Modelling Ocean Plastic Litter in a Changing Climate: Challenges and MitigationsInternal


Activity Overview

Type: Foresight Workshop
Start Date: April 26, 2018
End Date: April 27, 2018
Venue: Porto, Portugal
Website: ModelPlastics webpage on organisers' website
Contact: Irene Martins
E-mail: imartins [at]
Funding Call: EuroMarine 2017 call for FWS and WG proposals
Total Budget: €9,975
Funds Granted: €9,475

Manager(s): Irene Martins
Co-organiser(s): Ana Filipa Bessa, Ana Marta Gonçalves, Simone Libralato, Jesús Gago

Plastic pollution of marine ecosystems is a growing concern as the global production of plastics in 2014 was 311 million tonnes, of which between 4.8-12.7 million metric tons found their way into our oceans and seas. Modelling predicting tools to monitor this would be extremely useful to set research priorities, evaluate costeffective management scenarios and decide upon mitigation measures.
However, since the problem of plastic pollution has only become a major research topic in the last decade, few models have been applied to understand plastic effects in marine animals or populations over time, or even to describe the spatial distribution of plastic in the ocean. The plastics to be considered in this FWS include from macro- to micro and nano- plastics, all characterized by different dynamics in the marine systems.


  1. To compile the type of data available on plastic quantity and quality in the ocean;
  2. to identify patterns and tendencies of plastic distribution in the ocean;
  3. to gather data on the type of effects caused by plastic in marine organisms;
  4. to identify which type of models would be more suitable to understand and predict the effects of plastic in marine organisms;
  5. to identify which climatic stressors (temperature, salinity, ocean acidification, wind, anoxia, sea level rise, etc) are expected to interfere more with plastic breakage, decomposition and circulation;
  6. to come up with potential mitigation measures.

Expected outcomes

  • 1 position paper
  • 1 draft proposal to apply within a relevant European Call
  • To establish a network of interest under the subject Models to Understand plastic impacts in the Ocean - MODUNDER network

Expected impacts

The outputs from this workshop will:

  1. highlight and implement the need to compile and systematize in a general dataset the available and forthcoming empirical data on plastic pollution, discriminating the different types of plastic;
  2. identify priority research questions within the topic;
  3. infer short- and long-term effects of plastics in marine systems;
  4. propose mitigation measures within a IEA- Integrated Environmental Assessment perspective, i.e., producing and communicating future-oriented, policy-relevant information on key interactions between marine plastic pollution, natural environment and human society.

ModelPlastics was held at CIIMAR- Interdisciplinary Centre of Marine and Environmental Research of the University of Porto, Matosinhos, Portugal, 26 - 27 April 2018. A total number of 33 participants attended the workshop. Most participants came from the academic field (MSc and PhD students, researchers, lecturers), but there were also participants from the private sector (environmental companies), ONG’s and International research platforms (AIR centre). The workshop had contributions from 13 keynote speakers divided by three sessions. Each session targeted a different theme within the main goal of providing insight regarding the emerging issue of pollution by plastics in the marine environment and discussing the challenges and potential of using simulating tools (modelling) to help predicting the potential effects of plastics (from nanoplastics to macroplastics) in marine ecosystems. In all three sessions, participants were actively enrolled in discussions, which caused a dynamic atmosphere of debate during the two days of the workshop.



The main outcome of the discussion highlighted the point that different types of models have the potential to provide relevant information and evidence about the effects of plastic pollution on biota, from the molecular level to the whole ecosystem scale, depending on which type of model is used. However, before this can be achieved, data gaps (which were also identified during group discussion) need to be fulfilled. One major need is that data are obtained and expressed in units that meet model needs; data must also be clearly reported in terms of time and space scales. In addition, depending on the study aims, specific parameters may be required for the selected type of model. Thus, approaches that merge experimental work with modelling needs are essential.

Update 5 June 2019 - A paper summarising the overarching issues that emerged from the MODELPlastics workshop has been accepted into the September 2019 issue of Marine Pollution Bulletin. Titled "MODELPlastics workshop - Modelling Ocean Plastic Litter in a Changing Climate: Gaps and future directions", the paper's authors describe how multi-desciplinary approaches are needed to tackle plastic pollution, how data quantity and quality must be improved to develop accurate models and that models are crucial tools to predict cumulative impacts of multiple stressors.


Next steps and leverage

A second outcome paper is under preparation and will delve further into the main challenges and points of concern regarding the impacts and levels of plastic pollution in any size/shape, relating those with oceanographic processes and climate events, and how models can help predicting interactions, effects and transport of plastics in marine ecosystems.


Networking effect

Since the workshop gathered a considerable number of experts with different backgrounds (ecology, ecotoxicology, oceanography, modelling), the base for the foundation of a network (MODELPlastics Network) of experts in the area of modelling plastic pollution in marine systems was created. Besides sharing data and knowledge, the MODELPlastics network aims at providing future collaborations for the preparation of joint research proposals at the national and European levels.

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