Physical Sciences and Mathematics Commons^™

Towards Globally Customizable Ecosystem Service Models, Javier Martínez-López, Kenneth J. Bagstad, Stefano Balbi, Ainhoa Magrach, Brian Voigt, Ioannis Athanasiadis, Marta Pascual, Simon Willcock, Ferdinando Villa

Rubenstein School of Environment and Natural Resources Faculty Publications

Scientists, stakeholders and decision makers face trade-offs between adopting simple or complex approaches when modeling ecosystem services (ES). Complex approaches may be time- and data-intensive, making them more challenging to implement and difficult to scale, but can produce more accurate and locally specific results. In contrast, simple approaches allow for faster assessments but may sacrifice accuracy and credibility. The ARtificial Intelligence for Ecosystem Services (ARIES) modeling platform has endeavored to provide a spectrum of simple to complex ES models that are readily accessible to a broad range of users. In this paper, we describe a series of five “Tier 1” …