Systematic Review of Multi-Species Models in Fisheries: Key Features and Current Trends
Abstract
:1. Introduction
2. Material and Methods
2.1. PRISMA Method
2.2. Eligibility Criteria
2.3. Features of Multi-Species Models
- Conceptual and qualitative models: Such methods focus on identifying specific, large-scale stressors and their effects on natural systems, rather than assessing a particular species or multiple species [37,38]. These models do not incorporate the precise quantitative estimates of the magnitude or strength of the species interactions. Instead, these models only account for the qualitative sign (+, −, 0) of the species interactions [39]. These types of models were outside the scope of the present review and were, therefore, not included.
- Extensions of single-species models (EXT): They focus on the dynamics of a single species, but include the effects of interactions with different species as fixed effects. These models can explicitly include predation mortality, although it is usually treated as another type of fishery rather than being estimated as part of natural mortality [7,40].
- Dynamic multi-species models (DYN): These models use a limited number of species or functional groups that are likely to have relevant interactions with the target species. They are built upon single-species theory to understand the dynamics of multi-species fisheries, but do not address the ecosystem as a whole. They can include diverse environmental variables depending on the scenario [41,42,43].
- Aggregated ecosystem models (AGG): These models consider all trophic levels (producers and consumers) in the ecosystem to explore energy flow among the levels. They include both top-down and bottom-up processes, which allows for the development of trade-off relationships between prey harvest and predator biomass [44]. The most representative example is Ecopath with Ecosim (EwE) [45,46] and its spatial form, Ecospace. Ecopath creates a mass-balanced snapshot, while Ecosim uses Ecopath parameters as initial conditions to produce time-dynamic simulations [45,47].
- End-to-end models (E2E): These models track nutrient flows through the ecosystem components, simulating annual cycles of nutrients and feeding into a representation of lower trophic levels, higher trophic levels, and even anthropogenic effects. E2E models can be coupled to different submodels, such as NEMURO [48,49,50]. The use of E2E models has been focused on strategic management, such as performing management strategy evaluations (MSEs) [15]. In this context, models such as Atlantis [51,52] can be employed as operating models to represent the impacts of fishing and other anthropogenic effects and capable of simulating the full trophic spectrum and considering physical, biochemical, and human components in a spatially resolved area.
- Coupled and hybrid model platforms (C&H): These models incorporate interactions by coupling or combining different types of model platforms. Unlike EwE and Atlantis, this framework is specifically designed for the coupling or combination of diverse model types [35]. Individual-based (IBM) and agent-based models fall within this category, employing multiple submodels to integrate the complexity of individual behavior, which can influence system dynamics. Models such as OSMOSE (Object-oriented Simulator of Marine Ecosystems Exploitation) [53] can incorporate IBM-based age-structured fish or predator population and trophic interaction models, biogeochemical plankton production models, hydrodynamic and environmental models, habitat models, representations of human activities, and potentially even representations of their social and economic drivers [35].
2.4. Clustering of Multi-Species Models
3. Results
3.1. Identification of Multi-Species Models
3.2. Categorization and Geographical Distribution of Multi-Species Models
- -
- Northeast U.S.: Atlantic cod (Gadus morhua), Atlantic herring (Clupea harengus), and Atlantic menhaden (Brevoortia tyrannus).
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- Baltic Sea: Atlantic cod, Atlantic herring, and sprat (Sprattus sprattus).
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- Gulf of Alaska: Arrowtooth flounder (Atheresthes stomias), Pacific cod (Gadus macrocephalus), and pollock (Theragra chalcogramma).
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- Mediterranean Sea: European hake (Merluccius merluccius), sardine (Sardina pilchardus), and European anchovy (Engraulis encrasicolus).
- -
- North Sea: Haddock (Melanogrammus aeglefinus), Atlantic herring, and Atlantic cod.
3.3. Multi-Species Models’ Clustering
4. Discussion
4.1. Regional Interest in Multi-Species Models
4.1.1. North Sea
4.1.2. Baltic Sea
4.1.3. Gulf of Alaska
4.1.4. Mediterranean Sea
4.1.5. Gulf of Maine
4.2. Multi-Species Model Groups
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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id | Model Name | Large Marine Ecosystem (LME) | Specific Location | Reference | |
---|---|---|---|---|---|
Extension of singles-species models | |||||
1. | MSSCAA | Statistical catch-at-age model with predation | Gulf of Alaska | Gulf of Alaska | [65] |
2. | PS-mod | Schaefer surplus production model modified | Indonesian Sea | Java sea, Rembang Regency | [66] |
3. | PS-mod | Schaefer surplus production model modified | Indonesian Sea | Java sea, Pati Regency | [67] |
4. | PS-mod | Schaefer surplus production model modified | Indonesian Sea | Java sea, Semarang city | [68] |
5. | PPI-CSA | Predation pressure index for Collie–Sissenwine catch-survey analysis | Northeast U.S. Continental Shelf | Gulf of Maine | [69] |
6. | SPM-SH | Steele–Henderson surplus production model with predation | Northeast U.S. Continental Shelf | Northwest Atlantic coastal ecosystem | [44] |
Dynamic multi-species models | |||||
7. | SMOM | Spatial multispecies operating model | Antarctica | Scotia Sea | [70] |
8. | CHS | Age-structured dynamic model | Baltic Sea | Baltic Sea | [71] |
9. | EE MSM | Ecological–economic multispecies model | Baltic Sea | Central Baltic Sea | [72] |
10. | SMS | Stochastic multispecies model | Baltic Sea | Baltic Sea | [73] |
11. | MSI-SOM | Multispecies interaction stochastic operative model | Baltic Sea | Baltic Sea | [74] |
12. | MSPM | Multispecies stock production model | Baltic Sea | Baltic Sea | [75] |
13. | Gadget | Globally Applicable Area-Disaggregated General Ecosystem Toolbox | Baltic Sea | Baltic Sea | [75] |
14. | Gadget | Globally Applicable Area-Disaggregated General Ecosystem Toolbox | Baltic Sea | Baltic Sea | [76] |
15. | Gadget | Globally Applicable Area-Disaggregated General Ecosystem Toolbox | Barents Sea | Barents Sea | [42] |
16. | ASPM | Model of intermediate complexity for ecosystem assessment | Benguela Current | Benguela | [77] |
17. | MSM | Multispecies size-spectrum model | Celtic-Biscay Shelf | Celtic Sea, 7e-j | [78] |
18. | LeMans | Length-based multispecies analysis by numerical simulation | Celtic-Biscay Shelf | Irish Sea | [79] |
19. | MBD | Multispecies biomass dynamics model | East Bering Sea | Bering Sea | [80] |
20. | MDD | Multispecies delay difference model | Eastern Bering Sea | Eastern Bering Sea | [81] |
21. | MBD | Multispecies biomass dynamics model | Eastern Bering Sea | Eastern Bering Sea | [81] |
22. | CEATTLE | Climate-enhanced, age-based model with temperature-specific trophic linkages and energetics | Eastern Bering Sea | Eastern Bering Sea | [41] |
23. | MS-ASA | Multispecies age-structured assessment model | Gulf of Alaska | Gulf of Alaska | [82] |
24. | MS-PROD | Multispecies production model | Gulf of Alaska | Gulf of Alaska | [83] |
25. | MSASA | Multispecies age-structured assessment model | Gulf of Alaska | Gulf of Alaska | [84] |
26. | MICE-in-space | Spatio-temporal model of intermediate complexity for ecosystem assessments | Gulf of Alaska | Gulf of Alaska | [85] |
27. | CEATTLE | Climate-enhanced, age-based model with temperature-specific trophic linkages and energetics | Gulf of Alaska | Gulf of Alaska | [86] |
28. | MSVPA | Multispecies virtual population analysis | Humboldt Current | Southern Chilean waters | [87] |
29. | LB-MSM | Length-based multispecies fisheries model | Indonesian Sea | Wakatobi National Park | [88] |
30. | Gadget | Globally applicable area-disaggregated general ecosystem toolbox | Labrador-Newfoundland | Flemish cap | [89] |
31. | GadCap | Globally applicable area-disaggregated general ecosystem toolbox | Labrador-Newfoundland | Flemish cap | [90] |
32. | MICE | Model of intermediate complexity for ecosystem assessment | Mediterranean Sea | Pomo pits | [91] |
33. | mizer | Multispecies size-spectrum model | No LME | Central and eastern tropical Pacific sea | [92] |
34. | MICE | Model of intermediate complexity for ecosystem assessment | No LME | Moorea Island | [93] |
35. | SMS | Stochastic multispecies assessment model | North Sea | North Sea | [94] |
36. | mizer | Multispecies size-spectrum model | North Sea | North Sea | [95] |
37. | T-ONS | Trade-offs North Sea model | North Sea | North Sea | [96] |
38. | FishSUMs | Size-structured multispecies model | North Sea | North Sea | [97] |
39. | FishSUMs | Size-structured multispecies model | North Sea | North Sea | [98] |
40. | LB-MSM | Length-based multispecies analysis by numerical simulation modified | North Sea | North Sea | [99] |
41. | AS-MSM | Multispecies age-structured population model | Northeast U.S. Continental Shelf | Georges Bank | [100] |
42. | MSVPA-X | Extended multispecies virtual population analysis | Northeast U.S. Continental Shelf | Northeast U.S. Coast | [101] |
43. | MS-PROD | Multispecies production model | Northeast U.S. Continental Shelf | Georges Bank | [83] |
44. | MSSCAA | Multispecies statistical catch-at-age model | Northeast U.S. Continental Shelf | Georges Bank | [102] |
45. | LeMans | Length-based multispecies analysis by numerical simulation | Northeast U.S. Continental Shelf | Georges Bank | [103] |
46. | MSSCAA | Multispecies statistical catch-at-age model | Northeast U.S. Continental Shelf | Northwest Atlantic coastal ecosystem | [44] |
47. | mizer | Multispecies size-spectrum model | Southeastern Australian Shelf | Australian Southern and Eastern | [104] |
48. | mizer | Multispecies size-spectrum model | Yellow Sea | Haizhou Bay | [105] |
49. | MSSM | Multispecies size-spectrum model | Yellow Sea | North Yellow Sea | [106] |
50. | MSSM | Multispecies size-spectrum model | Yellow Sea | North Yellow Sea | [107] |
51. | MSSM | Multispecies size-spectrum model | Yellow Sea | Haizhou Bay | [108] |
Aggregated ecosystem models | |||||
52. | EwE | Ecopath with Ecosim | Baltic Sea | Baltic Sea | [75] |
53. | EwE | Ecopath with Ecosim | Canary current | Canary Islands, El Hierro | [109] |
54. | EwE | Ecopath with Ecosim | Celtic-Biscay Shelf | Bay of Viscay | [110] |
55. | nGoM Ecopath | Ecopath with Ecosim | Gulf of Mexico | Gulf of Mexico | [111] |
56. | EwE | Ecopath with Ecosim | Insular Pacific-Hawaiian | Puakō, Hawaii | [112] |
57. | EwE | Ecopath with Ecosim | Mediterranean Sea | Greek Ionian Sea | [113] |
58. | EwE-Ecospace | Ecopath with Ecosim and Ecospace | Mediterranean Sea | Gulf of Gabes | [114] |
59. | EwE | Ecopath with Ecosim | Mediterranean Sea | Thermaikos Gulf | [115] |
60. | EwE | Ecopath with Ecosim | Northeast U.S. Continental Shelf | Northwest Atlantic coastal ecosystem | [44] |
61. | EwE-MICE | Intermediate complexity Ecopath with Ecosim | Northeast U.S. Continental Shelf | Northwest Atlantic coastal ecosystem | [44] |
62. | EwE | Ecopath with Ecosim | Somali Coastal Current | Chwaka Bay | [116] |
63. | EwE | Ecopath with Ecosim | Somali Coastal Current | Gazi Bay, Kenya | [117] |
64. | EwE | Ecopath with Ecosim | Southeast U.S. Continental Shelf | Core sound | [118] |
65. | EwE | Ecopath with Ecosim | Sulu-Celebes Sea | Danajon Bank | [119] |
End-to-end models | |||||
66. | Atlantis | Atlantis | California Current | California currents | [120] |
67. | Atlantis | Atlantis | Iceland Shelf and Sea, Faroe Plateau and part of the Greenland Sea | Arctic and Atlantic waters (Iceland) | [121] |
68. | Atlantis | Atlantis | New Zealand Shelf | Chatham Rise | [122] |
69. | Atlantis | Atlantis | Northeast U.S. Continental Shelf | NEUS (Gulf of Maine to Cape Hatteras) | [123] |
70. | Atlantis | Atlantis | Norwegian and Barents Sea | Nordic and Barrent Sea | [120] |
71. | Atlantis-SE | Atlantis | South-eastern Australian Shelf | Southern Australian waters | [124] |
72. | Atlantis | Atlantis | South-eastern Australian Shelf | Southern Australian waters | [125] |
73. | Atlantis-RCC | Atlantis | South-eastern Australian Shelf | Southern, southwest and Eastern central Australian waters | [126] |
Coupled and hybrid model platforms | |||||
74. | OSMOSE-Coupled | Coupled end-to-end model for the southern Benguela | Benguela Current | Benguela | [127] |
75. | IBM-Coupled | Coupled end-to-end model for the California Current system | California Current | California current | [50] |
76. | OSMOSE-Coupled | Coupled end-to-end model for the Eastern English Channel fish community | Celtic-Biscay Shelf | Eastern English Channel | [128] |
77. | MSSM-Coupled | Coupled multispecies size spectrum model for the eastern Bering Sea | East Bering Sea | Eastern Bering Sea | [129] |
78. | OSMOSE-SoG | Coupled end-to-end model for the Strait of Georgia | Gulf of Alaska | Strait of Georgia, Canada | [130] |
79. | OSMOSE-PNCIMA | Coupled end-to-end model for the Pacific North Coast Integrated Management Area | Gulf of Alaska | PNCIMA off western Canada | [131] |
80. | IBM | Spatially explicit individual-based model | Gulf of Mexico | Gulf of Mexico | [132] |
81. | OSMOSE-WFS | Coupled end-to-end model for the West Florida Shelf | Gulf of Mexico | West Florida Shelf | [133] |
82. | OSMOSE-GoG | Coupled end-to-end model for the Gulf of Gabes | Mediterranean Sea | Gulf of Gabes | [134] |
83. | OSMOSE-Coupled | Coupled end-to-end model for the Mediterranean Sea | Mediterranean Sea | Mediterranean Sea | [135] |
84. | OSMOSE-GoG | Coupled end-to-end model for the Gulf of Gabes | Mediterranean Sea | Gulf of Gabes | [136] |
85. | OSMOSE-MED | Coupled end-to-end model for the Mediterranean Sea | Mediterranean Sea | Mediterranean Sea | [137] |
86. | SS-DBEM | Size spectrum dynamic bio-climate envelope model | Somali Coastal Current | EEZs Kenya and Tanzania | [138] |
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Couve, P.; Bahamon, N.; Canales, C.M.; Company, J.B. Systematic Review of Multi-Species Models in Fisheries: Key Features and Current Trends. Fishes 2024, 9, 372. https://doi.org/10.3390/fishes9100372
Couve P, Bahamon N, Canales CM, Company JB. Systematic Review of Multi-Species Models in Fisheries: Key Features and Current Trends. Fishes. 2024; 9(10):372. https://doi.org/10.3390/fishes9100372
Chicago/Turabian StyleCouve, Pablo, Nixon Bahamon, Cristian M. Canales, and Joan B. Company. 2024. "Systematic Review of Multi-Species Models in Fisheries: Key Features and Current Trends" Fishes 9, no. 10: 372. https://doi.org/10.3390/fishes9100372
APA StyleCouve, P., Bahamon, N., Canales, C. M., & Company, J. B. (2024). Systematic Review of Multi-Species Models in Fisheries: Key Features and Current Trends. Fishes, 9(10), 372. https://doi.org/10.3390/fishes9100372