Abstract

The modeling of land use impacts on biodiversity is considered a priority in life cycle assessment (LCA). Many diverging approaches have been proposed in an expanding literature on the topic. The UNEP/SETAC Life Cycle Initiative is engaged in building consensus on a shared modeling framework to highlight best-practice and guide model application by practitioners. In this paper, we evaluated the performance of 31 models from both the LCA and the ecology/conservation literature (20 from LCA, 11 from non-LCA fields) according to a set of criteria reflecting (i) model completeness, (ii) biodiversity representation, (iii) impact pathway coverage, (iv) scientific quality, and (v) stakeholder acceptance. We show that LCA models tend to perform worse than those from ecology and conservation (although not significantly), implying room for improvement. We identify seven best-practice recommendations that can be implemented immediately to improve LCA models based on existing approaches in the literature. We further propose building a "consensus model" through weighted averaging of existing information, to complement future development. While our research focuses on conceptual model design, further quantitative comparison of promising models in shared case studies is an essential prerequisite for future informed model choice.

Keywords

Life cycle assessment; land use; biodiversity; UNEP/SETAC Life Cycle Initiative; ecological modelling

Published in

Environmental Science and Technology
2016, Volume: 50, number: 6, pages: 2782-2795

SLU Authors

• Maia De Souza, Danielle

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    
  • Lethbridge Research and Development Centre
  • University of Alberta

Sustainable Development Goals

Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss


UKÄ Subject classification

Environmental Management
Ecology
Environmental Sciences


Publication identifier

DOI: https://doi.org/10.1021/acs.est.5b04681

Permanent link to this page (URI)

https://res.slu.se/id/publ/69163