An adaptive modelling technology
Keeping it simple, but realistic
ARIES is an artificial intelligent modeller 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.

Modelling 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 modelling. 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.

Hightlights
While work continues on ARIES’ web-based infrastructure that will enable more its independent use, ARIES is being used by researches and practitioners to quantify, map, and evaluate a broad spectrum of ecosystem services and beneficiaries in case studies across the globe. We have partnered with government agencies, universities, NGOs, and other stakeholders to develop data and models that are relevant to resource management, producing high-quality knowledge and understanding to support decision making. The case studies highlighted here were designed using local, high-resolution spatial datasets whenever available to populate models that account for a broad range of ecosystem services in a variety of ecological and socio-economic settings. The map below highlights some of the projects where ARIES has been used. Click a pin on the map to review the details for individual case studies.