Modeling the Senegalese artisanal fisheries migrations

Using an interdisciplinary multi-agent model, this study demonstrates that while climate change has a minor impact on Senegalese artisanal fisheries, reducing fishing effort is critical to preventing fishery collapse and mass migration, thereby enabling a sustainable equilibrium that restores historical catch levels.

The Gist

Imagine the coast of Senegal as a giant, bustling kitchen. For decades, this kitchen has been incredibly productive, thanks to a natural "updraft" of cold, nutrient-rich water from the deep ocean that brings in fresh ingredients (plankton) for the fish to eat. This has made Senegal's artisanal fishers the most skilled chefs in West Africa, feeding millions and employing thousands.

However, the kitchen is starting to run out of ingredients, and the chefs are getting desperate. This report, titled "Modeling the Senegalese Artisanal Fisheries Migrations," is like a flight simulator built by scientists to figure out why the kitchen is failing and what will happen next.

Here is the story of the paper, broken down into simple concepts:

1. The Problem: The "Empty Fridge" Syndrome

For a long time, the fish were everywhere. But since the 1980s, too many boats (both local and foreign) have been fishing, and the fish have started to disappear.

• The Migration: When the fish near their home village run out, the fishers don't just give up. They pack up their boats and families and move down the coast to find new schools of fish. This is called migration.
• The Desperation: Recently, the fish have become so scarce that some fishers are using their boats not just to catch fish, but to smuggle people to Europe. The "kitchen" is so empty that people are leaving the profession entirely.

2. The Big Question: Is it the Climate or the Fishing?

There is a lot of debate. Some people say, "The climate is changing! The water is getting hotter, and the fish are moving away!" Others say, "No, it's just that we have too many boats catching too many fish."

The scientists built a computer game (called the "Lolli" simulator) to test these theories. They created a virtual world with:

• Virtual Fish: Four types of fish that move around based on water temperature.
• Virtual Fishers: Three types of boats (small, medium, and large) that can travel different distances.
• Virtual Markets: Landing sites where fish are sold. If a market is too full, the fishers can't sell their catch, so they move to a new town.

3. The Experiment: Running the Simulation

The researchers ran the game under different scenarios to see what would happen:

• Scenario A: The "Real World" (Too Many Boats)
  They set the game to match the current number of boats and the current fishing efficiency.

  • Result: Catastrophe. Within just a few years, the fish stocks collapsed completely. The fishers had to migrate everywhere, and eventually, there was nothing left to catch. The "kitchen" was empty.
  • The Lesson: Even if the climate stays perfect, overfishing alone is enough to destroy the fishery.

• Scenario B: The "Climate Change" Test
  They turned up the heat in the virtual ocean by 1.5°C and even 3°C (simulating a very hot future).

  • Result: The fish did move north to cooler waters, but the fishery didn't collapse any faster than it did in the "Real World" scenario.
  • The Lesson: Climate change is a problem, but it's not the main villain right now. The fish are adaptable enough to move with the temperature. The real killer is the sheer number of boats.

• Scenario C: The "Responsible" Test
  They reduced the number of boats and the amount of fish caught per hour (simulating better management).

  • Result: Success! The fish population stabilized. The fishery produced about 250,000 tons of fish a year, which is a healthy, sustainable amount. This worked even with the hotter climate scenarios.
  • The Lesson: If we slow down the fishing, the system can survive and thrive, even if the weather gets worse.

4. The "Fishmeal" Twist

The report also points out a sneaky problem: Fishmeal factories.
Imagine a giant machine that turns fish into powder to feed farm animals. These factories are popping up along the coast (especially in Mauritania). They act like a vacuum cleaner, sucking up huge amounts of small fish (sardinella) that the local fishers rely on. The report suggests that these factories are a major reason why the fish are disappearing so fast.

5. The Final Verdict: What Should We Do?

The scientists conclude with a clear message for the leaders and managers:

1. Stop Blaming the Weather: While climate change is real, the fishery isn't collapsing because the water is hot. It's collapsing because we are catching fish faster than they can reproduce.
2. Manage the "Vacuum Cleaners": We need to control the fishmeal factories and the total number of boats.
3. Regional Cooperation: Fish don't respect borders. A fish caught in Senegal might have been born in Mauritania. The countries from Morocco to Guinea need to work together to manage the "kitchen" as one big team, not as competitors.
4. The "Lolli" Tool: This computer model is now a tool for decision-makers. They can use it to test ideas (like "What if we close this bay for a year?") before trying them in real life.

In a nutshell:
The Senegalese fishers are like skilled drivers in a car that is running out of gas. The scientists are saying, "Don't just blame the road (climate); we need to stop driving so fast (fishing effort) and share the remaining gas (fish) wisely, or the car will stop moving entirely."

Technical Summary

Here is a detailed technical summary of the paper "Modeling the Senegalese artisanal fisheries migrations" (D3.5).

1. Problem Statement

The Senegalese artisanal fishing sector, the largest in West Africa, faces a complex crisis driven by the interplay of overfishing, socio-economic pressures, and climate change.

• Overexploitation: Since the 1980s, increased fishing effort and the proliferation of fishmeal factories have led to a progressive depletion of fish stocks (reduced by ~50% since 1980).
• Migration Dynamics: Fishers are increasingly forced to migrate longer distances to find fish, shifting from local daily trips to multi-month "campaigns" across national borders (Mauritania, Guinea-Bissau, etc.). In extreme cases, this has led to fishers acting as transporters for irregular migration to Europe.
• Climate Uncertainty: While climate change is expected to alter Sea Surface Temperature (SST) and fish habitat distribution, its specific impact on the socio-ecosystem of artisanal fisheries remains poorly understood.
• The Gap: Existing models often fail to integrate spatially explicit climate scenarios with the adaptive behavioral logic of artisanal fishers (migrations, gear switching) and infrastructure constraints (landing site capacities). There is a lack of tools to identify "tipping points" where the fishery collapses versus where it remains sustainable.

2. Methodology

The authors developed an Agent-Based Model (ABM) named "Lolli" (implemented in the Gama simulation platform) to simulate the socio-ecosystem of Senegalese artisanal fisheries.

A. Conceptual Framework

The model follows the ODD (Overview, Design concepts, Details) protocol and integrates three subsystems:

1. Fisheries Subsystem: The core of the model, representing fishing units and their behaviors.
2. Climate Subsystem: Represented by Sea Surface Temperature (SST) and bathymetry, driving fish habitat.
3. Socio-Economic Subsystem: Represented by landing site processing capacities and market demand.

B. Model Entities and Agents

• Fishing Units (Agents): Three categories based on boat size and gear (Line/Longline, Gillnet, Rotating Seine). They differ in:
  • Storage capacity (limiting trip duration).
  • Catchability (efficiency).
  • Mobility: Daily trips (50km), Tides (up to 15 days, 500km), and Campaigns (up to 12 months, >1000km, potentially crossing borders).
  • Logic: Agents maximize income by selecting fishing grounds based on fish biomass and landing sites based on processing capacity saturation.
• Fish Agents: Four "model-species" aggregating real species into two affinities (Saharan cold-water vs. Guinean warm-water) and two habitats (Pelagic vs. Demersal).
  • Dynamics: Logistic growth (reproduction twice a year) and random walk movement constrained by SST and bathymetry.
• Environment: A 10km resolution grid covering Morocco to Guinea. SST is updated monthly based on climate scenarios.
• Landing Sites: 15 major sites with defined daily processing capacities. If a site is saturated, it becomes unattractive, forcing fishers to migrate.

C. Key Processes

• Fishing: Catch is calculated using a Holling Type III functional response (applied in later simulations) to mimic the difficulty of catching fish when biomass is low.
• Migration: Triggered when fishers cannot find fish within their radius or when landing sites are saturated.
• Climate Scenarios:
  • Reference: ERA5 reanalysis (1979–2014).
  • Optimistic: Reference + 1.5°C SST.
  • Pessimistic: Reference + 3°C SST.

D. Sensitivity Analysis

A Saltelli sensitivity analysis was performed to identify the most influential parameters on cumulative catch, focusing on catchability, campaign probability, and fleet size.

3. Key Contributions

1. Interdisciplinary Integration: Successfully merged physical oceanography (SST/habitat), marine biology (stock dynamics), and sociology (fisher decision-making/migration) into a single spatially explicit simulation.
2. The "Lolli" Simulator: A novel decision-support tool specifically designed for the West African context, capable of testing "One Factor at a Time" (OFT) scenarios regarding fleet size, infrastructure, and climate.
3. Identification of Tipping Points: The model explicitly distinguishes between a sustainable equilibrium and a collapsed state based on fishing effort and infrastructure distribution.
4. AI Integration: The project laid the groundwork for using AI (Deep Learning on satellite/drone imagery) to automate the census of fishing units, addressing data gaps in real-time monitoring.

4. Key Results

The simulations tested various combinations of fishing effort (fleet size), catchability, and climate scenarios.

• Climate Change Impact (Secondary):
  • Climate scenarios (+1.5°C and +3°C) significantly shifted fish habitats northward (concentrating biomass off Mauritania).
  • Crucially, climate change alone had a negligible impact on the fishery's trajectory compared to fishing pressure. The fishery's resilience to climate change was high if fishing effort was managed.
• Fishing Effort Impact (Primary Driver):
  • Current/High Effort (Simulations 8.1, 9.1, 10.1): With the current number of fishing units and high catchability (representing the status quo), the model predicts a rapid collapse of fish stocks (within 5–7 years) regardless of the climate scenario. This leads to massive long-term migrations and fishery abandonment.
  • Reduced Effort (Simulations 8, 9, 10): When fishing effort was reduced (simulating a 100x slower catch rate or reduced fleet), the fishery reached a sustainable equilibrium with annual catches of ~250,000 tons (mostly in Senegal), comparable to historical records from the 2000s. This equilibrium was stable across all climate scenarios.
• Infrastructure Role: The distribution of processing capacity (e.g., fishmeal factories in Mauritania) acts as a magnet for migration. High capacity in specific areas accelerates the depletion of local stocks and drives fishers to migrate to those hubs, exacerbating regional overexploitation.

5. Significance and Implications

• Management Priority: The study concludes that overfishing is the primary threat, not climate change. The "tipping point" for collapse is determined by fishing effort and infrastructure capacity, not SST increases.
• Policy Recommendations:
  • Sub-Regional Management: Management must occur at the scale of fish migration (Morocco to Guinea), not just national borders.
  • Effort Reduction: Immediate reduction in fishing effort (fleet size or catchability) is necessary to prevent collapse.
  • Infrastructure Control: Regulating the processing capacity of fishmeal factories is critical to preventing the concentration of fishing effort that leads to stock depletion.
• Migration Link: The model suggests that without sustainable fisheries management, artisanal fishers will continue to migrate, potentially increasing the flow of irregular migration to Europe as fishers seek alternative livelihoods.
• Future Work: The authors propose using the model for role-playing games with stakeholders to visualize long-term consequences and integrating more complex biogeochemical models to account for primary productivity changes.

In summary, the paper provides robust evidence that the Senegalese artisanal fishery is on a path to collapse due to current fishing pressure, but that a sustainable future is achievable through reduced effort and regional cooperation, even under severe climate change scenarios.