Is Diversity the Missing Link in Coastal Fisheries Management?
Fisheries management has historically focused on the population elasticity of target fish based primarily on demographic modeling, with the key assumptions of stability in environmental conditions and static trophic relationships. The predictive capacity of this fisheries framework is poor, especial...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Diversity |
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| Online Access: | https://www.mdpi.com/1424-2818/14/2/90 |
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| author | Stuart Kininmonth Thorsten Blenckner Susa Niiranen James Watson Alessandro Orio Michele Casini Stefan Neuenfeldt Valerio Bartolino Martin Hansson |
| author_facet | Stuart Kininmonth Thorsten Blenckner Susa Niiranen James Watson Alessandro Orio Michele Casini Stefan Neuenfeldt Valerio Bartolino Martin Hansson |
| author_sort | Stuart Kininmonth |
| collection | DOAJ |
| description | Fisheries management has historically focused on the population elasticity of target fish based primarily on demographic modeling, with the key assumptions of stability in environmental conditions and static trophic relationships. The predictive capacity of this fisheries framework is poor, especially in closed systems where the benthic diversity and boundary effects are important and the stock levels are low. Here, we present a probabilistic model that couples key fish populations with a complex suite of trophic, environmental, and geomorphological factors. Using 41 years of observations we model the changes in eastern Baltic cod (<i>Gadus morhua)</i>, herring <i>(Clupea harengus)</i>, and Baltic sprat (<i>Sprattus sprattus balticus</i>) for the Baltic Sea within a Bayesian network. The model predictions are spatially explicit and show the changes of the central Baltic Sea from cod- to sprat-dominated ecology over the 41 years. This also highlights how the years 2004 to 2014 deviate in terms of the typical cod–environment relationship, with environmental factors such as salinity being less influential on cod population abundance than in previous periods. The role of macrozoobenthos abundance, biotopic rugosity, and flatfish biomass showed an increased influence in predicting cod biomass in the last decade of the study. Fisheries management that is able to accommodate shifting ecological and environmental conditions relevant to biotopic information will be more effective and realistic. Non-stationary modelling for all of the homogeneous biotope regions, while acknowledging that each has a specific ecology relevant to understanding the fish population dynamics, is essential for fisheries science and sustainable management of fish stocks. |
| first_indexed | 2024-03-09T22:09:30Z |
| format | Article |
| id | doaj.art-846206f93f784a69b98330689df47cb2 |
| institution | Directory Open Access Journal |
| issn | 1424-2818 |
| language | English |
| last_indexed | 2024-03-09T22:09:30Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diversity |
| spelling | doaj.art-846206f93f784a69b98330689df47cb22023-11-23T19:34:41ZengMDPI AGDiversity1424-28182022-01-011429010.3390/d14020090Is Diversity the Missing Link in Coastal Fisheries Management?Stuart Kininmonth0Thorsten Blenckner1Susa Niiranen2James Watson3Alessandro Orio4Michele Casini5Stefan Neuenfeldt6Valerio Bartolino7Martin Hansson8Stockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, SwedenStockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, SwedenStockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, SwedenStockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, SwedenDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Turistgatan 5, SE-453 30 Lysekil, SwedenDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Turistgatan 5, SE-453 30 Lysekil, SwedenNational Institute of Aquatic Resources, Section for Oceans and Arctic, Technical University of Denmark, Kemitorvet 202, 2800 Kongens Lyngby, DenmarkDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Turistgatan 5, SE-453 30 Lysekil, SwedenOceanographic Unit, Swedish Meteorological and Hydrological Institute—SMHI, Sven Källfelts Gata 15, SE-426 71 Västra Frölunda, SwedenFisheries management has historically focused on the population elasticity of target fish based primarily on demographic modeling, with the key assumptions of stability in environmental conditions and static trophic relationships. The predictive capacity of this fisheries framework is poor, especially in closed systems where the benthic diversity and boundary effects are important and the stock levels are low. Here, we present a probabilistic model that couples key fish populations with a complex suite of trophic, environmental, and geomorphological factors. Using 41 years of observations we model the changes in eastern Baltic cod (<i>Gadus morhua)</i>, herring <i>(Clupea harengus)</i>, and Baltic sprat (<i>Sprattus sprattus balticus</i>) for the Baltic Sea within a Bayesian network. The model predictions are spatially explicit and show the changes of the central Baltic Sea from cod- to sprat-dominated ecology over the 41 years. This also highlights how the years 2004 to 2014 deviate in terms of the typical cod–environment relationship, with environmental factors such as salinity being less influential on cod population abundance than in previous periods. The role of macrozoobenthos abundance, biotopic rugosity, and flatfish biomass showed an increased influence in predicting cod biomass in the last decade of the study. Fisheries management that is able to accommodate shifting ecological and environmental conditions relevant to biotopic information will be more effective and realistic. Non-stationary modelling for all of the homogeneous biotope regions, while acknowledging that each has a specific ecology relevant to understanding the fish population dynamics, is essential for fisheries science and sustainable management of fish stocks.https://www.mdpi.com/1424-2818/14/2/90benthic couplingfisheries modellingBayesian networksspatially explicitBaltic Seanon-stationary |
| spellingShingle | Stuart Kininmonth Thorsten Blenckner Susa Niiranen James Watson Alessandro Orio Michele Casini Stefan Neuenfeldt Valerio Bartolino Martin Hansson Is Diversity the Missing Link in Coastal Fisheries Management? Diversity benthic coupling fisheries modelling Bayesian networks spatially explicit Baltic Sea non-stationary |
| title | Is Diversity the Missing Link in Coastal Fisheries Management? |
| title_full | Is Diversity the Missing Link in Coastal Fisheries Management? |
| title_fullStr | Is Diversity the Missing Link in Coastal Fisheries Management? |
| title_full_unstemmed | Is Diversity the Missing Link in Coastal Fisheries Management? |
| title_short | Is Diversity the Missing Link in Coastal Fisheries Management? |
| title_sort | is diversity the missing link in coastal fisheries management |
| topic | benthic coupling fisheries modelling Bayesian networks spatially explicit Baltic Sea non-stationary |
| url | https://www.mdpi.com/1424-2818/14/2/90 |
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