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Sustainable Development

Sustainable Development

As the human population continues to grow and use resources, we must be mindful of our planet’s natural limits. Sustainable development provides a pathway to maintain and improve human life now while also ensuring that future generations will have the resources that they need. The long-term success of sustainability efforts rests on understanding the interplay between human actions and ecological systems.

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Updated: Jun 13, 2025

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Published on: November 20, 2017

Revisiting Fishery Sustainability Targets.

Vincent Cattoni¹, Leah F South^2,3, David J Warne^2,3

¹The University of Queensland School of Mathematics and Physics, Saint Lucia, Australia.

Bulletin of Mathematical Biology

|September 16, 2024

Summary

This summary is machine-generated.

Classic population models suggest harvesting at 40-50% of carrying capacity. However, the Hockey-Stick model, when applied to 284 fish species, often recommends higher population sizes for sustainable harvest.

Keywords:

Bayesian model selection Fisheries management Fishery reference points Harvest strategies Maximum sustainable yield Optimal escapement

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Area of Science:

Ecology
Fisheries Science
Population Dynamics

Background:

Density-dependent population dynamic models are crucial for global harvest policies.
Established models like Beverton-Holt and Ricker typically advise maintaining populations at 40-50% of carrying capacity for maximum sustainable harvest.
These models form the basis for most fisheries' sustainability targets and biomass reference points.

Purpose of the Study:

To investigate the recommendations of the Hockey-Stick model compared to classic models (Beverton-Holt, Ricker) for fisheries harvest policies.
To analyze how model choice and parameter estimation influence optimal population size targets.
To assess the implications of model uncertainty for fisheries management.

Main Methods:

Fitted the Hockey-Stick, Ricker, and Beverton-Holt models to population time series data from 284 species in the RAM Stock Assessment database.
Compared the recommended optimal population sizes (as a proportion of carrying capacity) across the three models.
Conducted a computational experiment simulating data from each model to evaluate model-fitting performance and uncertainty.

Main Results:

The Hockey-Stick model generally recommended higher population sizes than the Beverton-Holt and Ricker models (in 69-81% of datasets).
In 77% of datasets, the Hockey-Stick model suggested targets exceeding 60% of carrying capacity.
Model fitting showed considerable uncertainty, with the best-fitting model rarely having strong support (>95% probability).
The Beverton-Holt model often fit best even when it was not the generating model, indicating data limitations.

Conclusions:

Fisheries data may be insufficient to definitively distinguish between density-dependent growth models.
The widespread reliance on classic models may lead to suboptimal harvest strategies, particularly for slow-growing species.
Sustainability targets and biomass reference points may require re-evaluation based on a broader range of population dynamic models.