DISPLACE Documentation

Introduction

DISPLACE, a cutting edge, agent based modelling platform that helps scientists, managers and stakeholders evaluate how fisheries respond to spatial marine planning decisions.

1. Why such a model?

Traditional fishery assessments often treat the ocean as a uniform backdrop, ignoring where vessels actually operate and how they react to closures, wind farms or other sea uses. DISPLACE fills that gap by coupling high resolution biological dynamics with individual vessel decision making in both time and space. This bi directional link is rare in the literature but essential for realistic impact assessments.

DISPLACE is an acronym for Dynamic Individual vessel based Spatial Planning and Effort Displacement. It emphasizes that the model works at the level of individual fishing vessels, simulating their day to day decisions and how those decisions shift when spatial measures (e.g., marine protected areas, offshore wind farms, gear restrictions) are introduced. This vessel focused approach enables detailed estimates of effort redistribution, catch changes, and economic impacts, which are then used for risk assessment and policy evaluation in European marine spatial planning and ecosystem based fisheries management contexts.

Component	Meaning
Dynamic	The model runs forward in time, updating vessel behaviour each simulated day.
Individual vessel based	Each fishing vessel (or fleet segment) is represented as a separate agent with its own characteristics and decision rules.
Spatial Planning	The model evaluates how spatial management measures (MPAs, wind farm zones, gear restrictions, etc.) reshape where vessels fish.
Effort Displacement	It quantifies how fishing effort moves away from restricted areas and the resulting changes in catch, revenue, and ecological impact.

2. Core components

Component	What it does	Example output
Population dynamics module	Mortality of target species at a fine spatial grid	Seasonal biomass maps for cod, herring, etc.
Vessel dynamics behavior module	Each vessel decides where, when and how much effort to apply, based on profitability, gear limits and regulatory constraints.	Effort displacement routes when a Marine Protected Area is introduced.
Economic module	Calculates revenues, costs, fuel use and profit margins for each fleet/metier.	Changes in fleet income under different spatial scenarios.

|Cross sector layer|Allows inclusion of other sea uses—offshore wind, shipping lanes, aquaculture—to see how they compete for space| Assessment of effort loss when a wind farm array occupies a productive ground.|

All modules run on a spatio temporal grid that can be tailored—from basin wide (North Sea, Baltic) to local (Northern Adriatic) scales, see www.displace-project.org.

3. What can DISPLACE tell us?

1. Ecological impact – predicts how closures affect stock biomass and fishing mortality.
2. Economic outcome – quantifies revenue shifts, fuel consumption and CO₂ emissions for each fleet.
3. Effort displacement – visualises new routes vessels take when excluded zones appear, helping planners anticipate “leakage” effects.
4. Multi sector trade offs – evaluates whether a wind farm placement harms fisheries more than it benefits renewable energy goals. These outputs feed directly into Marine Spatial Planning (MSP) processes, giving policymakers evidence based options rather than guesswork.

4. Real world applications

DISPLACE has already been applied to several European seas—Adriatic, Ionian, Black, Baltic and Celtic—testing scenarios ranging from demersal stock protection to coexistence with offshore wind farms. In the northern Adriatic, the model helped identify spatial arrangements that protect high value demersal stocks while allowing sustainable fishing effort to persist.

5. Take away

1. DISPLACE bridges biology and economics at a granular spatial scale, something most legacy models lack.
2. It supports transparent, scenario based decision making, crucial for balancing food security, livelihoods and emerging marine industries.
3. By visualising effort displacement, it reveals hidden costs and opportunities that would otherwise remain invisible. In short, DISPLACE equips us with a quantitative “what if” laboratory for the seas, enabling smarter, more resilient fisheries management in an increasingly crowded seascape

7. California app

UCSB used DISPLACE to evaluate the potential impacts of California’s Offshore Wind energy development lease areas on the DTS fisheries operating off the coast of California. This notebook summarizes the requirements, inputs, outputs, and processes for running DISPLACE and the associated R routines. Separate documentation about DISPLACE can be found on the project website.

This repository includes an application example based on this Californian study. It does not use actual vessel or fisheries data, but rather example data that do not reflect any confidential fishing information. This allows for a complete test run of the parametrization and model, and provides an opportunity to become familiar with the processes and different model components.

Working environment

The current project uses DISPLACE version 1.5.8 on Windows 11. You can download the installer here. The R routines run on R version 4.5.0 (on any platform or operating system). All required R packages are detailed in r/config.R.

The repository contains all the scripts required to prepare input data in the DISPLACE format, along with scripts for basic processing of outputs in the r and routines folders. It also includes example data in the raw_inputs folder, which serve as reference for data contents and structure when building a DISPLACE application.

The processed_inputs folder is initially empty and is automatically populated when running the routines with r/functions_routines.R. To explore DISPLACE results, you will need to manually move the model output files into the outputs folder so they can be read by r/functions_outputs.R.

DISPLACE_California
  |__ docs
  |__ qmd
  |__ raw_inputs
  |__ processed_inputs
  |__ outputs
  |__ routines
  |__ r

Quick Setup & Run

For a quick execution and model run to test whether it can run on your machine, execute:

source(here::here("r/functions_routines.R"))

Before executing, make sure to update the installer directory in the directory parameter of the generate_dis_run_files function in functions_routines.R. Running this script will populate the processed_inputs folder, whose contents then need to be moved to the machine where DISPLACE is run. This must be a Windows machine, and the inputs must be located in C:/. You should also create a folder named DISPLACE_outputs in C:/, where the outputs will be stored.

We recommend reviewing the entire repository to understand the inputs and processes in more detail before executing.