Sea-ice sampling stations during the Oden Southern Ocean 2010/2011 cruise.

<p>Data of average sea extent from December 2010 was provided by the National Snow and Ice Data Center (<a href="http://nsidc.org/" target="_blank">http://nsidc.org/</a>). Map was created using the Quantarctica 2.14 QGIS-package, developed by the Norwegian Polar Institute (<a href="http://www.quantarctica.org" target="_blank">www.quantarctica.org</a>).</p

Microalgal photophysiology and macronutrient distribution in summer sea ice in the Amundsen and Ross Seas, Antarctica

<div><p>Our study addresses how environmental variables, such as macronutrients concentrations, snow cover, carbonate chemistry and salinity affect the photophysiology and biomass of Antarctic sea-ice algae. We have measured vertical profiles of inorganic macronutrients (phosphate, nitrite + nitrate and silicic acid) in summer sea ice and photophysiology of ice algal assemblages in the poorly studied Amundsen and Ross Seas sectors of the Southern Ocean. Brine-scaled bacterial abundance, chl <i>a</i> and macronutrient concentrations were often high in the ice and positively correlated with each other. Analysis of photosystem II rapid light curves showed that microalgal cells in samples with high phosphate and nitrite + nitrate concentrations had reduced maximum relative electron transport rate and photosynthetic efficiency. We also observed strong couplings of PSII parameters to snow depth, ice thickness and brine salinity, which highlights a wide range of photoacclimation in Antarctic pack-ice algae. It is likely that the pack ice was in a post-bloom situation during the late sea-ice season, with low photosynthetic efficiency and a high degree of nutrient accumulation occurring in the ice. In order to predict how key biogeochemical processes are affected by future changes in sea ice cover, such as <i>in situ</i> photosynthesis and nutrient cycling, we need to understand how physicochemical properties of sea ice affect the microbial community. Our results support existing hypothesis about sea-ice algal photophysiology, and provide additional observations on high nutrient concentrations in sea ice that could influence the planktonic communities as the ice is retreating.</p></div

Correlation between chl <i>a</i> and inorganic macronutrient concentrations (a–c), and between PSII capacity (rETR_max) and inorganic macronutrient concentrations (d–f).

<p>The grey areas represent 95% prediction intervals of the fitted lines. All concentrations are scaled to brine volume.</p

Simple linear regressions for the major drivers of PSII activity in Southern Ocean sea ice during summer.

<p>Data illustrate the relationships between sampling depth and F_v/F_m (<b>a</b>), and light saturation point (E_k) and snow depth (<b>b</b>). Maximum rate of electron transport rate (rETR_max) (<b>c</b>) and non-photochemical quenching (NPQ) (<b>d</b>) are negatively and positively correlated with brine salinity in sea-ice algal communities, respectively. P-values are reported from Pearson’s correlation, and the grey areas represent 95% predictor interval of the fitted line.</p

Station list, environmental and biological characteristics of the sea ice.

<p>Stations are numbered according to a previous study [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195587#pone.0195587.ref034" target="_blank">34</a>]. Bacterial abundance and chl <i>a</i> concentrations are depth-integrated throughout the sea ice column, and presented in either single or duplicated cores.</p

RDA ordination plot of environmental variables (black solid lines) explaining photophysiological data (grey, dashed lines).

<p>The first two RDA axes were significant (pseudo-F = 13.4, p = 0.001, 1000 permutations in Monte Carlo permutation test) and account for 51.0% of the total variation in the dataset. The environmental variables are inorganic macronutrient concentrations (nitrite + nitrate (NO₂ + NO₃), phosphate (PO₄), silicic acid (Si)), brine salinity, dissolved inorganic carbon (DIC), pH, snow depth, sampling depth (ice thickness). Photophysiological data include F_v/F_m, rETR_max, E_k, α_PSII (alpha_PSII) and brine-scaled chl <i>a</i> concentration.</p

Climate change projections for the surface ocean around New Zealand

<p>The future status of the surface ocean around New Zealand was projected using two Earth System Models and four emission scenarios. By 2100 mean changes are largest under Representative Concentration Pathway 8.5 (RCP8.5), with a +2.5°C increase in sea surface temperature, and decreases in surface mixed layer depth (15%), macronutrients (7.5–20%), primary production (4.5%) and particle flux (12%). Largest macronutrient declines occur in the eastern Chatham Rise and subantarctic waters to the south, whereas dissolved iron increases in subtropical waters. Surface pH projections, validated against subantarctic time-series data, indicate a 0.335 decline to ∼7.77 by 2100. However, projected pH is sensitive to future CO₂ emissions, remaining within the current range under RCP2.6, but decreasing below it by 2040 with all other scenarios. Sub-regions vulnerable to climate change include the Chatham Rise, polar waters south of 50°S, and subtropical waters north of New Zealand, whereas the central Tasman Sea is least affected.</p

Ocean acidification in New Zealand waters: trends and impacts

<p>The threat posed by ocean acidification (OA) to the diversity and productivity of New Zealand marine ecosystems is assessed in a synthesis of published trends and impacts. A 20-year time series in Subantarctic water, and a national coastal monitoring programme, provide insight into pH variability, and context for experimental design, modelling and projections. A review of the potential impact of changes in the carbonate system on the major phyla in New Zealand waters confirms international observations that calcifying organisms, and particularly their early life-history stages, are vulnerable. The synthesis considers ecosystem and socio-economic impacts, and identifies current knowledge gaps and future research directions, including mechanistic studies of OA sensitivity. Advanced ecosystem models of OA, that incorporate the indirect effects of OA and interactions with other climate stressors, are required for robust projection of the future status of New Zealand marine ecosystems.</p