02 - Open Ecosystem Service Science for Policy and Finance Decisions: Lessons Learned from Developing the Natural Capital Project’s InVEST Software Suite

Presented by: Lisa Mandle

Abstract

The contributions of Earth’s natural systems to human well-being and livelihoods has long been undervalued in decision-making, leading to choices that undermine sustainable development. Scientific understanding of ecosystem services, the benefits nature provides to people and the economy, has grown rapidly, but still remains outside many policy and financial decision-making processes.

The Natural Capital Project’s suite of open-source software tools aims to accelerate the inclusion of nature’s values into decision-making by making ecosystem service data and science widely accessible. Our InVEST® software suite includes 25 spatially explicit models for mapping and quantifying ecosystem services. InVEST models have been used in over 700 scientific publications and applied in nearly every country worldwide, and have informed management decisions around the world, from coastal zone planning to payments for ecosystem services to urban planning.

Here we present experiences and lessons learned from more than 10 years of developing this open-source software and engaging with and supporting a global community of users. Key practices include co-development of research questions and approaches with decision-makers, and close collaboration among software engineers, geospatial analysts, and scientists to develop practical tools. A driving principle in our software development has been making InVEST widely accessible and reaching users in any part of the world. This has meant releasing binaries for multiple operating systems, offering a user interface and documentation in multiple languages, designing memory-efficient algorithms for resource-constrained hardware, and being mindful of internet availability.

We also share – and seek feedback on – our progress towards a next-generation software platform to increase the pace and scale at which transparent and reproducible ecosystem service science is generated and available for decision-making. Our efforts are focused across four domains: data, computation, visualization, and community. Our goals are to make it easier for users to incorporate existing models and data into new workflows and extract meaning from large geospatial datasets, and to learn from one another and share new ecosystem service science and data.