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.

The authors present to the Working Group on Ecosystem Monitoring and Management (WG EMM) the scientific background and justification for the development of a marine protected area (MPA) in the Weddell Sea planning area. In accordance with the recommendations by WG-EMM-14 (SC-CAMLR-XXIII, Annex 6), this was done in three separate documents (Part A-C). WG-EMM-16/01 (Part A) sets out the general context of the establishment of CCAMLR-MPAs and provides the background information on the Weddell Sea MPA (WSMPA) planning area; WG-EMM-16/02 (Part B) informs on the data retrieval process and WG-EMM-16/03 (Part C) describes the methods and the results of the scientific analyses as well as the development of the objectives and finally of the borders for the WSMPA.

Earlier versions of Parts A-C were already presented at the meetings of EMM and SC-CAMLR in 2015. The Scientific Committee did recognise that the body of science of the background documents (SC-CAMLR-XXXIV/BG/15, BG/16, BG/17) provides the necessary foundation for developing a WSMPA proposal (SC-CAMLR-XXXIV, § 5.11).

Here, the authors present the final version of Part C to WG EMM. Part C has been further revised in the light of comments received at the above mentioned meetings and in the 2015/16 intersessional period. The text has also undergone final editorial corrections. Chapter 1 shows a revision of the data analysis including, for example, newly analysed data layers on seabirds and demersal fish. Chapter 2 provides an update of the newly conducted MPA scenario development incorporating a cost layer analysis.

Penguins, albatrosses, petrels, elephant seals and fur seals are marine top predators that have to come on land to reproduce. Therefore, they are the only marine top predators that can be studied from land base sites, making them the most accessible convenient models to study marine ecosystems. Indeed, seabirds and seals are considered as good indicators of changes in ecosystems at differential spatial and temporal scales. However, current conservation measures, which comprise relatively few impact mitigation actions and restricted protection of the sole coastal areas, are insufficient, especially for the oceanic realm. Today, there is an urgent need to identify and protect the open sea environments where seabirds and marine mammals forage.

The first stage of most conservation planning is to identify areas that warrant protection (including areas that are already protected). The main criteria used to identify such areas are biological diversity (species richness), rarity, population abundance, environmental representativeness and site area. Where distribution data are both comprehensive and accurate, it is possible to identify areas of high species richness (hotspots), focusing on threat level (endangered species).

This Atlas of top predators from the French Southern Territories in the Southern Indian Ocean is a summary of information on the use of the southern Indian Ocean by 22 seabirds and seals species: king penguin, gentoo penguin, Adelie penguin, eastern rockhopper penguin, northern rockhopper penguin, macaroni penguin, Amsterdam albatross, wandering albatross, black-browed albatross, Indian yellow-nosed albatross, light-mantled albatross, sooty albatross, southern giant petrel, northern giant petrel, southern fulmar, Cape petrel, snow petrel, white-chinned petrel, grey petrel, brown skua, southern elephant seal and Antarctic fur seal.

The distribution map of each species was obtained by the use of tracking methods that allow identifying important areas in the southern Indian Ocean. The determination of zones of high species richness suggests several important areas for top predators. First the breeding colonies and surrounding zones: Amsterdam and Saint Paul Islands, Marion and Prince Edward islands and the Del Cano Rise, Crozet Islands, Kerguelen Plateau and East Antarctica (Adelie Land sector). Second, the upwelling-current zones: Benguela and Agulhas Currents Systems and third several the oceanic zones: the Southwest Indian Ridge (East Bouvetoya and the North Subtropical Front), the Mid-Indian Ridge (North of Kerguelen and the Eastern Indian Ocean, the Southeast Indian Ridge (Great Australian Bight and Tasmania, Ob and Lena Banks, and East Antarctica (Prydz Bay - Queen Maud Land sectors, Adelie Land sector).

The analysis of distribution indicates that some pelagic species have a much wider foraging range outside the breeding season than during the breeding season (some disperse over very large areas, i.e. wandering albatross). This highlights the urgent need to strengthen collaborations, namely between conservation and management organisms such as CCAMLR and the fisheries organisations (RFMOs), to ensure the protection of these species and the conservation of the ecosystem that will also be beneficial for many other species.

In conclusion, although this inventory of areas of key importance is preliminary because of the lack of data on several keystone species such as burrowing petrels which could not be studied in this work, the results presented here show an unprecedented improvement in the identification of priority areas within the Southern Indian Ocean, which should be the primary targets of site-based conservation efforts in the near future. The Southern Indian Ocean is not pristine. The most serious threats are linked to industrial fishing activities, including fishery discards, bycatch of seabirds and marine mammals, as well as, in a lesser extent, degradation of marine environments through global and local pollution. On land, alien introductions and diseases are now the main threats. Despite much improvement in the conservation measures taken by several fisheries, especially in the southern part of the Indian Ocean, fisheries continue to exert an important negative influence on several seabirds, especially on the high seas. However climate change is now increasingly considere to have a negative impact on seabirds at some Antarctic and sub-Antarctic localities.

The authors present to the Working Group on Ecosystem Monitoring and Management (WG EMM) the scientific background and justification for the development of a marine protected area (MPA) in the Weddell Sea planning area. In accordance with the recommendations by WG-EMM-14 (SC-CAMLR-XXIII, Annex 6), this was done in three separate documents (Part A-C). WG-EMM-16/01 (Part A) sets out the general context of the establishment of CCAMLR-MPAs and provides the background information on the Weddell Sea MPA (WSMPA) planning area; WG-EMM-16/02 (Part B) informs on the data retrieval process and WG-EMM-16/03 (Part C) describes the methods and the results of the scientific analyses as well as the development of the objectives and finally of the borders for the WSMPA.

Earlier versions of Parts A-C were already presented at the meetings of EMM and SC- CAMLR in 2015. The Scientific Committee did recognise that the body of science of the background documents (SC-CAMLR-XXXIV/BG/15, BG/16, BG/17) provides the necessary foundation for developing a WSMPA proposal (SC-CAMLR-XXXIV, § 5.11).

Here, the authors present to WG EMM the final version of Part B that provides a systematic overview of the environmental (chapter 1) and ecological data sets (chapter 2) acquired for the WSMPA planning. Part B has been further revised in the light of comments received at the above mentioned meetings and in the 2015/16 intersessional period. Some data sets were newly acquired (e.g. data on seabirds, demersal fish) and final editorial changes were done.

Antarctic krill (Euphausia superba) are considered to be one of the key species in the Antarctic marine food web, being prey to a wide variety of dependent species as well as being commercially harvested. The commercial exploitation of krill is managed under the direction of CCAMLR (Commission for the Conservation of Antarctic Marine Living Resources), utilising results derived from the CCAMLR generalised yield model and krill yield model (Constable and de la Mare, 1996; Butterworth et al. 1994). A key parameter of the krill yield model is an estimate of the pre-exploitation biomass of krill (B₀). The current estimate of B₀ which is used by CCAMLR in the model is derived from the CCAMLR-2000 synoptic acoustic survey (hereafter CCAMLR-2000) in the Food and Agriculture Organisation (FAO) statistical subareas 48.1, 48.2, 48.3 and 48.4 (Hewitt et al. 2004; Watkins et al. 2004). The design, planning, implementation and subsequent first analysis of the CCAMLR-2000 B₀ estimate were initiated in 1995 and documented within the CCAMLR WG-EMM reports (SC-CAMLR-XIV, Annex 4, Paragraph 4.61;  SC-CAMLR-XV, Annex 4, Paragraphs 3.72 to 3.75, 8.8; SC-CAMLR-XVI, Annex 4, Paragraphs 8.109 to 8.129; SC-CAMLR-XVII, Annex 4, Paragraphs 9.49 to 9.90; SC-CAMLR-XVIII, Annex 4, paragraphs 8.41 to 8.49) as well as papers tabled at those meetings (CCAMLR 1995; 1996; 1997; 1998; 1999). In particular two workshops, one planning (SC-CAMLR-XVIII, Annex 4, Appendix D) and one analysis (SC-CAMLR-XIX, Annex 4, Appendix G), provide background and detail to the survey design, implementation and original analysis (CCAMLR 1999; 2000). Since 2000 a number of re-analyses, improvements and corrections to the acoustic protocol to determine krill density have been tabled at the CCAMLR WG-EMM and SG-ASAM meetings. This document aims to summarise those changes and their rationale.

For ease of reading, this document has been separated into nine sections: Survey design; Acoustic data collection; Acoustic data processing; Target strength (TS) model and implementation; Target identification; Echo integration; Conversion of acoustic backscatter to areal biomass; Estimation of total biomass from areal biomass; and Estimation of uncertainty. Key methods and their derivations are highlighted in bold. This document does not describe a re-design of the CCAMLR synoptic survey, but details changes to the initial analysis, and the procedures (Table 1) which lead to the current estimate of B₀.

We report on preliminary analyses to estimate macaroni penguin consumption of prey in Subarea 48.3 during the period when penguins are constrained by breeding. We show that the greatest levels of consumption occur during incubation and pre-moult, but that there are also evident increases towards the end of guard and the end of crèche. Our initial results indicate that levels of krill consumption are comparable with some previously reported estimates, but with some important differences. This work represents a collaborative study by scientists working through WG-EMM-STAPP. We propose that similar such analyses should be undertaken for the other krill-eating penguin species breeding in Area 48, and that such analyses are best undertaken collaboratively.