Learn and participate

4

Enhancing coastal ecosystem resilience to climate and land use change

6

Marine ecology and fisheries by marine eco-environmental informatics

11

Social-ecological systems modelling

13

Predictive modelling and real-time surveillance: Strengthening Ebola response in Liberia with epidemic intelligence systems

15

Innovative approaches to ecosystem-based fisheries management: integrating climate resilience and socio-economic factors

16

Reservoir and riverine water quality modeling workshop with 1D and 2D software

17

Advancing ecological modelling for sustainable ecosystem management

20

Artificial intelligence and machine learning to advance process modelling in ecological and environmental sciences

21

Integrating machine learning and genome data digitalisation for biodiversity conservation and dynamic ecosystem modelling

23

Integration of integrated assessment models (IAM) and land change models (LCM) for sustainable ecosystem management

27

Sustainable and resilient ecosystems modelling: innovations for future challenges

28

Oneness water quality with neural network

29

Marine social ecological system modelling for the human ocean coupling

31

Towards better understanding of plastic transport and accumulation processes in inland waters

32

Harness the power of AI and process understanding for predictive ecology

34

Climate change, REDD+, and gendered benefit sharing in forest-dependent communities of Africa

35

Modeling relationships between species diversity and ecosystem services and functions

37

Towards improved understanding of ecosystem dynamics in arid and semi-arid regions with limited water resources

40

Modelling forest ecosystems: integration through multiple scales

41

Advancing predictive models of forest greenhouse gas exchange: from biogeochemical processes to global impacts

42

Ecosystem modeling for environmental impact assessment of human activities

46

Modeling of watersheds, lake, ocean and ecosystems related to climate change impacts

47

Species distribution modeling for developing intelligent conservation strategies in the context of climate change

49

Transforming data into action: advancing ecological modeling for sustainable ecosystem management in Africa

52

Socio-ecological system modeling for natural resources management and ecological conservation

53

Advancements in machine learning algorithms for ecological big data processing

57

Advances in Data Assimilation (DA) and optimization techniques

59

Dynamic energy budget modeling

60

Ecosystem services and community interplay in mountain areas

61

Challenges and advances in integrating ecological and earth system models across multiple sectors

63

Land change modeling for sustainable land management

64

Modeling water quality and ecosystems in estuarine and coastal areas: Japan and other countries under human activities and climate change

65

Data-driven ecosystems: Modeling for improved health outcomes and sustainable development

66

Modeling species distributions and interactions in ecological communities

67

Marine plastic modelling: Biological interactions, transport dynamics, and ecosystem impacts

68

Advances in signal processing for bioacoustics

69

Marine biogeochemical/ecological modelling: advancements and best practices

72

Ecological informatics: A rapidly advancing discipline in a changing world

91

Sustainably feeding the global population through responsible fisheries management using ecological and bioeconomic models

Ecological network analysis

Brian Fath

Towson University, USA. International Institute for Applied Systems Analysis, Austria

Abstract

Network analysis as a tool in systems research is an immensely growing field. Many of the analyses types are based on foundations accumulated over the past decades, and new approaches are continuously emerging in the different fields. We aim to provide course participants with several aspects and hands-on experience of network analyses as applied to ecosystems and socio-economic systems.

The session includes both theoretical and practical parts. Emphasis will be given on the foundations of network models and constructing network models. Sample data are available to construct test models, but participants are encouraged to bring their own network data if they have it.

Course participants will benefit having some working knowledge of R.

Modeling Aquatic Food Webs with Ecopath with Ecosim: A Hands-On Introduction

Irene Martins

University of Porto Interdisciplinary Centre of Marine and Environmental Research, Portugal

Abstract

This one-day workshop provides a practical and accessible introduction to Ecopath with Ecosim (EwE), a globally recognized modeling framework for exploring the structure and dynamics of aquatic food webs. EwE is widely used in marine and freshwater research to assess trophic interactions, energy flow, and the ecological impacts of human activities.

Participants will learn how to construct and balance mass-balance food web models using Ecopath, with particular attention to defining functional groups and quantifying diet compositions in the diet matrix—the foundation of all EwE models. The workshop will explore how trophic flows are derived from consumption, production, and biomass estimates, and how these flows structure the energy pathways through ecosystems. Ecosim will be introduced as a tool for simulating the temporal dynamics of these interactions and evaluating responses to perturbations such as fishing pressure or species removals.

Topics include parameterizing trophic interactions, working with empirical diet data, interpreting food web structure, and using EwE’s indicators to assess ecosystem functioning. Guided, hands-on exercises will reinforce concepts and provide participants with practical modeling experience using a demonstration dataset.

No prior experience with EwE is required. A basic understanding of ecological concepts—particularly trophic levels, energy flow, and predator–prey relationships—is recommended. Participants are encouraged to bring laptops with the EwE software pre-installed.

By the end of the workshop, attendees will have the skills to begin building and interpreting food web models, evaluate ecosystem responses to change, and integrate EwE into research projects in ecology, fisheries science, and environmental management. The session will also highlight best practices in the use and communication of food web models in academic and applied contexts.

Using Dynamic Energy Budget (DEB) models to model life cycles and life-history traits of organisms - an introduction

Nina Marn^1,2, Marko Jusup³

¹Ruđer Bošković Institute, Croatia. ²The University of Western Australia, Australia. ³Japan Fisheries Research and Education Agency, Japan

Abstract

Dynamic Energy Budget models can simulate a whole life cycle of an individual, by following energy and/or matter from assimilation to allocation to growth, maintenance, development, and reproduction. The Add-my-Pet database currently houses over 6000 entries with DEB-model parameters and referenced life-history data for animals of all major phyla (https://www.bio.vu.nl/thb/deb/deblab/add_my_pet/species_list.html). The code used to obtain the parameters (DEBtool - https://github.com/add-my-pet/DEBtool_M/) and that used for exploring the collection and parameter patterns (AmPtool - http://www.github.com/add-my-pet/AmPtool/) are both freely available on GitHub. In this workshop we will cover the basics of constructing and using a model within the DEB framework.

The workshop will be more useful for people with some basic knowledge in programming and/or DEB theory, but beginners are welcome too, perhaps for an overview. Ideally you will need a Matlab installed (a trial/student/home version is sufficient), but functionality is provided for .R too. We will guide you through creating a DEB model for a species, to simulate its life-cycle and follow DEB variables and corresponding observable traits through its life. Depending on the interest and motivation of the participants, we will discuss your current research in the context of DEB (e.g. how and where to include your datasets into DEBtool routines, how to identify and describe the most relevant process to follow). Further, we could explore the existing collection of parameters by using corresponding AmPtool routines, also coded in Matlab.

Individual-Based and Agent-based Modelling Jürgen Groeneveld

Helmholtz Centre for Environmental Research UFZ, Germany Abstract

Agent-Based and Individual-Based Modelling (ABMs from here on) has become an established modelling paradigm. The course is designed primarily to help academic and industry researchers start using (or teaching) ABM modeling. Major topics include model design—how to determine what things should be in a model or left out. We will look at example models that are programmed in NetLogo. We will discuss advantages and challenges of ABMs in contrast to other model paradigms in Ecological Modelling such as equation based models. The content of the course will be mainly based on material provided in the two text books of Volker Grimm and Steve Railsback (https://www.railsback-grimm-abm-book.com).