FN Clarivate Analytics Web of Science
VR 1.0
PT J
AU Oostdijk, M
   Elsler, LG
   Van Deelen, J
   Auping, WL
   Kwakkel, J
   Schadeberg, A
   Vastenhoud, BMJ
   Nedelciu, CE
   Berzaghi, F
   Prellezo, R
   Wisz, MS
AF Oostdijk, Maartje
   Elsler, Laura G.
   Van Deelen, Julie
   Auping, Willem L.
   Kwakkel, Jan
   Schadeberg, Amanda
   Vastenhoud, Berthe M. J.
   Nedelciu, Claudiu Eduard
   Berzaghi, Fabio
   Prellezo, Raul
   Wisz, Mary S.
TI Modeling fisheries and carbon sequestration ecosystem services under
   deep uncertainty in the ocean twilight zone
SO AMBIO
LA English
DT Article
DE Blue carbon; Carbon sequestration; Deep uncertainty; Mesopelagic
   fishery; Social-ecological modeling
ID MESOPELAGIC FISHES; SCENARIO DISCOVERY; MANAGEMENT; IMPACTS; SYSTEM;
   DYNAMICS; ECOLOGY; DRIVE
AB Mesopelagic fishes are a vital component of the biological carbon pump and are, to date, largely unexploited. In recent years, there has been an increased interest in harvesting the mesopelagic zone to produce fish feed for aquaculture. However, great uncertainties exist in how the mesopelagic zone interacts with the climate and food webs, presenting a dilemma for policy. Here, we investigate the consequences of potential policies relating to mesopelagic harvest quotas with a dynamic social-ecological modeling approach, combining system dynamics and global sensitivity analyses informed by participatory modeling. Our analyses reveal that, in simulations of mesopelagic fishing scenarios, uncertainties about mesopelagic fish population dynamics have the most pronounced influence on potential outcomes. The analysis also shows that prioritizing the development of the fishing industry over environmental protection would lead to a significantly higher social cost of climate change to society. Given the large uncertainties and the potential large impacts on oceanic carbon sequestration, a precautionary approach to developing mesopelagic fisheries is warranted.
C1 [Oostdijk, Maartje] Agr Univ Iceland, Fac Agr Sci, Keldnaholt,Arleynir 22, IS-112 Reykjavik, Iceland.
   [Berzaghi, Fabio] World Maritime Univ, Ocean Sustainabil Governance & Management, Fiskehamnsgatan 1, S-21118 Malmo, Sweden.
   [Wisz, Mary S.] Univ Iceland, Sci Inst, Saemundargata 2, IS-101 Reykjavik, Iceland.
   [Elsler, Laura G.] Harvard TH Chan Sch Publ Hlth, Boston, MA 02115 USA.
   [Van Deelen, Julie; Auping, Willem L.; Kwakkel, Jan] Delft Univ Technol, Fac Technol Policy & Management, Dept Multiactor Syst, Policy Anal Sect, Jaffalaan 5, NL-2628 BX Delft, Netherlands.
   [Schadeberg, Amanda] Wageningen Univ, Environm Econ & Nat Resources Grp, Hollandseweg 1, NL-6706 KN Wageningen, Netherlands.
   [Schadeberg, Amanda] Wageningen Univ, Environm Policy Grp, Hollandseweg 1, NL-6706 KN Wageningen, Netherlands.
   [Vastenhoud, Berthe M. J.] Tech Univ Denmark, Natl Inst Aquat Resources, Kemitorvet 201, DK-2800 Lyngby, Denmark.
   [Nedelciu, Claudiu Eduard] Univ Bergen, Dept Geog, Syst Dynam Grp, Fosswinckelsgate 6, N-5007 Bergen, Norway.
   [Prellezo, Raul] AZTI Marine Res Unit Txatxarramendi Ugartea Z G, Sukarrieta 48395, Spain.
C3 University of Iceland; Harvard University; Harvard T.H. Chan School of
   Public Health; Delft University of Technology; Wageningen University &
   Research; Wageningen University & Research; Technical University of
   Denmark; University of Bergen
RP Oostdijk, M (corresponding author), Agr Univ Iceland, Fac Agr Sci, Keldnaholt,Arleynir 22, IS-112 Reykjavik, Iceland.; Auping, WL (corresponding author), Delft Univ Technol, Fac Technol Policy & Management, Dept Multiactor Syst, Policy Anal Sect, Jaffalaan 5, NL-2628 BX Delft, Netherlands.
EM maartjeoostdijk@gmail.com; l.elsler@outlook.com;
   vandeelen.julie@technopolis-group.com; W.L.Auping@tudelft.nl;
   j.h.kwakkel@tudelft.nl; amanda.schadeberg@wur.nl; bmjv@aqua.dtu.dk;
   Claudiu.Nedelciu@uib.no; fab@wmu.se; rprellezo@azti.es; msw@wmu.se
RI Kwakkel, Jan/D-9680-2013; Auping, Willem/ABE-5689-2021; Schadeberg,
   Amanda/PIF-8024-2026; Wisz, Mary/J-7826-2013; Prellezo, Raul/B-8231-2009
OI Auping, Willem/0000-0003-1898-643X; Schadeberg,
   Amanda/0000-0003-4758-7331; Vastenhoud, Berthe Maria
   Johanna/0000-0002-1729-5998; 
FU Horizon 2020 Framework Programme [2019-2023, 817669]; Horizon 2020
   project MEESO Ecologically and Economically Sustainable Mesopelagic
   Fisheries [817806]; European Union's Horizon 2020 research and
   innovation program; H2020 Societal Challenges Programme [817806] Funding
   Source: H2020 Societal Challenges Programme
FX This work is delivered as part of the Horizon 2020 project MEESO
   Ecologically and Economically Sustainable Mesopelagic Fisheries
   (2019-2023), Grant Agreement No. 817669. RP acknowledges funding from
   the European Union's Horizon 2020 research and innovation program under
   Grant Agreements No. 817806 (SUMMER). We thank the stakeholders for
   participating in our interview campaign and the workshop. We also thank
   Marloes Kraan for her leading role in organizing the two stakeholder
   workshops and Rolf Groeneveld for supporting the organization of the
   stakeholder workshops, and comments on the paper. We also thank two
   anonymous reviewers for their constructive comments.
CR Alvheim AR, 2020, FOODS, V9, DOI 10.3390/foods9030344
   Anderson TR, 2019, ICES J MAR SCI, V76, P690, DOI 10.1093/icesjms/fsx234
   [Anonymous], 2007, STAT WORLD FISH AQ 2, DOI [10.4060/ca9229en, DOI 10.4060/CC0461-N, DOI 10.4060/CA9229EN]
   [Anonymous], 2021, THESIS TU DELFT
   Barange M, 2017, FRONT MAR SCI, V3, DOI 10.3389/fmars.2016.00290
   Bernstein JH, 2015, J RES PRACT, V11
   Bisson K, 2023, COMMUN EARTH ENVIRON, V4, DOI 10.1038/s43247-023-00823-4
   Bjelle EL, 2021, ECOL ECON, V185, DOI 10.1016/j.ecolecon.2021.107059
   Bjorndal T, 2014, MAR RESOUR ECON, V29, P69, DOI 10.1086/676286
   Boyd PW, 2019, NATURE, V568, P327, DOI 10.1038/s41586-019-1098-2
   Brown V.A., 2010, Tackling the Wicked Problems, Earth Scan
   Caddell R, 2018, INT J MAR COAST LAW, V33, P199, DOI 10.1163/15718085-13310013
   Carpenter G, 2016, MAR POLICY, V64, P9, DOI 10.1016/j.marpol.2015.11.001
   Chancel L, 2022, NAT SUSTAIN, V5, P931, DOI 10.1038/s41893-022-00955-z
   Cottrell RS, 2021, REV AQUACULT, V13, P1583, DOI 10.1111/raq.12535
   Cullis-Suzuki S, 2010, MAR POLICY, V34, P1036, DOI 10.1016/j.marpol.2010.03.002
   Davison PC, 2013, PROG OCEANOGR, V116, P14, DOI 10.1016/j.pocean.2013.05.013
   Dornan T, 2022, P ROY SOC B-BIOL SCI, V289, DOI 10.1098/rspb.2021.1781
   Dowd S, 2022, ECOL APPL, V32, DOI 10.1002/eap.2578
   Drazen JC, 2017, ANNU REV MAR SCI, V9, P337, DOI 10.1146/annurev-marine-010816-060543
   Elsler LG, 2022, FRONT MAR SCI, V9, DOI 10.3389/fmars.2022.880424
   Elsler LG, 2021, REG ENVIRON CHANGE, V21, DOI 10.1007/s10113-021-01747-5
   Eppinga MB, 2023, ECOL ECON, V211, DOI 10.1016/j.ecolecon.2023.107861
   Fjeld K, 2023, MAR POLICY, V147, DOI 10.1016/j.marpol.2022.105359
   Forrester JW., 1961, IND DYNAMICS
   Free CM, 2022, NATURE, V605, P490, DOI 10.1038/s41586-022-04674-5
   Froehlich HE, 2018, NAT SUSTAIN, V1, P298, DOI 10.1038/s41893-018-0077-1
   Froese R, 2017, FISH FISH, V18, P506, DOI 10.1111/faf.12190
   Fryxell JM, 2017, P NATL ACAD SCI USA, V114, P12333, DOI 10.1073/pnas.1705525114
   Funtowicz S.O., 1990, Uncertainty and Quality in Science for Policy, DOI DOI 10.1007/978-94-009-0621-1
   Groeneveld R., 2022, SHOULD WE FISH MESOP
   Halim RA, 2016, FUTURES, V81, P148, DOI 10.1016/j.futures.2015.09.004
   Hickel J, 2022, GLOBAL ENVIRON CHANG, V73, DOI 10.1016/j.gloenvcha.2022.102467
   Hicks CC, 2019, NATURE, V574, P95, DOI 10.1038/s41586-019-1592-6
   Hidalgo M, 2019, ICES J MAR SCI, V76, P609, DOI 10.1093/icesjms/fsz067
   ICES, 2020, ICES STRATEGY, V5, DOI [10.17895/ices.pub.5466, DOI 10.17895/ICES.PUB.5466]
   ICES, 2022, ICES ADVICE 2022, DOI [10.17895/ices.pub.c.5796935.v105, DOI 10.17895/ICES.PUB.C.5796935.V105]
   Iglesias IS, 2023, FRONT MAR SCI, V10, DOI 10.3389/fmars.2023.1220088
   Irigoien X, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms4271
   JACKSON A., 2009, International Aquafeed, V12, P32
   Jaxa-Rozen M, 2018, ENVIRON MODELL SOFTW, V107, P245, DOI 10.1016/j.envsoft.2018.06.011
   Jin D, 2020, SCI TOTAL ENVIRON, V749, DOI 10.1016/j.scitotenv.2020.141357
   Kaartvedt S, 2012, MAR ECOL PROG SER, V456, P1, DOI 10.3354/meps09785
   Kourantidou M, 2022, NAT RESOUR MODEL, V35, DOI 10.1111/nrm.12350
   Kraan M., 2022, REPORT REPORT SYSTEM
   Kwakkel JH, 2017, ENVIRON MODELL SOFTW, V96, P239, DOI 10.1016/j.envsoft.2017.06.054
   Kwakkel JH, 2016, J WATER RES PLAN MAN, V142, DOI 10.1061/(ASCE)WR.1943-5452.0000626
   Lade S.J., 2022, ROUTLEDGE HDB RES ME, P359
   Lade SJ, 2020, NAT SUSTAIN, V3, P119, DOI 10.1038/s41893-019-0454-4
   Lassen H, 2014, ICES J MAR SCI, V71, P166, DOI 10.1093/icesjms/fst146
   Lenton TM, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0123
   Marchau V.A. W. J., 2019, Decision making under deep uncertainty, DOI [DOI 10.1007/978-3-030-05252-2, 10.1007/978-3-030-05252-2]
   Mariani G, 2020, SCI ADV, V6, DOI 10.1126/sciadv.abb4848
   Marine Research Institute, 2015, MARINE RES ICELAND, P182
   Martin AH, 2021, ONE EARTH, V4, P680, DOI 10.1016/j.oneear.2021.04.019
   Martin R, 2015, FRONT ENV SCI-SWITZ, V3, DOI 10.3389/fenvs.2015.00066
   McMonagle H, 2023, PROG OCEANOGR, V217, DOI 10.1016/j.pocean.2023.103078
   Melnychuk MC, 2017, P NATL ACAD SCI USA, V114, P178, DOI 10.1073/pnas.1609915114
   Moallemi EA, 2020, GLOBAL ENVIRON CHANG, V65, DOI 10.1016/j.gloenvcha.2020.102186
   Morzaria-Luna HN, 2022, MAR ECOL PROG SER, V681, P37, DOI 10.3354/meps13900
   Navarro-Racines C, 2020, SCI DATA, V7, DOI 10.1038/s41597-019-0343-8
   Naylor RL, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-25516-4
   Olivar MP, 2012, DEEP-SEA RES PT I, V62, P53, DOI 10.1016/j.dsr.2011.12.014
   Olivar MP, 2022, DEEP-SEA RES PT II, V198, DOI 10.1016/j.dsr2.2022.105053
   Oostdijk M, 2022, FRONT MAR SCI, V9, DOI 10.3389/fmars.2022.764609
   Orach K, 2017, ENVIRON SCI POLICY, V76, P90, DOI 10.1016/j.envsci.2017.06.010
   Pace ML, 2017, ECOSYSTEMS, V20, P44, DOI 10.1007/s10021-016-0021-z
   Paoletti S, 2021, FRONT MAR SCI, V08, DOI 10.3389/fmars.2021.720897
   Passow U, 2012, MAR ECOL PROG SER, V470, P249, DOI 10.3354/meps09985
   Perissi I, 2017, ECOL MODEL, V359, P285, DOI 10.1016/j.ecolmodel.2017.06.009
   Petrik CM, 2019, PROG OCEANOGR, V176, DOI 10.1016/j.pocean.2019.102124
   Pinti J, 2023, BIOGEOSCIENCES, V20, P997, DOI 10.5194/bg-20-997-2023
   Pörtner HO, 2023, SCIENCE, V380, DOI 10.1126/science.abl4881
   Pouso S, 2019, ESTUAR COAST SHELF S, V217, P226, DOI 10.1016/j.ecss.2018.11.026
   Prellezo R, 2019, ICES J MAR SCI, V76, P771, DOI 10.1093/icesjms/fsy001
   Proud R, 2019, ICES J MAR SCI, V76, P718, DOI 10.1093/icesjms/fsy037
   Proud R, 2017, CURR BIOL, V27, P113, DOI 10.1016/j.cub.2016.11.003
   Rennert K, 2022, NATURE, V610, P687, DOI 10.1038/s41586-022-05224-9
   Richards DR, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18118-z
   Robinson C, 2010, DEEP-SEA RES PT II, V57, P1504, DOI 10.1016/j.dsr2.2010.02.018
   Röckmann C, 2012, MAR POLICY, V36, P1072, DOI 10.1016/j.marpol.2012.02.027
   Saba GK, 2021, LIMNOL OCEANOGR, V66, P1639, DOI 10.1002/lno.11709
   Schadeberg A, 2023, NPJ OCEAN SUSTAIN, V2, DOI [10.1038/s44183-023-00008-8, 10.1038/s44183-023-00008-8]
   SCHAEFER MB, 1957, J FISH RES BOARD CAN, V14, P669, DOI 10.1139/f57-025
   St John MA, 2016, FRONT MAR SCI, V3, DOI 10.3389/fmars.2016.00031
   Thorson JT, 2017, ECOL APPL, V27, P2262, DOI 10.1002/eap.1606
   UNFSA, 1995, UN C STRADD FISH STO
   van Denderen PD, 2021, GLOBAL ECOL BIOGEOGR, V30, P1822, DOI 10.1111/geb.13348
   Machado FLV, 2021, ECOL ECON, V185, DOI 10.1016/j.ecolecon.2021.107057
   Vastenhoud BMJ, 2023, FRONT MAR SCI, V10, DOI 10.3389/fmars.2023.1285793
   Woods PJ, 2015, MAR POLICY, V55, P1, DOI 10.1016/j.marpol.2015.01.004
NR 91
TC 14
Z9 15
U1 0
U2 12
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0044-7447
EI 1654-7209
J9 AMBIO
JI Ambio
PD NOV
PY 2024
VL 53
IS 11
BP 1632
EP 1648
DI 10.1007/s13280-024-02044-1
EA AUG 2024
PG 17
WC Engineering, Environmental; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Environmental Sciences & Ecology
GA H2Q9A
UT WOS:001302296100002
PM 39207669
OA Green Submitted, hybrid
DA 2026-06-14
ER

PT J
AU Quang, RGT
   Kourantidou, M
   Jin, D
AF Quang, Rohan Gowda Thanh
   Kourantidou, Melina
   Jin, Di
TI Assessing the potential economic effects of mesopelagic fisheries as a
   novel source of fishmeal
SO NATURAL RESOURCE MODELING
LA English
DT Article
DE aquaculture; fishmeal; forage fisheries; markets; mesopelagic;
   profitability
ID CARBON
AB The continuous growth of the aquaculture industry implies increased demand for efficient sources of aquafeed, such as fishmeal. Pelagic fish are a desirable source of fishmeal due to their high nutritional content. Nevertheless, several pelagic stocks that have been exploited extensively for fishmeal production face ecological limits due to commercial exploitation, and the aquaculture industry is now seeking novel, efficient, and sustainable sources of aquafeed. The mesopelagic zone, an ecosystem with many scientific uncertainties, is being considered as a potential source for fishmeal, largely owing to the abundance of mesopelagic fish and their robust nutritional profile. However, both the ecological and economic viability of commercial exploitation of mesopelagic fish are not yet well understood. To understand the conditions that would make such an endeavor economically viable in the context of global fishmeal production systems, we use a bioeconomic model that assesses the economic consequences of including mesopelagic fish as a fishmeal source. Through simulations, we assess the economic implications of this hypothetical mesopelagic fishery on major pelagic fishmeal production systems. The mesopelagic fishery can be economically profitable for harvesters, and its addition to global fishmeal production reduces fishmeal market price, thus making it more accessible to aquaculture farmers and less profitable for pelagic fishers. While this may reduce fishing pressure on pelagic forage-fish stocks, the implications of commercial exploitation of mesopelagic on key ecosystem services remain a concern.
   The continuous growth of the aquaculture industry implies increased demand for efficient sources of aquafeed, such as fishmeal. Several pelagic stocks that have been exploited extensively for fishmeal production face ecological limits due to commercial exploitation, and the aquaculture industry is now seeking novel, efficient, and sustainable sources of aquafeed. The mesopelagic zone is being considered as a potential source for fishmeal. However, both the ecological and economic viability of commercial exploitation of mesopelagic fish are not yet well understood. We use a bioeconomic model to assess the economic consequences of including mesopelagic fish as a fishmeal source and the economic implications of this hypothetical fishery on major pelagic fishmeal production systems. The results show that mesopelagic fishery could be profitable for harvesters, and its addition to global fishmeal production would reduce fishmeal market price, thus making it more accessible to aquaculture farmers and less profitable for pelagic fishers.
C1 [Quang, Rohan Gowda Thanh] Pomona Coll, Biol Dept, Claremont, CA USA.
   [Kourantidou, Melina; Jin, Di] Woods Hole Oceanog Inst, Marine Policy Ctr, Woods Hole, MA USA.
   [Kourantidou, Melina] Univ Southern Denmark, Dept Sociol Environm & Business Econ, Esbjerg, Denmark.
   [Kourantidou, Melina] Univ Bretagne Occidentale, AMURE, Plouzane, France.
   [Jin, Di] Woods Hole Oceanog Inst, Marine Policy Ctr, Falmouth, MA 02543 USA.
C3 Claremont Colleges; Pomona College; Woods Hole Oceanographic
   Institution; University of Southern Denmark; Universite de Bretagne
   Occidentale; Ifremer; Woods Hole Oceanographic Institution
RP Jin, D (corresponding author), Woods Hole Oceanog Inst, Marine Policy Ctr, Falmouth, MA 02543 USA.
EM djin@whoi.edu
RI ; Jin, Di/KHX-5887-2024
OI Kourantidou, Melina/0000-0001-9595-3354; Jin, Di/0000-0002-6403-7983
FU WHOI's Ocean Twilight Zone program which is part of the Audacious
   Project, a collaborative endeavor, housed at TED; WHOI Summer Student
   Fellowship program
FX This study is supported by WHOI's Ocean Twilight Zone program which is
   part of the Audacious Project, a collaborative endeavor, housed at TED.
   Rohan Gowda Thanh Quang would like to thank the WHOI Summer Student
   Fellowship program for support. We also wish to thank the two anonymous
   reviewers for their constructive comments.
CR Alvheim AR, 2020, FOODS, V9, DOI 10.3390/foods9030344
   Anderson TR, 2019, ICES J MAR SCI, V76, P690, DOI 10.1093/icesjms/fsx234
   [Anonymous], 2007, STAT WORLD FISH AQ 2, DOI [10.4060/ca9229en, DOI 10.4060/CC0461-N, DOI 10.4060/CA9229EN]
   [Anonymous], 1997, REV STATE WORLD FISH
   [Anonymous], 2022, OECD-FAO Agricultural Outlook 2022-2031, DOI DOI 10.1787/F1B0B29C-EN
   [Anonymous], 2014, Sustainable Fisheries and Aquaculture for Food Security and Nutrition. A Report by the High Level Panel of Experts on Food Security and Nutrition of the Committee on World Food Security
   Buesseler K., 2022, OCEAN TWILIGHT ZONES
   Dowd S, 2022, ECOL APPL, V32, DOI 10.1002/eap.2578
   EUMOFA, 2018, Situation Report and Perspectives
   Fjeld K, 2023, MAR POLICY, V147, DOI 10.1016/j.marpol.2022.105359
   Froehlich HE, 2018, NAT SUSTAIN, V1, P298, DOI 10.1038/s41893-018-0077-1
   Garlock T, 2022, GLOB FOOD SECUR-AGR, V32, DOI 10.1016/j.gfs.2022.100620
   Gatto A, 2023, RESOUR CONSERV RECY, V197, DOI 10.1016/j.resconrec.2023.106907
   Geay F, 2011, BMC GENOMICS, V12, DOI 10.1186/1471-2164-12-522
   Grimaldo E, 2020, ICES J MAR SCI, V77, P2541, DOI 10.1093/icesjms/fsaa114
   Hidaka K, 2001, DEEP-SEA RES PT I, V48, P1923, DOI 10.1016/S0967-0637(01)00003-6
   IndexMundi, 2023, FISH MEAL PRODUCTION
   Irigoien X, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms4271
   Johnson P, 2011, TRADE OFFS BIODIVERS
   Kourantidou M, 2022, NAT RESOUR MODEL, V35, DOI 10.1111/nrm.12350
   Liu T, 2021, AQUACULT REP, V20, DOI 10.1016/j.aqrep.2021.100756
   Liu XR, 2020, AQUACULT REP, V18, DOI 10.1016/j.aqrep.2020.100472
   Mariani G, 2020, SCI ADV, V6, DOI 10.1126/sciadv.abb4848
   Martin AH, 2021, ONE EARTH, V4, P680, DOI 10.1016/j.oneear.2021.04.019
   Merino G, 2012, GLOBAL ENVIRON CHANG, V22, P795, DOI 10.1016/j.gloenvcha.2012.03.003
   Merino G, 2010, J MARINE SYST, V81, P196, DOI 10.1016/j.jmarsys.2009.12.010
   Mullon C, 2009, NAT RESOUR MODEL, V22, P564, DOI 10.1111/j.1939-7445.2009.00053.x
   Naito Y, 2013, FUNCT ECOL, V27, P710, DOI 10.1111/1365-2435.12083
   Naylor RL, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-25516-4
   Ntsama I.S.B., 2018, EGYPT J AQUATIC RES, V44, P145, DOI [10.1016/j.ejar.2018.06.006, DOI 10.1016/j.ejar.2018.06.006, 10.1016/j.ejar.2018.06.006, DOI 10.1016/J.EJAR.2018.06.006]
   Olsen RE, 2020, DEEP-SEA RES PT II, V180, DOI 10.1016/j.dsr2.2019.104722
   Paoletti S, 2021, FRONT MAR SCI, V08, DOI 10.3389/fmars.2021.720897
   Prellezo R, 2019, ICES J MAR SCI, V76, P771, DOI 10.1093/icesjms/fsy001
   Roberts C M., 2020, Entering the Twilight Zone: The ecological role and importance of mesopelagic fishes
   Saba GK, 2021, LIMNOL OCEANOGR, V66, P1639, DOI 10.1002/lno.11709
   Schadeberg A, 2023, NPJ OCEAN SUSTAIN, V2, DOI [10.1038/s44183-023-00008-8, 10.1038/s44183-023-00008-8]
   Schaefer M., 1954, Bulletin of the Inter-American Tropical Tuna Commission, V1, P27, DOI DOI 10.1007/BF02464432
   Sigurdsson T., 2015, STATE MARINE STOCKS
   Smith ADM, 2011, SCIENCE, V333, P1147, DOI 10.1126/science.1209395
   St John MA, 2016, FRONT MAR SCI, V3, DOI 10.3389/fmars.2016.00031
   Standal D, 2020, MAR POLICY, V119, DOI 10.1016/j.marpol.2020.104043
   Ulrich C, 2002, FISH RES, V58, P379, DOI 10.1016/S0165-7836(01)00393-9
   Underwood Melanie J., 2021, Aquaculture and Fisheries, V6, P519, DOI [10.1016/j.aaf.2020.05.002, 10.1016/j.aaf.2020.05.002]
   Valinassab T, 2007, J APPL ICHTHYOL, V23, P573, DOI 10.1111/j.1439-0426.2007.01034.x
   Vastenhoud BMJ, 2023, FRONT MAR SCI, V10, DOI 10.3389/fmars.2023.1285793
NR 45
TC 6
Z9 7
U1 0
U2 17
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0890-8575
EI 1939-7445
J9 NAT RESOUR MODEL
JI Nat. Resour. Model.
PD AUG
PY 2024
VL 37
IS 3
DI 10.1111/nrm.12398
EA APR 2024
PG 19
WC Environmental Sciences; Mathematics, Interdisciplinary Applications
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Mathematics
GA C4T9Y
UT WOS:001208136700001
OA Green Submitted, gold
DA 2026-06-14
ER

PT J
AU Buendia-Hernandez, FA
   Alvarez-Garcia, FJ
   OrtizBevia, MJ
   RuizdeElvira, A
AF Buendia-Hernandez, Francisco A.
   Alvarez-Garcia, Francisco J.
   OrtizBevia, Maria J.
   RuizdeElvira, Antonio
TI Dynamic modeling of air traffic emissions with a two variable system
SO INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION
LA English
DT Article
DE Air traffic emissions; emissions stabilization; environmental policies;
   feedbacks; two variable model
ID CLIMATE-CHANGE; AVIATION EMISSIONS; CARBON EMISSIONS; CO2 EMISSIONS;
   TRANSPORT; IMPACTS; ATTITUDES
AB Greenhouse gases emissions modify the radiative balance of the Earth, causing changes in its climate. Climate Change is considered one of the greatest threats to economic and social stability. Aviation is responsible for around a 2.5% of greenhouse gases emissions. This contribution is steadily increasing, thus the interest of assessing the impacts that different policies might have on it. The simple feedback model proposed here was intended as a tool in order to investigate the stabilization issue. The model was based on the relationship between the number of air traffic passengers and the associated CO2 emissions. It incorporated a representation of the feedback of the technological innovation on the emissions rate and of those of the socioeconomic response to the climatic impact on the passengers number. The model parameters were estimated using data from a variety of robust air traffic sources. However, it was found that neither of the feedback terms succeeded at stabilizing the emissions, although they might slow down their growth. In addition, there is also a nonlinear version of the model that includes a representation of the passengers perception of insecurity, similar to the one experienced in the current pandemic. This model favors the stability of both, the number of passengers and CO2 emissions, as it would also be able to control unprecedented situations.
C1 [Buendia-Hernandez, Francisco A.; Alvarez-Garcia, Francisco J.; OrtizBevia, Maria J.; RuizdeElvira, Antonio] Univ Alcala, Dept Fis & Matemat, Madrid 28801, Spain.
C3 Universidad de Alcala
RP OrtizBevia, MJ (corresponding author), Univ Alcala, Dept Fis & Matemat, Madrid 28801, Spain.
EM mjose.ortiz@uah.es
RI ; BUENDIA, FRANCISCO/PDW-2615-2025
OI Ruiz de Elvira, Antonio/0000-0001-9067-0865; OrtizBevia, Maria
   J/0000-0003-1644-2041; 
CR Ackerman J., 2005, TRANSPORT RES D-TR E, V10, P11
   [Anonymous], 2007, MITIGATION CLIMATE C
   [Anonymous], Climate Change 2014, Synthesis Report, DOI DOI 10.1017/CBO9781107415416.005
   [Anonymous], 2008, AN EUR AIR TRANSP MA
   Bock L, 2019, ATMOS CHEM PHYS, V19, P8163, DOI 10.5194/acp-19-8163-2019
   Brasseur GP, 2016, B AM METEOROL SOC, V97, P561, DOI 10.1175/BAMS-D-13-00089.1
   Chao H, 2019, TRANSPORT RES D-TR E, V75, P42, DOI 10.1016/j.trd.2019.08.015
   Chen D, 2016, TRANSPORT RES D-TR E, V48, P46, DOI 10.1016/j.trd.2016.08.003
   Chen ZH, 2019, TRANSPORT RES D-TR E, V69, P168, DOI 10.1016/j.trd.2019.01.030
   Chevallier J., 2011, ECON INTEGRATION, V2, P151
   Cheze B., 2010, CAHIERS EC
   Chèze B, 2013, TRANSPORT RES D-TR E, V18, P91, DOI 10.1016/j.trd.2012.08.008
   Chèze B, 2011, ENERG POLICY, V39, P5147, DOI 10.1016/j.enpol.2011.05.049
   Choi AS, 2018, TRANSPORT RES D-TR E, V62, P225, DOI 10.1016/j.trd.2018.02.018
   Davison L, 2014, J AIR TRANSP MANAG, V36, P13, DOI 10.1016/j.jairtraman.2013.12.007
   Dietz S, 2018, ANNU REV ENV RESOUR, V43, P455, DOI 10.1146/annurev-environ-102017-025817
   Eckstein D., 2021, Global Climate Risk Index 2021
   Fukui H, 2017, TRANSPORT RES D-TR E, V50, P234, DOI 10.1016/j.trd.2016.10.015
   Gössling S, 2020, J CLEAN PROD, V266, DOI 10.1016/j.jclepro.2020.122015
   Hassan M, 2018, TRANSPORT RES D-TR E, V63, P362, DOI 10.1016/j.trd.2018.06.006
   Hermans J, 2017, MRS ENERGY SUSTAIN, V4, DOI 10.1557/mre.2017.2
   Higham JES, 2014, J TRAVEL RES, V53, P462, DOI 10.1177/0047287513500393
   ICAO, 2016, ENV REPORT
   Krammer P, 2013, TRANSPORT RES D-TR E, V23, P64, DOI 10.1016/j.trd.2013.03.013
   Kreuz M., 2013, WCTR2013RIO SELECTED
   Lee DS, 2009, ATMOS ENVIRON, V43, P3520, DOI 10.1016/j.atmosenv.2009.04.024
   Lee J, 2011, INT J ENV RES PUB HE, V8, P3777, DOI 10.3390/ijerph8093777
   Lu JL, 2018, TRANSPORT RES D-TR E, V59, P96, DOI 10.1016/j.trd.2017.12.024
   Macintosh A, 2009, ENERG POLICY, V37, P264, DOI 10.1016/j.enpol.2008.08.029
   Morrell P, 2009, J AIR TRANSP MANAG, V15, P151, DOI 10.1016/j.jairtraman.2008.09.021
   Owen B, 2010, ENVIRON SCI TECHNOL, V44, P2255, DOI 10.1021/es902530z
   Peeters P, 2016, TRANSPORT RES D-TR E, V44, P30, DOI 10.1016/j.trd.2016.02.004
   Pejovic T, 2008, CLIMATIC CHANGE, V88, P367, DOI 10.1007/s10584-007-9370-0
   Perko L., 2001, DIFFER EQUAT DYN SYS, V7, DOI [DOI 10.1007/978-1-4613-0003-8, 10.1007/978-1-4613-0003-8]
   Sanderson BM, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-66275-4
   Scheelhaase JD, 2016, TRANSPORT RES D-TR E, V45, P112, DOI 10.1016/j.trd.2015.09.002
   Upham, 2009, CALCULATING EMISSION
   Urban, 2017, 450125 DEUTSCHELUFT
   van Manen J, 2019, TRANSPORT RES D-TR E, V67, P388, DOI 10.1016/j.trd.2018.12.016
   Vedantham A, 1998, ENERG POLICY, V26, P625, DOI 10.1016/S0301-4215(98)00021-4
   Wasiuk DK, 2015, TRANSPORT RES D-TR E, V35, P142, DOI 10.1016/j.trd.2014.11.022
   Zanin M, 2013, EUR PHYS J-SPEC TOP, V215, P5, DOI 10.1140/epjst/e2013-01711-9
   Zhang SR, 2016, NETW SPAT ECON, V16, P643, DOI 10.1007/s11067-015-9292-8
NR 43
TC 6
Z9 6
U1 0
U2 8
PU TAYLOR & FRANCIS INC
PI PHILADELPHIA
PA 530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA
SN 1556-8318
EI 1556-8334
J9 INT J SUSTAIN TRANSP
JI Int. J. Sustain. Transp.
PD NOV 3
PY 2021
VL 16
IS 11
BP 1003
EP 1012
DI 10.1080/15568318.2021.1959683
EA JUL 2021
PG 10
WC Green & Sustainable Science & Technology; Environmental Studies;
   Transportation
WE Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology;
   Transportation
GA 5X1SQ
UT WOS:000686415600001
DA 2026-06-14
ER

PT J
AU Nguyen, RT
   Eggert, RG
   Severson, MH
   Anderson, CG
AF Nguyen, Ruby T.
   Eggert, Roderick G.
   Severson, Mike H.
   Anderson, Corby G.
TI Global Electrification of Vehicles and Intertwined Material Supply
   Chains of Cobalt, Copper and Nickel
SO RESOURCES CONSERVATION AND RECYCLING
LA English
DT Article
ID FUTURE; FLOWS; BATTERIES; TRACKING
AB Electric vehicles (EVs) will be an important part of a low-carbon economy. Future EV adoption depends on overcoming multiple barriers, including charging infrastructure, sufficient electricity generation, and the availability of battery raw materials at acceptable costs, including cobalt, copper and nickel - which typically are co-produced. Various EV projections have been made, along with associated requirements for battery raw materials (demand). There have been separate assessments of the availability of raw materials (supply). However, integrated assessments of supply and demand and their interaction over time are lacking to support decision-making. Using a dynamic market model that reflects the co-produced nature of cobalt, copper and nickel production as well as recycling, we estimate global output of these three metals under different EV growth scenarios from 2020 to 2040. Results suggest that starting in 2025, replacement demand for battery raw materials becomes important. Thus, estimates for future material demand that consider only demands from new EVs are incomplete and misleading. EV deployment and associated increased demand for raw materials will have a greater impact on prices for cobalt than nickel and, in turn, for nickel than copper. High EV deployment scenarios will be difficult to achieve without larger supplies of copper, nickel and cobalt than forthcoming under the conditions modeled here, which anticipates a six-year time lag between a demand increase and the expansion of metal-production capacity. Shortening battery lifetimes and improving collection and recycling rates increase secondary supply, but the extent to which these factors support additional EV deployment is mixed.
C1 [Nguyen, Ruby T.; Severson, Mike H.] Idaho Natl Lab, Idaho Falls, ID 83402 USA.
   [Eggert, Roderick G.; Anderson, Corby G.] Colorado Sch Mines, Golden, CO 80401 USA.
C3 United States Department of Energy (DOE); Idaho National Laboratory;
   Colorado School of Mines
RP Nguyen, RT (corresponding author), Idaho Natl Lab, Idaho Falls, ID 83402 USA.
EM ruby.nguyen@inl.gov
RI ; Nguyen, Ruby/O-5931-2019
OI Severson, Mike/0000-0002-3895-7698; Nguyen, Ruby/0000-0002-5791-5004
FU Critical Materials Institute, an Energy Innovation Hub - U.S. Department
   of Energy, Office of Energy Efficiency and Renewable Energy, Advanced
   Manufacturing Office [AL-12-350-001]; U.S. Department of Energy
   [DE-AC07-05ID14517]
FX This work is supported by the Critical Materials Institute, an Energy
   Innovation Hub funded by the U.S. Department of Energy, Office of Energy
   Efficiency and Renewable Energy, Advanced Manufacturing Office under
   Grant AL-12-350-001. (c) This manuscript has been authored by Battelle
   Energy Alliance, LLC under Contract No. DE-AC07-05ID14517 with the U.S.
   Department of Energy. The United States Government retains and the
   publisher, by accepting the article for publication, acknowledges that
   the United States Government retains a nonexclusive, paid-up,
   irrevocable, world-wide license to publish or reproduce the published
   form of this manuscript, or allow others to do so, for United States
   Government purposes.
CR [Anonymous], 2018, COBALT DEMAND SUPPLY, DOI DOI 10.2760/97710
   Australian Mines Limited, 2018, BANK FEAS STUD SUPP, P122
   Azevedo M., 2018, METALS MINING, P19
   Baker T., 2019, ELECT VEHICLES ARE M, P7
   Bloomberg New Energy Finance, 2019, EL VEH OUTL 2019
   Burton M., 2019, DOWNTURN BATTERY RAW
   Campagnol N., 2017, FUTURE NICKEL CLASS, P14
   Chen ZY, 2019, SCI TOTAL ENVIRON, V672, P752, DOI 10.1016/j.scitotenv.2019.02.411
   Cobalt Institute, 2019, COB PROD STAT
   Cooper A., 2018, ELECT VEHICLE SALES, P15
   Copper Development Association Inc, 2017, COPP DRIV EL VEH
   Deloitte, 2019, NEW MARK NEW ENTR NE, P20
   Derousseau M, 2017, JOM-US, V69, P1575, DOI 10.1007/s11837-017-2368-9
   eCobalt, 2019, BUILD N AM NEXT PRIM
   Elshkaki A, 2017, RESOUR CONSERV RECY, V125, P300, DOI 10.1016/j.resconrec.2017.07.002
   Fischer CS, 2011, EUR PHYS J A, V47, DOI 10.1140/epja/i2011-11028-1
   Forrester JayWright., 2013, Industrial dynamics
   Fu XK, 2020, ENVIRON SCI TECHNOL, V54, P2985, DOI 10.1021/acs.est.9b04975
   Gaines L, 2014, SUSTAIN MATER TECHNO, V1-2, P2, DOI 10.1016/j.susmat.2014.10.001
   Glöser S, 2013, ENVIRON SCI TECHNOL, V47, P6564, DOI 10.1021/es400069b
   Glöser-Chahoud S, 2016, SYST DYNAM REV, V32, P279, DOI 10.1002/sdr.1565
   Harper EM, 2012, ENVIRON SCI TECHNOL, V46, P1079, DOI 10.1021/es201874e
   Harper G, 2019, NATURE, V575, P75, DOI 10.1038/s41586-019-1682-5
   International Copper Study Group, 2018, WORLD COPP FACTB 201
   International Energy Agency, 2017, GLOB EV OUTL 2018 CR, P144
   International Energy Agency, 2019, GLOBAL EV OUTLOOK 20, P219
   InvestmentMine, 2020, HIST NICK PRIC PRIC
   InvestmentMine, 2020, HIST COPP PRIC PRIC
   InvestmentMine, 2020, HIST COB PRIC PRIC C
   Kennedy W., 2019, BLOOMBERG
   McNulty T., 2014, PLANT RAMP PROFILES
   McRae M.E., 2018, 2015 MINERALS YB NIC, P29
   Nguyen RT, 2019, WASTE MANAGE, V83, P209, DOI 10.1016/j.wasman.2018.11.017
   OICA, 2020, SAL NEW VEH 2005 201
   Olivetti EA, 2017, JOULE, V1, P229, DOI 10.1016/j.joule.2017.08.019
   Richa K, 2014, RESOUR CONSERV RECY, V83, P63, DOI 10.1016/j.resconrec.2013.11.008
   Roskill, 2018, COB GLOB IND MARK OU, V14th
   Scheele F., 2016, ENV POLLUTION
   Selby M., 2017, METAL B 5 INT NICK C
   Shedd K.B., 2017, GLOBAL TRENDS AFFECT
   Shedd K.B., 2017, 2015 MINERALS YB COB, P19
   Sherritt, 2017, INV PRES
   Singer DA, 2017, ORE GEOL REV, V86, P271, DOI 10.1016/j.oregeorev.2017.02.022
   SNL Metals & Mining, 2015, SNL MET MIN LAUNCH A
   Standridge C R., 2014, Remanufacturing, Repurposing and Recycling of Post-Vehicle-Application Lithium-Ion Batteries
   Sverdrup HU, 2014, RESOUR CONSERV RECY, V87, P158, DOI 10.1016/j.resconrec.2014.03.007
   Sverdrup HU, 2017, BioPhysical Economics and Resource Quality, V2, DOI [10.1007/s41247-017-0017-0, 10.1007/s41247-017-0017-0, DOI 10.1007/S41247-017-0017-0]
   Swanson J, 2002, J OPER RES SOC, V53, P472, DOI 10.1057/palgrave.jors.2601336
   Tisserant A, 2016, Journal of Economic Structures, V5, DOI [10.1186/s40008-016-0035-x, 10.1186/s40008-016-0035-x, DOI 10.1186/S40008-016-0035-X]
   Union of Concerned Scientists, 2020, EL VEH BATT MAT COST
   USGS, 2020, NICK STAT INF
   Wentker M, 2019, ENERGIES, V12, DOI 10.3390/en12030504
   World Population Review, 2020, DR CONG POP 2020
   Xu GC, 2016, J MATER CYCLES WASTE, V18, P469, DOI 10.1007/s10163-016-0487-y
   Yang F, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04826-0
NR 55
TC 87
Z9 99
U1 4
U2 90
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0921-3449
EI 1879-0658
J9 RESOUR CONSERV RECY
JI Resour. Conserv. Recycl.
PD APR
PY 2021
VL 167
AR 105198
DI 10.1016/j.resconrec.2020.105198
EA FEB 2021
PG 11
WC Engineering, Environmental; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Environmental Sciences & Ecology
GA SE4CF
UT WOS:000652020200001
OA Green Submitted
DA 2026-06-14
ER

PT J
AU Vidal, O
   Rostom, FZ
   François, C
   Giraud, G
AF Vidal, Olivier
   Rostom, Fatma Zahra
   Francois, Cyril
   Giraud, Gael
TI Prey-Predator Long-Term Modeling of Copper Reserves, Production,
   Recycling, Price, and Cost of Production
SO ENVIRONMENTAL SCIENCE & TECHNOLOGY
LA English
DT Article
ID NATURAL-RESOURCES; DYNAMIC-ANALYSIS; GLOBAL TRENDS; SCARCITY; DEMAND;
   STOCKS; AVAILABILITY; INDICATORS; METALS; IMPACT
AB The dynamics of copper production is modeled with a prey-predator approach linking the evolution of reserves to that of industrial wealth. Our model differs from earlier approaches in that it does not require a priori knowledge of the initial stock of resources. The model variables and a long-term reference price are estimated from historical data, taking into account the combined effects on price and reserve of technological improvements and changes in ore grade. The business-as-usual scenarios invariably lead to a peak of primary production by the middle of the century. The peak of production is not the result of the complete exhaustion of exploitable copper but of the combination of (1) the deviation of growth of reserves from the exponential historical trend and (2) the incapacity of technological improvements to offset the increase in production costs. In the leveled-off-demand scenario for which future demand is simulated based on assumed evolutions of world population and gross domestic product per capita, no collapse of primary production is observed within the century for optimistic regeneration of reserves and a collection-recycling rate reaching 70% by 2100, at constant energy prices.
C1 [Vidal, Olivier; Francois, Cyril] Univ Grenoble Alpes, ISTerre, F-38400 Gieres, France.
   [Vidal, Olivier; Giraud, Gael] CNRS, F-75016 Paris, France.
   [Rostom, Fatma Zahra] Univ Paris 1 Pantheon Sorbonne, F-75013 Paris, France.
   [Rostom, Fatma Zahra; Giraud, Gael] Chaire Energie & Prosperite, F-75002 Paris, France.
   [Giraud, Gael] Agence Francaise Dev, F-75012 Paris, France.
C3 Communaute Universite Grenoble Alpes; Universite Grenoble Alpes (UGA);
   Centre National de la Recherche Scientifique (CNRS); Institut de
   Recherche pour le Developpement (IRD); Universite Gustave-Eiffel;
   Universite Savoie Mont Blanc; Centre National de la Recherche
   Scientifique (CNRS)
RP Vidal, O (corresponding author), Univ Grenoble Alpes, ISTerre, F-38400 Gieres, France.; Vidal, O (corresponding author), CNRS, F-75016 Paris, France.
EM olivier.vidal@univ-grenoble-alpes.fr
RI vidal, olivier/E-7285-2012
FU SURFER (ADEME)
FX This study was financed by the projects REMINER (Mission
   interdisciplinaire du CNRS) and SURFER (ADEME). The authors thank the
   three anonymous reviewers for their valuable comments.
CR Ali SH, 2017, NATURE, V543, P367, DOI 10.1038/nature21359
   [Anonymous], 2014, COCHILCO COMISION CH
   [Anonymous], 2014, GLOBAL MINERAL RESOU, P3, DOI DOI 10.3133/FS20143004
   Arndt NT, 2017, GEOCHEM PERSPECT, V6, P1, DOI 10.7185/geochempersp.6.1
   Bardi U, 2009, ENERGIES, V2, P646, DOI 10.3390/en20300646
   Bleischwitz R., 2016, SATURATION GROWTH TI
   Bleischwitz R, 2018, GLOBAL ENVIRON CHANG, V48, P86, DOI 10.1016/j.gloenvcha.2017.11.008
   Bolt J, 2014, ECON HIST REV, V67, P627, DOI 10.1111/1468-0289.12032
   Calvo G, 2016, RESOURCES-BASEL, V5, DOI 10.3390/resources5040036
   Chapman P.F., 1974, Metals and Materials, V8, P107
   CHAPMAN PF, 1975, ENERG POLICY, V3, P47, DOI 10.1016/0301-4215(75)90053-1
   Donella H., 1972, Limits to Growth
   Elshkaki A, 2018, ENVIRON SCI TECHNOL, V52, P2491, DOI 10.1021/acs.est.7b05154
   Elshkaki A, 2016, GLOBAL ENVIRON CHANG, V39, P305, DOI 10.1016/j.gloenvcha.2016.06.006
   Gerst MD, 2008, ECON GEOL, V103, P615, DOI 10.2113/gsecongeo.103.3.615
   Glöser S, 2013, ENVIRON SCI TECHNOL, V47, P6564, DOI 10.1021/es400069b
   Gordon RB, 2006, P NATL ACAD SCI USA, V103, P1209, DOI 10.1073/pnas.0509498103
   Govett G., 1976, WORLD MINERAL SUPPLI, V3, P343
   Graedel TE, 2015, P NATL ACAD SCI USA, V112, P6295, DOI 10.1073/pnas.1312752110
   Graedel TE, 2011, ANNU REV MATER RES, V41, P323, DOI 10.1146/annurev-matsci-062910-095759
   Graedel TE, 2010, P NATL ACAD SCI USA, V107, P20905, DOI 10.1073/pnas.1011019107
   Gutowski TG, 2013, PHILOS T R SOC A, V371, DOI 10.1098/rsta.2012.0003
   Harmsen JHM, 2013, ENERGY, V50, P62, DOI 10.1016/j.energy.2012.12.006
   Henckens MLCM, 2016, RESOUR POLICY, V49, P102, DOI 10.1016/j.resourpol.2016.04.012
   Herfindahl O.C., 1959, Copper costs and prices: 1870-1957
   Hubbert M.K., 1962, Energy resources: a report to the Committee on Natural Resources of the National Academy of Sciences--National Research Council
   Hubbert MK, 1956, Nuclear Energy and the Fossil Fuels, P1
   International Copper Study Group ICSG, 2017, WORLD COPP FACTB 201
   Johnson J, 2007, ENVIRON SCI TECHNOL, V41, P1759, DOI 10.1021/es060736h
   Kerr RA, 2014, SCIENCE, V343, P722, DOI 10.1126/science.343.6172.722
   Kesler SE, 2008, GEOLOGY, V36, P255, DOI 10.1130/G24317A.1
   Lotka A. J, 1956, ELEMENTS MATH BIOL
   May D., 2012, NAT RESOUR RES, V21, P43, DOI DOI 10.1007/S11053-011-9163-Z
   Meinert LD, 2016, RESOURCES-BASEL, V5, DOI 10.3390/resources5010014
   Mudd GM, 2008, ENVIRON SCI TECHNOL, V42, P2624, DOI 10.1021/es702249v
   Mudd GM, 2007, RESOUR POLICY, V32, P42, DOI 10.1016/j.resourpol.2007.05.002
   Mudd GM, 2010, RESOUR POLICY, V35, P98, DOI 10.1016/j.resourpol.2009.12.001
   Müller J, 2011, MATH GEOSCI, V43, P625, DOI 10.1007/s11004-011-9351-8
   Muller J., 2010, Geoscience Engineering, VLVI, P44
   Muller J, 2011, GEODYN, V28, P39
   Nickless E., 2014, Resourcing future generations white paper: mineral resources and future supply
   Norgate T, 2010, MINER ENG, V23, P65, DOI 10.1016/j.mineng.2009.10.002
   Northey S, 2014, RESOUR CONSERV RECY, V83, P190, DOI 10.1016/j.resconrec.2013.10.005
   Porter K. E, 2014, COPPER STAT
   Prior T, 2012, GLOBAL ENVIRON CHANG, V22, P577, DOI 10.1016/j.gloenvcha.2011.08.009
   Rauch JN, 2009, P NATL ACAD SCI USA, V106, P18920, DOI 10.1073/pnas.0900658106
   Rosenkranz R. D, 1976, ENERGY CONSUMPTION D
   Rudnick R.L., 2003, The Crust, V3, DOI [DOI 10.1016/B0-08-043751-6/03016-4, 10.1016/b978-0-08-095975-7.00301-6, DOI 10.1016/B978]
   Schipper BW, 2018, RESOUR CONSERV RECY, V132, P28, DOI 10.1016/j.resconrec.2018.01.004
   Schlesinger ME, 2011, EXTRACTIVE METALLURGY OF COPPER, 5TH EDITION, P1
   Schodde R., 2010, MEMS C MIN MET MARK
   Singer D., 2010, Quantitative mineral resource assessments - an integrated approach
   Singer DA, 2017, ORE GEOL REV, V86, P271, DOI 10.1016/j.oregeorev.2017.02.022
   Singer DA, 2013, ORE GEOL REV, V55, P80, DOI 10.1016/j.oregeorev.2013.04.009
   Soulier M, 2018, RESOUR CONSERV RECY, V129, P143, DOI 10.1016/j.resconrec.2017.10.013
   Steinbach Volker, 2010, Sustainability, V2, P1408, DOI 10.3390/su2051408
   Sverdrup H., 2013, J ENV SCI ENG B, VB2, P189
   Sverdrup HU, 2014, GEOCHEM PERSPECT, V3, P129, DOI 10.7185/geochempersp.3.2
   Sverdrup HU, 2014, RESOUR CONSERV RECY, V87, P158, DOI 10.1016/j.resconrec.2014.03.007
   Tilton JE, 2007, RESOUR POLICY, V32, P19, DOI 10.1016/j.resourpol.2007.04.001
   Vidal O, 2018, EPJ WEB CONF, V189, DOI 10.1051/epjconf/201818900018
   Vidal O, 2017, ELEMENTS, V13, P319, DOI 10.2138/gselements.13.5.319
   Vidal O, 2013, NAT GEOSCI, V6, P894, DOI 10.1038/ngeo1993
   Vieira MDM, 2012, ENVIRON SCI TECHNOL, V46, P12772, DOI 10.1021/es302721t
   VOLTERRA VITO, 1926, MEM R ACCAD NAZ LINCEI CL FIS MAT E NAT, V2, P31
   Wellmer FW, 2008, Z DTSCH GES GEOWISS, V159, P575, DOI 10.1127/1860-1804/2008/0159-0575
   Yellishetty M, 2010, RESOUR CONSERV RECY, V54, P1084, DOI 10.1016/j.resconrec.2010.03.003
NR 67
TC 17
Z9 23
U1 1
U2 35
PU AMER CHEMICAL SOC
PI WASHINGTON
PA 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
SN 0013-936X
EI 1520-5851
J9 ENVIRON SCI TECHNOL
JI Environ. Sci. Technol.
PD OCT 1
PY 2019
VL 53
IS 19
BP 11323
EP 11336
DI 10.1021/acs.est.9b03883
PG 14
WC Engineering, Environmental; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Engineering; Environmental Sciences & Ecology
GA JC0TU
UT WOS:000488993500030
PM 31432667
DA 2026-06-14
ER

PT J
AU Rammelt, CF
   van Schie, M
AF Rammelt, Crelis Ferdinand
   van Schie, Maarten
TI Ecology and equity in global fisheries: Modelling policy options using
   theoretical distributions
SO ECOLOGICAL MODELLING
LA English
DT Article
DE Fishing economy; System dynamics; Ecological economics; Environmental
   justice; Political ecology
ID ECONOMIC-SYSTEMS; MANAGEMENT; SUSTAINABILITY; STELLA
AB Global fisheries present a typical case of political ecology or environmental injustice, i.e. a problem of distribution of resources within ecological limits. We built a stock-flow model to visualize this challenge and its dynamics, with both an ecological and a social dimension. We incorporated theoretical distributions for non-linear variables that serve to calibrate the model as well as facilitate real-time exploration of scenarios. These scenarios represent potential policy interventions aimed at addressing ecology and equity concerns in fishing. Model results show oscillation representative of predator-prey dynamics, as well as various degrees of stabilisation, inequality in resource extraction and/or collapse. Our results support the view that the most effective policy choices directly affect the growth of physical capital for ecological stabilisation, and in the social dimension reduce inequity in political control over the accumulation of capital and allocation of resources. (C) 2016 Elsevier B.V. All rights reserved.
C1 [Rammelt, Crelis Ferdinand] Univ Utrecht, Dept Human Geog & Planning, Int Dev Studies, Fac Geosci, Heidelberglaan 2, NL-3508 TC Utrecht, Netherlands.
   [van Schie, Maarten] Bijltjespad 30B, NL-1018 KH Amsterdam, Netherlands.
C3 Utrecht University
RP Rammelt, CF (corresponding author), Univ Utrecht, Dept Human Geog & Planning, Int Dev Studies, Fac Geosci, Heidelberglaan 2, NL-3508 TC Utrecht, Netherlands.
EM c.f.rammelt@uu.nl; schiemaartenvan@gmail.com
RI Rammelt, Crelis/LDG-1551-2024
CR BenDor T, 2009, ECOL ECON, V68, P1061, DOI 10.1016/j.ecolecon.2008.07.014
   Bookchin Murray., 1990, Remaking Society: Pathways to a Green Future
   Castilla JC, 2005, SCIENCE, V309, P1324
   Costanza R, 1998, ECOL MODEL, V112, P81, DOI 10.1016/S0304-3800(98)00073-8
   Costanza R, 2001, ECOL MODEL, V143, P1, DOI 10.1016/S0304-3800(01)00358-1
   Daly H.E., 2004, ECOLOGICAL EC PRINCI
   Dew IM, 2001, ECOL MODEL, V143, P59, DOI 10.1016/S0304-3800(01)00356-8
   Dodds S, 1997, ECOL ECON, V23, P95, DOI 10.1016/S0921-8009(97)00047-5
   Dudley RG, 2008, SYST DYNAM REV, V24, P1, DOI 10.1002/sdr.392
   Global Footprint Network, 2015, WORLD FOOTPR
   Hickman M., 2009, REVEALED BID CORNER
   Hornborg A, 1998, ECOL ECON, V25, P127, DOI 10.1016/S0921-8009(97)00100-6
   Kaczynski VM, 2002, MAR POLICY, V26, P75, DOI 10.1016/S0308-597X(01)00039-2
   KAUFMANN R, 1987, ECOL MODEL, V38, P91, DOI 10.1016/0304-3800(87)90046-9
   Meadows D.H., 2008, Thinking in systems: A primer
   Msefer K., 1996, EC SUPPLY DEMAND MIT
   Ndiaye O., 2003, EXPERT CONSULTATION
   Pikitch EK, 2004, SCIENCE, V305, P346, DOI 10.1126/science.1098222
   Rammelt C. F., 2015, SYSTEMS THINKING HDB
   Rammelt CF, 2013, ECOL ECON, V93, P269, DOI 10.1016/j.ecolecon.2013.06.013
   Whelan J. G., 1994, BUILDING FISH BANKS
NR 21
TC 4
Z9 4
U1 0
U2 45
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 0304-3800
EI 1872-7026
J9 ECOL MODEL
JI Ecol. Model.
PD OCT 10
PY 2016
VL 337
BP 107
EP 122
DI 10.1016/j.ecolmodel.2016.06.011
PG 16
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA DV0EQ
UT WOS:000382591200012
OA Green Submitted, Bronze
DA 2026-06-14
ER

PT J
AU Glöser-Chahoud, S
   Hartwig, J
   Wheat, ID
   Faulstich, M
AF Gloeser-Chahoud, Simon
   Hartwig, Johannes
   Wheat, I. David
   Faulstich, Martin
TI The cobweb theorem and delays in adjusting supply in metals' markets
SO SYSTEM DYNAMICS REVIEW
LA English
DT Article
ID SYSTEM DYNAMICS; ADAPTIVE EXPECTATIONS; MODEL; RATES; PRICE
AB Global industrial metal markets have experienced a drastic price decline over the past years. In this paper we link the dynamics of raw material markets and commodity price fluctuations to a delayed adjustment of supply. Drawing on the classical cobweb theorem we show how the implementation of this theorem using system dynamics may yield a valuable explanation, not only for the recent price decline, but also for possible future price movements. Starting from a simple cobweb model of general industrial markets, we couple the price-adjusting mechanics to the global copper market and demonstrate how a simple market model can be merged with a physical material flow model. This model captures both market dynamics and technical aspects of raw material processing, recycling and substitution and adds an explanation for the widely accepted fact that the cost structure of the copper industry cannot explain current price levels. Finally, we compare the system dynamics forecasting model with a traditional econometric forecasting method and found the system dynamics model to be more intuitive and better suited to capture and convey the structural market fundamentals. Copyright (c) 2017 System Dynamics Society
C1 [Gloeser-Chahoud, Simon] Fraunhofer Inst Syst & Innovat Res ISI, Karlsruhe, Germany.
   [Gloeser-Chahoud, Simon; Faulstich, Martin] Tech Univ Clausthal, CUTEC Inst, Clausthal Zellerfeld, Germany.
   [Hartwig, Johannes] M Five GmbH Mobil Futures Innovat Econ, Karlsruhe, Germany.
   [Hartwig, Johannes; Wheat, I. David] Univ Bergen, Bergen, Norway.
C3 Fraunhofer Gesellschaft; Fraunhofer Germany; Fraunhofer Systems &
   Innovation Research; The Clausthal Institute for Environmental
   Technologies; TU Clausthal; University of Bergen
RP Glöser-Chahoud, S (corresponding author), Fraunhofer Inst Syst & Innovat Res ISI, Karlsruhe, Germany.; Glöser-Chahoud, S (corresponding author), Tech Univ Clausthal, CUTEC Inst, Clausthal Zellerfeld, Germany.
EM simon.gloeser@isi.fraunhofer.de
OI Glöser-Chahoud, Simon/0000-0002-2198-7751
CR Angerer G., 2009, Rohstoffe fur Zukunftstechnologien: Einfluss des branchenspezifischen Rohstoffbedarfs in rohstoffintensiven Zukunftstechnologien auf die zukunftige Rohstoffnachfrage
   [Anonymous], RMZ MAT GEOENVIRONME
   [Anonymous], 2016, The Economist
   ARMSTRONG JS, 1978, J BUS, V51, P549, DOI 10.1086/296016
   Auping W, 2012, P INT SYST DYN C 201
   Benner S., 1876, BENNERS PROPHESIES F
   Bornhoft N. A., 2013, P 27 ENVIROINFO C 20
   Buchholz P, 2010, RESOURCE ISSUE, V3, P25
   Buchholz P, 2010, NONRENEWABLE RESOURC, P157
   Chauhan S. P. S, 2009, MICROECONOMICS ADV T
   CHIARELLA C, 1988, ECON MODEL, V5, P377, DOI 10.1016/0264-9993(88)90010-7
   Colucci D, 2011, J ECON DYN CONTROL, V35, P1307, DOI 10.1016/j.jedc.2011.03.008
   Conceicao P., 2008, WORKING PAPER
   DAVUTYAN N, 1994, RESOUR POLICY, V20, P49, DOI 10.1016/0301-4207(94)90040-X
   Ezekiel M, 1938, Q J ECON, V52, P255, DOI 10.2307/1881734
   FAMA EF, 1970, J FINANC, V25, P383, DOI 10.2307/2325486
   Geanakoplos J, 2008, 1663 YAL U COWL FDN
   Gilbert CL., 2010, UN PUBLICATION, V197
   Glöser S, 2013, ENVIRON SCI TECHNOL, V47, P6564, DOI 10.1021/es400069b
   Gloser S, 2013, P INT SYST DYN C 201
   Gloser S, 2012, P INT SYST DYN C 201
   Gocht W., 1983, WIRTSCHAFTSGEOLOGIE, V2
   Groticke I., 2014, THESIS
   Hanau Arthur, 1928, VIERTELJAHRESHEFTE K
   HARLOW AA, 1960, J FARM ECON, V42, P842, DOI 10.2307/1235116
   Homer JB, 2012, SYST DYNAM REV, V28, P281, DOI 10.1002/sdr.1478
   Hommes CH, 1998, J ECON BEHAV ORGAN, V33, P333, DOI 10.1016/S0167-2681(97)00062-0
   HOMMES CH, 1994, J ECON BEHAV ORGAN, V24, P315, DOI 10.1016/0167-2681(94)90039-6
   Humphreys D., 2012, 201215 POL
   Humphreys D., 2012, 201248 POL
   International Monetary Fund, 2016, IMF PRIM COMM PRIC
   Irwin S. H., 2012, Journal of Agricultural and Applied Economics, V44, P371
   Jackson Tim., 2009, Prosperity Without Growth; Economics for a Finite Planet
   Kaldor N, 1933, REV ECON STUD, V1, P122
   Kampmann CE., 1992, THESIS
   Kwakkel J, 2014, P INT SYST DYN C 201
   Kwakkel J. H., 2014, P 32 INT C SYST DYN
   Labys WC, 2000, DEV ECON, V38, P330, DOI 10.1111/j.1746-1049.2000.tb00881.x
   LEONTIEF W, 1966, ESSAYS EC, V1
   Lyneis JM, 2000, SYST DYNAM REV, V16, P3, DOI 10.1002/(SICI)1099-1727(200021)16:1<3::AID-SDR183>3.0.CO;2-5
   Mashayekhi AN, 1998, SYST DYNAM REV, V14, P189, DOI 10.1002/(SICI)1099-1727(199822/23)14:2/3<189::AID-SDR148>3.0.CO;2-V
   Meadows D., 1985, ELECT ORACLE COMPUTE
   Meadows DL., 1969, THESIS
   MORISHIMA M, 1996, DYNAMIC EC THEORY
   MUTH JF, 1961, ECONOMETRICA, V29, P315, DOI 10.2307/1909635
   NERLOVE M, 1958, Q J ECON, V73, P227
   Oliva R, 2003, EUR J OPER RES, V151, P552, DOI 10.1016/S0377-2217(02)00622-7
   Ossimitz G, 2008, P INT SYST DYN C 200
   Pashigian B.P., 2008, The New Palgrave Dictionary of Economics
   Randers J, 2007, SYST DYNAM REV, V23, P253, DOI 10.1002/sdr.376
   Roberts MC, 2009, RESOUR POLICY, V34, P87, DOI 10.1016/j.resourpol.2009.02.001
   Rosenau-Tornow D, 2009, RESOUR POLICY, V34, P161, DOI 10.1016/j.resourpol.2009.07.001
   Schenk-Hoppé KR, 2004, J FORECASTING, V23, P621, DOI 10.1002/for.936
   SIMS CA, 1980, ECONOMETRICA, V48, P1, DOI 10.2307/1912017
   SOMMER M, 1984, TECHNOL FORECAST SOC, V25, P263, DOI 10.1016/0040-1625(84)90005-2
   Sprecher B, 2015, ENVIRON SCI TECHNOL, V49, P6740, DOI 10.1021/acs.est.5b00206
   Sterman J., 1984, DYNAMIC, V10, P51
   Sterman J.D., 2000, BUSINESS DYNAMICS
   Stevenson S, 2007, J PROP INVEST FINANC, V25, P223, DOI 10.1108/14635780710746902
   Sverdrup HU, 2014, RESOUR CONSERV RECY, V87, P158, DOI 10.1016/j.resconrec.2014.03.007
   Tilton JE, 2011, RESOUR POLICY, V36, P187, DOI 10.1016/j.resourpol.2011.01.006
   Toovey LM., 2012, COPPER INVESTME 0228
   van Vuuren DP, 1999, RESOUR POLICY, V25, P239, DOI 10.1016/S0301-4207(99)00031-8
   Vennix JAM., 1996, GROUP MODEL BUILDING
   Visser M, 2007, SYST DYNAM REV, V23, P453, DOI 10.1002/sdr.391
   WAUGH FV, 1964, J FARM ECON, V46, P732, DOI 10.2307/1236509
   Wellmer FW, 2012, MINER DEPOSITA, V47, P713, DOI 10.1007/s00126-012-0437-0
   World Bank, 2016, COMM PRIC FOR
   Zame W., 2008, The New Palgrave Dictionary of Economics, V2nd
NR 69
TC 11
Z9 15
U1 0
U2 13
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0883-7066
EI 1099-1727
J9 SYST DYNAM REV
JI Syst. Dyn. Rev.
PD JUL-DEC
PY 2016
VL 32
IS 3-4
BP 279
EP 308
DI 10.1002/sdr.1565
PG 30
WC Management; Social Sciences, Mathematical Methods
WE Social Science Citation Index (SSCI)
SC Business & Economics; Mathematical Methods In Social Sciences
GA ET9RH
UT WOS:000400644800007
DA 2026-06-14
ER

PT J
AU Merino, G
   Barange, M
   Mullon, C
   Rodwell, L
AF Merino, Gorka
   Barange, Manuel
   Mullon, Christian
   Rodwell, Lynda
TI Impacts of global environmental change and aquaculture expansion on
   marine ecosystems
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Climate change; Sustainable food production; Aquaculture; Fishmeal;
   Fisheries; Globalization; Fisheries management; Optimal/sub-optimal
   adaptive management
ID FISH-MEAL; CLIMATE-CHANGE; WORLD FISH; FISHERIES; OIL; GLOBALIZATION;
   VARIABILITY; AQUAFEEDS; BANDITS
AB The stability of world's reduction fisheries and the global fishmeal market they support is explored through a geographically-specific, global bio-economic model, driven by three interactive forcing factors: climate-driven changes in the biological production of regional fish stocks, the potential global expansion of aquaculture demand for fishmeal and differential management schemes. The model captures approximately 85% of the world's fishmeal and fish oil data and is driven by trade data from the period 1997-2004. Twenty-year model simulations are conducted considering, on the production side, a random recruitment variability of the fish stocks supporting all regional production systems, plus an El Nino-type perturbation altering the productivity of Peruvian and Chilean stocks. The production systems are confronted with two alternative aquaculture expansion scenarios, allowing for the quantification of the synergism between regional climate-driven fluctuations and economic globalization of marine commodities in determining sustainable and unsustainable pathways for the world's reduction fisheries. The simulation results are compared to trends in regional climate indices, trade information from international markets and aquaculture and small pelagic fisheries data. The work pioneers the quantification of the double exposure created by climate variability and change and economic globalization on particular natural resources and explains the stakes involved in the development of fishmeal trade for global aquaculture expansion for marine fish populations. The results demonstrate that regional stocks can recover from climate-driven fluctuations unless these act simultaneously to an expansion in international market demand, and are subject to sub-optimal management schemes. It is argued that the dynamics of the fishmeal price since the early 1990 already responds to the balance between climatic variability in production and market developments, as mimicked by the model. Furthermore, under sub-optimal management scenarios, a sequential pattern of overexploitation emerges as an endogenous property of the interaction between regional climatic disturbances and a globalized trade system. It is concluded that the way we manage climate impacts, both at regional and global level, will determine the sustainability of the world's reduction fisheries, a conclusion that could be extended to other, similarly affected, natural resources. (C) 2010 Elsevier Ltd. All rights reserved.
C1 [Merino, Gorka; Barange, Manuel] Plymouth Marine Lab, Plymouth PL1 3DH, Devon, England.
   [Merino, Gorka; Rodwell, Lynda] Univ Plymouth, Sch Marine Sci & Engn, Plymouth PL4 8AA, Devon, England.
   [Mullon, Christian] Ctr Rech Halieut, Unite Rech Ecosyst Upwelling, F-34200 Sete, France.
C3 Plymouth Marine Laboratory; University of Plymouth
RP Merino, G (corresponding author), Plymouth Marine Lab, Prospect Pl, Plymouth PL1 3DH, Devon, England.
EM gmerin@pml.ac.uk
RI ; Barange, Manuel/D-2689-2016; /D-5979-2018; , Gorka/D-5979-2018
OI Rodwell, Lynda/0000-0002-6580-2974; Barange, Manuel/0000-0002-1508-0483;
   , Gorka/0000-0001-6170-9396
FU Natural Environment Research Council of the UK; NERC [pml010005,
   NE/F001517/1] Funding Source: UKRI; Natural Environment Research Council
   [NE/F001517/1, pml010005] Funding Source: researchfish
FX Funding for this study has been provided by the Natural Environment
   Research Council of the UK as a contribution to the QUEST-Fish project
   (http://web.pml.ac.uk/quest-fish). The authors would like to thank
   Damien Eloire (PML, UK) and Guillermo Bejarano for his assistance in
   producing the figures, Drs M. Niquen (IMARPE, Peru), P. Freon (IRD,
   France) and J. F. Mittaine (IFFO, UK) and the World Bank for providing
   valuable data and Drs F. Maynou (CSIC, Spain) and G. Pilling (CEFAS, UK)
   and an anonymous reviewer for their valuable comments.
CR Anderson CNK, 2008, NATURE, V452, P835, DOI 10.1038/nature06851
   [Anonymous], 2007, The state of world fisheries and aquaculture 2006, P162
   ARIASSCREIBER M, 2010, CLIMATE CHANGE FISH
   Arnason R, 2006, NEW HORIZ ENVIRON EC, P1
   Asche F, 2004, J AGR ECON, V55, P245, DOI 10.1111/j.1477-9552.2004.tb00095.x
   Berkes F, 2006, SCIENCE, V311, P1557, DOI 10.1126/science.1122804
   Briones RM, 2006, FISH FISH, V7, P303, DOI 10.1111/j.1467-2979.2006.00228.x
   Chavez FP, 2003, SCIENCE, V299, P217, DOI 10.1126/science.1075880
   Checkley DM, 2009, CLIMATE CHANGE AND SMALL PELAGIC FISH, P344
   De Silva SS, 2008, J AGR ENVIRON ETHIC, V21, P459, DOI 10.1007/s10806-008-9109-6
   Delgado C. L., 2003, FISH 2020 SUPPLY DEM
   Deutsch L, 2007, GLOBAL ENVIRON CHANG, V17, P238, DOI 10.1016/j.gloenvcha.2006.08.004
   Drakeford B., 2007, GLOBAL AQUACULTURE A, V10, P79
   Drakeford Ben, 2008, Aquaculture Economics and Management, V12, P155, DOI 10.1080/13657300802306079
   Failler P., 2007, 9724 FAO 1, P204
   *FAO, 2008, FISHSTAT STAT COLL
   *FAO, 2008, GROW DEM AGR RIS PRI, P23
   Ganuza E, 2008, AQUACULTURE, V277, P109, DOI 10.1016/j.aquaculture.2008.02.005
   Garcia SM, 2005, ICES J MAR SCI, V62, P311, DOI 10.1016/j.icesjms.2004.12.003
   Grafton RQ, 2007, SCIENCE, V318, P1601, DOI 10.1126/science.1146017
   Hannesson R, 2006, NEW HORIZ ENVIRON EC, P1
   Hansen J, 2006, P NATL ACAD SCI USA, V103, P14288, DOI 10.1073/pnas.0606291103
   JACKSON A, 2008, IFFO INT FISH FISH O
   Jacobson LD, 2001, CAN J FISH AQUAT SCI, V58, P1891, DOI 10.1139/cjfas-58-9-1891
   Kristofersson D., 2004, DISCUSSION PAPERS NO
   Kristofersson D, 2006, MAR POLICY, V30, P721, DOI 10.1016/j.marpol.2005.11.004
   Lebel L, 2002, AMBIO, V31, P311, DOI 10.1639/0044-7447(2002)031[0311:ITASAI]2.0.CO;2
   Liu YJ, 2008, MAR POLICY, V32, P497, DOI 10.1016/j.marpol.2007.09.012
   Merino G, 2010, J MARINE SYST, V81, P196, DOI 10.1016/j.jmarsys.2009.12.010
   Mora C, 2009, PLOS BIOL, V7, DOI 10.1371/journal.pbio.1000131
   Mullon C, 2009, NAT RESOUR MODEL, V22, P564, DOI 10.1111/j.1939-7445.2009.00053.x
   Naylor RL, 2000, NATURE, V405, P1017, DOI 10.1038/35016500
   New MichaelB., 2002, FAO Fisheries Circular No. 975
   O'Brien KL, 2000, GLOBAL ENVIRON CHANG, V10, P221, DOI 10.1016/S0959-3780(00)00021-2
   Oakerson R. J., 1992, Making the commons work: theory, practice, and policy., P41
   Pauly D, 2002, NATURE, V418, P689, DOI 10.1038/nature01017
   Perry RI, 2010, MARINE ECOSYSTEMS AND GLOBAL CHANGE, P221
   Scales H, 2006, SCIENCE, V313, P612, DOI 10.1126/science.313.5787.612c
   Schaefer M.B., 1954, Bulletin of Mathematical Biology, V53, P253, DOI DOI 10.1007/BF02464432
   Tacon AGJ, 2003, AQUACULTURE, V226, P181, DOI 10.1016/S0044-8486(03)00476-9
   Tacon AGJ, 2008, AQUACULTURE, V285, P146, DOI 10.1016/j.aquaculture.2008.08.015
   Ulrich C, 2002, FISH RES, V58, P379, DOI 10.1016/S0165-7836(01)00393-9
   Walters C.J., 1986, Adaptive management of renewable resources
   Worm B, 2009, SCIENCE, V325, P578, DOI 10.1126/science.1173146
NR 44
TC 59
Z9 65
U1 0
U2 98
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD OCT
PY 2010
VL 20
IS 4
SI SI
BP 586
EP 596
DI 10.1016/j.gloenvcha.2010.07.008
PG 11
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA 682XR
UT WOS:000284436800007
DA 2026-06-14
ER

PT J
AU Merino, G
   Barange, M
   Mullon, C
AF Merino, Gorka
   Barange, Manuel
   Mullon, Christian
TI Climate variability and change scenarios for a marine commodity:
   Modelling small pelagic fish, fisheries and fishmeal in a globalized
   market
SO JOURNAL OF MARINE SYSTEMS
LA English
DT Article; Proceedings Paper
CT Symposium on Advances in Marine Ecosystem Modelling Research
CY JUN 23-26, 2008
CL Plymouth, ENGLAND
DE Small pelagic fisheries; Fish meal; Economic models; Fishery management;
   Climate variability and change; Economic globalization
ID PRIMARY PRODUCTIVITY; REGIME SHIFTS; WORLD FISH; AQUACULTURE; DYNAMICS;
   IMPACTS
AB The world's small pelagic fish populations, their fisheries, fishmeal and fish oil production industries and markets are part of a globalised production and consumption system. The potential for climate variability and change to alter the balance in this system is explored by means of bioeconomic models at two different temporal scales, with the objective of investigating the interactive nature of environmental and human-induced changes on this globalised system. Short-term (interannual) environmental impacts on fishmeal production are considered by including an annual variable production rate on individual small pelagic fish stocks over a 10-year simulation period. These impacts on the resources are perceived by the fishmeal markets, where they are confronted by two aquaculture expansion hypotheses. Long-term (2080) environmental impacts on the same stocks are estimated using long-term primary production predictions as proxies for the species' carrying capacities, rather than using variable production rates, and are confronted on the market side by two alternative fishmeal management scenarios consistent with IPCC-type storylines. The two scenarios, World Markets and Global Commons, are parameterized through classic equilibrium solutions for a global surplus production bioeconomic model, namely maximum sustainable yield and open access, respectively. The fisheries explicitly modelled in this paper represent 70% of total fishmeal production, thus encapsulating the expected dynamics of the global production and consumption system. Both short and long-term simulations suggest that the sustainability of the small pelagic resources, in the face of climate variability and change, depends more on how society responds to climate impacts than on the magnitude of climate alterations per se. (C) 2009 Elsevier B.V. All rights reserved.
C1 [Merino, Gorka; Barange, Manuel] Plymouth Marine Lab, Plymouth PL1 3DH, Devon, England.
   [Merino, Gorka] Univ Plymouth, Sch Earth Ocean & Environm Sci, Plymouth PL4 8AA, Devon, England.
   [Mullon, Christian] Ctr Rech Halieut, Unite Rech Ecosyst Upwelling, F-34200 Sete, France.
C3 Plymouth Marine Laboratory; University of Plymouth
RP Merino, G (corresponding author), Plymouth Marine Lab, Prospect Pl, Plymouth PL1 3DH, Devon, England.
EM gmerin@pml.ac.uk
RI /D-5979-2018; Barange, Manuel/D-2689-2016; , Gorka/D-5979-2018
OI Barange, Manuel/0000-0002-1508-0483; , Gorka/0000-0001-6170-9396
FU NERC [pml010005, NE/F001517/1] Funding Source: UKRI; Natural Environment
   Research Council [pml010005, NE/F001517/1] Funding Source: researchfish
CR [Anonymous], 2007, STAT WORLD FISH AQ
   [Anonymous], 2006, Alternative future scenarios for marine ecosystems
   Arnason R, 2006, NEW HORIZ ENVIRON EC, P1
   Asche F, 2004, J AGR ECON, V55, P245, DOI 10.1111/j.1477-9552.2004.tb00095.x
   Barange M., 2009, FAO FISHERIES TECHNI
   Behrenfeld MJ, 2006, NATURE, V444, P752, DOI 10.1038/nature05317
   Behrenfeld MJ, 1997, LIMNOL OCEANOGR, V42, P1479, DOI 10.4319/lo.1997.42.7.1479
   Berkes F, 2006, SCIENCE, V311, P1557, DOI 10.1126/science.1122804
   Brown JH, 2004, ECOLOGY, V85, P1771, DOI 10.1890/03-9000
   Chavez FP, 2003, SCIENCE, V299, P217, DOI 10.1126/science.1075880
   Checkley DM, 2009, CLIMATE CHANGE AND SMALL PELAGIC FISH, P344
   Checkley DM, 2009, CLIMATE CHANGE AND SMALL PELAGIC FISH, P1
   Company JB, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0001431
   De Silva SS, 2008, J AGR ENVIRON ETHIC, V21, P459, DOI 10.1007/s10806-008-9109-6
   Delgado C. L., 2003, Fish to 2020: supply and demand in changing global markets
   Deutsch L, 2007, GLOBAL ENVIRON CHANG, V17, P238, DOI 10.1016/j.gloenvcha.2006.08.004
   Drakeford B., 2007, GLOBAL AQUACULTURE A, V10, P79
   FAILLER P, 2007, FUTURE PROSPECTS F 1, V4
   *FAO, 2008, FISHSTAT STAT COLL
   Folke C, 2004, ANNU REV ECOL EVOL S, V35, P557, DOI 10.1146/annurev.ecolsys.35.021103.105711
   Ganuza E, 2008, AQUACULTURE, V277, P109, DOI 10.1016/j.aquaculture.2008.02.005
   Garcia SM, 2005, ICES J MAR SCI, V62, P311, DOI 10.1016/j.icesjms.2004.12.003
   Gergis JL, 2009, CLIMATIC CHANGE, V92, P343, DOI 10.1007/s10584-008-9476-z
   Gordon HS, 1954, J POLIT ECON, V62, P124, DOI 10.1086/257497
   Hannesson R, 2006, NEW HORIZ ENVIRON EC, P296
   Hansen J, 2006, P NATL ACAD SCI USA, V103, P14288, DOI 10.1073/pnas.0606291103
   Jackson A., 2008, IFFO INT FISHM FISH
   Jennings S, 2008, P ROY SOC B-BIOL SCI, V275, P1375, DOI 10.1098/rspb.2008.0192
   Kashiwai Makoto, 1995, Bulletin of the Hokkaido National Fisheries Research Institute, V59, P81
   Kristofersson D, 2006, MAR POLICY, V30, P721, DOI 10.1016/j.marpol.2005.11.004
   Lebel L, 2002, AMBIO, V31, P311, DOI 10.1639/0044-7447(2002)031[0311:ITASAI]2.0.CO;2
   Lehodey P, 2006, J CLIMATE, V19, P5009, DOI 10.1175/JCLI3898.1
   Lewy P, 2004, FISH RES, V68, P237, DOI 10.1016/j.fishres.2003.12.004
   Liu YJ, 2008, MAR POLICY, V32, P497, DOI 10.1016/j.marpol.2007.09.012
   MARRA J, 2003, ALGORITHM CALCULATIO
   Maynou F, 2008, J MARINE SYST, V71, P294, DOI 10.1016/j.jmarsys.2006.09.008
   Merryfield WJ, 2006, J CLIMATE, V19, P4009, DOI 10.1175/JCLI3834.1
   Mueter FJ, 2006, FISH RES, V81, P189, DOI 10.1016/j.fishres.2006.07.010
   Mullon C, 2009, NAT RESOUR MODEL, V22, P564, DOI 10.1111/j.1939-7445.2009.00053.x
   MYERS RA, 1995, SCIENCE, V269, P1106, DOI 10.1126/science.269.5227.1106
   Nakicenovic N., 2000, IPCC Special Report on Emissions Scenarios (SRES)
   Naylor RL, 2000, NATURE, V405, P1017, DOI 10.1038/35016500
   NEW MB, 2003, J WORLD AQUACULT SOC, V34, P26
   O'Brien KL, 2000, GLOBAL ENVIRON CHANG, V10, P221, DOI 10.1016/S0959-3780(00)00021-2
   Oakerson R. J., 1992, Making the commons work: theory, practice, and policy., P41
   Perry RI, 2008, PROG OCEANOGR, V77, P241, DOI 10.1016/j.pocean.2008.03.005
   Polovina JJ, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2007GL031745
   Sarmiento JL, 2004, GLOBAL BIOGEOCHEM CY, V18, DOI 10.1029/2003GB002134
   Schaefer M., 1954, Bulletin of the Inter-American Tropical Tuna Commission, V1, P27, DOI DOI 10.1007/BF02464432
   Solomon S, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P1
   Tacon AGJ, 2003, AQUACULTURE, V226, P181, DOI 10.1016/S0044-8486(03)00476-9
   Takasuka A, 2008, PROG OCEANOGR, V77, P225, DOI 10.1016/j.pocean.2008.03.008
   Taylor AH, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023792
   Trenberth KE, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P235
   Ulrich C, 2002, FISH RES, V58, P379, DOI 10.1016/S0165-7836(01)00393-9
   Walters C.J., 1986, Adaptive management of renewable resources
   WARE DM, 2005, BOTTOM UP ECOSYSTEM, P1280
   *WORLD BANK, 2008, COMM PRIC DAT
   Young O.R., 2002, I DIMENSIONS ENV CHA, DOI DOI 10.7551/MITPRESS/3807.001.0001
NR 59
TC 47
Z9 51
U1 2
U2 47
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0924-7963
EI 1879-1573
J9 J MARINE SYST
JI J. Mar. Syst.
PD APR
PY 2010
VL 81
IS 1-2
SI SI
BP 196
EP 205
DI 10.1016/j.jmarsys.2009.12.010
PG 10
WC Geosciences, Multidisciplinary; Marine & Freshwater Biology;
   Oceanography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Conference Proceedings Citation Index - Science (CPCI-S)
SC Geology; Marine & Freshwater Biology; Oceanography
GA 576TV
UT WOS:000276172700016
DA 2026-06-14
ER

PT J
AU Mullon, C
   Mittaine, JF
   Thébaud, O
   Péron, G
   Merino, G
   Barange, M
AF Mullon, C.
   Mittaine, J-F.
   Thebaud, O.
   Peron, G.
   Merino, G.
   Barange, M.
TI MODELING THE GLOBAL FISHMEAL AND FISH OIL MARKETS
SO NATURAL RESOURCE MODELING
LA English
DT Article
DE Bio-economic modeling; networks economics; small pelagic fisheries;
   fishmeal; fish oil
ID BIOECONOMIC SIMULATION-MODEL; FISHERIES; ANCHOVY; SARDINE; VARIABILITY;
   AQUACULTURE; DYNAMICS
AB P>To explore the drivers of change in the complex system relating small pelagic fisheries and fishmeal/fish oil markets, to identify the interactions between these drivers and their overall impacts, we propose a bio-economic model, coupling the ecological and the economic dynamics of these global commodities. The model enables an analysis of the consequences of both global and local changes in the environment of production systems. Through sensitivity analysis of specific input parameters, we evaluate the robustness of the overall system to such changes and show that local responses of production systems and markets cannot be considered in isolation from the set of interactions at global level.
C1 [Mullon, C.] Unite Rech Ecosyst Marins Exploites, F-34200 Sete, France.
   [Mittaine, J-F.] Conservatoire Natl Arts & Metiers, Paris, France.
   [Thebaud, O.; Peron, G.] IFREMER, UMR AMURE, Dept Econ Maritime, F-29280 Plouzane, France.
   [Merino, G.; Barange, M.] Plymouth Marine Lab, Plymouth PL1 3, Devon, England.
C3 Ifremer; Institut de Recherche pour le Developpement (IRD); Universite
   de Montpellier; heSam Universite; Conservatoire National Arts & Metiers
   (CNAM); Universite de Bretagne Occidentale; Ifremer; Plymouth Marine
   Laboratory
RP Mullon, C (corresponding author), Unite Rech Ecosyst Marins Exploites, Ave Jean Monnet, F-34200 Sete, France.
EM Christian.Mullon@ird.fr
RI /D-5979-2018; Barange, Manuel/D-2689-2016; Thebaud, Olivier/D-9792-2011;
   , Gorka/D-5979-2018
OI Barange, Manuel/0000-0002-1508-0483; Thebaud,
   Olivier/0000-0001-8665-3827; , Gorka/0000-0001-6170-9396
FU ANR (France); QUEST_FISH project (UK)
FX This research is part of the program of the IRD Research Unit, Upwelling
   Ecosystems. Christian Mullon and Olivier Thebaud have been supported by
   the program CHALOUPE founded by ANR (France). Gorka Merino and Manuel
   Barange have been supported by QUEST_FISH project (UK). We thank Pierre
   Lopez for his work on the figures. We thank Pierre Freon for many
   advices and suggestions. We finally thank the anonymous referees of the
   paper for pertinent remarks.
CR Alheit J, 2004, PROG OCEANOGR, V60, P201, DOI 10.1016/j.pocean.2004.02.006
   Anderson JamesL., 2003, INT SEAFOOD TRADE
   ANDERSON RW, 1980, EUR ECON REV, V14, P281, DOI 10.1016/S0014-2921(80)80001-8
   [Anonymous], ADV FISHERIES EC
   [Anonymous], 2000, IPCC INTERGOVERNMENT
   Asche F, 2004, J AGR ECON, V55, P245, DOI 10.1111/j.1477-9552.2004.tb00095.x
   Barange M, 1999, S AFR J MARINE SCI, V21, P367
   Barange M, 2008, AM FISH S S, V49, P977
   Brander KM, 2007, P NATL ACAD SCI USA, V104, P19709, DOI 10.1073/pnas.0702059104
   Chavez FP, 2003, SCIENCE, V299, P217, DOI 10.1126/science.1075880
   Cheung WWL, 2010, GLOBAL CHANGE BIOL, V16, P24, DOI 10.1111/j.1365-2486.2009.01995.x
   CISNEROSMATA MA, 1995, 36 CALCOFI INPCRIP
   Coelli T.J., 1997, INTRO EFFICIENCY PRO
   Coetzee JC, 2008, AFR J MAR SCI, V30, P205, DOI 10.2989/AJMS.2008.30.2.1.551
   Deutsch L, 2007, GLOBAL ENVIRON CHANG, V17, P238, DOI 10.1016/j.gloenvcha.2006.08.004
   Facchinei F., 2003, Finite-Dimensional Variational Inequalities and Complementarity Problem, DOI [DOI 10.1007/978-0-387-21815-16, 10.1007/978-0-387-21815-16]
   Facchinei F., 2003, FINITE DIMENSIONAL V, VII
   FREON P, 2008, PROGR OCEAN IN PRESS
   GARCIA JG, 2006, THESIS U BARCELONA
   Garcia SM, 2005, PHILOS T R SOC B, V360, P21, DOI 10.1098/rstb.2004.1580
   Gordon D.V., 1996, MAR RESOUR ECON, V11, P223, DOI DOI 10.1086/mre.11.4.42629167
   GRANT WE, 1981, ECOL MODEL, V13, P195, DOI 10.1016/0304-3800(81)90052-1
   Grimm V, 2005, SCIENCE, V310, P987, DOI 10.1126/science.1116681
   HANNESSON R, 2006, CLIMATE CHANGE EC WO, V17
   Hardy RW, 2002, RESPONSIBLE MARINE AQUACULTURE, P311, DOI 10.1079/9780851996042.0311
   IOANNIDES C, 1987, MAR POLICY, V11, P143
   ISAKSON KG, 1982, J INT SOCIOLOGICAL E, V4, P61
   Jacobson LD, 2001, CAN J FISH AQUAT SCI, V58, P1891, DOI 10.1139/cjfas-58-9-1891
   Kawasaki T., 1993, Fisheries Oceanography, V2, P244, DOI 10.1111/j.1365-2419.1993.tb00139.x
   Kristofersson D, 2006, MAR POLICY, V30, P721, DOI 10.1016/j.marpol.2005.11.004
   Lehodey P, 2006, J CLIMATE, V19, P5009, DOI 10.1175/JCLI3898.1
   LEYTON M, 2001, RISE MAKING WORLDS L
   Lleonart J, 2003, SCI MAR, V67, P337, DOI 10.3989/scimar.2003.67s1337
   Lluch-Belda D., 1992, Fisheries Oceanography, V1, P339, DOI 10.1111/j.1365-2419.1992.tb00006.x
   Mardle S, 2002, J ENVIRON MANAGE, V65, P49, DOI 10.1006/jema.2001.0518
   Mente E, 2006, AQUACULT INT, V14, P499, DOI 10.1007/s10499-006-9051-4
   Merino G, 2007, SCI MAR, V71, P537, DOI 10.3989/scimar.2007.71n3537
   Mullon C, 2005, FISH FISH, V6, P111, DOI 10.1111/j.1467-2979.2005.00181.x
   Nagurney A., 1993, Network Economics: A Variational Inequality Approach
   NIELSEN M, 1999, E U SEAFOOD MARKETS
   PASCOE S, 1999, 433 FAO
   PAULY D, 1995, TRENDS ECOL EVOL, V10, P430, DOI 10.1016/S0169-5347(00)89171-5
   Pinnegar JK, 2008, REV FISH BIOL FISHER, V18, P1, DOI 10.1007/s11160-007-9058-6
   Samuelson PA, 1952, AM ECON REV, V42, P283
   Sanchirico James N., 2007, International Journal of Global Environmental Issues, V7, P106, DOI 10.1504/IJGENVI.2007.013569
   SARGENT JR, 2007, BR J NUTR, V78, pS5
   Schaffner J., 1954, I RAD ENG T CIRC IRE T CIRCUIT THEORY, VCT-1, P2
   Schwartzlose RA, 1999, S AFR J MARINE SCI, V21, P289
   SMITH VL, 1969, J POLIT ECON, V77, P181, DOI 10.1086/259507
   SPARRE PJ, 1993, COMPUTERIZED INFORM
   SUMAILA UR, 2008, ICES J MAR SCI
   Ulrich C, 2002, FISH RES, V58, P379, DOI 10.1016/S0165-7836(01)00393-9
   WARD JM, 1999, 433 FAO
   ZHU DL, 1993, OPER RES LETT, V14, P111, DOI 10.1016/0167-6377(93)90103-N
NR 54
TC 35
Z9 41
U1 0
U2 17
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0890-8575
EI 1939-7445
J9 NAT RESOUR MODEL
JI Nat. Resour. Model.
PD NOV
PY 2009
VL 22
IS 4
BP 564
EP 609
DI 10.1111/j.1939-7445.2009.00053.x
PG 46
WC Environmental Sciences; Mathematics, Interdisciplinary Applications
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Mathematics
GA 515KS
UT WOS:000271469300005
OA Bronze
DA 2026-06-14
ER

EF