ARIES is a networked software technology that redefines ecosystem service assessment and valuation for decision-making. The ARIES approach to mapping natural capital, natural processes, human beneficiaries, and service flows to society is a powerful new way to visualize, value, and manage the ecosystems on which the human economy and well-being depend.

A better way to model ecosystem services

ARIES maps the agents of provision of ecosystem services (sources), their beneficiaries (use), and any biophysical features that can deplete service flows (sinks) automatically choosing the best available models and data. Through artificial intelligence and innovative semantic modeling, ARIES assembles spatial data and expert-contributed model components – deterministic or probabilistic – to quantify and map ecosystem services, at the appropriate spatial scales and specifically for each ecological and socio-economic context.

An ecosystem of models

Models and data used in ARIES are stored on an expanding semantic web. While users can provide their own data and models, an extensible network hosts data, models and model services that are assembled according to context. In this kind of collaborative modelling:

  1. Models and data are developed by the individual, independent experts;
  2. Open source technology allows researchers and institutions to add models and data to the network;
  3. Models and data can be made available to all users or restricted communities;
  4. Artificial Intelligence negotiates the most appropriate models to solve user queries;
  5. Transparent documentation can be generated for all the models used and their integrated results.

Two-step rapid assessment

On the user side, ARIES enables a simple, two-step ecosystem service assessment process. Client software (desktop & soon web-based) allows modeling with minimal configuration and training. After users are logged into the network (through a secure certificate), modeling reduces to

  • Step 1: set the context (for example, searching for a watershed name, or drawing a region on an online map)
  • Step 2: find a concept representing the issue of interest using free-form search, and drop it on the context to observe it.

At that point, ARIES uses its internal knowledge and the data and models on the network to creates agents and processes, connect them into a flow network, and produce a complete assessment of socio-ecological structure and function in the context.

An adaptive modeling technology

Keeping it simple, but realistic

ARIES is an artificial intelligent modeler rather than a single model or collection of models. ARIES chooses ecological process models where appropriate, and turns to simpler models where process models do not exist or are inadequate. Based on a simple user query, ARIES builds all the agents involved in the nature/society interaction, connects them into a flow network, and creates the best possible models for each agent and connection. The result is a detailed, adaptive, and dynamic assessment of  how nature provides benefits to people.

A time of growth for ARIES – starting with its name!

We are happy to announce a new definition for the ARIES acronym to better capture the scope and breadth of the project. From now on ARIES means Artificial Intelligence for Environment and Sustainability. With this rebranding, we align the project's identity to its...

Interoperability of data and models for a more sustainable European Atlantic Coast

“One of ARIES main goals is to have different models talking and interacting among each other and, to achieve this, we need to make them interoperable.” These were Alba Márquez’s opening words during her online presentation on September 15, at iEmss Conference 2020,...

ARIES for SEEA-EEA for rapid natural capital accounts generation

Picture by Pok Rie   How aware is the global community of the benefits of FAIR (Findable, Accessible, Interoperable, Reusable) data and models? And are we willing to change our data and model management habits to achieve them? These were some of the questions...

Releasing the wrap-up of the #AriesChat on AI for better food security

Picture by Tom Fisk   Last September 29, the @aries_project Twitter account hosted an online discussion on the role of artificial intelligence (AI) in achieving global food security. The main takeaways focused on how AI and big data may be able to help in taking...

#AriesChat: Artificial Intelligence for better food security

Big Data is reshaping agriculture. More and more farmers embrace data-driven solutions like artificial intelligence (AI), machine learning and remote sensing for their ability to aggregate trends, track supplies, assess risk and reward, generate predictive models, and...

Challenges and opportunities within ecosystem services from the ARIES perspective

Picture by Pok Rie   Articulating, customising and integrating models and data with innovative technology is ARIES’ main aim to assess and value ecosystem services efficiently. This is why ARIES lead investigator Ferdinando Villa was invited to give a...

What is the semantic web, and why could it be a game changer for ecosystem services?

Toward faster, better, cheaper ecosystem service assessments “It’s just semantics” – Easy way to end a minor disagreement about what to call something “Data collection and preparation takes up 60% of the time needed for environmental modeling” – apocryphal Big data...

New study links land and sea through an ecological-economic model of coral reef recreation in West Maui, Hawai’i

Picture by Kevin Weng, VA Institute of Marine Science and UH Fisheries Ecology Research Lab   Coastal zones are popular recreational areas that substantially contribute to social welfare. Tourism is a critical economic driver for Hawai'i and specifically the...

At a glance: Renewable energy and ecosystem services mapping and assessment in Japan

Picture by oadtz--3657813   Kii Hayashi is Professor at Nagoya University, Japan, and at the Institute of Materials and Systems for Sustainability (IMaSS). As part of the ARIES team, Prof. Hayashi uses the k.LAB technology for mapping and assessing ecosystem...

Twitter discussion’s wrap-up: #AriesChat

Picture by icon0.com   What does natural capital accounting (NCA) stand for? What’s the added value that it offers to improve policy-making decisions against GDP? How can NCA and artificial intelligence (AI) be used in combination to inform climate mitigation and...

#AriesChat: Discussing the benefits of natural capital accounting for ecosystem services

What does natural capital accounting (NCA) stand for? Why is it important for the sustainability of our ecosystem services? Nature must be at heart of decision-making. Since natural resources are scarce, NCA helps to translate ecological results into environmental and...

ARIES launches the video series #ARIESAtHome

In March 2020, different governments across the world implemented wide ranging control measures to slow the spread of COVID-19. Fortunately, the lockdown restrictions did not affect the ARIES group members based at the Basque Centre for climate Change (BC3) and the...

#WorldOceansDay: Integrating knowledge from ocean data

Picture by Jaymantri   Pressures on ocean systems and the communities that rely on them will increase along with those impacts from the multiple stressors of climate change and human activities. At the same time, more ocean data has been collected in the last two...

ALICE Project: Developing nature-based strategies to prevent natural disasters

Picture by Ignacio Pérez Silos   In celebration of the 46th anniversary of the World Environment Day, on June 5th, 2020, the Environmental Hydraulics Institute of the University of Cantabria ‘IHCantabria’, coordinator of the European Project ALICE, and the Basque...

The International Spring University rescheduled to May 2021

The ARIES team regrets to announce that due to the global crisis deriving from the COVID-19 pandemic, the 2020 edition of the Basque Centre for Climate Change (BC3) International Spring University (ISU) on Ecosystem Services Modelling will not be able to take place...

A preview release of the ARIES explorer is now available

The team has presented the ARIES (Artificial Intelligence for Ecosystem Services) modelling framework at the 10th World Conference of the Ecosystem Services Partnership (ESP) in a pre-conference training. The participants to the training had the chance to try a...

OPEN IEEM: Linking ecosystem services to economic models for Latin America and the Caribbean

The ARIES team is collaborating with the Interamerican Development Bank to link ecosystem service models with economic (computable general equilibrium) models. The OPEN Integrated Economic-Environmental Modeling platform (OPEN IEEM) will dynamically link economic...

ARIES is Coming!

2019 is the year in which Game of Thrones comes to a close and ARIES (@aries_project) goes public, so we thought, what the heck, let's go the extra mile! Now we can run ecosystem services models in Westeros, and soon you can too. Seriously, this year we are planning...

Modelling Beneficiaries with CSIR South Africa

The Biodiversity and Ecosystem Services (BES) group at the CSIR (South Africa) is an interdisciplinary, applied research group with expertise in research related to understanding and enhancing the governance of ecosystem services and social-ecological...

Running ecosystem service models using ARIES’ drag-and-drop interface

The ARIES team is about to hit two very important milestones. First, as of June 2018 we've submitted our first article on globally customizable ecosystem service (ES) models - a first batch of five ecosystem service models (plus a spatial multicriteria...

Modeling on the semantic web

ARIES is based on the radically novel k.LAB technology, which allows models and data to be contributed by independent researchers, hosted on a network, and automatically assembled into model workflows following a user’s simple. The technology, which can be applied beyond the field of ecosystem services, is the first operational example of semantically integrated, distributed, collaborative modeling. As an international network of scientific collaborators contribute data and models, the ARIES system grows by itself, and each new assessment automatically adopts the best data and models available. In the next year, users will be able to not only develop, but also run models directly from the world wide web, enabling a simple, two-step modeling workflow suitable for non-technical users, such as decision makers and their staff.