/3 CT tails. Like serine and threonine, tyrosine-phosphorylated group II proteins (likely mGlu3) were found in the striatum. Phosphorylation of mGlu2/3 receptors is functionally relevant. For instance, the PKA-mediated phosphorylation of mGlu2/3 receptors negatively modulates the presynaptic inhibitory function of mGlu2/3 by reducing the coupling efficiency of G proteins to the receptors. In addition to protein kinases, PP2C specifically binds to mGlu3 but not mGlu2 receptors. This supports existence of the functional PP2C-PKA interaction controlling phosphorylation of mGlu3 receptors. Overall, mGlu2/3 phosphorylation represents an important posttranslational modification that regulates responses of mGlu2/3 to changing synaptic input and presynaptically maintains homeostasis of excitatory synaptic transmission.Significant progress has been made in both pharmacological and biochemical studies aimed to explore and characterize the phosphorylation and regulation of presynaptic group II mGlu receptors by various protein kinases. Consistent pharmacological evidence supports a pivotal role of PKA in inhibiting mGlu2/3-mediated responses in a variety of functional assays both via a phosphorylation-dependent mechanism. Second, given that different kinases may act on the same phosphorylation site, robust crosstalk may occur among kinases to determine precise signaling and physiological outcomes. Similarly, crosstalk could occur at additional levels, such as between kinases and phosphatases and between phosphorylation and other types of posttranslational modifications. Third, two group II subtypes may have distinguishable properties in their phosphorylation reactions. Indeed, PP2C bound to and dephosphorylated only mGlu3 receptors  in mGlu2/3 intracellular domains  have yeteceptors . The mGleceptors . Fourth,eceptors . mGlu3 receptors . It is leceptors . Emergineceptors . TogetheMethodologically, the above mentioned future studies will be facilitated by recently established tools and approaches, including 1) orthosteric or allosteric agents with high selectivity for the individual mGlu2 or mGlu3 subtype, 2) mGlu2 or mGlu3 knockout mice or mGlu2/3 double knockout mice , 3) mGlu


Almost 65% of the human protein supply in the world originates from plants, with legumes being one of the highest contributors, comprising between 20 and 40% of the protein supply. Bioactive peptides from various food sources including legumes have been reported to show efficacy in modulating starch digestion and glucose absorption. This paper will provide a comprehensive review on recent in vitro studies that have been performed on leguminous antidiabetic peptides, focusing on the α-amylase inhibitor, α-glucosidase inhibitor, and dipeptidyl peptidase-IV (DPP-IV) inhibitor. Variations in legume cultivars and methods affect the release of peptides. Different methods have been used, such as in sample preparation, including fermentation , germination (t), and pre-cooking; in protein extraction, alkaline extraction, isoelectric precipitation, phosphate buffer extraction, and water extraction; in protein hydrolysis enzyme types and combination, enzyme substrate ratio, pH, and time; and in enzyme inhibitory assays, positive control type and concentration, inhibitor or peptide concentration, and the unit of inhibitory activity. The categorization of the relative scale of inhibitory activities among legume samples becomes difficult because of these method differences. Peptide sequences in samples were identified by means of HPLC/MS. Software and online tools were used in bioactivity prediction and computational modelling. The identification of the types and locations of chemical interactions between the inhibitor peptides and enzymes and the type of enzyme inhibition were achieved through computational modelling and enzyme kinetic studies. Diabetes is a global health problem and the world’s fastest growing chronic disease. Diabetes is one of the top ten causes of death in the world . Over thThere are three main types of diabetes: diabetes mellitus type 1 (T1DM), diabetes mellitus type 2 (T2DM), and gestational diabetes . Among tT2DM is a chronic condition characterized by insulin deficiency and peripheral insulin resistance which causes high blood-glucose levels. Diets high in readily digestible carbohydrates (starch) and highly processed foods, as well as a sedentary life, play a crucial role in the epidemy of T2DM .A healthy lifestyle is the foundation of T2DM management. This includes a healthy diet, regular physical exercise, not smoking, and maintaining a healthy body weight . For somThis paper focuses on in vitro studies that have been performed on leguminous antidiabetic peptides, i.e., an α-amylase inhibitor, an α-glucosidase inhibitor, and a DPP-IV inhibitor, in an attempt to understand the different methods used and their interpretations.The inhibition of salivary and pancreatic α-amylases will cause some fractions of the starch and polysaccharides in the food bolus to remain undigested when reaching the small intestine. This will reduce the number of substrates for α-glucosidase. Further, the inhibition of α-glucosidase will cause the digested amylose and amylopectin of starch to remain as maltose, maltotriose, branching oligosaccharides, and isomaltose. These intermediate starch digesta fractions are hence not absorbable by intestinal cells for transfer into the blood stream. The inhibition of α-amylase and α-glucosidase will result in a decreased serum glucose level, which is beneficial in controlling the postprandial blood-glucose level ,12.The inhibition of DPP-IV enzymes will prolong the biological activity of incretins. Incretins consist of two hormones, glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) ,15. ThesLong-term use of hypoglycaemic synthetic drugs, however, can cause side effects such as bloating, diarrhoea, abdominal pain, fluid retention, osteoporosis, hypoglycaemia, improper function of the liver, risk of kidney injury, and heart failure ,17. ThisResearchers worldwide have attempted to investigate the use of natural dietary compounds to reduce starch digestibility and glucose absorption by means of increasing resistant starch, either through processing or through its addition into products : the incThe main objective of this review is to provide a comprehensive review of recent in vitro studies that have been performed on leguminous antidiabetic peptides, focusing on the α-amylase inhibitor, α-glucosidase inhibitor, and dipeptidyl peptidase-IV (DPP-IV) inhibitor in an attempt to understand the methods used and their interpretations.Starch (polysaccharide) digestion begins in the mouth, where α-1,4 glycosidic linkages are cleaved by salivary α-amylase. Glucose is absorbed through the intestinal lining cells or enterocytes, across the epithelial cell and into the blood stream inside the villus. Glucose enters the epithelium through the apical membrane and leaves it through the basolateral membrane. A sodium-dependent hexose transporter (SGLT1) carries glucose into the enterocyte by first orienting towards the intestinal lumen to bind with sodium. This binding causes the transporter to change its conformation and opens the pocket for glucose to bind. When glucose binds, the transporter reorients and moves glucose and sodium into the cell. The transporter releases sodium and glucose into the cytoplasm and returns to its lumen-facing orientation to pick up more glucose and sodium. The sodium level in the cytoplasm is maintained in balance with potassium by a battery of sodium–potassium pumps on the basolateral membrane. These pumps shuttle out sodium in exchange for potassium. Glucose is transferred into capillary blood in the villus through a facilitated diffusion by another hexose transporter (GLUT2) on the basolateral membrane .The glucose concentration in the blood after a meal is called postprandial glucose. The glycaemic index (GI) is measured by the blood-glucose concentration after a meal. GI is a ranking of the carbohydrates in foods on a scale of 1–100, based on the extent to which they increase blood sugar levels after consumption. The GI is used to classify different sources of carbohydrate-rich foods by their effect on postprandial glycemia .The normal concentration of circulating blood glucose is approximately 3.9–5.4 mmol/L (70–90 mg/dL). It is predominantly controlled by the two pancreatic hormones: insulin and glucagon. These are peptide hormones that lower and raise the blood-glucose concentration, respectively. Insulin stimulates glucose uptake by cells when the blood-glucose level is too high, while glucagon stimulates the conversion of stored glycogen in the liver to glucose when the blood-glucose level is too low. Secretions of both insulin and glucagon are regulated by another hormone, called an incretin. Incretins are a group of metabolic hormones that stimulate the decrease in blood glucose by the secretion of insulin and inhibit the release of glucagon. Incretins can be deactivated by the presence of dipeptidyl peptidase IV (DPP-IV), which can lead to an increase in the blood-glucose level through the secretion of glucagon and the inhibition of insulin release . A DPP-IProteins are polymers of amino acids that are linked together by peptide bonds. There are hundreds of amino acids found in nature, but only 20 are found in the human body and other living organisms . ThroughShort-chain amino acid sequences obtained from protein may have potential physiological functions in addition to their nutritional contribution . The pepSpecific protein fragments, i.e., peptides, that promote physiological functions and the conditions of human health are defined as bioactive peptides. In the sequence of a parent protein, bioactive peptides are inactive. They can be released through hydrolysis. Enzymatic hydrolysis is the main process for obtaining peptides from their parent proteins and allowing them to actively function biologically .Vigna unguiculata genotype Epace 10) have a similar amino acid sequence to that of bovine insulin ; y-axis = 1/V), in which the Michaelis-Menten constant (Km) and the maximum velocity of enzymatic activity (Vmax) were calculated. The slopes, 1/Km values, and 1/Vmax values of the lines from varying inhibitor concentrations defined the type of inhibition. Competitive inhibition was indicated by increasing Km values and unchanged Vmax values with the increase in inhibitor concentrations. This type of inhibition is typical with intersecting lines at the y-axis at the same point, indicating unaffected Vmax values even when more inhibitors are present. Non-competitive inhibition is indicated by unchanged Km values and reduced Vmax values with increasing inhibitor concentrations. This type of inhibition is typical with intersecting lines at the x-axis at the same point, indicating1/Km values unaffected by various inhibitor concentrations. Uncompetitive inhibition is defined by reduced Km values and reduced Vmax values with an increase in inhibitor concentrations. For this type of inhibition, lines share the same slope.In an enzyme kinetics study, inhibitor peptides were analysed at a minimum of three levels of inhibitor concentrations using Lineweaver–Burk plots . Domain A consists of an eight-stranded, parallel β-barrel surrounded by a cylinder of α-helical segments. In this domain, the active sites are located at, ASN197, GLU233, and ASP300 . An α-glPhaseolus vulgaris L. inhibitory peptides on α-amylase were investigated [Pisum sativum L. inhibitory protein hydrolysates and peptides also reported a similar type of inhibition [Molecular docking of stigated ,61. Inhistigated  to have hibition .It was argued in at least two reports that hydrophobic  and hydrophilic  amino acids are responsible for human-salivary α-amylase inhibition through hydrophobic interactions and hydrogen bonds at the active site ,62. InhiPisum sativum L. peptides, similar to the results of Jiang’s group [Molecular docking studies between α-glucosidase and soybean , common ’s group .Amino acid residues with hydroxyl groups  or basic groups (K and R) on the side chain at N-terminal, P close at C-terminal, and A and M at the C-terminal position play important roles in α-glucosidase inhibition . The inhVigna unguiculata) interacted with the S2 (GLU205 and GLU206) and S3  active site pockets of DPP-IV. The second study [At least six papers have reported molecular docking studies between DPP-IV and leguminous inhibitory peptides ,61,126 fnd study  and Patend study .The molecular docking of common-bean inhibitory peptides   showed bOne review concluded that inhibitory peptides IPI, VPL, and LPL are very potent DPP-IV inhibitors . In othePhaseolus vulgaris), cowpea bean (Vigna unguiculata), Bambara bean (Vigna subterranea), soybean (Glycine max), and yellow field pea bean (Pisum sativum) have been the protein sources in antidiabetic α-Amylase, α-Glucosidase, and DPP-IV inhibitor studies to date. The studies describe sample preparation, protein extraction, hydrolysis, fractionation, inhibitory assays, molecular-mass profiling, peptide sequence identification, the potential bioactivity prediction of the peptide, computational modelling, and enzyme kinetics. Variations in legume cultivars and methods affected the release of peptides. Different methods were used in sample preparation, which include fermentation , germination (t), and pre-cooking; in protein extraction, including alkaline extraction isoelectric precipitation, phosphate buffer extraction, and water extraction; in protein hydrolysis, enzyme types and combination, enzyme substrate ratio, pH, and time; and in enzyme inhibitory assays’ positive control type and concentration, inhibitor or peptide concentration, and units of inhibitory activity. The categorization of the relative scale of inhibitory activities among legume samples becomes difficult due to these method differences. Peptide fractionations used ultrafiltration membranes from 1 to 100 kDa, ion-exchange chromatography, gel filtration, or reversed-phase high performance liquid chromatography (RP-HPLC). Semi-preparative peptides were obtained using solid-phase methods and standard 9-fluorenylmethyloxycarbonyl (Fmoc) chemistry. Peptide sequences in samples were identified by means of HPLC/MS. Software and online tools were used in bioactivity prediction and computational modelling. The identification of the types and locations of chemical interactions between inhibitor peptides and enzymes and the type of enzyme inhibition were achieved through computational modelling and enzyme kinetic studies.The common bean (The highest activity of α-amylase inhibition ranged between 14.9 and 89.1% relative to acarbose and between 57.48 and 101.61% in non-acarbose assays. The highest activity of α-glucosidase inhibition ranged between 22 and 97.34% inhibition relative to acarbose and 34.73% in non-acarbose assays. The highest activity of DPP-IV inhibition ranged between 47.94 and 96.7% inhibition. Peptide inhibitory activity against α-amylase, α-glucosidase, and DPP-IV was demonstrated to depend on its ability to dock at the enzyme catalytic sites. Studies, however, did not indicate the mechanism of how antidiabetic peptides are released into the human digestive system, absorbed into the blood stream, and transported to the target sites.Further research on leguminous antidiabetic peptides is needed to investigate protein sources from other legumes; the allergenicity and safety of the peptides; the actual sequence of events and the molecular determinants dictating the inhibition mechanism; and the stability, efficacy, and the bioavailability of the peptides. In addition, encapsulation and sensory studies are needed to reduce the typically bitter taste of hydrophobic amino acids; feeding studies using human volunteers are also needed. Lastly, when consumed as legumes in which peptides are still in their parent protein sequence, the yield following peptide release in the human digestive system is still unknown, especially when present in different matrices, macronutrient interactions, and dietary factors. This information is crucial when suggesting the incorporation of legumes into other starch-containing foods or as ingredients in normal diets.As legumes are an economical dietary protein source, research to explore antidiabetic peptides from other legume sources is needed;Some proteins may cause allergic reactions, and studies on allergenicity and safety of antidiabetic peptides are suggested;The mechanism of how antidiabetic peptides are released into the human digestive system, absorbed into the blood stream, and migrated to the target sites is not fully understood. Moreover, at the molecular level, the actual sequence of events and the molecular determinants dictating the inhibition mechanism are far from being understood, requiring an interdisciplinary approach, such as from nutrition and biomolecular science;When consumed as peptides, the harsh environment in the human digestion tract may cause changes in the peptides that will affect their bioactivity and bioavailability. Hence, peptide stability, efficacy, and bioavailability studies would assist in determining the dose of peptide intake;Low-molecular-weight peptides composed of hydrophobic amino acids are typically bitter, and the application of these peptides in foods without affecting the sensory profile will require a special process such as micro- or nanoparticle encapsulation. Research in this area may offer solutions not only for elucidating sensory aspects, but also bioavailability, bioactivity, and safety;Feeding studies using human volunteers will be required prior to the application of the inhibitory peptides as ingredients in the diets, in functional foods, or as nutraceuticals or pharmaceuticals supplements.The positive results of the in vitro studies prompt the need for further research on leguminous antidiabetic peptides, as follows:


Human serum albumin (HSA) is the most abundant plasma protein in circulation. The three most important drug-binding sites on HSA are Sudlow’s Site I (subdomain IIA), Sudlow’s Site II (subdomain IIIA), and Heme site (subdomain IB). Heme site and Site I are allosterically coupled; therefore, their ligands may be able to allosterically modulate the binding affinity of each other. In this study, the effects of four Heme site ligands  on the interaction of the Site I ligand warfarin with HSA were tested, employing fluorescence spectroscopic, ultrafiltration, and ultracentrifugation studies. Our major results/conclusions are the following. (1) Quenching studies indicated no relevant interaction, while the other fluorescent model used suggested that each Heme site ligand strongly decreases the albumin binding of warfarin. (2) Ultrafiltration and ultracentrifugation studies demonstrated the complex modulation of warfarin–HSA interaction by the different Heme site markers; for example, bilirubin strongly decreased while methyl orange considerably increased the bound fraction of warfarin. (3) Fluorescence spectroscopic studies showed misleading results in these diligand–albumin interactions. (4) Different Heme site ligands can increase or decrease the albumin binding of warfarin and the outcome can even be concentration dependent . Human serum albumin (HSA) is the most abundant plasma protein 35–50 mg/mL) in circulation ,2. HSA i–50 mg/mLK) of WAR–HSA complex is approximately 2 × 105 L/mol (logK ≈ 5.3)  is the concentration of albumin (unit: mol/L). UV-Vis spectra were recorded in PBS (pH 7.4) at 25 °C, employing a Jasco V730 UV-Vis spectrophotometer . Absorption spectra of Heme site ligands (5.0 μM each) have been recorded without and with increasing concentrations of HSA . Binding constants :The following equations are implemented in the Hyperquad program code: K) are defined by β:The stepwise association constants . Emission spectra of HSA (2.0 μM) were recorded in the absence and presence of the increasing concentrations of Heme site ligands . Before the evaluation of emission intensity data at 340 nm, the inner-filter effect of ligand molecules was corrected using the following equation  is the molar concentration of the quencher (Heme site ligands). The Hyperquad program code used is defined in Equations (2)–(7).Ligand–HSA interactions were evaluated with linear and non-linear fitting, using the graphical application of the Stern–Volmer equation  and the ex = 295 nm).In another experiment, fluorescence quenching studies were also performed in the presence of standard concentrations of HSA (2.0 μM) and Heme site ligands (each 1.0 μM), with increasing concentrations of the Site I marker WAR . Thereafter, the changes in the fluorescence emission signal at 340 nm were compared and evaluated (λex = 317 nm) [Finally, the effects of BIL, BVD, HEM, and MO were tested on the fluorescence signal of WAR–HSA complex. The interaction of WAR with HSA results in the strong increase in its fluorescence emission signal of WAR at 379 nm (λ 317 nm) . Therefo 317 nm) ,50, whil 317 nm) . EmissioEffects of BIL, BVD, HEM, and MO on the albumin-bound fraction of the Site I ligand WAR were examined by ultrafiltration ,49. Amicg and 20 °C applying a Beckman Coulter Optima MAX-XP tabletop ultracentrifuge (with MLA-130 fixed-angle rotor) [With the optimal conditions of ultracentrifugation, we can sediment the albumin fraction of a solution without the disruption of ligand–HSA interactions ,56,57. Cv/v%) as the mobile phase. WAR was detected at 390 nm (λex = 310 nm).We applied an integrated HPLC system  built up from an autosampler AS-4050), a binary pump (PU-4180), and a fluorescence detector (FP-920). Chromatographic data were evaluated employing ChromNAV2 software . WAR concentrations were quantified using the previously reported method ,50. Brie, a binarp < 0.05 and p < 0.01.Statistical significance was established by one-way ANOVA (with Tukey’s post hoc) test, employing SPSS Statistics software . The level of significance was set to The interactions of certain Heme site ligands  with HSA were tested employing UV-Vis and fluorescence quenching studies, where data were evaluated with both linear and non-linear fittings. These investigations underline that different spectroscopic techniques and data evaluation strategies can strongly affect the binding constants determined. Furthermore, the impacts of the above-listed Heme site ligands were examined on the interaction of the Site I ligand WAR with HSA, employing fluorescence spectroscopic, ultrafiltration, and ultracentrifugation techniques. Quenching studies gave only semi-quantitative results and showed no relevant effects of Heme site ligands on WAR–HSA interaction. The other fluorescent model  suggested that each Heme site ligand strongly decreased the albumin binding of WAR. However, ultrafiltration and ultracentrifugation studies demonstrated the complex modulation of WAR–HSA interaction by the different Heme site markers. In a concentration-dependent fashion, BIL strongly decreased while MO considerably increased the bound fraction of warfarin. Moreover, the low concentrations of BVD and HEM enhanced the albumin binding of WAR, while their higher concentrations caused a gradual increase in the filtered fraction of the Site I ligand. Another interesting observation is the fatty acid-induced remarkable increase in the emission signal of WAR, due to the increased albumin binding of the Site I ligand and the elevated fluorescence of the WAR–HSA complex in the presence of palmitic acid and stearic acid. Herein, we present novel data in regard to the impacts of BIL, BVD, HEM, and MO on the albumin binding of the Site I marker drug WAR. Our study highlights the complex modulation of WAR–HSA interaction by different Heme site ligands and strongly underlines the limitations of fluorescence spectroscopic studies in diligand–albumin models.


This paper presents the data from model-scale experiments on shallow water ice-structure interaction. The data is related to the original research article ‘Model-scale tests on ice-structure interaction in shallow water: Global ice loads and the ice loading process’ Lemström et al.(2022)[1]. During the conducted experiments, a ten-meter wide initially intact ice sheet was pushed against a sloping structure of the same width. As the ice failed against the structure, a grounded rubble pile accumulated in front of it. The structure consisted of ten identical one-meter-wide segments and the horizontal load on each of these segments was measured independently with load cells. These measurements are presented as load-time datasets. The horizontal load acting on the false bottom was measured with load cells and are also presented as load-time datasets. Furthermore, the ice pressure on two of the segments was measured with tactile sensors. These pressure measurements are presented as array-based pressure-time datasets. Video footage filmed from two different video angles is published. In addition, the coordinates of the rubble pile geometries at the end of each experiment are published. The data includes the top and side rubble pile geometries. In total, seven experiments were conducted. The data can be used by researchers, engineers and designers who work with ice structure interaction related issues in order to, for instance, optimize the design of offshore structures, improve ice load predictions or develop future experiments and simulations. The cascaseA_structure_load.txt, where For each case, load-time datasets and two video files from the experiment are published. The file with the filename caseA_bottom_load.txt include the load data measured from the bottom. The first column shows the time in seconds [s] and columns 2–5 show the horizontal load in Newtons [N], measured with four load cells attached to the false bottom. The columns are tab separated. Files with the filename caseA_pressure_segB.csv include the data measured from segments 5 and 6 by using tactile sensors. Only these two segments were instrumented with the tactile sensors. The files named caseA_videoC.mp4, where The video files are in MP4 format and named caseA_geometry_above.txt, caseA_geometry_side_top.txt and caseA_geometry_side_bottom.txt include the coordinates for the top pile profiles, above-water side and below-water side rubble pile profiles, respectively, at the end of each experiment. caseA_geometry_above.txt, the first column describes the caseA_geometry_side_top.txt and caseA_geometry_side_bottom.txt, the first column describes the The rubble pile geometry data is also published. The files named 22.1The model-scale experiments were conducted in the Aalto Ice Tank. The experimental set-up and the instrumentation used are presented in ce basin . The segThe retrievable bottom extended 4 m away from the structure . The botThe local ice pressures from segments 5 and 6  were mea2.2The model ice used in the experiments was granular and produced with the standard ice production techniques of the Aalto Ice Tank The flexural strength of the ice was measured in-situ with the cantilever beam method, as recommended by the International Towing Tank Conference (ITTC) This article does not involve the use of human or animal subjects.Ida Lemström: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Visualization. Arttu Polojärvi: Conceptualization, Methodology, Supervision, Writing – review & editing. Otto Puolakka: Methodology, Writing – review & editing. Jukka Tuhkuri: Conceptualization, Writing – review & editing.The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.


UiO-66-TLA was successfully synthesized as indicated by various characterization results. The adsorption kinetics conformed to the pseudo-second-order model, and the adsorption isotherm conformed to the Redlich-Peterson isotherm. This indicates that BB3 is a multi-parameter model of monolayer/multilayer arrangement on the adsorbent surface, and its rate-controlling step is chemisorption. The adsorption process was non-spontaneous and belonged to an endothermic reaction, in addition, it has great adsorption stability and regeneration The interaction of the modified UiO-66-TLA with BB3 was mainly affected by mechanisms, such as electrostatic interaction, π–π stacking as well as the abundant functional groups on UiO-66-TLA surface. These results demonstrate that UiO-66-TLA is an efficient, regenerable, water-stable material for the removal of BB3 in solution, with practical implications, suggesting its potential as a dye adsorbent.A novel metal-organic framework (MOF) UiO-66-TLA (UiO-66-Trimellitic Acid) was synthesized by one-pot method with trimellitic acid as modifier, which can effectively remove the basic dye Basic Blue 3 (BB3) in wastewater. Modification with carboxyl groups facilitates the adsorption of the cationic dye Basic Blue 3. The adsorption of BB3 by the modified UiO-66-TLA was significantly greater than that of its parent MOF. The adsorption capacity of the modified UiO-66-TLA for BB3 (234.23 mg g Metal-organic frameworks (MOFs) are crystalline coordination compounds whose periodic structures are composed of metal cations and clusters connected by organic linkers. . MOFs ar−1. 2  for rhodamine B, which was regenerative. After modification with -NH2, 2 exhibited high adsorption capacity for cationic dyes. Furthermore, the porosity and high surface area of UiO-66-NH2 are favorable for adsorption and preconcentration of metal ions. , have been applied to the adsorptive removal of toxic chemicals from aqueous solutions. . Adsorptal ions. . These w2 with significantly improved selective adsorption of methyl bromide and methylene blue.  was synthesized to adsorb different dyes from wastewater, and the maximum adsorption capacity of methylene blue (MB) and basic fuchsine (BF) was 299.8 and 789.2 mg⋅g−1, respectively. (2 for the adsorption of toxic dyes remains to be investigated.Zhang synthesized zeolitic imidazolate framework-8 (ZIF-8)-loaded UiO-66-NHne blue. . UiO-66-ctively. . To date2 to synthesize a novel and stable MOF containing both amino and carboxyl bifunctional groups. In general, the adsorbent will adsorb more anionic dyes after modification with -NH2, and more cationic dyes after modification with -COOH. Modification of UiO-66-NH2 with trimellitic acid can more effectively remove cationic dyes (basic dyes) in wastewater. Basic blue 3 (BB3) is used for dyeing wool/nylon and stick/acrylonitrile blended fabrics. It is also used for direct printing of acrylic carpets with rich colors and this basic dye has obvious toxicity, such as mutagenic and carcinogenic effects.  was easily synthesized in bulk by a simple hydrothermal method, and its structure and morphologies were investigated. The cationic dye BB3 was adsorbed from the dye system with -COOH from the UiO-66-TLA sorbent. Through batch adsorption experiments, the effects of pH, time, initial concentration, and temperature on the adsorption process, as well as the adsorption kinetics, were investigated. The thermodynamics and adsorption isotherms were evaluated; the adsorption capacity of the adsorbent was calculated; and the adsorption mechanism was explored. Adsorption experiments were conducted to study the effects of adsorption isotherms, kinetics, thermodynamics, and pH, and the UiO-66-TLA material was characterized by SEM, TEM, EDS TGA, XRD, XPS, FT-IR, and BET.4, 98%), N,N-dimethylformamide (HCON(CH3)2, DMF, 99.5%), 2-aminoterephthalic acid , trimellitic acid , HCl (37.0%), methanol , glacial acetic acid , basic blue 3  were used in the experiments. All chemical reagents were analytical grade, and no further purification was required. Deionized water produced in the laboratory was also used.Zirconium chloride (ZrCl4 (0.3673 g) was dissolved in DMF (14.583 ml), and HCl (2.917 ml) was added, then the mixture was sonicated for 20 min first. Next 2-aminoterephthalic acid  and DMF (30 ml) were added in succession, which was sonicated for 20 min again. Subsequently, trimellitic acid  was added, and the mixture was sonicated for 20 min to mix uniformly. The solution was transferred to a 100 ml sealed bottle and heated in an oven at 80°C for 24 h under self-pressure. When the reaction was completed, it was cooled to room temperature, filtered, and dried. The product was purified several times with anhydrous methanol and DMF, and then dried at 80°C for use. It is worth noting that all the filtration steps was performed while the solution was hot, as the solubility of trimellitic acid is greater at higher temperature.The synthesis of UiO-66-TLA was based on a previously reported one-pot hydrothermal method, with slight modifications. . Briefly−1 at resolution of 4 cm−1). The BET specific surface area and pore size distribution were determined using a nitrogen adsorption-desorption apparatus. The Zeta potential of the samples was measured at room temperature using Malvern Instruments Ltd. Dye ion concentrations were measured using UV-Vis spectroscopy.The morphology, microstructure, and elemental composition of the samples were observed using field emission scanning electron microscopy , transmission electron microscopy , and energy dispersive spectroscopy (EDS). X-ray diffraction  was used to determine the phase composition of the samples. The valence states and distribution of chemical elements in the adsorbent were analyzed by X-ray photoelectron spectroscopy  in the 2θ range of 5°–30°. The changes in the functional groups on the adsorbent surface were investigated by infrared  was added to an aqueous solution of BB3 (30 ml), and the resulting mixture was stirred in a thermostatic shaker. After adsorption, the clear filtrate was collected by suction filtration using a microfiltration membrane, and the concentration of BB3 was determined with a UV-Vis spectrophotometer. By setting different reaction times, the adsorption kinetics with an initial concentration of 300 mg/L were studied, and the adsorption equilibrium time was obtained. To explore the maximum adsorption capacity of the adsorbent, isotherm studies were conducted in the range of initial BB3 concentration of 100–500 mg/L. After shaking for 2 h, the remaining BB3 concentration in the supernatant was measured, and the adsorption capacity was calculated.To study the adsorption kinetics of BB3 on UiO-66-TLA, 30 mg of UiO-66-TLA and 30 ml of 300 mg/L BB3 solution reacted for a certain time . For the isotherm study, 30 mg adsorbent and 30 ml BB3 solution reacted for 2 h, and the BB3 concentration range was 100–500 mg/L. The data were fitted and analyzed by Langmuir, Freundlich, and Redlich Peterson models. To explore the adsorption of BB3 by UiO-66-TLA at different temperatures, the thermodynamic parameters were studied at 298, 313, and 328 K.2 and UiO-66-TLA are presented in 2 is a regular clustered octahedral particle, which is similar to previous reports. ), carbonyl (ν(C=O)), and amino (ν(C-N)) stretching vibrations, respectively. 1/3C8H3NH2O4. (centers. . When thH3NH2O4. . The masH3NH2O4. .0 < 0.2). This indicates the adsorbent is a mesoporous material, with unrestricted monolayer-multilayer adsorption. (2 in 2/g), pore volume (0.529 cm3/g), and pore width (Mode) (10.960 nm) of UiO-66-TLA significantly decreased. , which was significantly higher than the correlation coefficient R2 (0.89058) of the pseudo-first-order model. Thus, the adsorption behavior of BB3 on UiO-66-TLA was more precisely described as chemical adsorption.The kinetic parameters of different models were obtained by kinetic fitting of the experimental data in t and t1/2 of BB3 on UiO-66-TLA, which was not linear over the course of the entire experiment. The trace was divided into three steps, indicating that the adsorption process was not affected by a single diffusion factor. Rather, membrane diffusion, intraparticle diffusion, and surface adsorption all contribute to the adsorption kinetics. Theirs slopes are expressed as K1 > K2 > K3, respectively. The adsorption sites and adsorption rate gradually decreased with time.To further explore the intraparticle diffusion adsorption of BB3 on UiO-66-TLA, an intraparticle diffusion model was investigated. 2 were 234.23 and 121.24 mg g−1, respectively. The effect of concentration and adsorption isotherm experiment of BB3 on UiO-66-NH2 has been done, and its related experimental data have been sorted into the supporting material , crystal violet (CV), basic blue 3 (BB3), methylene blue (MB) and bromophenol blue (BPB), and their concentrations are all 200 mg/L. Take 30 mg of adsorbent and 30 ml of waste liquid into a conical flask, shake for 2 h at room temperature, and then conduct solid-liquid separation. The dye ion concentration before and after adsorption was determined by UV-Vis. The 2 for each dye in wastewater. By comparison, it is found that UiO-66-TLA in wastewater is selective to BB3, and the adsorption effect is better than that of UiO-66-NH2 before modification. The modified UiO-66-TLA contains carboxyl groups, which is beneficial to the adsorption of the cationic dye BB3. The modified adsorbent also has a certain adsorption effect on the anionic dye BPB, which may be due to its amino group. The carboxyl functional groups linked by chelation may occupy part of the site, making the adsorption effect partially weakened.The selective adsorption of BB3 by UiO-66-TLA in practical application was studyed by using laboratory wastewater, and a comparative experiment was carried out with the selectivity of UiO-66-NHThe reusability of the adsorbent is an important factor in water purification applications. The filtered adsorbent was washed 3 times with HCl for each adsorption. After drying under reduced pressure, the adsorbent is used for next cycle of dye adsorption. . There aThe adsorption mechanism of BB3 on UiO-66-TLA was explored using SEM, TEM, EDS TGA, XRD, XPS, FT-IR, and BET on UiO-66-TLA after adsorption. The SEM images of UiO-66-TLA-BB3  show dye−1, which was attributed to the alkyl C-N stretching vibration. . Thus, the modification significantly improved the maximum adsorption capacity. The adsorption of BB3 by UiO-66-TLA conformed to the pseudo-second-order kinetics model and the Redlich-Peterson model, indicating that it is a chemical adsorption process. In addition, the adsorption of BB3 by UiO-66-TLA is a multilayer form. From thermodynamic studies, the adsorption capacity of UiO-66-TLA for BB3 increased with increasing temperature, indicating the adsorption is an endothermic reaction. The trimellitic acid-modified UiO-66-TLA makes the carboxyl group and the amino group exist at the same time, which is not only conducive to the adsorption of cations, but also has a good adsorption effect on anionic dyes. Electrostatic attraction and π–π stacking between BB3 and UiO-66-TLA were the predominant adsorption interactions. Furthermore, the crystal structure of UiO-66-TLA remained intact after being placed in water at 80°C for 8 days, with good reusability.A novel and stable metal-organic framework material, UiO-66-TLA, was prepared by one-pot method to remove basic blue 3 from aqueous solutions. UiO-66-TLA was characterized by FE-SEM, EDS, TEM, XPD, FT-IR, BET, and XPS analysis, and the effects of contact time, concentration, temperature, and pH on the adsorption efficiency were investigated. It was shown that UiO-66-TLA is an efficient material for the removal of BB3 in solution. At 298 K, the reaction reached the adsorption equilibrium within 120 min, and the maximum adsorption capacity was 234.23 mg gIn conclusion, from the present findings, UiO-66-TLA is an efficient, regenerable, water-stable material for the removal of BB3 in solution, with practical implications, suggesting its potential as a dye adsorbent.


For the best part of my entire career, I have focused on the marginal ice zone, abbreviated to MIZ by most sea ice scientists. Defined perfunctorily by the National Snow & Ice Data Center as the part of the seasonal ice zone where waves, swells and other open ocean processes affect the sea ice, the MIZ habitually extends from the ice edge some 100–200 km into the ice pack with morphology that varies dramatically spatially and with time. In general, the Antarctic MIZ is wider than MIZs in the Arctic, recognizing that increases in the ferocity and incidence of storms and the durability of ice due to global climate change are already affecting the physical attributes of each MIZ. I provide here a somewhat historically tailored preamble to a unique compilation of up-to-the-minute MIZ research in this theme issue that includes the nexus between contemporary theoretical, modelling and experimental projects. A prognosticative synopsis of these projects is also included later in the volume, framed in the context of the ongoing ontogenesis of the research field.This article is part of the theme issue ‘Theory, modelling and observations of marginal ice zone dynamics: multidisciplinary perspectives and outlooks’. The good news is that much of this work is directly applicable to the MIZ and was done with that in mind, namely to deconstruct MIZ complexity sufficiently that parsimonious mathematical models could be devised to clarify the most significant physics. The bad news is that whereas considerable theoretical progress has been made, there still remains a dearth of field data to test its validity—essentially because Journal of Geophysical Research [While studies relating to the physics of the MIZ actually date back to the first half of the twentieth century—with classic articles by notable American geophysicists such as Maurice Ewing, Frank Press, Albert Crary and colleagues—and including prescient theoretical work done at the Courant Institute by the applied mathematician Joseph B. Keller, a more intensive period of activity began in the 1960s, exemplified by publications written by Gordon Robin (Weddell Sea), Ken Hunkins (Arctic Ocean) and David Evans (theory). My principal PhD supervisor, Peter Wadhams, engaged in MIZ research from the 1970s and was one of the scientists who pioneered and steered the multi-year MIZEX programme [Research –4 compilMarginal Ice Zone Program [Arctic Sea State and Boundary Layer Physics Program [Philosophical Transactions of the Royal Society A is multifaceted, yet it also targets specific features of MIZs that continue to receive enduring attention. Notwithstanding the immense progress made throughout and immediately following MIZEX, especially in understanding MIZ oceanography and meteorology, this emphasis arises because of the staggering complexity of the processes occurring in the MIZ in regard to how it influences and is influenced by the neighbouring open ocean and contiguous interior pack ice. Global climate warming has intensified and increased the frequency of storms since MIZEX as well, recalling that ocean waves and swell are a prime determinant of MIZ morphology—in fact, of whether an MIZ forms at all and of how it matures. Accordingly, three dominant themes emerge in the documented research that follows this preface: wave propagation across the MIZ; floe size distributions; and sea ice dynamics and breakup. A mini review that considers the wider implications of each topic to other areas of science precedes more technically orientated papers, but it is also important to recognize that the substance of the three threads is intertwined with ocean wave impacts having preponderant leverage.The comparatively recent  Program  and the  Program  in which Program ,8 have fMy personal interest in wave-ice interactions was originally stimulated by Gordon Robin and nurtured by Peter Wadhams, although my background initially engendered a greater proclivity towards mathematical modelling as opposed to experiment. This mindset changed rapidly as I discovered the delights of fieldwork in the polar and subpolar seas of both hemispheres and came to believe passionately that the development of theory and the gathering of validating data must be undertaken collaterally. The three reviews –11 I havAlthough I have published papers that employ more sophisticated rheologies to describe sea ice, e.g. my quixotic foray into thermorheologically simple materials during my PhD and, much later, my work on power law fluids, the austere Kirchhoff–Love plate with or without viscosity has served me and others well. In sum, my obsession has been to solve linear boundary value problems for different topographical situations, e.g. waves impinging on free edges, open and closed cracks, changes of thickness, changes of sea ice freeboard and draught, inhomogeneity, etc. Each of these situations is directly applicable to the MIZ—albeit a rather perfect one, but we have endeavoured to introduce randomness to the distribution of ice floes present in order to increase geophysical credibility. From the outset, my success has been predicated on a steady stream of wonderfully capable PhD students and postdoctoral fellows who have willingly shared their mathematical ingenuity and computational prowess with me. I owe them a great deal but so too does MIZ science, as will be evident in the papers that appear in this volume because our contemporary understanding of ocean wave propagation across the MIZ feeds directly into how the waves reshape it by breaking up floes and are continuously affected by the emerging floe size distribution. This leads to adjustments in the coupling and fluxes between the atmosphere above the MIZ and the ocean beneath, with a consequent transition in its dynamics.. 2in situ experiments are phenomenally difficult to carry out because nature is unsympathetic and rarely obliges with the right conditions. I have personally witnessed the sea ice breaking up just before instruments were installed, ice breakup during deployment that involved a hasty retreat across opening cracks on a snowmobile, an ice floe obliterating our instruments on an adjacent floe by rafting over it and more than 200 km of sea ice being annihilated by freak waves while I was enjoying a beer aboard RV Polarstern in the Weddell Sea. Moreover, the technology to conduct such experiments affordably and expeditiously, viz. satellite-tracked buoys with inertial measurement units that can be interrogated remotely, spaceborne interferometric synthetic aperture radar, etc., is relatively new. But the disconnect is perhaps also due to my erstwhile dogmatic yet naive belief that wave-ice interaction can be approached deterministically, i.e. via randomized scattering, dispersion and attenuation arising from the solution of a boundary value problem defined by prescribed solitary floe behaviour, and we need to accept that this approach does not always work for a medium as capricious as the MIZ.Taken on balance, it is evident that a disconnect remains between theory and observation despite the considerable advances that have been made in the development of mathematical theory to simulate how ocean wave trains affect and are altered by continuous sea ice sheets, solitary ice floes, random or specified aggregations of ice floes or ice cakes of simple geometry, different manifestations of sea ice embracing contrasting rheologies and so on. Partly this is undoubtedly due to a lack of field data, as such Holy Grail of geoscience that becomes more imperative as climate warming reshapes the polar and subpolar oceans and brings global repercussions.The corpus of research that follows hereinafter is a concrete step towards broadening our collective thinking about the critical physics of the MIZ for inclusion into fully coupled climate models and, conceivably, Earth system models; a current