Synergistic interactions among growing stressors increase risk to an Arctic ecosystem.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
07 12 2020
Historique:
received: 31 07 2019
accepted: 29 10 2020
entrez: 8 12 2020
pubmed: 9 12 2020
medline: 29 12 2020
Statut: epublish

Résumé

Oceans provide critical ecosystem services, but are subject to a growing number of external pressures, including overfishing, pollution, habitat destruction, and climate change. Current models typically treat stressors on species and ecosystems independently, though in reality, stressors often interact in ways that are not well understood. Here, we use a network interaction model (OSIRIS) to explicitly study stressor interactions in the Chukchi Sea (Arctic Ocean) due to its extensive climate-driven loss of sea ice and accelerated growth of other stressors, including shipping and oil exploration. The model includes numerous trophic levels ranging from phytoplankton to polar bears. We find that climate-related stressors have a larger impact on animal populations than do acute stressors like increased shipping and subsistence harvesting. In particular, organisms with a strong temperature-growth rate relationship show the greatest changes in biomass as interaction strength increased, but also exhibit the greatest variability. Neglecting interactions between stressors vastly underestimates the risk of population crashes. Our results indicate that models must account for stressor interactions to enable responsible management and decision-making.

Identifiants

pubmed: 33288746
doi: 10.1038/s41467-020-19899-z
pii: 10.1038/s41467-020-19899-z
pmc: PMC7721797
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

6255

Références

Sci Total Environ. 2019 Jun 20;670:379-397
pubmed: 30904652
Proc Natl Acad Sci U S A. 2014 Dec 16;111(50):17923-8
pubmed: 25468963
Sci Rep. 2019 Aug 12;9(1):11609
pubmed: 31406130
Proc Biol Sci. 2012 Jun 22;279(1737):2363-8
pubmed: 22319129
Science. 2020 Jul 10;369(6500):198-202
pubmed: 32647002
Science. 2012 Oct 19;338(6105):344-8
pubmed: 23087241
Ecol Evol. 2015 Sep;5(17):3842-56
pubmed: 26380710
J Acoust Soc Am. 2013 Jul;134(1):77-87
pubmed: 23862786
Nat Ecol Evol. 2017 Jun 22;1(7):195
pubmed: 28812592
J Theor Biol. 2020 May 21;493:110211
pubmed: 32097609
Ecol Lett. 2008 Dec;11(12):1278-86
pubmed: 18785986
Ecol Lett. 2008 Dec;11(12):1304-15
pubmed: 19046359
Glob Chang Biol. 2015 Jun;21(6):2122-40
pubmed: 25488061
PLoS One. 2014 Nov 03;9(11):e110933
pubmed: 25365430
Ecol Appl. 2008 Mar;18(2 Suppl):S97-125
pubmed: 18494365
Glob Chang Biol. 2016 Aug;22(8):2665-75
pubmed: 26648483
Ecol Appl. 2016 Apr;26(3):651-63
pubmed: 27411240
Glob Chang Biol. 2013 Jun;19(6):1884-96
pubmed: 23505245
J Acoust Soc Am. 2012 Jan;131(1):104-103
pubmed: 22280575
Nat Commun. 2016 Feb 05;7:10544
pubmed: 26847493
Phys Rev E. 2018 Jan;97(1-1):012309
pubmed: 29448477
Proc Natl Acad Sci U S A. 2008 Feb 12;105(6):1786-93
pubmed: 18258748
Ecol Evol. 2015 Apr;5(7):1538-47
pubmed: 25897392
Glob Chang Biol. 2014 Nov;20(11):3300-12
pubmed: 24771500
Nature. 2009 Sep 3;461(7260):53-9
pubmed: 19727193
Proc Biol Sci. 2016 Feb 10;283(1824):
pubmed: 26865306
Biol Lett. 2016 Sep;12(9):
pubmed: 27601724
Ann Rev Mar Sci. 2012;4:11-37
pubmed: 22457967
Glob Chang Biol. 2017 Apr;23(4):1525-1539
pubmed: 28078785
Science. 2010 Jun 18;328(5985):1523-8
pubmed: 20558709
Ambio. 2006 Jun;35(4):148-52
pubmed: 16944638
Conserv Biol. 2018 Dec;32(6):1368-1379
pubmed: 29797608
Glob Chang Biol. 2014 Jan;20(1):76-88
pubmed: 23913506
Science. 2008 Feb 15;319(5865):948-52
pubmed: 18276889

Auteurs

K R Arrigo (KR)

School of Earth, Energy & Environmental Sciences, Stanford University, Stanford, CA, USA. arrigo@stanford.edu.

Gert L van Dijken (GL)

School of Earth, Energy & Environmental Sciences, Stanford University, Stanford, CA, USA.

M A Cameron (MA)

Stanford Center for Ocean Solutions, Stanford University, Stanford, CA, USA.

J van der Grient (J)

School of Geography and the Environment, University of Oxford, Oxford, UK.

L M Wedding (LM)

Stanford Center for Ocean Solutions, Stanford University, Stanford, CA, USA.
School of Geography and the Environment, University of Oxford, Oxford, UK.

L Hazen (L)

Stanford Center for Ocean Solutions, Stanford University, Stanford, CA, USA.

J Leape (J)

Stanford Center for Ocean Solutions, Stanford University, Stanford, CA, USA.

G Leonard (G)

The Ocean Conservancy, Santa Cruz, CA, USA.

A Merkl (A)

The Ocean Conservancy, Santa Cruz, CA, USA.

F Micheli (F)

Stanford Center for Ocean Solutions, Stanford University, Stanford, CA, USA.
Hopkins Marine Station, Stanford University, Pacific Grove, CA, USA.

M M Mills (MM)

School of Earth, Energy & Environmental Sciences, Stanford University, Stanford, CA, USA.

S Monismith (S)

Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA.

N T Ouellette (NT)

Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA.

A Zivian (A)

The Ocean Conservancy, Santa Cruz, CA, USA.

M Levi (M)

Center for Advanced Study in the Behavioral Sciences, Stanford University, Stanford, CA, USA.

R M Bailey (RM)

School of Geography and the Environment, University of Oxford, Oxford, UK.

Articles similaires

Robotic Surgical Procedures Animals Humans Telemedicine Models, Animal

Odour generalisation and detection dog training.

Lyn Caldicott, Thomas W Pike, Helen E Zulch et al.
1.00
Animals Odorants Dogs Generalization, Psychological Smell

Selecting optimal software code descriptors-The case of Java.

Yegor Bugayenko, Zamira Kholmatova, Artem Kruglov et al.
1.00
Software Algorithms Programming Languages
Animals TOR Serine-Threonine Kinases Colorectal Neoplasms Colitis Mice

Classifications MeSH