Is Diversity the Missing Link in Coastal Fisheries Management?

Abstract

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 (Gadus morhua), herring (Clupea harengus), and Baltic sprat (Sprattus sprattus balticus) 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.

Climate Change Potential Impacts on the Tuna Fisheries in the Exclusive Economic Zones of Tonga

“…These variables have been shown as preferred habitats for various tuna species [100][101][102]. The application of species distribution modelling can be limited, for example, by model performance and the reliability of climatic future predictions [103] and by assuming that there is a balance between environmental changes and the spatial distribution of the species [104]. Nevertheless, our study provides a solid foundation for the future development of conservation measures aimed at the sustainable harvesting and management of the species populations.…”

Environmental Influences on Illex argentinus Trawling Grounds in the Southwest Atlantic High Seas

“…In summary, although many previous studies have shown that the concentration of Chl-a in seawater has little effect on squid fishing for Illex argentinus, this study indicates that for open-sea trawl fishing grounds, Chl-a is one of the main key environmental factors affecting fishing ground changes. And Kininmonth [35] conducted a comprehensive analysis of chlorophyll-a concentration and plankton community data, revealing the complex interactions between primary productivity and trophic structure in the Baltic Sea ecosystem. The results showed that the seasonal variations in chlorophyll-a concentration were significantly correlated with the biomass of major plankton species.…”

Application of the Method Evaluation and Risk Assessment Tool for a Small-Scale Grouper Fishery in Indonesia

“…The application of the MERA tool to evaluate management procedures in this study is built on knowledge of stock conditions based on historical catches and biological characteristics of the species studied. However, from an ecosystem dynamics point of view, stock abundance will also be influenced by habitat changes (e.g., nursery capacity) caused by dynamic interactions between biotic and environmental components (e.g., [65]), which is outside the scope of this study. Further study to understand the interactions between stocks and the habitat and environmental changes will be critical to reducing uncertainty in future stock estimates and improving adaptive fisheries management in Saleh Bay.…”