Evaluating Biodiversity Assessments in a Business Context A Comparative Analysis of Data Requirements, Limitations and Applicability

Abstract

Biodiversity loss is one of the most pressing environmental challenges of our time, largely driven by land use and land use change in sectors like forestry. As regulatory frameworks increasingly require companies to assess and disclose their biodiversity impacts, the need for practical and data-compatible assessment methods grows. This thesis evaluates the practical feasibility of two LCA-based biodiversity assessment methods, GLAM (Global Guidance for Life Cycle Impact Assessment) and BioMAPS (Biodiversity Multi-Scale Assessments of Product Systems), in a business context within the forestry sector. Through a comparative analysis of data requirements and a qualitative study including interviews with supply chain actors, the study maps data availability, governance structures, and traceability across the tissue product supply chain. The findings show that GLAM is readily applicable given current data practices, as its requirements (land occupation area, geographic location, land use classification, and management intensity) largely align with data already collected for LCA and certification purposes. The spatially explicit version of BioMAPS offers greater ecological detail by incorporating management parameters such as deadwood volume, tree age, and biomass density, and assesses three spatial scales, but its implementation is constrained by limited data transferability along the supply chain. A key finding is that relevant biodiversity data often exists within upstream actors but becomes fragmented, aggregated, or inaccessible as materials move through industrial processes, such as pulp production. The study identifies a trade-off between ecological detail and practical applicability. While the spatially explicit version BioMAPS better captures biodiversity complexity in forestry systems, GLAM represents the more feasible option on short term. Both methods are expected to benefit from increasing data availability driven by EU Deforestation Regulation compliance requirements.