The analysis of euphausiid larvae collected during january 2011 in the Weddell Scotia Confluence region show a strong decrease in the abundance of Euphausia superba larvae and an increase in Thysanoessa macrura. Oceanographic conditions didn’t show any significant variations respect historical information. The analysis was conducted using cluster and correspondence analysis finding that the associations of the different larvae and especies correspond to the available information. The densities observed during the cruise were compared with densities obtained in 1981 and 1995 calculating expected values at a fixed grid of points. Significance of the differences was established using a binomial test on their signs.

Antarctic krill is a key species in the Southern Ocean food web and is also the target of the greatest fishery in Antarctic waters. Management of the fishery is based on a precautionary catch limit, representing 0.11 the allowable catch limit for CCAMLR Area 48, and further divided by subarea. Despite that the fishery is operating in the Antarctic Peninsula area since 1980s, the spatial and temporal pattern of the fishery is only described in meso to macro scales (>>10⁴ km²). Here we present a novel analysis to identified fishing grounds, using statistical analysis of hotspots, in this case, fishing hotspots (FH), combined with a temporal analysis to assess persistence of these FHs. Results indicate that the fishery is presenting consistent FH across years, particularly during those years when the precautionary catch limit is reached. These events occur mainly in the centre of the Bransfield Strait and the northern section of the Gerlache Strait, and have a duration of 3 to 5 months. FH identified are small, equivalent to a circle of radius 25 km, and have a high catch density (>10 ton∙km^-2) during years when the catch limit is reached. The analysis show that the krill fishing fleet is concurring to know fishing grounds year after year, where they obtain high catches, and that the catch density (ton∙km^-2) inside the FHs is correlated with the total catch obtained, suggesting its use as an index of krill abundance in an area.

We studied Ross Sea killer whales (RSKWs; Orcinus orca, Antarctic type C), a fish-eating ecotype, in McMurdo Sound, Antarctica, during 7 seasons, over a 14-year period from 2001/02 to 2014/15. Using photo-identification methods, we identified 352 individual RSKWs in the Sound and up to 175 there annually. Despite high turnover of different whales between years, we used a Bayesian mark-recapture approach to identify a seasonal ‘resident’ population with an average annual abundance of 55 individuals (95% probability = 44-68) that exhibited strong inter- and intra-annual site fidelity, with individuals resighted over 2-14 years. Contrary to recent reports that commercial overfishing of Antarctic toothfish (Dissostichus mawsoni) may have led to a marked decline RSKW numbers in the southwestern Ross Sea, our analysis suggests that at least the resident killer whale population in McMurdo Sound is stable with the average annual estimated number of deaths (= 2.4, 95% probability = 1.2-4) being balanced by the estimated number of recruits (= 2.6, 95% probability = 0.9-4.4).

At the close of the Commission for the Conservation of Antarctic Marine Living Resources meeting in 2015, New Zealand and the United States introduced a revision to the proposed Ross Sea Region Marine Protected Area (RSRMPA) that included the addition of a Krill Research Zone (KRZ). A central aim of the proposed KRZ is to enhance research opportunities within the RSRMPA. To provide a background for this future research, we reviewed previous scientific work relevant to the proposed KRZ, focusing primarily on krill and krill-dependent predators. Here we provide a summary of that review, which demonstrates the potential ecological importance of the proposed KRZ and gaps in our knowledge of the area. Our review further validates the opportunity presented by the proposed KRZ for future scientific research.

We present a Stage-2 strategy for in-season feedback management (FBM) of the krill fishery in Subarea 48.1.  This strategy is a combination of two strategies that were separately proposed to the WG-EMM in 2015 and is based on a broad foundation of work undertaken to address a suite of action items specified by the WG-EMM.  A decision rule to adjust catches in groups of SSMUs (gSSMUs) is central to the strategy proposed here.  In “plain English” that decision rule has four components.  1) If penguin recruitment is expected to be sufficient for population maintenance, CEMP monitoring indicates acceptable predator performance during the current breeding season, and krill biomass has increased during the present summer, the local catch limit will be increased.  2). If penguin recruitment is expected to be sufficient for population maintenance but CEMP monitoring indicates a poor breeding season or krill biomass has not increased during the summer, the local catch limit will not be adjusted.  3) If penguin recruitment is expected to be so poor that the population will decline even if adult survival through the forthcoming winter is very high, the local catch limit will be decreased.  4) If penguin recruitment is expected to be so poor that the population will decline even if almost all adults survive through the forthcoming winter, the local catch limit will be set to zero.  Implementation of the FBM strategy proposed here includes defining a base catch limit for each gSSMU (there are various options for this), collecting data on predators and krill, delaying the start of the fishing season until this data-collection effort is underway, submitting the data to the Secretariat, increasing the frequency of catch and effort reporting by the fishery, having the Secretariat compute various state variables from the submitted data and applying the decision rule with the state variables relevant to each gSSMU, providing advance notice to fishing vessels about the outcomes of applying the decision rule, and adjusting the catch limit in each gSSMU.  A time line for this implementation process is proposed.  Adjusted catch limits would only apply for a single fishing season and the implementation process would restart every year.  We used historical data to conduct retrospective analyses of our FBM strategy for two gSSMUs.  These analyses demonstrate that local catch limits would have been decreased about half the time, particularly when penguin populations were known to have been in decline.  Local catch limits would not have been adjusted or might have been increased when penguin populations were stable or increasing.  The retrospective analyses also suggest that delaying the start of the fishing season but permitting some fishing to occur prior to the “adjustment date” can be a reasonable compromise between minimizing risks to krill-dependent predators and minimizing impacts on the fishery.  The FBM strategy proposed here is fully consistent with the agreed definition of a Stage-2 strategy, and we advocate that it be trialed in real life.

Here we compile three vignettes that, together, provide the basis for making upward adjustments to local catch limits for the krill fishery in Subarea 48.1.  We use the term local catch limit to refer to a catch limit that applies to a group of SSMUs (gSSMU), and the work presented here is based on the gSSMUs defined in another compilation of vignettes (AERD 2016a, pp. 3-13).  We propose upward adjustments to local catch limits as one component of a larger strategy for feedback management (FBM) of the krill fishery in Subarea 48.1 (see Watters et al. 2016).  Our proposal to make upward adjustments is founded on 1) a “stoplight” classification of predator performance to identify years when predator performance is good and suggest that upward adjustments of local catch limits may not negatively impact predator populations, 2) repeat acoustic surveys to identify years when local krill biomass increases during the fishing season, and 3) a decision rule that can be used to increase local catch limits when the stoplight is “green” and there has been a concomitant increase in local krill biomass. We demonstrate that a simple index based on normalized CEMP parameters can be used to categorize predator performance as good (“green-light”) or poor (“red-light”). The approach is relatively insensitive to missing values, agrees generally with expert opinion, and suggests that indices of foraging trip duration, fledge weight, and reproductive success are highly influential in determining a green- or red-light classification of summer predator performance. We then show that local estimates of krill biomass around the Antarctic Peninsula are spatially and temporally correlated. Such patterns suggest that repeat surveys of standard transects within gSSMUs can be used to characterize larger-scale patterns of krill abundance and detect within-season increases in krill biomass. Thus, a ratio of late to early summer krill biomass estimates can be indicative of “surplus” krill potentially available to the fishery. To capitalize on such surpluses, we propose a step-change decision rule to increase local catch limits.  Provided the stoplight is green, the ratio of late-summer to early-summer estimates of krill biomass from acoustics surveys provides a simple catch-limit multiplier that can increase a local catch limit if the biomass ratio is greater than one. We advocate real-life testing of the ideas proposed here to prove the concept; in particular it would be useful for fishing vessels to collect acoustic data on repeat transects twice per summer.

Here we compile four vignettes that, together, provide the basis for making downward adjustments to local catch limits for the krill fishery in Subarea 48.1.  We use the term local catch limit to refer to a catch limit that applies to a group of SSMUs (gSSMU), and the work presented here is based on the gSSMUs defined in another compilation of vignettes (AERD 2016a, pp. 3-13).  We propose downward adjustments to local catch limits as one component of a larger strategy for feedback management (FBM) of the krill fishery in Subarea 48.1 (see Watters et al. 2016).  Our proposal to make downward adjustments is founded on 1) a model that quantifies the survival and recruitment rates needed to maintain resilient penguin populations, 2) a leading indicator that predicts recruitment rates of penguin cohorts, 3) feasible methods to estimate the leading indicator from monitoring data, and 4) a decision rule that can be used to decrease local catch limits when penguin cohorts are expected to be relatively weak.  We quantified the survival and recruitment rates needed to maintain resilient penguin populations with a model that was fitted to mark-recapture data on Adélie penguins.  Our results show that resilient populations can be maintained when more than 10% of fledglings recruit back to their breeding populations and adult survival rates are greater than 90%.  We then fitted a Bayesian model to estimates of cohort strength and observations on breeding phenology for Adélie, chinstrap, and gentoo penguins.  Mean age at crèche can predict poor recruitment; when the chicks in a cohort crèche at a relatively young age, cohort strength is expected to be relatively weak.  We are participating in a multi-Member collaboration to monitor, with remote cameras, the mean ages at crèche of Adélie, chinstrap, and gentoo penguins at multiple sites in Subarea 48.1.  We developed a spline-based method to analyze the photographic data collected by this camera network, and camera-based estimates of age at crèche are on par with those based on visual observations taken following CEMP Standard Method A9.  We parameterized a decision rule that, if implemented, will decrease local catch limits when chicks crèche at a relatively young age and penguin cohorts are expected to be relatively weak.  We envision that this decision rule would be applied separately for each gSSMU within Subarea 48.1, using monitoring results for penguins that are known to forage within each gSSMU.  This decision rule is intended to provide the Commission with advance opportunity to proactively manage the krill fishery so that risks to dependent predators are mitigated in a manner consistent with Article II of the Convention.  Retrospective application of the decision rule to historical data suggests that catch limits in the Bransfield Strait would have been decreased about 43% of the time while catch limits for the group of coastal SSMUs in the Drake Passage and around Elephant Island would have been decreased about 32% of the time.  Adélie and chinstrap penguin populations were declining for substantial proportions of the periods over which these retrospective analyses apply.  The retrospective results should only be considered marginal results because the decision rule to decrease local catch limits is only one component of the overall FBM strategy we are proposing for Subarea 48.1.

Here we compile eight vignettes that, together, provide the background data and information needed to support development of a feedback management strategy for the krill fishery in Subarea 48.1. In this compilation, we provide support for combining SSMUs into groups of SSMUS (gSSMUs) to form larger management units. We believe that identifying management areas that are larger than SSMUs within Subarea 48.1 will both facilitate and expedite the allocation of a catch limit in the subarea without negatively impacting the krill fishery while simultaneously mitigating risks to krill-dependent predators. We review the logic for these gSSMUs and then use the gSSMU concept in many of the vignettes that follow. In the second vignette, we examine the influence of oceanic and shelf circulation on the distribution of krill biomass and commercial fishery catch and effort to better understand how retention and concentration mechanisms aggregate krill in fishable quantities above the background concentration. We use a circulation model and particle tracking to show that areas with high catches also tend to be areas of retention and are generally separated from the prevailing circulation. These findings indicate that local depletion within these areas is more likely when regional krill abundance is low.  In the third vignette, we examine the correlations between acoustic estimates of krill biomass and two measures of fishery performance, krill catches and nominal catch rates (CPUE), within and between gSSMUS and show that there is little correlation between biomass estimates from research surveys and either performance measure. In the fourth vignette, we examine how temporal variability in the seasonal sea-ice coverage of gSSMUs is related to krill catches. We show that krill catches decline rapidly when gSSMUs are more than 50% covered in ice, which acts as an environmentally-driven constraint on the duration of the fishing season in different gSSMUs. In the fifth vignette, we examine the overlap of krill catches and predator foraging distributions using data from a large telemetry study involving multiple species of birds and mammals during summer and winter. We show that direct overlap of krill-dependent predators with the krill fishery on small spatio-temporal scales is common throughout the Antarctic Peninsula region. Such overlap highlights the potential for competitive interactions between predators and the krill fishery and underscores the goal of the Commission to prevent concentration of fishing effort in small areas. In the sixth vignette, we show that fluctuations in krill size and biomass are related to changes in the durations of foraging trips made by Antarctic fur seals. In the seventh vignette, we quantify functional relationships both between local krill biomass and penguin performance and between local krill harvest rates and penguin performance. These functional relationships empirically demonstrate reduced penguin performance in the Antarctic Peninsula region when local krill biomass is low or when local krill catches are high relative to local biomass. The results further demonstrate that krill fishing in Subarea 48.1 may have already had negative impacts on penguin performance. In the final vignette, we evaluate three alternatives for allocating catch limits for krill among gSSMUs in Subarea 48.1. These alternatives are not exhaustive, and other alternatives can certainly be developed. Together, all eight vignettes provide background material referenced in other papers (AERD 2016b and 2016c) that Watters et al. (2016) use as the basis of a proposed feedback management strategy in Subarea 48.1.

The United Kingdom has contributed funding to the US-based non-governmental organisation Oceanites, to support its ongoing Antarctic Site Inventory project, which monitors penguin populations across the Antarctic Peninsula.  The Antarctic Site Inventory data, together with data from other sources, has been collated within Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD) which is on a publicly available website (Humphries et al. In Press). The data summary and analysis together with the methods described within Lynch et al. (2010), provide methods that are of direct relevance to the WG EMM discussions on feedback management. Consequently, the UK has submitted the documents as background papers.

Humphries G.R.W., Che-Castaldo C., Naveen R., Schwaller M., McDowall P., Schrimpf M., Lynch H.J. Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Data and tools for dynamic management and decision support (In Press)

Lynch H J., Fagan W. F. Naveen R., Population trends and reproductive success at a frequently visited penguin colony on the western Antarctic Peninsula Polar Biol (2010) 33:493–503.

A workshop was held in Paris from June 6 to 9^th 2016. It was convened by Philippe Koubbi and Christophe Guinet. The main aim was to determine ecoregions in the Kerguelen oceanic zones to give orientations for extending the actual coastal natural reserve managed by the Terres Australes and Antarctiques Françaises. The workshop listed general conservation objectives to evaluate boundaries of ecoregions based on abiotic (geography, geomorphology and oceanography) and biotic features such as pelagic, benthic (including demersal ichthyofauna) and top predators species or assemblages. As biodiversity is not only species diversity, the workshop also considered the functional diversity (trophic web, essential habitats, life history traits,…).

This report is a summary of the conclusions based on expert knowledge. It is divided into three parts:

-          A summary of the ecological characteristics of the Kerguelen oceanic zone;

-          The ecoregionalisation of the pelagic realm, the benthic realm and the top predators;

-          A final ecoregionalisation and recommendations for future works.

The workshop determined 12 main pelagic ecoregions based on oceanographic processes, pelagic assemblages and on keystone species distribution such as mesopelagic fish. Four Important areas for top predators were defined and 8 benthic ecoregions were drawn from the coast to the limit of the Kerguelen EEZ.

The experts found relevant to combine the pelagic and benthic ecoregions to obtain a global ecoregional map of 18 ecoregions based mainly on:

-      Habitat characteristics (bathymetry, oceanography, primary production, biogeochemical parameters, …),

-          Types of species assemblages with consideration of endemicity and conservation status,

-      Functionality (essential habitats such as spawning grounds, nursery grounds or foraging habitats, areas of high primary and secondary production or, structure of the habitat by benthic species,…).

In this process, the workshop verified the superposition of the ecoregional synthetic map with specific habitats of species (birds and mammals distribution, essential fish habitats,...). It corrected some of the boundaries of ecoregions with these ecological parameters so that some essential species habitats are mainly within one region. For each of the final ecoregions, the workshop summarized the essential characteristics that support the creation of the ecoregion and estimated its ecological importance.

To conclude, the workshop indicated the need to continue research and monitoring over this vast area and to identify special research zones such as observatories to:

-          Study the impacts of global change,

-          Minimize knowledge gaps in ecology and environment,

-          Consider natural variability,

-          Study the resistance and resilience towards potential human impacts.