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. 2023 Sep 20;18(9):e0290643.
doi: 10.1371/journal.pone.0290643. eCollection 2023.

Vulnerability to climate change of United States marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean

Matthew D Lettrich  1 , Michael J Asaro  2 , Diane L Borggaard  3 , Dorothy M Dick  4 , Roger B Griffis  5 , Jenny A Litz  6 , Christopher D Orphanides  2 , Debra L Palka  2 , Melissa S Soldevilla  6 , Brian Balmer  7 , Samuel Chavez  8 , Danielle Cholewiak  2 , Diane Claridge  9 , Ruth Y Ewing  6 , Kristi L Fazioli  10 , Dagmar Fertl  11 , Erin M Fougeres  12 , Damon Gannon  13 , Lance Garrison  6 , James Gilbert  14 , Annie Gorgone  15 , Aleta Hohn  16 , Stacey Horstman  12 , Beth Josephson  8 , Robert D Kenney  17 , Jeremy J Kiszka  18 , Katherine Maze-Foley  19 , Wayne McFee  20 , Keith D Mullin  21 , Kimberly Murray  2 , Daniel E Pendleton  22 , Jooke Robbins  23 , Jason J Roberts  24 , Grisel Rodriguez-Ferrer  25 , Errol I Ronje  26 , Patricia E Rosel  27 , Todd Speakman  28 , Joy E Stanistreet  29 , Tara Stevens  30 , Megan Stolen  31 , Reny Tyson Moore  32 , Nicole L Vollmer  33 , Randall Wells  32 , Heidi R Whitehead  34 , Amy Whitt  35
Affiliations

Vulnerability to climate change of United States marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean

Matthew D Lettrich et al. PLoS One. .

Abstract

Climate change and climate variability are affecting marine mammal species and these impacts are projected to continue in the coming decades. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species using currently available information. We conducted a trait-based climate vulnerability assessment using expert elicitation for 108 marine mammal stocks and stock groups in the western North Atlantic, Gulf of Mexico, and Caribbean Sea. Our approach combined the exposure (projected change in environmental conditions) and sensitivity (ability to tolerate and adapt to changing conditions) of marine mammal stocks to estimate vulnerability to climate change, and categorize stocks with a vulnerability index. The climate vulnerability score was very high for 44% (n = 47) of these stocks, high for 29% (n = 31), moderate for 20% (n = 22), and low for 7% (n = 8). The majority of stocks (n = 78; 72%) scored very high exposure, whereas 24% (n = 26) scored high, and 4% (n = 4) scored moderate. The sensitivity score was very high for 33% (n = 36) of these stocks, high for 18% (n = 19), moderate for 34% (n = 37), and low for 15% (n = 16). Vulnerability results were summarized for stocks in five taxonomic groups: pinnipeds (n = 4; 25% high, 75% moderate), mysticetes (n = 7; 29% very high, 57% high, 14% moderate), ziphiids (n = 8; 13% very high, 50% high, 38% moderate), delphinids (n = 84; 52% very high, 23% high, 15% moderate, 10% low), and other odontocetes (n = 5; 60% high, 40% moderate). Factors including temperature, ocean pH, and dissolved oxygen were the primary drivers of high climate exposure, with effects mediated through prey and habitat parameters. We quantified sources of uncertainty by bootstrapping vulnerability scores, conducting leave-one-out analyses of individual attributes and individual scorers, and through scoring data quality for each attribute. These results provide information for researchers, managers, and the public on marine mammal responses to climate change to enhance the development of more effective marine mammal management, restoration, and conservation activities that address current and future environmental variation and biological responses due to climate change.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Climate vulnerability matrix showing the number of marine mammal stocks for each sensitivity-exposure score combination.
Climate vulnerability is represented by cell color (green = low vulnerability, yellow = moderate vulnerability, orange = high vulnerability, red = very high vulnerability). Numbers indicate the number of stocks that scored in each sensitivity/exposure combination.
Fig 2
Fig 2. Climate vulnerability, exposure, and sensitivity by taxonomic group.
Climate vulnerability, exposure, and sensitivity of U.S. marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean Sea by taxonomic group. Note the different scales on the horizontal axis between taxonomic groups.
Fig 3
Fig 3. Exposure factor mean scores for all scored stocks.
Exposure factor mean scores for 108 U.S. marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean Sea. The vertical bar represents the median; the box is bounded by the first and third quartiles; whiskers represent 1.5 times the inter-quartile range; points represent all outlying values.
Fig 4
Fig 4. Leave-one-out sensitivity analysis for exposure factors.
Leave-one-out sensitivity analysis showing how many marine mammal stocks changed climate vulnerability score when a given exposure factor was omitted. Only ocean pH (change in mean), dissolved oxygen (change in mean), air temperature (change in mean), and sea surface temperature (change in mean) changed vulnerability scores when omitted.
Fig 5
Fig 5. Sensitivity attribute mean scores for all scored stocks.
Sensitivity attribute mean scores for 108 U.S. marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean Sea. The vertical bar represents the median; the box is bounded by the first and third quartiles; whiskers represent 1.5 times the inter-quartile range; points represent all outlying values.
Fig 6
Fig 6. Leave-one-out sensitivity analysis for sensitivity attributes.
Leave-one-out sensitivity analysis showing how many marine mammal stocks changed climate vulnerability score when a given sensitivity attribute was omitted. Home range did not change any vulnerability scores when omitted.
Fig 7
Fig 7. Mean exposure factor data quality scores.
Mean data quality scores of climate exposure factors for 108 marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean Sea. The vertical bar represents the median; the box is bounded by the first and third quartiles; whiskers represent 1.5 times the inter-quartile range; points represent all outlying values.
Fig 8
Fig 8. Mean sensitivity attribute data quality scores.
Mean data quality scores of climate sensitivity attributes for 108 marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean Sea. The vertical bar represents the median; the box is bounded by the first and third quartiles; whiskers represent 1.5 times the inter-quartile range; points represent all outlying values.
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