Ablation provides key macronutrients (nitrogen and phosphorous) to glacier ice algae in NW Greenland

Domain: neuroscience
Published: 2026-01-28
Editorial outcome: accept

Abstract
Dissolved phosphorus (P) is thought to limit the growth of glacier ice algae, which darken the surface of the Greenland Ice Sheet (GrIS) and enhance surface melt. This contention is largely based on the low level of P concentrations, which are often below the limit of detection of conventional methods. Here, we propose that low-level nutrient analysis is essential to understand the macronutrient limitation of glacier algal growth on the GrIS. We sample surface (≤5 cm) and shallow (5−10 and ~80−90 cm depth) ice from two sites in NW Greenland and measure the nano-molar concentrations of dissolved nitrogen (N) and P using a custom-built continuous segmented flow analyser. Quantifiable concentrations of these macronutrients are present, along with glacier ice algal abundances comparable to those of the Dark Zone, a zone of biologically enhanced ice sheet melting. Mass balance calculations for each site indicate that N and P released during seasonal ablation exceed the amounts incorporated into glacier ice algal biomass. These results suggest that dissolved macronutrients are unlikely to limit glacier ice algal growth on the Greenland Ice Sheet.

Introduction
The melt zones on glaciers and ice sheets worldwide are hotspots for microbial activity during the summer1–3. Surface ice on the Greenland Ice Sheet (GrIS) has consistently darkened during the summers of the last 20 years4–6 due to the growth of Streptophyte glacier ice algae7,8, a microalgae with a characteristically dark purple phenolic pigment9–11. The growth of these algae decreases the surface albedo by between 0.13 and 0.25 in areas with low (103 cells mL−1) and high (104 cells mL−1) biomass, respectively, increasing surface melt rates12. This seasonal darkening is most noticeable in the Dark Zone, identified as the area along the South-West margin of the ice sheet6. Glacier ice algae are endemic to most ice surfaces3, yet the controls or promoters of their growth are not well understood.

One of the likely controls on growth is macronutrient limitation. Carbon (C), nitrogen (N) and phosphorous (P) are the building blocks of life, being essential for cellular mass and metabolic activity13. Carbon is readily available to primary producers at the ice surface from atmospheric CO2 fixation. However, atmospheric N and P inputs to the ice surface are thought to be limited, other than those derived indirectly from snow and ice melt. More recently, attention has focused on the potential of atmospheric dust to fertilise the ice surface14–16. Bioavailable dissolved inorganic N (DIN; mostly ammonium [NH4+] and nitrate [NO3-]) is primarily derived from snow and ice melt17,18, or from nitrogen fixation in cryoconite holes19. Bioavailable P, often quantified as soluble reactive phosphorous (SRP), is largely derived from the chemical weathering or bio-mining of mineral dusts containing P-bearing minerals such as apatite, originating either from wet (snow and more often now rain) or dry deposition or melted out of meteoric ice14,15,20,21.

A few studies assessed macronutrient concentrations in surface ice and melt water samples collected within the Dark Zone of the GrIS, but conclusions may be limited by the relatively high detection limits of the analytical methodology in relation to the low concentrations of dissolved N and P species18,22. Dissolved N and P concentrations in surface ice melt are typically low17,18,23, often sub-micromolar, and near the detection limit of most standard automated spectrophotometric and IC analytical methods previously used in these environments. Recent studies suggest that concentrations of various nutrients may be higher in the micromelt (i.e., a thin layer of melt water of the surface of melting ice crystals) than in the bulk ice crystals24. However, even in these samples, the concentration of PO43-, NO3-, and NO2- was largely below the limit of detection (LOD)24. Dissolved organic N and P (DON and DOP) may be present in much higher concentrations22, but it is currently unclear whether these species are readily utilised by the glacier ice algae.

We contend that our knowledge of the potential limitation of the macronutrients on glacier algal growth is hampered by the high limit of detection of most conventional spectrophotometric analytical methods. We illustrate the need to accurately measure low concentrations by determining the mass of this macronutrient released from melting ice during the ablation season and comparing this with the mass of macronutrient contained in the pool of algae in the surface ice. We show that nutrients may appear to be limiting due to their low, nanomolar concentrations, but that since only a very small mass of nutrient is needed to maintain the population of glacier ice algae at the surface, these low concentrations, otherwise thought to denote oligotrophic conditions, may be sufficient to meet algal metabolic demands.

Here, we analysed samples from two sites in northwest Greenland (Fig. 1b), where seasonal darkening has been observed25–27, one on the Qaanaaq Ice cap, and the other on the nearby GrIS, and quantified the concentration of macronutrients present in the surface ice. We collected shallow ice cores (~80–90 cm in depth) and analysed three primary sections (Fig. 1c): (1) the topmost 5 cm of ice – the weathering crust (WC); (2) the transition zone (TZ) linking the weathering crust to the underlying unweathered ice (5–10 cm depth); and 3) the bottom 5 cm from the base of each ice core – representing the fully unweathered (UW) ice (density >0.91 g cm−328). In addition, we collected adjacent surface WC samples from a ~2 m2 area using a field-conditioned ice axe to scrape off the top layer (~3 cm) of the weathered ice. The loose surface ice samples were homogenized and stored in 2 L Whirlpak® bags. Both ice core samples and surface samples were melted in a field laboratory and filtered using in-line 0.45 µm PES filters into acid washed falcon tubes and frozen at −20 °C until analysis. We used a custom-built continuous segmented flow analyser fitted with a 250 cm flow path29. The 10- to 100-fold increase in path length, compared to most commercially available nutrient analysers, enabled accurate quantification of nanomolar concentrations of SRP and DIN. Alkali persulphate digestions30 were undertaken to quantify DOP and DON concentrations in our samples. We then used macronutrient mass balance calculations to determine how much meteoric ice melt is required to provide the macronutrients we estimate are held within the surface glacier ice algae, and then examined stochiometric ratios of N:P and assessed the potential for N and P limitation. Finally, we make the case that low-level nutrient analyses are an essential prerequisite for conducting nutrient limitation studies on the GrIS.

Results
Nutrient availability at and below the weathering crust
Our custom-built continuous segmented flow analyser was able to quantify SRP and DOP in all samples collected. Median SRP concentrations were broadly similar in both the Qaanaaq ice cap and Greenland ice sheet samples (Fig. 2a). Values ranged from 35 ± 12 nM and 28 ± 8.0 nM for surface (WC) samples and 18 ± 6.0 nM and 20 ± 7.0 nM for the UW samples at Qaanaaq and GrIS, respectively. Median DOP, defined as total dissolved P (TDP) minus SRP, was lower at the GrIS site than in Qaanaaq, particularly at the surface (WC; 47 ± 19 nM and 96 ± 49 nM, respectively). The transition zone (TZ) samples from Qaanaaq showed wider ranges of concentrations than the GrIS site. The median SRP and DOP concentrations at the surface (WC samples) were higher than the sub-surface concentrations (TZ and UW samples) at both sampling locations. However, the differences were only statistically significant for DOP at Qaanaaq (Supplementary Information, Figure S2). We caution that the DOP concentrations measured at the ice surface may be overestimated, since lysis of algal cells may occur during the melting of the samples and/or during filtration. We estimate that lysis of only between 2.8 to 3.8% of the cells counted at Qaanaaq (mean value: 2.4 × 105 cells mL−1) and GrIS sites (mean: 0.75 × 105 cells mL−1), respectively, would be sufficient to produce the DOP concentrations measured in the ice surface samples (see Supplementary Information text and, Table S1).

Total P (TP) concentrations measured in ice cores from the North Greenland Eemian (NEEM) drilling site were high and variable (7 − 637 nM), but it is important to note that TP was analysed on unfiltered samples, and so likely contain mineral bound-P. These TP concentrations are dependent on the age and climate interval that was sampled, and correlate with the dust content20, suggesting that particulates in the unweathered ice have the potential to be a source of at least some dissolved P. We have determined TDP on filtered samples and so have excluded particulate P contributions. However, our TDP values (means ranging from 36–142 nM; Table 1) lie within the wide range of TP values measured at NEEM. The SRP concentrations reported here (Table 1), are an order of magnitude higher than those measured in firn cores from the North East Greenland Ice Stream (NEGIS) ice core sampling site, within the GrIS accumulation zone (mean SRP at NEGIS: 2.7 nM21). The concentration of SRP measured in our samples were mostly within the range measured in NEEM ice core samples (SRP within NEEM: 3.0–32 nM20), however, some of the SRP concentrations in our samples were up to four times higher than the upper values found at NEEM (Table 1).

Dissolved N-species were predominantly inorganic in all samples (Fig. 2b). DIN concentrations were lowest at the surface. The median surface DIN concentration was 0.8 ± 0.7 µM and 2.2 ± 2.7 µM at Qaanaaq and GrIS, respectively (Table 1). Whilst in UW samples the concentrations were and 3.0 ± 0.3 µM and 4.3 ± 0.9 µM, at Qaanaaq and GrIS respectively. The dominant DIN species was NH4+, which comprised roughly 60% of the total DIN in the GrIS samples (Fig. 3), and up to 85% in surface ice at Qaanaaq (Fig. 3). The scatter in the dataset limits the ability to detect statistical differences between depths and sites; statistically significant differences are presented in the supplementary information (Figure S3–S6). Our custom-built analyser also allowed us to quantify very low nitrite (NO2-) concentrations (LOD=1.5 nM). Although NO2- only makes a small fraction of the DIN pool, our data show that the concentrations were between five and 10 times higher in surface samples (14 ± 5.4 nM and 25 ± 6.9 nM at GrIS and Qaanaaq, respectively) in comparison with those at depth (between 2.0 ± 2.6 nM and 3.7 ± 2.6 nM in UW samples). DIN concentrations were lower than those measured during the early melt season in wet surface ice and snow within the Dark Zone (2.3–5.2 µM18), when there were low light levels at the ice surface due to the overlying wet snow. However, the median concentrations in unweathered ice samples were similar (2.8–6.2 µM18). Other studies, conducted near Kangerlussuaq (Southern Greenland), later in the melt season, showed similar surface NO3- concentrations to ours (mean 0.6 µM31). Hence, the timing of our sample collection is likely linked to the relatively low surface concentrations of DIN and NO3-. The relative increase in NO2- at the surface (Table 1) could arise from atmospheric deposition or, potentially, be indicative of nitrification processes, which are associated with cryoconite granules32,33.

Dissolved organic N concentrations were highest at the surface (median concentrations of 2.0 ± 1.5 µM and 1.3 ± 1.4 µM at Qaanaaq and GrIS, respectively; Table 1), with lowest concentrations at the base of the ice cores (median UW concentrations of 0.3 µM at both Qaanaaq and GrIS; Table 1). As with DOP, the higher DON surface concentrations at Qaanaaq might be due to a methodological artefact arising from cell lysis (see Supplementary Information text and Table S1), in this case, hydrolysis of roughly 2.2% or 3.5% of the cells present would produce similar concentrations of DON.

The general pattern observed at both sites is that DIN is depleted at the surface relative to the deeper unweathered ice. This is consistent with the active uptake of nutrients by microbes, including glacier ice algae, that bloom primarily at the ice surface (WC samples). This matches a recent study, which suggests that glacier ice algae can utilise both NO3- and NH4+ as sources of N at similar rates34. Elevated concentrations of DON and DOP at the surface may be, in part, an artefact of sample processing, but could also arise as a result of algae accumulation and exudation of organic compounds under natural conditions. The concentrations of DON at these sites were relatively low compared to previously reported DON concentrations measured on the surface of the GrIS during spring, ~1300 km to the south, on the GrIS in the Dark zone site near Kangerlusssuaq (5.1 to 14.0 µM22), despite between seven to 10 times higher cell counts found at our sites. Although methodological artefacts may have also inflated the DON concentrations measured in previous studies, it is also possible that natural, overwinter lysis of dormant algal cells may contribute to the high concentrations found in spring22. Natural lysis of cells occurs due to factors such as viral35 or fungal infection36, and studies have found approximately 10% of cells within a population have been found to be inactive or dead34, which may impact the concentrations of organic N and P measured.

The exception to this pattern is SRP, which is elevated in the surface ice and may arise from surface dust dissolution and mineralization processes. Although we have only a few measurements of particle loadings, these show higher values in the samples from Qaanaaq (average of 26 mg L−1; n=2) than at the GrIS site (average of 8 mg L−1; n=3). The masses include both organic and inorganic particles, yet the higher particle loading is consistent with enhanced dry deposition of local dust at Qaanaaq versus the more remote GrIS site, which is further inland and at a higher elevation. The surface particles in the Qaanaaq samples consisted of approximately 95% wt.% quartz, with minor amounts of feldspar, mostly K-feldspars, and illite. This is consistent with the local geology near Qaanaaq, which consists primarily of quartz sandstones from the Thule sedimentary supergroup37. The dust collected from the GrIS site, while also dominated by quartz, contained amphiboles and a higher proportion of feldspars (including plagioclase feldspars), matching the local geology38. Although hydroxyapatite was found neither in the Qaanaaq nor in the GrIS samples according to XRD and SEM analyses, some of the minerals quantified in our dust samples (in particular the feldspars) may contain trace concentrations of P and so could provide some of the P to the surface ice39. This differs from the mineral composition of the ice-surface dust quantified in the dark zone near Kangerlussuaq14, where a link between hydroxyapatite in the dust and algal biomass could be established. In the samples from this study, the identified K-feldspars can also trace amounts of NH4+40,41, which could also supply some N to the system.

Regardless of the potential contributions from local dust, glacier ice algae have been documented to contain P granules34, indicating that they are able to store P through luxury P uptake mechanisms, as seen in other microalgae42. This P can then be utilised during periods when there would otherwise be P starvation. Finally, DOP is often considered more recalcitrant than SRP, but there is evidence of phosphatase activity by microbes on ice sheet surfaces43. These were primarily associated with cryoconite granules and cryoconite holes, which were also present at both the Qaanaaq and GrIS sites. Together, the concentrations of SRP and DOP measured in the ice surface samples in this current study suggest that the surface ice environments in the Qaanaaq Ice Sheet and the GrIS in this area have sufficient P to sustain the documented glacier ice algal blooms.

Our data show that dissolved inorganic species of both macronutrient N and P are present along with glacier ice algal cell concentrations typical of those found in melting surface ice of the Greenland Ice Sheet20,31. This in turn suggests that macronutrients in this site do not limit glacier ice algal growth in the classical sense, where complete absence denotes limitation. In these sites, the macronutrients are present in nanomolar concentrations and so could perhaps limit growth if the rate of their uptake is concentration dependent. However, we show below that the annual release of macronutrient N and P dissolved inorganic species from unweathered ice by melting alone exceed that of the mass of nutrients estimated in the glacier ice algae at the surface, which may mitigate any kinetic uptake limitation.

How much algal growth can ice melt support?
Summer melting progressively lowers the ice surface, effectively replacing the pre-existing ice surface with deeper ice. Hence, ice melt (ablation) provides a continual fresh source of nutrients to the surface equivalent to the N and P content of the deeper ice. Here, we calculate how much ablation is required to provide the mass of N and P in average glacier algae cells at our sites (Supplementary Information, Table S1). Based on our measurements, we take the average cell counts for each site (2.4 × 105 cells mL−1 in Qaanaaq and 0.75 × 105 cells mL−1 in GrIS), and assuming that the average Ancylonema spp. cell contains 8.8 pM C cell−144, we calculated that the mass of C in the glacier ice algal cells is 1.8 × 106 pmol C mL−1 in Qaanaaq and 7.1 × 105 pmol C mL−1 in GrIS. We then used the median intra-cellular molar C:N and C:P ratios of the glacier ice algal cells of 19 and 509, respectively34, and this resulted in the mass of N and P stored in the glacier ice algae of 9.3 × 104 pmol N mL−1 and 3.5 × 103 pmol P mL−1 at Qaanaaq, and 3.7 × 104 pmol N mL−1 and 1.4 × 103 pmol P mL−1 at GrIS respectively (Supplementary Information, Table S1). Finally, the ablation in units of cm, derived from mL (or cm3) of melt per cm2 of ice surface, required to give rise to these algal N and P masses from the DIN and SRP held in deeper meteoric ice was obtained by simply dividing the mass of algal N or P by the average DIN and SRP of the deeper ice (Supplementary Information, Table S1). The volume of water was converted into ablation of ice by dividing by the ice density 0.91 g cm−3, assuming that 1 g of unweathered ice melt has a volume of 1 cm328. Roughly 212 cm of ablation provides sufficient SRP to balance the estimated P stored within biomass at the surface of the Qaanaaq ice cap, as does 76 cm of ablation at the GrIS site. These values are lower than estimates of recent annual ablation at similar elevations on the Qaanaaq ice cap (~230 cm year−1) and the GrIS site (~100 cm year−145). The ablation required to provide sufficient N from DIN in unweathered ice is smaller, being 34 cm at Qaanaaq and 9.5 cm at the GrIS site. These calculations assume that all of the DIN and SRP is taken up by the glacier ice algae; in reality, the amount of ablation required will be greater because the DIN and SRP uptake efficiency of the algae is unlikely to be 100%, and there is a nutrient demand from other microbes in the microbial ecosystem46. Satellite imagery of the area suggests that 2023 was characterised by particularly high cell abundances47. Yet, it appears that there is sufficient DIN and SRP in the deeper unweathered ice to provide the mass of N and P in the surface glacier ice algal cells, given the present ablation rates at both sites. Thus, at these sites, there is no need for additional sources of P or N from, for example, mineral dust, as has been suggested to be the case in the Dark zone, near Kangerlussuaq14.

Clearly, inclusion of DOP and DON in the calculations decreases the amount of ablation that is required. The annual ablation that is required to produce the amount of N and P in the surface glacier algal cells falls to 32 cm and 105 cm at Qaanaaq, and 10 cm and 27 cm at the GrIS site, respectively. This too assumes that the glacier ice algae can directly take up DOP and DON with an efficiency of 100% and/or that heterotrophic microorganisms take up and recycle DOP and DON to inorganic form with 100% efficiency (i.e., without loss to downstream ecosystems).

Could nitrogen or phosphorous limit growth in the weathering crust?
Previous studies have used the low concentration of P in supraglacial environments, often below the limit of detection, which often ranges from 0.32 µM48 to 0.13 µM18, to argue that P is a limiting factor for microbial growth in these environments14,48,49. The detection limit of our custom-built analyser (2 and 5 nM for SRP and TON) allows us to actually determine the concentrations of both N and P at lower levels than in these previous biogeochemical studies. Nutrient uptake in healthy algal cells often follow the overall mean or median stoichiometric ratios, but this is also dependent on environmental stresses, such as changing light intensity, nutrient limitation and temperature shifts50–53. Furthermore, microalgae may prioritise P uptake and storage after periods of starvation42. Therefore, dissolved N:P ratios within environmental samples should be treated as indicative of potential limitation to glacier ice algal growth, and b should be interpreted with caution. Due to the impact of the dark purple pigment in glacier ice algae on surface albedo10, nutrient limitation in glacier surface samples has often focused on processes affecting Ancylonema spp. growth. Recent imaging of Ancylonema spp. cells by scanning electron microscopy (SEM), combined with energy-dispersive X-ray spectroscopy (EDS), determined within individual cells mean intracellular N:P ratios of 26:1, although there was a large range of N:P values (18:1 to 43:1)34. Ancylonema spp. is part of a wider microbial ecosystem, which includes species with potentially shared or have unique adaptations to different possible limiting factors. The N:P ratios of the bulk organic matter on other sites on the GrIS surface include both an assemblage of microbes and allochthonous matter, and have been reported to have a higher mean N:P ratio of 73:144. Considering that in our samples, both DIN and SRP were always detected in the weathering crust samples, and given that the estimated magnitude of ablation over the summer can provide N and P in excess of the nutrient stored in the glacier ice algae, it is unlikely that these macronutrients limit growth at the sites studied on times scales equivalent to the ablation season (often, up to several months). It is also worth noting that there is a positive correlation between bare ice duration (and consequently melt season length) and surface darkening54. This maybe partially due to a feedback effect, where increased melting releases more nutrients into the system, further sustaining biological activity. However, the distribution of glacier ice algal cells is very heterogeneous55, and ablation rates vary greatly throughout the summer at our and many other Arctic sites56–58, so there are likely to be occasions when nutrient limitation occurs either locally or for periods of days. Examples include localised surface depressions where water-borne transport and deposition have concentrated cells, and prolonged periods of very low ablation rates, in light conditions where ice algae can otherwise grow, but the replenishment of nutrients taken up by the cells via ablation is low.

The ablation required to provide the surface ice algae with N and P is smaller for N than P, suggesting that P will become limiting in these circumstances. It is instructive to examine the dissolved phase N:P ratios to visualise how close the weathering crust is to P limitation. We first examine inorganic N:P ratios, since these are a readily available form of nutrients, where the potential for processing artefacts in our dataset is much more limited. Figure 4a) shows surface (WC) samples have lower inorganic N:P ratios than the deeper (TZ and UW) samples. There is a broad range of surface values at the GrIS site, with a median value of 106:1, while there is a narrower range of surface values at Qaanaaq, with a lower median value of 24:1 (Table 2). Organic N:P ratios followed the opposite trend, with the highest organic N:P values at the surface (Fig. 4b). The median DON:DOP values at the surface were 32:1 and 29:1 at the GrIS site and Qaanaaq (Table 2), respectively, as opposed to the UW DON:DOP values, which were 6:1 at the GrIS site and largely below the LOD at Qaanaaq (Table 2). A combination of DIN+DON and SRP+DOP gives rise to the TDN:TDP ratios (TDN denotes total dissolved N) shown in Fig. 4c. Median TDN:TDP ratios are more similar across the three sampled depths, particularly at the GrIS site. It is noteworthy that five of the six sample groups lie within the range of bulk cellular N:P ratios.

In general, N:P ratios above the calculated bulk cellular or intracellular ratios, shown as green and purple bars in Fig. 4a, suggest that the ecosystem or the glacier ice algae, respectively, may become limited by P, whilst ratios below these values suggest a potential for N limitation. The inorganic N:P ratios of sub-surface ice (TZ and UW samples) all lie above the intracellular N:P ratios, except for some of the Qaanaaq TZ samples, which fall within this range. This suggests that ice melt due to ablation has the potential to become P-limiting at the surface, unless there are, for example, other sources of P to the surface ecosystem, particularly for Ancylonema spp. However, the inorganic N:P in surface ice (WC samples) at Qaanaaq lies within the range of the intracellular N:P range of Ancylonema spp., suggesting that P is not currently limiting for glacier ice algae at this site. Most of the GrIS surface ice (WC) samples lie above the glacier ice algae N:P ratios, suggesting that P is unlikely to limit glacier ice algal growth at present at these sites. There is evidence for balanced growth at an ecosystem level in some samples (Fig. 4a).

Previous studies have found evidence for phosphatase activity in ice surface ecosystems43, allowing the possibility of microbial recycling of DOP. DON may be similarly recycled31, thus the TDN:TDP of surface and sub-surface ice may reveal whether or not the glacier ice algae and the microbial community as a whole are close to balanced growth. We note that the cellular N:P ratio of the whole ecosystem should be treated with caution since its derivation could have included dead cells (Williamson et al. 44). Figure 4c could be regarded as remarkable, in that the majority of GrIS subsurface (TZ and UW) samples lie in the balanced growth for the microbial ecosystem, as do most of the surface (WC) ice samples. Several of the surface samples lie within the field of balanced growth for Ancylonema spp., and some are intermediate between the two boxed ratios.

Qaanaaq samples show the same pattern as the inorganic N:P ratio, with ratios being lowest in the surface, and increasing with depth. Thus, if the microbiome contains functional groups able to recycle organic nutrients, there is sufficient nutrients in the melting subsurface ice to support balanced growth of the microbial community. Liebigs Law of the Minimum, from which the concept of limiting nutrients is derived, was used to describe limiting factors for growth and yield of individual crop plants in agricultural soils, and not for biologically diverse ecosystems59. Studies on terrestrial ecosystems have found that co-limitation of nutrients often occurs at higher latitudes, where concentrations of N and P are relatively low60. Surface ice ecosystems appear to be likely candidates for nutrient co-limitation if there is ready utilisation of DON and DOP (and the concentrations measured are not methodological artefacts).

Implications for glacier ice algal growth
Here we demonstrated that at the sites sampled on the Qaanaaq Ice cap and the GrIS in NW Greenland, both SRP and DIN are present in low, yet quantifiable concentrations within ice surfaces colonised by glacier ice algae at concentrations typical of the Dark Zone (~104–~105 cells mL−1 9,55). This suggests that, at the time of sampling, glacier ice algal growth is not limited by the macronutrients, N and P. Using our measured DIN and SRP concentration in unweathered ice, along with cell concentrations, the mass of carbon in each cell, as well as stoichiometric C:N:P ratios, we estimated how much surface melt (ablation) is necessary to equal the mass of nutrient held in the glacier ice algae at each site. Our results indicate that annual ablation provides an excess of N and P relative to the glacier ice algae biomass at our locations. The N and P delivered by ablating ice is greater than the potential uptake by the algae during a single ablation season, especially considering that some glacier ice algae potentially survive from the previous winter, frozen into the surface ice61. This simple calculation suggests that macronutrient N and P do not limit glacier ice algal growth on seasonal timescales. We also observed higher DON and DOP concentrations at the surface, which generally exceed those of DIN and SRP. This may reflect artefacts introduced during sample processing, such as syringe or suction filtration methods, which can lyse cells, releasing intracellular DOC, DON and DOP. Cell imaging has previously shown ~10% of cells to be inactive34, potentially due to viral35 or fungal36 infections. Lysis of these cells could contribute significantly to the measured DON and DOP pools, which may be recycled within the wider ecosystem. Notably, the TDN:TDP ratios we observed fall within the range expected for balanced microbial growth if the microbial consortium can access these organic nutrient forms. Finally, we used N:P ratios to visualise how short-term nutrient shortage and periodically high cell counts may be limited by DIN and/or SRP. We conclude that P may become the limiting nutrient for short periods and spatially restricted areas with high cell counts. We contend that low-level nutrient analysis is essential to understand macronutrient limitation of glacier algal growth on the Greenland Ice Sheet.

Methods
Site description and sampling
Ice samples were collected between 27 July and 3 August 2023 at two different locations on two different ice bodies in North West Greenland. We sampled ice on the Qaanaaq Ice Cap at an elevation between 500 and 650 m.a.s.l., on 27, 29 and 30 July (at N77° 29.8606’ W069° 12.8812’, N77° 30.092’ W69° 09.691’ and N77° 30.150’ W69° 10.011’, respectively). The Qaanaaq Ice Cap is in the central part of the Piulip Nuna peninsula (Fig. 1b), it covers an area of 312 km2 and spans an elevation range between 30–1110 m.a.s.l. At the time of sampling, the ice surface was snow-free and had a shallow weathering crust (~5 cm) and dark banding from glacier ice algae and small cryoconite holes. On 3 August 2023, samples were collected from the main GrIS (at N77° 48.257’ W68° 21.044’) at an altitude of 780 m. Surface ice at this location, during sampling, had considerable biological darkening, speckled with small cryoconite holes and a shallow weathering crust (~5 cm).

Samples collected consisted of surface ice scrapings and or shallow ice cores, of which three depths were collected for analysis. Ice scrapings were collected using a field-conditioned ice axe to scrape the top layer of weathered ice in a ~2 × 2 m square and homogenized and collected into a 2 L Whirlpak® bag. These samples were categorised as weathering crust (hereafter WC) samples. Shallow cores (80–90 cm depth) were collected using a 9 cm diameter Kovax corer, targeting surface ice locations varying in surface darkness. The cores were extruded onto the inside of a clean 5.8 L whirlpak® bag, where the length of the core was quickly measured and cut into sections. From these cores, three primary 5 cm pucks were separated (Fig. 1c): (1) The top 5 cm, which contained the crumbly, active weathering crust (hereafter referred to as WC); (2) The underlying 5 cm (5–10 cm depth), which contained the transition zone from the weathering crust to the unweathered ice (hereafter referred to as TZ); 3) The last 5 cm at the base of the ice core, which consisted of fully unweathered ice (density >0.910 g cm−3; hereafter UW). The height of each ice puck was measured at six points around the circumference of the puck to obtain an average height, which was used to estimate the ice density.

On the Qaanaaq cap, samples were collected from the Qaanaaq glacier, which flows southwest from the southern part of the ice cap. At this site, a total of nine cores were drilled (with WC, TZ and UW samples collected for each) and five surface ice scraping samples were collected. Additionally, three cryoconite water samples and four supraglacial stream samples were collected. At the GrIS site, four cores were drilled (and WC, TZ and UW samples collected from each) and three surface ice scrapping samples were collected. Further, one cryoconite water sample and three supraglacial stream samples were collected at this site. All samples were transported to the base site in Qaanaaq town and processed as described below.

Sample processing
Samples were stored and partially melted in the fridge (5 °C) overnight, then stored at room temperature (~20 °C) until fully melted (approximately 2–4 hours). Samples were removed from the fridge in batches to avoid the samples warming up once melted. Immediately after melting, samples were filtered through 0.45 µm in-line PES filters, using 50 mL norm-ject syringe; previously acid-washed in 10% v/v HCl and rinsed six times with DI water. The first 5 mL of the filtered solution were discarded and approximately 45 mL of the filtered solution were aliquoted into three 15 mL falcon tubes (previously acid-washed in 10% v/v HCl and rinsed six times with DI water) and four 1.5 mL IC vials. All samples were then immediately frozen, stored at −20 °C and returned to the home laboratory on a frozen container ship. In the home laboratory, they were also stored at −20 °C until analysis.

Nutrient analysis
Soluble reactive phosphorous (SRP), nitrite (NO2-) and total oxidised nitrogen (TON; NO2-+NO3-) were analysed using colorimetric methods, as outlined in Patey, et al. 29, on a custom built continuous segmented flow analayser fitted with a 250 cm Longwave Capillary Cell (LWCC, part number: LWCC-3250, WPI (Germany)) using a Tungsten Light source and a ST-VIS Miniature Spectrometer (HL-2000-LL and ST-VIS-25, Ocean Insight (Germany)). Standard curves ranging from 5–200 nM P and 5–400 nM N were run daily on the LWCC, using TraceCERT™ phosphate standard (part num.: 38364-100ML, Sigma-Aldrich) and Specpure© nitrite standards (part num.: 040020.AP, ThermoFisher Scientific). The LWCC calibration for TON was cross-checked using both Specpure© nitrite standards and TraceCERT™ nitrate standards (part num.: 74246-100ML, Sigma-Aldrich). Mid-range standards consisting of 50 nM or 100 nM PO43- (for SRP and TDP, respectively) and 20 nM or 100 nM NO2- (for NO2- and TON, respectively) and 100 nM NO3- (for TON) were analysed regularly throughout the run (at least every eight samples). Limits of Detection calculated as 3.3σ/S, averaged 2 nM for SRP, 1.5 nM for NO₂⁻, and 5 nM for TON. The coefficient of variation, based on repeated analysis of 50 nM standards, was 1.6% for SRP, 1.1% for NO₂⁻, and 5.5% for TON. All reagents were made using 18.2 MΩ cm−1 water. Instrumental blanks (18.2 MΩ cm⁻¹ water) showed no signal above noise levels. The concentration of ammonium (NH4+) and concentrations above 10 ppb (~710 nM) TON, were quantified using a Gallery Aqua Master (ThermoFisher Scientific). The default low NH4+ (LOD=0.16 µM) and hydrazine reduction TON (LOD=0.35 µM) Gallery Aqua Master methods were used to quantify these nutrients. Procedural blanks consisted of 18.2 MΩ cm⁻¹ water transported to the field lab in a Nalgene carboy (acid-washed with 10% v/v HCl and rinsed six times with DI water), and processed identically to samples. These blanks yielded concentrations of 2.5 nM SRP, <LOD for TON and NO₂⁻, and 0.14 µM NH₄⁺.

To quantify total dissolved phosphorous (TDP) and total dissolved nitrogen (TDN) ̶ and calculate dissolved organic phosphorous (DOP) and dissolved organic nitrogen (DON) ̶ a 7 mL aliquot of each sample was digested by adding 0.7 mL of an alkali persulphate solution and autoclaving for 30 mins, as described in Hansen and Koroleff 30. Total nitrogen in the digested samples was then analysed using the hydrazine reduction TON method on a Gallery Aqua Master. Total phosphorous in these extracts was analysed using the colorimetric method and custom-built analyser, as detailed above. Procedural blanks for the digestion had average concentrations of 14.2 nM TDP and 0.52 µM TDN. All digestion results were corrected using procedural blanks.

Cell counts
Surface ice samples were counted in duplicate within 24 hours of collection, using a haemocytometer under an Olympus CX43 microscope. Magnification alternated between 100× and 200× depending on cell size. A total of 2 µL was counted per sample. Based on this volume, the detection limit for algal cells in this study was estimated at 500 cells mL⁻¹.

Mineralogy and particle loading
The melted samples were filtered through 47 mm Ø, 0.22-micrometre pore size polycarbonate filters using a glass filtration unit and a vacuum pump. For each sample, the volume filtered was used to evaluate the particle loadings (mg/L of melted solution). The solids retained on the filters were used for mineralogical quantifications. To do this, first, all samples were treated with 30% H₂O₂ for 48 hours to remove organic matter. Following this, the mineral particles were powdered manually using an agate mortar and the mineralogy of the powders was characterized by powder X-ray diffraction (pXRD). The measurements were performed using a STOE STADI P diffractometer equipped with a Cu X-ray source, a curved Ge (111) monochromator and a MYTHEN2 detector in flat plate transmission geometry. The obtained diffraction patterns were analysed using the PROFEX software for phase identification62.

Statistics
Statistical analysis of the data was performed in R version 4.2.1. The Kruskal-Wallis H test was used to determine if significant differences existed for macronutrient data among ice core sections within sites. When significance was observed, Dunn’s test of multiple comparisons was applied. For this study, the alpha level was set to 0.05. All errors reported in the text are one median absolute deviation about the median.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This is a well written and presented paper on the study of N and P dynamics within the upper icecap zones, and whether this\nmay explain microbial growth distribution and dynamics. I have very few comments as all the information is mainly well\npresented and carried out correctly, the key item is to double check the values in the text and the figures/tables to make sure\nthey match to the correct values.\nIntroduction:\nLine 19: “Intro” should be in full “introduction”\nL23: change to “The growth of these algae decreases…” as plural\nL31: delete “On the other hand,” or replace with However…\nResults:\nLine 89: “2.8 to 3.8% of the cells counted at Qaanaaq (mean value: 2.4 × 105 cells mL-1) and GrIS sites (mean: 0.75 × 105\ncells mL-1), respectively” – these values do not match what you are reporting in the supplementary data where it says 2.4%\nand 0.75*105 – please check all values for consistency and accuracy to your original dataset as I do not know which values\nare the correct/true ones\nLine 92: first sentence too long and needs rewording as I am not sure if you are presenting your findings here or values of\nNEGIS or NEEM\nLine 92: also for this paragraph please report in the same order of which the Table 1 is presenting data (so Total P, then\nSRP then DOP).\nLine 92: for this paragraph please refer to where your data are in tables and figs\nLine 101: you need to say what your range is if comparing to another range\nTable 1,2,3: these can all be in the same table\nFig 2: add info: “weathering crust (WC), transition zone (TZ) and unweathered ice (UW)” to help the reader\nFig 4 text: Nordenskiöldii should be lowercase n\nL183-184: the cell numbers do not match table S1\nL179: I suggest all of this long calculation-text be summerised as an equation somewhere in the document to make it easier\nto follow\nSuggest addition of findings from this recent paper to put values into context too (note I am not an author): Micromelt\nsampling of the glacier algal nutrient environment. Madeleine Lewis et al. FEMS Microbiology Ecology, Volume 101, Issue\n11, November 2025, fiaf098, https://doi.org/10.1093/femsec/fiaf098", "reviewer_2": "This study focuses on the nitrogen (N) and phosphorus (P) macronutrient limitation of glacial ice algal growth in\nnorthwestern Greenland. By employing a custom high-sensitivity analytical instrument to achieve nanomolar-level nutrient\nconcentration detection, combined with mass balance calculations and N:P ratio analysis, it draws the core conclusion that\n\"N and P do not limit glacial ice algal growth on a seasonal scale.\" The research topic holds significant implications for\nglacial ecology and climate interactions, with a logically sound experimental design and relatively solid data support.\nHowever, there is room for improvement in research depth, methodological details, conclusion generalizability,\nand certain mechanistic discussions.\nSpecific Revision Comments\nResearch Content and Mechanistic Discussion\n1. The study infers that the higher soluble reactive phosphorus (SRP) concentration in the surface layer than in the deep\nlayer is associated with surface dust dissolution and mineralization, and clarifies the differences in dust mineral composition\nbetween the Qaanaaq Ice Cap and Greenland Ice Sheet (GrIS) sampling sites. However, it fails to quantify the specific\ncontribution ratio of different minerals to N and P supply. It would enhance the persuasiveness of mechanistic explanations if\nlaboratory dust dissolution simulation experiments were supplemented, controlling key environmental factors such as\ntemperature and pH (matching glacial meltwater characteristics), measuring the N and P release rates of different mineral\nphases, and clarifying the influence weight of geological background differences on nutrient supply.\n2. Regarding the phenomenon that the nitrite (NO₂⁻) concentration in the surface layer is significantly higher than that in the\ndeep layer, only atmospheric deposition or nitrification is inferred as the source without distinguishing their contribution\nratios. It would improve the research on nitrogen cycling mechanisms if isotope tracing technology (e.g., ¹⁵N labeling) or\nfunctional gene detection (e.g., nitrification-related amoA gene) were integrated to accurately identify the main source of\nNO₂⁻, while supplementing data on cryoconite granule distribution density and analyzing its correlation with\nnitrification intensity.\n3. The study mentions that algal cell lysis during sample processing may overestimate dissolved organic nitrogen (DON)\nand dissolved organic phosphorus (DOP) concentrations. Supplementary Table S1 and the associated calculations detail\nthe estimation of DON/DOP derived from cell lysis. However, the study still lacks verification of the natural cell lysis rate\nunder in situ conditions. It would facilitate the revision of relevant conclusions if a fluorescence staining method (e.g.,\nSYTOX Green) were used to determine the mortality rate of glacial ice algae under natural conditions, quantify the DON and\nDOP produced by natural lysis, and evaluate its impact on the measured data.\nResearch Methods and Data Analysis\n1. The mass balance calculation for unweathered ice melt equivalent provides steps for estimating N/P\nstorage in algae and required ablation, but it still assumes 100% absorption efficiency of dissolved inorganic nitrogen (DIN) and\nSRP by algae, without considering nutrient loss through supraglacial runoff and competitive consumption by other microorganisms. It would\nimprove the reliability of conclusions if laboratory culture experiments were conducted to determine the actual N and P\nabsorption efficiency of algae, nutrient loss coefficients were calculated based on supraglacial runoff monitoring data,\nmicrobial competitive consumption parameters were introduced, and the existing balance model was revised.\n2. A custom continuous segmented flow analyzer is used for low-concentration nutrient detection, but its results have not\nbeen compared and verified with mainstream high-resolution mass spectrometry (e.g., LC-MS/MS). It would enrich the\nnutrient composition analysis if representative samples (covering different depths and nutrient concentration ranges) were\nselected for parallel detection by both methods to verify the accuracy of the custom instrument's results; meanwhile, attempts\ncould be made to identify more low-concentration N and P forms through mass spectrometry.\n3. The N:P ratio analysis is based on the median value of the overall sample, without considering the spatial heterogeneity\nof intracellular N:P ratios in algae. It would avoid misjudgment of limitation potential caused by overall mean analysis if\nsingle-cell level N:P ratio analysis (e.g., micro spectroscopic technology) was supplemented to explore the nutritional status\ndifferences of algal cells in different microhabitats at the same sampling site.\nConclusion Generalizability and Extended Research\n1. This study only sampled two sites in northwestern Greenland in July-August 2023 (mid-ablation season), without covering\ndifferent ablation stages and other regions (e.g., the dark zone in southeastern Greenland). It would enhance the\ncomprehensiveness of the research if the temporal and spatial limitations of the conclusions were clearly stated in the\ndiscussion section, prospects for multi-season and multi-region studies were supplemented, or preliminary analysis of the\nregional specificity of nutrient limitation was conducted by comparing existing data from different regions.\n2. The study mentions the positive feedback of \"melting - nutrient release - algal growth - further melting\" but does not\nquantify the contribution ratio of N and P supply in this feedback. It would strengthen the research depth and application\nvalue if a coupled model of glacial ablation and algal growth incorporating N and P cycling were constructed by combining\nnumerical simulation and field observation data, and the intensity of nutrient supply's role in the positive feedback was\nquantified.\n3. The potential impact of the continuous increase in glacial ablation rate under global warming on the balance between N\nand P supply and algal demand is not discussed. It would expand the research prospect if the CMIP6 climate model\nprediction results were integrated in the discussion to simulate changes in nutrient release and algal growth rate under\ndifferent future warming scenarios, and analyze whether the \"nutrient surplus\" state would be disrupted or new limiting\nfactors would emerge.\nExperimental Details and Data Presentation\n1. The study mentions \"discarding the first 5 mL of filtered solution after filtration\" but does not explain the specific basis for\nthis operation (e.g., whether pre-experiments were conducted to verify pollutant residue in the first 5 mL of solution). It would\nimprove the rigor of the experimental method if relevant verification data or reference support were supplemented to clarify\nthe rationality of this operation.\n2. Supplementary Table S1 provides key data such as cell counts, C/N/P mass estimates, and required ablation, but it would\nbe more user-friendly if additional annotations were added to clarify the derivation of parameters (e.g., citation of sources for\nthe 8.8 pM C cell⁻¹ value and C:N/C:P ratios) and unit consistency checks (e.g., confirmation of pmol/ml vs. other nutrient\nconcentration units).\n3. The calculation process for cell lysis estimates and unweathered ice melt equivalent is detailed, but it would enhance\nreproducibility if the raw data used in the calculations (e.g., raw cell count data, individual sample DIN/SRP/TDN/TDP\nconcentrations) were included in the supplementary materials, allowing readers to replicate the calculations independently.\nThis study addresses the challenge of accurately determining low-concentration nutrients using traditional methods through\ninnovative detection technology, and its core conclusions have certain scientific value. It is recommended that the authors\nsupplement relevant experimental data, revise the analysis model, improve mechanistic discussions and data presentation\nin response to the above comments, so as to further enhance the rigor, depth, and generalizability of the research."}, "author_response": "Response to Reviewer 1:\nWe would like to thank reviewer 1 for their commentary on our manuscript and for engaging\nwith the subject. Please see below for our point-by-point response to each of the comments\nraised (the response by the authors is in bold and italicized sans serif font):\n--\nReviewer #1 (Remarks to the Author):\nThis is a well written and presented paper on the study of N and P dynamics within the upper icecap\nzones, and whether this may explain microbial growth distribution and dynamics. I have very few\ncomments as all the information is mainly well presented and carried out correctly, the key item is to\ndouble check the values in the text and the figures/tables to make sure they match to the correct\nvalues.\nIntroduction:\nLine 19: “Intro” should be in full “introduction” - Done\nL23: change to “The growth of these algae decreases…” as plural - Done\nL31: delete “On the other hand,” or replace with However… - Replaced to “However”\nResults:\nLine 89: “2.8 to 3.8% of the cells counted at Qaanaaq (mean value: 2.4 × 105 cells mL-1) and GrIS\nsites (mean: 0.75 × 105 cells mL-1), respectively” – these values do not match what you are reporting\nin the supplementary data where it says 2.4% and 0.75*105 – please check all values for consistency\nand accuracy to your original dataset as I do not know which values are the correct/true ones\nWe reviewed the values, which were correct. However, the Supplementary reports 7.5\nx 104, which has been changed to 0.75 x 105 to maintain consistency.\nLine 92: first sentence too long and needs rewording as I am not sure if you are presenting your\nfindings here or values of NEGIS or NEEM.\nWe have broken the sentence into two and added some further clarification regarding\nthe values. It now reads as:\n“The SRP concentrations reported here (Table 1) are an order of magnitude higher\nthan those measured in firn cores from the North East Greenland Ice Stream (NEGIS)\nice core sampling site, within the GrIS accumulation zone (mean SRP at NEGIS: 2.7\nnM21). The concentrations of SRP measured in our samples were mostly within the\nrange measured in the NEEM ice core samples (SRP within NEEM: 3.0 - 32 nM20).\nHowever, some of the SRP concentrations in our samples were up to four times\nhigher than the upper values found at NEEM (Table 1).”\nLine 92: also for this paragraph please report in the same order of which the Table 1 is presenting data\n(so Total P, then SRP then DOP).\nWe have rearranged the paragraph so TDP is presented before SRP.\nLine 92: for this paragraph please refer to where your data are in tables and figs\nWe have added more mentions to table 1 for clarity.\nLine 101: you need to say what your range is if comparing to another range\nWe have added “(means ranging from 36 – 142 nM; Table 1)” for clarity.\nTable 1,2,3: these can all be in the same table\nWe have combined them as suggested.\nFig 2: add info: “weathering crust (WC), transition zone (TZ) and unweathered ice (UW)” to help the\nreader\nWe have added a line to the caption that reads “Sample types shown are weathering\ncrust (WC), transition zone (TZ) and unweathered ice (UW)”. We have added this to all\nthe figure captions for clarity.\nFig 4 text: Nordenskiöldii should be lowercase n - Done\nL183-184: the cell numbers do not match table S1\nValues had been rounded to 1 s.f., we have changed it to 2 s.f. for consistency.\nL179: I suggest all of this long calculation-text be summarised as an equation somewhere in the\ndocument to make it easier to follow\nWe have added four equations to the supplementary to make it easier for the reader.\nSuggest addition of findings from this recent paper to put values into context too (note I am not an\nauthor): Micromelt sampling of the glacier algal nutrient environment. Madeleine Lewis et al. FEMS\nMicrobiology Ecology, Volume 101, Issue 11, November 2025, fiaf098,\nhttps://doi.org/10.1093/femsec/fiaf098\nWe have included a mention to it in the introduction, to acknowledge that micromelt in\nsurface ice might have higher concentrations of nutrients. It also highlights the\ndifficulty of quantifying these concentrations. Most of the PO 3-, NO - and NO - values\n4 3 2\nreported in this paper were below their reported LOD (limit of detection). This may be\nan artefact of blank corrections, however I could not verify this from the paper and\nthere was no data repository link to further assess the data. Therefore, we have\nincluded the following sentence to our manuscript “Recent studies suggest that\nconcentrations of various nutrients may be higher in the “micromelt” (i.e. a thin layer\nof melt water of the surface of melting ice crystals) than in the bulk ice crystals24.\nHowever, even in these samples the concentration of PO 3-, NO - and NO - was largely\n4 3 2\nbelow the limit of detection (LOD)24” (line 44 - 47).\nWe note that these micromelt concentrations do not impact on the mass balance of\nnutrients in the surface ice, since the remaining parent ice is nutrient depleted.\nResponse to Reviewer 2:\nWe would like to thank reviewer 2 for their commentary on our manuscript. The review raises\nsome interesting questions. However, we feel that much of the suggested additional work is\nnot only beyond the scope of this study, but beyond the current leading edge of the science.\nWe hope that others will also be inspired to pose similar questions and therefore continue to\nmove the field forward. Our point-by-point response can be seen in bold and italicized sans-\nserif font.\n--\nReviewer #2 (Remarks to the Author):\nThis study focuses on the nitrogen (N) and phosphorus (P) macronutrient limitation of glacial ice algal\ngrowth in northwestern Greenland. By employing a custom high-sensitivity analytical instrument to\nachieve nanomolar-level nutrient concentration detection, combined with mass balance calculations\nand N:P ratio analysis, it draws the core conclusion that \"N and P do not limit glacial ice algal growth\non a seasonal scale.\" The research topic holds significant implications for glacial ecology and climate\ninteractions, with a logically sound experimental design and relatively solid data support. However,\nthere is room for improvement in research depth, methodological details, conclusion generalizability,\nand certain mechanistic discussions.\nSpecific Revision Comments\nResearch Content and Mechanistic Discussion\n1. The study infers that the higher soluble reactive phosphorus (SRP) concentration in the surface\nlayer than in the deep layer is associated with surface dust dissolution and mineralization, and clarifies\nthe differences in dust mineral composition between the Qaanaaq Ice Cap and Greenland Ice Sheet\n(GrIS) sampling sites. However, it fails to quantify the specific contribution ratio of different minerals\nto N and P supply. It would enhance the persuasiveness of mechanistic explanations if laboratory dust\ndissolution simulation experiments were supplemented, controlling key environmental factors such as\ntemperature and pH (matching glacial meltwater characteristics), measuring the N and P release rates\nof different mineral phases, and clarifying the influence weight of geological background differences\non nutrient supply.\nWe are grateful that the reviewer has engaged with the text enough to make these\nobservations. However, the source of the nutrients is not the current question we are\naiming to answer in this study. Our study aims to quantify the current levels of N and\nP at the ice surface and highlight the importance of using instruments which are able\nto quantify these low-level nutrients, since the impact of even low levels of nutrients\nhas such an impact on the numbers of glacier ice algal cells that surface ice at these\nlocations can maintain. Understanding the relative contributions of nutrients from\ndifferent dust sources is a great future research project that this paper has justified\nthe need for.\n2. Regarding the phenomenon that the nitrite (NO₂⁻) concentration in the surface layer is significantly\nhigher than that in the deep layer, only atmospheric deposition or nitrification is inferred as the source\nwithout distinguishing their contribution ratios. It would improve the research on nitrogen cycling\nmechanisms if isotope tracing technology (e.g., ¹⁵N labeling) or functional gene detection (e.g.,\nnitrification-related amoA gene) were integrated to accurately identify the main source of NO₂⁻, while\nsupplementing data on cryoconite granule distribution density and analyzing its correlation with\nnitrification intensity.\nWe highlight the increase in NO - at the surface relative to deeper within the ice, as an\n2\ninteresting result. However, we are careful to not overinterpret these results,\nparticularly as it is only a small fraction of the inorganic N pool. The time and\nassociated cost necessary to conduct this additional work makes it not only\nimpractical but unreasonable given the scope of the paper. We feel that this is another\ngreat future research project in the making.\n3. The study mentions that algal cell lysis during sample processing may overestimate dissolved\norganic nitrogen (DON) and dissolved organic phosphorus (DOP) concentrations. Supplementary\nTable S1 and the associated calculations detail the estimation of DON/DOP derived from cell lysis.\nHowever, the study still lacks verification of the natural cell lysis rate under in situ conditions. It\nwould facilitate the revision of relevant conclusions if a fluorescence staining method (e.g., SYTOX\nGreen) were used to determine the mortality rate of glacial ice algae under natural conditions,\nquantify the DON and DOP produced by natural lysis, and evaluate its impact on the measured data.\nThere is, to date, no information relating to the lysis and mortality rate of these algae,\nit is an open question at the leading edge of the science. We estimated the cell lysis\nthat would account for the DON and DOP concentrations measured to put our results\ninto perspective and to avoid over-interpretation of the organic data. We have\nincluded the current best estimates of dead or “inactive” cells which have been\nmeasured (~10%; in line 142-145), to acknowledge that algal cell lysis may also occur\nnaturally, even if our current understanding of the mortality rates of these algae is\nlimited. The very act of filtration almost certainly lyses cells, but the experimentation\nrequired to examine this effect is non-trivial because of the environmental stresses\nexperienced by the glacier ice algae during their collection and in preparation for their\nexperimentation and subsequent counting.\nResearch Methods and Data Analysis\n1. The mass balance calculation for unweathered ice melt equivalent provides steps for estimating N/P\nstorage in algae and required ablation, but it still assumes 100% absorption efficiency of dissolved\ninorganic nitrogen (DIN) and SRP by algae, without considering nutrient loss through supraglacial\nrunoff and competitive consumption by other microorganisms. It would improve the reliability of\nconclusions if laboratory culture experiments were conducted to determine the actual N and P\nabsorption efficiency of algae, nutrient loss coefficients were calculated based on supraglacial runoff\nmonitoring data, microbial competitive consumption parameters were introduced, and the existing\nbalance model was revised.\nWe acknowledge that this mass balance calculation is not perfect, this is\nacknowledged within the text:\n“in reality the amount of ablation required will be greater because the DIN and SRP\nuptake efficiency of the algae is unlikely to be 100%, and there is a nutrient demand\nfrom other microbes in the microbial ecosystem” (line 202-204) and again:\n“This too assumes that the glacier ice algae can directly take up DOP and DON with\nan efficiency of 100% and/or that heterotrophic microorganisms take up and recycle\nDOP and DON to inorganic forms with 100% efficiency (i.e., without no loss to\ndownstream ecosystems)” (line 213-215).\nThese calculations also assume that the bloom develops completely within one melt\nseason, which is unlikely, as we also mention in our manuscript:\n“The N and P delivered by ablating ice is greater than the potential uptake by the\nalgae during a single ablation season, especially considering that some glacier ice\nalgae potentially survive from the previous winter, frozen into the surface ice60”.\nThe laboratory culturing experiments are non-trivial and are beyond the current\nleading edge of the field. Only within the last few years have research groups been\nable to successfully culture them in the lab, as outlined by Jensen et al. (2023) paper\n“The dark art of cultivating glacier ice algae”. This, together with the other\nsuggestions already made by the reviewer takes us well beyond what is feasible to\nreport in one short journal paper, and would require several grants of multiple years\nto achieve.\n2. A custom continuous segmented flow analyzer is used for low-concentration nutrient detection, but\nits results have not been compared and verified with mainstream high-resolution mass spectrometry\n(e.g., LC-MS/MS). It would enrich the nutrient composition analysis if representative samples\n(covering different depths and nutrient concentration ranges) were selected for parallel detection by\nboth methods to verify the accuracy of the custom instrument's results; meanwhile, attempts\ncould be made to identify more low-concentration N and P forms through mass spectrometry.\nThe use of colorimetric/spectrophotometric methods to quantify N and P in water is\nstandard in many fields, particularly for environmental chemistry. Although our set-up\nand the use of a LWCC has not been use in supraglacial samples and is not widely\nused due to the difficulties associated with setting up the method and associated\nmaintenance, it has previously been used in marine sciences. We reference Patey et\nal. (2008) as our main source in the methods as we replicate their methods, and earlier\nstudies by Zhang et al. (2002) and Zhang et al. (2003) have used variations of this\nmethod. We use certified standards and standard curves to calibrate our method, and\nhave included some more details to the methods section to clarify this point:\n“Standard curves ranging from 5 – 200 nM P and 5 – 400 nM N were run daily on the\nLWCC, using TraceCERT™ phosphate standard (part num.: 38364-100ML, Sigma-\nAldrich) and Specpure© nitrite standards (part num.: 040020.AP, ThermoFisher\nScientific). The LWCC calibration for TON was cross-checked using both Specpure©\nnitrite standards and TraceCERT™ nitrate standards (part num.: 74246-100ML, Sigma-\nAldrich). Mid-range standards consisting of 50 nM or 100 nM PO43- (for SRP and TDP,\nrespectively) and 20 nM or 100nM NO2- (for NO2- and TON, respectively) and 100 nM\nNO3- (for TON) were analysed regularly throughout the run (at least every eight\nsamples).” (line 367-374).\nFinally, although LC-MS/MS would add a different dimension to our understanding of\nthe composition of the organic fractions, it is no way a “mainstream” method of doing\nthis, neither would it offer a direct comparison to the data presented here.\n3. The N:P ratio analysis is based on the median value of the overall sample, without considering the\nspatial heterogeneity of intracellular N:P ratios in algae. It would avoid misjudgment of limitation\npotential caused by overall mean analysis if single-cell level N:P ratio analysis (e.g., micro\nspectroscopic technology) was supplemented to explore the nutritional status differences of algal cells\nin different microhabitats at the same sampling site.\nThe intra-cellular N:P ratios discussed and their variability were part of a study\npublished earlier in the year by Halbach et al. (2025). We address the variability that\ncan be found within the population by specifically highlighting the wide range of N:P\nvalues that were measured in this study and including that variability in our plots (i.e.\nusing a shaded area in Fig. 4 rather than a simple line). It is beyond the scope of this\nstudy to conduct this same micro spectroscopic analysis on cells found at these\nsites. Quantifying the N:P range in different microhabitats is a significant and costly\nresearch task requiring a separate study of at least a year, which would be justified\nfrom the findings of this manuscript, but not necessary for the interpretation of our\nresults. Put simply, this is a foundational study that underscores the need for future\nfunding and continued advancement in the field.\nConclusion Generalizability and Extended Research\n1. This study only sampled two sites in northwestern Greenland in July-August 2023 (mid-ablation\nseason), without covering different ablation stages and other regions (e.g., the dark zone in\nsoutheastern Greenland). It would enhance the comprehensiveness of the research if the temporal and\nspatial limitations of the conclusions were clearly stated in the discussion section, prospects for multi-\nseason and multi-region studies were supplemented, or preliminary analysis of the regional specificity\nof nutrient limitation was conducted by comparing existing data from different regions.\nAs we highlight throughout the manuscript, there are very few studies that have\nquantified supraglacial nutrient concentrations. Even the studies that are available\nhave limitations due to the concentrations being at or below the limit of detection. We\nhave included some of the studies which look at nutrients in other polar regions (e.g.\nSvalbard and the alps) for context in the introduction. We have referenced the few\nresults available looking at nutrients at the surface of the GrIS to give context to our\nresults both geographically and the potential differences that may arise with within\ndifferent times in the melt-season. Particularly, we make reference to studies from\nKjæer et al. (2013 and 2015; which looked at P within ice and firn cores taken in the\naccumulation zone of the GrIS – incidentally using the same LWCC techniques\nemployed in this paper), Holland et al. (2019 and 2022; which attempted to quantify P\nand N during the early melt season in the dark zone of the GrIS with limited success\ndue to a high proportion of their values being below the LOD) and Telling et al. (2012;\nwhich analysed N in ice samples from Southern Greenland further into the melt\nseason) and to a lesser extent Stibal et al. (2011; also measured nutrients across a\ntransect in Southern Greenland but results were often below the LOD). Currently, our\nunderstanding of the variability of these nutrients across regions and seasons is\nbeyond what can be achieved in a single study, and requires further dedicated\nresearch funding of several years’ duration.\n2. The study mentions the positive feedback of \"melting - nutrient release - algal growth - further\nmelting\" but does not quantify the contribution ratio of N and P supply in this feedback. It would\nstrengthen the research depth and application value if a coupled model of glacial ablation and algal\ngrowth incorporating N and P cycling were constructed by combining numerical simulation and field\nobservation data, and the intensity of nutrient supply's role in the positive feedback was\nquantified.\nThis is a grand design well beyond the scope of this short journal paper, which would\nbe a significant foundational block to win the research funding and time needed to\nundertake such a project.\n3. The potential impact of the continuous increase in glacial ablation rate under global warming on the\nbalance between N and P supply and algal demand is not discussed. It would expand the research\nprospect if the CMIP6 climate model prediction results were integrated in the discussion to simulate\nchanges in nutrient release and algal growth rate under different future warming scenarios, and\nanalyze whether the \"nutrient surplus\" state would be disrupted or new limiting factors would emerge.\nWe do not yet know how these climate predictions are likely to affect the growth of\nglacier ice algae (or the wider glacial microbiome), therefore it would be highly\nspeculative to try to predict how these changes may affect the nutrient demands.\nThere are too many uncertainties at this time to be able to speculate how future\nwarming may affect the growth of glacier ice algae and how their nutrient demands\nmay be affected. This is another grand design well beyond the scope of this short\njournal paper, which would be a significant foundational block to win the research\nfunding and time needed to undertake such a project.\nExperimental Details and Data Presentation\n1. The study mentions \"discarding the first 5 mL of filtered solution after filtration\" but does not\nexplain the specific basis for this operation (e.g., whether pre-experiments were conducted to verify\npollutant residue in the first 5 mL of solution). It would improve the rigor of the experimental method\nif relevant verification data or reference support were supplemented to clarify the rationality of this\noperation.\nDiscarding some of the filtrate (first 0.5 -2 ml) is a relatively standard procedure to\nprecondition filters. This is done to remove contaminants or extractables and to\nprevent/reduce adsorption bias. It often appears as a recommendation on user\nmanuals for syringe filters (e.g. “User Guide Nonsterile 33 mm Millex® Syringe Filters\nMillex®-LG, LCR, GV, HV, GN, HN, GP, HP, FG, FH” by Millipore, recommends “you\ndiscard the first 1 mL”). We chose to increase the volume to 5 mL as a preventative\nmeasure to reduce the chances of interference from extractables or from adsorption\nbias. Since it is a standard procedure, we did not do additional testing, however, we\nanalysed procedural blanks that suggest there is no significant contamination arising\nfrom the filtering procedure.\n2. Supplementary Table S1 provides key data such as cell counts, C/N/P mass estimates, and required\nablation, but it would be more user-friendly if additional annotations were added to clarify the\nderivation of parameters (e.g., citation of sources for the 8.8 pM C cell⁻¹ value and C:N/C:P ratios)\nand unit consistency checks (e.g., confirmation of pmol/ml vs. other nutrient concentration units).\nThe citations for these values are all included in the text describing the calculations.\nThe 8.8 pM C cell⁻¹ value is a conversion from pg C/cell to pmol C/cell.\n3. The calculation process for cell lysis estimates and unweathered ice melt equivalent is detailed, but\nit would enhance reproducibility if the raw data used in the calculations (e.g., raw cell count data,\nindividual sample DIN/SRP/TDN/TDP concentrations) were included in the supplementary materials,\nallowing readers to replicate the calculations independently.\nThe data will be uploaded onto a data repository to facilitate this.\nThis study addresses the challenge of accurately determining low-concentration nutrients using\ntraditional methods through innovative detection technology, and its core conclusions have certain\nscientific value. It is recommended that the authors supplement relevant experimental data, revise the\nanalysis model, improve mechanistic discussions and data presentation in response to the above\ncomments, so as to further enhance the rigor, depth, and generalizability of the research."}]

Decision letter