In this article, the authors propose an impact assessment method for life cycle assessment (LCA) that adheres to established LCA principles for land use-related impact assessment, bridges current research gaps and addresses the requirements of different stakeholders for a methodological framework. The conservation of biodiversity is a priority for humanity, as expressed in the framework of the Sustainable Development Goals (SDGs). Addressing biodiversity across value chains is a key challenge for enabling sustainable production pathways. Life cycle assessment is a standardised approach to assess and compare environmental impacts of products along their value chains. The impact assessment method presented in this article allows the quantification of the impact of land-using production processes on biodiversity for several broad land use classes. It provides a calculation framework with degrees of customisation (e.g., to take into account regional conservation priorities), but also offers a default valuation of biodiversity based on naturalness. The applicability of the method is demonstrated through an example of a consumer product. The main strength of the approach is that it yields highly aggregated information on the biodiversity impacts of products, enabling biodiversity-conscious decisions about raw materials, production routes and end user products.

Land use and land use change are among the main drivers of the ongoing loss of biodiversity at a global-scale. Although there are already Life Cycle Impact Assessment (LCIA) methods to measure this impact, they are still rarely used by companies and municipalities in the life cycle assessment of products and processes. Therefore, this paper highlights four main requirements for a biodiversity methodological framework within LCIA in order to facilitate biodiversity assessments: first, to consider the global uneven distribution of biodiversity and its risks with respect to vulnerability and irreplaceability; second, to account for the need to regionalize the impacts of land use; third, to consider the specific impacts that different land use types have on biodiversity; and fourth, to analyze the biodiversity impacts of different land use management parameters and their influence on the intensity of land use. To this end, we provided a review of existing methods in respect to conformity and research gaps. The present publication describes the development of a new methodological framework that builds on these requirements in a three-level hierarchical framework, which enables the assessment of biodiversity in LCA at a global-scale. This publication reveals research gaps regarding the inclusion of proactive and reactive conservation concepts as well as methods of land management into LCIA methodology. The main objective of this concept paper is therefore to describe a new methodological framework for the assessment of biodiversity in the LCA that could fill some of the research gaps, including compilation and suggestion of suitable data sets. The conclusion discusses both the benefits and limitations of this framework.

Purpose: The impact of land use on biodiversity is a topic that has received considerable attention in life cycle assessment (LCA). The methodology to assess biodiversity in LCA has been improved in the past decades. This paper contributes to this progress by building on the concept of conditions for maintained biodiversity. It describes the theory for the development of mathematical functions representing the impact of land uses and management practices on biodiversity. Methods: The method proposed here describes the impact of land use on biodiversity as a decrease in biodiversity potential, capturing the impact of management practices. The method can be applied with weighting between regions, such as ecoregions. The biodiversity potential is calculated through functions that describe not only parameters which are relevant to biodiversity, for example, deadwood in a forest, but also the relationships between those parameters. For example, maximum biodiversity would hypothetically occur when the nutrient balance is ideal and no pesticide is applied. As these relationships may not be readily quantified, we propose the use of fuzzy thinking for biodiversity assessment, using AND/OR operators. The method allows the inclusion of context parameters that represent neither the management nor the land use practice being investigated, but are nevertheless relevant to biodiversity. The parameters and relationships can be defined by either literature or expert interviews. We give recommendations on how to create the biodiversity potential functions by providing the reader with a set of questions that can help build the functions and find the relationship between parameters. Results and discussion: We present a simplified case study of paper production in the Scandinavian and Russian Taiga to demonstrate the applicability of the method. We apply the method to two scenarios, one representing an intensive forestry practice, and another representing lower intensity forestry management. The results communicate the differences between the two scenarios quantitatively, but more importantly, are able to provide guidance on improved management. We discuss the advantages of this condition-based approach compared to pre-defined intensity classes. The potential drawbacks of defining potential functions from industry-derived studies are pointed out. This method also provides a less strict approach to a reference situation, consequently allowing the adequate assessment of cases in which the most beneficial biodiversity state is achieved through management practices. Conclusions: The originality of using fuzzy thinking is that it enables land use management practices to be accounted for in LCA without requiring sub-categories for different intensities to be explicitly established, thus moving beyond the classification of land use practices. The proposed method is another LCIA step toward closing the gap between land use management practices and biodiversity conservation goals.

The accelerating loss of biodiversity and ongoing ecosystem degradation rank among the most pressing global challenges today. Life Cycle Assessment (LCA) has emerged as a pivotal tool for evaluating the environmental sustainability of production systems; however, the integration of biodiversity impact assessments into LCA studies remains constrained by significant data gaps, limited spatial resolution, and methodological complexity. This dataset addresses these challenges by providing and integrating ready-to-use characterization factors for biodiversity impact assessment in current LCA software packages. Characterization factors (CF) were calculated for land occupation flows of three LCA databases (Agribalyse 3.1.1, Ecoinvent 3.10, and Sphera LCA For Experts) following the Biodiversity Value Increment (BVI) method. The CF are applicable at global and country level, considering both land-use intensity and location. The integration into current LCA Software packages (OpenLCA 2.1.0 and Sphera LCA For Experts), enhances accessibility for LCA practitioners, supporting more comprehensive evaluations especially in terms of biodiversity impact assessments.