Felipe S. Campos
Felipe S. Campos is a postdoctoral researcher at CREAF working at the interface of biodiversity, ecosystem services and ecological economics. His research uses GIS and remote sensing to investigate spatial patterns of biodiversity and ecosystem services, with a particular focus on indicators, monitoring and the ecological foundations of nature-based solutions. He develops spatial approaches that help link ecological knowledge with conservation research and practice.
Sessions
Earth Observation (EO), GIS and open geospatial workflows are transforming how biodiversity and ecosystem services can be assessed and applied to environmental decision-making. In this talk, I present an integrative research framework that combines EO-based mapping, biodiversity indicators, spatial modelling and nature-based solutions to generate ecosystem service indicators across multiple socioecological contexts. The presentation draws on concrete examples from projects in Europe, Africa and Latin America. These include MaSOT, which advances the mapping of ecosystem services from Earth Observations; ASEBIO, a national-scale assessment of biodiversity and ecosystem services in Portugal that combines stakeholder engagement, scenario analysis and WebGIS tools; MozambES, which uses GIS and remote sensing to map mangroves, assess pressures and support the valuation of mangrove ecosystem services in Mozambique; and FOREST-LED, which examines forest loss, forest expansion and carbon stocks in Spain under global change and natural hazards. Across these projects, I show how taxonomic, functional and phylogenetic dimensions of biodiversity can be combined with land-cover dynamics, ecosystem service indicators and economic valuation to support conservation prioritization and multifunctional landscape management. I also highlight recent studies on biodiversity indicators of ecosystem services, ecosystem service change under land-use dynamics, comparisons between model outputs and stakeholder perceptions, and the integration of eco-environmental factors into landslide susceptibility assessment through an eco-DRR perspective. Together, these examples show how open and reproducible EO workflows can connect environmental data, biodiversity science and applied modelling to produce scalable indicators for conservation, risk reduction and sustainability planning.