Researchers who model the effectiveness of spatially targeted measures, such as N(S)WRM, Best Management Practices, Nature-Based Solutions and Agri-Environmental Practices, in their case studies. Those using a multi-objective optimisation framework (e.g., CoMOLA), can apply ParetoPick-R to visualise, interpret and communicate Pareto-optimal solutions and identify stakeholder-preferred options. We also aim to involve stakeholders in OPTAIN case studies, especially land and water managers and spatial planners, who are willing to test the app for planning measure implementation.

ParetoPick-R is fully developed and operational as an interactive optimisation and visualisation tool building on the OPTAIN modelling framework. It has been tested in participatory contexts and applied in case studies. Next steps focus on maintenance, refinement, integration into future projects, and continued training and facilitation to support wider replication and long-term sustainability.

ParetoPick‑R handles large, complex Pareto datasets with many objectives, variables, and spatial units. Its visualisation and filtering features scale well with high-dimensional outputs. Independent of the optimisation model, it can be applied across diverse case studies, catchments, countries, or sectors.

ParetoPick‑R is open source on GitHub, with documentation and examples to support reuse and reproducibility. Being model-agnostic, any Pareto-optimal dataset can be imported if it follows the required format. This flexibility allows researchers to apply the workflow across varied projects and contexts.

ParetoPick‑R’s sustainability is supported by open-access licensing, transparent design, and long-term availability on GitHub and Zenodo. Built in the widely used R environment, it remains usable beyond OPTAIN. Its modular codebase enables future extensions, community input, and integration with other tools.