Sustainability of the Peruvian anchoveta-based supply chains from sea to plate ANCHOVETA-SC PROJECT status report Angel Avadi, IRD, Université Montpellier II Main project collaborators: Marilú Bouchon, IMARPE Camilo Cuba, UNFV Dr. Pierre Fréon, IRD Federico Iriarte, UNFV Ana Medina, IMARPE Jesus Nuñez, IRD Jorge Tam, IMARPE Rosa Vinatea, UNFV Otros colaboradores en IMARPE, e.g. Rocío Joo DISCOH Scientific Workshop 29-31 March 2012

Outline The ANCHOVETA-SC project Supply chain modelling and evaluation Sustainability indicators Initial LCA results

ANCHOVETA-SC Project financed by IRD and project partners Coordinator: Pierre Fréon, IRD Location: Peru Duration: 4 years (01.2010 - 12-2013) Theme: Environmental and socio-economic assessment of major international supply chains consuming Peruvian anchoveta (aligned to WP5 DISCOH) Outputs: Sustainability assessment Policy and sustainability suggestions PhD thesis (plus other theses)

Focus Characterisation of biophisical flows along the supply chains (SC) Featuring ecosystem-SC interactions Comparison of scenarios based on different fishing intensities and “fate” of landings (DHC vs IHC) Sustainability comparison of chains/scenarios based upon: Energy performance Environmental impacts (LCA) Seafood-specific impact categories Nutritional value Selected socio-economic indicators LCA o ACV: estudio de los impactos ambientales, expresados en una serie de categorías de impacto (e.g. GWP, eutrophication), asociados a la provisión de un bien o servicio a lo largo de todo su ciclo de vida, desde la extracción de materias primas pasando por la transformación y uso hasta la disposición final. La idea principal es permitir la comparación de productos y procesos productivos desde el punto de vista de su impacto ambiental.

1) Simplified SC diagram Inputs Anchoveta, predators Canned, cured, frozen Ecosystem dynamics DHC processing Inputs Emissions Fisheries Con-sumption Inputs (including crops) Emissions Inputs Inputs Chinese finfish? European salmon? Shrimp? Reduction Aquafeed Aquaculture Anchoveta Emissions Emissions Emissions

Modelling ecosystem-SC interactions Ecopath with Ecosym Trophic model Lindeman spine: gráfico de cadenas tróficas lineales Umberto Material and energy flow model

2) Scenarios and 3) Indicators Status quo (maximum anchoveta stock exploitation) (1-2% DHC) Increase in DHC (10-15% DHC) Diversification (reduction of anchoveta catches + increase of predator catches) Mixed model with anchoveta DHC/IHC and anchoveta predators DHC Harvest Fate Indicators rationale To compare feed ingredients, feed formulations and seafood products: Gross energy content (MJ/kg) Edible protein Energy Return On Investment (%) Biotic Resource Use (g C/kg) Ecological Footprint (ha/t) To compare intermediate and final seafood products, and competing supply chains: LCA impact categories Socio-economic indicators (to be defined)

LCAs carried out Two fishmeal plants: a conventional one producing only Fair Average Quality (FAQ) fishmeal and using mainly heavy fuel as energy source a more modern steam plant producing both FAQ and prime quality fishmeal and using both heavy fuel and natural gas Detailed inventories of industrial anchoveta fleet under processing preliminary LCA of representative “average“ 395 m3 vessel category Two aquafeed plants (Iquitos) A pilot facility and a working commercial facility One aquaculture farm (Iquitos) Peruvian Amazonian species

Iquitos Colossoma farm Colossoma macropomum (Gamitana), a large Amazonian fish Farm: 30 ha, converted from rain forest, 11.2 ha of ponds (no wastewater treatment), production: 100 t/a, feed: 150 t/a

Network: Colossoma farm

Characterisation: Colossoma farm Main impact contributors: feed and rain forest transformation FRY Marine ecotoxicity Freshwater ecotoxicity Freshwater eutrophication Terrestrial acidification Photochemical oxidant formation Ozone depletion Urban land occupation Terrestrial ecotoxicity Ionising radiation Agricultural land occupation Climate change Ecosystems Natural land transformation Particulate matter formation Human toxicity Climate change Human Health Metal depletion Fossil depletion

Iquitos Aquafeed plants 2 plants visited: 30 t/a IIAP plant 8 t/m commercial plant (competing with Purina, etc.) < 6% Peruvian fishmeal content in feeds > 33% Bolivian soymeal content > 45% local cornmeal content

Network: Aquafeed plant (8 t/m)

Characterisation: Aquafeed plant Main impact contributor: use phase LCA FISHMEAL PLANT Marine ecotoxicity Freshwater ecotoxicity Freshwater eutrophication Terrestrial acidification Photochemical oxidant formation Ozone depletion Urban land occupation Terrestrial ecotoxicity Ionising radiation Agricultural land occupation Climate change Ecosystems Natural land transformation Particulate matter formation Human toxicity Climate change Human Health Metal depletion Fossil depletion

Aquafeed plant use phase Impact contributors in use phase: oil-powered electricity feed ingredients, mainly Bolivian soymeal (due to clearcutting in Bolivia) Marine ecotoxicity Freshwater ecotoxicity Freshwater eutrophication Terrestrial acidification Photochemical oxidant formation Ozone depletion Urban land occupation Terrestrial ecotoxicity Ionising radiation Agricultural land occupation Climate change Ecosystems Natural land transformation Particulate matter formation Human toxicity Climate change Human Health Metal depletion Fossil depletion

Network: Hypothetical trout feed plant (43% fishmeal)

Comparison of feed plants

Network: Fishing vessel 395 m3

Design remarks Key aquaculture products haven’t been characterised for Peruvian conditions E.g. Peruvian rice and corn. Proxies were used and adaptations introduced when possible (e.g. Bolivian soymeal adapted from Brazilian) Key industrial products haven’t been characterised, yet it’s composition is known/estimated E.g. electric and combustion engines

LCA results Construction and maintenance of (reduction, feed) plants contributes negligibly Fuel use is the main contributor to impacts in all activities (fishing, reduction, feed processing) Feed provision is the main contributor to impacts in extensive Peruvian aquaculture The sourcing of feed ingredients is a critical factor for associated environmental impacts of feeds E.g. Brazilian soymeal performing much worst than Bolivian one, due to clear cutting of rain forest vs. of shrublands.

Further (ongoing) work EwE scenarios definition and integration with Umberto Selection of and data gathering for socio-economic indicators Statistical processing of fleet inventories and comprehensive LCA of fleet categories Further LCAs: Canning, curing and freezing plants Carnivore fish and shrimp aquaculture farms Gathering supply chains operative data and LCIs Background processes for provision of feed ingredients Published LCI/LCA data must be recalculated to ensure consistency

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